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The land-blending strategy: Contribution of metapopulation theory to the land sparing-sharing debate

2025· article· en· W4410028596 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueLand Use Policy · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural Economics and Policy
Canadian institutionsUniversité de Sherbrooke
FundersUniversité de Sherbrooke
KeywordsMetapopulationLand useGeographyEnvironmental resource managementEconomic geographyEnvironmental planningEconomicsSociologyEngineeringCivil engineeringDemography

Abstract

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Two land management strategies have been proposed to preserve biodiversity while maintaining sufficient agricultural production: land sparing and land sharing. Debate on their efficiency continues, although a third hybrid strategy has emerged. The balance between these strategies is context-dependent, limiting generalizations. We addressed this challenge using a metapopulation-based model to simulate species persistence in agricultural landscapes under different management strategies. Our model captures the influence of contextual factors, such as landscape composition, connectivity, and pest incidence, allowing us to evaluate how landscape management strategies influence biodiversity and ecosystem services such as pest regulation. Our results highlight key factors for designing effective landscape management strategies. First, maintaining intermediate quality habitats (e.g., agroforests) within the landscape is essential to support pest controllers and thus, the provision of ecosystem services. Second, although agroforestry expansion can reduce economic returns compared to conventional agriculture, biodiversity offsets these costs when pest pressure is high and biological control is effective. These findings emphasize the importance of an integrated approach to implement effective landscape management strategies, optimizing both productivity and biodiversity conservation. This study reveals the potential of a hybrid ‘land blending’ strategy, able to outperform traditional land sparing-sharing approaches, while offering greater flexibility for change and uncertainty. To our knowledge, this study represents the first theoretical modelling approach to assess the effectiveness of conservation strategies without considering specific contextual influences. Our findings enhance our understanding of the impact of context on optimal strategies, enriching the debate and suggesting new perspectives beyond its false dichotomy. • Even small amounts of semi-natural systems in the landscape maintain pest control services. • Biodiversity in landscapes provides indirect pest control benefits to intensive agriculture. • Biodiversity offsets semi-natural system costs through provision of pest-control services. • Mixing land sparing and sharing can outperform basic strategies, depending on landscape context. • Agricultural output and biodiversity can be optimized dispelling the debate dichotomy.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.266
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.030
GPT teacher head0.269
Teacher spread0.239 · 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