Niche shifts and environmental non-equilibrium undermine the usefulness of ecological niche models for invasion risk assessments.
Journal
Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288
Informations de publication
Date de publication:
14 05 2020
14 05 2020
Historique:
received:
21
06
2019
accepted:
15
04
2020
entrez:
16
5
2020
pubmed:
16
5
2020
medline:
15
12
2020
Statut:
epublish
Résumé
Niche shifts and environmental non-equilibrium in invading alien species undermine niche-based predictions of alien species' potential distributions and, consequently, their usefulness for invasion risk assessments. Here, we compared the realized climatic niches of four alien amphibian species (Hylarana erythraea, Rhinella marina, Hoplobatrachus rugulosus, and Kaloula pulchra) in their native and Philippine-invaded ranges to investigate niche changes that have unfolded during their invasion and, with this, assessed the extent of niche conservatism and environmental equilibrium. We investigated how niche changes affected reciprocal transferability of ecological niche models (ENMs) calibrated using data from the species' native and Philippine-invaded ranges, and both ranges combined. We found varying levels of niche change across the species' realized climatic niches in the Philippines: climatic niche shift for H. rugulosus; niche conservatism for R. marina and K. pulchra; environmental non-equilibrium in the Philippine-invaded range for all species; and environmental non-equilibrium in the native range or adaptive changes post-introduction for all species except H. erythraea. Niche changes undermined the reciprocal transferability of ENMs calibrated using native and Philippine-invaded range data. Our paper highlights the difficulty of predicting potential distributions given niche shifts and environmental non-equilibrium; we suggest calibrating ENMs with data from species' combined native and invaded ranges, and to regularly reassess niche changes and recalibrate ENMs as species' invasions progress.
Identifiants
pubmed: 32409706
doi: 10.1038/s41598-020-64568-2
pii: 10.1038/s41598-020-64568-2
pmc: PMC7224218
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
7972Références
Richardson, D. M., Pysek, P. & Carlton, J. T. In Fifty Years of Invasion Ecology: The Legacy of Charles Elton (ed David M. Richardson) Ch. 30, 409-420 (2011).
Lewis, S. L. & Maslin, M. A. Defining the anthropocene. Nature 519, 171–180, https://doi.org/10.1038/nature14258 (2015).
doi: 10.1038/nature14258
pubmed: 25762280
Crutzen, P. J. Geology of mankind. Nature 415, 23, https://doi.org/10.1038/415023a (2002).
doi: 10.1038/415023a
pubmed: 11780095
Mooney, H. A. & Cleland, E. E. The evolutionary impact of invasive species. Proc Natl Acad Sci U S A 98, 5446–5451, https://doi.org/10.1073/pnas.091093398 (2001).
doi: 10.1073/pnas.091093398
pubmed: 11344292
pmcid: 33232
Vila, M. et al. Ecological impacts of invasive alien plants: a meta-analysis of their effects on species, communities and ecosystems. Ecol Lett 14, 702–708, https://doi.org/10.1111/j.1461-0248.2011.01628.x (2011).
doi: 10.1111/j.1461-0248.2011.01628.x
pubmed: 21592274
Pejchar, L. & Mooney, H. A. Invasive species, ecosystem services and human well-being. Trends Ecol Evol 24, 497–504, https://doi.org/10.1016/j.tree.2009.03.016 (2009).
doi: 10.1016/j.tree.2009.03.016
pubmed: 19577817
Wittenberg, R., & Cock, M. J. (eds.). Invasive alien species: a toolkit of best prevention and management practices., (CABI, 2001).
Clout, M. N., Williams, P. A. (eds.). Invasive Species Management: A Handbook of Principles and Techniques. 308 (Oxford University Press, 2009).
Convention on Biological Diversity (CBD). The strategic plan for biodiversity 2011-2020 and the aichi biodiversity targets. Report No. UNEP/CBD/COP/DEC/X/2, (2010).
United Nations (IUCN). Transforming our world: the 2030 agenda for sustainable development. Resolution adopted by the General Assembly. Report No. A/RES/70/1, (2015).
