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Record W4404318871 · doi:10.5751/es-15513-290419

Assessing the delivery of ecosystem services and benefits to human well-being of three contrasting MPAs in Spain

2024· article· en· W4404318871 on OpenAlexvenueno aff
Pablo Pita, Antonio Arjona Castro, Jose De Santiago-Meijide, Mónica Expósito‐Granados, Antonio Garcı́a-Allut, Gonzalo Méndez Martínez, Jone Molina-Urruela, Ana Tubío, Sebastián Villasante

Bibliographic record

VenueEcology and Society · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicLand Use and Ecosystem Services
Canadian institutionsnot available
FundersXunta de GaliciaMinisterio de Ciencia, Innovación y Universidades
KeywordsMarine protected areaEcosystem servicesEnvironmental resource managementEcosystemGeographyBusinessEnvironmental planningEcologyEnvironmental scienceBiologyHabitat

Abstract

fetched live from OpenAlex

Marine and coastal ecosystems are indispensable for life on Earth, providing vital functions and serving as a significant source of prosperity for humanity. These ecosystems contribute to the generation of Marine Ecosystem Services (MES), encompassing the benefits derived from marine environments, which are pivotal for economic prosperity and societal well-being. Nonetheless, these valuable ecosystems are facing severe degradation due to various human-induced pressures. In response to this challenge, Marine Protected Areas (MPAs) have emerged as crucial tools advocated by numerous international policies to counteract the adverse impacts of human activities on marine ecosystems. Despite the diverse array of MPAs characterized by varying levels of protection, there remains a dearth of understanding regarding their disparities in providing all forms of MES and their implications for human well-being. Through a comprehensive analysis involving scientific literature, gray literature, and press news, this research scrutinizes the role of MPAs in generating benefits and addressing conflicts arising from MES provision. The main disciplines involved, text orientation, methodologies, and key results of the publications were assessed. Moreover, benefits to people, conflicts between stakeholders, and emotions and sentiments related to MES supply in three selected Spanish MPAs (the Atlantic Islands of Galicia Maritime-Terrestrial National Park, the Os Miñarzos Marine Reserve of Fishing Interest, and the Cabo de Gata-Níjar Natural Park) were identified and analyzed. This allowed for comparisons with their respective levels of protection. The findings reveal that conservation efforts within MPAs contribute significantly to scientific knowledge generation while concurrently supporting human well-being through food security, economic growth, and employment opportunities, particularly in the tourism and fisheries sectors. However, these sectors also engender conflicts concerning conservation policies and resource utilization. The study underscores that the level of protection is a crucial feature, alongside the governance structure and proximity to population centers and tourism hotspots, in determining the delivery of MES by MPAs and their influence on human welfare. The adoption of co-management strategies and the promotion of ecotourism initiatives within MPAs emerge as viable approaches to mitigate conflicts and optimize the provision of high-quality MES, thereby enhancing human well-being. The insights gleaned from this research offer valuable guidance for scientists, managers, and policymakers in fostering the conservation of marine biodiversity through the strategic management and design of MPA networks geared towards maximizing the distribution of benefits for human well-being.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.004
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.011
GPT teacher head0.233
Teacher spread0.222 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations7
Published2024
Admission routes1
Has abstractyes

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