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11 - Climate envelope models in systematics and evolutionary research: theory and practice

from Section 3 - Biogeography, migration and ecological niche modelling

Published online by Cambridge University Press:  16 May 2011

By
D. Rödder ,
S. Schmidtlein ,
S. Schick  and
S. Lötters
Edited by
Trevor R. Hodkinson ,
Michael B. Jones ,
Stephen Waldren  and
John A. N. Parnell
D. Rödder
Affiliation:
Trier University, Germany
S. Schmidtlein
Affiliation:
Bonn University, Germany
S. Schick
Affiliation:
Trier University, Germany
S. Lötters
Affiliation:
Trier University, Germany
Trevor R. Hodkinson
Affiliation:
Trinity College, Dublin
Michael B. Jones
Affiliation:
Trinity College, Dublin
Stephen Waldren
Affiliation:
Trinity College, Dublin
John A. N. Parnell
Affiliation:
Trinity College, Dublin
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Summary

Abstract

Climatic information from distribution data of a species can be used to compute its climate envelope. Climate envelope models (CEMs) are employed to predict potential geographic ranges of species as a function of climate by comparing the climate envelope with climatic conditions at locations of unknown occurrence. CEMs find their way into applied sciences such as conservation management and risk assessment, but they also perform well in systematics and evolutionary research, often supplementary to other methods. Although the application of CEM approaches is developing rapidly, there is a considerable lack of theoretical background. We summarise theoretical assumptions behind CEMs, describe how they work and discuss possible pitfalls when interpreting results. In addition, we provide examples from our ongoing research on the Afrotropical reed frogs, genus Hyperolius (Hyperoliidae). We delimit the potential distribution of a recently recognised taxon within the Hyperolius cinnamomeoventris species complex and propose possible speciation scenarios for H. mitchelli and H. puncticulatus.

Introduction

Climate and the geographic distribution of species

It is known that climate elements and factors have an important influence on the distribution of plant and animal species; likewise, the ecological niche concept has been well discussed (Grinnell, 1917; James et al., 1984). In recent years, there has been a remarkable increase in availability of information on climatic parameters in geographic space, including remote regions. There has also been improved recording of species distribution data.

Type
Chapter
Information
Climate Change, Ecology and Systematics , pp. 243 - 264
Publisher: Cambridge University Press
Print publication year: 2011

