Quantifying coastal ecosystem trophic state at a macroscale using a Bayesian analytical framework.

ABSTRACT: One of the goals of coastal ecological research is to describe, quantify and predict human effects on coastal ecosystems. Broad cross-systems assessments to classify ecosystem status or condition have been developed, but are not updated frequently, likely because a lot of information and effort is needed to implement them. Such assessments could be more useful if the probability of being in a class indicating status or condition could be predicted using widely available data and information, providing a useful way to interpret changes in underlying predictors by considering their expected impact on ecosystem condition. To illustrate a possible approach, we used chlorophyll-a as an indicator of condition, in place of the intended comprehensive condition assessment. We demonstrated a predict

SUBMITTER: Hagy JD 

PROVIDER: S-EPMC10031516 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature