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Evans MEK, Dey SMN, Heilman KA, Tipton JR, DeRose RJ, Klesse S, Schultz EL, Shaw JD. Tree rings reveal the transient risk of extinction hidden inside climate envelope forecasts. Proc Natl Acad Sci U S A 2024; 121:e2315700121. [PMID: 38830099 PMCID: PMC11181036 DOI: 10.1073/pnas.2315700121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2023] [Accepted: 04/03/2024] [Indexed: 06/05/2024] Open
Abstract
Given the importance of climate in shaping species' geographic distributions, climate change poses an existential threat to biodiversity. Climate envelope modeling, the predominant approach used to quantify this threat, presumes that individuals in populations respond to climate variability and change according to species-level responses inferred from spatial occurrence data-such that individuals at the cool edge of a species' distribution should benefit from warming (the "leading edge"), whereas individuals at the warm edge should suffer (the "trailing edge"). Using 1,558 tree-ring time series of an aridland pine (Pinus edulis) collected at 977 locations across the species' distribution, we found that trees everywhere grow less in warmer-than-average and drier-than-average years. Ubiquitous negative temperature sensitivity indicates that individuals across the entire distribution should suffer with warming-the entire distribution is a trailing edge. Species-level responses to spatial climate variation are opposite in sign to individual-scale responses to time-varying climate for approximately half the species' distribution with respect to temperature and the majority of the species' distribution with respect to precipitation. These findings, added to evidence from the literature for scale-dependent climate responses in hundreds of species, suggest that correlative, equilibrium-based range forecasts may fail to accurately represent how individuals in populations will be impacted by changing climate. A scale-dependent view of the impact of climate change on biodiversity highlights the transient risk of extinction hidden inside climate envelope forecasts and the importance of evolution in rescuing species from extinction whenever local climate variability and change exceeds individual-scale climate tolerances.
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Affiliation(s)
| | - Sharmila M. N. Dey
- Department of Earth and Planetary Sciences, Harvard University, Cambridge, MA02138
| | - Kelly A. Heilman
- Laboratory of Tree-Ring Research, University of Arizona, Tucson, AZ85721
| | - John R. Tipton
- Statistical Sciences Group, Los Alamos National Laboratory, Los Alamos, NM87545
| | - R. Justin DeRose
- Department of Wildland Resources and Ecology Center, Utah State University, Logan, UT84322
| | - Stefan Klesse
- Forest Dynamics, Swiss Federal Institute for Forest, Snow, and Landscape Research WSL, BirmensdorfCH-8903, Switzerland
| | - Emily L. Schultz
- Department of Biology, Colorado Mountain College, Breckenridge, CO80424
| | - John D. Shaw
- Riverdale Forestry Sciences Lab, Rocky Mountain Research Station, US Forest Service, Riverdale, UT84405
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Folk RA, Charboneau JLM, Belitz M, Singh T, Kates HR, Soltis DE, Soltis PS, Guralnick RP, Siniscalchi CM. Anatomy of a mega-radiation: Biogeography and niche evolution in Astragalus. AMERICAN JOURNAL OF BOTANY 2024; 111:e16299. [PMID: 38419145 DOI: 10.1002/ajb2.16299] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/07/2023] [Revised: 01/19/2024] [Accepted: 01/22/2024] [Indexed: 03/02/2024]
Abstract
PREMISE Astragalus (Fabaceae), with more than 3000 species, represents a globally successful radiation of morphologically highly similar species predominant across the northern hemisphere. It has attracted attention from systematists and biogeographers, who have asked what factors might be behind the extraordinary diversity of this important arid-adapted clade and what sets it apart from close relatives with far less species richness. METHODS Here, for the first time using extensive phylogenetic sampling, we asked whether (1) Astragalus is uniquely characterized by bursts of radiation or whether diversification instead is uniform and no different from closely related taxa. Then we tested whether the species diversity of Astragalus is attributable specifically to its predilection for (2) cold and arid habitats, (3) particular soils, or to (4) chromosome evolution. Finally, we tested (5) whether Astragalus originated in central Asia as proposed and (6) whether niche evolutionary shifts were subsequently associated with the colonization of other continents. RESULTS Our results point to the importance of heterogeneity in the diversification of Astragalus, with upshifts associated with the earliest divergences but not strongly tied to any abiotic factor or biogeographic regionalization tested here. The only potential correlate with diversification we identified was chromosome number. Biogeographic shifts have a strong association with the abiotic environment and highlight the importance of central Asia as a biogeographic gateway. CONCLUSIONS Our investigation shows the importance of phylogenetic and evolutionary studies of logistically challenging "mega-radiations." Our findings reject any simple key innovation behind high diversity and underline the often nuanced, multifactorial processes leading to species-rich clades.
