in

Niche shifts and environmental non-equilibrium undermine the usefulness of ecological niche models for invasion risk assessments

  • 1.

    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).

  • 2.

    Lewis, S. L. & Maslin, M. A. Defining the anthropocene. Nature 519, 171–180, https://doi.org/10.1038/nature14258 (2015).

  • 3.

    Crutzen, P. J. Geology of mankind. Nature 415, 23, https://doi.org/10.1038/415023a (2002).

  • 4.

    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).

  • 5.

    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).

  • 6.

    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).

  • 7.

    Wittenberg, R., & Cock, M. J. (eds.). Invasive alien species: a toolkit of best prevention and management practices., (CABI, 2001).

  • 8.

    Clout, M. N., Williams, P. A. (eds.). Invasive Species Management: A Handbook of Principles and Techniques. 308 (Oxford University Press, 2009).

  • 9.

    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).

  • 10.

    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).

  • 11.

    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).

  • 12.

    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).

  • 13.

    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).

    • Article
    • Google Scholar
  • 14.

    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).

  • 15.

    Venette, R. C. E. Pest risk modelling and mapping for invasive alien species. (Centre for Agriculture and Bioscience International, 2015).

  • 16.

    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).

    • Article
    • Google Scholar
  • 17.

    Franklin, J. Mapping species distributions: spatial inference and prediction. (Cambridge University Press, 2010).

  • 18.

    Peterson, A. T., et al Ecological niches and geographic distributions (MPB-49) Vol. 56 (Princeton University Press, 2011).

  • 19.

    Guisan, A., Thuiller, W., & Zimmermann, N. E. Habitat suitability and distribution models: with applications in R. (Cambridge University Press, 2017).

  • 20.

    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).

    • Article
    • Google Scholar
  • 21.

    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).

  • 22.

    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).

    • Article
    • Google Scholar
  • 23.

    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).

  • 24.

    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).

    • Article
    • Google Scholar
  • 25.

    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).

    • Article
    • Google Scholar
  • 26.

    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).

  • 27.

    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).

  • 28.

    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).

    • Article
    • Google Scholar
  • 29.

    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).

    • Article
    • Google Scholar
  • 30.

    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).

    • Article
    • Google Scholar
  • 31.

    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).

    • Article
    • Google Scholar
  • 32.

    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).

    • Article
    • Google Scholar
  • 33.

    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).

  • 34.

    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).

    • Article
    • Google Scholar
  • 35.

    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).

    • Article
    • Google Scholar
  • 36.

    Grinnell, J. The Niche-Relationships of the California Thrasher. The Auk 3, 427–433 (1917).

    • Article
    • Google Scholar
  • 37.

    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).

  • 38.

    Hutchinson, G. Concluding remarks. Cold Spring Harbor Symposia on Quantitative Biology 22, 415–427 (1957).

    • Article
    • Google Scholar
  • 39.

    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).

    • Article
    • Google Scholar
  • 40.

    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).

  • 41.

    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).

  • 42.

    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).

    • Article
    • Google Scholar
  • 43.

    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).

    • Article
    • Google Scholar
  • 44.

    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).

  • 45.

    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).

  • 46.

    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).

  • 47.

    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).

  • 48.

    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).

    • Article
    • Google Scholar
  • 49.

    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).

    • Article
    • Google Scholar
  • 50.

    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).

    • Article
    • Google Scholar
  • 51.

    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).

  • 52.

    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).

  • 53.

    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).

  • 54.

    Kraus, F. Alien reptiles and amphibians: a scientific compendium and analysis. Vol. 4 (Springer Science & Business Media, 2009).

  • 55.

    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).

    • Article
    • Google Scholar
  • 56.

    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).

  • 57.

    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).

  • 58.

    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).

    • Article
    • Google Scholar
  • 59.

    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).

    • Article
    • Google Scholar
  • 60.

    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).

  • 61.

    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).

  • 62.

    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).

    • Article
    • Google Scholar
  • 63.

    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).

  • 64.

    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).

    • Article
    • Google Scholar
  • 65.

    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).

  • 66.

    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).

    • Article
    • Google Scholar
  • 67.

    Global Biodiversity Information Facility (GBIF). GBIF Occurrence Download. v. doi: 10.15468/dl.hunni9 (Date of access: 17/2/2019) (2019).

  • 68.

    Darwin Core Task Group. Darwin Core. Biodiversity Information Standards (TDWG), http://www.tdwg.org/standards/450 (2009).

  • 69.

    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).

  • 70.

    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).

  • 71.

    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).

  • 72.

    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).

  • 73.

    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).

    • Article
    • Google Scholar
  • 74.

    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).

    • Article
    • Google Scholar
  • 75.

    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).

  • 76.

    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).

  • 77.

    Rohde, K. Latitudinal Gradients in Species Diversity: The Search for the Primary Cause. Oikos 65, https://doi.org/10.2307/3545569 (1992).

  • 78.

    Wells, K. D. The ecology and behavior of amphibians. (University of Chicago Press, 2010).

  • 79.

    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).

  • 80.

    Caldwell, R. S. Observations on the winter activity of the red-backed salamander, Plethodon cinereus, in Indiana. Herpetologica 31, 21–22 (1975).

    • Google Scholar
  • 81.

    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).

    • Article
    • Google Scholar
  • 82.

    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).

    • Article
    • Google Scholar
  • 83.

    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).

    • Article
    • Google Scholar
  • 84.

    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).

  • 85.

    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).

  • 86.

    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).

    • Article
    • Google Scholar
  • 87.

    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).

    • Article
    • Google Scholar
  • 88.

    R Core Team. R: A language and environment for statistical computing v. 3.6.0 (R Foundation for Statistical Computing, 2019).

  • 89.

    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).

  • 90.

    Silverman, B. W. Density estimation for statistics and data analysis. (Routledge, 2018).

  • 91.

    Schoener, T. W. Nonsynchronous Spatial Overlap of Lizards in Patchy Habitats. Ecology 51, 408–418, https://doi.org/10.2307/1935376 (1970).

    • Article
    • Google Scholar
  • 92.

    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).

  • 93.

    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).

    • Article
    • Google Scholar
  • 94.

    Hastie, T., Tibshirani, R. Generalized additive models. (John Wiley & Sons, Inc., 1990).

  • 95.

    McCullagh, P., Nelder, J. A. Generalized Linear Models. 2 edn, (Chapman & Hall/CRC, 1989).

  • 96.

    Friedman, J. H. Multivariate Adaptive Regression Splines. The Annals of Statistics 19, 1–67, https://doi.org/10.1214/aos/1176347963 (1991).

  • 97.

    Breiman, L., Friedman, J., Stone, C. J., Olshen, R.A. Classification and regression trees. (CRC press, 1984).

  • 98.

    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).

    • Article
    • Google Scholar
  • 99.

    Breiman, L. Random Forest. Machine Learning 45, 5–32, https://doi.org/10.1023/a:1010933404324 (2001).

  • 100.

    Friedman, J. H. Greedy Function Approximation: A Gradient Boosting Machine. The Annals of Statistics 29, 1189–1232 (2001).

  • 101.

    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).

    • Article
    • Google Scholar
  • 102.

    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).

    • Article
    • Google Scholar
  • 103.

    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).

    • Article
    • Google Scholar
  • 104.

    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).

  • 105.

    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).

    • Article
    • Google Scholar
  • 106.

    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).

    • Article
    • Google Scholar
  • 107.

    Swets, J. A. Measuring the accuracy of diagnostic systems. Science 240, 1285–1293, https://doi.org/10.1126/science.3287615 (1988).


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