Intraspecific differentiation: Implications for niche and distribution modelling

Aim Mounting evidence suggests that failure of species distribution models to integrate local adaptation hinders our ability to predict distribution ranges, raising the question of whether modelling should be performed at the level of species (clade models) or intraspecific lineages (subclade models...

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Published inJournal of biogeography Vol. 48; no. 2; pp. 415 - 426
Main Authors Collart, Flavien, Hedenäs, Lars, Broennimann, Olivier, Guisan, Antoine, Vanderpoorten, Alain
Format Journal Article Web Resource
LanguageEnglish
Published Oxford Wiley Subscription Services, Inc 01.02.2021
Blackwell
Subjects
Online AccessGet full text
ISSN0305-0270
1365-2699
1365-2699
DOI10.1111/jbi.14009

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Abstract Aim Mounting evidence suggests that failure of species distribution models to integrate local adaptation hinders our ability to predict distribution ranges, raising the question of whether modelling should be performed at the level of species (clade models) or intraspecific lineages (subclade models), characterized by the restricted availability of occurrence points. While Ensembles of Small Models (ESMs) offer an attractive framework for small datasets, their evaluation remains critical. We address these issues in the case of very small datasets inherent to subclade models and discuss which modelling strategy should be applied based on niche overlap among lineages. Location Sweden. Taxon Mosses. Methods Ensembles of Small Models were evaluated by null models built from randomly sampled presence points. We compared the extent of suitable area predicted by the projections of clade and subclade models. Niche overlap was quantified using Schoener's D and Hellinger'sImetrics, and the significance of these metrics in terms of niche conservatism or divergence was assessed by similarity tests. Results We introduced a simple procedure for evaluating ESMs based on the pooling of the statistics used to assess model accuracy from the replicates. Despite fairly high AUC and TSS values, 2 of the 23 subclade models did not perform better than null models and should be discarded. Combined predictions from subclade models contributed, on average, five times more than clade models to the total suitable area predicted by the combination of subclade and clade models. The D and I metrics averaged 0.45 and 0.71, with evidence for niche conservatism in half of the species and no signal for niche divergence. Main conclusions In addition to the assessment of ESM accuracy based on the simple procedure described here, we recommend that ESMs should be systematically evaluated against null models. Lumping or splitting occurrence data at the intraspecific level substantially impacted model projections. Given the poor performance of models based on small datasets, even when employing ESMs, we pragmatically suggest that, in the absence of evidence for niche divergence during diversification of closely related intraspecific lineages, SDMs should be based on all available occurrence data at the species level.
AbstractList Aim Mounting evidence suggests that failure of species distribution models to integrate local adaptation hinders our ability to predict distribution ranges, raising the question of whether modelling should be performed at the level of species (clade models) or intraspecific lineages (subclade models), characterized by the restricted availability of occurrence points. While Ensembles of Small Models (ESMs) offer an attractive framework for small datasets, their evaluation remains critical. We address these issues in the case of very small datasets inherent to subclade models and discuss which modelling strategy should be applied based on niche overlap among lineages. Location Sweden. Taxon Mosses. Methods Ensembles of Small Models were evaluated by null models built from randomly sampled presence points. We compared the extent of suitable area predicted by the projections of clade and subclade models. Niche overlap was quantified using Schoener's D and Hellinger'sImetrics, and the significance of these metrics in terms of niche conservatism or divergence was assessed by similarity tests. Results We introduced a simple procedure for evaluating ESMs based on the pooling of the statistics used to assess model accuracy from the replicates. Despite fairly high AUC and TSS values, 2 of the 23 subclade models did not perform better than null models and should be discarded. Combined predictions from subclade models contributed, on average, five times more than clade models to the total suitable area predicted by the combination of subclade and clade models. The D and I metrics averaged 0.45 and 0.71, with evidence for niche conservatism in half of the species and no signal for niche divergence. Main conclusions In addition to the assessment of ESM accuracy based on the simple procedure described here, we recommend that ESMs should be systematically evaluated against null models. Lumping or splitting occurrence data at the intraspecific level substantially impacted model projections. Given the poor performance of models based on small datasets, even when employing ESMs, we pragmatically suggest that, in the absence of evidence for niche divergence during diversification of closely related intraspecific lineages, SDMs should be based on all available occurrence data at the species level.
