The art of modelling range-shifting species

Methods in Ecology and Evolution - Tập 1 Số 4 - Trang 330-342 - 2010
Jane Elith1, Michael Kearney2, Steven Phillips3
1School of Botany, The University of Melbourne, Parkville 3010, Australia
2Department of Zoology, The University of Melbourne, Parkville 3010, Australia
3AT&T Laboratories – Research, 180 Park Avenue, Florham Park, NJ 07932, USA

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Abramowitz, 2010, Model independence in multi-model ensemble prediction, Australian Meteorological and Oceanographic Journal, 59, 3, 10.22499/2.5901.002

ANU 2009 anuclim http://fennerschool.anu.edu.au/publications/software/anuclim.php#contacts

Araújo, 2007, Ensemble forecasting of species distributions, Trends in Ecology and Evolution, 22, 42, 10.1016/j.tree.2006.09.010

Araújo, 2005, Equilibrium of species’ distributions with climate, Ecography, 28, 693, 10.1111/j.2005.0906-7590.04253.x

Araújo, 2006, Climate warming and the decline of amphibians and reptiles in Europe, Journal of Biogeography, 33, 1712, 10.1111/j.1365-2699.2006.01482.x

Araújo, 2005, Validation of species-climate impact models under climate change, Global Change Biology, 11, 1504, 10.1111/j.1365-2486.2005.01000.x

Austin, 2002, Spatial prediction of species distribution: an interface between ecological theory and statistical modelling, Ecological Modelling, 157, 101, 10.1016/S0304-3800(02)00205-3

Barry, 2006, Error and uncertainty in habitat models, Journal of Applied Ecology, 43, 413, 10.1111/j.1365-2664.2006.01136.x

van Beurden, 1981, Bioclimatic limits to the spread of Bufo marinus in Australia: a baseline, Proceedings of the Ecological Society of Australia, 11, 143

Bomford, 2009, Predicting establishment success for alien reptiles and amphibians: a role for climate matching, Biological Invasions, 11, 713, 10.1007/s10530-008-9285-3

Booth , G.D. Niccolucci , M.J. Schuster , E.G. 1994 Identifying proxy sets in multiple linear regression: an aid to better coefficient interpretation Intermountain Research Station, USDA Forest Service

Broennimann, 2008, Predicting current and future biological invasions: both native and invaded ranges matter, Biology Letters, 4, 585, 10.1098/rsbl.2008.0254

Broennimann, 2007, Evidence of climatic niche shift during biological invasion, Ecology Letters, 10, 701, 10.1111/j.1461-0248.2007.01060.x

Buisson, 2009, Uncertainty in ensemble forecasting of species distribution, Global Change Biology, 16, 1145, 10.1111/j.1365-2486.2009.02000.x

Busby, 1991, Nature Conservation: Cost Effective Biological Surveys and Data Analysis, 64

De Marco, 2008, Spatial analysis improves species distribution modelling during range expansion, Biology Letters, 4, 577, 10.1098/rsbl.2008.0210

Dormann, 2007, Promising the future? Global change projections of species distributions, Basic and Applied Ecology, 8, 387, 10.1016/j.baae.2006.11.001

Elith, 2009, Species distribution models: ecological explanation and prediction across space and time, Annual Review of Ecology, Evolution, and Systematics, 40, 677, 10.1146/annurev.ecolsys.110308.120159

Elith, 2008, A working guide to boosted regression trees, Journal of Animal Ecology, 77, 802, 10.1111/j.1365-2656.2008.01390.x

Elith, 2006, Novel methods improve prediction of species’ distributions from occurrence data, Ecography, 29, 129, 10.1111/j.2006.0906-7590.04596.x

Faith, 1987, Compositional dissimilarity as a robust measure of ecological distance, Vegetatio, 69, 57, 10.1007/BF00038687

Ficetola, 2007, Prediction and validation of the potential global distribution of a problematic alien invasive species the American bullfrog, Diversity and Distributions, 13, 476, 10.1111/j.1472-4642.2007.00377.x

Fitzpatrick, 2009, The projection of species distribution models and the problem of non-analog climate, Biodiversity and Conservation, 18, 2255, 10.1007/s10531-009-9584-8

