Remote seamounts are key conservation priorities for pelagic wildlife
Bibliographic record
Abstract
The pelagic ocean is Earth's largest habitat, constituting 99% of the global biosphere by volume, directly or indirectly supporting most marine life, and supplying the majority of fish consumed by humans (Game et al., 2009; Pauly et al., 2002). However, the world's pelagic fauna is globally declining largely as a result of unsustainable fishing (Pauly & Zeller, 2016). Industrial fishing has reduced the populations of tunas and their relatives by 60% and of oceanic sharks and rays by 71% over the past half century (Juan-Jordá et al., 2011; Pacoureau et al., 2021). Declines in pelagic wildlife weaken ecosystem functioning, drive biodiversity loss, and undermine food security and economic stability for many of the world's people. Remote regions of the ocean that remain less impacted by humans are refuges for mobile and heavily targeted species. These regions harbor wildlife assemblages with higher diversity, greater abundance, larger size, and increased biomass, and can yield valuable insights into ecological processes (Campbell et al., 2020; Juhel et al., 2019; Thompson & Meeuwig, 2022). Remote regions offer a glimpse of what the ocean was like prior to large-scale anthropogenic impact, a source from which the rest of the ocean can be regenerated, and a benchmark for marine protected areas (MPAs) and fisheries management. However, with human impacts now extending across the global ocean (Halpern et al., 2008; Tickler et al., 2018), remote areas are increasingly threatened. Urgent attention is required to ensure that remote regions avoid mirroring the degradation seen in areas more proximate to humans. Our knowledge of the pelagic ocean remains limited relative to shallow coastal habitats, making prioritizing conservation efforts difficult. This is especially the case in remote regions where scientific information is even more scarce. We do know, however, that pelagic species associate strongly with bathymetric features such as seamounts, undersea canyons, and oceanic islands (Bouchet, 2015; Morato et al., 2010; Thompson et al., 2021). Both physical and biological drivers make these features important locations for foraging, reproduction, navigation, and other essential functions of pelagic wildlife (Garrigue et al., 2015; Maguire et al., 2023; Rogers, 2018). Seamounts are particularly important to large pelagic animals and often hold relatively high densities of threatened and commercially important species such as sharks, tunas, and billfishes, some of which are generally highly mobile but show high residency at these features (Morato et al., 2008; Wright et al., 2021). However, the high economic value and conservative life histories of these species mean fishing can quickly decimate seamount communities. As such, seamount communities proximate to humans often become degraded first (Clark, 1999). There are an estimated 37,889 seamounts in the global ocean, yet less than 4% have been surveyed (Yesson et al., 2021; Figure 1). Moreover, less than 6% are located in fully and highly protected MPAs (mpatlas.org; Grorud-Colvert et al., 2021). The protection of seamounts thus represents a significant conservation opportunity. Importantly, different bathymetric structures support distinct assemblages (Thompson et al., 2021) and thus a range of remote structures should be included to ensure representative protection. The protection of subsurface features will benefit pelagic biodiversity, as well as providing significant benefits in the conservation of important demersal fish assemblages (Galbraith et al., 2021) and many vulnerable benthic marine ecosystems such as deep reef communities given their higher concentration at these features (Rogers, 2018). Many seamounts, including those proximate to human populations, have significant biodiversity conservation value (Morato et al., 2010). However, we argue that remote seamounts where degradation has been limited to date are priorities for protection given the high abundance of targeted species present and the disproportionate contribution that such places make to biodiversity and our understanding of how human impact is transforming our oceans. Well-designed and well-managed highly protected MPAs demonstrably halt and reverse declines in ocean wildlife, increase fisheries yields in adjacent waters, and enhance resilience to climate change (Edgar et al., 2014; Roberts et al., 2017; Sala & Giakoumi, 2018). The combination of remoteness and large-scale protection is particularly effective in biodiversity conservation (Juhel et al., 2018) and large fully and highly protected MPAs contribute significantly to seamount protection within EEZs. There is ample scientific evidence of the need to protect at least 30% of land and sea by 2030 (Dinerstein et al., 2019; O'Leary et al., 2016), a commitment now made in the Kunming–Montreal Global Biodiversity Framework, ratified in December 2022. The United Nations General Assembly has also recently established a treaty to facilitate conservation and sustainable use of marine biodiversity in areas beyond national jurisdiction (ABNJs; Stokstad, 2023; United Nations General Assembly, 2023). This instrument provides a legal framework for the implementation of MPAs in ABNJs. With 58% of seamounts located in ABNJs, and less than 1% of these in highly protected MPAs, remote seamounts are a prime target to deliver on biodiversity conservation commitments. Moreover, recent multinational treaties have recognized the importance of these features and are collaborating to protect areas both across national and international waters. For example, the Eastern Tropical Pacific Marine Corridor (CMAR) initiative extends across islands, coasts, and seamount chains in the Exclusive Economic Zones (EEZs) of Costa Rica, Panamá, Colombia, and Ecuador. Perú and Chile are also working together to protect the Nazca and Salas y Gómez Ridge system, which stretches across their EEZs and the international waters between them (Wagner et al., 2021). These progressive steps provide a clear and positive example of how collaboration among countries is possible and can protect valuable marine habitats. Increasing threats and growing recognition of the importance of the natural world have strengthened and necessitated the demand for protection of natural environments globally. The high density of life and residency of, generally highly mobile, pelagic fauna at remote seamounts make these locations prone to anthropogenic destruction but also ideal targets for conservation (Morato et al., 2010; Wright et al., 2021). Given the body of evidence on the importance of remote seamounts, their protection is a critical step in sustaining pelagic wildlife populations and will benefit the many species that utilize them, including ourselves. Data sharing not applicable—no new data generated. N/A
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".