Stohlgren, T. J. & Jarnevich, C. S. In Invasive Species Management. A Handbook of Principles and Techniques (ed M.N. Clout, Williams, P. A.) 19–35 (Oxford University Press, 2009).
Peterson, A. T. & Vieglais, D. A. Predicting Species Invasions Using Ecological Niche Modeling: New Approaches from Bioinformatics Attack a Pressing Problem. BioScience 51, 10.1641/0006-3568(2001)051[0363:Psiuen]2.0.Co;2 (2001).
Jiménez-Valverde, A., Lobo, J. M. & Hortal, J. Not as good as they seem: the importance of concepts in species distribution modelling. Diversity and Distributions 14, 885–890, https://doi.org/10.1111/j.1472-4642.2008.00496.x (2008).
doi: 10.1111/j.1472-4642.2008.00496.x
Jeschke, J. M. & Strayer, D. L. Usefulness of bioclimatic models for studying climate change and invasive species. Ann N Y Acad Sci 1134, 1–24, https://doi.org/10.1196/annals.1439.002 (2008).
doi: 10.1196/annals.1439.002
pubmed: 18566088
Venette, R. C. E. Pest risk modelling and mapping for invasive alien species. (Centre for Agriculture and Bioscience International, 2015).
Guisan, A. & Zimmermann, N. E. Predictive habitat distribution models in ecology. Ecological Modelling 135, 147–186, https://doi.org/10.1016/s0304-3800(00)00354-9 (2000).
doi: 10.1016/s0304-3800(00)00354-9
Franklin, J. Mapping species distributions: spatial inference and prediction. (Cambridge University Press, 2010).
Peterson, A. T., et al Ecological niches and geographic distributions (MPB-49) Vol. 56 (Princeton University Press, 2011).
Guisan, A., Thuiller, W., & Zimmermann, N. E. Habitat suitability and distribution models: with applications in R. (Cambridge University Press, 2017).
McGeoch, M. A. et al. Prioritizing species, pathways, and sites to achieve conservation targets for biological invasion. Biological Invasions 18, 299–314, https://doi.org/10.1007/s10530-015-1013-1 (2015).
doi: 10.1007/s10530-015-1013-1
Peterson, A. T. Predicting the Geography of Species’ Invasions via Ecological Niche Modeling. The Quarterly Review of Biology 78, 419–433, https://doi.org/10.1086/378926 (2003).
doi: 10.1086/378926
pubmed: 14737826
Araújo, M. B. & Pearson, R. G. Equilibrium of species’ distributions with climate. Ecography 28, 693–695, https://doi.org/10.1111/j.2005.0906-7590.04253.x (2005).
doi: 10.1111/j.2005.0906-7590.04253.x
Araújo, M. B., Pearson, R. G., Thuiller, W. & Erhard, M. Validation of species–climate impact models under climate change. Global Change Biology 11, 1504–1513, https://doi.org/10.1111/j.1365-2486.2005.01000.x (2005).
doi: 10.1111/j.1365-2486.2005.01000.x
Wiens, J. J. & Graham, C. H. Niche Conservatism: Integrating Evolution, Ecology, and Conservation Biology. Annual Review of Ecology, Evolution, and Systematics 36, 519–539, https://doi.org/10.1146/annurev.ecolsys.36.102803.095431 (2005).
doi: 10.1146/annurev.ecolsys.36.102803.095431
Elith, J. & Leathwick, J. R. Species Distribution Models: Ecological Explanation and Prediction Across Space and Time. Annual Review of Ecology, Evolution, and Systematics 40, 677–697, https://doi.org/10.1146/annurev.ecolsys.110308.120159 (2009).
doi: 10.1146/annurev.ecolsys.110308.120159
Broennimann, O. et al. Evidence of climatic niche shift during biological invasion. Ecol Lett 10, 701–709, https://doi.org/10.1111/j.1461-0248.2007.01060.x (2007).
doi: 10.1111/j.1461-0248.2007.01060.x
pubmed: 17594425
pmcid: 17594425
Petitpierre, B. et al. Climatic niche shifts are rare among terrestrial plant invaders. Science 335, 1344–1348, https://doi.org/10.1126/science.1215933 (2012).
