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CENTRE FOR ECOLOGY AND HYDROLOGY (Natural Environment Research Council) CEH Project Number: C02351NEW CCW Contract Number: FC 73-03-181

The current and potential impact of diffuse pollution on water dependent biodiversity in Wales B Reynolds1, D A Norris1, J Hilton2, J A B Bass2, D D Hornby2

1

Centre for Ecology and Hydrology Bangor Orton Building Deiniol Road Bangor Gwynedd LL57 2UP

2

Centre for Ecology and Hydrology Dorset Winfrith Technology Centre Winfrith Newburgh Dorchester Dorset DT2 8ZD

July 2004

EXECUTIVE SUMMARY Contamination of surface waters by diffuse pollutants is widely acknowledged as a major environmental problem in the UK which may directly affect compliance with a number of EU directives for water quality, ecological status and habitat quality in Wales. However the extent of the problem and its impact upon areas of conservation interest in Wales is unknown. The Countryside Council for Wales (CCW) have identified and designated a large number of sites in Wales containing water dependent species and habitats of either national or international importance. The objective of this project is to identify where these features are currently or potentially at risk from diffuse pollution. This will equip the CCW with the information required to evaluate, prioritise and ultimately address the issues of diffuse pollution at those sites for which water dependent biodiversity is deemed to be at significant risk. The project is concerned with fresh, surface waters and does not include groundwater, coastal waters or estuaries. The following have been identified as the main diffuse pollutants of concern in Wales: phosphate and acidity for lakes and running waters, suspended sediments and cypermethrin sheep dip for running waters only. A three stage approach has been adopted for the risk assessment. Firstly the susceptibility of species, species assemblages, communities and habitats to diffuse pollutants has been assessed using reviews of currently available scientific information and expert judgement (Chapter 2). The range of species was pre-selected to reflect current conservation priorities, including BAP species and habitats, and concentrates on those associated with SSSIs and cSACs. Species and communities were aggregated where they shared similar habitats, physiological responses or ecological traits which pre-dispose them to react in a similar manner to particular diffuse pollutants. The term ‘susceptibility’ has been used to reflect a combination of direct and indirect impacts, combining sensitivity with the likelihood of exposure. Susceptibility is expressed as HIGH/MEDIUM/LOW to diffuse pollutants. The second stage use a Geographical Information System (GIS) to assess the level of pressure exerted by individual pollutants using a combination of water quality data held by the Environment Agency Wales (EAW), primarily for running waters, and threshold modelling for lakes (Chapters 3 and 4). River phosphate; maps were created from GQA data supplied by the EAW for individual river reaches. Rivers with GQA scores from 3 to 6 inclusive were classed as posing a risk to sensitive water dependent species and habitats. Sheep dip, maps showing sites where concentrations had exceeded the Maximum Admissible Concentration for years 1997-2002 were used to define the ‘pressure’ from this pollutant. Suspended sediment data were supplied by the EAW from monitoring sites in Wales and these were used as the basis for mapping. Suspended sediment concentrations of 20 mg l-1 or greater were deemed to pose a risk to sensitive water dependent habitats and species.

Lake phosphate and acidity and acidity for running waters. Due to the scarcity of appropriate data, an alternative approach was adopted whereby the pressures from these pollutants were predicted on the basis of mapped catchment attributes. River and lake acidity; a scoring system developed by the Environment Agency was used which combined acid deposition loading with predicted catchment acid sensitivity taken from the map of Hornung et al. (1995). The scoring was modified according to the catchment cover of coniferous forestry (to increase sensitivity) and limed agricultural land (to decrease sensitivity). On a six point scale, lakes or river reaches with a score of 4 or greater were deemed to pose a risk to sensitive species and habitats. Phosphate risk to lakes was modelled using an export coefficient based model incorporating catchment P losses from land cover, stock density and human population. From this, annual total P concentration was estimated for each lake and 5 risk classes were generated using the Vollenweider classification. Phosphate risk to wetlands; a novel methodology was developed to give a preliminary indication of risk to wetlands. This essentially used the same approach as for lake phosphate. The final stage of the assessment was to use the GIS to map susceptible species and habitats within designated areas of conservation importance against the pressure for each pollutant to identify those areas currently and potentially at risk (Chapters 4 and 5). For lakes, the modelled predictions for phosphorus and acidity were evaluated against observations (Chapter 6). This showed that the models were generally successful in identifying lakes at risk from acidification and eutrophication. The combination of relatively low intensity agricultural management and high flow rates means that the majority of rivers in Wales have a very low risk of eutrophication from diffuse sources of phosphate. Areas at significant risk are in the lower, more slow moving parts of river systems in the north-east, southeast and south west of Wales and Anglesey. There are isolated areas deemed ‘at risk’ throughout Wales and these may warrant closer investigation. The risk assessment modelling for lakes suggests that a relatively large number of lakes in the lowland, more intensively managed parts of Wales along the eastern borders, north east Wales, the south coast and Anglesey are at risk of eutrophication from phosphate. The acidity risk assessment for rivers predicts that the majority of the upland headwater streams rising in the Cambrian mountains and Snowdonia are at severe risk of acidification along with some rivers draining the northern edges of the south Wales coalfield. The acidification risk assessment for lakes is consistent with that for rivers, indicating that lakes in the Cambrian mountains, Snowdonia and the Brecon Beacons are at high risk of acidification. The Upper Wye, Upper Usk and Teifi systems are the main rivers of concern in relation to risk from cypermethrin sheep dip. There are some additional isolated ‘high risk’ sites, notably in the Berwyn and in north Wales. Concentrations of suspended sediments are generally low in the upland areas of Wales reflecting the low intensity land management and absence of significant areas of arable farming. Concentrations are much higher in the south, along the Welsh borders and the north east. The Usk, Tywi, Ithon and Cleddau systems are the main river systems at risk.

CRYNODEB WEITHREDOL Mae llygru dŵr wyneb gan lygrynnau tryledol yn cael ei gydnabod fel problem amgylcheddol enfawr yn y DG, a gall hyn effeithio yn uniongyrchol ar y gallu i gydymffurfio â nifer o gyfarwyddebau’r UE am ansawdd dŵr, statws ecolegol ac ansawdd cynefinoedd yng Nghymru. Fodd bynnag, ni wyddom faint y broblem na’i effaith ar ardaloedd o ddiddordeb cadwriaethol yng Nghymru. Mae Cyngor Cefn Gwlad Cymru (CCGC) wedi nodi a dynodi nifer fawr o safleoedd yng Nghymru sydd yn cynnwys rhywogaethau a chynefinoedd sydd yn ddibynnol ar ddŵr, ac sydd naill ai o bwysigrwydd cenedlaethol neu ryngwladol. Nod y prosiect hwn yw gweld lle mae’r nodweddion hyn mewn perygl o lygru tryledol, neu lle gallant fod. Bydd hyn yn rhoi’r wybodaeth i CCGC er mwyn gwerthuso, blaenoriaethu ac yn y pen draw drin pwnc llygru tryledol yn y safleoedd hynny lle tybir bod bioamrywiaeth dibynnol ar ddŵr mewn perygl sylweddol. Ymwneud y mae’r prosiect â dyfroedd wyneb claear, ac nid yw’n cynnwys dŵr daear, dyfroedd arfordirol nac aberoedd. Nodwyd y canlynol fel y prif lygrynnau tryledol sy’n peri pryder yng Nghymru: ffosffad ac asidedd i lynnoedd a dyfroedd rhedegog, gwaddodion crog a dip defaid cypermethrin i ddyfroedd rhedegog yn unig. Mabwysiadwyd agwedd dair cam at yr asesiad risg. Yn gyntaf, aseswyd pa mor agored y mae rhywogaethau, cynulliadau rhywogaethau, cymunedau a chynefinoedd i lygrynnau tryledol. Defnyddiwyd y wybodaeth wyddonol gyfredol, a barn arbenigol, i wneud hyn (Pennod 2). Dewiswyd ystod y rhywogaethau ymlaen llaw er mwyn adlewyrchu blaenoriaethau cadwraeth cyfredol, gan gynnwys rhywogaethau a chynefinoedd BAP, a chanolbwyntiwyd ar y rhai sy’n gysylltiedig â SDdGA ac ACAa. Casglwyd rhywogaethau a chymunedau at ei gilydd lle’r oeddynt yn rhannu cynefinoedd, ymateb ffisiolegol neu nodweddion ecolegol tebyg sydd yn eu gwneud yn dueddol i ymateb yn yr un ffordd i lygrynnau tryledol penodol. Defnyddiwyd y term ‘derbynnedd’ i adlewyrchu cyfuniad o effeithiau uniongyrchol ac anuniongyrchol, sy’n cyfuno sensitifrwydd gyda thebygolrwydd bod yn agored i lygru. Mynegir derbynnedd fel UCHEL/CANOLIG/ISEL i lygrynnau tryledol. Mae’r ail gam yn defnyddio System Wybodaeth Ddaearyddol (GIS) i asesu lefel pwysedd llygrynnau unigol gan ddefnyddio cyfuniad o ddata ansawdd dŵr a ddelir gan Asiantaeth yr Amgylchedd Cymru (AAC), yn bennaf ar gyfer dyfroedd rhedegog, a modelu trothwy ar gyfer llynnoedd (Penodau 3 a 4). Ffosffad afonydd; crëwyd mapiau o ddata GQA a gyflenwyd gan AAC ar gyfer rhannau o afonydd unigol. Dosbarthwyd afonydd gyda sgoriau GQA o 3 i 6 gan gynnwys y ddau fel rhai oedd â risg i rywogaethau a chynefinoedd sensitif dibynnol ar ddŵr . Defnyddiwyd dipiau defaid, mapiau yn dangos safleoedd lle’r oedd cyddwysiadau wedi mynd dros yr Uchafswm Cyddwysiad Derbyniol am y blynyddoedd 1997-2002 i ddiffinio’r ‘pwysedd’ o’r llygryn hwn. Cyflenwyd data gwaddod crog gan AAC o’r safleoedd monitro yng Nghymru a defnyddiwyd y rhain fel sail i fapio. Dywedwyd bod cyddwysiadau gwaddod crog o 20 mg l-1 neu fwy yn risg i rywogaethau a chynefinoedd sensitif dibynnol ar ddŵr.