AIM: Mounting evidence suggests that failure of species distribution models to integrate local adaptation hinders our ability to predict distribution ranges, raising the question of whether modelling should be performed at the level of species (clade models) or intraspecific lineages (subclade models), characterized by the restricted availability of occurrence points. While Ensembles of Small Models (ESMs) offer an attractive framework for small datasets, their evaluation remains critical. We address these issues in the case of very small datasets inherent to subclade models and discuss which modelling strategy should be applied based on niche overlap among lineages. LOCATION: Sweden. TAXON: Mosses. METHODS: Ensembles of Small Models were evaluated by null models built from randomly sampled presence points. We compared the extent of suitable area predicted by the projections of clade and subclade models. Niche overlap was quantified using Schoener's D and Hellinger'sImetrics, and the significance of these metrics in terms of niche conservatism or divergence was assessed by similarity tests. RESULTS: We introduced a simple procedure for evaluating ESMs based on the pooling of the statistics used to assess model accuracy from the replicates. Despite fairly high AUC and TSS values, 2 of the 23 subclade models did not perform better than null models and should be discarded. Combined predictions from subclade models contributed, on average, five times more than clade models to the total suitable area predicted by the combination of subclade and clade models. The D and I metrics averaged 0.45 and 0.71, with evidence for niche conservatism in half of the species and no signal for niche divergence. MAIN CONCLUSIONS: In addition to the assessment of ESM accuracy based on the simple procedure described here, we recommend that ESMs should be systematically evaluated against null models. Lumping or splitting occurrence data at the intraspecific level substantially impacted model projections. Given the poor performance of models based on small datasets, even when employing ESMs, we pragmatically suggest that, in the absence of evidence for niche divergence during diversification of closely related intraspecific lineages, SDMs should be based on all available occurrence data at the species level.
Aim: Mounting evidence suggests that failure of species distribution models to integrate local adaptation hinders our ability to predict distribution ranges, raising the question of whether modelling should be performed at the level of species (clade models) or intraspecific lineages (subclade models), characterized by the restricted availability of occurrence points. While Ensembles of Small Models (ESMs) offer an attractive framework for small datasets, their evaluation remains critical. We address these issues in the case of very small datasets inherent to subclade models and discuss which modelling strategy should be applied based on niche overlap among lineages. Location: Sweden. Taxon: Mosses. Methods: Ensembles of Small Models were evaluated by null models built from randomly sampled presence points. We compared the extent of suitable area predicted by the projections of clade and subclade models. Niche overlap was quantified using Schoener's D and Hellinger'sImetrics, and the significance of these metrics in terms of niche conservatism or divergence was assessed by similarity tests. Results: We introduced a simple procedure for evaluating ESMs based on the pooling of the statistics used to assess model accuracy from the replicates. Despite fairly high AUC and TSS values, 2 of the 23 subclade models did not perform better than null models and should be discarded. Combined predictions from subclade models contributed, on average, five times more than clade models to the total suitable area predicted by the combination of subclade and clade models. The D and I metrics averaged 0.45 and 0.71, with evidence for niche conservatism in half of the species and no signal for niche divergence. Main conclusions: In addition to the assessment of ESM accuracy based on the simple procedure described here, we recommend that ESMs should be systematically evaluated against null models. Lumping or splitting occurrence data at the intraspecific level substantially impacted model projections. Given the poor performance of models based on small datasets, even when employing ESMs, we pragmatically suggest that, in the absence of evidence for niche divergence during diversification of closely related intraspecific lineages, SDMs should be based on all available occurrence data at the species level.
