Development of a surveillance scheme for priority lichens in Scotland

Scottish Natural Heritage Commissioned Report No. 567

Development of a surveillance scheme for priority lichens in Scotland

COMMISSIONED REPORT

Commissioned Report No. 567

Development of a surveillance scheme for priority lichens in Scotland

For further information on this report please contact: Dr David Genney Scottish Natural Heritage Great Glen House INVERNESS IV3 8NW Telephone: 01463 725231 E-mail: [email protected] This report should be quoted as: Britton, A.J., Mitchell, R.J., Potts J.M. & Genney, D.R. 2013. Development of a surveillance scheme for priority lichens in Scotland. Scottish Natural Heritage Commissioned Report No. 567. This report, or any part of it, should not be reproduced without the permission of Scottish Natural Heritage. This permission will not be withheld unreasonably. The views expressed by the author(s) of this report should not be taken as the views and policies of Scottish Natural Heritage. © Scottish Natural Heritage 2013.

COMMISSIONED REPORT

Summary Development of a surveillance scheme for priority lichens in Scotland Commissioned Report No.: 567 Project no: 13024 Contractor: A.J. Britton Year of publication: 2013 Background Understanding trends in species populations, range and habitat quality is a principle requirement for conservation evaluations. Such evaluations are vital if we are to direct conservation resources to protect species that are in most urgent need of action and for which Scotland has greatest international responsibility. Detecting species trends is also an important step in understanding the impact of environmental pressures on these species. Surveillance is a priority for lichen species on the Scottish Biodiversity List (SBL) as transcribed from the pre-devolution UK Biodiversity Action Plan. Surveillance is also required for statutory reporting against delivery of Scotland’s Biodiversity Strategy and the wider UK Terrestrial Biodiversity Surveillance Strategy. However, there has been relatively little development of statistically robust, cost effective protocols for direct surveillance of priority lichen species. This report outlines a series of studies that will help implement future repeatable and comparable surveillance protocols. Main findings  Surveillance capabilities will always be limited by resource availability, so the first step in this project was to explore how the comparatively large list of lichens on the SBL could be further prioritised. A number of methods are compared and it is recommended that a system which focuses on those species which are endemic or for which Scotland hosts internationally important populations is used.  The next phase of the project considers the approaches required to develop a costeffective suite of surveillance methods. The objectives and parameters of lichen surveillance are discussed and this is related to the lichens on the SBL. To identify the range of surveillance methods required, species are grouped by their geographic distribution and habitat requirements. This demonstrates that the largest group of SBL lichens are corticolous with the most common broad habitats being general closed woodland, trees in open habitats and oceanic western woodland.  Identification and mapping of suitable habitat for the target species is a prerequisite to the design of any surveillance protocol. Chapter 4 of this report considers how to do this for the oceanic woodland lichen Pseudocyphellaria norvegica (Norwegian Specklebelly). The method presented here overlays the distribution of native broadleaf woodland with 1 km

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squares that contain records for P. norvegica and/or a suite of other ancient oceanic woodland indicator lichens.  Using the above information, a number of survey methods were tested to assess their feasibility and statistical robustness. In particular the methods compared inter-surveyor and between-method variability in target species detection and duration of survey. The results are analysed and discussed in detail, but the largest source of variation in the data was between surveyors rather than between methods. However, surveyor variability was substantially reduced by restricting the survey to time-limited presence/absence surveys of individual 1 ha cells.  In order to calculate the sample size required to detect a particular percentage change in a lichen population over a particular time, an estimate of the rate of turnover within a population is needed. Limited data from pre-existing survey reports were available to help perform this power analysis. Although assumptions are made, it is estimated that baseline surveillance of 1400 1 ha cells would need to be established across 30 1 km squares to have an 80% chance of detecting a 10% decline in P. norvegica. These should be stratified to cover the full range of the lichen in Scotland.  The report concludes by recommending the next steps to develop and implement a surveillance programme for priority SBL lichens across Scotland.

For further information on this project contact: Dr David Genney, Scottish Natural Heritage, Great Glen House, Inverness, IV3 8NW. Tel: 01463 725253 For further information on the SNH Research & Technical Support Programme contact: Knowledge & Information Unit, Scottish Natural Heritage, Great Glen House, Inverness, IV3 8NW. Tel: 01463 725000 or [email protected]

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Table of Contents

Page

1. 

INTRODUCTION 1.1  Background 1.2  Aims of the project

1  1  1 

2. 

PRIORITISATION OF UKBAP LICHENS FOR SURVEILLANCE ACTION 2.1  Review of prioritisation methods 2.2  A prioritisation method for UKBAP lichens 2.2.1  Recommended prioritisation method for Scottish BAP lichens

3  3  4  7 

3. 

DEVELOPMENT OF A SUITE OF METHODS FOR SURVEILLANCE OF BAP LICHENS 3.1  Background to surveillance design 3.2  Aims of Scottish BAP lichen surveillance 3.2.1  Objectives 3.2.2  What to monitor 3.3  Geographic and habitat distribution of Scottish BAP lichens 3.4  Increasing cost-efficiency of BAP species surveillance 3.4.1  Grouping of species for survey purposes 3.4.2  Use of existing surveillance data within the programme 3.4.3  Integration of lichen habitat SCM and BAP species surveillance 3.5  General approach to surveillance of BAP lichens

10  10  11  11  12  13  17  17  17  17  18 

4. 

DEVELOPMENT OF MAPS OF POTENTIALLY SUITABLE HABITAT 4.1  Aims of map development 4.2  Methods 4.3  Results 4.4  Discussion

19  19  19  19  23 

5. 

TRIAL OF LICHEN SURVEILLANCE METHODOLOGIES 5.1  Aims of the trial 5.2  Selected species 5.3  Methods 5.3.1  Survey 1 5.3.2  Survey 2 5.3.3  Data analysis 5.4  Results – Survey 1 5.4.1  Differences between transect methods A, B and C. 5.4.2  Differences between fixed transect patterns and a time-limited search. 5.4.3  Differences in time taken for fixed transect patterns and time-limited searches. 5.4.4  Inter-surveyor variation. 5.5  Results – Survey 2 5.5.1  Number of occupied trees 5.5.2  Time taken to search 1ha 5.5.3  Distance walked 5.5.4  Time taken to find the first Pseudocyphellaria norvegica 5.5.5  Presence/absence data 5.6  Discussion 5.6.1  Transect versus searches 5.6.2  Surveyor variability 5.6.3  Ways to reduce surveyor variation 5.6.4  Presence/absence versus population 5.6.5  Further development of surveillance methodologies. 5.7  Conclusion

24  24  24  24  24  28  30  30  30  31 

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31  32  34  34  34  35  38  41  41  41  42  42  43  43  44 

6. 

ASSESSING POPULATION TURNOVER 6.1  Aims 6.2  Methods 6.2.1  Glen Shira – data collection 6.2.2  Site condition monitoring reports – data collection 6.3  Results 6.3.1  Glen Shira – Results 6.3.2  Site condition monitoring reports – site level results 6.3.3  Site condition monitoring reports – DMP results 6.3.4  Power analysis – site/subsite level data 6.3.5  Power analysis – patch/tree level data 6.4  Discussion 6.5  Conclusion

45  45  45  45  45  46  46  46  47  48  49  49  50 

7. 

CONCLUSION AND NEXT STEPS 7.1  Prioritization 7.2  Survey methodology 7.3  Habitat condition monitoring 7.4  Pollution and climate data 7.5  Setting up the surveillance scheme 7.6  Next steps 7.6.1  Pseudocyphellaria norvegica surveillance 7.6.2  Surveillance of other widespread BAP species 7.6.3  Surveillance of scarce BAP species

51  51  51  52  52  52  53  53  53  53 

8. 

REFERENCES

54 

ANNEX 1: PRIORITISATION CRITERIA FOR SCOTTISH BAP SPECIES

57 

ANNEX 2: UK DISTRIBUTIONS OF SCOTTISH BAP LICHENS

58 

ANNEX 3: FULL REPORT FROM BRIAN COPPINS ON GLEN SHIRA

147 

ANNEX 4: SCM DATA FOR PSEUDOCYPHELLARIA NORVEGICA AT THE SITE LEVEL

152 

ANNEX 5: DATA FROM DMP FOR PSEUDOCYPHELLARIA NORVEGICA

155 

ANNEX 6: DATA FROM SURVEY 1: OCCUPIED TREES AND SUITABLE HABITAT

159 

ANNEX 7: DATA FROM SURVEY 1: TIME (MINUTES) TAKEN FOR TRANSECTS

163 

ANNEX 8: 20 MINUTE SEARCH DATA FROM SURVEY 1

164 

ANNEX 9: DATA FROM SURVEY 2

165 

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List of Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Figure 11 Figure 12 Figure 13 Figure 14 Figure 15 Figure 16 Figure 17 Figure 18 Figure 19 Figure 20 Figure 21

Page

Map of potentially suitable habitat for Pseudocyphellaria norvegica in Western Scotland. ............................................................................................... 21  Map of potentially suitable habitat for Atlantic Hazel woods in Western Scotland .............................................................................................................. 22  Map and aerial photograph of Glen Nant 1 km trial survey square ..................... 26  Diagram of the three transect methods ............................................................... 27  The 35 cells at Glen Nant and Glen Nant and Collias Nathais surveyed during Survey 2.. ................................................................................................. 29  Length of suitable habitat identified in each 1 ha cell by transect type and surveyor. .............................................................................................................. 30  Number of occupied trees in each 1 ha cell by survey method and surveyor. .............................................................................................................. 31  Time taken to survey each 1 ha cell by survey method and surveyor. ................ 31  Occupied trees per unit of suitable habitat by surveyor....................................... 32  Comparison of 4 surveyors carrying out transect method C. .............................. 33  Number of trees colonised with Pseudocyphellaria norvegica found within a 20 minute search .............................................................................................. 34  Time spent searching the 1 ha cell. ..................................................................... 35  Distance walked while searching the 1 ha cell.. .................................................. 36  Routes taken by two surveyors within Collias Nathais. ....................................... 37  Routes taken by two surveyors within Glen Nant. ............................................... 38  Time taken to find the first occupied tree by Pseudocyphellaria norvegica within a 1 ha cell .................................................................................................. 39  Time taken by surveyors to find the first occupied tree in relation to the total number of occupied trees found within the 1 ha cell.................................... 40  Number of occupied trees in relation to distance between the first occupied tree found by two different surveryors. ................................................. 40  Percentage of 1 ha cells where surveyors had the same or different presence/absence data ....................................................................................... 41  Changes in the presence of Pseudocyphellaria norvegica at sites/subsites. ...................................................................................................... 47  Changes in the presence of patches of Pseudocyphellaria norvegica during the two cycles of SCM. ............................................................................. 47 

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List of Tables Table 1 Table 2 Table 3 Table 4 Table 5 Table 6

Table 7 Table 8

Page

Priority ranking of the 89 UK BAP lichen species present in Scotland according to different prioritisation methods. ........................................................... 8  Habitat and substratum affiliations and number of occupied 10 x 10 km squares 1960-2010 for BAP lichen species present in Scotland. .......................... 14  Classification of Scottish BAP lichens species by number of occupied 10 km squares between 1960 and 2010. .................................................................... 16  Classification of Scottish BAP lichens by substratum. ........................................... 16  Summary of habitat groupings for Scottish BAP lichen species. Average species priority ranking are based on the preferred prioritisation of species given in Table 1. .................................................................................................... 16  Differences in area of potentially suitable habitat for Pseudocyphellaria norvegica identified when maps are created using records for Pseudocyphellaria norvegica or a minimum of 10, 15, 20 or 30 WSIEC species................................................................................................................... 20  Summary of presence of Pseudocyphellaria norvegica on tagged trees in 1996 and 2012 ....................................................................................................... 46  Data required for power calculation ....................................................................... 48 

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Acknowledgements This work was jointly funded by Scottish Natural Heritage and the Scottish Government’s Rural and Environment Research and Analysis Directorate. We thank the British Lichen Society for allowing us to use their lichen distribution data, and the members who collected these data. Brian Coppins, Sandy Coppins, Andy Acton and Anna Griffith all contributed to useful discussion during the design of the survey methods. We thank the Scottish Forestry Commission for access to their land and the Surveyors for carrying out the work.

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1.

INTRODUCTION

1.1

Background

Effective biodiversity surveillance is a key requirement for assessing the current and changing status of our natural capital for a variety of purposes, including assessing the effectiveness of conservation actions. The Scottish Parliament requires to be informed of the changing state of nature in relation to our European and wider responsibilities. Scotland has devolved responsibilities for surveillance under the Habitats regulations and engages in all other UK international reporting obligations. The Scottish Biodiversity Committee (SBC) has asked SNH to take a lead role in prioritising these species for conservation and surveillance action. Scotland has a biodiversity strategy (Scottish Executive, 2004) that includes a list of species of principal importance for biodiversity conservation action. This is called the Scottish Biodiversity List (SBL) and includes 89 lichens that were originally identified in the UK Biodiversity Action Plan (BAP). During the present study there has been a shift in emphasis from the UK BAP to devolved priority lists such as the SBL, however we continue to refer to the UK BAP species here because these species were the original focus of this work and the criteria and actions have not changed. 1.2

Aims of the project

This partnership project between The James Hutton Institute and SNH is the first stage in development of a surveillance scheme for priority lichen species in Scotland. The aim is to fulfil the data requirements for reporting on species status at national and European levels. Attributes for surveillance are set out in the Habitats Directive: a. Habitat range is stable / increasing; structure and functions are maintained; and the status of its typical species is favourable (Article 1); b. Species population dynamics are viable; range not being reduced; and sufficient habitat is available (Article 1); c. Ecological coherence (Article 3, 10) is maintained / developed; d. Effectiveness of conservation measures on Special Areas of Conservation (Article 6); e. Incidental capture and killing of Annex 4 (Habitats and Species Directive) animal species (Article 12) is recorded; f.

Exploitation of Annex 5 (Habitats and Species Directive) plants and animals is compatible with their being maintained at favourable conservation status; and

g. Results of surveillance are maintained, made available and reported every six years (Article 17).

1

For the purposes of this project we define species surveillance as: The systematic collation of species data in a way that allows trends in a species’ distribution, area of occurrence, population size or habitat condition to be assessed over time for the purposes of reporting on conservation status. In order to fulfil obligations on reporting the status of species, surveillance will need to be implemented for a large number of species. However, since there are currently 89 UKBAP lichen species on the SBL, immediate implementation of comprehensive surveillance for all species would be extremely resource intensive. For this reason, the first component of the project is to develop an objective set of criteria which can be used to further prioritise species in terms of surveillance needs (Chapter 2). Following on from this, the second component of the project is to develop protocols for rapid surveillance of these species. This is broken down into four stages (Chapters 3-6). 1.

In order to identify the range of surveillance methods required, species are grouped by their geographic distribution, habitat requirements, objectives of the surveillance programme and key parameters to be measured identified (Chapter 3).

2.

Methods to produce maps of the areas of suitable habitat to be sampled are developed (Chapter 4).

3.

Sampling methodologies are developed and tested (Chapter 5).

4.

Calculations are made of the number of samples that will be required to detect a particular percentage change in a lichen population over a particular time (Chapter 6).

The emphasis is on providing guidance to provide quick and simple protocols that will produce scientifically robust data to track lichen population performance through time. This will minimise cost and maximise the number of species which can be monitored with limited resources. Since BAP lichen species occur in a range of habitats it is envisaged that a limited range of habitat-specific protocols will be required.

2

2. 2.1

PRIORITISATION OF UKBAP LICHENS FOR SURVEILLANCE ACTION Review of prioritisation methods

Despite the increasing realisation of the importance of biodiversity, resources available for species conservation are limited in comparison with the number of threatened species (Joseph et al., 2009). This means there is a need to develop objective methods of prioritising species for conservation and surveillance action to ensure best use of available resources. The question of how to objectively prioritise species for conservation action in the face of limited resources has been extensively debated in the scientific literature over the last few years. There has been much discussion surrounding the nature of the criteria which should be applied during priority-setting, the methods by which multiple criteria can be combined and the issues surrounding the calculation of conservation-priority metrics from often patchy and incomplete species information. The International Union for Conservation of Nature (IUCN) threat categories (IUCN, 2001) are one of the most well-known examples of objective criteria being used to rank species according to their conservation status. In this scheme, species are classified into nine categories according to extinction risk; extinct (EX), extinct in the wild (EW), critically endangered (CR), endangered (EN), vulnerable (VU), near threatened (NT), least concern (LC), data deficient (DD), and not evaluated (NE). Species classified as CR, EN and VU are referred to as threatened and are determined with respect to one or more of five criteria relating to population size, dynamics and distribution. The IUCN categories were originally designed to assess extinction risk for entire species at the global scale, but are now also increasingly used to derive ‘red lists’ of threatened species at national and regional scales (Palmer et al., 1997; Gärdenfors, 2001). This can, however, cause problems if national red lists are used to set conservation priorities, because national threat status does not always reflect conservation needs (Palmer et al., 1997; Schmeller et al., 2008b). Species assessed as threatened at the national scale may include those which have much larger populations outside the area of interest, while those which are under threat globally may not meet red list criteria within the focal area. In general it is accepted that while red lists of threatened species can be influential in setting conservation priorities they must be combined with other criteria to enable effective allocation of conservation resources (Schmeller et al., 2008a; Gauthier et al., 2010). The concept of ‘national responsibility’ has been developed to overcome some of the issues surrounding setting national conservation priorities for species whose distribution spans multiple political jurisdictions (Gärdenfors, 2001; Schmeller et al., 2008b). The assessment of national responsibility considers the fact that some parts of the species’ range will be more important than others in terms of ensuring its overall survival. For example, a nationally rare species with a very small number of occurrences but which is widespread in other countries would be assessed as a lower priority than a more widespread species which is endemic to, or has a major part of its population in, the country under consideration. The species priority rankings derived from such an assessment are frequently very different from those derived from assessments of threat such as the IUCN criteria above, but their use in setting conservation priorities may help to ensure the most efficient, cost-effective solution to biodiversity conservation at a global scale (Schmeller et al. 2008b). A wide range of studies have considered the issue of how to combine multiple measures of ‘conservation need’ to give a single metric which can be used to rank species in order of conservation priority (e.g. Martinez et al., 2006; Regan et al., 2008; Schmeller et al., 2008a; Joseph et al., 2009; Gauthier et al., 2010; Jimenez-Alfaro et al., 2010). Many different criteria have been employed, including threat status (e.g. IUCN categories), local rarity, national or regional responsibility (as described above), legal status, taxonomic uniqueness, and species ‘value’, with little consensus on the best criteria to use. In addition to 3

considerations of which criteria to include in a metric, there are also multiple methods by which these criteria may be combined in order to produce the final species ranking. These range from hierarchical systems where species are assessed against a sequence of criteria ranking them into a series of groups, to simple point-scoring methods where scores against each criterion are added up to give a species’ total and then ranked, to more complex methods involving differential weighting and averaging of criteria. Several authors point out, however, that to be usable in an applied ecological setting, metrics for assigning conservation priorities need to be transparent, with well-defined criteria which have minimal data requirements, since many species groups do not have detailed surveillance data on which to base assessments of population status, trends and distributions (Schmeller et al., 2008 a, b; Gauthier et al., 2010). This last issue results in a certain amount of circularity when defining priorities for surveillance in particular since, for many species groups, adequate surveillance data on which to base assessments of status and threat and thus species priorities may be lacking. 2.2

A prioritisation method for UKBAP lichens

An initial prioritisation method for surveillance requirements of UKBAP species was developed and agreed by the Scottish Biodiversity Committee (SBC), prior to the start of this project. Existing information regarding the distribution, abundance and long-term population trends of lichens on the UKBAP list were collated and assessed against four criteria using a hierarchical method (Annex 1). These four criteria were ‘importance’ (is the species listed on UKBAP or the Scottish Biodiversity list?), ‘status in Scotland’ (is the species within its natural range in Scotland?), ‘decline in Scotland’ (is the species reported as declining via BAP reporting or other evidence?), and ‘other strong reasons’ for surveillance (species is nationally rare or endemic, and under threat, UKBAP species where Scotland holds >75% of the UK population or other reasons such as species being listed on the Species Action Framework). A positive response to both of the first two criteria and either of the last two criteria identified the species as a high priority for surveillance (category A). Species meeting the first two criteria but not the second two were identified as medium/low priority for surveillance (category B). Of the 89 species of UKBAP lichens present in Scotland, 75 qualified as high priority species for surveillance (category A) using this method (Table 1). Since this is too large a proportion of the total to tackle with the existing level of resources, a more discriminatory prioritisation method is clearly needed to refine the ranking process. With the aim of developing a simple but more discriminatory metric, we investigated alternative ways in which the existing agreed SBC criteria could be used to provide a more detailed ranking. Since the first two criteria (‘importance’ and ‘status in Scotland’, see above and Annex 1) are met by all UKBAP lichens in Scotland, we focused our attention on the attributes contained in the second two criteria (‘decline in Scotland’ and ‘other strong reasons’). This resulted in a list of four criteria which could be used to discriminate between species. These were: 1.