doi: 10.1126/science.1215933
pubmed: 22422981
Medley, K. A. Niche shifts during the global invasion of the Asian tiger mosquito,Aedes albopictusSkuse (Culicidae), revealed by reciprocal distribution models. Global Ecology and Biogeography 19, 122–133, https://doi.org/10.1111/j.1466-8238.2009.00497.x (2010).
doi: 10.1111/j.1466-8238.2009.00497.x
Fitzpatrick, M. C., Weltzin, J. F., Sanders, N. J. & Dunn, R. R. 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, https://doi.org/10.1111/j.1466-822X.2006.00258.x (2006).
doi: 10.1111/j.1466-822X.2006.00258.x
Hill, M. P., Gallardo, B. & Terblanche, J. S. A global assessment of climatic niche shifts and human influence in insect invasions. Global Ecology and Biogeography 26, 679–689, https://doi.org/10.1111/geb.12578 (2017).
doi: 10.1111/geb.12578
Strubbe, D., Beauchard, O. & Matthysen, E. Niche conservatism among non-native vertebrates in Europe and North America. Ecography 38, 321–329, https://doi.org/10.1111/ecog.00632 (2015).
doi: 10.1111/ecog.00632
Li, Y., Liu, X., Li, X., Petitpierre, B. & Guisan, A. Residence time, expansion toward the equator in the invaded range and native range size matter to climatic niche shifts in non-native species. Global Ecology and Biogeography 23, 1094–1104, https://doi.org/10.1111/geb.12191 (2014).
doi: 10.1111/geb.12191
Tingley, R., Vallinoto, M., Sequeira, F. & Kearney, M. R. Realized niche shift during a global biological invasion. Proc Natl Acad Sci U S A 111, 10233–10238, https://doi.org/10.1073/pnas.1405766111 (2014).
doi: 10.1073/pnas.1405766111
pubmed: 24982155
pmcid: 4104887
Strubbe, D., Broennimann, O., Chiron, F. & Matthysen, E. Niche conservatism in non-native birds in Europe: niche unfilling rather than niche expansion. Global Ecology and Biogeography 22, 962–970, https://doi.org/10.1111/geb.12050 (2013).
doi: 10.1111/geb.12050
Tingley, R., Thompson, M. B., Hartley, S. & Chapple, D. G. Patterns of niche filling and expansion across the invaded ranges of an Australian lizard. Ecography 39, 270–280, https://doi.org/10.1111/ecog.01576 (2016).
doi: 10.1111/ecog.01576
Grinnell, J. The Niche-Relationships of the California Thrasher. The Auk 3, 427–433 (1917).
doi: 10.2307/4072271
Blossey, B. & Notzold, R. Evolution of Increased Competitive Ability in Invasive Nonindigenous Plants: A Hypothesis. The Journal of Ecology 83, https://doi.org/10.2307/2261425 (1995).
Hutchinson, G. Concluding remarks. Cold Spring Harbor Symposia on Quantitative Biology 22, 415–427 (1957).
doi: 10.1101/SQB.1957.022.01.039
Keane, R. Exotic plant invasions and the enemy release hypothesis. Trends in Ecology & Evolution 17, 164–170, https://doi.org/10.1016/s0169-5347(02)02499-0 (2002).
doi: 10.1016/s0169-5347(02)02499-0
Urban, M. C., Phillips, B. L., Skelly, D. K. & Shine, R. The cane toad’s (Chaunus [Bufo] marinus) increasing ability to invade Australia is revealed by a dynamically updated range model. Proc Biol Sci 274, 1413–1419, https://doi.org/10.1098/rspb.2007.0114 (2007).
doi: 10.1098/rspb.2007.0114
pubmed: 17389221
pmcid: 2176198
Broennimann, O. & Guisan, A. Predicting current and future biological invasions: both native and invaded ranges matter. Biol Lett 4, 585–589, https://doi.org/10.1098/rsbl.2008.0254 (2008).
doi: 10.1098/rsbl.2008.0254
pubmed: 18664415
pmcid: 2610080
Beaumont, L. J. et al. Different climatic envelopes among invasive populations may lead to underestimations of current and future biological invasions. Diversity and Distributions 15, 409–420, https://doi.org/10.1111/j.1472-4642.2008.00547.x (2009).
