There is an urgent need to understand species and community responses to climatic and ecological changes to predict biodiversity patterns given anticipated global change. The current distribution of species and the environment provide a limited perspective to study and predict ecological responses; therefore, biodiversity responses to past environmental changes must be examined. The rapid development of ecological niche models (ENMs) and their use in reconstructing past species distributions has facilitated inclusion of past observations into predictive models. Paleodata offer an opportunity to test the predictive ability of ENMs and their underlying assumptions. However, paleodata remain underutilized despite the rapidly growing field of paleoinformatics. New modeling methods that incorporate species associations, coupled with paleodata, provide more robust approaches to studying species and community responses, especially given the predicted emergence of no-analog climates and communities in the future.


Article metrics loading...

Loading full text...

Full text loading...


Literature Cited

  1. Acevedo P, Melo-Ferreira J, Real R, Alves PC. 2012. Past, present and future distributions of an Iberian endemic, Lepus granatensis: ecological and evolutionary clues from species distribution models. PLOS ONE 7:12e51529 [Google Scholar]
  2. Ahmed SE, McInerny G, O'Hara K, Harper R, Salido L. 2015. Scientists and software: surveying the species distribution modeling community. Divers. Distrib. 21:258–67 [Google Scholar]
  3. Alba-Sánchez F, López-Sáez JA, Pando BB-D, Linares JC, Nieto-Lugilde D, López-Merino L. 2010. Past and present potential distribution of the Iberian Abies species: a phytogeographic approach using fossil pollen data and species distribution models. Divers. Distrib 16:2214–28 [Google Scholar]
  4. Araújo MB, Luoto M. 2007. The importance of biotic interactions for modelling species distributions under climate change. Glob. Ecol. Biogeogr. 16:6743–53 [Google Scholar]
  5. Baselga A, Araújo MB. 2009. Individualistic versus community modelling of species distributions under climate change. Ecography 32:55–65 [Google Scholar]
  6. Baselga A, Araújo MB. 2010. Do community-level models describe community variation effectively?. J. Biogeogr.1842–50 [Google Scholar]
  7. Behrensmeyer AK, Kidwell SM, Gastaldo RA. 2000. Taphonomy and paleobiology. Paleobiology 26:Suppl.103–47 [Google Scholar]
  8. Blaauw M. 2010. Methods and code for “classical” age-modelling of radiocarbon sequences. Quat. Geochronol. 5:512–18 [Google Scholar]
  9. Blois JL, Gotelli NJ, Behrensmeyer AK, Faith JT, Lyons SK. et al. 2014. A framework for evaluating the influence of climate, dispersal limitation, and biotic interactions using fossil pollen associations across the late Quaternary. Ecography 37:1095–108 [Google Scholar]
  10. Blois JL, Williams JW, Fitzpatrick MC, Ferrier S, Veloz SD. et al. 2013a. Modeling the climatic drivers of spatial patterns in vegetation composition since the Last Glacial Maximum. Ecography 36:4460–73 [Google Scholar]
  11. Blois JL, Williams JW, Fitzpatrick MC, Jackson ST, Ferrier S. 2013b. Space can substitute for time in predicting climate-change effects on biodiversity. PNAS 110:9374–79 [Google Scholar]
  12. Blois JL, Williams JW, Grimm EC, Jackson ST, Graham RW. 2011. A methodological framework for assessing and reducing temporal uncertainty in paleovegetation mapping from late-Quaternary pollen records. Quat. Sci. Rev. 30:1926–39 [Google Scholar]
  13. Blois JL, Zarnetske PL, Fitzpatrick MC, Finnegan S. 2013c. Climate change and the past, present, and future of biotic interactions. Science 341:499–504 [Google Scholar]
  14. Bonthoux S, Baselga A, Balent G. 2013. Assessing community-level and single-species model predictions of species distributions and assemblage composition after 25 years of land cover change. PLOS ONE 8:e54179 [Google Scholar]