The species is declining in Scotland;

2.

The species is nationally rare or endemic, and under threat in Scotland;

3.

Scotland holds a significant proportion (>75%) of the UK population; or

4.

Other strong reasons for prioritising the species in Scotland.

These criteria (with the exception of number 3) are focused around evidence of decline or the threat of decline in Scottish populations. While criterion 3 includes some measure of the importance of Scottish populations within the UK context, any international context or indication of ‘national responsibility’ (see section 2.1) is lacking. For this reason we decided

4

to include an additional criterion ‘International Responsibility’ based on whether Britain had an international responsibility as assessed within the 2010 Conservation Evaluation of British Lichens (Woods & Coppins 2010). This report identifies species where the British population is not of international significance because Britain supports 75% of the UK population), then criterion 4 (other strong reasons), then criterion 5 (international responsibility). 2. Focus on importance. Species were ranked first according to criterion 5 (international responsibility), then criterion 3 (Scotland holds >75% of the UK population), then criterion 1 (decline in Scotland), then criterion 2 (rare or endemic and under threat), then criterion 4 (other strong reasons). 3. Combined threat and importance. Species were ranked first according to criterion 3 (Scotland holds >75% of the UK population), then criterion 1 (decline in Scotland), then criterion 2 (rare or endemic and under threat), then criterion 5 (international responsibility), then criterion 4 (other strong reasons). Each of these three methods produced very different rankings of the species (Table 1). All three methods divided the species on the list into the same 14 groups, with a maximum of 17 species in any one group, but the order in which the criteria were used altered the ranking of the groups. Discrimination between the species on the list was improved relative to the simple summed scores method, with a larger number of groups containing smaller numbers of species. The ‘focus on threats’ method prioritised those species known, or thought to be, declining or at risk in Scotland; however, six out of the top seven priority species under this method are in fact more widespread outside of Scotland or the UK and may not be threatened at the global scale. This includes species such as Cladonia botrytes, Peltigera malacea and Peltigera venosa. In contrast, focusing on importance gave top priority to a

5

group of species for which Scotland hosts important populations and which are thought to be under threat, but also gave high priority to a large group of internationally important species which are relatively widespread in Scotland and not thought be declining or under threat. In addition, this ranking placed a group of 10 species which had originally been assessed as of low priority for surveillance using the SBC methodology (Annex 1) as a medium priority. The combined threat and importance ranking placed highest priority on those species with their UK population headquarters in Scotland which are also considered to be declining or threatened. This ranking placed less emphasis on the international importance of populations so some species which are much more common elsewhere were again picked up as top priorities, but a large proportion of the top 20 species were those for which Scotland has international responsibilities and which are thought to be under some degree of threat. As a final alternative we tested variations on the method of prioritisation suggested by Gauthier et al. (2010). Rather than using the pre-existing categorisation used by the SBC, for this prioritisation we returned to the primary data to give transparency to the exact criteria being used for ranking. Gauthier et al. (2010) proposed that species should be ranked according to a hierarchical application of three criteria; regional responsibility, local abundance and habitat vulnerability. We derived scores from 1-5 for each of these criteria for each species using readily available data from the Scottish Sites Lichen Database and the Conservation Evaluation of British Lichens (Woods & Coppins 2010). Regional responsibility was classified as: endemic to the UK (score 5), international responsibility (score 3) or no special responsibility (score 1). Local abundance scores were based on the number of occupied 10 x 10 km grid squares in Scotland; 30 (score 1). Habitat vulnerability was based on an assessment of the dynamics of the species’ primary habitat and the likelihood of direct anthropogenic disturbance. Terricolous species and those in transient habitats such as cut tree stumps scored 5. Corticolous species in managed habitats such as wayside trees, parkland, orchards and fence posts scored 4. Corticolous species in relatively stable woodland environments (e.g. ancient woodland) scored 3. Saxicolous species in anthropogenic or dynamic habitats such as in rivers, or on mining spoil, shingle or gravestones, scored 2. Finally saxicolous species in stable habitats such as upland boulders and outcrops scored 1. As a potential extra criterion to further refine prioritisation we added a score for national threat status based on the IUCN categories in the 2010 British Lichen Conservation Evaluation (Woods & Coppins 2010). This graded species from 5 (most threatened) to 1 (least threatened) according to the IUCN categories CR, EN, VU, NT and LC/DD. Species rankings were then calculated in two ways; either by adding up the total scores across criteria or by hierarchical application of the criteria as originally suggested by Gauthier et al. (2010). This was also done with the IUCN-based national threat status criterion either included or excluded. The species rankings developed using the Gauthier et al. (2010) method departed markedly from the rankings obtained using SBC criteria. Notably, the species originally designated high and low priority for surveillance were mixed up through the list. Similarly to the ranking with ‘focus on importance’, described above, priority is placed on those species for which the UK has international responsibility (but with added emphasis on endemics) especially where hierarchical ranking rather than summed scores are used. One of the main benefits of these ranking criteria is that their derivation is transparent and they do not rely on surveillance data beyond simple 10 km grid-square mapping data, which should be relatively robust. Inclusion of the IUCN categories as a fourth criterion has both pros and cons. Including this criterion helps to further refine the ranking; where it is included hierarchically it does not greatly change the priority order, but splits the groups into smaller units. However, where the species scores are summed, it has a greater influence and shifts the priority ranking towards species considered highly threatened. There may be some issues with this, since the data used for the initial IUCN categorisation are not completely transparent and may be 6

influenced by the quality of existing surveillance data; in addition, the threat categories are partly based on species’ national rarity and so this might be considered as giving unwarranted extra weighting to this aspect of species’ distribution or status. However, including this measure does enable more emphasis to be given to those species known to have undergone recent declines not detected by the broad 1960-present window used for mapping data. 2.2.1

Recommended prioritisation method for Scottish BAP lichens

The choice of a single preferred method of ranking species in terms of surveillance priority is essentially a subjective one. However, we suggest that the Gauthier et al. (2010) method has several advantages over the previously used SBC criteria. In particular it allows an improved focus on those species which are endemic or for which Scotland hosts internationally important populations. Arguably, where resources are limited, these species should be the priority for conservation and surveillance action in order to achieve the best chances of biodiversity conservation at a global scale. The Gauthier criteria also allow the likelihood of change in different habitat types to be taken into account through the habitat vulnerability criterion, and inclusion of the IUCN categories helps to give more priority to those species which are thought to have undergone rapid population change in recent years. The criteria for this ranking scheme are also easily assessed from readily available data, meaning that the ranking can be easily updated, should the BAP list change in future, and could readily be applied to other species groups.

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Table 1 - Priority ranking of the 89 UK BAP lichen species present in Scotland according to different prioritisation methods. ‘Initial SBC’ refers to the A/B ranking derived from the SBC method set out in Annex 1; ‘Summed SBC’ is the total number of SBC criteria met by each species; ‘Focus on threat’, ‘Focus on importance’ and ‘Combined threat + importance’ refer to different hierarchical arrangements of the SBC criteria and international responsibility categories from the 2010 Conservation Evaluation as set out in section 2.2; ‘Gauthier ranking including IUCN categories’ refers to ranking according to hierarchical use of regional responsibility, local abundance, habitat vulnerability and IUCN threat categories as described in section 2.2. For all Priority rankings except for Initial SBC and Summed SBC, the species are ranked from 1 (highest priority for surveillance) to 89 (lowest priority for surveillance). Where species are ranked equally, they are all given the same number. Bold type indicates the recommended ranking method. Species name

Alectoria ochroleuca Anaptychia ciliaris subsp. ciliaris Arthonia atlantica Arthonia cohabitans Arthonia invadens Arthonia patellulata Arthothelium dictyosporum Arthothelium macounii Aspicilia melanaspis Bacidia circumspecta Bacidia incompta Bacidia subincompta Biatoridium monasteriense Brodoa intestiniformis Bryoria furcellata Buellia violaceofusca Calicium corynellum Calicium diploellum Caloplaca ahtii Caloplaca caesiorufella Caloplaca flavorubescens Caloplaca lucifuga Caloplaca luteoalba Caloplaca virescens Candelariella superdistans Catapyrenium psoromoides Catillaria alba Chaenotheca gracilenta Chaenotheca laevigata Cladonia botrytes Cladonia peziziformis Collema dichotomum Collema fasciculare Collema fragile Collema fragrans Cyphelium trachylioides Diplotomma pharcidium Fuscopannaria ignobilis Fuscopannaria sampaiana Gomphillus calycioides Graphis alboscripta

Initial SBC

Summed SBC

Focus on threat

Focus on importance

Combined threat + importance

A A

2 1

22 74

44 84

19 84

Gauthier ranking incl. IUCN cats. 68 76

A A B A A A A B A A A A A A A A A A B A A A A A A A A A A B A A A A A A A A A

2 3 1 1 3 3 1 1 2 1 2 2 1 3 2 3 2 2 0 1 1 1 2 1 1 1 2 3 2 0 2 1 4 3 1 1 2 2 3

41 8 76 65 8 8 65 76 7 65 39 22 65 8 39 8 22 22 86 44 74 44 22 44 44 44 22 1 6 86 54 44 5 8 65 65 54 54 8

27 1 30 61 1 1 61 30 71 61 72 44 61 1 72 1 44 44 86 74 84 74 44 74 74 74 44 40 70 86 15 74 26 1 61 61 15 15 1

59 5 74 47 5 5 47 74 58 47 62 19 47 5 62 5 19 19 86 64 84 64 19 64 64 64 19 1 57 86 36 64 56 5 47 47 36 36 5

14 1 2 79 3 24 62 16 78 86 55 64 56 22 58 11 70 50 76 50 82 47 69 54 71 47 47 74 40 87 33 72 7 6 85 83 33 33 5

8

Species name

Gyalecta ulmi Gyalidea roseola Hypogymnia vittata Lecania chlorotiza Lecanographa amylacea Lecanora achariana Lecanora cinereofusca Lecanora quercicola Lecidea erythrophaea Leptogium brebissonii Leptogium cochleatum Leptogium hibernicum Leptogium saturninum Megalospora tuberculosa Melanelixia subargentifera Nephroma arcticum Parmeliella testacea Peltigera lepidophora Peltigera malacea Peltigera venosa Pertusaria velata Phaeophyscia endococcina Poeltinula cerebrina Polychidium dendriscum Porina hibernica Porina sudetica Pseudocyphellaria intricata Pseudocyphellaria lacerata Pseudocyphellaria norvegica Pyrenula dermatodes Pyrenula hibernica Ramonia chrysophaea Ramonia dictyospora Rinodina degeliana Rinodina isidioides Schismatomma graphidioides Sclerophora pallida Stereocaulon delisei Stereocaulon symphycheilum Sticta canariensis Synalissa symphorea Thelenella modesta Toninia sedifolia Umbilicaria spodochroa Usnea florida Vulpicida pinastri Wadeana dendrographa Wadeana minuta

Initial SBC

Summed SBC

Focus on threat

Focus on importance

Combined threat + importance

A A A B B A A B A A A A A B A A A A A A B A A A A A A A A A A B A A B A A A A A A A B A B A B A

3 3 2 1 1 2 2 1 1 2 2 3 1 1 2 2 2 2 3 3 1 2 1 3 2 1 2 3 2 3 3 1 2 2 1 2 1 2 1 3 1 2 0 2 0 2 1 2

8 1 22 76 76 22 22 76 65 54 54 8 65 76 22 22 54 22 1 1 76 22 44 8 41 44 54 8 54 8 8 76 41 22 76 54 65 54 44 8 44 22 86 22 86 22 76 54

1 40 44 30 30 44 44 30 61 15 15 1 61 30 44 44 15 44 40 40 30 44 74 1 27 74 15 1 15 1 1 30 27 44 30 15 61 15 74 1 74 44 86 44 86 44 30 15

5 1 19 74 74 19 19 74 47 36 36 5 47 74 19 19 36 19 1 1 74 19 64 5 59 64 36 5 36 5 5 74 59 19 74 36 47 36 64 5 64 19 86 19 86 19 74 36

9

Gauthier ranking incl. IUCN cats. 29 58 42 15 20 58 50 8 81 33 31 27 89 32 45 41 33 58 67 75 8 72 66 24 10 42 33 16 39 11 13 18 4 56 18 20 83 28 65 24 42 45 88 62 53 79 22 30

3. 3.1

DEVELOPMENT OF A SUITE OF METHODS FOR SURVEILLANCE OF BAP LICHENS Background to surveillance design

Biodiversity surveillance has been the subject of increased attention in the academic literature in recent years. This is mainly due to the target agreed by world leaders at the World Summit on Sustainable Development in Johannesburg in 2002 ‘to achieve, by 2010, a significant reduction of the current rate of biodiversity loss’ (United Nations Environment Programme, 2002). Similar commitments were made at the European level where, for example, the European Union Council agreed that ‘biodiversity decline should be halted by 2010’ (European Council, 2001). Measurement of progress against these criteria requires that sufficient data on species’ distributions and populations should be available in order to: a) determine ‘baseline’ conditions of population size and geographical distribution and: b) determine trends in these parameters in order to assess rates of decline or expansion. Several authors have reviewed existing biodiversity surveillance programmes, across Europe and more widely, and assessed their ability to provide the kind of data needed to determine whether targets for biodiversity conservation are being met (Balmford et al., 2005; Legg & Nagy, 2006; Lengyel et al., 2008; Kull et al., 2008). The majority of authors are very critical of the ability of most current conservation surveillance programmes to provide the necessary data with which to assess progress in halting the decline of biodiversity (Legg & Nagy, 2006; Lengyel et al., 2008; Kull et al., 2008), citing in particular the limited taxonomic scope of surveillance, a lack of clarity in the initial objectives, poor sampling design, failure to fully assess the ability of schemes to detect significant changes and, often, failure to actually analyse the data and make the results available. A particularly common problem, detected in many surveillance schemes, is the failure to develop clear objectives when designing the scheme, followed by collection of insufficient information to enable statistically valid conclusions to be drawn about species’ trends over the timescales required (Kull et al., 2008; Hovestadt & Nowicki, 2008). Inadequately designed surveillance programmes are a major issue, not only because the poor quality information which they produce may be misleading, but because they represent a waste of scarce resources, and create the false impression that something useful has been done (Legg & Nagy, 2006). Establishing the initial ‘Why?’, ‘What?’ and ‘How?’ of the surveillance to be undertaken is key to designing an effective and efficient surveillance programme (Yoccoz et al., 2001; Balmford et al., 2005; Legg & Nagy 2006). Having a clear statement of objectives is an essential first step in designing a surveillance programme, yet is commonly lacking in the belief that any additional data will be useful (Yoccoz et al., 2001). Objectives may be scientific (focusing on developing an understanding of the system being monitored) or based on management requirements (providing information on which to base management decisions) but setting them out as a clear series of hypotheses to be tested will aid in the development of an appropriate sampling design (Yoccoz et al., 2001; Legg & Nagy, 2006). Decisions on what to monitor will largely be determined by the initial hypotheses, but, for threatened European vascular plants, Kull et al. (2008) identified three basic groups of population parameters which could be assessed during surveillance: population size, population extent and population viability. In their review of plant surveillance schemes within Europe, they found that population size was the most commonly assessed parameter (measured in 92% of schemes), while population extent was measured in 43% of schemes and population viability in only 19%. This probably reflects the relative costs and difficulty of measuring these parameters; assessing spatial extent of a population may require substantially more resources than simple population counts at a limited number of locations, while determining population viability implies a good degree of knowledge of the biology and ecology of the species being assessed. When deciding what to monitor it is also useful to consider the wider context of the work. Most surveillance projects, by their very nature, are 10

long-term pieces of work and substantial sums of money may be expended in collecting the data. Consideration of what data requirements may be in the future, or of how datasets could be integrated for wider scale analyses may help to ‘future proof’ surveillance designs and lead to greater cost-effectiveness in the long run. Related to this, Kull et al. (2008) identified a threat that surveillance schemes designed only to meet legal obligations can become too simplistic. Aside from providing the minimum data needed to report on species status, such schemes may provide little information which can be used to aid conservation decision-making. Population trend data alone is of little use for guiding conservation, since it gives no indication of the drivers behind the observed changes. As a minimum, some information on key aspects of habitat condition should be collected alongside population data to aid in interpretation of the results. Having decided on the objectives of the surveillance programme and identified the key parameters to be measured, the final stage is to develop an appropriate sampling strategy. In order for the surveillance data to be useful there needs to be a consideration of issues such as the magnitude of changes which the scheme should be able to detect, the timescales we wish to detect them over and the level of certainty with which we want to detect them. Critical in our ability to detect, for example, trends in population size, is the accuracy with which we can measure the parameter of interest (measurement error) and also its natural year-to-year variability (process error). Many schemes fail to take this into account, with the results that the data collected are inadequate to detect even very large trends over the required timescale. On the other hand, expectation of the trends which may be detected should be realistic, given the resources available. For example, European Union reporting requires that a 1% annual decline in population be detected over 6-year reporting period. Hovestadt & Nowicki (2008) showed that detection of such a trend over such a short time period is almost impossible unless populations could be measured with 100% accuracy; to detect a 1% trend at all would require a very high precision population estimate and a time series of at least 15 years (with annual data). With data spanning 10 years, the likelihood of detecting a 5% annual change may be less than 50% with a moderate measurement error. Using data from a large-scale biodiversity surveillance scheme in Canada, Nielsen et al. (2009) showed that a species detectability of 66% and prevalence of 50% were needed to ensure than an annual change of 3% was detected at 50 sites over a 20 year period. For species groups such as lichens, and especially rare lichens, detection of the species presence may be difficult, resulting in low detectability and thus high measurement error. McCune et al. (1997) showed that, even with expert observers, almost one third of lichen species at a site may remain undetected. Expectations of the trends which may be picked up for populations of rare and difficult-to-detect species should not, therefore, be raised too high. Appropriate survey design (minimising measurement errors while maximising sample size within the resources available), can, however, help to maximise the chances of detecting population trends (Nielsen et al., 2009). Where measurement error and inter-annual variability can be quantified, a power analysis will allow the surveillance scheme’s ability to detect trends to be tested at the outset. 3.2 3.2.1

Aims of Scottish BAP lichen surveillance Objectives

The principle aim of Scottish BAP lichen surveillance is to provide information on temporal changes in species’ population size and range for the purposes of assessing conservation status and reporting to Europe. In addition, we wish to examine the links between population dynamics and likely drivers of change including air pollution (primarily nitrogen (N) and sulphur (S) deposition), climate change, and change in habitat condition (successional change, management action, land use change) in order to inform conservation actions for these species. An ideal surveillance scheme would provide data to enable all of the following questions to be addressed: 11

1. 2. 3. 4. 5.

Is there a temporal trend in the size of local and/or national populations? Does the temporal trend in local population size vary spatially? If there is spatial variation in population trends, does this relate to spatial patterns of pollution, climate, or habitat condition? Is there a temporal trend in the area occupied by the national population? Is there a temporal change in the location of the species’ range within Scotland?

The relevance of some of these questions may vary slightly between species. In particular, spatial trends in population size (question 2) will not be relevant to those Scottish BAP species which are known from only one site. For these species, and others with small numbers of known locations or limited geographic extent, our ability to discriminate between potential causes of change (question 3) will also be limited by the small sample size. 3.2.2

What to monitor

Three key parameters related to the lichen species’ populations must be measured in order to answer the five questions set out above in the objectives. These are: 1. 2. 3.

The number of ‘individuals’ within each local population; The area of habitat which the species occupies (Area Of Occupancy – AOO); and The spatial distribution of the occupied areas (Range).