Ffosffad ac asidedd dyfroedd rhedegog. Oherwydd prinder data priodol, mabwysiadwyd agwedd gwahanol lle rhagfynegwyd y pwysau o’r llygrynnau hyn ar sail nodweddion dalgylchoedd a fapiwyd. Asidedd afonydd a llynnoedd; defnyddiwyd system sgorio a ddatblygwyd gan Asiantaeth yr Amgylchedd oedd yn cyfuno llwythiad dyddodi asid gyda rhagfynegiad am sensitifrwydd asid dalgylch a gymerwyd o fapiau Hornung et al. (1995). Addaswyd y sgorio yn ôl trwch coed conifferaidd yn y dalgylch (i gynyddu sensitifrwydd) a thir amaethyddol a galchwyd (i leihau sensitifrwydd). Ar raddfa chwe phwynt, dywedwyd bod llynnoedd neu ddarnau o afonydd gyda sgôr o 4 neu fwy yn risg i rywogaethau a chynefinoedd sensitif. Modelwyd risg ffosffad i lynnoedd trwy ddefnyddio model symud cyfernod oedd yn ymgorffori colled dalgylch P o dir, dwysedd stoc a phoblogaeth ddynol. O hyn, amcangyfrifwyd cyfanswm colledion P blynyddol ar gyfer pob llyn a chynhyrchwyd 5 dosbarth risg gan ddefnyddio dosbarthiad Vollenweider. Risg ffosffad i wlyptiroedd; defnyddiwyd methodoleg newydd i roi syniad cychwynnol o’r risg i wlyptiroedd. Yr oedd hyn yn ei hanfod yn defnyddio’r un agwedd ag ar gyfer ffosffad mewn llynnoedd. Cam olaf yr asesiad oedd defnyddio’r GIS i fapio rhywogaethau a chynefinoedd a allai fod yn agored i lygru mewn ardaloedd cadwraeth dynodedig yn erbyn y pwysedd o du pob llygryn i nodi’r ardaloedd hynny sydd mewn perygl ar hyn o bryd ac a allai fod (Penodau 4 a 5). Ar gyfer llynnoedd,, gwerthuswyd y rhagdybiaethau a fodelwyd ar gyfer ffosfforws ac asidedd yn erbyn arsylwadau (Pennod 6). Dangosodd hyn fod y modelau ar y cyfan yn llwyddo i nodi llynnoedd oedd mewn perygl o asideiddio a gorfaethu. Mae’r cyfuniad o reolaeth amaethyddol gymharol isel ei ddwysedd a chyfraddau llif uchel yn golygu mai perygl isel iawn sydd i’r rhan fwyaf o afonydd yng Nghymru orfaethu o ffynonellau llygredd tryledol. Ardaloedd sydd mewn perygl sylweddol yw rhannau is, arafach systemau afonydd yn y gogledd-ddwyrain, y de-ddwyrain, a Môn. Tybir bod ardaloedd unigol ‘mewn perygl’ ledled Cymru a buasai’n werth ymchwilio’n fanylach i’r rhain. Mae’r modelu asesiad risg ar gyfer llynnoedd yn awgrymu fod nifer cymharol faw ro lynnoedd yn nhir isel Cymru, sydd wedi ei reoli yn ddwysach, ar hyd y ffin ddwyreiniol, y gogledd-ddwyrain, arfordir y de a Môn mewn perygl o orfaethu gan ffosffad. Mae’r asesiad risg asidedd am afonydd yn rhagweld fod y rhan fwyaf o ffrydiau blaenddwr yr ucheldir sy’n codi ym mynyddoedd y Cambrian ac Eryri mewn perygl difrifol o asideiddio, ynghyd â rhai afonydd sy’n draenio ymylon gogleddol maes glo’r de. Mae’r asesiad risg asideiddio ar gyfer llynnoedd yn gyson â’r un ar gyfer afonydd, sy’n dangos fod llynnoedd mynyddoedd y Cambrian, Eryri a Bannau Brycheiniog oll mewn perygl mawr o asideiddio. Systemau afonydd Gŵy Uchaf, y Wysg Uchaf ac Afon Teifi yw’r prif afonydd sy’n peri pryder mewn perthynas â risg o ddip defaid cypermethrin. Mae rhai safleoedd ‘risg uchel’ unigol eraill, yn bennaf ym mynyddoedd y Berwyn a’r gogledd. Mae cyddwysiadau o waddodion crog yn isel ar y cyfan yn ucheldir Cymru, sy’n adlewyrchu dwysedd isel rheoli’r tir a phrinder ardaloedd helaeth o dir âr. Mae cyddwysiadau yn uwch o lawer yn y de, ar hyd y ffin ac yn y gogledd-ddwyrain. Systemau Afonydd Wysg, Tywi, Ithon a Chleddau yw’r prif systemau afonydd sydd mewn perygl.

CONTENTS

Page Numbers 1.

INTRODUCTION ......................................................................................................... 1

2.

SUSCEPTIBILITY OF BAP SPECIES AND HABITATS TO DIFFUSE POLLUTANTS.............................................................................................................. 4 2.1 2.2 2.3

3.

Background ........................................................................................................ 4 Susceptibility rankings for species..................................................................... 4 Susceptibility rankings for habitats.................................................................. 11

MODELLING THRESHOLD SCORES FOR ACIDITY AND PHOSPHORUS ...... 12 3.1 3.2

Acidity threshold scores for rivers................................................................... 12 Lakes ................................................................................................................ 13 3.2.1 3.2.2 3.2.3 3.2.4

4.

Methodology for acidification risk assessment.................................... 13 Effect of acid deposition values on lake acidification risk assessment ........................................................................................... 14 Methodology for eutrophication risk class .......................................... 15 Effect of using total and diffuse P loading on P eutrophication risk class for lakes....................................................................................... 16

MAPPING METHODS ............................................................................................... 17 4.1 4.2

Background ...................................................................................................... 17 Data provision.................................................................................................. 17 4.2.1 4.2.2 4.2.3

4.3

Pollutant pressure maps ................................................................................... 17 4.3.1 4.3.2 4.3.3 4.3.4 4.3.5

4.4

Environment Agency data.................................................................... 17 CCW data............................................................................................. 17 Supporting data sets ............................................................................. 17

River phosphate ................................................................................... 18 Cypermethrin sheep dip in rivers......................................................... 18 Suspended sediments in rivers ............................................................. 18 River acidity......................................................................................... 18 Lake acidity and phosphorus pressure maps........................................ 18

Linking susceptibility ranking with water dependent features ........................ 19 4.4.1 4.4.2 4.4.3 4.4.4

Definition of water dependent features................................................ 19 Mapping SSSIs containing water dependent features.......................... 19 Combining water dependent features, pollutant susceptibility and SSSIs .................................................................................................... 19 Combining site susceptibility and pollutant pressure .......................... 22

4.5 5.