  15. Booker DJ, Snelder TH, Greenwood MJ, Crow SK. 2015. Relationships between invertebrate communities and both hydrological regime and other environmental factors across New Zealand's rivers. Ecohydrology 8:13–32 [Google Scholar]
  16. Botkin DB, Saxe H, Araújo MB, Betts R, Bradshaw RHW. 2007. Forecasting the effects of global warming on biodiversity. BioScience 57:3227–36 [Google Scholar]
  17. Braganza K, Karoly D, Hirst A, Mann M, Stott P. et al. 2003. Simple indices of global climate variability and change: Part I—variability and correlation structure. Clim. Dyn. 20:5491–502 [Google Scholar]
  18. Brewer S, Jackson ST, Williams JW. 2012. Paleoecoinformatics: applying geohistorical data to ecological questions. Trends Ecol. Evol. 27:2104–12 [Google Scholar]
  19. Bronk Ramsey C. 2008. Radiocarbon dating: revolutions in understanding. Archaeometry 50:2249–75 [Google Scholar]
  20. Cannariato KG, Kennett JP, Behl RJ. 1999. Biotic response to late Quaternary rapid climate switches in Santa Barbara Basin: ecological and evolutionary implications. Geology 27:63–66 [Google Scholar]
  21. Clark JS, Gelfand AE, Woodall CW, Zhu K. 2014. More than the sum of the parts: forest climate response from joint species distribution models. Ecol. Appl. 24:5990–99 [Google Scholar]
  22. COHMAP Memb 1988. Climate changes of the last 18,000 years: observations and model simulations. Science 241:1043–52 [Google Scholar]
  23. Collevatti RG, Terribile LC, de Oliveira G, Lima-Ribeiro MS, Nabout JC. et al. 2013. Drawbacks to palaeodistribution modelling: the case of South American seasonally dry forests. J. Biogeogr. 40:2345–58 [Google Scholar]
  24. Cunze S, Heydel F, Tackenberg O. 2013. Are plant species able to keep pace with the rapidly changing climate?. PLOS ONE 8:7e67909 [Google Scholar]
  25. Dawson TP, Jackson ST, House JI, Prentice IA, Mace GM. 2011. Beyond predictions: biodiversity conservation in a changing climate. Science 332:53–58 [Google Scholar]
  26. Dobrowski SZ, Thorne JH, Greenberg JA, Safford HD, Mynsberge AR. et al. 2011. Modeling plant ranges over 75 years of climate change in California, USA: temporal transferability and species traits. Ecol. Monogr. 81:2241–57 [Google Scholar]
  27. Dormann CF. 2007. Promising the future? Global change projections of species distributions. Basics Appl. Ecol. 8:387–97 [Google Scholar]
  28. Dormann CF, McPherson JM, Araújo MB, Bivand R, Bolliger J. et al. 2007. Methods to account for spatial autocorrelation in the analysis of species distributional data: a review. Ecography 30:5609–28 [Google Scholar]
  29. Dudei NL, Stigall AL. 2010. Palaeogeography, palaeoclimatology, palaeoecology. Palaeogeogr. Palaeoclim. Palaeoecol. 296:28–43 [Google Scholar]
  30. Elith J, Leathwick JR. 2009. Species distribution models: ecological explanation and prediction across space and time. Annu. Rev. Ecol. Evol. Syst. 40:677–97 [Google Scholar]
  31. Ellis N, Smith SJ, Pitcher CR. 2012. Gradient forests: calculating importance gradients on physical predictors. Ecology 93:156–68 [Google Scholar]
  32. Faith JT. 2011. Late Pleistocene climate change, nutrient cycling, and the megafaunal extinctions in North America. Quat. Sci. Rev. 30:1675–80 [Google Scholar]
  33. FAUNMAP Work. Group 1996. Spatial response of mammals to late Quaternary environmental fluctuations. Science 272:1601–6 [Google Scholar]
  34. Feeley KJ, Silman MR. 2010. Biotic attrition from tropical forests correcting for truncated temperature niches. Glob. Change Biol. 16:61830–36 [Google Scholar]
  35. Ferrier S, Guisan A. 2006. Spatial modelling of biodiversity at the community level. J. Appl. Ecol. 43:3393–404 [Google Scholar]
  36. Ferrier S, Manion G, Elith J, Richardson K. 2007. Using generalized dissimilarity modelling to analyse and predict patterns of beta diversity in regional biodiversity assessment. Divers. Distrib. 13:253–64 [Google Scholar]