doi: 10.1111/j.1472-4642.2008.00547.x
Wilson, J. R. U. et al. Residence time and potential range: crucial considerations in modelling plant invasions. Diversity and Distributions 13, 11–22, https://doi.org/10.1111/j.1366-9516.2006.00302.x (2007).
doi: 10.1111/j.1366-9516.2006.00302.x
Pysek, P. et al. Geographical and taxonomic biases in invasion ecology. Trends Ecol Evol 23, 237–244, https://doi.org/10.1016/j.tree.2008.02.002 (2008).
doi: 10.1016/j.tree.2008.02.002
pubmed: 18367291
van Wilgen, N. J., Gillespie, M. S., Richardson, D. M. & Measey, J. A taxonomically and geographically constrained information base limits non-native reptile and amphibian risk assessment: a systematic review. PeerJ 6, e5850, https://doi.org/10.7717/peerj.5850 (2018).
doi: 10.7717/peerj.5850
pubmed: 30425887
pmcid: 6230440
Bellard, C. & Jeschke, J. M. A spatial mismatch between invader impacts and research publications. Conserv Biol 30, 230–232, https://doi.org/10.1111/cobi.12611 (2016).
doi: 10.1111/cobi.12611
pubmed: 26308661
Guisan, A., Petitpierre, B., Broennimann, O., Daehler, C. & Kueffer, C. Unifying niche shift studies: insights from biological invasions. Trends Ecol Evol 29, 260–269, https://doi.org/10.1016/j.tree.2014.02.009 (2014).
doi: 10.1016/j.tree.2014.02.009
pubmed: 24656621
Broennimann, O. et al. Measuring ecological niche overlap from occurrence and spatial environmental data. Global Ecology and Biogeography 21, 481–497, https://doi.org/10.1111/j.1466-8238.2011.00698.x (2012).
doi: 10.1111/j.1466-8238.2011.00698.x
Blonder, B., Lamanna, C., Violle, C. & Enquist, B. J. Then-dimensional hypervolume. Global Ecology and Biogeography 23, 595–609, https://doi.org/10.1111/geb.12146 (2014).
doi: 10.1111/geb.12146
Blonder, B. et al. New approaches for delineatingn-dimensional hypervolumes. Methods in Ecology and Evolution 9, 305–319, https://doi.org/10.1111/2041-210x.12865 (2018).
doi: 10.1111/2041-210x.12865
Warren, D. L., Glor, R. E. & Turelli, M. Environmental niche equivalency versus conservatism: quantitative approaches to niche evolution. Evolution 62, 2868–2883, https://doi.org/10.1111/j.1558-5646.2008.00482.x (2008).
doi: 10.1111/j.1558-5646.2008.00482.x
pubmed: 18752605
Pili, A. N., Sy, E. Y., Diesmos, M. L. L. & Diesmos, A. C. Island Hopping in a Biodiversity Hotspot Archipelago: Reconstructed Invasion History and Updated Status and Distribution of Alien Frogs in the Philippines1. Pacific Science 73, https://doi.org/10.2984/73.3.2 (2019).
Pili, A. N., Supsup, Christian, E., Diesmos, Mae Lowe, L. & Diesmos, Arvin C. In Island invasives: scaling up to meet the challenge (eds. C. R. Veitch, Clout, M. N., Martin, J. C., Russel, J. C., & West, C. J.) 327–347 (IUCN, Dundee, Scotland, 2019).
Kraus, F. Alien reptiles and amphibians: a scientific compendium and analysis. Vol. 4 (Springer Science & Business Media, 2009).
Kraus, F. Impacts from Invasive Reptiles and Amphibians. Annual Review of Ecology, Evolution, and Systematics 46, 75–97, https://doi.org/10.1146/annurev-ecolsys-112414-054450 (2015).
doi: 10.1146/annurev-ecolsys-112414-054450
Araujo, M. B. & New, M. Ensemble forecasting of species distributions. Trends Ecol Evol 22, 42–47, https://doi.org/10.1016/j.tree.2006.09.010 (2007).
doi: 10.1016/j.tree.2006.09.010
pubmed: 17011070
HerpWatch Pilipinas, I., Pili, A. N., Diesmos, M. L. L. & Diesmos, A. C. DAYO: Invasive Alien Amphibians in the Philippines. Version 1.4. HerpWatch Pilipinas, Inc. Occurrence dataset accessed. v. 1.0, https://doi.org/10.15468/o24m0j (Date of access: 17/2/2019) (2019).