For species such as lichens, an ‘individual’ may not be well defined or easy to recognise in the field. It must also be considered what unit comprises a functional individual for the purposes of population dynamics. For example, in long-lived, late successional, corticolous species, Scheidegger & Werth (2009) suggested that all conspecific thalli occupying a single tree could be considered as a single functional individual, because their fate is intimately linked to that of the host tree. Such definitions will vary according to the life-style and substratum of the species concerned, but this aspect must be borne in mind when collecting data to support evaluation of species conservation status. When considering very rare species, however, such as those known only from a single tree or fence post, pragmatism may require that some assessment of the species abundance is made at a scale below the usual minimum functional unit. Consideration of the spatial scale of measurement is particularly important when measuring area of occupancy (Hartley & Kunin, 2003); the area occupied decreases rapidly as grid cell sizes are reduced. Two species with identical area of occupancy assessed using the commonly used 10 km square mapping data may have very different areas of occupancy when assessed at the sub 10 km scale. The scale of measurement may also affect our ability to detect trends in species abundance (Hartley & Kunin, 2003; Joseph & Possingham, 2008). Large scale measurements may detect a rolling front of extinction spreading across a species range, but are generally unable to detect even severe population declines where these occur randomly at a scale below that of the measurement grid (Joseph & Possingham, 2008). A species must become completely extinct within a grid cell before a decline is registered. Measurement of area of occupancy at multiple spatial scales may provide useful information on the nature of change in species’ populations (Hartley & Kunin, 2003) and can reveal whether changes in overall population are due to local population fluctuations, changes in habitat availability or changes in range. In practice, the amount of recording time required, and hence cost of data collection, will increase rapidly as the size of the grid cells being recorded decreases. There will thus be a trade-off between accuracy of data recording and the funds available, although a suitable sub-sampling regime may be able to mitigate this. Species range size may be one of the least cost-effective parameters to assess for very rare species. Present range size is based on the distribution of 10 km grid squares in which the 12

species has been positively identified. To quantify a change in range requires that a species is confirmed as absent in an existing square, or identified as present in a previously unknown square. Confirming absences may be problematic for rare species with low detectability which could be easily missed when surveying large areas of habitat. Equally, identifying new squares also requires that a significant amount of time is spent searching potential habitat for species with low prevalence and low detectability, and consequently with a low likelihood of a positive outcome. However, without searching areas in which the species is not currently known, results of range change analyses will be biased towards recording declines. Aside from collecting information on each species’ spatial and temporal variation in abundance, information on the three key drivers of change identified above (pollution, climate and habitat condition) are required to enable interpretation of the reasons for any detected population trends. Spatial datasets with national coverage at the 5 km, or occasionally down to 1 km scale are readily available for pollution and climate variables (e.g. see www.apis.ac.uk or www.metoffice.gov.uk/climate) which would be impractical and expensive to measure directly at the site scale. Information on habitat condition would, however, need to be measured alongside the lichen population parameters. The most relevant parameters to measure when assessing habitat condition will vary according to the species’ ecology and the habitat it occupies, but for most species would be likely to include light, humidity and availability of suitable substrate. Habitat attributes for lichens have already been identified for a wide range of habitats as part of the Site Condition Monitoring (SCM) programme and could be modified or augmented to reflect any particular requirements of rare species. There is also potential to integrate the requirements of SCM and rare species surveillance to improve overall cost effectiveness (see section 3.4, below). 3.3

Geographic and habitat distribution of Scottish BAP lichens

Annex 2 shows the pre- and post-1960 UK distribution of each of the 89 species on the Scottish BAP list according to the latest data on the National Biodiversity Network. Table 2 shows simplified habitat and substratum affiliations for all of these species along with the number of 10 x 10 km grid cells in which they have been recorded in Scotland post 1960, based on the most recent data from the Scottish Sites Lichen Database (November 2010). Of the 89 species 24% are known from a single 10 km grid cell only, a further 24% have distributions restricted to between 2 and 5 10 km cells, 31% are slightly more widespread with 6 to 19 10 km cells and only 21% are known from 20 or more 10 km cells (Table 3). It is important to note, however, that those species which are restricted to a small number of grid cells may not be restricted to a small geographical area; it is not unusual for the small number of cells to be widely scattered across Scotland. This may reflect the distribution of suitable habitat, but also potentially, a lack of recording effort for these species in the baseline data or the low likelihood of detecting rare and cryptic species during site surveys.

13

Table 2 - Habitat and substratum affiliations and number of occupied 10 x 10 km squares 1960-2010 for BAP lichen species present in Scotland. Species name

Main habitat

Substratum

Arthonia cohabitans Arthothelium macounii Graphis alboscripta Pyrenula hibernica Collema dichotomum Arthonia patellulata Caloplaca ahtii Candelariella superdistans Caloplaca caesiorufella Cyphelium trachylioides Anaptychia ciliaris subsp. ciliaris Bacidia incompta Caloplaca flavorubescens Caloplaca lucifuga Caloplaca luteoalba Caloplaca virescens Catillaria alba Chaenotheca gracilenta Collema fragrans Fuscopannaria ignobilis Lecania chlorotiza Lecanora quercicola Melanelixia subargentifera Porina hibernica Schismatomma graphidioides Sclerophora pallida Thelenella modesta Bryoria furcellata Arthonia atlantica Aspicilia melanaspis Brodoa intestiniformis Calicium corynellum Collema fragile Gyalecta ulmi Gyalidea roseola Lecanora achariana Peltigera lepidophora Peltigera venosa Phaeophyscia endococcina Poeltinula cerebrina Porina sudetica Stereocaulon delisei Stereocaulon symphycheilum Synalissa symphorea Toninia sedifolia Umbilicaria spodochroa Vulpicida pinastri Alectoria ochroleuca Cladonia peziziformis Hypogymnia vittata Nephroma arcticum Peltigera malacea Cladonia botrytes

Ancient hazelwoods Ancient hazelwoods Ancient hazelwoods Ancient hazelwoods Aquatic Aspen woods Aspen woods Aspen woods Fenceposts Fenceposts Parkland/roadside trees/open forest Parkland/roadside trees/open forest Parkland/roadside trees/open forest Parkland/roadside trees/open forest Parkland/roadside trees/open forest Parkland/roadside trees/open forest Parkland/roadside trees/open forest Parkland/roadside trees/open forest Parkland/roadside trees/open forest Parkland/roadside trees/open forest Parkland/roadside trees/open forest Parkland/roadside trees/open forest Parkland/roadside trees/open forest Parkland/roadside trees/open forest Parkland/roadside trees/open forest Parkland/roadside trees/open forest Parkland/roadside trees/open forest Pinewoods Saxicolous Saxicolous Saxicolous Saxicolous Saxicolous Saxicolous Saxicolous Saxicolous Saxicolous Saxicolous Saxicolous Saxicolous Saxicolous Saxicolous Saxicolous Saxicolous Saxicolous Saxicolous Scrub Terricolous Terricolous Terricolous Terricolous Terricolous Tree stumps

lichenicolous corticolous corticolous corticolous saxicolous corticolous corticolous corticolous lignicolous lignicolous corticolous corticolous corticolous corticolous corticolous corticolous corticolous corticolous corticolous corticolous corticolous corticolous corticolous corticolous corticolous corticolous corticolous corticolous saxicolous saxicolous saxicolous saxicolous saxicolous saxicolous saxicolous saxicolous saxicolous saxicolous saxicolous saxicolous bryicolous saxicolous saxicolous saxicolous saxicolous saxicolous corticolous terricolous terricolous terricolous terricolous terricolous lignicolous

14

No. occupied 10 km cells 2 11 18 4 26 19 5 10 2 1 13 20 13 4 26 1 5 4 1 21 7 1 1 3 17 23 1 4 1 1 3 1 5 11 2 2 1 15 6 1 1 19 2 2 76 1 12 10 1 1 1 8 15

Species name

Main habitat

Substratum

Calicium diploellum Fuscopannaria sampaiana Gomphillus calycioides Leptogium brebissonii Leptogium cochleatum Leptogium hibernicum Megalospora tuberculosa Parmeliella testacea Polychidium dendriscum Pseudocyphellaria intricata Pseudocyphellaria lacerata Pseudocyphellaria norvegica Pyrenula dermatodes Rinodina isidioides Sticta canariensis Wadeana dendrographa Arthonia invadens Arthothelium dictyosporum Bacidia circumspecta Bacidia subincompta Biatoridium monasteriense Buellia violaceofusca Catapyrenium psoromoides Chaenotheca laevigata Collema fasciculare Diplotomma pharcidium Lecanographa amylacea Lecanora cinereofusca Lecidea erythrophaea Leptogium saturninum Pertusaria velata Ramonia chrysophaea Ramonia dictyospora Rinodina degeliana Usnea florida Wadeana minuta

Western woodlands Western woodlands Western woodlands Western woodlands Western woodlands Western woodlands Western woodlands Western woodlands Western woodlands Western woodlands Western woodlands Western woodlands Western woodlands Western woodlands Western woodlands Western woodlands Woodland Woodland Woodland Woodland Woodland Woodland Woodland Woodland Woodland Woodland Woodland Woodland Woodland Woodland Woodland Woodland Woodland Woodland Woodland Woodland

corticolous corticolous corticolous corticolous corticolous corticolous corticolous corticolous corticolous corticolous corticolous corticolous corticolous corticolous corticolous corticolous lichenicolous corticolous corticolous corticolous corticolous corticolous corticolous corticolous corticolous corticolous corticolous corticolous corticolous corticolous corticolous corticolous corticolous corticolous corticolous corticolous

No. occupied 10 km cells 1 80 36 74 22 15 21 83 17 65 8 98 1 7 11 12 2 8 7 21 1 12 1 3 79 23 11 3 13 31 2 5 12 2 1 23

Classifying species according to their main substratum type (Table 4) reveals that the Scottish BAP list is dominated by corticolous species (66%), with a further 21% of saxicolous species and much smaller proportions of terricolous, lignicolous, lichenicolous and bryicolous species (6%, 3%, 2% and 1% respectively). The species may also be grouped by the broad habitat type within which they occur, resulting in 12 species groups covering a wide range of habitats (Table 2, Table 5). Three of the four largest groups represent woodland habitats: general closed woodland (20 species), species of well-lit trees in parkland, wayside or open forest situations (17 species) and species of oceanic western woodlands (16 species). Other, smaller, woodland habitat groups include ancient hazel woods of the west coast (an internationally important habitat type), aspen woodlands, and native pinewoods. The largest of the remaining groups are the saxicolous group (18 species) occurring on boulders and rock outcrops in a wide range of lowland, upland or alpine situations, and the terricolous group (five species) occurring in heathland and short turf in montane and coastal situations. Other habitats represented on the list include aquatic, scrub, fence posts and tree stumps. Many of these habitat groupings contain species which have very different distributions, despite occurring in similar habitat; however, the ancient hazel woods, aspen woods and western woodlands represent species groups

15

with congruent geographic ranges. In these habitats several BAP species occur either together at the same sites, or within a limited geographic range and thus may form useful units when considering how best to approach surveillance activities (see section 3.4, below). Table 3 - Classification of Scottish BAP lichens species by number of occupied 10 km squares between 1960 and 2010. Number of occupied 10 km squares 1 2-5 6-19 20+ Total

Number of species 21 21 28 19 89

% 24 24 31 21 100

Table 4 - Classification of Scottish BAP lichens by substratum. Substratum type Corticolous Saxicolous Terricolous Lignicolous Lichenicolous Bryicolous Total

Number of species 59 19 5 3 2 1 89

% 66 21 6 3 2 1 100

Table 5 - Summary of habitat groupings for Scottish BAP lichen species. Average species priority ranking are based on the preferred prioritisation of species given in Table 1. Main habitat Ancient hazelwoods Aquatic Aspen woods Fence posts Parkland/roadside trees/open forest Pinewoods Saxicolous Scrub Terricolous Tree stumps Western woodlands Woodland

Number of species 4 1 3 2 17

Geographically distinct group? Yes N/A Yes No No

Average species priority ranking 11 87 73 28 50

1 18 1 5 1 16 20

N/A No N/A No N/A Yes No

56 56 79 54 74 26 41

16

3.4 3.4.1

Increasing cost-efficiency of BAP species surveillance Grouping of species for survey purposes

Many of the Scottish BAP species occur in remote locations, and a large proportion of the cost of implementing surveillance may be taken up by travelling time. It may be possible to make surveys more cost effective by grouping certain species together. Where species occur in the same locations and habitat, there may also be efficiencies in terms of collecting associated data on habitat condition. Categorisation of the species into habitat groups (section 3.3, Table 2, Table 5) identified three groups of species which occur in the similar habitats and geographic areas. These were Ancient hazelwoods, Aspen woods and Western woodlands. Ancient hazelwoods contain a small suite of specialist species which mainly rank as high priority for surveillance (Table 5); the habitat has previously been identified as being one of international importance for Scotland and so should be seen as a very high priority for implementation. The habitat and associated BAP species have a fairly restricted distribution along the western seaboard, and so could be efficiently addressed with a combined surveillance programme. Aspen woods also contain a small suite of associated BAP species and occur in a limited geographic area. These species could also be more efficiently monitored together, but generally have a much lower priority ranking (Table 5), as many of the species within the group tend to be better represented in other parts of Europe. The final and largest habitat group to be identified was the western woodland group. This group contains both rare and restricted species (small number of known locations) along with a number of much more widespread, but internationally important species with a large number of locations in Scotland. The distribution of this habitat is restricted to the western seaboard, but covers a large geographic area. The relatively large number of BAP species (16) and the large geographic area means that to survey this set of species as a group would be a very large undertaking, but could provide considerable savings over surveillance of the individual species separately at different times. In terms of the average priority rating of the species it contains, western woodlands were second only to the ancient hazelwoods group (Table 5). Given the importance of the western woodlands to Scotland’s contribution to global biodiversity this habitat grouping should be considered a high priority. The remaining habitat groups identified were not geographically congruent and so do not provide sensible groupings for survey purposes. However, when selecting individual species for survey, especially those with a very limited number of sites, consideration should be given as to whether there are other species on the list which occur in nearby locations and could be monitored at the same time. 3.4.2

Use of existing surveillance data within the programme

A limited amount of prior survey data is available for a small number of species on the BAP list. Those species with BAP dossiers may have lists of known extant sites at the time of writing (generally within the period 1993-2003) and occasionally have information from repeat visits to ascertain the species’ continued presence. This information may be helpful in setting up a baseline for surveillance, but is generally not quantitative and so of limited usefulness for extrapolating population trends back in time. For a very small number of species (e.g. Catapyrenium psoromoides, Nephroma arcticum) permanent quadrat surveillance has been established in the past. For these species which are present at a single site only, monitoring of these permanent quadrats could be continued in the new surveillance programme, giving longer continuity of data. 3.4.3

Integration of lichen habitat SCM and BAP species surveillance

Surveillance of BAP lichen species will require collection of information on habitat condition similar to that required for Site Condition Monitoring (SCM). SCM is only carried out for 17

those SSSIs where lichens are a notified feature and not all BAP species sites occur on SSSIs, so we suggest that habitat condition measures used in BAP species surveys could be selected such that they can also fulfil SCM requirements. Combining BAP surveillance and lichen SCM could give cost savings in terms of travel and surveying time and would allow surveyors a longer total time in the field, improving their ability to form a complete picture of site condition. The habitat monitoring for BAP species in non-SSSI sites could also substantially increase knowledge of wider habitat condition in Scotland for some habitats. 3.5

General approach to surveillance of BAP lichens

The diversity of species, habitats, distributions and potential drivers of change represented on the Scottish BAP lichen list is such that any general surveillance scheme will require adaptation on a case-by-case basis to suit the needs of the species being considered. However, here we set out general aspects of surveillance which will apply to most species. In the light of the species information set out in section 3.3, above, our ability to answer the ideal set of surveillance questions laid out in section 3.2.1 for all species can be assessed in more detail. The level of information which could feasibly be derived from a surveillance programme is particularly affected by the spatial distribution of species’ populations. In particular, spatial analysis of the drivers of change in local population size is impossible for those species known only from a single location (24% of species), and likely to be very limited for those present in more than one but less than 20 10 km squares (55 % of species), especially where the geographic distribution of the locations is clumped. More detailed analysis of the causes of change may only be realistically possible for the 21% of species with more wide ranging distributions. The complexity of the design used for surveillance of each species should thus reflect the information which can be derived from the scheme. Once the objectives of the surveillance programme and the key parameters to be measured have been identified (Section 3.1), the final stage is to develop an appropriate sampling strategy. For this the following is required: 1. Map of area of suitable habitat to be sampled; 2. Test of sampling methodology to assess the efficiency and repeatability of the survey (e.g. repeatability between surveyors, time taken for different survey methods, detectability of the species); and 3. Population density, distribution and variability through time to enable a power analysis to be performed. This will enable the sample size required to detect a given level of change to be calculated. This information is not readily available for the BAP lichen species and habitat types for which we wished to design a sampling methodology. To develop a full sampling design for all of the 89 species on the BAP list is beyond the scope of this project. Therefore the following chapters focus on providing examples as to how this information may be gathered and on a sampling trial designed to test some of these variables and gain a better understanding of the repeatability and efficiency of different survey approaches. Chapter 4 shows how maps of potentially suitable habitat maybe developed for Pseudocyphellaria norvegica and for the ancient hazelwoods lichen group (Arthonia cohabitans, Arthothelium macounii, Graphis alboscripta, Pyrenula hibernica). In Chapter 5 methods design to monitor Pseudocyphellaria norvegica are trialled and used to assess the repeatability between surveyors and differences between fixed transect and search survey methods. Chapter 6 uses site condition monitoring data for Pseudocyphellaria norvegica to look at population turnover and to perform a power analysis to calculate sample size.

18

4. 4.1

DEVELOPMENT OF MAPS OF POTENTIALLY SUITABLE HABITAT Aims of map development

The first stage of the survey methodology (section 3.5) requires the development of maps of potentially suitable habitat on which to base selections of survey areas. It is beyond the scope of this project to develop potentially suitable habitat maps for all BAP species. Here we show maps which we have developed for Pseudocyphellaria norvegica and for the ancient hazelwoods lichen group (Arthonia cohabitans, Arthothelium macounii, Graphis alboscripta, Pyrenula hibernica). The aim was to identify all areas of suitable habitat, even if the target species had not previously been recorded in these areas. 4.2

Methods

In order to develop the maps, we used polygons classed as broadleaf woodland from the semi-natural woodland map (Highland Birchwoods, undated) as our base layer and overlaid both the distribution of the target lichen species and of a suite of additional lichen species, specific to the type of woodland associated with the target species. For Pseudocyphellaria norvegica we used species from the West of Scotland Index of Ecological Continuity (WSIEC) (Coppins & Coppins, 2002), selecting all polygons containing semi-natural woodland and either P. norvegica or a minimum of 10, 15, 20 or 30 lichen species from the WSIEC list. For Atlantic hazelwood habitat we used four species which are known to be hazel specialists (Eopyrenula septemseptata, Melaspilea atroides, Pyrenula coryli and Thelotrema macrosporum) in addition to the four BAP target species (Arthonia cohabitans, Arthothelium macounii, Graphis alboscripta, Pyrenula hibernica), overlaying the distribution of these species onto the woodland map. In both cases, lichen distribution records from the British Lichen Society Database (British Lichen Society undated) at the 1 x 1 km scale were used, to give a trade-off between identifying all areas of suitable habitat and including large areas of unsuitable woodland identified due to the coarse scale of some lichen recording (e.g. 10 x 10 km records). 4.3

Results

The habitat map for Pseudocyphellaria norvegica identified 1742 polygons containing seminatural woodland and either P. norvegica or a minimum of 10 lichen species from the WSIEC list, with the number of polygons declining as the number of WSIEC species increased (Table 1). There was 9026 ha of suitable habitat contained within 311 1 km squares identified using P. norvegica or a minimum of 10 lichen species from the WSIEC list and 5812 ha contained within 206 1 km squares for P. norvegica or a minimum of 30 lichen species from the WSIEC list (Table 1). Irrespective of the number of WSIEC lichens (10, 15, 20 or 30) about 76% of polygons were 5 ha or less in size; 7% of polygons were between 5 and 10ha, only 6% of polygons were larger than 25 ha (Table 1). A map composed of P. norvegica or a minimum of 10 lichen species from the WSIEC list is recommended to identify potential P. norvegica habitat as well as current habitat (Fig. 1). It would be possible to choose a higher threshold to eliminate woodland that is currently less suitable for P. norvegica, but this would limit detection of positive trends due to colonisation of new areas of woodland as they potentially become more optimal habitat for the lichen with age. The map for Atlantic hazelwoods identified 3568 ha of potentially suitable habitat (Fig. 2). This was composed of 687 polygons or 611 sites across 144 1 km squares. The majority of the polygons (76.9%) were ≤ 5ha; 6.8% of polygons were between 5-10ha, only 5.8% of polygons were bigger than 25ha.