DIFFUSE POLLUTION MAPS .................................................................................. 25 5.1 5.2

6.

Wetlands .......................................................................................................... 23

Introduction...................................................................................................... 25 Map outputs ..................................................................................................... 25

EVALUATING THRESHOLD SCORE MODELLING FOR LAKES AND RIVERS ...................................................................................................................... 42 6.1

Testing the acidity risk assessment for Welsh lakes........................................ 42 6.1.1 6.1.2 6.1.3

6.2

Testing the eutrophication risk assessment for Welsh lakes............................ 45 6.2.1 6.2.2 6.2.3

6.3

Comparison of acidity threshold scores and AWIC scores ................. 48

OBSERVATIONS AND CONCLUDING REMARKS.............................................. 51 7.1

Risk assessment mapping ................................................................................ 51

7.2

Mapping outputs .............................................................................................. 51 7.2.1 7.2.2 7.2.3 7.2.4

8.

Methodology ........................................................................................ 45 Results.................................................................................................. 46 6.2.2.1 Welsh lakes data ...................................................................... 46 Conclusions.......................................................................................... 48

Testing the acidity risk assessment for Welsh rivers ....................................... 48 6.3.1

7.

Welsh lakes data .................................................................................. 42 Results.................................................................................................. 43 Conclusions.......................................................................................... 45

Phosphorus........................................................................................... 51 Acidification ........................................................................................ 52 Sheep dip.............................................................................................. 52 Suspended sediments ........................................................................... 52

REFERENCES ........................................................................................................... 53

APPENDIX 1 TABLE 1 Diffuse pollutant susceptibility rankings for water dependent species, species groups and habitats ..................................................................................................................................... 57 APPENDIX 2 Revised methodology for total P for lakes............................................................................... 61

1.

INTRODUCTION

Contamination of surface waters by diffuse pollution is widely acknowledged as a major environmental problem in the UK, particularly as legislative controls and control technologies for point sources of pollution have become more effective. Diffuse pollution arises from agricultural and urban sources dispersed across a catchment, and does not arise from discrete, controllable, effluent discharges. It is likely to be intermittent or sporadic, and is often associated with climatic episodes, making monitoring and control more difficult. The extent and significance of diffuse pollution is determined by a range of environmental factors such as climate, geography and geology which influence the local land use, the characteristics of runoff and the sensitivity of the receiving waters. Compliance with a number of EU directives (Water Framework Directive, Habitats Directive, Birds Directive) for water quality, ecological status and habitat quality in Wales is directly affected by issues of diffuse pollution. However the extent of the problem across Wales, and more specifically its impact upon areas of conservation interest in Wales is unknown. The output of this project is designed to equip the CCW with the information required to evaluate, prioritise and ultimately address the issues of diffuse pollution at those sites for which water dependent biodiversity is deemed to be at significant risk. The following have been identified as the main diffuse pollutants of concern in Wales: phosphate and acidity for lakes and running waters, suspended sediments and cypermethrin sheep dip for running waters only. Phosphorus plays a critical role in freshwater ecosystems, as it is often the factor controlling plant production. Its widespread usage in agricultural fertilisers and animal feeds provides a ready source, which may leach in to water bodies directly, or bound to soil particles. It is estimated that at least 50% of the phosphorus entering surface waters is from diffuse sources, and this is likely to achieve greater significance as steps are taken to control point sources under EC Directives. Acidification in Wales remains a significant environmental issue because of the extent to which upland soils and streams that are affected, and the particular impacts on salmonids. The extent of acidification is still widespread even though there have been large cuts in sulphur dioxide emissions over the past 20 years. Within the UK, Wales is the country which is most affected as indicated by impacts on terrestrial and freshwater ecosystems. However, comparison of the extent by which critical loads for freshwater acidity are exceeded by acid deposition loading indicates that there have been improvements in the acidification status of freshwaters in Wales since the 1990s reflecting the decline in acid deposition. Soil erosion through the action of water running over bare or disturbed ground can generate high levels of suspended sediments in receiving water courses. The impacts occur when disturbed areas of ground, such as construction sites, arable fields or forest harvesting sites and access tracks are poorly managed making soils vulnerable to erosion. Erosion of banksides can occur where these are not protected by vegetation, and overstocking and trampling by livestock at feeding and watering points can also lead to exposed soil being eroded. The risk of soil erosion is influenced by local characteristics of soil type, relief, and climate, as well as by the vegetation cover and land use. In receiving waters, suspended sediments can have physical effects on habitats due to increased rates of sedimentation and

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high levels of turbidity. Suspended sediments can also carry phosphate, pesticides, toxic metals and faecal pathogens leading to broader ecological impacts. Since 1995 there has been an increasing awareness of the environmental problems associated with the use of synthetic pyrethroid based sheep dips such as cypermethrin. Given the importance and prevalence of sheep farming within Wales, monitoring and pollution prevention visits have been carried out since 1997. Sheep dip may enter watercourses through accidental spillages and runoff from dipping areas. The extent of mobilisation of such pesticides will depend on the properties of the pesticide, local conditions and weather patterns following application. The CCW have identified and designated a large number of sites containing water dependent species and habitats of either national or international importance in Wales. The objective of this project is therefore to identify where these features are currently or potentially at risk from diffuse pollution. The project has been concerned with fresh, surface waters and does not include groundwater, coastal waters or estuaries. A three stage approach has been adopted. Firstly the susceptibility of species and habitats to diffuse pollutants has been assessed using reviews of currently available scientific information and expert judgement (see Chapter 2). The second stage assesses the level of pressure exerted by individual pollutants using a combination of water quality data held by the Environment Agency Wales (EAW), primarily for running waters, and threshold modelling for lakes (see Chapters 3 and 4). For river phosphate, maps were created from GQA data supplied by the EAW for individual river reaches. Rivers with GQA scores from 3 to 6 inclusive were classed as posing a risk to sensitive water dependent species and habitats. For sheep dip, maps showing sites where concentrations had exceeded the Maximum Admissible Concentration for years 1997-2002 were used to define the ‘pressure’ from this pollutant. Suspended sediment data were supplied by the EAW from monitoring sites in Wales and these were used as the basis for mapping. Suspended sediment concentrations of 20 mg l-1 or greater were deemed to pose a risk to sensitive water dependent habitats and species. Due to the relative scarcity of phosphate and acidity data for lakes and acidity data for potentially sensitive headwater streams, an alternative approach was adopted whereby the pressures from these pollutants were predicted on the basis of mapped catchment attributes. For river and lake acidity, a scoring system developed by the Environment Agency was used which combined acid deposition loading with predicted catchment acid sensitivity taken from the map of Hornung et al. (1995). The scoring was modified according to the catchment cover of coniferous forestry (to increase sensitivity) and limed agricultural land (to decrease sensitivity). On a six point scale, lakes or river reaches with a score of 4 or greater were deemed to pose a risk to sensitive species and habitats. Phosphate risk to lakes was modelled using an export coefficient based model incorporating catchment P losses from land cover, stock density and human population. From this, annual total P concentration was estimated for each lake and 5 risk classes were generated using the Vollenweider classification. The final stage of the assessment was to map susceptible species and habitats against the pressure for each pollutant to identify those areas currently and potentially at risk (Chapters 4 and 5).

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There are advantages and disadvantages associated with each approach to mapping pollutant pressure. Maps based on water quality measurements provide accurate data for a limited number of sample points or river reaches. Depending on the sample site density, this may leave large and possibly sensitive parts of the river network unrepresented. For example, the water quality of headwater streams is often not routinely monitored yet these are usually the most acid sensitive parts of the river network. Likewise, there are too few water quality data for lakes in Wales to make a valid risk assessment for all lakes based on data alone. In contrast, GIS-based modelling offers the possibility of predicting water quality variables for the entire stream network or population of lakes. However, there can be large uncertainties associated with modelling which relate to the structure and parameterisation of the models and the availability of appropriately detailed catchment spatial data. For national scale modelling, as required in this project, there is a balance to be struck between model complexity, data availability and the objectives and timescale of the project. For this assessment, relatively simple models were used since they required readily accessible spatial data whilst meeting the aims and deadlines of the project. With respect to lakes, it was possible to evaluate the modelled predictions for phosphorus and acidity against observations (Chapter 6). This gave a qualitative estimate of confidence in the model predictions and showed that they were generally successful in identifying lakes at risk from acidification and eutrophication.