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References

Araújo, M. B. and Guisan, A. (2006). Five (or so) challenges for species distribution modelling. Journal of Biogeography, 33, 1677–1688.CrossRefGoogle Scholar
Araújo, M.B. and Pearson, R. G. (2007). Equilibrium of species' distributions with climate. Ecography, 28, 693–695.CrossRefGoogle Scholar
Araújo, M. B., Cabeza, M., Thullier, W., Hannah, L. and Williams, P. H. (2004). Would climate change drive species out of reserves? An assessment of existing reserve-selection methods. Global Change Biology, 10, 1618–1626.CrossRefGoogle Scholar
Beaumont, L. J., Hughes, L. and Poulsen, M. (2005). Predicting species distributions: use of climatic parameters in BIOCLIM and its impact on predictions of species' current and future distributions. Ecological Modelling, 186, 250–269.CrossRefGoogle Scholar
Beaumont, L. J., Hughes, L. and Pitman, A. J. (2008). Why is the choice of future climate scenarios for species distribution modelling important?Ecology Letters, 11, 1135–1146.CrossRefGoogle ScholarPubMed
Broennimann, O., Treier, U. A., Müller-Schärer, H. et al. (2007). Evidence of climatic niche shift during biological invasion. Ecology Letters, 10, 701–709.CrossRefGoogle ScholarPubMed
Busby, J. R. (1991). BIOCLIM: a bioclimatic analysis and prediction system. In Nature Conservation: Cost Effective Biological Surveys and Data Analysis, ed. Margules, C. R. and Austin, M. P.. Melbourne: CSIRO, pp. 64–68.Google Scholar
Carnaval, A. C. and Moritz, C. (2008). Historical climate modelling predicts patterns of current biodiversity in the Brazilian Atlantic forest. Journal of Biogeography, 25, 1187–1201.CrossRefGoogle Scholar
Carpenter, G., Gillison, A. N. and Winter, J. (1993). DOMAIN: a flexible modeling procedure for mapping potential distributions of plants and animals. Biodiversity and Conservation, 2, 667–680.CrossRefGoogle Scholar
Dormann, C. F., McPherson, J., Araújo, M. B. et al. (2007). Methods to account for spatial autocorrelation in the analysis of species distributional data: a review. Ecography, 30, 609–628.CrossRefGoogle Scholar
Elith, J., Graham, C. H., Anderson, R. P. et al. (2006). Novel methods improve prediction of species' distributions from occurrence data. Ecography, 29, 129–151.CrossRefGoogle Scholar
Elton, C. (1927). Animal Ecology. London: Sedgwick and Jackson.Google Scholar
Fielding, A. H. and Bell, J. F. (1997). A review of methods for the assessment of prediction errors in conservation presence/absence models. Environmental Conservation, 24, 38–49.CrossRefGoogle Scholar
Fisher, J., Lindenmayer, D. B., Nix, H. A., Stein, J. L. and Stein, J. A. (2001). Climate and animal distribution: a climatic analysis of the Australian marsupialTrichosurus caninus. Journal of Biogeography, 28, 293–304.Google Scholar
Fitzpatrick, M. C., Weltzin, J. F., Sanders, N. J. and Dunn, R. R. (2007). The biogeography of prediction error: why does the introduced range of the fire ant over-predict its native range?Global Ecology and Biogeography, 16, 24–33.CrossRefGoogle Scholar
Flato, G. M., Boer, G. J., Lee, W. G. et al. (2000). The Canadian Centre for Climate Modelling and Analysis global coupled model and its climate. Climate Dynamics, 16, 451–467.CrossRefGoogle Scholar
Frost, D. R. (2010). Amphibian species of the world: an online reference. Version 5.4. New York, NY: American Museum of Natural History. http://research.amnh.org/vz/herpetology/amphibia.
Gordon, C., Cooper, C., Senior, C. A. et al. (2000). The simulation of SST, sea ice extents and ocean heat transports in a version of the Hadley Centre coupled model without flux adjustments. Climate Dynamics, 16, 147–168.CrossRefGoogle Scholar
Graham, C. H., Ron, S. R., Santos, J. C., Schneider, C. J. and Moritz, C. (2004). Integrating phylogenetics and environmental niche models to explore speciation mechanisms in dendrobatid frogs. Evolution, 58, 1781–1793.CrossRefGoogle ScholarPubMed
Graham, C. H., Elith, J., Hijmans, R. J. et al. (2008). The influence of spatial errors in species' occurrence data used in distribution models. Journal of Applied Ecology, 45, 239–247.CrossRefGoogle Scholar
Grinnell, J. (1917). The niche-relationships of the California Thrasher. Auk, 34, 427–433.CrossRefGoogle Scholar
Gu, W. and Swihart, R. K. (2004). Absent or undetected? Effects of non-detection of species occurrence on wildlife-habitat models. Biological Conservation, 116, 195–203.CrossRefGoogle Scholar
