Uncovering broad macroecological patterns by comparing the shape of species' distributions along environmental gradients

Détails

ID Serval
serval:BIB_3D0B0A4B4098
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Institution
Titre
Uncovering broad macroecological patterns by comparing the shape of species' distributions along environmental gradients
Périodique
American Naturalist
Auteur⸱e⸱s
Bramon Mora B., Guisan A., Alexander J.M.
Statut éditorial
Publié
Date de publication
2024
Peer-reviewed
Oui
Volume
203
Numéro
1
Pages
124-138
Langue
anglais
Résumé
Species’ distributions can take many different forms. For example, fat-tailed or skewed distributions are very common in nature, as these can naturally emerge as a result of individual variability and asymmetric environmental tolerances, respectively. Studying the basic shape of distributions can teach us a lot about the ways climatic processes and historical contingencies shape ecological communities. Yet we still lack a general understanding of how their shapes and properties compare to each other along gradients. Here, we use Bayesian nonlinear models to quantify range shape properties in empirical plant distributions. With this approach, we are able to distil the shape of plant distributions and compare them along gradients and across species. Studying the relationship between distribution properties, we revealed the existence of broad macroecological patterns along environmental gradients—such as those expected from Rapoport’s rule and the abiotic stress limitation hypothesis. We also find that some aspects of the shape of observed ranges—such as kurtosis and skewness of the distributions—could be intrinsic properties of species or the result of their historical contexts. Overall, our modeling approach and results untangle the general shape of plant distributions and provide a mapping of how this changes along environmental gradients.
Mots-clé
community assembly, community modeling, community distribution, joint species distribution models, nonlinear response curves, environmental filtering
Création de la notice
09/08/2023 14:46
Dernière modification de la notice
18/05/2024 5:59
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