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2.

SUSCEPTIBILITY OF BAP SPECIES AND HABITATS TO DIFFUSE POLLUTANTS

2.1 Backround The range of species, species assemblages, communities and habitats covered in this review were pre-selected to reflect current conservation priorities. These included BAP species and habitats and concentrates on those associated with SSSIs and cSACs. We have aggregated species and communities where they share similar habitats, physiological responses or ecological traits which pre-dispose them to react in a similar manner to particular diffuse pollutants (See Appendix 1). All species and habitats considered can be exposed to waterborne pollutants, though it should be stressed that the risk of exposure and its consequences are not solely dependant on environmental concentrations of individual pollutants, but subject to local circumstances and in some cases seasonal susceptibility. In this review we use the term ‘susceptibility’ to reflect a combination of direct and indirect impacts, combining sensitivity with the likelihood of exposure. Susceptibility is expressed as HIGH/MEDIUM/LOW to diffuse pollutants. It should be noted that published information is lacking or conflicting for many species, also within species groups and communities. Theoretical sensitivity is useful for interpretation of change scenarios for a diffuse pollutant, but some pragmatic judgements had to be applied for many species. Two extreme examples are: (1) species occupying restricted ecological niches that strongly influence exposure to, or isolation from, certain diffuse pollutants; (2) coastal communities which include species sensitive to diffuse pollutants, but living in a well-buffered environment. The initial susceptibility rankings were reviewed by CCW staff and the authors of the report would like to especially thank Tristan Hatton-Ellis, an acknowledged expert on the ecology of rare and endangered fish for his useful comments.

2.2 Susceptibility rankings for species The susceptibility rankings for species and groups of species are summarised in Table 1 of Appendix 1. The text below gives a more detailed account of how the rankings were derived.

OTTER Diffuse pollutants summary (Chanin, 2003) Potential important sources: run-off from farms, acid rain, mercury, also cadmium and lead, pesticides and PCBs. Critical levels of the latter two are (concentrations in spraints) >16 mg kg-1 of PCB and dieldrin singly or combined or concentrations of total organochlorines >20 mg kg-1; synthetic pyrethroids – sheep dips – implicated in 24% of pollution incidents recorded in 1998 in Wales (these events may have indirect impacts on otter food supply). The high mobility of otters means that local food supply problems can be avoided, but geographically widespread impacts will be deleterious.

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Suspended Sediment - MEDIUM Cypermethrin sheepdip - MEDIUM Soluble Reactive Phosphorus - MEDIUM Acid rain - MEDIUM

RIVER LAMPREY Diffuse pollutants summary (Maitland, 2003) Eutrophication from agro-chemicals (sufficient to generate prolonged anoxia in sediment deposits). Conditions in all parts of any river where (river) lamprey occur, or pass through on migration, should be at least UK Water Quality Class A2 in Scotland or B in England, Wales and Northern Ireland. Susceptibility to soluble reactive phosphorus is classed as MEDIUM on the basis of increased risk of sediment anoxia (ammocete habitat). Suspended Sediment – LOW Cypermethrin sheepdip – MEDIUM Soluble Reactive Phosphorus – MEDIUM Acid rain – MEDIUM

BROOK LAMPREY Diffuse pollutants summary (Maitland, 2003) Eutrophication from agro-chemicals (sufficient to generate prolonged anoxia in sediment deposits). Conditions in all parts of any river where (river) lamprey occur, or pass through on migration, should be at least UK Water Quality Class A2 in Scotland or B in England, Wales and Northern Ireland. For Cypermethrin sheepdip, susceptibility was classed as HIGH based on greater exposure risk in small streams both from the water and via contaminated sediment to the ammocetes. At the population level, a higher proportion of brook lampreys (than river lampreys) were gauged to be at increased risk of exposure – based on their more widespread occurrence in small streams. Suspended Sediment – LOW Cypermethrin sheepdip – HIGH (small streams – greater risk) Soluble Reactive Phosphorus - MEDIUM Acid rain - MEDIUM

SEA LAMPREY Diffuse pollutants summary (Maitland, 2003) Eutrophication from agro-chemicals (sufficient to generate prolonged anoxia in sediment deposits). Note: as an ammocete the sea lamprey is more tolerant of low oxygen concentrations than other lamprey species, whilst oxygen consumption of adult sea lamprey at various temperatures is comparable to salmonids of similar weight.

5

Suspended Sediment – LOW (less sensitive to resultant short-term anoxia) Cypermethrin sheepdip – MEDIUM Soluble Reactive Phosphorus - LOW Acid rain - LOW

SALMON Diffuse pollutants summary (Hendry and Cragg-Hine, 2003) Salmon are susceptible to high concentrations of fine suspended solids in the water which can: choke fish, disrupt feeding behaviour, smother salmonid eggs, prevent or disrupt alevin emergence and reduce the fitness of the fry and parr. Nutrients used as fertiliser in agriculture and forestry increase the output of fertilisers such as nitrate and phosphate during initial site preparation, and again during clear-felling operations. Eggs and alevins are highly sensitive to acidification and cannot tolerate a pH of much less than 4.5. Older parr stages are also susceptible, even to short duration acid events. Oxygen concentrations should not fall below a single-day mean of 8 mg l-1 for spawning fish, although 5.0–6.5 mg l-1 is acceptable to adult fish at other times. Inadequate disposal of synthetic pyrethroid (SP) sheep dips has seriously affected several thousand kilometres of upland streams in England and Wales. Suspended Sediment –HIGH (eggs/fry) Cypermethrin sheepdip –HIGH (fry/parr) Soluble Reactive Phosphorus - MEDIUM Acid rain – HIGH (headwaters)

FRESHWATER PEARL MUSSEL Diffuse pollutants summary (Skinner et al., 2003) Freshwater Pearl Mussel requires nitrate levels not exceeding 1.0 mg l-1, although higher values of 1.5 mg l-1 may be encountered in some British rivers. Phosphates should be 1.5 keqH+ ha-1 yr-1 If > 75% catchment area is in acid sensitivity Class 1 If > 20% of catchment area = LCM2000 class 2.1(coniferous woodland) If < 1.5% of catchment area is agricultural land receiving lime

Score 2

Otherwise 0

2 1

0 0

1

0

Acid deposition data are the national 5 x 5 km square values for non-marine sulphur deposition + total nitrogen deposition for 1995-97. A GIS derived catchment boundary was used to identify the acid deposition squares contained within each catchment. The average of all these 5 x 5 km sqaures was then calculated. Predicted acid sensitivity is derived from the map of Hornung et al., (1995). Agricultural land has been defined from the LCM2000 as an amalgamation of Class 4 (Arable and Horticultural) with Class 5.1 (Improved grassland). Calcareous grassland was omitted as this is implicitly incorporated within the freshwater sensitivity map. Indeed, the sensitivity map was used to define neutral grassland, calcareous grassland and acid grassland at subclass level in LCM2000. The output is a map of 1 km river reaches coloured according to the acidity threshold scores. The threshold scores have been interpreted by the Environment Agency to give the following acidification risk assessment: Score below 4 Score 4 Score 5 Score 6

Not at risk At risk (low confidence) At risk (moderate confidence) At risk (high confidence)

Designated areas are defined and mapped as being ‘At risk’ where acidity threshold scores of 4 and above, calculated using the methodology, intersect water dependent species and habitats of ‘medium and high susceptibility’ – see Section 4.4.4.