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Affiliation(s)
- Ryan A Folk
- Department of Biological Sciences, Mississippi State University, Mississippi State, MS, USA
| | - Joseph L M Charboneau
- Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, MI, USA
| | - Michael Belitz
- Florida Museum, University of Florida, Gainesville, FL, USA
| | - Tajinder Singh
- Department of Biological Sciences, Mississippi State University, Mississippi State, MS, USA
| | | | - Douglas E Soltis
- Florida Museum, University of Florida, Gainesville, FL, USA
- Genetics Institute, University of Florida, Gainesville, FL, USA
- Biodiversity Institute, University of Florida, Gainesville, FL, USA
- Department of Biology, University of Florida, Gainesville, FL, USA
| | - Pamela S Soltis
- Florida Museum, University of Florida, Gainesville, FL, USA
- Genetics Institute, University of Florida, Gainesville, FL, USA
- Biodiversity Institute, University of Florida, Gainesville, FL, USA
| | - Robert P Guralnick
- Florida Museum, University of Florida, Gainesville, FL, USA
- Biodiversity Institute, University of Florida, Gainesville, FL, USA
| | - Carolina M Siniscalchi
- Department of Biological Sciences, Mississippi State University, Mississippi State, MS, USA
- General Libraries, Mississippi State University, Mississippi State, MS, USA
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Perret DL, Evans MEK, Sax DF. A species' response to spatial climatic variation does not predict its response to climate change. Proc Natl Acad Sci U S A 2024; 121:e2304404120. [PMID: 38109562 PMCID: PMC10769845 DOI: 10.1073/pnas.2304404120] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2023] [Accepted: 10/23/2023] [Indexed: 12/20/2023] Open
Abstract
The dominant paradigm for assessing ecological responses to climate change assumes that future states of individuals and populations can be predicted by current, species-wide performance variation across spatial climatic gradients. However, if the fates of ecological systems are better predicted by past responses to in situ climatic variation through time, this current analytical paradigm may be severely misleading. Empirically testing whether spatial or temporal climate responses better predict how species respond to climate change has been elusive, largely due to restrictive data requirements. Here, we leverage a newly collected network of ponderosa pine tree-ring time series to test whether statistically inferred responses to spatial versus temporal climatic variation better predict how trees have responded to recent climate change. When compared to observed tree growth responses to climate change since 1980, predictions derived from spatial climatic variation were wrong in both magnitude and direction. This was not the case for predictions derived from climatic variation through time, which were able to replicate observed responses well. Future climate scenarios through the end of the 21st century exacerbated these disparities. These results suggest that the currently dominant paradigm of forecasting the ecological impacts of climate change based on spatial climatic variation may be severely misleading over decadal to centennial timescales.