Gallagher, R. V., Beaumont, L. J., Hughes, L. & Leishman, M. R. Evidence for climatic niche and biome shifts between native and novel ranges in plant species introduced to Australia. Journal of Ecology 98, 790–799, https://doi.org/10.1111/j.1365-2745.2010.01677.x (2010).
doi: 10.1111/j.1365-2745.2010.01677.x
Simberloff, D. The Role of Propagule Pressure in Biological Invasions. Annual Review of Ecology, Evolution, and Systematics 40, 81–102, https://doi.org/10.1146/annurev.ecolsys.110308.120304 (2009).
doi: 10.1146/annurev.ecolsys.110308.120304
Soberon, J. & Arroyo-Pena, B. Are fundamental niches larger than the realized? Testing a 50-year-old prediction by Hutchinson. PLoS One 12, e0175138, https://doi.org/10.1371/journal.pone.0175138 (2017).
doi: 10.1371/journal.pone.0175138
pubmed: 28403170
pmcid: 5389801
Phillips, B. L., Brown, G. P. & Shine, R. Evolutionarily accelerated invasions: the rate of dispersal evolves upwards during the range advance of cane toads. J Evol Biol 23, 2595–2601, https://doi.org/10.1111/j.1420-9101.2010.02118.x (2010).
doi: 10.1111/j.1420-9101.2010.02118.x
pubmed: 20939838
Kolbe, J. J., Kearney, M. & Shine, R. Modeling the consequences of thermal trait variation for the cane toad invasion of Australia. Ecol Appl 20, 2273–2285, https://doi.org/10.1890/09-1973.1 (2010).
doi: 10.1890/09-1973.1
Kearney, M. & Porter, W. Mechanistic niche modelling: combining physiological and spatial data to predict species’ ranges. Ecol Lett 12, 334–350, https://doi.org/10.1111/j.1461-0248.2008.01277.x (2009).
doi: 10.1111/j.1461-0248.2008.01277.x
pubmed: 19292794
Pulliam, H. R. On the relationship between niche and distribution. Ecology Letters 3, 349–361, https://doi.org/10.1046/j.1461-0248.2000.00143.x (2000).
doi: 10.1046/j.1461-0248.2000.00143.x
Scalera, R. et al. Progress toward pathways prioritization in compliance to Aichi Target 9. Report No. UNEP/CBD/SBSTTA/20/1/Rev.1., (Convention on Biological Diversity 2016).
Elith, J. & Graham, C. H. Do they? How do they? WHY do they differ? On finding reasons for differing performances of species distribution models. Ecography 32, 66–77, https://doi.org/10.1111/j.1600-0587.2008.05505.x (2009).
doi: 10.1111/j.1600-0587.2008.05505.x
Global Biodiversity Information Facility (GBIF). GBIF Occurrence Download. v. doi: 10.15468/dl.hunni9 (Date of access: 17/2/2019) (2019).
Darwin Core Task Group. Darwin Core. Biodiversity Information Standards (TDWG), http://www.tdwg.org/standards/450 (2009).
IUCN (International Union for Conservation of Nature), Conservation International & NatureServe. Hoplobatrachus rugulosus. The IUCN Red List of Threatened Species. v. 6.1. IUCN, http://www.iucnredlist.org (Date of access: 17/2/2019) (2008).
IUCN (International Union for Conservation of Nature), Conservation International & NatureServe. Rhinella marina. The IUCN Red List of Threatened Species. v. 6.1. IUCN, http://www.iucnredlist.org (Date of access: 17/2/2019) (2009).
IUCN (International Union for Conservation of Nature), Conservation International & NatureServe. Kaloula pulchra. The IUCN Red List of Threatened Species. v. 6.1. IUCN, http://www.iucnredlist.org (Date of access: 17/2/2019) (2008).