  37. Fitzpatrick MC, Sanders NJ, Ferrier S, Longino JT, Weiser MD, Dunn R. 2011. Forecasting the future of biodiversity: a test of single- and multi-species models for ants in North America. Ecography 34:836–47 [Google Scholar]
  38. Fordham DA, Brook BW, Moritz C, Nogués-Bravo D. 2014. Better forecasts of range dynamics using genetic data. Trends Ecol. Evol. 29:8436–43 [Google Scholar]
  39. Garcia RA, Cabeza M, Rahbek C, Araújo MB. 2014. Multiple dimensions of climate change and their implications for biodiversity. Science 344:1247579 [Google Scholar]
  40. Garzon MB, Sanchez de Dios R, Sainz Ollero H. 2008. The evolution of the Pinus sylvestris L. area in the Iberian Peninsula from the last glacial maximum to 2100 under climate change. Holocene 18:5705–14 [Google Scholar]
  41. Gavin DG, Fitzpatrick MC, Gugger PF, Heath KD, Rodríguez-Sánchez F. et al. 2014. Climate refugia: joint inference from fossil records, species distribution models and phylogeography. N. Phytol. 204:137–54 [Google Scholar]
  42. Gill JL, Williams JW, Jackson ST, Donnelly JP, Schellinger GC. 2012. Climate and megaherbivory controls on late-glacial vegetation dynamics: a new, high-resolution, multi-proxy record from Silver Lake, Ohio. Quat. Sci. Rev. 34:66–80 [Google Scholar]
  43. Gilman SE, Urban MC, Tewksbury J, Gilchrist GW, Holt RD. 2010. A framework for community interactions under climate change. Trends Ecol. Evol. 25:6325–31 [Google Scholar]
  44. Goring S, Lacourse T, Pellatt MG, Mathewes RF. 2013. Pollen assemblage richness does not reflect regional plant species richness: a cautionary tale. J. Ecol. 101:1137–45 [Google Scholar]
  45. Gotelli NJ, McCabe DJ. 2002. Species co-occurrence: a meta-analysis of J.M. Diamond's assembly rules model. Ecology 83:32091–96 [Google Scholar]
  46. Gotelli NJ, Ulrich W. 2010. The empirical Bayes approach as a tool to identify non-random species associations. Oecologia 162:463–77 [Google Scholar]
  47. Graham RW. 2005. Quaternary mammal communities: relevance of the individualistic response and non-analogue faunas. Paleontol. Soc. Pap. 11:141–58 [Google Scholar]
  48. Hampton SE, Strasser CA, Tewksbury JJ, Gram WK, Budden AE. et al. 2013. Big data and the future of ecology. Front. Ecol. Environ. 11:3156–62 [Google Scholar]
  49. Harris DJ. 2015. Generating realistic assemblages with a joint species distribution model. Methods Ecol. Evol. 6:465–73 [Google Scholar]
  50. Hutchinson GE. 1957. Concluding remarks. Cold Spring Harb. Symp. Quant. Biol. 22:415–27 [Google Scholar]
  51. Jackson ST, Betancourt JL, Booth RK, Gray ST. 2009. Ecology and the ratchet of events: climate variability, niche dimensions, and species distributions. PNAS 106:Suppl. 219685–92 [Google Scholar]
  52. Jackson ST, Blois JL. 2015. Community ecology in a changing environment: perspectives from the Quaternary. PNAS 112:4915–21 [Google Scholar]
  53. Kattge J, Díaz S, Wirth C. 2014. Of carrots and sticks. Nat. Geosci. 7:11778–79 [Google Scholar]
  54. Kissling WD, Dormann CF, Groeneveld J, Hickler T, Kühn I. et al. 2012. Towards novel approaches to modelling biotic interactions in multispecies assemblages at large spatial extents. J. Biogeogr. 39:122163–78 [Google Scholar]
  55. Kitamura A. 2004. Effects of seasonality, forced by orbital-insolation cycles, on offshore molluscan faunal change during rapid warming in the Sea of Japan. Palaeogeogr. Palaeoclim. Palaeoecol. 203:169–78 [Google Scholar]
  56. Lambeck RJ. 1997. Focal species: a multi-species umbrella for nature conservation. Conserv. Biol. 11:849–56 [Google Scholar]
  57. Landesman WJ, Nelson DM, Fitzpatrick MC. 2014. Soil properties and tree species drive β-diversity of soil bacterial communities. Soil Biol. Biochem. 76:201–9 [Google Scholar]