19

Table 6 - Differences in area of potentially suitable habitat for Pseudocyphellaria norvegica identified when maps are created using records for Pseudocyphellaria norvegica or a minimum of 10, 15, 20 or 30 WSIEC species. Number of WSIEC species

Total area Number of 1 Number of (ha) km squares polygons

Percentage of polygons

≤5 ha

5-10 ha

20m).

40

5.5.5

Presence/absence data

Of the 54 1 ha cells surveyed, Surveyor 1 found P. norvegica in 35 cells and Surveyor 3 found P. norvegica in 30 cells. There were 26 cells where both surveyors found occupied trees and 15 cells were both surveyors did not find any occupied trees (Fig.19). There were nine cells where Surveyor 1 found occupied trees and Surveyor 3 did not and four cells where Surveyor 3 found occupied trees and Surveyor 1 did not. This included one cell which Surveyor 1 assessed as having no suitable habitat, yet Surveyor 3 found P. norvegica to be present. Whilst these results are not statistically significant, presence/absence provides a less powerful test of differences than the number of occupied trees, and in view of the statistically significant differences in the time taken to find the first occupied tree, it is quite likely that with a larger sample size a significant result would be found. The result of no significant difference between surveyors based on presence/absence data should therefore be interpreted with caution.

Figure 19. Percentage of 1 ha cells where surveyors had the same or different presence/absence data. Both found = both surveyors found Pseudocyphellaria norvegica present, both absent = both surveyors found Pseudocyphellaria norvegica absence, Surveyor 1 only = only surveyor 1 found Pseudocyphellaria norvegica, Surveyor 3 only = only Surveyor 3 found Pseudocyphellaria norvegica. 5.6 5.6.1

Discussion Transect versus searches

In terms of collecting baseline data on species distribution and density, we found no evidence to suggest that controlled survey methodologies using fixed transect patterns were any better in terms of consistency between surveyors than a 20 minute search of the areas in the cell deemed most suitable by an experienced surveyor. Given that following the fixed transect patterns took approximately twice as much time as a 20 minute search, the search method would clearly be more cost-effective when there are large numbers of cells to survey. Fixed transect patterns might be considered to be worth the extra time investment if there was evidence that these methods were more repeatable between surveyors than the search method, but there was no evidence that this was the case, since between-surveyor variability did not change between survey methods.

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5.6.2

Surveyor variability

This small-scale trial of survey methodologies leads to the clear conclusion that differences between surveyors are likely to be an important issue when planning and implementing any larger scale survey of priority lichen species. Other studies have also found significant differences between teams of highly skilled lichenologists (McCune et al., 1997; Brunialti et al., 2002, 2012; Giordani et al., 2009). Brunialti et al. (2012) classified the sources of error as sampling errors, and non-sampling errors (including instrumental accuracy and subjectivity). Sampling errors are generated by the nature of the sampling itself and by the degree of variability in the target population. Sampling errors will always occur but can be controlled by appropriate sampling design (Köhl et al., 2000). In this study the only source of instrumentation error was the accuracy of the GPSs to locate the transects/1 ha cells. This could have been the source of some differences between the surveyors. However, as differences between surveyors were consistent across cells, the variability appears to be due to the surveyors themselves rather than their equipment. As the surveyors were professional lichenologists and highly skilled, it is unlikely that the results of this study could be improved by further training of the surveyors, as suggested by some studies (Giordani et al., 2009) or by employing more qualified surveyors (McCune et al., 1997). If calibration between surveyors were possible this would enable surveyor variability to be taken into account during the analysis. However this was not possible with the data collected from Survey 1 as we did not know if Surveyor 2 was finding a subset of the trees detected by Surveyor 1 or if Surveyor 2 was finding a different set of trees. The methodology would need to be changed in order to test this and to calibrate between the two surveyors. Development of a calibration method between surveyors was considered, however calibration would have to be done in the field for each surveyor which is costly in terms of surveyor time. In addition, there would be no way to standardize between surveyors in different years as even if the same people were able to do the work, their lichen identification skills or speed of surveying may have changed. An artificial method of calibration using photo recognition in a computer simulation model might allow comparison between years, as the same model could be used for each survey. However, this does not equate to the difficulties of walking through a wood looking for the species which will influence surveyors ‘success’ in recording. An artificial method of calibration, e.g. using pins in woodlands and seeing how many pins the surveyors find, would include the difficulties of walking through the woodland but would again only allow calibration in any given year as it would be difficult to ensure that the pins were hidden with the same level of difficulty in future years. One method to overcome this would be to repeat the calibration several times in lots of different places but this would be costly and would result in a reduction in the resources available to carry out the actual survey work. We conclude that there is no practicable way of calibrating between surveyors that would enable us to calibrate not only within any year but also between years. Therefore any method to monitor priority lichens needs to be such that variability between surveyors does not mask temporal changes in populations. 5.6.3

Ways to reduce surveyor variation

Ways to reduce surveyor variability include either using fixed plots, thus removing any variability due to differences in route taken despite using a very accurate GPS, or to reduce the level of detail recorded: recording presence/absence data instead of population data. If only plots containing the species to be monitored are established then the survey is biased to recording a declining or stable population and not an increase (MacKenzie et al., 2003). To overcome this requires that a species is confirmed as absent in an existing plot, or identified as present in a previously unknown plot. This requires empty or blank permanent plots to be established; however, it is not known how many blank recording plots would be required to detect an increase in population. The establishment of permanent plots also raises a number of practical issues: (1) a large amount of time would be required to set up 42

plots over a large area, such as the range of P. norvegica, which would be costly when limited resources are available for lichen surveillance; (2) plot markers would have to be maintained over time, probably tens of years and (3) there might be difficulties in relocating plots during each survey. Presence/absence data are relatively quick to collect, depending on the scale of measurement, and are less prone to observer error than more complex measurements which require estimation of areas, cover, or counts of individuals. Confirming absences may be problematic for rare species with low detectability which could be easily missed when surveying large areas of habitat and this may be a source of inter-surveyor variation. Equally, depending on the size of the area to be searched, identifying areas where the species is now present but was previously absent also requires that a significant amount of time is spent searching potential habitat for species with low prevalence and low detectability, and consequently with a low likelihood of a positive outcome. 5.6.4

Presence/absence versus population

The presence/absence data at the 1 ha scale in Survey 1 showed a 100% match in results between surveyors. However when this was tested with a larger number of samples (Survey 2) this did not hold true with only 80% of cells having the same result (presence or absence) between surveyors. However this is an improvement on the count data in Survey 2 where only 31% of cells had the same result (2 cells with same number of trees and 15 cells with both surveyors recording zeros). The results suggest that recording presence/absence data at the 1 ha scale, while not removing all the surveyor variability, does reduce it. If data are to be collected as presence/absence consideration of the spatial scale of measurement is important (Section 3.2.2). At smaller scales, presence/absence in a grid of cells may also be used as a measure of abundance or local population size. The disadvantage of this is that the entire population has to be lost from a measurement unit before a change in population is recorded. If large scale units (e.g. 1 x 1 km) are used then a substantial decrease in the population may have occurred before a change is recorded. In the Section 3.2.2 three key population parameters were identified that must be measured: the number of ‘individuals’, area of occupancy (AOO) and the range. This work has highlighted the difficulties associated with measuring the number of ‘individuals’ in each population. If presence/absence data are recorded the closest measurement to population change will be change in number of occupied 1 ha cells within a 1 km square or within a site. A method that recorded presence/absence and instructed the surveyor to move onto the next 1 ha cell as soon as P. norvegica was found would enable more 1 ha cells to be surveyed than if a full 20 minute search is carried out. This will enable more information on AOO and range to be collected for the same level of resources but at the expense of detailed information on the number of individuals. Any survey method will be a compromise between assessment of area of occupancy (AOO) and population change. If data on change in number of individuals are too variable to give meaningful results then resources should be targeted towards providing information on AOO and range. Recording at the 1 ha level allows data to be collected at a resolution 100 times greater than at the 1 km square level and allows changes in both AOO and range to be assessed. The results of this study suggest that this is a suitable compromise between recording number of individuals and changes in AOO and range and reduces, but not eliminates, surveyor variability. 5.6.5

Further development of surveillance methodologies

If presence/absence data are to be collected the expectations of the changes in occupancy that will be detected need to be realistic, with data from this study showing that only 80% of 1 ha cells had the same results when surveyed by two surveyors. This may require the revision of conservation definitions of threatened species as detection of the level of change 43

required by the current definitions may not be possible. Using the map of potentially suitable habitat a sampling strategy of 1 ha cells to be surveyed needs to be developed. However, a realistic power analysis to calculate the number of 1 ha cells which should be surveyed to detect population change requires data from a survey that has been repeated after a number of years to assess population turnover. If the limitations of using presence/absence data are not acceptable then the only alternative is permanent surveillance plots together with an acknowledgement that a significant amount of investment is required to establish and maintain these plots. For rare and difficult to detect species there may be no quick, easy and cheap surveillance method that will allow surveillance to be done at a sufficiently high standard to detect change at the required level of precision. An alternative to surveillance of the population is the use of habitat proxies: monitoring the habitat condition rather than the species itself. In the UK this is currently the approach taken by JNCC’s common standards monitoring (JNCC, 2005). However more information on the autecology of these BAP lichen species is required before this approach can be tried. Such an approach is also risky as the habitat may change in some way that is not assessed and the population may decline without it being realised due to the lack of direct surveillance. 5.7

Conclusion

There is no evidence that estimates of priority lichen populations using controlled survey methods (fixed transect patterns) were any better in terms of consistency between surveyors than a 20 minute search of areas of a 1 ha cell deemed most suitable by an experienced surveyor. However, as the resources were not available to carry out exhaustive searches of each cell, we do not know the extent to which the time-constrained searches underestimated the true number of occupied trees. Fixed transect patterns took approximately twice as long to carry out as 20 minute searches, therefore the search method is clearly more cost effective when there are a large number of cells to survey. When using count data, variability between surveyors was high making it impossible to reliably identify temporal changes in populations, and identify population trends. Using presence/absence data at the 1 ha cell level reduced, but not eliminated, the surveyor variability and is suggested as a suitable compromise between recording ‘individuals’ within a population and changes in area occupied.

44

6.

ASSESSING POPULATION TURNOVER

6.1

Aims

This chapter aims to show, using the example of P. norvegica, how population turnover in a species can be assessed. This information is required to gain an understanding of likely rates of turnover in habitat occupancy and potential rates of change in populations through time. Such information is required to conduct a power calculation for the sample size required to monitor population turnover. 6.2

Methods

Information on population turnover for BAP lichens is not currently available and, as the surveys in Chapter 5 were only done at one point in time, this information was not available. Data were instead collected from two sources: 1) colonies marked on trees at Glen Shira and 2) searching site condition monitoring reports. It is acknowledged that these data are not directly comparable to turnover at the 1 ha scale but the aim was to use them to provide a rough indication of the likely number of 1 ha cells that should be established for baseline monitoring. Once a repeat survey of these baseline surveillance cells is carried out, more accurate information on population turnover will be available to provide a more accurate power calculation. 6.2.1

Glen Shira – data collection

In their report on the lichens of Glen Shira, Coppins & Coppins (1996) recorded several instances of P. norvegica including four on ash trees and one on oak. These trees were tagged by them as part of their survey. Glen Shira was visited by Brian and Sandy Coppins on 2nd March 2012, with the aim of re-finding the marked trees and recording if the tree was still occupied (yes/no) and, if yes, how many of the original colonies of P. norvegica are apparently still present. GPS readings were made for each tree, and each was rephotographed from approximately the direction as in the 1996 report. 6.2.2

Site condition monitoring reports – data collection

As the five trees from Glen Shira were not sufficient to look at population turnover the data were supplemented by searching site condition monitoring (SCM) reports to identify additional sites where P. norvegica has been recorded on more than one occasion. Sixty-nine site condition monitoring reports were identified where P. norvegica had been recorded. Each report was read to assess changes in the occurrence of P. norvegica within the site (or within different parts of the site depending on available information) and changes in the individual patches of P. norvegica using data from the Direct Monitoring Proformas (DMPs). Changes within the site or sub-site level were recorded as presence/absence of P. norvegica and based on the information provided in the SCM reports. This included historical information on occurrence based on old survey records and documents. DMPs were set up in the first round of SCM which started in 2004. Individual patches of P. norvegica were marked, photographed and recorded for condition/size (the exact details of what was recorded depended on the surveyor). In the second round of SCM these DMPs were revisited and the presence of the lichen patches recorded together with any information on changes in the size and/or condition of the lichen patch. Data on changes in the presence/absence of P. norvegica patches was therefore extracted from the DMPs.

45

6.3

Results

6.3.1

Glen Shira – Results

Of the five trees tagged in 1996, P. norvegica was no longer present on two of the trees, had increased in size on two trees and remained the same size on a third tree (Table 7). The full results can be found in Annex 3. Table 7 - Summary of presence of Pseudocyphellaria norvegica on tagged trees in 1996 and 2012 Tag no.

GR

Tree species

02185 02186 02199 02231 02234

NN 12682 13022 NN 12698 12993 NN 14576 16177 NN 14480 16340 NN 14741 16358

Fraxinus Fraxinus Quercus Fraxinus Fraxinus

6.3.2

P. norvegica present Yes No Yes Yes No

Overall change Increase Loss ± same Increase Loss

Site condition monitoring reports – site level results

From the 69 SCM reports, 47 sites/sub-sites were identified where P. norvegica was recorded. Of these, 40 sites/sub-sites had more than one visit, 15 sites had three visits, two sites had four visits and one site had five visits. The data covers 1970-2011 but the time period between any two visits varies hugely between individual sites. The maximum time was 30 years and the minimum 5 years. Of the 40 sites with more than one visit, 30 sites had P. norvegica on all visits. This included sites where the lichen was recorded as present, then not recorded and then re-recorded. This assumed that the ‘lost’ record was due to it not being found rather than it really having been lost from the site. There were three sites where it was noted as being recorded for the first time having not been present at a previous visit. There were six sites were it was recorded on the first visit but then not re-found so categorised within this report as lost (Fig. 20). There was one site where P. norvegica was noted as being absent, then present and then absent over the course of three surveys. This could either be due to mis-identification or not searching in the correct place for the lichen. This record was not included in the above data. A full summary of the results at the site/sub-site level are shown in Annex 4.

46

Figure 20. Changes in the presence of Pseudocyphellaria norvegica at sites/subsites. P = present in all years, i = absent then present, d = present in first visit, then absent. Data is from 40 sites covering 1970 to 2011 but the time period between any two monitoring visits varies hugely between sites 6.3.3

Site condition monitoring reports – DMP results

From the DMPs, 64 patches were identified which had repeat visits. These 64 patches came from 22 separate trees. Of the 64 patches, 29 patches were present in both visits, 17 patches were lost (i.e. present in the first visit but not in the second) and 18 patches were identified as new (Fig. 21). The ‘lost’ patches were those patches where the correct location was re-found but the lichen was no-longer present. It did not include patches where it was not possible to re-find the location. It should be noted that of the 18 new patches, 15 of these were from one DMP on Eigg. The timescale between the two records of any given patch varied between 5 and 7 years.

50 45

% of patches

40 35 30 25 20 15 10 5 0 p

i

d

Figure 21. Changes in the presence of patches of Pseudocyphellaria norvegica during the two cycles of SCM.

47

p = present in both cycles of monitoring, i = absence in first cycle, present in second cycles, d = present in first cycle, absent in second cycle of monitoring. 6.3.4

Power analysis – site/subsite level data

When data are collected as presence/absence, McNemar’s test may be carried out which compares the frequency of presences changing to absences (b) with that of absences changing to presences (c). If the population is stable, we would expect that b=c, or equivalently that the ratio b/(b+c)=0.5. Table 8 - Data required for power calculation Present Time 2 a c a+c

Absent Time 2 b d b+d

Row Total a+b c+d n

Present Time 1 Absent Time 1 Column Total   We assume that the area of a site/sub-site listed in Annex 4 roughly corresponds to 1 ha, although in reality the sites/sub-sites are probably quite variable in size. The Site Condition Monitoring (SCM) site/sub-site data provide a value of a=31 and b=6 (Fig. 20). If we assume no trend in the population, then c would also be 6. However, as in general only sites/subsites where the species was recorded at the time of the initial survey have been monitored, we do not have a value for d (or for n which would allow us to calculate it). Data from our Survey 2 were therefore used to provide an estimate the prevalence of P. norvegica in 1 ha squares. At Glen Nant P. norvegica was found in 86% of 1 ha squares, whereas Collias Nathais it was found in 26%, giving an average of 60%. However, as the Glen Nant 1 km square was purposely chosen because of the known presence of P. norvegica, 25% prevalence is perhaps a more realistic estimate and will provide a more cautious estimate of the number of 1 km squares required. For the SCM sub-site data a prevalence rate of 25% would imply that n=37/0.25=148. The power of the McNemar test to detect a change will depend on both the probability of a change of status and on the ratio of the probabilities of the two types of change. The ratio of the probabilities of the two types of change will be closest to 1 if the decrease in the population is entirely due to an increase in the number of extinctions, rather than being combined with a decrease in the number of colonisations. So in order to provide a cautious estimate of the required sample size, we consider this case. Suppose that we want to have an 80% chance of being able to detect a 10% decline in the population. In the case of 25% prevalence, the estimated ratio of probabilities would then be (6+0.1×37)/6=1.617 and the estimated probability of change is (2x6+0.1×37)/148=0.106. The required sample sizes were then calculated using the SMCNEMAR procedure in Genstat 14 (VSN International, 2011). This gave a required sample size of 1393 1 ha cells to be surveyed. However, if the prevalence is 50% only half that number would be required. If all the 1 ha cells within a 1 km square contained suitable habitat then 14 1 km squares would be required to be surveyed. However it is unlikely that all the 1 ha cells within a 1 km square will contain suitable habitat and there is a trade-off between fewer 1 ha cells per 1 km square and more 1 km squares being surveyed (providing greater geographical cover) and the increased costs associated with greater travel time. Assuming 50% of the 1 km squares contained suitable habitat, and all the 1 ha cells with suitable habitat were surveyed, then the power calculations suggest a minimum of 28 1 km squares should be surveyed.

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6.3.5

Power analysis – patch/tree level data

The DMP provides repeated monitoring of patches on marked trees. It is questionable whether comparing the number of patches between sampling occasions is a useful means of monitoring change. What is measured between DMPs varies; sometime it is the thallus and sometimes a patch. This results in there being no clear definition of an individual (Section 3.2.2). If one large patch has broken down over time into several smaller patches, this would appear to be an increase, even though the total area covered by the lichen has in fact decreased. Similarly, if several small patches merge to form one large patch, this would appear to be a decrease in the number of patches, even though the total area covered by the lichen has in fact increased. Instances of these types of ’increase’ and ’decrease’ were noted when searching the SCM reports for data. DMP data predominately monitors declines or losses of patches as DMPs are not set up on trees without P. norvegica and monitored to see if it colonizes. New patches were identified but most of these came from one site and could only be identified as new as the previous photos showed them as such. The identification of such new patches is likely to over-estimate the probability of a new patch occurring as new thalli are more likely to establish on a tree/branch already colonised than an un-colonised tree/branch. In order to accurately estimate population increase, blank DMPs would have to be established. An alternative way of using these data would be to simply look at presence/absence on marked trees. Power calculations could then be carried out as above (Section 6.3.4) to calculate how many individual trees should be monitored. However, the analysis showed that the required sample size is very large and the prevalence very small. Surveys 1 and 2 (Chapter 5) found an average of only around eight occupied trees per 1 ha cell in which the lichen was present. The number of trees per hectare is not known, but could be between 100 and 300; this suggests a prevalence rate of less than 10%. With such a low level of prevalence, a very large number of trees would need to be marked and monitored. On the majority of these the lichen would be absent. It is not sufficient simply to monitor trees on which the lichen was previously present as we would not then know whether or not the number of colonisations is equal to the number of extinctions. The approach of using marked trees is therefore unlikely to be feasible, so we did not proceed any further with power calculations. 6.4

Discussion

The data from the SCM reports provide an example of how population turnover maybe used to conduct a power analysis to assess how many 1 ha cells are required to be monitored. However, there are many limitations with the data used and many assumptions made during this calculation:   



The sites/sub-sites were assumed to be equivalent in size to the 1 ha cells used in the surveys. This is unlikely to be true; The time between repeat visits ranged from 5-30 years, which will influence the rate of turnover recorded; The probability of measurement error (i.e. of a species being recorded as lost from a site when it was actually still present) would be similar for re-surveys of 1 ha squares to that in the SCM reports. When a species was recorded as lost at the site level, there is no indication of how thoroughly the site had been searched for the species or if the level of recorder effort between the two surveys was consistent; and The prevalence of P. norvegica is unknown and was taken to be 25% based on data from Collias Nathais.

