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Connectivity, non‐random extinction and ecosystem function in experimental metacommunities

2010· article· en· W2143027491 on OpenAlexaff
Philip L. Staddon, Zoë Lindo, P. D. Crittenden, Francis Gilbert, Andrew Gonzalez

Bibliographic record

VenueEcology Letters · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicEcology and Vegetation Dynamics Studies
Canadian institutionsMcGill University
Fundersnot available
KeywordsEcosystemEcologyTrophic cascadeBiodiversityExtinction debtTrophic levelExtinction (optical mineralogy)BiologyMetacommunityHabitatApex predatorFunctional ecologyFood webHabitat destructionBiological dispersalPopulation

Abstract

fetched live from OpenAlex

The spatial insurance hypothesis indicates that connectivity is an important attribute of natural ecosystems that sustains both biodiversity and ecosystem function. We tested the hypothesis by measuring the impact of manipulating connectivity in experimental metacommunties of a natural and diverse microecosystem. Isolation led to the extinction of large-bodied apex predators, subsequently followed by increases in prey species abundance. This trophic cascade was associated with significantly altered carbon and nitrogen fluxes in fragmented treatments. The ecosystem impacts were characteristic of a function debt because they persisted for several generations after the initial loss of connectivity. Local extinctions and disruption of ecosystem processes were mitigated, and even reversed, by the presence of corridors in the connected metacommunities, although these beneficial effects were unexpectedly delayed. We hypothesized that corridors maintained grazer movement between fragments, which enhanced microbial activity, and decomposition in comparison to isolated fragments. Our results indicate that knowledge of habitat connectivity and spatial processes is essential to understand the magnitude and timing of ecosystem perturbation in fragmented 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.

How this classification was reachedexpand

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 score0.075
Threshold uncertainty score0.977

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)0.0010.000

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 head0.006
GPT teacher head0.212
Teacher spread0.206 · 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 teacher head, 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

Citations191
Published2010
Admission routes1
Has abstractyes

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