  58. Latimer AM, Baerjee S, Sang H, Mosher ES, Silander SA Jr. 2009. Hierarchical models facilitate spatial analysis of large data sets: a case study on invasive plant species in the northeastern United States. Ecol. Lett. 12:144–54 [Google Scholar]
  59. Lawing AM, Matzke NJ. 2014. Conservation paleobiology needs phylogenetic methods. Ecography 37:1109–22 [Google Scholar]
  60. Lawing AM, Polly PD. 2011. Pleistocene climate, phylogeny, and climate envelope models: an integrative approach to better understand species' response to climate change. PLOS ONE 6:12e28554 [Google Scholar]
  61. le Roux PC, Pellissier L, Wisz MS, Luoto M. 2014. Incorporating dominant species as proxies for biotic interactions strengthens plant community models. J. Ecol. 102:3767–75 [Google Scholar]
  62. le Roux PC, Virtanen R, Heikkinen RK, Luoto M. 2012. Biotic interactions affect the elevational ranges of high-latitude plant species. Ecography 35:111048–56 [Google Scholar]
  63. Liu Z, Otto-Bliesner BL, He F, Brady EC, Tomas R. et al. 2009. Transient simulation of last deglaciation with a new mechanism for Bølling-Allerød warming. Science 325:310–14 [Google Scholar]
  64. Lorenzen ED, Nogués-Bravo D, Orlando L, Weinstock J, Binladen J. et al. 2012. Species-specific responses of Late Quaternary megafauna to climate and humans. Nature 479:359–64 [Google Scholar]
  65. Lugo AE. 2009. The emerging era of novel tropical forests. Biotropica 41:5589–91 [Google Scholar]
  66. Maguire KC, Stigall AL. 2009. Using ecological niche modeling for quantitative biogeographic analysis: a case study of Miocene and Pliocene Equinae in the Great Plains. Paleobiology 35:4587–611 [Google Scholar]
  67. Maiorano L, Cheddadi R, Zimmermann NE, Pellissier L, Petitpierre B. et al. 2013. Building the niche through time: using 13,000 years of data to predict the effects of climate change on three tree species in Europe. Glob. Ecol. Biogeogr. 22:3302–17 [Google Scholar]
  68. Malizia RW, Stigall AL. 2011. Niche stability in Late Ordivician articulate brachiopod species before, during, and after the Richmondian Invasion. Palaeogeogr. Palaeoclim. Palaeoecol. 311:154–70 [Google Scholar]
  69. Martínez Meyer E, Peterson AT. 2006. Conservatism of ecological niche characteristics in North American plant species over the Pleistocene-to-Recent transition. J. Biogeogr. 33:101779–89 [Google Scholar]
  70. Martínez Meyer E, Townsend Peterson A, Hargrove WW. 2004. Ecological niches as stable distributional constraints on mammal species, with implications for Pleistocene extinctions and climate change projections for biodiversity. Glob. Ecol. Biogeogr. 13:4305–14 [Google Scholar]
  71. McGuire JL, Davis EB. 2013. Using the palaeontological record of Microtus to test species distribution models and reveal responses to climate change. J. Biogeogr. 40:81490–500 [Google Scholar]
  72. Metcalf JL, Prost S, Nogués-Bravo D, DeChaine EG, Anderson C. et al. 2014. Integrating multiple lines of evidence into historical biogeography hypothesis testing: a Bison bison case study. Proc. R. Soc. B 281:20132782 [Google Scholar]
  73. Morgan AV, Morgan A. 1980. Faunal assemblages and distributional shifts of Coleoptera during the late Pleistocene in Canada and the northern United States. Can. Entomol. 112:1105–28 [Google Scholar]
  74. Myers CE, Stigall AL, Lieberman BS. 2015. PaleoENM: applying ecological niche modeling to the fossil record. Paleobiology 41:226–44 [Google Scholar]
  75. Neiva J, Assis J, Fernandes F, Pearson GA, Serrao EA. 2014. Species distribution models and mitochondrial DNA phylogeography suggest an extensive biogeographical shift in the high-intertidal seaweed Pelvetia canaliculata. J. Biogeogr. 41:61137–48 [Google Scholar]
  76. Nieto-Lugilde D, Lenoir J, Abdulhak S, Aeschimann D, Dullinger S. et al. 2015. Tree cover at fine and coarse spatial grains interacts with shade tolerance to shape plant species distributions across the Alps. Ecography 38:578–89 [Google Scholar]