49

Changes in any one of these values will alter the results from the power calculation. However, a sample size of 1400 1 ha cells does at least provide an initial estimate of the number of baseline monitoring cells to be established and the results from this can be used to refine the estimate of the number of cells required. It should also be noted that the sample size (1400 cells) is designed to have an 80% chance of detecting a 10% change in population. This is a considerably lower threshold than that required by the European Union (a 1% annual decline in population be detected over 6-year reporting period, Section 3.1). 6.5

Conclusion

Using the limited data available on population turnover for P. norvegica from the SCM reports, it is estimated that baseline surveillance of 1400 1 ha cells needs to be established to have an 80% chance of being able to detect a 10% decline in the population. This assumes a prevalence of 25%, but if the prevalence is 50%, only half that number would be required. Assuming that only 50% of each 1 km square identified as having suitable habitat will actually be suitable, about 30 1 km squares should be monitored to provide the required 1400 1 ha cells for P. norvegica. These squares should be a stratified random sample of the potentially suitable habitat. It is suggested that the 1 km cells are stratified so that they cover the current range of the species from north–south and east–west. All the 1 ha cells within each of the 30 1 km squares that contain suitable habitat should be surveyed. Following the establishment of baseline surveillance for P. norvegica, and a repeated visit, it would be possible to calculate more accurately the number of 1 ha cells that should be monitored to record population change.

50

7.

CONCLUSION AND NEXT STEPS

This work has highlighted the challenges involved with surveillance of priority lichen populations, in particular the requirement for clear aims and objectives, the need for realistic expectations of the level of population change that can be detected, and that surveyor variability is a key issue in the design of any surveillance programme. We have identified a new method of prioritization for the surveillance of Scottish BAP lichens and developed an outline methodology for the surveillance of the more widespread BAP species. The report details the next steps required to implement this surveillance in the field and to develop monitoring methods for the scarce BAP species. 7.1

Prioritization

This work has tested several different methods to prioritise surveillance of BAP lichens. The species rankings developed using the Gauthier et al. (2010) method departed markedly from the rankings obtained using SBC criteria. The Gauthier et al. (2010) method has several advantages over the previously used SBC criteria. In particular it allows an improved focus on those species which are endemic, or for which Scotland hosts internationally important populations. Arguably, where resources are limited, these species should be the priority for conservation and surveillance action in order to achieve the best chances of biodiversity conservation at a global scale. The Gauthier criteria also allow the likelihood of change in different habitat types to be taken into account through the habitat vulnerability criterion. Inclusion of the IUCN categories helps to give more priority to those species which are thought to have undergone rapid population change in recent years. The criteria for this ranking scheme are also easily assessed from readily available data, meaning that the ranking can be easily updated should the BAP list change in future. 7.2

Survey methodology

For the 19 widespread BAP lichen species, a 1 ha grid based surveillance approach using presence/absence data is probably the most pragmatic solution for a long-term surveillance scheme. Presence/absence data are relatively quick to collect, and the results from this study suggest they are less prone to observer error than counts of individuals. The data can be assessed at a range of spatial scales to monitor changes in range, area of occupied habitat and local population size. Range is usually identified as presence/absence within 10 km squares and, as noted above (Section 3.2.2), identification of species range changes (new and lost 10 km squares) is likely to be extremely time consuming and expensive. Unless the species is known to occupy an extremely limited habitat, the returns in terms of information on species population dynamics will probably be extremely limited. Given the limited funds likely to be available for surveillance, we therefore recommend that long-term surveillance is restricted to those 10 km squares where the species is currently known to exist. Where funds allow, this should be complemented with surveys of areas where suitable habitat exists but where the species is not known to be present. Any new sites found could be incorporated into the on-going surveillance programme. Area of occupied habitat is currently assessed in km2 with data recorded at the 10 km scale reported to Europe. We suggest that a smaller scale of measurement is more appropriate to allow trends in species conservation status to be detected before extinctions occur at the 10 km scale. Within each occupied 10 km square, all 1 km squares containing potentially suitable habitat should be identified using maps similar to those developed in Chapter 4. Sample 1 km squares should be selected from among this population. Each selected 1 km square should be subdivided into a 1 ha grid. Each 1 ha should be searched for suitable habitat and the presence/absence of the target species recorded. It is suggested that a fixed 51

search time should be set for each 1 ha to avoid the survey being excessively timeconsuming. A 20 minute time limit appeared to work well for P. norvegica but this was based on expert judgement and further work could test if this time limit is appropriate. When species groups are monitored rather than just single species it may be appropriate to have a longer time limit. The trade-off between collecting data on local population size (number of occupied trees) versus presence/absence data has already been discussed (Section 5.6.4). The results from this study suggest that the best (or least variable) method of measuring local population will be the number of occupied 1 ha cells within a 1 km square. 7.3

Habitat condition monitoring

Alongside measures of population size and area of occupied habitat, information on habitat condition should be recorded to assist in determining the reasons for observed trends. Unlike climate and pollution parameters, habitat condition could be expected to vary on a small scale and could be readily measured at the 1 ha scale. We therefore suggest that habitat condition be measured for all species, regardless of their distribution size. Habitat condition should be recorded for each 1 ha where local population size is assessed, even if the population size is zero. Sets of attributes for qualitatively describing habitat condition relevant to lichen populations have already been developed as part of SCM. In order to allow integration of SCM data and BAP species surveillance, we suggest that these preexisting monitoring attributes are adopted for describing habitat condition during BAP species surveillance. Quantitative measures of habitat condition would be preferable from the point of view of data analysis, particularly for those more generally distributed species where more complex analysis could be undertaken but few simple repeatable measures are suitable. From the point of view of lichen populations, aside from substratum availability, it is probably habitat structure, and particularly the influence of surrounding higher plant structure on levels of light and humidity which have the greatest influence on population performance. For terricolous and saxicolous species, simple quantitative estimates of higher plant and bryophyte cover and sward height may suffice to describe stand structure. For woodland species, simple, quantitative description of stand structure is much more difficult, and the qualitative parameters of SCM may have to suffice. In all cases we strongly recommend that the 1 ha cells are photographed from fixed points at every visit as such photos form a useful reference when assessing changes in habitat condition between survey visits. This should be done from each of the cardinal compass point for each 1 ha (i.e. four photos per cell) and the grid reference recorded to aid relocation and repeated photos to be taken. 7.4

Pollution and climate data

For those species present in more than 20 10 km squares within Scotland, additional information on nitrogen and sulphur deposition, and climate parameters (rainfall, July maximum temperature, January minimum temperature, number of days with rain and number of days of frost) for each monitoring location should be included in the dataset for use in a spatial analysis of population change. The number of species for which such analyses could be carried out is quite limited, but this type of investigation could provide useful information to underpin conservation management. 7.5

Setting up the surveillance scheme

Initial setting up of baseline surveillance will be the most time consuming (and expensive) phase of the programme. Additional time and resources will be needed to ascertain at which of the post-1960 10 km squares the species/habitat is still present and to establish habitat distribution maps as the basis for selecting which 1 km squares to sample. After this initial

52

phase is complete, subsequent surveillance cycles could be expected to require less preparation. 7.6 7.6.1

Next steps Pseudocyphellaria norvegica surveillance

To complete the development of a methodology for surveillance of P. norvegica, information on the number of 1 km squares and 1 ha cells within the 1 km that should be monitored is required. This information will only be available once the power analysis has been repeated using more reliable information on population prevalence at the 1 km and 1 ha scale and on turnover from repeated visits. Initially, based on our very rough estimate of around 1400 1 ha squares, and assuming that only around 50% of the 1 ha squares within a 1 km square may contain suitable habitat, it is suggested that a stratified random sample of 30 1 km squares be established. The samples should be taken from 1 km squares which contain suitable habitat and for which there is a record of the species present at the 10 km square level. The samples should be stratified north–south, east–west along the distribution of the suitable habitat. Within each 1 km square all 1 ha cells with suitable habitat should be surveyed as in Section 7.2. The survey should be repeated after 5 or 10 years and the data used to assess population change and to carry out a power analysis to inform future surveillance. Depending on the results of the power analysis the number of squares monitored could be modified in future cycles of the surveillance programme. 7.6.2

Surveillance of other widespread BAP species

It is suggested that the other 18 widespread BAP species present in 20 or more 10 km squares (Table 2) could be monitored in a similar way to that for P. norvegica. Firstly maps of suitable habitat for these lichens should be developed. Then the methodology outlined in section 7.2 should be trialled. For groups of BAP species, and species that are harder to detect, the length of time given to search each 1 ha cell may need to be increased. The number of 1 ha and 1 km squares required to be monitored will vary between species or species groups depending on their turnover and level of annual variability. Therefore a similar process to that described in Section 7.6.1 will be required. 7.6.3

Surveillance of scarce BAP species

Spatial analysis of the drivers of change in local population size is impossible for those species known only from a single location and is likely to be very limited for those present in more than one but fewer than 20 10 km squares. For very rare species, such as those occupying a single tree or very small area, the size of the sampling unit should be scaled down to one which would enable trends in performance to be measured e.g. small grid cells (5 x 5 cm) within a quadrat on a tree or fence post. Even if present at only a single location, the setting of baseline blank quadrats or recording cells, for example on a different part of the same tree or a neighbouring tree, would allow the detection of an increasing population as well as a declining one. In addition to recording species presence/absence, it would also be valuable to record the species’ reproductive status, e.g. where apothecia / isidia / soredia are present. Further work is required to develop a monitoring protocol for these scarce BAP species. As with this project, the repeatability of the survey method should be tested.

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8.

REFERENCES

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Hovestadt, T. & Nowicki, P. 2008. Process and measurement errors of population size: their mutual effects on precision and bias of estimates for demographic parameters. Biodiversity and Conservation, 17, 3417-3429. IUCN 2001. IUCN Red List categories and criteria. Version 3.1. IUCN Species Survival Commission, IUCN, Gland, Switzerland and Cambridge, United Kingdom.

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Jimenez-Alfaro, B., Colubi, A. & González-Rodríguez, G. 2010. A comparison of pointscoring procedures for species prioritization and allocation of seed collection resources in a mountain region. Biodiversity and Conservation, 19, 3667-3684. JNCC 2005. Common Standards Monitoring Guidance for Bryophytes and Lichens, Version July 2005, ISSN 1743-8160 Online http://jncc.defra.gov.uk/page-2231. Joseph, L.N. & Possingham, H.P. 2008. Grid-based monitoring methods for detecting population declines: sensitivity to spatial scale and consequences of scale correction. Biological Conservation, 141, 1868-1875. Joseph, L.N., Maloney, R.F. & Possingham, H.P. 2009. Optimal allocation of resources among threatened species: a project prioritization protocol. Conservation Biology, 23, 328338. Köhl, M., Traub, B. Paivinen, R 2000.Harmonisation and standardisation in multinationalenvironmental statistics – mission impossible? Environmental Monitoring and Assessment, 63, 361-380. Kull, T., Sammul, M., Kull, K., Lanno, K., Tali, K., Gruber, B., Schmeller, D. & Henle, K. 2008. Necessity and reality of monitoring threatened European vascular plants. Biodiversity and Conservation, 17, 3383-3402. Legg, C.J. & Nagy, L. 2006. Why most conservation is, but need not be, a waste of time. Journal of Environmental Management, 78, 194-199. Lengyel, S., Déri, E., Varga, Z., Horváth, R., Tóthmérész, B., Henry, P.Y., Kobler, A., Kutnar, L., Babij, V., Seliškar, A., Christia, C., Papastergiadou, E., Gruber, B. & Henle, K. 2008. Habitat monitoring in Europe: a description of current practices. Biodiversity and Conservation, 17, 3327-3339. MacKenzie, D.I., Nichols, J.D., Hines, J.E., Knutson, M.G. & Franklin, A.B. (2003). Estimating site occupancy, colonisation, and local extinction when a species is detected imperfectly. Ecology 84: 2200-2207. Martínez, G.J., Planchuelo, A.M. & Fuentes, E. 2006. A numeric index to establish conservation priorities for medicinal plants in the Paravachasca Valley, Córdoba, Argentina. Biodiversity and Conservation, 15, 2457-2475. McCune, B., Dey, J.P., Peck, J.E., Cassell, D., Heiman, K., Will-Wolf, S. & Neitlich, P.N. 1997. Repeatability of community data: species richness versus gradient scores in largescale lichen studies. Bryologist, 100, 40-46. Nielsen, S.E., Haughland, D.L., Bayne, E. & Schieck, J. 2009. Capacity of large-scale, longterm biodiversity monitoring programmes to detect trends in species prevalence. Biodiversity and Conservation, 18, 2961-2978. Palmer, M.A., Hodgetts, N.G., Wiggington, M.J., Ing, B. & Stewart, N.F. 1997. The application to the British flora of the World Conservation Union’s revised red list criteria and the significance of red lists for species conservation. Biological Conservation, 82, 219-226. Regan, H.M., Hierl, L.A., Franklin, J., Deutschman, D.H., Schmalbach, H.L., Windchell, C.S. & Johnson, B.S. 2008. Diversity and Distributions, 14, 462-471.

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Scheidegger, C. & Werth, S. 2009. Conservation strategies for lichens: insights from population biology. Fungal Biology Reviews 23, 55-66. Schmeller, D.S., Bauch, B., Gruber, B., Juškaitis, R., Budrys, E., Babji, V., Lanno, K., Sammul, M., Varga, Z. & Henle, K. 2008a. Determination on conservation priorities in regions with multiple political jurisdictions. Biodiversity and Conservation, 17, 3623-3630. Schmeller, D.S., Gruber, B., Bauch, B., Lanno, K., Budrys, E., Babji, V., Juškaitis, R., Sammul, M., Varga, Z. & Henle, K. 2008b. Determination of national conservation responsibilities for species conservation in regions with multiple political jurisdictions. Biodiversity and Conservation, 17, 3607-3622. Scottish Executive 2004. Scotland’s Biodiversity: It’s in Your Hands. ISBN 0-7559-4120-9 (online at http://www.scotland.gov.uk/Publications/2004/05/19366/37239). United Nations Environment Programme 2002. Report on the Sixth Meeting of the Conference of the Parties to the Convention on Biological Diversity (UNEP/CBD/COP/6/20/Part2) Strategic Plan Decision VI/26 (Convention on Biological Diversity, 2002) p. 319. http://www.biodiv.org/doc/meetings/cop/cop-06/official/cop-06-20part2-en.pdf VSN International 2011. GenStat for Windows 14th Edition. VSN International, Hemel Hempstead, UK. Web page: GenStat.co.uk Woods, R.G. & Coppins, B.J. 2010. A Conservation Evaluation of British Lichens. British Lichen Society, London. Yoccoz, N.G., Nichols, J.D. & Boulinier, T. 2001. Monitoring of biological diversity in space and time. Trends in Ecology and Evolution, 16, 446-453.

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ANNEX 1: PRIORITISATION CRITERIA FOR SCOTTISH BAP SPECIES Scottish species experts have reviewed the actions assigned to the 600+ Scottish species to ensure appropriateness to Scotland. They also prioritised the list into two categories: A = high priority for action in Scotland B = medium/low priority The prioritisation process is detailed below: 1. Identification of importance  Species listed as a UK BAP priority species, and present in Scotland.......................2  Species listed on the Scottish Biodiversity List (SBL)…………………………………..2 2. Status in Scotland  Species occurs regularly and is within its natural range in Scotland ……..………..….3  Species known to be introduced, escaped, or casual and ………..No action required outside its natural range in Scotland. 3. Decline in Scotland  Species assessed through UK BAP reporting as ‘declining’ in Scotland...................A  Evidence that species has declined in Scotland by at least 25% over 25 years, …....A (for example, SBL criterion S5, UKBAP criteria 2/3, or species monitoring data).  Species assessed by a recent source as ‘stable’ or ‘increasing’ in Scotland………....4  Insufficient data to assess trend in Scotland…………………………………………..….4 4. Other strong reasons for prioritising species in Scotland  Species is nationally rare or endemic and under threat in Scotland ……....................A  Species is on the UKBAP list and Scotland holds a significant proportion (>75%)…..A of the UK population.  Other strong reasons for prioritising species in Scotland, for example ……………….A species listed on the Species Action Framework.  None of the above criteria apply or insufficient information to assess

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ANNEX 2: UK DISTRIBUTIONS OF SCOTTISH BAP LICHENS Data downloaded from the NBN on 24th January 2011. All available datasets used to generate maps. Records are divided into pre- and post- 1960. 10 km squares with records for Alectoria ochroleuca in Great Britain and Ireland Includes the following taxa: Alectoria ochroleuca var. citrina, Alectoria ochroleuca forma tenuior, Alectoria ochroleuca forma citrina & Usnea ochroleuca.

© Crown Copyright. All rights reserved NERC 100017897 2004

10 km square legend 1960 to 2011 (top) 1600 to 1959 (bottom)

Note: the most recent (top most) dates will overlay the earlier dates (lower ones) where squares have records in more than one date class.

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10 km squares with records for Anaptychia ciliaris subsp. ciliaris in Great Britain and Ireland Includes the following taxa: Anaptychia ciliaris forma saxicola, Physcia ciliaris, Borrera ciliaris, Lichen ciliaris, Physcia ciliaris var. saxicola & Parmelia ciliaris.

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10 km square legend 1960 to 2011 (top) 1600 to 1959 (bottom)

Note: the most recent (top most) dates will overlay the earlier dates (lower ones) where squares have records in more than one date class.

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10 km squares with records for Arthonia atlantica in Great Britain and Ireland. Includes the following taxa: Arthonia dendritica, Enterographa dendritica, Stigmatidium dendriticum, Arthonia atlantica, Arthonia atlantica var. positiva, Arthonia atlantica var. atlantica & Arthonia atlantica var. positiva.

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10 km square legend 1960 to 2011 (top) 1600 to 1959 (bottom)

Note: the most recent (top most) dates will overlay the earlier dates (lower ones) where squares have records in more than one date class.

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10 km squares with records for Arthonia cohabitans in Great Britain and Ireland

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10 km square legend 1960 to 2011 (top) 1600 to 1959 (bottom)

Note: the most recent (top most) dates will overlay the earlier dates (lower ones) where squares have records in more than one date class.

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10 km squares with records for Arthonia invadens in Great Britain and Ireland

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10 km square legend 1960 to 2011 (top) 1600 to 1959 (bottom)

Note: the most recent (top most) dates will overlay the earlier dates (lower ones) where squares have records in more than one date class.

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10 km squares with records for Arthonia patellulata in Great Britain and Ireland

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10 km square legend 1960 to 2011 (top) 1600 to 1959 (bottom)

Note: the most recent (top most) dates will overlay the earlier dates (lower ones) where squares have records in more than one date class.

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10 km squares with records for Arthothelium dictyosporum in Great Britain and Ireland Includes the following taxa: Arthothelium ilicinum var. dictyosporum & Arthothelium ilicinum var. dictyosporum.

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10 km square legend 1960 to 2011 (top) 1600 to 1959 (bottom)

Note: the most recent (top most) dates will overlay the earlier dates (lower ones) where squares have records in more than one date class.

