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Title: Hindcast‐validated species distribution models reveal future vulnerabilities of mangroves and salt marsh species
Abstract

Rapid climate change is threatening biodiversity via habitat loss, range shifts, increases in invasive species, novel species interactions, and other unforeseen changes. Coastal and estuarine species are especially vulnerable to the impacts of climate change due to sea level rise and may be severely impacted in the next several decades. Species distribution modeling can project the potential future distributions of species under scenarios of climate change using bioclimatic data and georeferenced occurrence data. However, models projecting suitable habitat into the future are impossible to ground truth. One solution is to develop species distribution models for the present and project them to periods in the recent past where distributions are known to test model performance before making projections into the future. Here, we develop models using abiotic environmental variables to quantify the current suitable habitat available to eight Neotropical coastal species: four mangrove species and four salt marsh species. Using a novel model validation approach that leverages newly available monthly climatic data from 1960 to 2018, we project these niche models into two time periods in the recent past (i.e., within the past half century) when either mangrove or salt marsh dominance was documented via other data sources. Models were hindcast‐validated and then used to project the suitable habitat of all species at four time periods in the future under a model of climate change. For all future time periods, the projected suitable habitat of mangrove species decreased, and suitable habitat declined more severely in salt marsh species.

 
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Award ID(s):
2027654
NSF-PAR ID:
10373744
Author(s) / Creator(s):
 ;  ;  
Publisher / Repository:
Wiley Blackwell (John Wiley & Sons)
Date Published:
Journal Name:
Ecology and Evolution
Volume:
12
Issue:
9
ISSN:
2045-7758
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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