  77. Nogués-Bravo D. 2009. Predicting the past distribution of species climatic niches. Glob. Ecol. Biogeogr. 18:5521–31 [Google Scholar]
  78. Nogués-Bravo D, Rodríguez J, Hortal J, Batra P, Araújo MB. 2008. Climate change, humans, and the extinction of the woolly mammoth. PLOS Biol. 6:4e79 [Google Scholar]
  79. Ordonez A, Martinuzzi S, Radeloff VC, Williams JW. 2014. Combined speeds of climate and land-use change of the conterminous US until 2050. Nat. Clim. Change 4:9811–16 [Google Scholar]
  80. Ovaskainen O, Hottola J, Siitonen J. 2010. Modeling species co-occurrence by multivariate logistic regression generates new hypotheses on fungal interactions. Ecology 91:92514–21 [Google Scholar]
  81. Ovaskainen O, Soininen J. 2011. Making more out of sparse data: hierarchical modeling of species communities. Ecology 92:2289–95 [Google Scholar]
  82. Pearman PB, Guisan A, Broennimann O, Randin CF. 2008a. Niche dynamics in space and time. Trends Ecol. Evol. 23:3149–58 [Google Scholar]
  83. Pearman PB, Randin CF, Broennimann O, Vittoz P, van der Knaap WO. et al. 2008b. Prediction of plant species distributions across six millennia. Ecol. Lett. 11:4357–69 [Google Scholar]
  84. Pedersen MK, Ginolhac A, Orlando L, Olsen J, Andersen K. 2013. A comparative study of ancient environmental DNA to pollen and macrofossils from lake sediments reveal taxonomic overlap and additional plant taxa. Quat. Sci. Rev. 75:161–68 [Google Scholar]
  85. Peres-Neto PR. 2004. Patterns in the co-occurrence of fish species in streams: the role of site suitability, morphology and phylogeny versus species interactions. Oecologia 140:2352–60 [Google Scholar]
  86. Peters SE, Foote M. 2001. Biodiversity in the Phanerozoic: a reinterpretation. Paleobiology 27:4583–601 [Google Scholar]
  87. Peterson AT, Nyári ÁS. 2007. Ecological niche conservatism and Pleistocene refugia in the thrush-like mourner, Schiffornis sp., in the Neotropics. Evolution 62:173–83 [Google Scholar]
  88. Peterson AT, Soberón J, Pearson RG, Anderson RP, Martínez-Myer E. et al. 2011. Ecological Niches and Geographic Distributions Princeton, NJ: Princeton Univ. Press [Google Scholar]
  89. Pollock LJ, Tingley R, Morris WK, Golding N, O'Hara RB. et al. 2014. Understanding co-occurrence by modelling species simultaneously with a Joint Species Distribution Model (JSDM). Methods Ecol. Evol. 5:5397–406 [Google Scholar]
  90. Randin CF, Dirnböck T, Dullinger S, Zimmermann NE, Zappa M, Guisan A. 2006. Are niche-based species distribution models transferable in space?. J. Biogeogr. 33:101689–703 [Google Scholar]
  91. Record S, Fitzpatrick MC, Finley AO, Veloz S, Ellison AM. 2013. Should species distribution models account for spatial autocorrelation? A test of model projections across eight millennia of climate change. Glob. Ecol. Biogeogr. 22:6760–71 [Google Scholar]
  92. Reu B, Zaehle S, Bohn K, Pavlick R, Schmidtlein S. et al. 2014. Future no-analogue vegetation produced by no-analogue combinations of temperature and insolation. Glob. Ecol. Biogeogr. 23:156–67 [Google Scholar]
  93. Richards CL, Carstens BC, Lacey Knowles L. 2007. Distribution modelling and statistical phylogeography: an integrative framework for generating and testing alternative biogeographical hypotheses. J. Biogeogr. 34:111833–45 [Google Scholar]
  94. Ricklefs RE. 2004. A comprehensive framework for global patterns in biodiversity. Ecol. Lett. 7:1–15 [Google Scholar]
  95. Rödder D, Lawing AM, Flecks M, Ahmadzadeh F, Dambach J. et al. 2013. Evaluating the significance of paleophylogeographic species distribution models in reconstructing Quaternary range-shifts of Nearctic Chelonians. PLOS ONE 8:10e72855 [Google Scholar]
  96. Rodríguez-Sánchez F, Arroyo J. 2008. Reconstructing the demise of Tethyan plants: climate-driven range dynamics of Laurus since the Pliocene. Glob. Ecol. Biogeogr. 17:6685–95 [Google Scholar]
