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Habitat fragmentation, the random sample hypothesis and critical thresholds Henrik AndrPn, Grirnso Wildlife Research Station, Dept of Conservation Biology, Swedish Univ. of Agricultural Sciences (SLU), SE-730 91 Riddarhyttan, Sweden @
[email protected]). Monkkonen and Reunanen (1999) recently reanalysed the data in Andren (1994) and found a stronger effect of landscape type on the probability to reject the random sample hypothesis, than of proportion of suitable habitat in the landscape. Therefore, they concluded that the empirical evidence for a threshold in proportion of suitable habitat is not supported. However, both landscape type and proportion of suitable habitat have very strong and significant effects ( p < 0.0001 for both). The two variables are also confounded and therefore it is difficult to separate between the two. Landscape type and proportion of suitable habitat can be alternative explanations, but more likely both can be important. Furthermore, all effect of landscape type was due to only one particular landscape type, namely forested landscape. If one removes this landscape type from the analyses, then there will be a stronger effect of proportion of suitable habitat than of landscape type (Table I). Thus, I conclude that the proportion of suitable habitat in the landscape is an important factor to be able to reject the random sample hypothesis, which is expected from theoretical models (Andren 1996, Bascompte and Sole 1996, Fahrig 1997, With 1997, With and King 1997, With et al. 1997). But I also agree with Mijnkkonen and Reunanen (1999) that landscape type might be important, which is shown by berg et al.
(1995) and also expected from theoretical models (Stamps et al. 1987, Taylor et al. 1993, With et al. 1997). The landscape type might influence the colonization probabilities of a habitat fragment. The probability of colonization is a combination of distance between habitat fragments, the dispersal distances of a species and the constitution of the matrix. Thus, even if a habitat fragment lies within the species' trivial range, it may not be reachable because the matrix is too hostile to cross (Taylor et al. 1993). Therefore, the distribution of a species in habitat fragments is not only dependent on the proportion of suitable habitat in the landscape, habitat fragment size and distance between habitat fragment but also the type of surrounding habitat. Monkkonen and Reunanen (1999) also argued that species will be lost long before one might reach a critical threshold. These species are often the most threatened ones. Therefore, one should not use the threshold 10-30% of original habitat as a general value in landscape management or conservation of threatened species. I agree with Monkkonen and Reunanen (1999). and it is very important to point out that Andren (1994) analysed different factors that might influence the probability to reject the random sample hypothesis. Andren (1994) concluded that there might be a threshold in the proportion of suitable habitat in the
Table 1. Effects of landscape type and the proportion of suitable habitat in the landscape on the probability to reject the random sample hypothesis. Data from Andren (1994: Appendix). Landscape type was classified into three classes (archipelago, farmland and other landscapes), thus forest landscape was excluded from the analyses. The first step includes only one variable. The deviance refers to the effect of adding a second variable to the model. Variables in the model
G
df
P
suitable habitat +landscape type Landscape type +% suitable habitat
3.55
1
0.059
4.84
2
0.089
%
306
Deviance
df
P
3.22
2
0.20
1.93
1
0.17
OIKOS 84 2 (1999)
Proportion of original habitat in the landscape (%) Fig. 1. Loss of species in relation to habitat loss. The dotted line shows the relationship according to log S = log k + z log A. with a :-value of 0.26. Open and filled circles show the relationship from simulations for two species pools, with small and large mean area requirements, respectively (from Andren 1997 (reproduced with permission) and partly redrawn after McLellan et al. 1986).