Guisan, A. and Thuiller, W. (2005). Predicting species distributions: offering more than simple habitat models. Ecology Letters, 8, 993–1009.CrossRefGoogle Scholar
Guisan, A. and Zimmermann, N. (2000). Predictive habitat distribution models in ecology. Ecological Modelling, 135, 147–186.CrossRefGoogle Scholar
Hanley, J. and McNeil, B. (1982). The meaning of the use of the area under a receiver operating characteristic (ROC) curve. Radiology, 143, 29–36.CrossRefGoogle Scholar
Heikkinen, R. K., Luoto, M., Araújo, M. B. et al. (2006). Methods and uncertainties in bioclimatic envelope modeling under climate change. Progress in Physical Geography, 30, 751–777.CrossRefGoogle Scholar
Hijmans, R. J. and Graham, C. H. (2006). The ability of climate envelope models to predict the effect of climate change on species' distributions. Global Change Biology, 12, 2272–2281.CrossRefGoogle Scholar
Hijmans, R. J., Guarino, L. and Rojas, E. (2002). DIVA-GIS: A Geographical Information System for the Analysis of Biodiversity Data. Manual. Lima: International Potato Center.Google Scholar
Hijmans, R. J., Guarino, L., Jarvis, A. et al. (2005a). DIVA-GIS, version 5.2. Manual. www.diva-gis.org.
Hijmans, R. J., Cameron, S. E., Parra, J. L., Jones, P. G. and Jarvis, A. (2005b). Very high resolution interpolated climate surfaces for global land areas. International Journal of Climatology, 25, 1965–1978.CrossRefGoogle Scholar
Hirzel, A. H. and Lay, G. (2008). Habitat suitability modelling and niche theory. Journal of Applied Ecology, 45, 1372–1381.CrossRefGoogle Scholar
Hortal, J., Jiménez-Valverde, A., Gómez, J. F., Lobo, J. M. and Baselga, A. (2008). Historical bias in biodiversity inventories affects the observed environmental niche of the species. OIKOS, 117, 847–858.CrossRefGoogle Scholar
Hutchinson, G. E. (1957). Concluding remarks. Cold Spring Harbor Symposia on Quantitative Biology, 22, 415–427.CrossRefGoogle Scholar
Hutchinson, G. E. (1978). An Introduction to Population Ecology. New Haven, CT: Yale University Press.Google Scholar
Hutchinson, M. F. (1995). Interpolating mean rainfall using thin plate smoothing splines. International Journal of Geographical Information Systems, 9, 385–403.CrossRefGoogle Scholar
Hutchinson, M. F. (2004). Anusplin version 4.3. Canberra: Centre for Resource and Environment Studies, Australian National University.Google Scholar
James, F. C., Johnston, R. F., Warner, N. O., Niemi, G. and Boecklen, W. (1984). The Grinnellian niche of the Wood Thrush. American Naturalist, 124, 17–47.CrossRefGoogle Scholar
Jiménez-Valverde, A. and Lobo, J. M. (2006). The ghost of unbalanced species distribution data in geographical model predictions. Diversity and Distributions, 12, 512–524.CrossRefGoogle Scholar
Jiménez-Valverde, A., Lobo, J. M. and Hortal, J. (2008). Not as good as they seem: the importance of concepts in species distribution modeling. Diversity and Distributions, 14, 885–890.CrossRefGoogle Scholar
Kiehl, J. T. and Gent, P. R. (2004). The Community Climate System Model, version 2. Journal of Climate, 17, 1666–1669.2.0.CO;2>CrossRefGoogle Scholar
Köhler, J., Scheelke, K., Schick, S., Veith, M. and Lötters, S. (2005). Contribution to the taxonomy of hyperoliid frogs (Amphibia, Anura, Hyperoliidae): advertisement calls of twelve species from East and Central Africa. African Zoology, 40, 127–142.Google Scholar
Kozak, K. H., Graham, C. H. and Wiens, J. J. (2008). Integrating GIS-based environmental data into evolutionary biology. Trends in Ecology and Evolution, 23, 141–148.CrossRefGoogle ScholarPubMed
Kremen, C., Cameron, A., Moilanen, A. et al. (2008). Aligning conservation priorities across taxa in Madagascar with high-resolution planning tools. Science, 320, 222–226.CrossRefGoogle ScholarPubMed
Lobo, J. M., Jiménez-Valverde, A. and Real, R. (2008). AUC: a misleading measure of the performance of predictive distribution models. Global Ecology and Biogeography, 17, 145–151.CrossRefGoogle Scholar
Lötters, S., Rotich, D., Scheelke, K. et al. (2004). Bio-sketches and partitioning of syntopic reed frogs, genus Hyperolius (Amphibia: Hyperoliidae), in two humid tropical African forest regions. Journal of Natural History, 38, 1969–1997.CrossRefGoogle Scholar
Lötters, S., Rödder, D., Bielby, J. et al. (2008). Meeting the challenge of conserving Madagascar's megadiverse amphibians: addition of a risk assessment for the chytrid fungus. PLoS Biology, 6.Google Scholar
