Biogeography Meets Niche Modeling: Inferring the Role of Deep Time Climate Change When Data Is Limited
Geographic range shifts are one major organism response to climate change, especially if the rate of climate change is higher than that of species adaptation. Ecological niche models (ENM) and biogeographic inferences are often used in estimating the effects of climatic oscillations on species range...
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2021-09-01
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doaj-15c68c2ffb6d45a39127d00bc6d94c362021-09-27T08:18:36ZengFrontiers Media S.A.Frontiers in Ecology and Evolution2296-701X2021-09-01910.3389/fevo.2021.662092662092Biogeography Meets Niche Modeling: Inferring the Role of Deep Time Climate Change When Data Is LimitedVictoria Culshaw0Victoria Culshaw1Mario Mairal2Isabel Sanmartín3Real Jardín Botánico (RJB), CSIC, Madrid, SpainDepartment of Ecology and Ecosystem Management, Technische Universität München (TUM), Munich, GermanyDepartamento de Biodiversidad, Ecología y Evolución, Facultad de Biología, Universidad Complutense de Madrid, Madrid, SpainReal Jardín Botánico (RJB), CSIC, Madrid, SpainGeographic range shifts are one major organism response to climate change, especially if the rate of climate change is higher than that of species adaptation. Ecological niche models (ENM) and biogeographic inferences are often used in estimating the effects of climatic oscillations on species range dynamics. ENMs can be used to track climatic suitable areas over time, but have often been limited to shallow timescales; biogeographic inference can reach greater evolutionary depth, but often lacks spatial resolution. Here, we present a simple approach that treats them as independent and complementary sources of evidence, which, when used in partnership, can be employed to reconstruct geographic range shifts over deep evolutionary timescales. For testing this, we chose two extreme African disjunctions: Camptoloma (Scrophulariaceae) and Canarina (Campanulaceae), each comprising of three species disjunctly distributed in Macaronesia and eastern/southern Africa. Using inferred ancestral ranges in tandem with preindustrial and paleoclimate ENM hindcastings, we show that the disjunct pattern was the result of fragmentation and extinction events linked to Neogene aridification cycles. Our results highlight the importance of considering temporal resolution when building ENMs for rare endemics with small population sizes and restricted climatic tolerances such as Camptoloma, for which models built on averaged monthly variables were more informative than those based on annual bioclimatic variables. Additionally, we show that biogeographic information can be used as truncation threshold criteria for building ENMs in the distant past. Our approach is suitable when there is sparse sampling on species occurrences and associated patterns of genetic variation, such as in the case of ancient endemics with widely disjunct distributions as a result of climate change.https://www.frontiersin.org/articles/10.3389/fevo.2021.662092/fullbiogeographic reconstructiondeep-time climate changeecological niche modelgeographic disjunctionRand Floratemporal resolution |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Victoria Culshaw Victoria Culshaw Mario Mairal Isabel Sanmartín |
spellingShingle |
Victoria Culshaw Victoria Culshaw Mario Mairal Isabel Sanmartín Biogeography Meets Niche Modeling: Inferring the Role of Deep Time Climate Change When Data Is Limited Frontiers in Ecology and Evolution biogeographic reconstruction deep-time climate change ecological niche model geographic disjunction Rand Flora temporal resolution |
author_facet |
Victoria Culshaw Victoria Culshaw Mario Mairal Isabel Sanmartín |
author_sort |
Victoria Culshaw |
title |
Biogeography Meets Niche Modeling: Inferring the Role of Deep Time Climate Change When Data Is Limited |
title_short |
Biogeography Meets Niche Modeling: Inferring the Role of Deep Time Climate Change When Data Is Limited |
title_full |
Biogeography Meets Niche Modeling: Inferring the Role of Deep Time Climate Change When Data Is Limited |
title_fullStr |
Biogeography Meets Niche Modeling: Inferring the Role of Deep Time Climate Change When Data Is Limited |
title_full_unstemmed |
Biogeography Meets Niche Modeling: Inferring the Role of Deep Time Climate Change When Data Is Limited |
title_sort |
biogeography meets niche modeling: inferring the role of deep time climate change when data is limited |
publisher |
Frontiers Media S.A. |
series |
Frontiers in Ecology and Evolution |
issn |
2296-701X |
publishDate |
2021-09-01 |
description |
Geographic range shifts are one major organism response to climate change, especially if the rate of climate change is higher than that of species adaptation. Ecological niche models (ENM) and biogeographic inferences are often used in estimating the effects of climatic oscillations on species range dynamics. ENMs can be used to track climatic suitable areas over time, but have often been limited to shallow timescales; biogeographic inference can reach greater evolutionary depth, but often lacks spatial resolution. Here, we present a simple approach that treats them as independent and complementary sources of evidence, which, when used in partnership, can be employed to reconstruct geographic range shifts over deep evolutionary timescales. For testing this, we chose two extreme African disjunctions: Camptoloma (Scrophulariaceae) and Canarina (Campanulaceae), each comprising of three species disjunctly distributed in Macaronesia and eastern/southern Africa. Using inferred ancestral ranges in tandem with preindustrial and paleoclimate ENM hindcastings, we show that the disjunct pattern was the result of fragmentation and extinction events linked to Neogene aridification cycles. Our results highlight the importance of considering temporal resolution when building ENMs for rare endemics with small population sizes and restricted climatic tolerances such as Camptoloma, for which models built on averaged monthly variables were more informative than those based on annual bioclimatic variables. Additionally, we show that biogeographic information can be used as truncation threshold criteria for building ENMs in the distant past. Our approach is suitable when there is sparse sampling on species occurrences and associated patterns of genetic variation, such as in the case of ancient endemics with widely disjunct distributions as a result of climate change. |
topic |
biogeographic reconstruction deep-time climate change ecological niche model geographic disjunction Rand Flora temporal resolution |
url |
https://www.frontiersin.org/articles/10.3389/fevo.2021.662092/full |
work_keys_str_mv |
AT victoriaculshaw biogeographymeetsnichemodelinginferringtheroleofdeeptimeclimatechangewhendataislimited AT victoriaculshaw biogeographymeetsnichemodelinginferringtheroleofdeeptimeclimatechangewhendataislimited AT mariomairal biogeographymeetsnichemodelinginferringtheroleofdeeptimeclimatechangewhendataislimited AT isabelsanmartin biogeographymeetsnichemodelinginferringtheroleofdeeptimeclimatechangewhendataislimited |
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