landscape below which the species loss or decline in population size was greater than expected from the random sample hypothesis. However. it is very important to point out that also the random sample hypothesis predicts loss of species and a decline in population size as the proportion of original habitat decreases (Dial 1995. Andren 1997). One can predict the species loss in relation to habitat loss, according to the random sample hypothesis. Firstly, one assumes that the total number of individuals for all species living in the original habitat has a one-to-one relationship to the proportion of the original in the landscape. This assumption can easily be tested by a regression between the log (number of individuals) and the log (O/O original habitat in the landscape). The random sample hypothesis predicts a slope of 1 (AndrCn et al. 1997). Secondly, one ignores that the habitat is divided into several smaller fragments and pools all habitat into one large fragment. Then, the number of species restricted to the original habitat will be related to the proportion of original habitat in the landscape with the same equation as species number is related to area, i.e. log S = log k + z log A (Preston 1962, Dial 1995). The random sample hypothesis can be viewed as a null model and therefore gives a minimum of change in species number restricted to the original habitat (Fig. 1). The extinction rate of species in the landscape will initially be low but will increase as the proportion of original habitat decreases (Fig. 1). The order of species that will disappear from the landscape with decreasing proportion of habitat in the landscape will depend on their abundance. the rarest species being the first to go. The slope in the species-area relationship ( r ) will depend on the evenOIKOS 84.2 (1999)
ness of the distribution of individuals among species (Preston 1962, May 1975). Koopowitz et al. (1994) used a grid based simulation model to predict the loss of plant species in 17 Neotropical countries in relation to the reduction of forested land. Dial (1995) compared the results from the simulation by Koopowitz et al. (1994) with a random expectation from a lognormal species-abundance distribution (Preston 1962). The relationship between fraction of habitat remaining and fraction of species lost was almost identical for the two models. Thus. the simple model log S = log k + r log A. with a I-value around 0.26 (range 0.12-0.33) might be a very good description of the loss of species as the proportion of a certain habitat decreases in a landscape (Dial 1995). Similarly, McLellan et al. (1986) simulated the loss of species from the landscape as the proportion of suitable habitat is lost. They used two hypothetical species pools with different mean area requirements and dispersal. The loss of species was low at the beginning of habitat loss but increased as the proportion of lost habitat was above 70-80% depending on the species pool (Fig. 1). However, the difference between their simulation and the expected species loss based on a random sample is not very large for the species pool with large mean area requirement (Fig. 1). The difference appears only at a high degree of habitat loss that might represent a critical threshold. For the species pool with small mean area requirement, the null model of habitat loss, i.e. a species-area relationship with a r-value of 0.26 actually, overestimated the species loss (Fig. 1). T o conclude, predicting the effects of habitat fragmentation on the distribution of species is an important task in conservation biology. Critical thresholds in proportion of original habitat where the loss of species or decline in population sizes is particularly large are expected from theoretical models (Lande 1987. Andren 1996, Bascompte and Sole 1996. Fahrig 1997. With 1997, With and King 1997, With et al. 1997) and are important to find. However, these thresholds will probably vary between landscape types, species, species groups, etc. Furthermore, for the preservation of species there will be extinction before these thresholds are reached and the species lost will be the most sensitive ones. However. it might be very hard to separate between effects of habitat fragmentation and pure habitat loss in landscapes with a fairly high proportion of original habitat, as the prediction from the two models might be very similar. i.e. one has very low statistical power to separate between the two models (Andren 1996). Finally, Fahrig (1997) found that the effects of habitat loss was very much stronger than the effects of habitat fragmentation on the risk of extinction. Therefore, one of the most important efforts in conservation biology should be to stop the loss of habitat and habitat restoration (Fahrig 1997). 307
.Ickno~vledgements - The study h a s supported by the Swedish Environmental Protection Agency and the private foundations "Olle och Signhild Engkvists stiftelser".
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Koopowitz. H., Thornhill, A. D. and Andersen, M. 1994. A general stochastic model for the prediction of biodiversity losses based on habitat conversion. Conserv. Biol. 8: 425-438. Lande, R. 1987. Extinction thresholds in demographic models of territorial populations. - Am. Nat. 130: 624-635. May, R. M. 1975. Patterns of species abundance and diversity. - In: Cody, M . L. and Diamond. J. W. (eds), Ecology and evolution of communities. Belknap Press, Cambridge, MA, pp. 81-120. McLellan. C. H., Dobson, A. P., Wilcove. D. S. and Lynch. J. F. 1986. Effects of forest fragmentation on new- and old-world bird communities: empirical observations and theoretical implications. In: Verner. J., Morrison, M. L. and Ralph. C. J. (eds), Wildlife 2000. Modeling habitat relationships of terrestrial vertebrates. Univ. of Wisconsin Press, Madison, W1, pp. 305-313. Monkkonen. M. and Reunanen, P. 1999. On critical thresholds in landscape connectivity: a management perspective. - Oikos 84: 302-305. Preston. F. W. 1962. The canonical distribution of commonness and rarity. - Ecology 43: 185-215. Stamps, J. A,, Buechner, M and Krishnan, V. V. 1987. The effect of edge permeability and habitat geometry on emigration from patches of habitat. - Am. Nat. 129: 532-552. Taylor. P. D.. Fahrig. L.. Henein. K. and Merriam. G. 1993. -connectivity is :vital element of landscape structure. Oikos 68: 571-573. With, K. A. 1997. The a ~ ~ l i c a t i oofn neutral l a n d s c a ~ emodels in conservation bioloiy. - Conserv. Biol. 11: 1669- 1080. With, K. A. and King, A. W. 1997. The use and misuse of neutral landscape models in ecology. - Oikos 79: 219-229. With. K. A., Gardner, R. H. and Turner, M. 1997. Landscape connectivity and population distributions in heterogeneous environments. Oikos 78: 151-169. -
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