Fitzpatrick, 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, 10.1111/j.1466-8238.2006.00258.x

Friedman, 2000, Additive logistic regression: a statistical view of boosting, The Annals of Statistics, 28, 337, 10.1214/aos/1016218223

Hanley, 1982, The meaning and use of the area under a receiver operating characteristic (ROC) curve, Radiology, 143, 29, 10.1148/radiology.143.1.7063747

Harrell, 2001, Regression Modeling Strategies with Applications to Linear Models, Logistic Regression and Survival Analysis, 10.1007/978-1-4757-3462-1

Hastie, 2008, GAM: Generalized Additive Models

Hastie, 1990, Generalized Additive Models

Hastie, 2009, The Elements of Statistical Learning: Data Mining, Inference, and Prediction, 10.1007/978-0-387-84858-7

Hayes, 2008, Are there any consistent predictors of invasion success?, Biological Invasions, 10, 483, 10.1007/s10530-007-9146-5

Heikkinen, 2006, Methods and uncertainties in bioclimatic envelope modelling under climate change, Progress in Physical Geography, 30, 751, 10.1177/0309133306071957

Hijmans, 2006, The ability of climate envelope models to predict the effect of climate change on species distributions, Global Change Biology, 12, 2272, 10.1111/j.1365-2486.2006.01256.x

Hooten, 2007, Hierarchical spatiotemporal matrix models for characterizing invasions, Biometrics, 63, 558, 10.1111/j.1541-0420.2006.00725.x

Jose, 2008, Simple robust averages of forecasts: some empirical results, International Journal of Forecasting, 24, 163, 10.1016/j.ijforecast.2007.06.001

Kearney, 2009, Mechanistic niche modelling: combining physiological and spatial data to predict species’ ranges, Ecology Letters, 12, 334, 10.1111/j.1461-0248.2008.01277.x

Kearney, 2010, Correlative and mechanistic models of species distribution provide congruent forecasts under climate change, Conservation Letters, 10.1111/j.1755-263X.2010.00097.x

Kearney, 2008, Modelling species distributions without using species distributions: the cane toad in Australia under current and future climates, Ecography, 31, 423, 10.1111/j.0906-7590.2008.05457.x

Lockwood, 2007, Invasion Ecology

Marmion, 2008, Evaluation of consensus methods in predictive species distribution modelling, Diversity and Distributions, 15, 59, 10.1111/j.1472-4642.2008.00491.x

Mau-Crimmins, 2006, Can the invaded range of a species be predicted sufficiently using only native-range data? Lehmann lovegrass (Eragrostis lehmanniana) in the southwestern United States, Ecological Modelling, 193, 736, 10.1016/j.ecolmodel.2005.09.002

McCullagh, 1989, Generalized Linear Models, 10.1007/978-1-4899-3242-6

Medley, 2010, Niche shifts during the global invasion of the Asian tiger mosquito, Aedes albopictus Skuse (Culicidae), revealed by reciprocal distribution models, Global Ecology and Biogeography, 19, 122, 10.1111/j.1466-8238.2009.00497.x

Menke, 2009, Characterizing and predicting species distributions across environments and scales: Argentine ant occurrences in the eye of the beholder, Global Ecology and Biogeography, 18, 50, 10.1111/j.1466-8238.2008.00420.x

Morin, 2009, Comparing niche- and process-based models to reduce prediction uncertainty in species range shifts under climate change, Ecology, 90, 1301, 10.1890/08-0134.1

NT Government 2006 http://www.nt.gov.au/nreta/wildlife/animals/canetoads/pdf/nt_distribution_2006_Cane_Toad.pdf

Parmesan, 2006, Ecological and evolutionary responses to recent climate change, Annual Review of Ecology, Evolution, and Systematics, 37, 637, 10.1146/annurev.ecolsys.37.091305.110100

Pearson, 2006, Model-based uncertainty in species range prediction, Journal of Biogeography, 33, 1704, 10.1111/j.1365-2699.2006.01460.x

Phillips, 2006, Maximum entropy modeling of species geographic distributions, Ecological Modelling, 190, 231, 10.1016/j.ecolmodel.2005.03.026

Phillips, 2008, The toad ahead: challenges of modelling the range and spread of an invasive species, Wildlife Research, 35, 222, 10.1071/WR07101

