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Record W2503994443 · doi:10.3390/f7080172

Baseline Mortality Analysis Reveals Legacy of Contrasting Land Use Practices on the Structural Sustainability of Endangered Moroccan and Spanish Mountain Forests

2016· article· en· W2503994443 on OpenAlexaff
John D. Castello, Jonathan A. Cale, Cortney D’Angelo, Juan Carlos Linares

Bibliographic record

VenueForests · 2016
Typearticle
Languageen
FieldEnvironmental Science
TopicForest Insect Ecology and Management
Canadian institutionsUniversity of Alberta
FundersAgencia Española de Cooperación Internacional para el Desarrollo
KeywordsSustainabilityDisturbance (geology)GeographySustainable forest managementEndangered speciesBaseline (sea)Sustainable managementEcologyAgroforestryForest managementEnvironmental resource managementForestryBiologyEnvironmental scienceHabitatFishery

Abstract

fetched live from OpenAlex

Disturbances can affect forest health and are important modulating factors of tree responses to environmental changes. However, standard methods are needed to assess and elucidate the relative effects of disturbance legacies on forest health among species. Here, structural sustainability was used to evaluate and to compare the impacts of contrasting disturbances on the health of Quercus ilex, Cedrus atlantica, and Abies pinsapo forest stands in Morocco and Spain. Disturbance effects on structural sustainability were related to type, severity, and land-use history, and showed inter-regional variability. Cedrus atlantica was structurally sustainable in its core distribution in Morocco, but not at its southern and northernmost geographical range limits. Quercus ilex was structurally sustainable in Morocco. Abies pinsapo was structurally sustainable at optimal elevation sites in Morocco (Rif Mts.), but considering the whole A. pinsapo dataset including Morocco and Spain, the species is structurally unsustainable due to excessive mortality. However, at the lower elevation plots in Spain, unsustainability was due to insufficient mortality. Although some forests were structurally sustainable, none of them were deemed healthy because none met their management objectives. Results also support the key role of disturbance regimes as drivers of forest structural sustainability and adaptive capacity.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.092
Threshold uncertainty score0.919

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
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 head0.021
GPT teacher head0.284
Teacher spread0.263 · 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

Citations4
Published2016
Admission routes1
Has abstractyes

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