12

3.2 Lakes 3.2.1 Methodology for acidification risk assessment. The Environment Agency ‘Fozzard method’ supplied by Geoff Philips of the Environment Agency has been used. This combines acid deposition to the lake catchment, with catchment attributes of predicted acid sensitivity and land use derived from the National Lakes Inventory to calculate an acidity threshold score. The acidity threshold score for a lake equals the sum of the scores in Table 3.2. Table 3.2 Calculation of acidity threshold scores for lakes Criterion Net acid deposition > ‘x’ keqH+ ha-1 yr-1 Dominant Freshwater sensitivity class < 3 LCM2000 class 2.1 = coniferous woodland >20% Non-agricultural land >98.5%

Score 2 2 1 1

Otherwise 0 0 0 0

In order to identify an appropriate threshold value, three acidity scores were calculated with a value ‘x’ set at an acid deposition value of a) 0.5; b) 1.0 or c) 1.5 keqH+ ha-1 yr-1 mapped to the lake catchment from the national 5 x 5 km square values for non-marine sulphur deposition + total nitrogen deposition. Predicted acid sensitivity is derived from the map of Hornung et al., (1995). Non-agricultural land is defined from the CEH LCM2000 as the summed areas of classes: 11: Fen, marsh and swamp 21: Littoral sediment 6.1: Rough grass 8.1: Acid grassland 9.1: Bracken 10.1: Dwarf shrub heath 10.2: Open shrub heath 12.1: Bog The acidity threshold scores have been mapped as points denoting the centroid of each lake polygon. The acidity threshold scores have been interpreted by the Environment Agency to give the following: Score below 4 Score 4 Score 5 Score 6

Not at risk At risk (low confidence) At risk (moderate confidence) At risk (high confidence)

13

3.2.2 Effect of acid deposition values on lake acidification risk assessment The methodology in Table 3.2 produces three maps of lake acidity threshold scores for ‘x’ = 0.5, 1.0 and 1.5 keqH+ ha-1 yr-1. The distribution of the scores amongst the lakes has been summarised in Figure 3.1.

350

300

No. of lakes

250

200

150

100

50

0 0

1

2

3

4

5

6

Threshold score Dep = 0.5

Dep = 1.0

Dep = 1.5

Figure 3.1 Histogram showing distribution of acidity threshold scores for acid deposition values of 0.5, 1.0 and 1.5 keqH+ ha-1 yr-1. From Figure 3.1, assigning deposition values of 0.5 or 1.0 keqH+ ha-1 yr-1 makes little difference to the distribution of acidity threshold scores amongst the lakes. A deposition value of 1.5 keqH+ ha-1 yr-1 yields 138 lakes with a score of 0 and decreases the number of lakes with a score of 4. This has the effect of increasing the number of lakes ‘not at risk’ (Score < 4) by 56 compared to a deposition value of 0.5 keqH+ ha-1 yr-1 (Table 3.3). Visual scrutiny of the respective maps suggests that a deposition value of 1.5 keqH+ ha-1 yr-1 gives a more realistic assessment of lakes ‘at risk’. This value renders 35% of Welsh lakes at risk from acidification. The confidence in the acidification risk is ‘moderate to high’ for about 8% of the population of Welsh lakes (50 lakes). Table 3.3 Numbers of Welsh lakes at risk of acidification with respect to acid deposition value used to derive the acidity threshold scores. Acid deposition value (keqH+ ha-1 yr-1) 0.5 1.0 1.5

Number of lakes at risk (Score >= 4) 267 (45 %) 266 (44%) 211 (35%)

14

Number of lakes not at risk (Score < 4) 332 333 388

For sake of consistency with the SEPA risk assessment protocol developed by Ian Fozzard, and from the maps and this analysis of the data, a deposition value of 1.5 keqH+ ha-1 yr-1 has been used for mapping lake acidity threshold scores (as centroid points) against the polygons of susceptible SSSIs - see Section 4.4.4. 3.2.3 Methodology for eutrophication risk class The eutrophication risk assessment for lakes has been calculated using an export coefficient based model incorporating the catchment P losses related to land cover, stock density and human population. The input data for each lake assessment is derived from the UK National Lakes Inventory. For each lake catchment: Ploadhuman = surpop91 x export coefficient (0.38) where surpop91 = 1991 population census data for the catchment Ploadland-cover = ∑(catchment area x %LCi x export coefficienti) where %LCi = proportion of catchment covered by land cover type i export coefficienti = P export coefficient for land cover type i Ploadanimals = ∑ (numberi x export coefficienti x 100) / (%catchment with available data) where numberi = number of particular type of animal i export coefficienti = P export coefficient associated with animal i Total P load = Ploadhuman + Ploadland-cover + Ploadanimals Total P loaddiffuse = (0.2 x Ploadhuman) + Ploadland-cover + Ploadanimals Where 0.2 is chosen because the maximum amount of P which could be removed from point sources using generally available current technology is about 80%. Inflow concentration = totalPload x 106 / Discharge (m3 yr-1) Where, discharge (m3 yr-1) is derived from: (mean annual rainfall – evapotranspiration loss) x catchment area Using the OECD estimation of mean annual total P concentration (not differentiating between deep and shallow lakes), i.e. P concentrationOECD = 1.55 x (inflow concentration)0.82 / (1+√(retention time)) Where retention time = lake volume / discharge. NB. Actual data on lake volume are only available for a small number of lakes. Mean depth and hence volume, were estimated using a simple algorithm relating depth to lake area (Hughes et al., 2004). As a result the estimation errors can be quite high in some cases.

15

The risk class is then given by Vollenweider classes, i.e. Criterion OECD-TP < 4 µg l-1 OECD-TP < 10 µg l-1 OECD-TP < 35 µg l-1 OECD-TP < 100 µg l-1 OECD-TP > 100 µg l-1

Class 1 2 3 4 5

Two sets of risk classes have been generated, one for total P and one for diffuse P (P loaddiffuse)

3.2.4 Effect of using total and diffuse P loading on P eutrophication risk class for lakes The outcome of the two approaches to P risk assessment using total P load and total diffuse loading are compared in Figure 3.2.

350

300

No. of lakes

250

200

150

100

50

0 2

3

4

5

Risk class Total P

Diffuse P

Figure 3.2 Histogram showing the distribution of risk classes for modelled total P loading and modelled diffuse P loading. The effect of using the modelled diffuse load compared to total P load is to reduce the number of lakes in class 5 by 25 and redistribute these into classes 3 and 4. Overall the difference between the two methods is very small; 25 lakes amounts to about 4% of the total population of 599 Welsh lakes. The result probably reflects the upland nature of the majority of Welsh lakes with catchments containing very small human populations. On the basis of this analysis of the data, the risk classes derived from modelled diffuse P loading have been used for mapping as centroid points against the polygons for susceptible SSSIs – see Section 4.4.4.

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4.

MAPPING METHODS

4.1 Background The maps for the report were produced using a Geographical Information System (GIS). A GIS is a computing environment which allows the user to handle geographically referenced data. Data can be captured, processed, analysed and output in the form of maps and /or tables. The GIS system used for the work was ArcGIS (version 8.3), mounted on a DELL Dimension 8300 personal computer. Map data are held in a number of files which contain information about the points or linework and their geographical location. These files are referred to as shape files. Associated with the shape files are dBASE IV files. These are spreadsheets which contain data about the lines, points or polygons in the shape files. Using tools in ArcGIS a map can be interrogated resulting in new maps and tables being generated.

4.2 Data provision 4.2.1 Environment Agency data CCW provided a number of Environment Agency GIS data files as shape files:Phosphate GQA classes 2001 (vector data) Average suspended solids concentrations (point data) Cypermethrin Maximum Admissible Concentration excedences 1995-2002 (point data) 4.2.2 CCW data CCW provided:GIS data as shape files showing SSSI boundaries EXCEL spreadsheets showing:Qualifying water dependant species for each SSSI Qualifying water dependant habitats for each SSSI 4.2.3 Supporting data sets Other data sets used:CEH LCM2000 (Land Cover Map 2000) CEH DEM (Digital Elevation Model) Freshwater Sensitivity Classes (derived by Hornung et al., 1995) Acid deposition data from the National Focal Centre at CEH Monkswood. Annual deposition of non-seasalt sulphur, reduced and oxidised forms of nitrogen at 5 x 5 km square resolution. Lakes data derived from the National Lakes Inventory (all lakes in Wales with an area exceeding 1 ha).