  97. Saltré F, Saint-Amant R, Gritti ES, Brewer S, Gaucherel C. et al. 2013. Climate or migration: What limited European beech post-glacial colonization?. Glob. Ecol. Biogeogr. 22:111217–27 [Google Scholar]
  98. Semken HA Jr, Graham RW, Stafford TW Jr. 2010. AMS 14C analysis of Late Pleistocene non-analog faunal components from 21 cave deposits in southeastern North America. Quat. Int. 217:240–55 [Google Scholar]
  99. Shi M-M, Michalski SG, Welk E, Chen X-Y, Durka W. 2014. Phylogeography of a widespread Asian subtropical tree: Genetic east-west differentiation and climate envelope modelling suggest multiple glacial refugia. J. Biogeogr. 41:91710–20 [Google Scholar]
  100. Soranno PA, Cheruvelil KS, Elliott KC, Montgomery GM. 2014. It's good to share: why environmental scientists' ethics are out of date. BioScience 65:169–73 [Google Scholar]
  101. Stigall AL. 2013. Analysing links between biogeography, niche stability and speciation: the impact of complex feedbacks on macroevolutionary patterns. Palaeontology 56:61225–38 [Google Scholar]
  102. Stigall Rode AL, Lieberman BS. 2005. Using environmental niche modeling to study the Late Devonian biodiversity crisis. Understanding Late Devonian and Permian-Triassic Biotic and Climatic Events: Towards an Integrated Approach DJ Over, JR Morrow, PB Wigall 2093–179 Amsterdam: Elsevier [Google Scholar]
  103. Svenning J-C, Fitzpatrick MC, Normand S, Graham CH, Pearman PB. et al. 2010. Geography, topography, and history affect realized-to-potential tree species richness patterns in Europe. Ecography 33:61070–80 [Google Scholar]
  104. Svenning J-C, Fløjgaard C, Marske KA, Nogués-Bravo D, Normand S. 2011. Applications of species distribution modeling to paleobiology. Quat. Sci. Rev. 30:2930–47 [Google Scholar]
  105. Svenning J-C, Skov F. 2004. Limited filling of the potential range in European tree species. Ecol. Lett. 7:565–73 [Google Scholar]
  106. Svenning J-C, Skov F. 2007. Could the tree diversity pattern in Europe be generated by postglacial dispersal limitation?. Ecol. Lett. 10:6453–60 [Google Scholar]
  107. Swanson AK, Dobrowski SZ, Finley AO, Thorne JH, Schwartz MK. 2013. Spatial regression methods capture prediction uncertainty in species distribution model projections through time. Glob. Ecol. Biogeogr. 22:2242–51 [Google Scholar]
  108. Thuiller W, Georges D, Engler R. 2014. biomod2: ensemble platform for species distribution modeling. R package version 3.1-64. http://CRAN.R-project.org/package=biomod2
  109. Tingley MW, Beissinger SR. 2009. Detecting range shifts from historical species occurrences: new perspectives on old data. Trends Ecol. Evol. 24:11625–33 [Google Scholar]
  110. Tzedakis PC. 1994. Vegetation change through glacial-interglacial cycles: a long pollen sequence perspective. Philos. Trans. R. Soc. Lond. B 345:403–32 [Google Scholar]
  111. Uhen MD, Barnosky AD, Bills B, Blois J, Carrano MT. et al. 2013. From card catalogs to computers: databases in vertebrate paleontology. J. Vertebr. Paleontol. 33:113–28 [Google Scholar]
  112. Ulrich W. 2008. Pairs—a FORTRAN program for studying pairwise species associations in ecological matrices Work. Pap., Dep. Anim. Ecol., Univ. Torun [Google Scholar]
  113. Varela S, Lobo JM, Hortal J. 2011. Using species distribution models in paleobiogeography: a matter of data, predictors and concepts. Palaeogeogr. Palaeoclim. Palaeoecol. 310:451–63 [Google Scholar]
  114. Varela S, Lobo JM, Rodríguez J, Batra P. 2010. Were the Late Pleistocene climatic changes responsible for the disappearance of the European spotted hyena populations? Hindcasting a species geographic distribution across time. Quat. Sci. Rev. 29:2027–35 [Google Scholar]
  115. Varela S, Rodríguez J, Lobo JM. 2009. Is current climatic equilibrium a guarantee for the transferability of distribution model predictions? A case study of the spotted hyena. J. Biogeogr. 36:91645–55 [Google Scholar]
