Investigating cumulative effects across ecological scales.

Conserv Biol

National Center for Ecological Analysis and Synthesis, University of California, 735 State Street #300, Santa Barbara, CA 93101, U.S.A.

Published: February 2019

AI Article Synopsis

  • Species and ecosystems are facing increased anthropogenic stressors, prompting research to understand the cumulative effects of environmental changes.
  • Since the 1970s, diverse methods have been developed in both applied and academic research to assess cumulative effects, with past reviews focusing mainly on practitioners' approaches.
  • The study reviews six categories of CEA methods and identifies research gaps, suggesting that combining different methods can enhance understanding and improve assessments across various ecological impacts and complexities.

Article Abstract

Species, habitats, and ecosystems are increasingly exposed to multiple anthropogenic stressors, fueling a rapidly expanding research program to understand the cumulative impacts of these environmental modifications. Since the 1970s, a growing set of methods has been developed through two parallel, sometimes connected, streams of research within the applied and academic realms to assess cumulative effects. Past reviews of cumulative effects assessment (CEA) methods focused on approaches used by practitioners. Academic research has developed several distinct and novel approaches to conducting CEA. Understanding the suite of methods that exist will help practitioners and academics better address various ecological foci (physiological responses, population impacts, ecosystem impacts) and ecological complexities (synergistic effects, impacts across space and time). We reviewed 6 categories of methods (experimental, meta-analysis, single-species modeling, mapping, qualitative modeling, and multispecies modeling) and examined the ability of those methods to address different levels of complexity. We focused on research gaps and emerging priorities. We found that no single method assessed impacts across the 4 ecological foci and 6 ecological complexities considered. We propose that methods can be used in combination to improve understanding such that multimodel inference can provide a suite of comparable outputs, mapping methods can help prioritize localized models or experimental gaps, and future experiments can be paired from the outset with models they will inform.

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Source
http://dx.doi.org/10.1111/cobi.13125DOI Listing

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