Phillips, 2008, Modeling of species distributions with MaxEnt: new extensions and a comprehensive evaluation, Ecography, 31, 161, 10.1111/j.0906-7590.2008.5203.x

Phillips, 2009, Sample selection bias and presence-only models of species distributions, Ecological Applications, 19, 181, 10.1890/07-2153.1

Platts, 2008, Predicting tree distributions in an East African biodiversity hotspot: model selection, data bias and envelope uncertainty, Ecological Modelling, 218, 121, 10.1016/j.ecolmodel.2008.06.028

Prasad, 2010, Modeling the invasive emerald ash borer risk of spread using a spatially explicit cellular model, Landscape Ecology, 25, 353, 10.1007/s10980-009-9434-9

R Development Core Team, 2009, R: A Language and Environment for Statistical Computing

Ridgeway , G. 2007 GBM: Generalized Boosted Regression Models http://www.i-pensieri.com/gregr/gbm.shtml

Rödder, 2009, Alien invasive slider turtle in unpredicted habitat: a matter of niche shift or of predictors studied?, PLoS ONE, 4, e7843, 10.1371/journal.pone.0007843

Roura-Pascual, 2004, Geographic potential of Argentine ants (Linepithema humile Mayr) in the face of global climate change, Proceedings of the Royal Society of London Series B - Biological Sciences, 271, 2527, 10.1098/rspb.2004.2898

Roura-Pascual, 2006, Niche differentiation and fine-scale projections for Argentine ants based on remotely-sensed data, Ecological Applications, 16, 1832, 10.1890/1051-0761(2006)016[1832:NDAFPF]2.0.CO;2

Roura-Pascual, 2009, Consensual predictions of potential distributional areas for invasive species: a case study of Argentine ants in the Iberian Peninsula, Biological Invasions, 11, 1017, 10.1007/s10530-008-9313-3

Scheller, 2005, A spatially interactive simulation of climate change, harvesting, wind, and tree species migration and projected changes to forest composition and biomass in northern Wisconsin, USA, Global Change Biology, 11, 307, 10.1111/j.1365-2486.2005.00906.x

Smolik, 2010, Integrating species distribution models and interacting particle systems to predict the spread of an invasive alien plant, Journal of Biogeography, 37, 411, 10.1111/j.1365-2699.2009.02227.x

Sutherst, 1995, The potential geographic distribution of the Cane Toad, Bufo marinus, in Australia, Conservation Biology, 9, 294

Tebaldi, 2007, The use of the multimodel ensemble in probabilistic climate projections, Philosophical Transactions of the Royal Society of London Series A, 365, 2053

Thuiller, 2004, Patterns and uncertainties of species’ range shifts under climate change, Global Change Biology, 10, 2020, 10.1111/j.1365-2486.2004.00859.x

Thuiller, 2005a, Niche properties and geographical extent as predictors of species sensitivity to climate change, Global Ecology and Biogeography, 14, 347, 10.1111/j.1466-822X.2005.00162.x

Thuiller, 2005b, Niche-based modelling as a tool for predicting the risk of alien plant invasions at a global scale, Global Change Biology, 11, 2234, 10.1111/j.1365-2486.2005.001018.x

Thuiller, 2008, Predicting global change impacts on plant species’ distributions: future challenges, Perspectives in Plant Ecology, Evolution and Systematics, 9, 137, 10.1016/j.ppees.2007.09.004

Urban, 2007, The cane toad’s (Chaunus (Bufo) marinus) increasing ability to invade Australia is revealed by a dynamically updated range model, Proceedings of the Royal Society B-Biological Sciences, 274, 1413, 10.1098/rspb.2007.0114

Warren, 2008, Environmental niche equivalency versus conservatism: quantitative approaches to niche evolution, Evolution, 62, 2868, 10.1111/j.1558-5646.2008.00482.x

Williams, 2007, Projected distributions of novel and disappearing climates by 2100 AD, Proceedings of the National Academy of Sciences, 104, 5738, 10.1073/pnas.0606292104

Zadrozny, 2004, Proceedings of the Twenty-First International Conference on Machine Learning, 114

Zurrell, 2009, Static species distribution models in dynamically changing systems: how good can predictions really be?, Ecography, 31, 1