IUCN (International Union for Conservation of Nature) & Conservation International. Hylarana erythraea. The IUCN Red List of Threatened Species. v. 6.1. IUCN, http://www.iucnredlist.org (Date of access: 17/2/2019) (2014).
Elith, J., Kearney, M. & Phillips, S. The art of modelling range-shifting species. Methods in Ecology and Evolution 1, 330–342, https://doi.org/10.1111/j.2041-210x.2010.00036.x (2010).
doi: 10.1111/j.2041-210x.2010.00036.x
Boria, R. A., Olson, L. E., Goodman, S. M. & Anderson, R. P. Spatial filtering to reduce sampling bias can improve the performance of ecological niche models. Ecological Modelling 275, 73–77, https://doi.org/10.1016/j.ecolmodel.2013.12.012 (2014).
doi: 10.1016/j.ecolmodel.2013.12.012
Fick, S. E. & Hijmans, R. J. WorldClim 2: new 1-km spatial resolution climate surfaces for global land areas. International Journal of Climatology 37, 4302–4315, https://doi.org/10.1002/joc.5086 (2017).
doi: 10.1002/joc.5086
Bennett, A. F. Thermal dependence of locomotor capacity. Am J Physiol 259, R253–258, https://doi.org/10.1152/ajpregu.1990.259.2.R253 (1990).
doi: 10.1152/ajpregu.1990.259.2.R253
pubmed: 2201218
Rohde, K. Latitudinal Gradients in Species Diversity: The Search for the Primary Cause. Oikos 65, https://doi.org/10.2307/3545569 (1992).
Wells, K. D. The ecology and behavior of amphibians. (University of Chicago Press, 2010).
Caldwell, R. S. & Jones, G. S. Winter Congregations of Plethodon cinereus in Ant Mounds, with Notes on Their Food Habits. American Midland Naturalist 90, https://doi.org/10.2307/2424475 (1973).
Caldwell, R. S. Observations on the winter activity of the red-backed salamander, Plethodon cinereus, in Indiana. Herpetologica 31, 21–22 (1975).
Fraser, D. F. Empirical Evaluation of the Hypothesis of Food Competition in Salamanders of the Genus Plethodon. Ecology 57, 459–471, https://doi.org/10.2307/1936431 (1976).
doi: 10.2307/1936431
Alford, R. A. & Richards, S. J. Global Amphibian Declines: A Problem in Applied Ecology. Annual Review of Ecology and Systematics 30, 133–165, https://doi.org/10.1146/annurev.ecolsys.30.1.133 (1999).
doi: 10.1146/annurev.ecolsys.30.1.133
Araújo, M. B., Thuiller, W. & Pearson, R. G. Climate warming and the decline of amphibians and reptiles in Europe. Journal of Biogeography 33, 1712–1728, https://doi.org/10.1111/j.1365-2699.2006.01482.x (2006).
doi: 10.1111/j.1365-2699.2006.01482.x
Buckley, L. B. & Jetz, W. Environmental and historical constraints on global patterns of amphibian richness. Proc Biol Sci 274, 1167–1173, https://doi.org/10.1098/rspb.2006.0436 (2007).
doi: 10.1098/rspb.2006.0436
pubmed: 17327208
pmcid: 2189569
Sodhi, N. S. et al. Measuring the meltdown: drivers of global amphibian extinction and decline. PLoS One 3, e1636, https://doi.org/10.1371/journal.pone.0001636 (2008).
doi: 10.1371/journal.pone.0001636
pubmed: 18286193
pmcid: 2238793
Austin, M. P. Spatial prediction of species distribution: an interface between ecological theory and statistical modelling. Ecological Modelling 157, 101–118, https://doi.org/10.1016/s0304-3800(02)00205-3 (2002).
doi: 10.1016/s0304-3800(02)00205-3
Di Cola, V. et al. ecospat: an R package to support spatial analyses and modeling of species niches and distributions. Ecography 40, 774–787, https://doi.org/10.1111/ecog.02671 (2017).
doi: 10.1111/ecog.02671
R Core Team. R: A language and environment for statistical computing v. 3.6.0 (R Foundation for Statistical Computing, 2019).