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10 km squares with records for Arthothelium macounii in Great Britain and Ireland Includes the following taxa: Arthonia macounii, Arthothelium ilicinum var. reagens, Arthothelium reagens & Arthothelium ilicinum var. reagens.

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10 km square legend 1960 to 2011 (top) 1600 to 1959 (bottom)

Note: the most recent (top most) dates will overlay the earlier dates (lower ones) where squares have records in more than one date class.

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10 km squares with records for Aspicilia melanaspis in Great Britain and Ireland Includes the following taxa: Lecanora melanaspis, Lobothallia melanaspis, Parmelia melanaspis, Squamaria melanaspis, Lobothallia melanaspis & Parmelia melanaspis.

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10 km square legend 1960 to 2011 (top) 1600 to 1959 (bottom)

Note: the most recent (top most) dates will overlay the earlier dates (lower ones) where squares have records in more than one date class.

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10 km squares with records for Bacidia circumspecta in Great Britain and Ireland Includes the following taxa: Bacidia quercicola, Bacidia bacillifera var. circumspecta & Lecidea muscorum var. quercicola.

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10 km square legend 1960 to 2011 (top) 1600 to 1959 (bottom)

Note: the most recent (top most) dates will overlay the earlier dates (lower ones) where squares have records in more than one date class.

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10 km squares with records for Bacidia incompta in Great Britain and Ireland Includes the following taxa: Bacidia incompta, Bilimbia incompta & Lecidea incompta.

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10 km square legend 1960 to 2011 (top) 1600 to 1959 (bottom)

Note: the most recent (top most) dates will overlay the earlier dates (lower ones) where squares have records in more than one date class.

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10 km squares with records for Bacidia subincompta in Great Britain and Ireland Includes the following taxa: Bacidia affinis, Bacidia atrosanguinea sensu auct. brit., Lecidea subincompta & Secoliga atrosanguinea var. affinis.

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10 km square legend 1960 to 2011 (top) 1600 to 1959 (bottom)

Note: the most recent (top most) dates will overlay the earlier dates (lower ones) where squares have records in more than one date class.

69

10 km squares with records for Biatoridium monasteriense in Great Britain and Ireland Includes the following taxa: Biatorella monasteriensis & Biatorella resinae sensu Mudd p.p.

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10 km square legend 1960 to 2011 (top) 1600 to 1959 (bottom)

Note: the most recent (top most) dates will overlay the earlier dates (lower ones) where squares have records in more than one date class.

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10 km squares with records for Brodoa intestiniformis in Great Britain and Ireland Includes the following taxa: Hypogymnia encausta, Parmelia encausta, Parmelia intestiniformis, Hypogymnia intestiniformis, Lichen encaustus & Lichen intestiniformis.

© Crown Copyright. All rights reserved NERC 100017897 2004

10 km square legend 1960 to 2011 (top) 1600 to 1959 (bottom)

Note: the most recent (top most) dates will overlay the earlier dates (lower ones) where squares have records in more than one date class.

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10 km squares with records for Bryoria furcellata (Forked Hair-lichen) in Great Britain and Ireland Includes the following taxa: Alectoria nidulifera, Cetraria furcellata & Forked Hair-lichen.

© Crown Copyright. All rights reserved NERC 100017897 2004

10 km square legend 1960 to 2011 (top) 1600 to 1959 (bottom)

Note: the most recent (top most) dates will overlay the earlier dates (lower ones) where squares have records in more than one date class.

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10 km squares with records for Buellia violaceofusca in Great Britain and Ireland

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10 km square legend 1960 to 2011 (top) 1600 to 1959 (bottom)

Note: the most recent (top most) dates will overlay the earlier dates (lower ones) where squares have records in more than one date class.

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10 km squares with records for Calicium corynellum in Great Britain and Ireland Includes the following taxa: Calicium corynellum var. subsessile, Caliciella corynella var. subsessile & Lichen corynellus.

© Crown Copyright. All rights reserved NERC 100017897 2004

10 km square legend 1960 to 2011 (top) 1600 to 1959 (bottom)

Note: the most recent (top most) dates will overlay the earlier dates (lower ones) where squares have records in more than one date class.

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10 km squares with records for Calicium diploellum in Great Britain and Ireland

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10 km square legend 1960 to 2011 (top) 1600 to 1959 (bottom)

Note: the most recent (top most) dates will overlay the earlier dates (lower ones) where squares have records in more than one date class.

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10 km squares with records for Caloplaca ahtii in Great Britain and Ireland

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10 km square legend 1960 to 2011 (top) 1600 to 1959 (bottom)

Note: the most recent (top most) dates will overlay the earlier dates (lower ones) where squares have records in more than one date class.

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10 km squares with records for Caloplaca caesiorufella in Great Britain and Ireland Includes the following taxa: Lecanora caesiorufella.

© Crown Copyright. All rights reserved NERC 100017897 2004

10 km square legend 1960 to 2011 (top) 1600 to 1959 (bottom)

Note: the most recent (top most) dates will overlay the earlier dates (lower ones) where squares have records in more than one date class.

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10 km squares with records for Caloplaca flavorubescens in Great Britain and Ireland Includes the following taxa: Caloplaca aurantiaca sensu auct. p.p., Placodium aurantiacum sensu auct. p.p., Lecidea aurantiaca sensu auct. & Lichen flavorubescens.

© Crown Copyright. All rights reserved NERC 100017897 2004

10 km square legend 1960 to 2011 (top) 1600 to 1959 (bottom)

Note: the most recent (top most) dates will overlay the earlier dates (lower ones) where squares have records in more than one date class.

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10 km squares with records for Caloplaca lucifuga in Great Britain and Ireland

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10 km square legend 1960 to 2011 (top) 1600 to 1959 (bottom)

Note: the most recent (top most) dates will overlay the earlier dates (lower ones) where squares have records in more than one date class.

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10 km squares with records for Caloplaca luteoalba (Orange-fruited Elm-lichen) in Great Britain and Ireland Includes the following taxa: Callopisma luteoalbum, Placodium luteoalbum, Lecidea ulmicola, Lichen luteoalbus, Patellaria ulmicola & Orange-fruited Elm-lichen.

© Crown Copyright. All rights reserved NERC 100017897 2004

10 km square legend 1960 to 2011 (top) 1600 to 1959 (bottom)

Note: the most recent (top most) dates will overlay the earlier dates (lower ones) where squares have records in more than one date class.

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10 km squares with records for Caloplaca virescens in Great Britain and Ireland Includes the following taxa: Lepraria virescens.

© Crown Copyright. All rights reserved NERC 100017897 2004

10 km square legend 1960 to 2011 (top) 1600 to 1959 (bottom)

Note: the most recent (top most) dates will overlay the earlier dates (lower ones) where squares have records in more than one date class.

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10 km squares with records for Candelariella superdistans in Great Britain and Ireland Includes the following taxa: Lecanora superdistans.

© Crown Copyright. All rights reserved NERC 100017897 2004

10 km square legend 1960 to 2011 (top) 1600 to 1959 (bottom)

Note: the most recent (top most) dates will overlay the earlier dates (lower ones) where squares have records in more than one date class.

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10 km squares with records for Catapyrenium psoromoides (Tree Catapyrenium) in Great Britain and Ireland Includes the following taxa: Dermatocarpon psoromoides, Verrucaria psoromoides, Physalospora psoromoides, Endocarpon psoromoides, Guignardia psoromoides, Laestadia psoromoides, Physalospora psoromoides, Tree Psoromoides & Tree Catapyrenium.

© Crown Copyright. All rights reserved NERC 100017897 2004

10 km square legend 1960 to 2011 (top) 1600 to 1959 (bottom)

Note: the most recent (top most) dates will overlay the earlier dates (lower ones) where squares have records in more than one date class.

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10 km squares with records for Catillaria alba in Great Britain and Ireland

© Crown Copyright. All rights reserved NERC 100017897 2004

10 km square legend 1960 to 2011 (top) 1600 to 1959 (bottom)

Note: the most recent (top most) dates will overlay the earlier dates (lower ones) where squares have records in more than one date class.

84

10 km squares with records for Chaenotheca gracilenta in Great Britain and Ireland Includes the following taxa: Calicium gracilentum, Cybebe gracilenta, Coniocybe gracilenta & Coniocybe gracilenta.

© Crown Copyright. All rights reserved NERC 100017897 2004

10 km square legend 1960 to 2011 (top) 1600 to 1960 (bottom)

Note: the most recent (top most) dates will overlay the earlier dates (lower ones) where squares have records in more than one date class.

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10 km squares with records for Chaenotheca laevigata in Great Britain and Ireland

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10 km square legend 1960 to 2011 (top) 1600 to 1959 (bottom)

Note: the most recent (top most) dates will overlay the earlier dates (lower ones) where squares have records in more than one date class.

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10 km squares with records for Cladonia botrytes (Stump Lichen) in Great Britain and Ireland Includes the following taxa: Lichen botrytes & Stump Lichen.

© Crown Copyright. All rights reserved NERC 100017897 2004

10 km square legend 1960 to 2011 (top) 1600 to 1959 (bottom)

Note: the most recent (top most) dates will overlay the earlier dates (lower ones) where squares have records in more than one date class.

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10 km squares with records for Cladonia peziziformis in Great Britain and Ireland Includes the following taxa: Cladonia leptophylla, Lichen peziziformis, Cladonia capitata & Lichen capitatus.

© Crown Copyright. All rights reserved NERC 100017897 2004

10 km square legend 1960 to 2011 (top) 1600 to 1959 (bottom)

Note: the most recent (top most) dates will overlay the earlier dates (lower ones) where squares have records in more than one date class.

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10 km squares with records for Collema dichotomum (River Jelly Lichen) in Great Britain and Ireland Includes the following taxa: Leptogium cataclystum, Leptogium fluviatile, Tremella dichotoma, Collema fluviatile, Leptogium rivulare auct. brit. non (Ach.) Mont, Enchylium fluviale, Leptogium rivulare sensu auct. brit., Lichen fluviatilis & River Jelly Lichen.

© Crown Copyright. All rights reserved NERC 100017897 2004

10 km square legend 1960 to 2011 (top) 1600 to 1959 (bottom)

Note: the most recent (top most) dates will overlay the earlier dates (lower ones) where squares have records in more than one date class.

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10 km squares with records for Collema fasciculare in Great Britain and Ireland Includes the following taxa: Synechoblastus aggregatus, Synechoblastus ascaridosporus, Synechoblastus fascicularis, Collema aggregatum sensu auct., Collema fasciculare var. aggregatum, Enchylium fasciculare, Enchylium fasciculare var. aggregatum, Lethagrium ascaridosporum, Lichen fascicularis & Synechoblastus aggregatus.

© Crown Copyright. All rights reserved NERC 100017897 2004

10 km square legend 1960 to 2011 (top) 1600 to 1959 (bottom)

Note: the most recent (top most) dates will overlay the earlier dates (lower ones) where squares have records in more than one date class.

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10 km squares with records for Collema fragile in Great Britain and Ireland Includes the following taxa: Leptogium fragile & Collemodium fragile.

© Crown Copyright. All rights reserved NERC 100017897 2004

10 km square legend 1960 to 2011 (top) 1600 to 1959 (bottom)

Note: the most recent (top most) dates will overlay the earlier dates (lower ones) where squares have records in more than one date class.

91

10 km squares with records for Collema fragrans in Great Britain and Ireland Includes the following taxa: Collema terrulentum, Leptogium fragrans & Leptogium microphyllum.

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10 km square legend 1960 to 2011 (top) 1600 to 1959 (bottom)

Note: the most recent (top most) dates will overlay the earlier dates (lower ones) where squares have records in more than one date class.

92

10 km squares with records for Cyphelium trachylioides in Great Britain and Ireland Includes the following taxa: Cyphelium trachylioides & Arthonia trachylioides.

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10 km square legend 1960 to 2011 (top) 1600 to 1959 (bottom)

Note: the most recent (top most) dates will overlay the earlier dates (lower ones) where squares have records in more than one date class.

93

10 km squares with records for Diplotomma pharcidium in Great Britain and Ireland Includes the following taxa: Buellia geophila auct. brit., Buellia geophila sensu auct. brit., non (Flörke ex Sommerf.) Lynge, Buellia pharcidia & Lecanora pharcidia.

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10 km square legend 1960 to 2011 (top) 1600 to 1959 (bottom)

Note: the most recent (top most) dates will overlay the earlier dates (lower ones) where squares have records in more than one date class.

94

10 km squares with records for Fuscopannaria ignobilis (Caledonian Pannaria) in Great Britain and Ireland Includes the following taxa: Pannaria servitiana, Pannaria ignobilis (Caledonian Pannaria) & Caledonian Pannaria.

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10 km square legend 1960 to 2011 (top) 1600 to 1959 (bottom)

Note: the most recent (top most) dates will overlay the earlier dates (lower ones) where squares have records in more than one date class.

95

10 km squares with records for Fuscopannaria sampaiana in Great Britain and Ireland Includes the following taxa: Pannaria sampaiana.

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10 km square legend 1960 to 2011 (top) 1600 to 1959 (bottom)

Note: the most recent (top most) dates will overlay the earlier dates (lower ones) where squares have records in more than one date class.

96

10 km squares with records for Gomphillus calycioides in Great Britain and Ireland Includes the following taxa: Gomphillus calycioides forma microcephalus, Baeomyces calycioides & Baeomyces microcephalus.

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10 km square legend 1960 to 2011 (top) 1600 to 1959 (bottom)

Note: the most recent (top most) dates will overlay the earlier dates (lower ones) where squares have records in more than one date class.

97

10 km squares with records for Graphis alboscripta in Great Britain and Ireland Includes the following taxa: Fissurina alboscripta.

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10 km square legend 1960 to 2011 (top) 1600 to 1959 (bottom)

Note: the most recent (top most) dates will overlay the earlier dates (lower ones) where squares have records in more than one date class.

98

10 km squares with records for Gyalecta ulmi (Elm Gyalecta) in Great Britain and Ireland Includes the following taxa: Gyalecta rubra, Phialopsis rubra, Lichen ulmi, Patellaria rubra & Elm Gyalecta.

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10 km square legend 1960 to 2011 (top) 1600 to 1959 (bottom)

Note: the most recent (top most) dates will overlay the earlier dates (lower ones) where squares have records in more than one date class.

99

10 km squares with records for Gyalidea roseola in Great Britain and Ireland Includes the following taxa: Gyalecta roseola.

© Crown Copyright. All rights reserved NERC 100017897 2004

10 km square legend 1960 to 2011 (top) 1600 to 1959 (bottom)

Note: the most recent (top most) dates will overlay the earlier dates (lower ones) where squares have records in more than one date class.

100

10 km squares with records for Hypogymnia vittata in Great Britain and Ireland Includes the following taxa: Parmelia vittata & Parmelia physodes var. vittata.

© Crown Copyright. All rights reserved NERC 100017897 2004

10 km square legend 1960 to 2011 (top) 1600 to 1959 (bottom)

Note: the most recent (top most) dates will overlay the earlier dates (lower ones) where squares have records in more than one date class.

101

10 km squares with records for Lecania chlorotiza in Great Britain and Ireland Includes the following taxa: Catillaria chlorotiza, Biatorina fallax sensu A.L. Smith, non (Hepp) A.L. Sm., Catillaria chlorotiza & Lecidea chlorotiza.

© Crown Copyright. All rights reserved NERC 100017897 2004

10 km square legend 1960 to 2011 (top) 1600 to 1959 (bottom)

Note: the most recent (top most) dates will overlay the earlier dates (lower ones) where squares have records in more than one date class.

102

10 km squares with records for Lecanographa amylacea in Great Britain and Ireland Includes the following taxa: Lecanactis illecebrosa, Lichen amylaceus, Lecanactis amylacea & Opegrapha illecebrosa.

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10 km square legend 1960 to 2011 (top) 1600 to 1959 (bottom)

Note: the most recent (top most) dates will overlay the earlier dates (lower ones) where squares have records in more than one date class.

103

10 km squares with records for Lecanora achariana (Tarn Lecanora) in Great Britain and Ireland Includes the following taxa: Squamaria cartilaginea sensu auct. brit., Protoparmeliopsis achariana & Tarn Lecanora.

© Crown Copyright. All rights reserved NERC 100017897 2004

10 km square legend 1960 to 2011 (top) 1600 to 1959 (bottom)

Note: the most recent (top most) dates will overlay the earlier dates (lower ones) where squares have records in more than one date class.

104

10 km squares with records for Lecanora cinereofusca in Great Britain and Ireland

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10 km square legend 1960 to 2011 (top) 1600 to 1959 (bottom)

Note: the most recent (top most) dates will overlay the earlier dates (lower ones) where squares have records in more than one date class.

105

10 km squares with records for Lecanora quercicola in Great Britain and Ireland

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10 km square legend 1960 to 2011 (top) 1600 to 1959 (bottom)

Note: the most recent (top most) dates will overlay the earlier dates (lower ones) where squares have records in more than one date class.

106

10 km squares with records for Lecidea erythrophaea in Great Britain and Ireland Includes the following taxa: Biatora tenebricosa sensu auct. brit. p.p., Lecidea minuta sensu auct. p.p., Biatora hyalinella & Lecidea hyalinella.

© Crown Copyright. All rights reserved NERC 100017897 2004

10 km square legend 1960 to 2011 (top) 1600 to 1959 (bottom)

Note: the most recent (top most) dates will overlay the earlier dates (lower ones) where squares have records in more than one date class.

107

10 km squares with records for Leptogium brebissonii in Great Britain and Ireland Includes the following taxa: Collema ruginosum, Leptogium ruginosum, Leptogium chloromelum & Lichen chloromelus.

© Crown Copyright. All rights reserved NERC 100017897 2004

10 km square legend 1960 to 2011 (top) 1600 to 1959 (bottom)

Note: the most recent (top most) dates will overlay the earlier dates (lower ones) where squares have records in more than one date class.

108

10 km squares with records for Leptogium cochleatum in Great Britain and Ireland Includes the following taxa: Leptogium azureum auct. brit., non (Swartz) Mont., Leptogium tremelloides auct. brit., non (Linnaeusfil.) Gray, Leptogium azureum auct. brit., Leptogium azureum sensu auct. brit., Collema tremelloides sensu auct. brit. p.p., Lepraria cochleatum, Leptogium tremelloides, Lichen cochleatus & Lichen tremelloides.

© Crown Copyright. All rights reserved NERC 100017897 2004

10 km square legend 1960 to 2011 (top) 1600 to 1959 (bottom)

Note: the most recent (top most) dates will overlay the earlier dates (lower ones) where squares have records in more than one date class.

109

10 km squares with records for Leptogium hibernicum in Great Britain and Ireland

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10 km square legend 1960 to 2011 (top) 1600 to 1959 (bottom)

Note: the most recent (top most) dates will overlay the earlier dates (lower ones) where squares have records in more than one date class.

110

10 km squares with records for Leptogium saturninum in Great Britain and Ireland Includes the following taxa: Lichen saturninus.

© Crown Copyright. All rights reserved NERC 100017897 2004

10 km square legend 1960 to 2011 (top) 1600 to 1959 (bottom)

Note: the most recent (top most) dates will overlay the earlier dates (lower ones) where squares have records in more than one date class.

111

10 km squares with records for Megalospora tuberculosa in Great Britain and Ireland Includes the following taxa: Bombyliospora incana, Lecidea tuberculosa, Megalospora pachycarpa, Bombyliospora pachycarpa auct., non (Delise ex Duby) Massal., Bombyliospora pachycarpa auct., Bombyliospora pachycarpa sensu auct., Lecidea incana sensu auct. brit. 19th C, Lecidea pachycarpa, Lichen incanus sensu Smith (1807) & Patellaria pachycarpa.

© Crown Copyright. All rights reserved NERC 100017897 2004

10 km square legend 1960 to 2011 (top) 1600 to 1959 (bottom)

Note: the most recent (top most) dates will overlay the earlier dates (lower ones) where squares have records in more than one date class.

112

10 km squares with records for Melanelia subargentifera in Great Britain and Ireland Includes the following taxa: Parmelia subargentifera & Melanelixia subargentifera.

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10 km square legend 1960 to 2011 (top) 1600 to 1959 (bottom)

Note: the most recent (top most) dates will overlay the earlier dates (lower ones) where squares have records in more than one date class.

