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    Applications of Species Distribution Models

    (modified from Guisan & Thuilller 2005)

    Example applications relevant to Texas

    Beard, C.B.et al., 2003. Chagas Disease in a Domestic Transmission Cycle in SouthernTexas, USA. , 9(1), pp.103-105.

    Drake, J.M. & Bossenbroek, J.M.,2004. The Potential Distribution of Zebra Mussels in the United States. BioScience,54(10), p.931.

    Fitzpatrick, M.C. & Weltzin, J.F.,2005. Ecological niche models and the geography of biological invasions: areview and a novel application. Invasive plants: ecological and agriculturalaspects, pp.45–60.

    González, C. et al., 2010. Climate Changeand Risk of Leishmaniasis in North America: Predictions from Ecological NicheModels of Vector and Reservoir Species. PLoS neglected tropical diseases. 4(1)

    Herborg, L.M., Mandrak, N.E., et al.,2007. Comparative distribution and invasion risk of snakehead (Channidae) andAsian carp (Cyprinidae) species in North America. Canadian Journal ofFisheries and Aquatic Sciences, 64(12), pp.1723–1735.

    Herborg, L.-M., Jerde, C.L., et al.,2007. PREDICTING INVASION RISK USING MEASURES OF INTRODUCTION EFFORT ANDENVIRONMENTAL NICHE MODELS. Ecological Applications, 17(3), pp.663-674.

    Labay B, Cohen AE, Sissel B, Hendrickson DA, Martin FD, et al. (2011) Assessing Historical Fish Community Composition Using Surveys, Historical Collection Data, and Species Distribution Models. PLoS ONE 6(9): e25145. doi:10.1371/journal.pone.0025145 

    Martínez-Meyer, E., Peterson, A.T. &Navarro-Sigüenza, A.G., 2004. Evolution of seasonal ecological niches in thePasserina buntings (Aves: Cardinalidae). Proceedings of the Royal Society B:Biological Sciences, 271(1544), pp.1151-1157.

    Mau-Crimmins, T.M., Schussman, H.R. &Geiger, E.L., 2006. Can the invaded range of a species be predictedsufficiently using only native-range data?: Lehmann lovegrass (Eragrostislehmanniana) in the southwestern United States. Ecological Modelling,193(3-4), pp.736-746.

    Pyron, R.A., Burbrink, F.T. & Guiher,T.J., 2008. Claims of Potential Expansion throughout the U.S. by InvasivePython Species Are Contradicted by Ecological Niche Models. PLoS ONE,3(8), p.e2931.

    Ron, S.R., 2005. Predicting theDistribution of the Amphibian Pathogen Batrachochytrium dendrobatidis in theNew World1. Biotropica, 37(2), pp.209-221.

    Sarkar, Sahotra et al., 2010. ChagasDisease Risk in Texas. PLoS Negl Trop Dis, 4(10), p.e836.

    Testing biogeographical, ecological and evolutionary hypotheses

    Anderson, R.P., Peterson, A.T. & Gómez-Laverde,M., 2002. Using niche-based GIS modeling to test geographic predictions ofcompetitive exclusion and competitive release in South American pocket mice. Oikos,pp.3–16.

    Fitzpatrick, M.C. et al., 2007. Thebiogeography of prediction error: why does the introduced range of the fire antover-predict its native range? Global Ecology and Biogeography, 16(1),pp.24–33.

    Graham, C.H. et al., 2004. Integratingphylogenetics and environmental niche models to explore speciation mechanismsin dendrobatid frogs. Evolution, 58(8), pp.1781–1793.

    Leathwick, J.R., 1998. Are New Zealand’sNothofagus species in equilibrium with their environment? Journal ofVegetation Science, pp.719–732.

    Wiens, J.J. et al., 2010. Nicheconservatism as an emerging principle in ecology and conservation biology. Ecologyletters.

    Assessing species invasion and proliferation

    Beerling, D.J., Huntley, B. & Bailey,J.P., 1995. Climate and the distribution of Fallopia japonica: use of anintroduced species to test the predictive capacity of response surfaces. Journalof Vegetation Science, pp.269–282.

    Elith, J., Kearney, M. & Phillips,S., 2010. The art of modelling range-shifting species. Methods in ecologyand evolution.

    Ficetola, G.F., Thuiller, W. & Miaud,C., 2007. Prediction and validation of the potential global distribution of aproblematic alien invasive species-the American bullfrog. Diversity andDistributions, 13(4), pp.476–485.

    Peterson, A.T. & Vieglais, D.A.,2001. Predicting species invasions using ecological niche modeling: newapproaches from bioinformatics attack a pressing problem. BioScience,51(5), pp.363–371.

    Peterson, A.T., Papes, M. & Kluza,D.A., 2003. Predicting the potential invasive distributions of four alien plantspecies in North America. Weed Science, 51(6), pp.863–868.

    Vaclavik, T. & Meentemeyer, R.K.,2009. Invasive species distribution modeling (iSDM): Are absence data anddispersal constraints needed to predict actual distributions? Ecologicalmodelling, 220(23), pp.3248–3258.

    Assessing the impact of climate and land use on species distributions

    Diniz-Filho, J.A.F. et al., 2009.Partitioning and mapping uncertainties in ensembles of forecasts of speciesturnover under climate change. Ecography, 32(6), pp.897–906.

    Falk, W. & Mellert, K.H., 2011.Species distribution models as a tool for forest management planning underclimate change: risk evaluation of Abies alba in Bavaria. Journal ofVegetation Science.