4.3 Pollutant pressure maps The first stage in identifying and mapping SSSIs in Wales at risk from diffuse pollution was to create maps showing the level of pressure exerted by each of the diffuse pollutants. Two broad approaches were used to generate these maps depending upon the available data and the state of development of risk assessment protocols. For cypermethrin sheep dip and suspended sediments point data were used to create the pressure maps whilst GQA river reach data were used for river phosphate. For lake phosphorus, and both river and lake acidity

17

the risk assessment protocols described in Chapter 3 were used as the basis of the pressure maps. The methods used to map each diffuse pollutant are described below. 4.3.1 River phosphate Maps of threshold scores for river phosphorus were created from the GQA data supplied by the Environment Agency Wales mapped to individual river reaches (stretches). Following discussion between EAW and CCW it was decided that river reaches with GQA scores of 3 to 6 (inclusive) would be classed as potentially posing a risk to a water dependent SSSI. River reaches with a score greater than or equal to 3 were selected from the GQA map to create a map showing only these reaches. 4.3.2 Cypermethrin sheep dip in rivers The maps of sheep dip failures (ie points in the river network where the Maximum Admissible Concentration was exceeded) for years 1997 to 2002 were supplied by the Environment Agency Wales. 4.3.3 Suspended sediments in rivers Maps of suspended sediment concentrations for individual sites were supplied by the Environment Agency Wales. 4.3.4 River acidity Using the protocol described in Section 3.2, acidity threshold scores were modelled for river catchments spaced at one kilometre intervals along the 1:250,000 scale version of the CEH Intelligent River Network (Dawson et al., 2002). Catchments were created by splitting up the network into one kilometre stretches. For each stretch, the downstream end was identified as a point and extracted. Using standard GIS functions, each identified point was used to locate a cell on the flow accumulation grid (a spatial dataset which is a grid where each cell value represents the number of cells flowing into it). A second GIS function was used to generate a catchment, the boundary being defined by cells with no other cells flowing into them. The catchment is converted into a polygon and stored with the ID of the 1 km stretch. All the individual catchment polygons were combined into one shape file. Next acid deposition, freshwater sensitivity classes and CEH LCM2000 map data were imported into ArcGIS. Using ArcGIS functions an acidity threshold score was calculated for each catchment (Section 3.2) which was assigned to the respective one kilometre stretch of the 1:250,000 scale version of the CEH Intelligent River Network. A selection was made of river stretches with an acidity threshold score of four or more to create a map containing only these stretches. 4.3.5 Lake acidity and phosphorus pressure maps Acidity threshold scores for lakes were calculated within MS Access using the protocol described in Section 3.2.1 and data from the National Lakes Inventory. Threshold scores were provided as point data representing the centroid of the water body. A similar procedure (Section 3.2.3) was used for calculating phosphorus pressure scores which were supplied as point data representing the centroid of the water body.

18

4.4 Linking susceptibility ranking with water dependent features The next stage in producing the maps was to identify and map SSSIs containing water dependent features and relate these to the susceptibility rankings for individual species described in Chapter 2. 4.4.1 Definition of water dependent features For the purposes of this study, water dependent features were defined according to the criteria presented in Table 4.1. Table 4.1 Ecological criteria for identifying water dependent Habitats and Species. SPECIES

HABITATS

Criteria 1: Aquatic species living in surface Criteria 1: Habitats which consist of waters for the whole of their life cycle (e.g. surface water or occur entirely within bottle-nose dolphin, freshwater pearl mussel) surface water (e.g. oligotrophic waters; Rananculus Habitat. Criteria 2: Species with at least one aquatic life stage dependent on surface water (i.e. species that use surface water for breeding; incubation, juvenile development; sexual maturation, feeding or roosting)

Criteria 2: Habitats which depend on frequent inundation by surface water, or on the level of groundwater (e.g. alluvial alder wood, wetlands, blanket bog, fens)

Criteria 3: Species that rely on the non- Criteria 3: Non-aquatic habitats which aquatic but water-dependent habitats relevant depend on the influence of surface water under 2 and 3 in the habitats column. e.g. spray, humidity (bryophyte-rich gorges)

The priority categories for mapping were those species and habitats fulfilling Criteria 1 or 2, as they are most liable to be impacted upon by deterioration in water quality due to diffuse pollution. Many of the species and habitats in criteria 3 are dependent upon aquatic processes which occur irrespective of water quality, and they have therefore been excluded. 4.4.2 Mapping SSSIs containing water dependent features A dBASE IV table was created containing all the SSSIs with water dependent species or habitats. This involved combining all the spreadsheets for the different species and habitat criteria. As an SSSI could have more than one water dependent species or habitat recorded any duplicate records were deleted. This left a list of SSSIs recorded as having water dependent species or habitats. A dBASE IV table of these data was imported into ArcGIS. A map showing all the SSSIs in Wales was also imported. The SSSIs with water dependent species or habitats were then selected from the full SSSI dataset. A new map was then created containing only SSSIs having water dependent species or habitats. 4.4.3 Combining water dependent features, pollutant susceptibility and SSSIs A dBASE IV table was created containing the diffuse pollutant susceptibility rankings for each of the water dependent species, species groups and habitats (Appendix 1 Table 1). This table was imported into ArcGIS and part of it is shown below in Table 4.2.

19

The complete list of qualifying water dependent species and habitats for each SSSI was also imported as a dBASE IV table. This table contains all the Criteria 1 and 2 water dependent species and habitats for each SSSI. i.e. a SSSI could have more than one qualifying species or habitat. A section of this table is also shown in Table 4.2. In order to select which SSSIs are susceptible to diffuse pollution, a series of relates was setup between the tables and maps. A relate sets up a link between one or more spreadsheets based on common fields, allowing, for example, results of searches in one table to be related to another table. A relate was first created in ArcGIS between the ‘susceptibility table’ and the ‘SSSI species and habitats table’ using CEH Name as the common column (see Table 4.2). For example, a selection can be made from the ‘susceptibility table’ which identifies all species and habitats with high and medium levels of susceptibility to acidity. Relating this selection to the second table, identifies all the rows containing the susceptible species or habitats and the SSSIs they are present in. A second relate was set up using Site Code as the common column between the ‘SSSI species and habitats’ table and the map of all SSSIs with water dependent species or habitats. Thus by relating the initial selection from the ‘susceptibility table’ to the ‘species and habitats’ table and thence to the water dependent species and habitats map, a new map can be created showing the SSSIs in Wales which contain species and / or habitats which are susceptible to a particular type of diffuse pollutant.

20

Table 4.2 Section of dBASE IV table containing pollutant susceptibility rankings for each water dependent species and habitat linked to table containing SSSIs.

CCW name

CEH name

Sediment

Sheep dip

Phosphorus

Acidity

Atlantic salmon

Atlantic salmon

High

High

Med

High

Brook lamprey

Brook lamprey

Low

High

Med

Med

Bullhead

Bullhead

Med

Med

Low

Low

Floating Water-plantain

Floating Water-plantain

Med

Low

Med

Med

A marine snail

Freshwater invertebrate

Med

High

Med

High

A stonefly

Freshwater invertebrate

Med

High

Med

High

A water beetle

Freshwater invertebrate

Med

High

Med

High

Great Silver Water Beetle

Freshwater invertebrate

Med

High

Med

High

Medicinal Leech

Freshwater invertebrate

Med

High

Med

High

Freshwater Pearl Mussel

Freshwater Pearl Mussel

High

High

High

Med

Great Crested Newt

Great Crested Newt

Low

Med

Low

Low

SH780612

CEH_Name Fen (topogenous mires in valleys, basins and

SSSI_Name Fen (topogenous mires in valleys, basins and

SH780612

Marshy grassland

Marshy grassland

SH780612

Standing water

Standing water

SH780612

Swamp

Swamp Grey Heron

Site Code

Site ID

Site Name

Grid Ref

31WAA

640

Mwyngloddiau a Chreigiau Gwydyr

640

Mwyngloddiau a Chreigiau Gwydyr

31WAA

640

Mwyngloddiau a Chreigiau Gwydyr

31WAA

640

Mwyngloddiau a Chreigiau Gwydyr

31WAA

31WAB

957

Benarth Wood

SH788770

Inland and riverine bird

31WAB

957

Benarth Wood

SH788770

Running water

Running water

31WAC

406

Cae'r Felin

SH842486

Marshy grassland

Marshy grassland

31WAD

430

Eryri

SH668606

Atlantic salmon

Atlantic salmon Blanket bog (other ombrogenous mire) Fen (topogenous mires in valleys, basins and

31WAD

430

Eryri

SH668606

31WAD

430

Eryri

SH668606

Blanket bog (other ombrogenous mire) Fen (topogenous mires in valleys, basins and

31WAD

430

Eryri

SH668606

Floating Water-plantai

Floating Waterplantain

31WAD

430

Eryri

SH668606

Flush and spring (soligenous mire)

Flush and spring (soligenous mire)