113

10 km squares with records for Nephroma arcticum (Arctic Kidney-lichen) in Great Britain and Ireland Includes the following taxa: Lichen arcticus & Arctic Kidney-lichen.

© Crown Copyright. All rights reserved NERC 100017897 2004

10 km square legend 1960 to 2011 (top) 1600 to 1959 (bottom)

Note: the most recent (top most) dates will overlay the earlier dates (lower ones) where squares have records in more than one date class.

114

10 km squares with records for Parmeliella testacea in Great Britain and Ireland

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10 km square legend 1960 to 2011 (top) 1600 to 1959 (bottom)

Note: the most recent (top most) dates will overlay the earlier dates (lower ones) where squares have records in more than one date class.

115

10 km squares with records for Peltigera lepidophora (Ear-lobed Dog-lichen) in Great Britain and Ireland Includes the following taxa: Peltigera canina var. lepidophora, Peltigera rufescens var. lepidophora & Ear-lobed Dog-lichen.

© Crown Copyright. All rights reserved NERC 100017897 2004

10 km square legend 1960 to 2011 (top) 1600 to 1959 (bottom)

Note: the most recent (top most) dates will overlay the earlier dates (lower ones) where squares have records in more than one date class.

116

10 km squares with records for Peltigera malacea (Matt Felt Lichen) in Great Britain and Ireland Includes the following taxa: Peltidea malacea & Matt Felt Lichen (Matt Felt Lichen).

© Crown Copyright. All rights reserved NERC 100017897 2004

10 km square legend 1960 to 2011 (top) 1600 to 1959 (bottom)

Note: the most recent (top most) dates will overlay the earlier dates (lower ones) where squares have records in more than one date class.

117

10 km squares with records for Peltigera venosa (Pixie Gowns Lichen) in Great Britain and Ireland Includes the following taxa: Peltidea venosa, Lichen venosus & Pixie Gowns Lichen (Pixie Gowns Lichen).

© Crown Copyright. All rights reserved NERC 100017897 2004

10 km square legend 1960 to 2011 (top) 1600 to 1959 (bottom)

Note: the most recent (top most) dates will overlay the earlier dates (lower ones) where squares have records in more than one date class.

118

10 km squares with records for Pertusaria velata in Great Britain and Ireland Includes the following taxa: Parmelia velata & Variolaria velata.

© Crown Copyright. All rights reserved NERC 100017897 2004

10 km square legend 1960 to 2011 (top) 1600 to 1959 (bottom)

Note: the most recent (top most) dates will overlay the earlier dates (lower ones) where squares have records in more than one date class.

119

10 km squares with records for Phaeophyscia endococcina in Great Britain and Ireland Includes the following taxa: Parmelia endococcinea.

© Crown Copyright. All rights reserved NERC 100017897 2004

10 km square legend 1960 to 2011 (top) 1600 to 1959 (bottom)

Note: the most recent (top most) dates will overlay the earlier dates (lower ones) where squares have records in more than one date class.

120

10 km squares with records for Poeltinula cerebrina in Great Britain and Ireland Includes the following taxa: Lithographa cerebrina, Melanospora cerebrina, Opegrapha cerebrina & Encephalographa cerebrina.

© Crown Copyright. All rights reserved NERC 100017897 2004

10 km square legend 1960 to 2011 (top) 1600 to 1959 (bottom)

Note: the most recent (top most) dates will overlay the earlier dates (lower ones) where squares have records in more than one date class.

121

10 km squares with records for Polychidium dendriscum in Great Britain and Ireland Includes the following taxa: Ephebe byssoides, Leptogidium dendriscum, Leptogidium moorei sensu auct., non Nyl. & Leptogium moorei.

© Crown Copyright. All rights reserved NERC 100017897 2004

10 km square legend 1960 to 2011 (top) 1600 to 1959 (bottom)

Note: the most recent (top most) dates will overlay the earlier dates (lower ones) where squares have records in more than one date class.

122

10 km squares with records for Porina hibernica in Great Britain and Ireland Includes the following taxa: Zamenhofia hibernica & Porina hibernica.

© Crown Copyright. All rights reserved NERC 100017897 2004

10 km square legend 1960 to 2011 (top) 1600 to 1959 (bottom)

Note: the most recent (top most) dates will overlay the earlier dates (lower ones) where squares have records in more than one date class.

123

10 km squares with records for Porina sudetica in Great Britain and Ireland Includes the following taxa: Verrucaria sudetica.

© Crown Copyright. All rights reserved NERC 100017897 2004

10 km square legend 1960 to 2011 (top) 1600 to 1959 (bottom)

Note: the most recent (top most) dates will overlay the earlier dates (lower ones) where squares have records in more than one date class.

124

10 km squares with records for Pseudocyphellaria intricata in Great Britain and Ireland Includes the following taxa: Cyanisticta normalis, Sticta intricata var. thouarsii, Stictina intricata var. thouarsii, Pseudocyphellaria thouarsii & Sticta intricata.

© Crown Copyright. All rights reserved NERC 100017897 2004

10 km square legend 1960 to 2011 (top) 1600 to 1959 (bottom)

Note: the most recent (top most) dates will overlay the earlier dates (lower ones) where squares have records in more than one date class.

125

10 km squares with records for Pseudocyphellaria lacerata (Ragged Pseudocyphellaria) in Great Britain and Ireland Includes the following taxa: Ragged Pseudocyphellaria.

© Crown Copyright. All rights reserved NERC 100017897 2004

10 km square legend 1960 to 2011 (top) 1600 to 1959 (bottom)

Note: the most recent (top most) dates will overlay the earlier dates (lower ones) where squares have records in more than one date class.

126

10 km squares with records for Pseudocyphellaria norvegica in Great Britain and Ireland Includes the following taxa: Cyanisticta aberrans, Cyanisticta ecyphellata, Pseudocyphellaria thouarsii auct. p.p., Pseudocyphellaria thouarsii sensu auct. brit. p.p. pre-1978, Cyanisticta norvegica, Sticta intricata var. thouarsii sensu auct. p.p., Sticta thouarsii forma aberrans, Stictina intricata var. thouarsii sensu auct. p.p., Stictina thouarsii var. ecyphellata & Sticta thouarsii sensu auct. brit. p.p. pre-1978.

© Crown Copyright. All rights reserved NERC 100017897 2004

10 km square legend 1960 to 2011 (top) 1600 to 1959 (bottom)

Note: the most recent (top most) dates will overlay the earlier dates (lower ones) where squares have records in more than one date class.

127

10 km squares with records for Pyrenula dermatodes in Great Britain and Ireland Includes the following taxa: Verrucaria achroopora, Verrucaria glabratula & Verrucaria dermatodes.

© Crown Copyright. All rights reserved NERC 100017897 2004

10 km square legend 1960 to 2011 (top) 1600 to 1960 (bottom)

Note: the most recent (top most) dates will overlay the earlier dates (lower ones) where squares have records in more than one date class.

128

10 km squares with records for Pyrenula hibernica in Great Britain and Ireland Includes the following taxa: Anthracothecium hibernicum, Pyrenula chilensis, Verrucaria pyrenuloides var. hibernica, Parmentaria chilensis, Anthracothecium pyrenuloides sensu auct. brit., non (Mont.) Müll. Arg., Anthracothecium pyrenuloides sensu auct. brit., Polyblastia hibernica & Verrucaria hibernica.

© Crown Copyright. All rights reserved NERC 100017897 2004

10 km square legend 1960 to 2011 (top) 1600 to 1960 (bottom)

Note: the most recent (top most) dates will overlay the earlier dates (lower ones) where squares have records in more than one date class.

129

10 km squares with records for Ramonia chrysophaea in Great Britain and Ireland Includes the following taxa: Ocellaria chrysophaea, Peziza chrysophaea, Propolis chrysophaea & Stictis chrysophaea.

© Crown Copyright. All rights reserved NERC 100017897 2004

10 km square legend 1960 to 2011 (top) 1600 to 1959 (bottom)

Note: the most recent (top most) dates will overlay the earlier dates (lower ones) where squares have records in more than one date class.

130

10 km squares with records for Ramonia dictyospora in Great Britain and Ireland

© Crown Copyright. All rights reserved NERC 100017897 2004

10 km square legend 1960 to 2011 (top) 1600 to 1959 (bottom)

Note: the most recent (top most) dates will overlay the earlier dates (lower ones) where squares have records in more than one date class.

131

10 km squares with records for Rinodina degeliana in Great Britain and Ireland

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10 km square legend 1960 to 2011 (top) 1600 to 1959 (bottom)

Note: the most recent (top most) dates will overlay the earlier dates (lower ones) where squares have records in more than one date class.

132

10 km squares with records for Rinodina isidioides in Great Britain and Ireland Includes the following taxa: Borrera isidioides, Lecanora isidioides & Parmelia isidioides.

© Crown Copyright. All rights reserved NERC 100017897 2004

10 km square legend 1960 to 2011 (top) 1600 to 1959 (bottom)

Note: the most recent (top most) dates will overlay the earlier dates (lower ones) where squares have records in more than one date class.

133

10 km squares with records for Schismatomma graphidioides in Great Britain and Ireland Includes the following taxa: Chiodecton graphidioides, Enterographa graphidioides, Platygrapha rimatum, Schismatomma farinosum, Schismatomma rimatum, Platygrapha periclea sensu auct. brit., Platygrapha rimata sensu auct. brit., Lecidea farinosa, Lichen pericleus, Schismatomma abietinum, Schismatomma pericleum & Verrucaria abietina.

© Crown Copyright. All rights reserved NERC 100017897 2004

10 km square legend 1960 to 2011 (top) 1600 to 1959 (bottom)

Note: the most recent (top most) dates will overlay the earlier dates (lower ones) where squares have records in more than one date class.

134

10 km squares with records for Sclerophora pallida in Great Britain and Ireland Includes the following taxa: Coniocybe pallida var. coniophaea, Roesleria hypogaea, Trichia nivea, Roesleria pallida, Coniocybe pallida, Pilacre pallida, Sclerophora nivea, Sclerophora nivea non Trichia nivea O.F. Müll., 1778, Calicium cantherellum sensu Sm., Calicium pallidum, Calicium peronellum sensu auct. brit., non (Ach.) Ach., Coniocybe coniophaea, Phacotrum cantherellum sensu Gray & non (Ach.) Gray.

© Crown Copyright. All rights reserved NERC 100017897 2004

10 km square legend 1960 to 2011 (top) 1600 to 1959 (bottom)

Note: the most recent (top most) dates will overlay the earlier dates (lower ones) where squares have records in more than one date class.

135

10 km squares with records for Stereocaulon delisei in Great Britain and Ireland

© Crown Copyright. All rights reserved NERC 100017897 2004

10 km square legend 1960 to 2011 (top) 1600 to 1959 (bottom)

Note: the most recent (top most) dates will overlay the earlier dates (lower ones) where squares have records in more than one date class.

136

10 km squares with records for Stereocaulon symphycheilum in Great Britain and Ireland

© Crown Copyright. All rights reserved NERC 100017897 2004

10 km square legend 1960 to 2011 (top) 1600 to 1959 (bottom)

Note: the most recent (top most) dates will overlay the earlier dates (lower ones) where squares have records in more than one date class.

137

10 km squares with records for Sticta canariensis in Great Britain and Ireland

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10 km square legend 1960 to 2011 (top) 1600 to 1959 (bottom)

Note: the most recent (top most) dates will overlay the earlier dates (lower ones) where squares have records in more than one date class.

138

10 km squares with records for Synalissa symphorea in Great Britain and Ireland Includes the following taxa: Collema ramulosum, Collema symphoreum, Lichen symphoreus & Synalissa ramulosa.

© Crown Copyright. All rights reserved NERC 100017897 2004

10 km square legend 1960 to 2011 (top) 1600 to 1959 (bottom)

Note: the most recent (top most) dates will overlay the earlier dates (lower ones) where squares have records in more than one date class.

139

10 km squares with records for Thelenella modesta (Warty Wax-lichen) in Great Britain and Ireland Includes the following taxa: Microglaena modesta, Verrucaria modesta & Warty Wax-lichen.

© Crown Copyright. All rights reserved NERC 100017897 2004

10 km square legend 1960 to 2011 (top) 1600 to 1959 (bottom)

Note: the most recent (top most) dates will overlay the earlier dates (lower ones) where squares have records in more than one date class.

140

10 km squares with records for Toninia sedifolia in Great Britain and Ireland Includes the following taxa: Lichen sedifolius, Toninia coeruleonigricans, Toninia caeruleonigricans auct., Biatorina caeruleonigricans sensu auct., Lichen caeruleonigricans sensu auct., Toninia caeruleonigricans sensu auct. & Thalloidima caeruleonigricans sensu auct.

© Crown Copyright. All rights reserved NERC 100017897 2004

10 km square legend 1960 to 2011 (top) 1600 to 1959 (bottom)

Note: the most recent (top most) dates will overlay the earlier dates (lower ones) where squares have records in more than one date class.

141

10 km squares with records for Umbilicaria spodochroa in Great Britain and Ireland Includes the following taxa: Gyrophora spodochroa.

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10 km square legend 1960 to 2011 (top) 1600 to 1959 (bottom)

Note: the most recent (top most) dates will overlay the earlier dates (lower ones) where squares have records in more than one date class.

142

10 km squares with records for Usnea florida (Witches' Whiskers Lichen) in Great Britain and Ireland Includes the following taxa: Lichen floridus & Witches' Whiskers Lichen (Witches' Whiskers Lichen).

© Crown Copyright. All rights reserved NERC 100017897 2004

10 km square legend 1960 to 2011 (top) 1600 to 1959 (bottom)

Note: the most recent (top most) dates will overlay the earlier dates (lower ones) where squares have records in more than one date class.

143

10 km squares with records for Vulpicida pinastri in Great Britain and Ireland Includes the following taxa: Lichen pinastri, Platysma pinastri & Cetraria pinastri.

© Crown Copyright. All rights reserved NERC 100017897 2004

10 km square legend 1960 to 2011 (top) 1600 to 1959 (bottom)

Note: the most recent (top most) dates will overlay the earlier dates (lower ones) where squares have records in more than one date class.

144

10 km squares with records for Wadeana dendrographa in Great Britain and Ireland Includes the following taxa: Lithographa dendrographa.

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10 km square legend 1960 to 2011 (top) 1600 to 1959 (bottom)

Note: the most recent (top most) dates will overlay the earlier dates (lower ones) where squares have records in more than one date class.

145

10 km squares with records for Wadeana minuta in Great Britain and Ireland

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10 km square legend 1960 to 2011 (top) 1600 to 1959 (bottom)

Note: the most recent (top most) dates will overlay the earlier dates (lower ones) where squares have records in more than one date class.

146

ANNEX 3: FULL REPORT FROM BRIAN COPPINS ON GLEN SHIRA SNH BAP lichens surveillance trial – Pseudocyphellaria norvegica at Glen Shira Background In their report on the lichens of Glen Shira, Coppins & Coppins (1996), recorded several instances of the UK BAP lichen, P. norvegica (Norwegian specklebelly), including four on ash trees and once on oak. These trees were tagged by them as part of their survey. They also, recorded P. norvegica on hazel in a few areas, although the location of these hazels is less precise (GPS not then used). Objective To re-visit as many marked trees where P. norvegica was known to be present as possible within time constraints. Focus on those trees which were permanently marked with tree tags, moving onto groups of hazels not tagged only if time. Record if tree is still occupied (yes/no) and, if yes, how many of the original colonies of P. norvegica are apparently still present. The Survey Glen Shira was visited by Brian and Sandy Coppins on 2nd March 2012, and all five of the tagged trees located using the notes, maps and photographs in Coppins & Coppins (1996). GPS reading were made for each tree, and each was re-photographed from approximately the direction as in the 1996 report. Some hazels were also investigated in passing but no P. norvegica located. Access to the trees to the E of Drimlee, on the W side of River Shira, was by way of the track running from Elrigbeag. Tagged trees Ash tagged 02185 (NN 12682 13022) 1996 (p. 27 & fig. 1.8): upslope from the lay-by, a large, fairly isolated tree, beside a transverse ditch of a small burn. Girth of tree: 2.10m. P. norvegica: several colonies on S & SW side of the trunk. Colonies on S face are at 1.36m to 1.47m up; those on SW face are 0.79m to 0.83m up. The two colonies appear to benefit from a rain track. (Fig. 1.8 taken from upslope, looking down on the tree, with the road and lay-by (with car) perfectly visible to aid re-finding the tree). 2012 (Fig. 1): P. norvegica still present and more extensive than noted in 1996. 12 thalli on S face from 0.25m to 1.65 m; 5 thalli on SW face, still at between 0.79m to 0.83m. Thalli mostly healthy (Fig. 2), and the S-face colonies with many young lobes. Ash tagged 02186 (NN 12698 12993) 1996 (p. 29, figs 1.9 & 1.10): in a sheltered, shallow gully, beside the burn. This tree is further upslope, near the shelter of an old boundary wall. Tree girth: not measured. Trunk has dense bryophyte cover and luxuriant Lobarion. Two colonies of P. norvegica, one near base on SE side at 0.54 to 0.77m up; the second on NE face at 0.75 to 0.79m up. (Fig. 1.9 shows the tree in relation to the old boundary wall and the narrow burn gulley). 2012 (Fig. 3): P. norvegica not present, probably due to a sloughing off of bryophyte mat with which it was associated (Fig. 4). From fig. 1.10 of the 1996 report, a large colony of Lobaria pulmonaria has been lost in a similar way, and only a small scrappy patch of this species was seen on the lower part of the trunk. This may be a cyclical event.

147

Oak tagged 02199 (NN 14576 16177) 1996 (p. 123, fig. 6.5): two trunks from former coppice, close to the east edge of the river beside (outside) the Forestry fence, c. 150m upstream from the footbridge across to Drimlee (FE riverside area beyond Drimlee). The western of the two trunks was tagged (girth of W trunk 1.15m). Fig. 6.5 shows the twin-trunked oak in relation to the Forestry fence and the river. P. norvegica present on both trunks. 2012

(Fig. 5): P. norvegica still present on both trunks on W trunk a single healthy thallus on ESE side, about 2.20 m up. on E trunk a small thallus at c. 1 m up, parasitized by the lichenicolous fungus Pyrenidium actinellum. Another, smaller, moribund thallus present c. 15 cm below.

Ash tagged 02231 (NN 14480 16340) 1996 (p. 77, fig. 3.1): tree with twin-trunks (one of which has rotted away) arising from large base; the remaining trunk showing signs of decay [so may not still be present]. Tree girth 4.47m (fig. 3.1, showing the tree on a flushed slope, E of Drimlee). Small thallus of P. norvegica on WSW side, at 1.25m up. 2012 (Fig. 6): P. norvegica still present, but not where it occurred in 1996. In 2012 it occurred as 9 thalli from c. 2m to 2.5m up the trunk (Fig. 7). Ash tagged 02234 (NN 14741 16358) 1996 (p. 82, fig. 3.7): a well-lit tree, standing at the edge of a small plateau above the slope to the river. Large thallus of P. norvegica near base; circled in fig. 3.7. 2012 (Fig. 8): P. norvegica not present. Where it occurred in 1996 is now more or less bare bark, suggesting that the thallus and its associated bryophyte mat has sloughed off. Additional occurrence Ash at NN 14503 16309 (just downslope to that tagged 02231, see above). P. norvegica present as a single healthy thallus near the base of the trunk on the E side. Summary of presence of P. norvegica on tagged trees in 1996 and 2012 Tag no.

GR

Tree species

02185 02186 02199 02231 02234

NN 12682 13022 NN 12698 12993 NN 14576 16177 NN 14480 16340 NN 14741 16358

Fraxinus Fraxinus Quercus Fraxinus Fraxinus

P. norvegica present Yes No Yes Yes No

Overall change Increase Loss ± same Increase Loss

Acknowledgements Many thanks to Marina Pugh (SNH) for arranging access permission from Argyll Estates, to whom especial thanks is given for allowing us vehicular access - thus saving us at least 10 miles of walking! Thanks too to Sandy Coppins for extracting the information from our 1996 report, acting as my PA, and as my photographer.

148

Reference Coppins, A.M. & Coppins, B.J. (1996) Glen Shira (including Achnatra CFR and Glen Shira CFR), Inverary, Argyll (VC 98) – Lichen Survey. Report to Scottish Natural Heritage (Contract No. 38/F2B/485). Pp 199. Brian Coppins 37 High Street, East Linton, EH40 3AA.

