Reciprocal insights from global aquatic stressor maps and local reporting across the Ramsar wetland network. (February 2020)

• Record Type: Journal Article
• Authors: Fluet-Chouinard, Etienne; Stewart-Koster, Ben; Davidson, Nick; Max Finlayson, C.; B. McIntyre, Peter
• Is Part Of: Ecological indicators. Volume 109(2020)
• Publication Date: 2020-02
• Subjects: Freshwater ecosystems -- Multi-stressor -- Global mapping -- In situ monitoring -- Ramsar convention -- Wetlands; Environmental monitoring -- Periodicals; Environmental management -- Periodicals; Environmental impact analysis -- Periodicals; Environmental risk assessment -- Periodicals; Sustainable development -- Periodicals; 333.71405
• DOI: 10.1016/j.ecolind.2019.105772
• Languages: English
• ISSNs: 1470-160X

Abstract

Highlights: Stressor exposure from global maps and in situ reporting aligns weakly. Hydrological stressors have the highest agreement among data sources. Stressor weights can be estimated from in situ stressor data. Integration of in situ stressor monitoring can improve cumulative stress indices. Ecological monitoring networks can help monitor ecological stressors globally. Abstract: Aquatic ecosystems are exposed to a host of anthropogenic stressors whose combined effect can be synthesized with cumulative stress indices. The reliability of cumulative stress indices depends primarily on: 1) stressor incidence maps derived from remote sensing or modeling but rarely validated against on-the-ground observations, and 2) the weighting scheme used to combine multiple stressors into a cumulative index typically based on expert opinion. In this paper, we evaluate the exposure and weights for 13 aquatic stressor maps of the world's rivers with a comparison against local stress reporting across 1018 inland and coastal sites from the Ramsar Wetlands of International Importance. We found that globally-mapped and locally-reported stressors are poorly aligned overall (AUC-ROC = 0.50–0.63), and that concordance did not improve when stratifying by ecosystem types or continents. Agreement varied across individual stressors, was highest for hydrological stressors and lowest for habitat disconnectivity stressors. We estimated stressor weights from the comparison and found them to be remarkably aligned well with expert-generated weights, suggesting there is convergence on a stressor hierarchy across local and global scales. Our comparison illustrates the value of integrating data across scales to inform the calculation of global stressor indices. Continued systematic stressor monitoring across environmental observation networks is central to benchmarking maps of ecosystem stress globally.