AimMounting evidence suggests that failure of species distribution models to integrate local adaptation hinders our ability to predict distribution ranges, raising the question of whether modelling should be performed at the level of species (clade models) or intraspecific lineages (subclade models), characterized by the restricted availability of occurrence points. While Ensembles of Small Models (ESMs) offer an attractive framework for small datasets, their evaluation remains critical. We address these issues in the case of very small datasets inherent to subclade models and discuss which modelling strategy should be applied based on niche overlap among lineages.LocationSweden.TaxonMosses.MethodsEnsembles of Small Models were evaluated by null models built from randomly sampled presence points. We compared the extent of suitable area predicted by the projections of clade and subclade models. Niche overlap was quantified using Schoener's D and Hellinger'sImetrics, and the significance of these metrics in terms of niche conservatism or divergence was assessed by similarity tests.ResultsWe introduced a simple procedure for evaluating ESMs based on the pooling of the statistics used to assess model accuracy from the replicates. Despite fairly high AUC and TSS values, 2 of the 23 subclade models did not perform better than null models and should be discarded. Combined predictions from subclade models contributed, on average, five times more than clade models to the total suitable area predicted by the combination of subclade and clade models. The D and I metrics averaged 0.45 and 0.71, with evidence for niche conservatism in half of the species and no signal for niche divergence.Main conclusionsIn addition to the assessment of ESM accuracy based on the simple procedure described here, we recommend that ESMs should be systematically evaluated against null models. Lumping or splitting occurrence data at the intraspecific level substantially impacted model projections. Given the poor performance of models based on small datasets, even when employing ESMs, we pragmatically suggest that, in the absence of evidence for niche divergence during diversification of closely related intraspecific lineages, SDMs should be based on all available occurrence data at the species level.
Author Collart, Flavien
Vanderpoorten, Alain
Hedenäs, Lars
Guisan, Antoine
Broennimann, Olivier
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2010; 143
1999; 285
2010; 185
2018; 40
2014; 29
2018; 45
2014; 63
2016; 39
2016; 38
2011; 19
2016; 180
2012; 10
2017; 315
2005; 25
2018; 9
2014; 4
2010; 1
2013; 16
2009; 53
2019; 25
2019; 28
2016; 43
2019; 118
2014; 17
2020; 43
2009; 19
2018; 33
2008; 62
2007; 22
2012; 21
2009; 15
2018; 37
2010; 9
2012; 62
2005; 36
2010; 33
2019; 9
2015; 6
2019; 191
2010; 37
2015; 5
2019; 5
2020; 42
2017; 26
2013; 40
2017; 66
2019; 34
2008; 17
2013; 100
2019; 223
1999; 102
2001; 29
2016; 18
2018; 67
1985; 88
2019; 140
2011; 38
2007; 56
2006; 199
2012; 73
2017; 109
2016; 6
2015; 69
2013; 36
2013; 38
2019; 41
2004; 58
2005; 5
2019
2014; 37
2017
2016
2013
2020; 114
2016; 29
2016; 27
2016; 26
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Hijmans R. J. (e_1_2_7_35_1) 2017
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Snippet Aim Mounting evidence suggests that failure of species distribution models to integrate local adaptation hinders our ability to predict distribution ranges,...
AimMounting evidence suggests that failure of species distribution models to integrate local adaptation hinders our ability to predict distribution ranges,...
AIM: Mounting evidence suggests that failure of species distribution models to integrate local adaptation hinders our ability to predict distribution ranges,...
Aim: Mounting evidence suggests that failure of species distribution models to integrate local adaptation hinders our ability to predict distribution ranges,...
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SubjectTerms biogeography
Biologie végétale (sciences végétales, sylviculture, mycologie...)
Boyce index
bryophytes
data collection
Datasets
Divergence
Diversity of life
Environmental sciences & ecology
Geographical distribution
Life sciences
Livets mångfald
local adaptation
Lumping
Model accuracy
Modelling
niche conservatism
Niche overlap
niche similarity
Niches
Phytobiology (plant sciences, forestry, mycology...)
Sciences de l’environnement & écologie
Sciences du vivant
Species
species distribution models
statistics
Sweden
taxonomy
Title Intraspecific differentiation: Implications for niche and distribution modelling
URI https://onlinelibrary.wiley.com/doi/abs/10.1111%2Fjbi.14009
https://www.proquest.com/docview/2488847071
https://www.proquest.com/docview/2551938648
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Volume 48
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