How are the impacts of multiple anthropogenic drivers considered in marine ecosystem service research? A systematic literature review
Data files
Feb 26, 2024 version files 62.88 KB
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Data_file._Results_of_database_search_string.xlsx
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Data_file._Selected_publications_for_review.xlsx
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README.md
Abstract
In recent decades, great research efforts have been made to understand how specific anthropogenic drivers impact coastal marine ecosystems and their services. Nevertheless, we still lack a synthesis of the existing knowledge on single and multiple anthropogenic drivers impacts to coastal marine systems, which is necessary to guide future work. The objective of this paper is to assess the current knowledge on the cumulative impacts of anthropogenic drivers on coastal marine ecosystem services, with emphasis on abiotic drivers as dissolved nutrients (eutrophication or de-eutrophication), temperature (warming), pH (acidification), and oxygen (hypoxia). We performed a systematic review of the literature consisting of 164 papers using the PRISMA method (Preferred Reporting Items for Systematic Reviews and Meta-Analyses). We only include English-written papers, we exclude non-English papers to avoid potential errors in representing or interpreting scientific information due to language limitations among the authors. The results show that coastal marine ecosystem service research has largely focused on single drivers, while multiple driver assessments are less common. Assessments partially integrate multiple driver complexity, but they do not consider 1) relations and feedbacks between drivers; 2) social processes dynamics; and 3) temporal and spatial scales. Synthesis and applications: Our review indicates that multiple drivers and their interactions are a pending issue in coastal marine ecosystem services research, as well as the integration of multiple temporal and spatial scales. The failure to integrate multiple driver and scale complexity limits our understanding of reality and results in high levels of uncertainty and deficient coastal ecosystem service management. Policies and management actions, which are based on the information provided by coastal marine ecosystem services research suffer from great uncertainty levels. To fill this gap, we propose a framework to guide future marine ecosystem services research in the integration of multiple driver dynamics, and temporal and spatial scales.
README: How are the impacts of multiple anthropogenic drivers considered in marine ecosystem service research? A systematic literature review
https://doi.org/10.5061/dryad.nvx0k6f01
In this dataset you can find 4 different files:
- Data_file._Results_of_database_search_string.xlsx: is the first necessary DATA file, which contains the results of all the papers found in Scopus using this search string. We limited our bibliographical search to any peer-reviewed publication published from 2004 (the year of the first paper found) to November 2020.
To identify relevant literature, we have conducted a bibliographic search in the Scopus database with the following search string:
Title | Key words | Title, abstract, keywords | Limit to |
---|---|---|---|
"ecosystem service*" | "coastal" OR "marine" | “ocean acidification" OR "sea” “surface temperature" OR "deoxygenation" OR "ocean warming" OR "hypoxia" OR "acidification" OR "sea level rise" OR "temperature" OR "eutrophication" OR "human impact*" OR "impact*" OR "stressor*" OR "multiple stressors" OR "cumulative impact*" OR "multi stressors" OR "multiple impacts" OR "climate change" OR "global change" OR "global warming" OR "human impact*" OR "anthropogenic impact*" | LANGUAGE, "English" |
- Data_file._Selected_publications_for_review.xlsx: is the second necessary DATA file, which contains all the papers finally used for this review, after excluding the papers that did not meet the follwoing criteria: (1) analyze/evaluate/conceptualize/map/quantify drivers of coastal marine ecosystems services; (2) publications in peer-reviewed journals; (3) publications written in English; and (4) papers focused on coastal marine areas.
Methods
This systematic literature review followed the PRISMA statement (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) as means to ensure scientific robustness and reproductivity. The PRISMA checklist and the review protocol can be found in the supplementary material of the publication [DOI to be provided].
To identify relevant literature, we have conducted a bibliographic search in the Scopus database on coastal marine ecosystem services and four main drivers that may affect them: dissolved nutrient concentrations (eutrophication or de-eutrophication), temperature (warming), pH (acidification), and oxygen concentration (hypoxia). We limited our bibliographical search to any peer-reviewed publication published from 2004 (year of the first paper found) to November of 2020.
The search string contained following terms in the keywords “coastal” and “marine”, and terms related to drivers or stressors in the tittle, key words or abstract, Table 1.
Table 1. Search string
Title |
Key words |
Title, abstract, key words |
Limit to |
"ecosystem service*" |
"coastal" OR "marine" |
“ocean acidification" OR "sea” “surface temperature" OR "deoxygenation" OR "ocean warming" OR "hypoxia" OR "acidification" OR "sea level rise" OR "temperature" OR "eutrophication" OR "human impact*" OR "impact*" OR "stressor*" OR "multiple stressors" OR "cumulative impact*" OR "multi stressors" OR "multiple impacts" OR "climate change" OR "global change" OR "global warming" OR "human impact*" OR "anthropogenic impact*" |
LANGUAGE, "English" |
We defined the following inclusion criteria: (1) analyse/ evaluate/ conceptualize/ map/ quantify/ drivers of coastal marine ecosystems services; (2) publications in peer-reviewed journals; (3) publications written in English; and (4) papers focused on coastal marine areas.
We analysed 23 variables and their corresponding response categories to assess how drivers are integrated into coastal marine ecosystem service research. Afterwards, we reviewed all the manuscripts and filled the database. We used basic descriptive statistics to summarize the basic features of the data collected, e.g., count and percentages.