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Does weighting presence records improve the performance of species distribution models? A test using fish larval stages in the Yangtze Estuary

Articolo
Data di Pubblicazione:
2020
Abstract:
To obtain realistic forecasts of the impacts of climate change on species habitat suitability, novel approaches based on species distribution models (SDMs) are being developed and scrutinized. We argue here that, when dealing with data from long-term monitoring programmes, incorporating a temporal weight on the occurrence points may result in a more realistic prediction of a species' potential distribution. Using larval fish presence records collected from 1999 to 2013 in the Yangtze Estuary, China, we compared the performance of ensembles of standard SDMs versus SDMs constructed with weighted time-series presence records in predicting the present and future distributions of the larval stages of two dominant fish. The results of the ensemble SDMs showed that weighted presence records can significantly improve SDM performance, as measured through standard validation metrics. The SDM projections suggest that suitable habitat for both species will decrease under future climate scenarios, with one species (Stolephorus commersonnii) predicted to be more susceptible to climate change than the other (Engraulis japonicus). In addition to range contraction, model projections suggest that the future habitats of both species will shift northward--an implication of climate change that should be considered in future management and conservation strategies for the Yangtze Estuary.
Tipologia CRIS:
01.01 Articolo in rivista
Keywords:
Climate change; Dominant ichthyoplankton; Habitat suitability; Species distribution modelling; The Yangtze Estuary; Weighting distribution data
Elenco autori:
Mammola, Stefano
Autori di Ateneo:
MAMMOLA STEFANO
Link alla scheda completa:
https://iris.cnr.it/handle/20.500.14243/403650
Pubblicato in:
SCIENCE OF THE TOTAL ENVIRONMENT
Journal
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http://www.scopus.com/record/display.url?eid=2-s2.0-85086890829&origin=inward
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