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Title: Understanding and predicting harmful algal blooms in a changing climate: A trait‐based framework
Abstract

The worldwide proliferation of harmful algal blooms (HABs) both in freshwater and marine ecosystems make understanding and predicting their occurrence urgent. Trait‐based approaches, where the focus is on functional traits, have been successful in explaining community structure and dynamics in diverse ecosystems but have not been applied extensively to HABs. The existing trait compilations suggest that HAB taxa differ from non HAB taxa in key traits that determine their responses to major environmental drivers. Multi‐trait comparisons between HAB‐forming and other phytoplankton taxa, as well as within the HAB groups to characterize interspecific and intraspecific differences will help better define ecological niches of different HAB taxa, develop trait‐based mechanistic models, and better identify environmental conditions that would likely lead to HABs. Building databases of HAB traits and using them in diverse statistical and mechanistic models will increase our ability to predict the HAB occurrence, composition, and severity under changing conditions, including the anthropogenic global change.

 
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Award ID(s):
1754250
NSF-PAR ID:
10402107
Author(s) / Creator(s):
 
Publisher / Repository:
Wiley Blackwell (John Wiley & Sons)
Date Published:
Journal Name:
Limnology and Oceanography Letters
Volume:
8
Issue:
2
ISSN:
2378-2242
Page Range / eLocation ID:
p. 229-246
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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