31WAD

430

Eryri

SH668606

Marshy grassland

Marshy grassland

31WAD

430

Eryri

SH668606

Running water

Running water

31WAD

430

Eryri

SH668606

Standing water

Standing water

31WAD

430

Eryri

SH668606

Swamp

Swamp

31WAD

430

Eryri

SH668606

Wet heath

Wet heath

21

4.4.4 Combining site susceptibility and pollutant pressure The final stage of mapping was to identify from amongst the SSSIs containing susceptible species and / or habitats those where diffuse pollution is considered to pose a threat. This was done by overlaying the SSSIs containing susceptible species and / or habitats for a particular pollutant on to the respective pollutant pressure map. Those SSSIs which intersect with the pollutant pressure data above a specified threshold were selected as being at risk. The data and methods for individual pollutants are described below. River phosphate The SSSIs containing water dependent species and habitats with medium or high susceptibility to phosphate were selected. These SSSIs were overlayed on the map of river reaches with a threshold class of three or greater for phosphate GQA 2001 data. Those susceptible SSSIs which intersected the phosphate data at or above the threshold class were mapped as being at risk from phosphate pollution (Figure 5.3). Cypermethrin sheep dip in rivers The SSSIs containing water dependent species and habitats with medium or high susceptibility to cypermethrin sheep dip were selected. A 500 metre buffer zone was created around these SSSI boundaries. This was done to take into account that some sheep dip failure sites although not in a SSSI could be located on streams which flowed into a SSSI and could possibly have an influence. A selection was then made of susceptible SSSIs containing sheep dip failure sites or having them within 500 metres (Figure 5.5). Suspended sediments in rivers The SSSIs containing water dependent species and habitats with medium or high susceptibility to suspended sediments were selected. A 500 metre buffer zone was created around these SSSI boundaries. This was done to take into account that some suspended sediment sample sites although not in a SSSI could be located on streams which flowed into a SSSI and could possibly have an influence. A selection was then made of susceptible SSSIs containing suspended solid sites or having them within 500 metres (Figure 5.7). River acidification The SSSIs containing water dependent species and habitats with medium or high susceptibility to acidity were selected. These SSSIs were overlayed on the 1:250,000 scale version of the CEH Intelligent River Network displaying 1 km reaches with acidity threshold scores of four or greater. The susceptible SSSIs which intersected the selected segments of the CEH Intelligent River Network data were mapped as those at risk from acidification (Figure 5.9). Lake acidity The SSSIs containing water dependent species and habitats with medium or high susceptibility to acidity were selected. The acidity threshold scores for all lakes falling within the boundaries of the susceptible SSSIs were mapped as a point representing the centroid of the water body (Figure 5.11). Lake phosphorus The SSSIs containing water dependent species and habitats with medium or high susceptibility to phosphate were selected. The phosphorus threshold scores for all lakes falling within the boundaries of the susceptible SSSIs were mapped as a point representing the centroid of the water body (Figure 5.14).

22

4.5 Wetlands A novel methodology was developed to provide a preliminary risk assessment of eutrophication risk to wetlands. The first part of the procedure was to identify appropriate habitat types from The Habitats of Wales (Phase 1) data set to define ‘wetland’ areas in Wales (Table 4.3). The next stage was to identify the wetland areas which intersect SSSIs designated for water-dependent habitats and/or species. This selection was further refined to extract those SSSIs designated for water-dependent habitats and/or species which are deemed as being at risk from eutrophication and which intersect a wetland area with a modelled phosphate risk assessment score of 4 or greater (Figure 5.17). Table 4.3 Phase 1 habitats used to define ‘wetlands’ in Wales. Code B.5 B.5.1 B.5.2 D.2 D.6 E.1.6.1 E.1.6.2 E.1.7 E.2 E.2.1 E.2.2 E.2.3 E.3 E.3.1 E.3.1.1 E.3.2 E.3.2.1 E.3.3 E.3.3.1 F.1 F.1.1 F.2.2

Habitat marshy grassland marshy grassland Juncus dominated marshy grassland Molinia dominated wet heath wet heath/acid grassland mosaic blanket bog raised bog wet modified bog flush and spring acid/neutral flush basic flush brophyte-dominated spring Fen valley mire modified valley mire basin mire modified basin mire flood-plain mire modified flood plain mire Swamp scattered swamp inundation vegetation

The following GIS-based methodology was developed for the wetland risk assessment. The CEH Wallingford 1:50,000 flow accumulation grid was used to estimate the catchment boundary, for each wetland site in turn. The catchment area for each 50x50m square within a SSSI boundary was obtained and then all the catchments for a site were added together to give a single catchment encapsulating all the subcatchments. The catchment area was then used to select and extract appropriate GIS layers for MAFF animal statistics (cattle, sheep, pigs), population from the 1995, SURPOP data, land cover from the 1990 land cover map and hydrologically effective rainfall (HER) using data supplied by CEH Wallingford. The number of animals, human population, area of each land use type and total volume of HER to the catchment was estimated from these base data and converted to P loads using appropriate export coefficients (Hilton et al., 2002). In order to allow comparisons between sites, the 23

loads were turned into pseudo-concentrations by dividing by the hydrologically effective rainfall. There are no recognised classes for wetland quality with respect to eutrophication. In the absence of any other classification system the Vollenweider classes have been applied but it should be recognised that the relevance of these limits to wetlands is not known since the limits were derived for lakes under assumptions which are not relevant to wetlands. Reports of the effects of nutrient rich runoff into wetlands indicate that significant effects can be seen in localised areas near the input, suggesting that a wetland area will reduce in size as a result of eutrophication, rather than develop algal communities like a lake. However, the Vollenweider are not likely to be orders of magnitude away from the relevant class boundaries for wetlands and, as such, give an indication of the sites most at risk. It is likely to be the sites in the middle of the range which are likely to be missed.

24

5.

DIFFUSE POLLUTION MAPS

5.1 Introduction The maps resulting from the risk assessments described in Chapters 3 and 4 are reproduced in this chapter and are provided to CCW as GIS Shape files. 5.2 Map outputs

Figure 5.1

All SSSIs within which water-dependent criteria 1 or 2 habitats and/or species are identified as site features of conservation importance

25

Figure 5.2

Phosphate threshold scores for the Welsh river network based on the GQA monitoring programme. On river sections with GQA scores of 3 or greater habitats and species that are susceptible will be at significant risk

26

Figure 5.3

SSSIs containing rivers within which water-dependent habitats and/or species have been identified as being at risk from phosphate pollution or eutrophication.

27

Figure 5.4

All Welsh sheep dip monitoring sites indicating whether the Maximum Admissible Concentration was exceeded in any year between 1997 and 2001 on the Welsh river network

28

Figure 5.5

SSSIs containing rivers within which water-dependent habitats and/or species have been identified as being at risk from sheep dip pollution based on the presence of exceedances within the site or within a 500 m buffer of the site

29

Figure 5.6

Annual mean suspended sediments concentrations for all monitoring locations on the Welsh river network. River locations with mean values greater than 20 mg l-1 will put habitats and species at risk

30

Figure 5.7

Annual mean suspended sediments concentrations for monitoring locations in SSSIs containing rivers, or those with locations within a 500 m buffer of the site for which water-dependent habitats and/or species have been identified as being at risk from suspended sediments. River locations with mean values greater than 20 mg l-1 will put habitats and species at risk 31

Figure 5.8

Acidity threshold scores for the Welsh river network based on a modelled acidification risk assessment. On river sections with scores of 4 or greater habitats and species that are susceptible will be at significant risk

32

Figure 5.9

SSSIs within which water-dependent criteria 1 or 2 habitats and/or species have been identified as being at risk from acidification from a modelled acidification risk assessment

33

Figure 5.10

Acidity threshold scores for Welsh lakes, based on a modelled acidification risk assessment for acid deposition of 1.5 keq ha-1 yr-1. In lakes with scores of 4 or greater habitats and species that are susceptible will be at significant risk.