    Hijmans, R.J. & Graham, C.H., 2006.The ability of climate envelope models to predict the effect of climate changeon species distributions. Global Change Biology, 12(12), pp.2272–2281.

    Thomas, C.D., Cameron, A., et al., 2004.Extinction risk from climate change. Nature, 427(6970), pp.145–148.

    Thuiller, W., 2004. Patterns anduncertainties of species’ range shifts under climate change. Global ChangeBiology, 10(12), pp.2020–2027.

    Wiens, J.A. et al., 2009. Niches, models,and climate change: Assessing the assumptions and uncertainties. Proceedingsof the National Academy of Sciences, 106(Supplement 2), p.19729.

    Suggesting unsurveyed sites of high potential of occurrence for rare species

    Elith, J. & Burgman, M.A., 2002. Predictions and their validation: rare plants in the Central Highlands, Victoria, Australia. Predicting species occurrences: issues of accuracy and scale, 303, p.313.

    Engler, R., Guisan, A. & Rechsteiner,L., 2004. An improved approach for predicting the distribution of rare andendangered species from occurrence and pseudo-absence data. Journal ofApplied Ecology, 41(2), pp.263–274.

    Raxworthy, C.J. et al., 2003. Predictingdistributions of known and unknown reptile species in Madagascar. Nature,426(6968), pp.837–841.

    Supporting management plans for habitat restoration, species recovery, and suitable repatriation sites

    Anderson, J.T., Saldana Rojas, J. &Flecker, A.S., 2009. High-quality seed dispersal by fruit-eating fishes inAmazonian floodplain habitats. Oecologia, 161(2), pp.279–290.

    Johnson, C.J. & Gillingham, M.P.,2005. An evaluation of mapped species distribution models used for conservationplanning. Environmental Conservation, 32(2), pp.117–128.

    Lopez-Arevalo, H.F. et al., 2011. Localknowledge and species distribution models’ contribution towards mammalianconservation. Biological Conservation.

    Pearce, J. & Lindenmayer, D., 1998.Bioclimatic analysis to enhance reintroduction biology of the endangeredhelmeted honeyeater (Lichenostomus melanops cassidix) in southeasternAustralia. Restoration Ecology, 6(3), pp.238–243.

    Rodríguez, J.P. et al., 2007. Theapplication of predictive modelling of species distribution to biodiversityconservation. Diversity and Distributions, 13(3), pp.243–251.

    Vanreusel, W., Maes, D. & Van Dyck,H., 2007. Transferability of species distribution models: a functional habitatapproach for two regionally threatened butterflies. Conservation biology,21(1), pp.201–212.

    Wilson, C.D., Roberts, D. & Reid, N.,2010. Applying species distribution modelling to identify areas of highconservation value for endangered species: A case study using Margaritiferamargaritifera (L.). Biological Conservation.

    Supporting conservation planning and reserve selection

    Araújo, M.B. et al., 2004. Would climatechange drive species out of reserves? An assessment of existingreserve-selection methods. Global Change Biology, 10(9), pp.1618–1626.

    Esselman, P.C. & Allan, J.D., 2010.Application of species distribution models and conservation planning softwareto the design of a reserve network for the riverine fishes of northeasternMesoamerica. Freshwater Biology, 56(1), pp.71-88.

    Ferrier, S. et al., 2002. Extendedstatistical approaches to modelling spatial pattern in biodiversity innortheast New South Wales. I. Species-level modelling. Biodiversity andConservation, 11(12), pp.2275–2307.

    Klein, C. et al., 2009. Incorporatingecological and evolutionary processes into continental-scale conservationplanning. Ecological Applications, 19(1), pp.206–217.

    Kremen, C. et al., 2008. Aligningconservation priorities across taxa in Madagascar with high-resolution planningtools. Science, 320(5873), p.222.

    Sarkar, S. & Margules, C., 2002.Operationalizing biodiversity for conservation planning. Journal ofbiosciences, 27(4), pp.299–308.

    Sarkar, S., Pressey, R.L., et al., 2006.Biodiversity conservation planning tools: present status and challenges for thefuture. Annual Review of Environment and Resources, 31(1), p.123.

    Sarkar, Sahotra et al., 2009. Systematicconservation assessment for the Mesoamerica, Chocó, and Tropical Andesbiodiversity hotspots: a preliminary analysis. Biodiversity and Conservation,18(7), pp.1793-1828.

    Modelling species assemblages from individual species predictions

    Ferrier, S. et al., 2002. Extendedstatistical approaches to modelling spatial pattern in biodiversity innortheast New South Wales. I. Species-level modelling. Biodiversity andConservation, 11(12), pp.2275–2307.

    Guisan, A. et al., 2000. Equilibriummodeling of alpine plant distribution: how far can we go? In Vegetation andclimate. A selection of contributions presented at the 42nd Symposium of theInternational Association of Vegetation Science, Bilbao, Spain, 26-30 July1999. pp. 353–384.

    Labay, B.J. et al., (In Press). Assessing historical fish community composition using surveys, historical collection data, and species distribution models. PLoS ONE.

    Leathwick, J.R., Whitehead, D. &McLeod, M., 1996. Predicting changes in the composition of New Zealand’sindigenous forests in response to global warming: a modelling approach. EnvironmentalSoftware, 11(1-3), pp.81–90.

    Building bio- or ecogeographic regions

    No Published example found

    Improving the calculation of ecological distance between patches in landscape meta-population dynamic and gene flow models

    No Published example found