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Affiliation(s)
- Daniel L. Perret
- Department of Ecology, Evolution, and Organismal Biology, Brown University, Providence, RI02912
| | | | - Dov F. Sax
- Department of Ecology, Evolution, and Organismal Biology, Brown University, Providence, RI02912
- Institute at Brown for Environment and Society, Brown University, Providence, RI02912
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Monnier-Corbel A, Robert A, Hingrat Y, Benito BM, Monnet AC. Species Distribution Models predict abundance and its temporal variation in a steppe bird population. Glob Ecol Conserv 2023. [DOI: 10.1016/j.gecco.2023.e02442] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/30/2023] Open
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Auld J, Everingham SE, Hemmings FA, Moles AT. Alpine plants are on the move: Quantifying distribution shifts of Australian alpine plants through time. DIVERS DISTRIB 2022. [DOI: 10.1111/ddi.13494] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023] Open
Affiliation(s)
- Jennifer Auld
- Evolution & Ecology Research Centre School of Biological Earth and Environmental Sciences UNSW Sydney New South Wales Australia
| | - Susan E. Everingham
- Evolution & Ecology Research Centre School of Biological Earth and Environmental Sciences UNSW Sydney New South Wales Australia
- The Australian PlantBank Australian Institute of Botanical Science Royal Botanic Gardens and Domain Trust Botanic Gardens Greater Sydney New South Wales Australia
- Institute of Plant Sciences University of Bern Bern Switzerland
- Oeschger Centre for Climate Change Research University of Bern Bern Switzerland
| | - Frank A. Hemmings
- Evolution & Ecology Research Centre School of Biological Earth and Environmental Sciences UNSW Sydney New South Wales Australia
| | - Angela T. Moles
- Evolution & Ecology Research Centre School of Biological Earth and Environmental Sciences UNSW Sydney New South Wales Australia
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Thomas SM, Verhoeven MR, Walsh JR, Larkin DJ, Hansen GJA. Species distribution models for invasive Eurasian watermilfoil highlight the importance of data quality and limitations of discrimination accuracy metrics. Ecol Evol 2021; 11:12567-12582. [PMID: 34594521 PMCID: PMC8462136 DOI: 10.1002/ece3.8002] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2021] [Revised: 06/20/2021] [Accepted: 07/19/2021] [Indexed: 11/12/2022] Open
Abstract
AIM Availability of uniformly collected presence, absence, and abundance data remains a key challenge in species distribution modeling (SDM). For invasive species, abundance and impacts are highly variable across landscapes, and quality occurrence and abundance data are critical for predicting locations at high risk for invasion and impacts, respectively. We leverage a large aquatic vegetation dataset comprising point-level survey data that includes information on the invasive plant Myriophyllum spicatum (Eurasian watermilfoil) to: (a) develop SDMs to predict invasion and impact from environmental variables based on presence-absence, presence-only, and abundance data, and (b) compare evaluation metrics based on functional and discrimination accuracy for presence-absence and presence-only SDMs. LOCATION Minnesota, USA. METHODS Eurasian watermilfoil presence-absence and abundance information were gathered from 468 surveyed lakes, and 801 unsurveyed lakes were leveraged as pseudoabsences for presence-only models. A Random Forest algorithm was used to model the distribution and abundance of Eurasian watermilfoil as a function of lake-specific predictors, both with and without a spatial autocovariate. Occurrence-based SDMs were evaluated using conventional discrimination accuracy metrics and functional accuracy metrics assessing correlation between predicted suitability and observed abundance. RESULTS Water temperature degree days and maximum lake depth were two leading predictors influencing both invasion risk and abundance, but they were relatively less important for predicting abundance than other water quality measures. Road density was a strong predictor of Eurasian watermilfoil invasion risk but not abundance. Model evaluations highlighted significant differences: Presence-absence models had high functional accuracy despite low discrimination accuracy, whereas presence-only models showed the opposite pattern. MAIN CONCLUSION Complementing presence-absence data with abundance information offers a richer understanding of invasive Eurasian watermilfoil's ecological niche and enables evaluation of the model's functional accuracy. Conventional discrimination accuracy measures were misleading when models were developed using pseudoabsences. We thus caution against the overuse of presence-only models and suggest directing more effort toward systematic monitoring programs that yield high-quality data.
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Affiliation(s)
- Shyam M. Thomas
- Department of Fisheries Wildlife & Conservation Biology and Minnesota Aquatic Invasive Species Research CenterUniversity of MinnesotaSt. PaulMinnesotaUSA
| | - Michael R. Verhoeven
- Department of Fisheries Wildlife & Conservation Biology and Minnesota Aquatic Invasive Species Research CenterUniversity of MinnesotaSt. PaulMinnesotaUSA
| | - Jake R. Walsh
- Department of Fisheries Wildlife & Conservation Biology and Minnesota Aquatic Invasive Species Research CenterUniversity of MinnesotaSt. PaulMinnesotaUSA
- Minnesota Department of Natural ResourcesSt. PaulMinnesotaUSA
| | - Daniel J. Larkin
- Department of Fisheries Wildlife & Conservation Biology and Minnesota Aquatic Invasive Species Research CenterUniversity of MinnesotaSt. PaulMinnesotaUSA
| | - Gretchen J. A. Hansen
- Department of Fisheries Wildlife & Conservation Biology and Minnesota Aquatic Invasive Species Research CenterUniversity of MinnesotaSt. PaulMinnesotaUSA
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