Martinez-Meyer, E., Peterson, A. T. and Navarro-Siguenza, A. G. (2004). Evolution of seasonal ecological niches in the Passerina buntings (Aves: Cardinalidae). Proceedings of the Royal Society of London B, 271, 1151–1157.CrossRefGoogle Scholar
Monserud, R. A. and Leemans, R. (1992). Comparing global vegetation maps with kappa statistics. Ecological Modelling, 62, 275–293.CrossRefGoogle Scholar
New, M., Hulme, M. and Jones, P. D. (1999). Representing twentieth century space-time climate variability. Part 1: development of a 1961–90 mean monthly terrestrial climatology. Journal of Climate, 12, 829–856.2.0.CO;2>CrossRefGoogle Scholar
New, M., Hulme, M. and Jones, P. D. (2000). Representing twentieth century space-time climate variability. Part 2: development of 1901–96 monthly grids of terrestrial surface climate. Journal of Climate, 13, 2217–2238.2.0.CO;2>CrossRefGoogle Scholar
Nix, H. (1986). A biogeographic analysis of Australian elapid snakes. In Atlas of Elapid Snakes of Australia, ed. Longmore, R.. Canberra: Bureau of Flora and Fauna, pp. 4–15.Google Scholar
Pearce, J. and Ferrier, S. (2000). An evaluation of alternative algorithms for fitting species' distribution models using logistic regression. Ecological Modelling, 128, 128–147.CrossRefGoogle Scholar
Pearman, P. B., Guisan, A., Broennimann, O. and Randin, C. F. (2007). Niche dynamics in space and time. Trends in Ecology and Evolution, 23, 149–158.CrossRefGoogle Scholar
Pearman, P. B., Randin, C. F., Broennimann, O. et al. (2008). Prediction of plant species' distributions across six millennia. Ecology Letters, 11, 357–369.CrossRefGoogle Scholar
Pearson, R.G. (2007). Species' Distribution Modeling for Conservation Educators and Practitioners: Synthesis. http://ncep.amnh.org. New York, NY: American Museum of Natural History.Google Scholar
Pearson, R. G., Raxworthy, C. J., Nakamura, M. and Peterson, A. T. (2007). Predicting species' distributions from small numbers of occurrence records: a test case using cryptic geckos in Madagascar. Journal of Biogeography, 34, 102–117.CrossRefGoogle Scholar
Peterson, A. T. (2003). Predicting the geography of species' invasions via ecological niche modeling. The Quarterly Review of Biology, 78, 419–433.CrossRefGoogle ScholarPubMed
Peterson, A. T. and Vargas, N. (1993). Ecological diversity in scrub jays, Aphelocoma coerulescens. In The Biological Diversity of Mexico: Origins and Distribution, ed. Ramamoorthy, T. P., Bye, R. and Fa, J.. New York, NY: Oxford University Press, pp. 309–317.Google Scholar
Peterson, A. T. and Vieglais, D. A. (2001). Predicting species' invasions using ecological niche modeling: new approaches from bioinformatics attack a pressing problem. BioScience, 51, 363–371.CrossRefGoogle Scholar
Peterson, A. T., Soberón, J. and Sánchez-Cordero, V. (1999). Conservation of ecological niches in evolutionary time. Science, 285, 1265–1267.CrossRefGoogle Scholar
Phillips, S. J., Dudík, M. and Shapire, R. E. (2004). A maximum entropy approach to species' distribution modeling. In Proceedings of the 21st International Conference on Machine Learning. New York, NY: ACM Press, pp. 655–662.Google Scholar
Phillips, S. J., Anderson, R. P. and Schapire, R. E. (2006). Maximum entropy modeling of species' geographic distributions. Ecological Modeling, 190, 231–259.CrossRefGoogle Scholar
Puliam, H. R. (2000). On the relationship between niche and distribution. Ecology Letters, 3, 349–361.CrossRefGoogle Scholar
Raxworthy, C. J., Ingram, C. M., Rabibisoa, N. and Pearson, R. G. (2007). Applications of ecological niche modeling for species' delimitation: a review and empirical evaluation using day geckos (Phelsuma) from Madagascar. Systematic Biology, 56, 907–923.CrossRefGoogle Scholar
Rödder, D. (2009). ‘Sleepless in Hawaii’: does anthropogenic climate change enhance ecological and socioeconomic impacts of the alien invasive Eleutherodactylus coqui Thomas, 1966 (Anura: Eleutherodactylidae)?North-Western Journal of Zoology, 5, 16–25.Google Scholar
Rödder, D. and Böhme, W. (2009). Who is who? Comparison of the advertisement calls of two East African sister species of Hyperolius (Anura: Hyperoliidae). Salamandra, 45, 180–185.Google Scholar
Rödder, D. and Dambach, J. (2010). Review: modelling future trends of relict species. In Relict Species: Phylogeography and Conservation Biology, ed. Habel, J. C. and Assmann, T., New York, NY: Springer, pp. 373–382.Google Scholar
