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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Main Authors: Victoria Culshaw, Mario Mairal, Isabel Sanmartín
Format: Article
Language:English
Published: Frontiers Media S.A. 2021-09-01
Series:Frontiers in Ecology and Evolution
Subjects:
Online Access:https://www.frontiersin.org/articles/10.3389/fevo.2021.662092/full
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spelling 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
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