149

Fig. 1. Glen Shira. Ash tagged 02185. March 2012.

Fig. 2. Glen Shira. Ash tagged 02185. Pseudocyphellaria norvegica, here associated with Degelia cyanoloma. March 2012.

Fig. 3. Glen Shira. Ash tagged 02186. March 2012.

Fig. 4. Glen Shira. Ash tagged 02186. Part of trunk rather bare, being re-colonized after previous sloughing-off of bryophyte/lichen mat. March 2012.

150

Fig. 5. Glen Shira. Oak tagged 02199. P. norvegica on both trunks; W trunk on left. March 2012.

Fig. 6. Glen Shira. Ash tagged 02231. March 2012.

Fig. 7. Glen Shira. Ash tagged 02231. BJC pointing to one of the 9 thalli on the WSW side. March 2012.

Fig. 8. Glen Shira. Ash tagged 02234. March 2012. P. norvegica no longer present.

151

ANNEX 4: SCM DATA FOR PSEUDOCYPHELLARIA NORVEGICA AT THE SITE LEVEL Changes in the occurrence of Pseudocyphellaria norvegica at the site and subsite level from site condition monitoring reports. In the change column p = present, ie lichen present on all visits (although in some cases the lichen was present, disappeared and was then rerecorded, in such cases it is assumed the lichen was present throughout but missed during the survey); i = lichen increased, ie the lichen was not present and was then found in a subsequent visit; d = decreased, i.e. the lichen was present in the first visit(s) and was subsequently not found. Sub-site

Barran Dubh Blar Na Caillich Buidhe (Morar) Cleadale (Eig) Coille Dalavil (Skye) Coille Mhor Coille Thogabhaig Cosag Sallow Doire Dhonn Ellary Woods Plot N5 Ellary Woods NR71932 75175 (Davey site 8) Ellary Woods Site13 Davey Ellary Woods Site3 Davey Glen Barisdale Glen Creran Glen Nant Area B Glen Nant Area A Glen Nant Area F

Change

1

1

1 1

1

1 1 1

1 1 0

1 1 1

1

0 1 1 1 1

1

152

2012

2011

2009

2008

2010 1 1

p p 1 1

1

1

1

p

1 1

1

1

2007

1 1

1 1

2006

2005

2004

2002

2001

1999

1997

1996

1994

1992

1987

1985

1980

1977

1976

1975

1974

1972

Year 1970

Site

0

d p p p

1 1 1 1

p p

p p i p p p p p

Sub-site

Glen Nant Plot11 transect 1 Glen Nant Plot11 transect 2 Glen Ralloch to Baravalla Woods Gruinart Flats Inverneil Burn TG Plot2a Inverneil Burn TG Plot2c Inverneil Burn TG1 Inverneil Burn Kentra Bay and Moss Kinloch and Kyleakin Hill Knapdale woods Area A1 Knapdale woods Area A2 Knapdale woods Barnluasgan plot 2a Knapdale woods Barnluasgan plot 2b Knapdale woods Barnluasgan plot 2c Knapdale woods Fairy Isles plot 1 Knapdale woods Fairy Isles plot 2 Knapdale woods Fairy Isles TG1 Knapdale woods Port Luna Knapdale woods

Change

1 1 1

1 0

1

2012

2011

2010

2009

2008

2007

2006

2005

2004

2002

2001

1999

1997

1996

1994

1992

1987

1985

1980

1977

1976

1975

1974

1972

Year 1970

Site

1 1

p p

1

p d

0 1 1 1

1

1

1

p 1

1

1

1

0

1

0

0 1 1 0 1

1 1 1 0 1

1

153

p d d

1

1 1 1 1

p

1 0 0

1 1

1

1

1

p

i p p d i p

1

2012

2011

2010

2009

p

1

0 0 1

d p p p p p

1 1

154

2008

1

1

1

2007

2006

2005

2004

2002

2001

1

1 An cap Ceol na mara

1999

1997

1996

1994

1992

1987

1985

1980

1977

1976

1975

Poll nam Partan hazelwoods Stuidh hazelwood

1974

Laig to Kildonnan Laig to Kildonnan Loch a' Mhuilinn Sunart SSSI Sunart SSSI Taynish Woods Glen Shira

Change

Year 1972

Sub-site 1970

Site

0

1

1 1 1 1 1

ANNEX 5: DATA FROM DMP FOR PSEUDOCYPHELLARIA NORVEGICA Changes in the occurrence of Pseudocyphellaria norvegica patches. In the change column p = patch present on both visits, i = patch absent on first visit but present on second visit, d = patch present on first visit but not there in second visit. Site

DMP

Patch no 1986

Blar Na Caillich Buidhe (Morar) Blar Na Caillich Buidhe (Morar) Blar Na Caillich Buidhe (Morar) Cleadale (Eig) Cleadale (Eig) Cleadale (Eig) Cleadale (Eig) Cleadale (Eig) Cleadale (Eig) Cleadale (Eig) Cleadale (Eig) Cleadale (Eig) Cleadale (Eig) Cleadale (Eig) Cleadale (Eig) Cleadale (Eig) Cleadale (Eig) Cleadale (Eig) Cleadale (Eig) Cleadale (Eig) Cleadale (Eig) Cleadale (Eig) Cleadale (Eig) Coille Dalavil (Islay)

2 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1

1 2 3 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 1

2004 1 1 1

2005

1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1

155

Year 2006

2009

2010

1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1

2011

Number of records 1 1 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 2

Change

p p p p i i i i i i i i i i i i i i i p

Site

DMP

Patch no 1986

Coille Mhor Glen Ralloch to Baravalla Woods Glen Ralloch to Baravalla Woods Glen Ralloch to Baravalla Woods Glen Ralloch to Baravalla Woods Glen Ralloch to Baravalla Woods Glen Ralloch to Baravalla Woods Kentra Bay and Moss Kentra Bay and Moss Kentra Bay and Moss Kentra Bay and Moss Kentra Bay and Moss Kentra Bay and Moss Kentra Bay and Moss Kentra Bay and Moss Kentra Bay and Moss Kinloch and Kyleakin Hill Kinloch and Kyleakin Hill Kinloch and Kyleakin Hill Knapdale woods Knapdale woods Knapdale woods Knapdale woods Knapdale woods

2005

Year 2006

2009

2010

2011 1

Number of records

Change

2

p

1

1

2004 1

3

1

1

1

2

p

5

1

1

1

2

p

6

1

1

1

2

p

11

1

1

1

2

p

13

1

1

1

2

p

16 2 4 4 4 4 4 5 5 5 4 5 11 1b DMP5 plot1a DMP5 plot1b DMP5 plot1c DMP5 plot1d

1 1 1 2 3 4 5 1 2 3 1 1 1 1 1 1 1 1

1

0 1 1 1 1 1 1 1 1 1

2 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2

d

1 1 1 1 1 1 0 1 156

1 1 1 1 0

p p p i d

Site

DMP

Patch no 1986

Knapdale woods Knapdale woods Knapdale woods Knapdale woods Knapdale woods Knapdale woods Knapdale woods Knapdale woods Knapdale woods Knapdale woods Knapdale woods Knapdale woods Knapdale woods Knapdale woods Knapdale woods Knapdale woods Knapdale woods Knapdale woods Laig to Kildonnan Laig to Kildonnan Laig to Kildonnan Loch a' Mhuilinn Loch a' Mhuilinn Loch a' Mhuilinn Loch a' Mhuilinn Loch a' Mhuilinn Loch a' Mhuilinn Loch a' Mhuilinn

DMP5 plot1d DMP5 plot1d DMP5 plot1d DMP5 plot1d DMP5 plot1e DMP5 plot1f DMP7 plot2a DMP7 plot2a DMP7 plot2a DMP7 plot2a DMP7 plot2a DMP7 plot2a DMP7 plot2a DMP7 plot2a DMP7 plot2a DMP3 plot2a DMP3 plot2b DMP3 plot2d DMP4 DMP4 DMP4 DMP1 DMP1 DMP1 DMP2tree1 DMP2tree1 DMP2tree1 DMP2tree1

2 3 4 5 1 1 1 2 3 4 5 6 7 8 9 1 1 1 1 2 3 1 2 3 1 2 3 4

2004 1 1 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 1 1 1 1 157

2005

Year 2006

2009

2010

2011 0 0 0 1 1 1 1 1 1 1 1 1 1 0 0 0

0 0 1 0 0 0 0

Number of records

Change

2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 2 1 1 1 1 2 2 2 2 2 2 2

d d d i p p p p p p p p p d d d

d d i d d d d

Site

DMP

Patch no 1986

Loch a' Mhuilinn Loch a' Mhuilinn Loch a' Mhuilinn Loch a' Mhuilinn Loch a' Mhuilinn Loch a' Mhuilinn Loch a' Mhuilinn Loch a' Mhuilinn Loch a' Mhuilinn Taynish Woods Taynish Woods Taynish Woods

DMP2tree1 DMP2tree2 DMP2tree2 DMP2tree2 DMP2tree2 DMP2tree2 DMP2tree2 DMP2tree2 DMP6 DMP2 DMP3 DMP6

5 1 2 3 4 5 6 7 1 1 1 1

2004 1 1 1 1 1 1 1 1

2005

Year 2006

2009

2010 0 1 0 0 1 1 1 1 1

0 1 1

1

158

2011

Number of records

Change

2 2 2 2 2 2 2 2 1 1 1 2

d p d d p p p p

p

ANNEX 6: DATA FROM SURVEY 1: OCCUPIED TREES AND SUITABLE HABITAT Number of trees occupied with Pseudocyphellaria norvegica trees and length (m) of suitable habitat. S1-4 = Surveyor 1-4. As no Pseudocyphellaria norvegica was found on rocks this data is not presented.

Grid cell

No. occupied trees Transect Section S1 S2 S3 S4 pattern

NN01 A

B

C

NN02 A

B

C

NN11 A

B

1-2 3-4 5-6 7-8 9-10 1-2 3-4 5-6 7-8 1-2 3-4 5-6 7-8 9-10 1-2 3-4 5-6 7-8 9-10 1-2 3-4 5-6 7-8 1-2 3-4 5-6 7-8 9-10 1-2 3-4 5-6 7-8 9-10 1-2 3-4 5-6 7-8

2 1 2 3 6 2 2 3 3 0 5 1 0 2 3 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 4 1 1 2 2 2 4

0 1 1 2 2 1 0 2 0 1 4 0 0 1 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 4 2 3 2 2 1

Suitable habitat (m) S1 S2 S3 S4 15 40 60 63 95 55 40 70 60 60 45 55 40 70 100 0 5 0 0 0 0 0 0 15 5 0 0 1 90 90 90 75 50 70 100 95 60

1 4 3 0 4

0 0 0 0 0

159

15 40 35 70 85 60 20 45 25 50 30 30 10 20 35 5 10 0 0 0 0 10 0 10 5 0 0 5 0 30 80 80 80 60 75 75 65

70 95 95 35 85

10 0 0 0 0

Grid cell

No. occupied trees Transect Section S1 S2 S3 S4 pattern C

NN12 A

B

C

NN21 A

B

C

NN22 A

B

C

1-2 3-4 5-6 7-8 9-10 1-2 3-4 5-6 7-8 9-10 1-2 3-4 5-6 7-8 1-2 3-4 5-6 7-8 9-10 1-2 3-4 5-6 7-8 9-10 1-2 3-4 5-6 7-8 1-2 3-4 5-6 7-8 9-10 1-2 3-4 5-6 7-8 9-10 1-2 3-4 5-6 7-8 1-2

2 1 3 1 2 0 1 3 3 3 2 1 6 1 0 1 4 1 2 0 0 0 3 3 1 0 3 0 1 1 1 0 0 0 0 2 0 0 2 1 0 1 1

3 2 1 0 0 1 0 5 1 0 0 0 4 2 0 2 3 0 1 0 0 0 0 2 0 0 1 0 1 0 0 0 0 2 0 0 0 0 1 0 0 0 3

6 4 3 2 6

0 5 4 6 3

0 2 4 6 7

1 2 0 0 0

6 0 1 0 0

2

4

160

Suitable habitat (m) S1 S2 S3 S4 35 70 65 60 30 50 25 35 60 75 76 55 45 55 0 30 60 55 65 50 45 15 75 65 60 20 50 10 55 70 45 5 10 50 37 45 50 15 54 34 25 75 80

40 60 60 60 40 20 40 60 60 70 60 55 65 70 0 50 70 55 60 30 30 15 65 50 86 80 90 30 60 55 54 30 5 60 25 15 10 5 36 0 10 40 80

85 70 80 80 60

0 25 45 60 80

5 30 40 60 90

53 46 44 22 3

60 30 50 40 5

60

90

Grid cell

No. occupied trees Transect Section S1 S2 S3 S4 pattern

NN31 A

B

C

NN32 A

B

C

NN42 A

B

C

3-4 5-6 7-8 9-10 1-2 3-4 5-6 7-8 9-10 1-2 3-4 5-6 7-8 1-2 3-4 5-6 7-8 9-10 1-2 3-4 5-6 7-8 9-10 1-2 3-4 5-6 7-8 1-2 3-4 5-6 7-8 9-10 1-2 3-4 5-6 7-8 9-10 1-2 3-4 5-6 7-8 1-2 3-4

2 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 1 0 0 1 3 0 2 0 3 0 5 3 5 1 2 8 9 8 3 1 2

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 3 1 1 0 2 0 2 0 0 0 2 6 7 2 3 2 11 6 4 0 0

2 0 0 0

1 0 0 0

0 0 0 0 0

1 0 0 1 1

0 0 2 0 1

3 3 6 9 3

2 3

3 5

161

Suitable habitat (m) S1 S2 S3 S4 75 45 30 10 40 5 0 0 0 0 2 10 0 5 0 5 5 5 0 0 5 25 5 0 2 5 35 2 35 5 10 0 70 70 50 30 80 105 100 125 105 20 70

60 40 0 0 5 5 15 0 0 0 5 10 0 0 0 0 5 10 0 0 15 5 20 10 10 10 20 10 25 10 10 5 70 65 60 50 80 80 80 80 50 0 0

50 65 30 5

70 10 10 10

2 0 0 2 8

10 10 10 20 20

8 50 7 18 7

5 30 30 30 30

7 20

30 50

Grid cell

No. occupied trees Transect Section S1 S2 S3 S4 pattern

NN43 A

B

C

5-6 7-8 9-10 1-2 3-4 5-6 7-8 9-10 1-2 3-4 5-6 7-8 1-2 3-4 5-6 7-8 9-10

4 5 4 1 2 0 0 0 1 0 1 0 2 2 0 0 1

6 0 0 1 0 0 0 0 0 0 1 0 1 0 0 0 1

8 6 2

4 3 1

0 0 0 0 0

1 2 1 2 0

162

Suitable habitat (m) S1 S2 S3 S4 65 90 80 100 35 0 5 0 5 20 10 0 50 20 15 15 5

60 70 40 50 10 0 10 5 10 15 20 5 10 15 15 10 20

65 51 40

80 80 50

40 10 10 0 0

30 20 20 10 10

ANNEX 7: DATA FROM SURVEY 1: TIME (MINUTES) TAKEN FOR TRANSECTS Grid cell

Transect pattern

NN01

A B C A B C A B C A B C A B C A B C A B C A B C A B C A B C

NN02

NN11

NN12

NN21

NN22

NN31

NN32

NN42

NN43

Surveyor 1 40 50 55 25 20 30 45 45 40 35 50 40 50 50 35 30 30 35 10 20 20 30 25 40 65 60 45 45 30 35

Surveyor 2

Surveyor 3

Surveyor 4

85 45 35 20 45 55 60 70 50 50 45 75 50 55 35 35

17

120

50 30 30 70

35

163

50

70

46

100

40

70

34

90

40

90

69

180

40

150

ANNEX 8: 20 MINUTE SEARCH DATA FROM SURVEY 1 Number of trees occupied with Pseudocyphellaria norvegica trees found during a 20 minute search. Grid Cell NN01 NN02 NN11 NN12 NN21 NN22 NN31 NN32 NN42 NN43

Surveyor 1

Surveyor 2

13 3 14 17 7 6 3 6 24 3

4 2 11 5 4 3 1 5 26 2

164

ANNEX 9: DATA FROM SURVEY 2 Total number of occupied trees found within a 20 minute search (No. occupied trees); time spent search up to a maximum of 20 minutes (Search time); time taken to find the first Pseudocyphellaria norvegica (1st time); Distance walked during search (m), and whether P. norvegica was present (1) or absence (0) within the 1 ha cell. S1 = surveyor 1 and S4 = surveyor 4.

Site NM9831 NM9831 NM9831 NM9831 NM9831 NM9831 NM9831 NM9831 NM9831 NM9831 NM9831 NM9831 NM9831 NM9831 NM9831 NM9831 NM9831 NM9831 NM9831 NM9831 NN0128

1ha 10 11 12 13 14 15 20 24 25 41 42 43 44 52 53 54 55 63 64 73 0

No. occupied trees S1 S4 0 0 0 0 0 0 0 0 0 0 0 0 2 1 0 0 0 0 14 2 5 0 4 1 0 0 3 3 1 0 0 0 0 0 0 1 2 1 0 1 18 9

Search time S1 20 20 20 8 7 5 20 17 11 20 20 20 20 20 20 20 9 14 20 13 20

S4 20 20 20 20 20 17 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20

1st time

Distance walked

S1

S4

7

16

2 7 1

10

1 14

18

4

15 20 6 3

1 1

165

S1 506 509 423 183 119 187 402 360 207 213 321 266 373 301 379 353 249 277 369 235 221

S4 418 343 259 461 405 603 297 406 269 394 318 214 371 286 291 282 564 318 295 329 470

Presence S1 0 0 0 0 0 0 1 0 0 1 1 1 0 1 1 0 0 0 1 0 1

S4 0 0 0 0 0 0 1 0 0 1 0 1 0 1 0 0 0 1 1 1 1

Site NN0128 NN0128 NN0128 NN0128 NN0128 NN0128 NN0128 NN0128 NN0128 NN0128 NN0128 NN0128 NN0128 NN0128 NN0128 NN0128 NN0128 NN0128 NN0128 NN0128 NN0128 NN0128 NN0128 NN0128 NN0128 NN0128 NN0128

1ha 6 07* 08* 9 10 13 16 17 18 19 20 23 24 25 26 27 28 29 30 34 35 36 40 46 50 60 61

No. occupied trees S1 S4 0 0 0 3 0 0 8 0 22 2 10 9 3 4 9 11 3 0 4 4 8 5 7 2 1 2 2 3 11 10 4 5 15 6 4 1 0 1 2 0 3 5 17 8 1 4 2 5 19 12 3 0 1 0

Search time S1 7 0 0 10 20 20 20 16 10 20 20 20 20 20 20 20 20 20 14 20 20 20 19 20 20 17 7

S4 7 20 4 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20 20

1st time S1

Distance walked S4 9

1 2 3 3 5 1 10 1 3 6 12 2 3 1 1

3 2 2

2 2 6 14 2 10 1 7 14 6

10 4 1 9 13 3 1 5

12 5 9 1 1

166

S1 230 0 0 192 158 210 276 406 271 366 211 274 232 250 287 278 222 336 203 287 285 326 327 347 206 299 158

S4 186 144 96 92 311 170 346 304 346 395 177 298 203 242 229 325 272 383 702 311 409 395 364 260 202 380 622

Presence S1 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 1 1 1 1 1 1 1 1

S4 0 1 0 0 1 1 1 1 0 1 1 1 1 1 1 1 1 1 1 0 1 1 1 1 1 0 0

Site NN0128 NN0128 NN0128 NN0128 NN0128 NN0128

1ha 62 70 71 72 80 90

No. occupied trees S1 S4 0 0 14 1 0 0 4 0 5 0 12 1

Search time S1 7 20 11 20 20 20

S4 13 20 20 20 20 20

1st time

Distance walked

S1

S4

1

5

8 5 1

12

S1 146 260 742 332 182 289

S4 407 217 774 649 245

Presence S1 0 1 0 1 1 1

S4 0 1 0 0 0 1

*the 1 ha was deemed as not containing any suitable habitat by Surveyor 1 when seen from a distance, hence the zero search time. Surveyor 4 did survey the 1ha.

167

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