MétaCan
Menu
Back to cohort
Record W1768310950 · doi:10.1088/1748-9326/10/9/094014

Strong and nonlinear effects of fragmentation on ecosystem service provision at multiple scales

2015· article· en· W1768310950 on OpenAlex
Matthew G. E. Mitchell, Elena M. Bennett, Andrew Gonzalez

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

VenueEnvironmental Research Letters · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicLand Use and Ecosystem Services
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsEcosystem servicesLand coverFragmentation (computing)Environmental resource managementLand useHabitat fragmentationEcosystemHabitatHabitat destructionNatural (archaeology)Environmental scienceGeographyAgroforestryEcologyBiology

Abstract

fetched live from OpenAlex

Human actions, such as converting natural land cover to agricultural or urban land, result in the loss and fragmentation of natural habitat, with important consequences for the provision of ecosystem services. Such habitat loss is especially important for services that are supplied by fragments of natural land cover and that depend on flows of organisms, matter, or people across the landscape to produce benefits, such as pollination, pest regulation, recreation and cultural services. However, our quantitative knowledge about precisely how different patterns of landscape fragmentation might affect the provision of these types of services is limited. We used a simple, spatially explicit model to evaluate the potential impact of natural land cover loss and fragmentation on the provision of hypothetical ecosystem services. Based on current literature, we assumed that fragments of natural land cover provide ecosystem services to the area surrounding them in a distance-dependent manner such that ecosystem service flow depended on proximity to fragments. We modeled seven different patterns of natural land cover loss across landscapes that varied in the overall level of landscape fragmentation. Our model predicts that natural land cover loss will have strong and unimodal effects on ecosystem service provision, with clear thresholds indicating rapid loss of service provision beyond critical levels of natural land cover loss. It also predicts the presence of a tradeoff between maximizing ecosystem service provision and conserving natural land cover, and a mismatch between ecosystem service provision at landscape versus finer spatial scales. Importantly, the pattern of landscape fragmentation mitigated or intensified these tradeoffs and mismatches. Our model suggests that managing patterns of natural land cover loss and fragmentation could help influence the provision of multiple ecosystem services and manage tradeoffs and synergies between services across different human-dominated landscapes.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.053
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.001

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.

Opus teacher head0.023
GPT teacher head0.270
Teacher spread0.247 · 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