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Title: Structural forecasting of species persistence under changing environments
Abstract

The persistence of a species in a given place not only depends on its intrinsic capacity to consume and transform resources into offspring, but also on how changing environmental conditions affect its growth rate. However, the complexity of factors has typically taken us to choose between understanding and predicting the persistence of species. To tackle this limitation, we propose a probabilistic approach rooted on the statistical concepts of ensemble theory applied to statistical mechanics and on the mathematical concepts of structural stability applied to population dynamics models – what we callstructural forecasting. We show how this new approach allows us to estimate a probability of persistence for single species in local communities; to understand and interpret this probability conditional on the information we have concerning a system; and to provide out‐of‐sample predictions of species persistence as good as the best experimental approaches without the need of extensive amounts of data.

 
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Award ID(s):
2024349
NSF-PAR ID:
10451017
Author(s) / Creator(s):
 ;  ;  ;
Publisher / Repository:
Wiley-Blackwell
Date Published:
Journal Name:
Ecology Letters
Volume:
23
Issue:
10
ISSN:
1461-023X
Page Range / eLocation ID:
p. 1511-1521
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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