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Knowns and unknowns in future human pressures on the ocean

Cite this dataset

Vargas Fonseca, Olga Alejandra (2024). Knowns and unknowns in future human pressures on the ocean [Dataset]. Dryad.


Growing demands on ocean resources are placing increasing pressure on ocean ecosystems. To assess the current state of knowledge of future human pressures on the ocean, we conducted a literature review of recent and projected trends of 25 anthropogenic pressures, comprising most of the identified human pressures on the global oceans. To better understand gaps in the data, we developed a comprehensive framework of the activities contributing to each pressure. All pressures were allocated to five categories (biological disruption, disturbance, and removal, altered ocean chemistry, pollution, and climate pressures). All pressures are expected to worsen in the future under business-as-usual scenarios (or similar) based on past trajectories and/or models of future scenarios. Eight of the pressures assessed have not been projected into the future (diseases and pathogens, introduced coastal wildlife predation, disruption to sediment dynamics, wildlife strikes, organic and inorganic chemical pollution, and light and noise pollution), likely due to the limited availability of data describing current pressures, the challenges of modeling future pressures, and high levels of uncertainty. We thus recommend they receive priority attention to assess their likely future trajectories, given their potential magnitude of influence.


A list of anthropogenic pressures (n=25) and corresponding activities was pre-determined and defined, building on similar efforts to catalog pressures (Halpern et al., 2007; O’Hara and Halpern 2022). The summarized list is presented in Figure 1 and the full description of each pressure is in the Supporting Information. This was followed by a scoping review (Collins et al., 2015) to identify available publications on projected ocean pressures at a global scale that had either quantitative or qualitative trend outputs.

The literature search was completed between February and May 2022, using the SCOPUS database. Academic journal articles, books, reports, and grey literature published between 2000-2022, in English, were included. Word search criteria (of titles) included: (global* OR world OR ocean OR coast*) AND (forecast* OR project* OR trend OR predict* OR estimate* OR ensemble OR review); with additional keywords according to each pressure (e.g., “sea level rise”). The results of the database were automatically organized by relevance. A minimum of 60 results was examined by reading the title, abstract, and in some cases full document, to determine its importance. This threshold was chosen arbitrarily.

Additional sources of information were searched, including reports from the Intergovernmental Panel on Climate Change (IPCC), the Food and Agriculture Organization (FAO), and the United Nations (UN). Cross references (snowball sampling) and other documents suggested by co-authors were assessed if relevant. This approach may introduce potential biases, as it tends to exclude less cited and more recent works with clear relevance. However, all co-authors have good exposure to recent publications and were able to suggest useful sources that mitigate this bias. We then synthesized the literature using a narrative approach (Booth et al., 2016) which characterises studies in terms of multiple groupings to explore heterogeneity descriptively, rather than statistically. The synthesis phase consisted of extracting and categorizing the projected pressure data from selected papers based on: spatial resolution; temporal range; type of analysis (e.g., quantitative/mapped, qualitative/unmapped, qualitative, or mixed); if available, the specific scenarios used for future projections (i.e., Representative Concentration Pathway (RCP), Shared Socioeconomic Pathway (SSP)); and description of the general trend of each pressure (e.g., upward, downward or static trajectory). The terminology is described in Table 1.


National Science Foundation, Award: Federal Award Number FAIN:2019902 and Subaward number NSF: KK2153