PaleoENM: applying ecological niche modeling to the fossil record

Abstract

Abstract.-Ecological niche modeling (ENM) is a quantitative approach to predict species' abiotic requirements. It is a correlative technique, requiring geographically explicit information on species occurrences and the suites of environmental conditions experienced at each occurrence point. The output of these models is a set of environmental suitability rules that can be projected geographically and through time to test biogeographic, ecologic, and evolutionary hypotheses. Although developed by biologists and used extensively in the modern, ENM is in its early stages of application to the deep-time fossil record (hence PaleoENM). In part its limited use in the fossil record thus far reflects the methodological challenge of constructing paleoenvironmental layers needed for PaleoENM analysis, whereas in the modern these layers are available from large public databases (e.g., WorldClim). This paper provides a contextual and methodological framework for appropriately applying PaleoENM, including best practices for developing species occurrence and paleoenvironmental data sets for PaleoENM analyses.

Oscillayers: A dataset for the study of climatic oscillations over Plio‐Pleistocene time‐scales at high spatial‐temporal resolution

“…Such spatially explicit models through time, either derived from ENMs (assuming niche conservatism) or ancestral climatic envelope reconstructions (taking niche divergence into account) might also be used for phylogeographic inferences "as is", or for modelling and testing population demographic hypotheses within a coalescent framework (Collevatti et al, 2015(Collevatti et al, , 2013. Other potential applications include, for example, the generation of PalaeoENMs via georeferenced fossils (Myers et al, 2015); the testing of biodiversity-related hypotheses about palaeo-climatic stability in the tropics (e.g. Couvreur et al, 2015;Kissling et al, 2016;Rakotoarinivo et al, 2013); the testing of predictions of the glacial-sensitive model of island biogeography (Fernández-Palacios et al, 2016;Norder et al, 2019) or the facilitation of landscape connectivity (dispersal corridor) analyses over time in a conservation context (Eberle, Rödder, Beckett, & Ahrens, 2017;Yu et al, 2015).…”

“…Plio‐Pleistocene) climate oscillations is of great utility for understanding the evolution of organisms and their future response to anthropogenic climate change (Bálint et al, ; Comes & Kadereit, ; Espíndola et al, ; Haywood et al, ; Hewitt, ; Lawing & Polly, ; Myers, Stigall, & Lieberman, ). Spatially explicit palaeo‐climatic data have provided important insights into macroecology (Bálint et al, ; Couvreur et al, ; Kissling, Blach‐Overgaard, Zwaan, & Wagner, ; Rakotoarinivo et al, ), macroevolution (Meseguer et al, ), palaeobiology (Myers et al, ), systematics (Frajman et al, ; Younger et al, ), biogeography (Benítez‐Benítez, Escudero, Rodríguez‐Sánchez, Martín‐Bravo, & Jiménez‐Mejías, ; Espíndola et al, ; Silva, Antonelli, Lendel, Moraes, & Manfrin, ; Wang et al, ), palaeophylogeography (Lawing & Polly, ; Lawing, Polly, Hews, & Martins, ; Rödder et al, ) and conservation (Alsos, Alm, Normand, & Brochmann, ). However, such palaeo‐climatic data are currently restricted to a few time periods (e.g.…”

“…explicit palaeo-climatic data have provided important insights into macroecology (Bálint et al, 2018;Couvreur et al, 2015;Kissling, Blach-Overgaard, Zwaan, & Wagner, 2016;Rakotoarinivo et al, 2013), macroevolution (Meseguer et al, 2018), palaeobiology (Myers et al, 2015), systematics (Frajman et al, 2019;Younger et al, 2018), biogeography (Benítez-Benítez, Escudero, Rodríguez-Sánchez, Martín-Bravo, & Jiménez-Mejías, 2018;Espíndola et al, 2012;Silva, Antonelli, Lendel, Moraes, & Manfrin, 2018;Wang et al, 2015), palaeophylogeography (Lawing & Polly, 2011;Lawing, Polly, Hews, & Martins, 2016;Rödder et al, 2013) and conservation (Alsos, Alm, Normand, & Brochmann, 2009). However, such palaeo-climatic data are currently restricted to a few time periods (e.g.…”

Concept drift over geological times: predictive modeling baselines for analyzing the mammalian fossil record

“…Predictive modeling for paleoclimate reconstruction has methodological similarities to ecological niche modeling. The goal there is to predicting or characterize environmental conditions at which a given species can occur (Myers et al 2015;Warton et al 2015). In paleoclimate reconstruction, which is the subject of our study, the task is to predict climate given species occurrences with or without complementary data, describing characteristics of those species.…”

Cyst size trends in the genus Leiosphaeridia across the Mulde (lower Silurian) biogeochemical event

“…Shape of the distribution, on the other hand shows how the nutrients and produced biomass are distributed in the planktonic community. It is increasingly recognized that inferred paleoniches are dynamic states which evolve in response to physical perturbations as well as biogeographic and evolutionary turnovers (Myers et al 2015, Lieberman & Saupe 2016, Patzkowsky & Holland 2016. Therefore, the quantification of these parameters is a crucial step in narrowing down the probable determinants and understanding the geobiological consequences of the eco-evolutionary change of phytoplankton.…”