34

Figure 5.11

Acidity threshold scores for lakes within SSSIs designated for waterdependent habitats and/or species that have been identified as being as at risk from acidification and containing a lake. Based on a modelled acidification risk assessment for acid deposition of 1.5 keq ha-1 yr-1. In lakes with scores of 4 or greater habitats and species that are susceptible will be at significant risk 35

Figure 5.12

SSSIs designated for water-dependent habitats and/or species that have been identified as being as at risk from acidification and contain a lake with a score of 4 or greater. Based on a modelled acidification risk assessment for acid deposition of 1.5 keq ha-1 yr-1 36

Figure 5.13

Phosphate threshold scores for Welsh lakes based on a modelled phosphate risk assessment. In lakes with scores of 4 (equivalent to 35 µg l-1 P) or greater, habitats and species that are susceptible will be at significant risk. Some Oligotrophic lakes will be at risk at lower scores 37

Figure 5.14

Phosphate threshold scores for lakes within SSSIs designated for waterdependent and/or species that have been identified as being at risk from eutrophication and containing a lake, based on a modelled phosphate risk assessment. In lakes with scores of 4 (equivalent to 35 µg l-1 P) or greater habitats and species that are susceptible will be at significant risk

38

Figure 5.15

SSSIs designated for water-dependent habitats and/or species that have been identified as being as at risk from eutrophication and containing a lake with a score of 4 or greater, based on a modelled phosphate risk assessment

39

Figure 5.16

Modelled phosphate risk assessment score categories for wetland areas (defined from Phase I maps) which intersect SSSIs designated for waterdependent habitats and/or species

40

Figure 5.17

SSSIs designated for water-dependent habitats and/or species that have been identified as being as at risk from eutrophication which intersect a wetland area with a modelled phosphate risk assessment score of 4 or greater 41

6.

EVALUATING THRESHOLD SCORE MODELLING FOR LAKES AND RIVERS

6.1 Testing the acidity risk assessment for Welsh lakes The effectiveness of the risk assessment methodology for distinguishing between lakes at risk from acidification and those not at risk was investigated using a subset of Welsh lakes for which lake water alkalinity data were available. Lake water alkalinity is a useful measure of the sensitivity of a lake to acidifcation, as it measures the capacity of the lake water to buffer changes in acidity. Lakes with a low alkalinity are more susceptible to acidification although there is debate as to what value defines an acid sensitive lake or one at risk of acidification. Testing the risk assessment method against observed lake chemistry data may shed some light on this definition. 6.1.1 Welsh lakes data The risk assessment methodology was applied to 599 lakes in Wales. These are all the Welsh lakes with an area greater than 1 ha. Lake catchment data were taken from the National Lakes Inventory database and the risk assessment was performed as described in Section 3.1. Lake water chemistry data were extracted from a number of sources. The primary source was the DEFRA Critical Loads and Metals (CLAM) database hosted by University College London. This provided data collected from the following studies: Wales Random Survey (Henriksen et al., 1997), the Snowdonia survey (Kernan 1995), within square variability study (Curtis et al., 1995) and the Nitrogen survey (Curtis et al., 1998). In addition, data were provided by the CCW Migneint lakes study (Carvalho et al., 2003); the Welsh Acid Waters Survey (Stevens et al., 1997) and the CEH GANE Lakes project funded by the NERC (CEH Unpublished data). With the exception of the data contained in the GANE Lakes project and the CCW Migneint study which were collected in 2001 / 2002, all the other lake chemistry samples were collected over a period of years between 1995 and 1998. For some surveys (eg Wales Random Survey) only one sample was collected, whereas some projects (eg Welsh Acid Waters Survey) sampled much more frequently (up to monthly). A brief analysis of sites with monthly data revealed that a number of the more alkaline lakes showed strong seasonal variation in alkalinity concentration over the year with autumn/winter minima. As this exercise was focused on acidification risk, alkalinity data for the period between October and April were used in the assessment. This period represents the time of greatest acid sensitivity and coincides with the “winter” season defined for the Welsh Acid Waters Survey. Applying this seasonal criteria resulted in 168 lakes being selected from the various data bases. Where more than one sample had been collected in the “winter” season, a single mean value was generated. The lake chemistry and risk assessment data bases were merged to provide a final combined set for which risk assessment and chemistry data were available. This required careful matching of lake names (where available) and national grid references. Some discrepancies in both descriptors were noted and verification on OS maps was required in a number of instances. Thirty four lakes from the chemistry / risk assessment data base of 168 lakes were excluded as these had an area of less than 1 ha. The alkalinity data from the remaining 134 lakes were checked for “internal” consistency by plotting against pH, non-seasalt calcium concentration and charge balance acid neutralising capacity. As a result, one lake in south Wales (Llan Bwlch Llyn lake) was rejected on account of its anomalous chemistry (calcium

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concentration = 10047 mg l-1; sulphate concentration = 5490 mg l-1), leaving a final test data set of 133 lakes. 6.1.2 Results The test data set represents 22% of the population of lakes in Wales with an area greater than 1 ha. An analysis of the distribution of acidity threshold scores revealed that the test data set had a greater proportion of scores greater than 3 compared with the entire population of Welsh lakes (Table 6.1), indicating bias towards greater acid sensitivity. Table 6.1 Distribution of acidity threshold scores for the data set of all Welsh lakes with an area > 1 ha and the test data set. (Acid deposition threshold = 1.5 keq ha-1 yr-1) Acidity threshold score 1-3 4 5 6

Wales data set (599 lakes) No. of lakes % 388 65 161 27 46 8 4 0.8 (High Status) assume no risk (0) > 0.5 (Good Status), assume low risk (1) > 0.33 (Mod Status), assume moderate risk (2) < = 0-.33 (Poor or worse), assume high risk (3)

Confidence was assessed on the basis of the catchment area. Where catchment area was > 10 km2 confidence was assumed to be Moderate (2). Where catchments area was > 2 km2 confidence was assumed to be Low (1). Catchments less than 2 km2 were assumed to be too small to be assessed at a site specific level (no confidence 0). (Note, with current models it is assumed that no high confidence estimates of TP load can be made) Measured TP (taken from CEH spreadsheet and assumed to be annual mean) was also compared with the target by deriving an EQR as above. These data are taken to be a provisional measure of impact (Provisional Status). In this instance all impact measures were assumed to have high confidence. In the future additional measures of impact can be included in this process (eg palaeolimnology) A combination of pressure and impact assessment was made by taking the greater confidence value of the impact or pressure assessment. Together with its estimate of confidence. A final status assessment was made using a matrix to combine Pressure and Confidence according to the 2nd approach suggested by Graeme Storey (3 Jan 04) for the WFD. Note this method is still very provisional (see table on next slide for illustration).

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Pressure H 3 Confidence 2 1 0

M 3 6 5 4 3

L 2 5 4 3 2

N 1 -2 -1 0 1

0 -3 -2 -1 0

Matrix used to derive final risk H M L 3 2 1 0

= High pressure = Moderate pressure = Low pressure = High confidence = Moderate confidence = Low confidence = Negligible confidence

Red – Water body considered to be at risk of failing target. Orange – Water body considered to be at risk of failing target but where information is insufficient. Yellow – Water body considered to be not at significant risk of failing target on the basis of available information. Blue – Water body not considered at significant risk of failing target. Note: Matrix derived by adding elements of H and M pressure and subtracting Pressure from Confidence for L and N. Values then used via lookup table to assign final risk. The percentage of TP load derived from agriculture is also given. Thus those sites shown to be at risk can be compared with this value to establish the possible role of agriculture.

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The resulting maps are shown below.

Figure A.1 Application of Provisional Risk Assessment to all lakes in Wales Shows sites thought to be at risk after consideration of confidence of assessments. Highest confidence is associated where impact data (measured TP ) are available. Lowest confidence is where impact is estimated from export model and catchment area is < 2 km2.

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Figure A. 2 Application of Provisional Risk Assessment to all lakes in Wales from Agriculture. As above but only shows sites where agricultural sources are > 75% of total TP load

Figure A.3 Application of Provisional Risk Assessment to all lakes in Wales Pressure from agriculture >75% total load (regardless of confidence) Shows sites where agricultural sources are > 75% of total TP load. These data represent pressures and have not been converted to risk as no confidence assessment has been included.

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Figure A.4 Application of Provisional Risk Assessment to all lakes in Wales Pressure from agriculture + people (regardless of confidence) As for Figure 2, but based on the load assessed from agricultural statistics and population data. Points to note. • The substantial effect of considering the confidence of the assessments, far fewer sites are shown to be at risk than would be concluded from pressure data. • The use of site specific targets, rather than a 35µg l-1 standard threshold. This identifies more sites in central Wales at high or moderate pressure as many targets are lower. Limitations 1. Method is still under development, current output derived very rapidly using access queries that still need to be checked. 2. Our risk assessment approach plans to use point source data to confirm human P load and other sources. 3. The use of export modelling is still an approach that requires further development. 4. The majority of lakes in this study have very small catchments, many of which are too small for site specific assessments. 5. No attempt has been made to identify non-natural sources of water. Thus the risk assessment is based on catchments derived from topographical data. 6. The final method of combining pressure and impact data has still to be agreed by the programme. Until this is completed results described in this note should be treated as provisional.

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