Rödder, D. and Lötters, S. (2009). Niche shift or niche conservatism? Climatic properties of the native and invasive range of the Mediterranean Housegecko Hemidactylus turcicus. Global Ecology and Biogeography, 18, 674–687.CrossRefGoogle Scholar
Rödder, D. and Weinsheimer, F. (2009). Will future anthropogenic climate change increase the potential distribution of the alien invasive Cuban treefrog (Anura: Hylidae)?Journal of Natural History, 43, 1207–1217.CrossRefGoogle Scholar
Rödder, D., Solé, M. and Böhme, W. (2008). Predicting the potential distribution of two alien invasive housegeckos (Gekkonidae: Hemidactylus frenatus, Hemidactylus mabouia). North-Western Journal of Zoology, 4, 236–246.Google Scholar
Rödder, D., Schmidtlein, S., Veith, M. and Lötters, S. (2009). Alien invasive Slider turtle in unpredicted habitat: a matter of niche shift or predictors studied?PLoS ONE, 4, e7843.CrossRefGoogle ScholarPubMed
Rödder, D., Schlüter, A. and Lötters, S. (2010). Is the ‘Lost World’ lost? High endemism of amphibians and reptiles on South American tepuis in a changing climate. In Relict Species: Phylogeography and Conservation Biology, ed. Habel, J. C. and Assmann, T.. New York, NY: Springer, pp. 401–416.Google Scholar
Sax, D. F., Stachowicz, J. J., Brown, J. H. et al. (2008). Ecological and evolutionary insights from species invasions. Trends in Ecology and Evolution, 22, 465–471.CrossRefGoogle Scholar
Schiøtz, A. (1999). Treefrogs of Africa. Frankfurt: Chimaira.Google Scholar
Soberón, J. (2007). Grinnellian and Eltonian niches and geographic distributions of species. Ecology Letters, 10, 1115–1123.CrossRefGoogle ScholarPubMed
Soberón, J. and Peterson, A. T. (2004). Biodiversity informatics: managing and applying primary biodiversity data. Philosophical Transactions of the Royal Society of London B, 359, 689–698.CrossRefGoogle ScholarPubMed
Soberón, J. and Peterson, A. T. (2005). Interpretation of models of fundamental ecological niches and species' distributional areas. Biodiversity Informatics, 2, 1–10.CrossRefGoogle Scholar
Stockwell, D. B. R. and Noble, I. R. (1992). Introduction of sets of rules from animal distribution data: a robust and informative method of data analysis. Math and Computers in Simulation, 33, 385–390.CrossRefGoogle Scholar
Stockwell, D. and Peters, D. (1999). The GARP modeling system problems and solutions to automated spatial prediction. International Journal of Geographical Information Science, 13, 143–158.CrossRefGoogle Scholar
Swets, K. (1988). Measuring the accuracy of diagnostic systems. Science, 240, 1285–1293.CrossRefGoogle ScholarPubMed
Thuiller, W. (2003). BIOMOD: optimising predictions of species distributions and projecting potential future shifts under global change. Global Change Biology, 9, 1352–1362.CrossRefGoogle Scholar
Thuiller, W., Albert, C., Araújo, M. B. et al. (2008). Predicting global change impacts on plant species' distributions: future challenges. Perspectives in Plant Ecology, Evolution and Systematics, 9, 137–152.CrossRefGoogle Scholar
Tilman, D., May, R. M., Lehman, C. L. and Nowak, M. A. (1994). Habitat destruction and the extinction debt. Nature, 371, 65–66.CrossRefGoogle Scholar
Veith, M., Kosuch, J., Rödel, M. O. et al. (2009). Multiple evolution of sexual dichromatism in Afrotropical reed frogs. Molecular Phylogenetics and Evolution, 51, 388–393.CrossRefGoogle Scholar
Waltari, E. and Guralnick, R. P. (2009). Ecological niche modelling of montane mammals in the Great Basin, North America: examining past and present connectivity of species across basins and ranges. Journal of Biography, 36, 148–161.CrossRefGoogle Scholar
Waltari, E., Hijmans, R. J., Peterson, A. T. et al. (2007). Locating Pleistocene refugia: comparing phylogeographic and ecological niche model predictions. PLoS ONE, 7, 1–11.Google Scholar
Warren, D. L., Glor, R. E. and Turelli, M. (2008). Environmental niche equivalency versus conservatism: quantitative approaches to niche evolution. Evolution, 62, 2868–2883.CrossRefGoogle ScholarPubMed
Wiens, J. J. and Graham, C. H. (2005). Niche conservatism: integrating evolution, ecology, and conservation biology. Annual Review of Ecology and Systematics, 36, 519–539.CrossRefGoogle Scholar
Wisz, M. S., Hijmans, R. J., Peterson, A. T. et al. (2008). Effects of sample size on the performance of species' distribution models. Diversity and Distributions, 14, 763–773.CrossRefGoogle Scholar

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