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 in | Journal of biogeography Vol. 48; no. 2; pp. 415 - 426 |
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Main Authors | , , , , |
Format | Journal Article Web Resource |
Language | English |
Published |
Oxford
Wiley Subscription Services, Inc
01.02.2021
Blackwell |
Subjects | |
Online Access | Get full text |
ISSN | 0305-0270 1365-2699 1365-2699 |
DOI | 10.1111/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. |
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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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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 |
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