Olson, D. M. et al. Terrestrial Ecoregions of the World: A New Map of Life on Earth. BioScience 51, 10.1641/0006-3568(2001)051[0933:Teotwa]2.0.Co;2 (2001).
Silverman, B. W. Density estimation for statistics and data analysis. (Routledge, 2018).
Schoener, T. W. Nonsynchronous Spatial Overlap of Lizards in Patchy Habitats. Ecology 51, 408–418, https://doi.org/10.2307/1935376 (1970).
doi: 10.2307/1935376
Blonder, B. & Harris, D. J. High Dimensional Geometry and Set Operations Using Kernel Density Estimation, Support Vector Machines, and Convex Hulls. R package. v. 2.0.11 (2018).
Mammola, S. & Leroy, B. Applying species distribution models to caves and other subterranean habitats. Ecography 41, 1194–1208, https://doi.org/10.1111/ecog.03464 (2018).
doi: 10.1111/ecog.03464
Hastie, T., Tibshirani, R. Generalized additive models. (John Wiley & Sons, Inc., 1990).
McCullagh, P., Nelder, J. A. Generalized Linear Models. 2 edn, (Chapman & Hall/CRC, 1989).
Friedman, J. H. Multivariate Adaptive Regression Splines. The Annals of Statistics 19, 1–67, https://doi.org/10.1214/aos/1176347963 (1991).
doi: 10.1214/aos/1176347963
Breiman, L., Friedman, J., Stone, C. J., Olshen, R.A. Classification and regression trees. (CRC press, 1984).
Lek, S. & Guégan, J. F. Artificial neural networks as a tool in ecological modelling, an introduction. Ecological Modelling 120, 65–73, https://doi.org/10.1016/s0304-3800(99)00092-7 (1999).
doi: 10.1016/s0304-3800(99)00092-7
Breiman, L. Random Forest. Machine Learning 45, 5–32, https://doi.org/10.1023/a:1010933404324 (2001).
doi: 10.1023/a:1010933404324
Friedman, J. H. Greedy Function Approximation: A Gradient Boosting Machine. The Annals of Statistics 29, 1189–1232 (2001).
doi: 10.1214/aos/1013203451
Phillips, S. J., Anderson, R. P. & Schapire, R. E. Maximum entropy modeling of species geographic distributions. Ecological Modelling 190, 231–259, https://doi.org/10.1016/j.ecolmodel.2005.03.026 (2006).
doi: 10.1016/j.ecolmodel.2005.03.026
Barbet-Massin, M., Jiguet, F., Albert, C. H. & Thuiller, W. Selecting pseudo-absences for species distribution models: how, where and how many? Methods in Ecology and Evolution 3, 327–338, https://doi.org/10.1111/j.2041-210x.2011.00172.x (2012).
doi: 10.1111/j.2041-210x.2011.00172.x
Thuiller, W., Lafourcade, B., Engler, R. & Araújo, M. B. BIOMOD - a platform for ensemble forecasting of species distributions. Ecography 32, 369–373, https://doi.org/10.1111/j.1600-0587.2008.05742.x (2009).
doi: 10.1111/j.1600-0587.2008.05742.x
Thuiller, W., Georges, D., Engler, R. & Breiner, F. biomod2: Species distribution modeling within an ensemble forecasting framework. R Package v. 3.3-7.1 (2016).
Fielding, A. H. & Bell, J. F. A review of methods for the assessment of prediction errors in conservation presence/absence models. Environmental Conservation 24, 38–49, https://doi.org/10.1017/s0376892997000088 (2002).
doi: 10.1017/s0376892997000088
Allouche, O., Tsoar, A. & Kadmon, R. Assessing the accuracy of species distribution models: prevalence, kappa and the true skill statistic (TSS). Journal of Applied Ecology 43, 1223–1232, https://doi.org/10.1111/j.1365-2664.2006.01214.x (2006).
doi: 10.1111/j.1365-2664.2006.01214.x
Swets, J. A. Measuring the accuracy of diagnostic systems. Science 240, 1285–1293, https://doi.org/10.1126/science.3287615 (1988).
doi: 10.1126/science.3287615
pubmed: 3287615
pmcid: 3287615