  116. Veloz SD, Williams JW, Blois JL, He F, Otto-Bliesner B, Liu Z. 2012. No-analog climates and shifting realized niches during the late quaternary: implications for 21st-century predictions by species distribution models. Glob. Change Biol. 18:51698–713 [Google Scholar]
  117. Waltari E, Guralnick RP. 2009. Ecological niche modelling of montane mammals in the Great Basin, North America: examining past and present connectivity of species across basins and ranges. J. Biogeogr. 36:1148–61 [Google Scholar]
  118. Waltari E, Hijmans RJ, Peterson AT, Nyári ÁS, Perkins SL, Guralnick RP. 2007. Locating Pleistocene refugia: comparing phylogeographic and ecological niche model predictions. PLOS ONE 2:7e563 [Google Scholar]
  119. Werneck FP, Costa GC, Colli GR, Prado DE, Sites JW Jr. 2011. Revisiting the historical distribution of Seasonally Dry Tropical Forests: new insights based on palaeodistribution modelling and palynological evidence. Glob. Ecol. Biogeogr. 20:2272–88 [Google Scholar]
  120. Wiens JA, Stralberg D, Jongsomjit D, Howell CA, Snyder MA. 2009. Niches, models, and climate change: assessing the assumptions and uncertainties. PNAS 106:Suppl. 219729–36 [Google Scholar]
  121. Willerslev E, Davison J, Moora M, Zobel M, Coissac E. 2014. Fifty thousand years of Arctic vegetation and megafaunal diet. Nature 506:47–51 [Google Scholar]
  122. Williams JW, Blois JL, Gill JL, Gonzales LM, Grimm EC. et al. 2013. Model systems for a no-analog future: species associations and climates during the last deglaciation. Ann. N.Y. Acad. Sci. 1297:29–43 [Google Scholar]
  123. Williams JW, Blois JL, Shuman BN. 2011. Extrinsic and intrinsic forcing of abrupt ecological change: case studies from the late Quaternary. J. Ecol. 99:664–77 [Google Scholar]
  124. Williams JW, Jackson ST. 2007. Novel climates, no-analog communities, and ecological surprises. Front. Ecol. Environ. 5:9475–82 [Google Scholar]
  125. Williams JW, Jackson ST, Kutzback JE. 2007. Projected distributions of novel and disappearing climates by 2100 AD. PNAS 104:145738–42 [Google Scholar]
  126. Williams JW, Kharouba HM, Veloz S, Vellend M, McLachlan J. et al. 2012. The ice age ecologist: testing methods for reserve prioritization during the last global warming. Glob. Ecol. Biogeogr. 22:3289–301 [Google Scholar]
  127. Williams JW, Shuman BN, Webb T III, Bartlein PJ, Leduc PL. 2004. Late-Quaternary vegetation dynamics in North America: scaling from taxa to biomes. Ecol. Monogr. 74:2309–34 [Google Scholar]
  128. Wisz MS, Pottier J, Kissling WD, Pellissier L, Lenoir J. et al. 2013. The role of biotic interactions in shaping distributions and realised assemblages of species: implications for distribution modeling. Biol. Rev. 88:15–30 [Google Scholar]
  129. Wolkovich EM, Cook BI, McLauchlan KK, Davies TJ. 2014. Temporal ecology in the Anthropocene. Ecol. Lett. 17:111365–79 [Google Scholar]
  130. Worth JRP, Williamson GJ, Sakaguchi S, Nevill PG, Jordan GJ. 2014. Environmental niche modelling fails to predict Last Glacial Maximum refugia: niche shifts, microrefugia or incorrect palaeoclimate estimates?. Glob. Ecol. Biogeogr. 23:111186–97 [Google Scholar]
  131. Yannic G, Pellissier L, Ortego J, Lecomte N, Couturier S. et al. 2014. Genetic diversity in caribou linked to past and future climate change. Nat. Clim. Change 4:2132–37 [Google Scholar]
  132. Zarnetske PL, Skelly DK, Urban MC. 2012. Biotic multipliers of climate change. Science 366:1516–18 [Google Scholar]
  133. Zimmermann NE, Edwards TC Jr, Graham CH, Pearman PB, Svenning J-C. 2010. New trends in species distribution modelling. Ecography 33:6985–89 [Google Scholar]

Data & Media loading...

Supplementary Data

  • Article Type: Review Article
This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error