MétaCan
Menu
Back to cohort

Forestcheck: terrestrial vertebrate associations with fox control and silviculture in jarrah (<i>Eucalyptus marginata</i>) forest

2011· article· en· W1972490102 on OpenAlexaff
Adrian F. Wayne, Graeme Liddelow, Matthew R. Williams

Bibliographic record

VenueAustralian Forestry · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsDepartment of Environment and Conservation
FundersConservation Leadership Programme
KeywordsBiologyEcologySpecies richnessSilviculture

Abstract

fetched live from OpenAlex

Summary Terrestrial vertebrate associations with silviculture and other factors were investigated as part of the FORESTCHECK monitoring program in the jarrah (Eucalytpus marginata) forests of south-west Western Australia. A total of 48 integrated monitoring grids form the basis of this study—sampled over five years (2001–2006), across five ecosystem-defined regions (one sampled per year), each with replicates of two silvicultural treatments (shelterwood, gap release) and external reference forest (uncut forest or structurally mature forest that had not been harvested for timber for over 40 y). Terrestrial vertebrates were surveyed in spring and autumn using pitfall traps and wire cages. Forty-one terrestrial vertebrate taxa (8 frogs, 22 reptiles, 11 mammals) comprising 1165 captures were recorded. Fox (Vulpes vulpes) control had the strongest effect on terrestrial vertebrates, with baited areas supporting significantly more individuals (three-fold increase) than unbaited areas. The mammals Trichosurus vulpecula, Bettongia penicillata, Cercartetus concinnus and Dasyurus geoffroii, and the skink Tiliqua rugosa were particularly more abundant in fox-baited forest. Several terrestrial vertebrate community attributes (species accumulations by grids and number of individuals, dominance-diversity plots, overall community structure and overall abundance) differed little among the three treatments (i.e. two silvicultural, plus external reference forest). However, external reference grids had significantly lower species richness than the shelterwood grids and a significantly different community structure. These differences resulted from a greater prevalence within shelterwood of some species such as the reptiles Egernia napoleonis, Menetia greyii, Ctenotus labillardieri and Ramphotyphlops australis. Forests that had never been harvested, a subset (8/15 grids) of the external reference treatment, had the lowest overall abundance, due largely to a confounding with fox control. The level of replication enabled differences between treatments of greater than 23% in species richness, and 37% in overall abundance, to be detected as statistically significant. Significant ecosystem/year differences were found. Differences in community structure between ecosystems/years approximated the geographic/bioclimatic relationships between the grids, with the distinction between southern jarrah communities (Jarrah South/2001–02 and Jarrah Blackwood Plateau/2005–06) and the northern communities being particularly apparent. Time since last fire, live tree basal area, and the proportion of basal area removed by harvesting and silvicultural treatment were not correlated with vertebrate species richness, abundance or community structure. In comparison to the effect of fox control and regional/temporal variation, silvicultural treatment and the intensity of timber harvesting had minor impacts. Suggestions for the improvement of this and similar studies are discussed, with a particular focus on reducing residual variance and increasing sample size.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.038
Threshold uncertainty score0.076

Distilled classifier scores by category (both heads)

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 head0.016
GPT teacher head0.207
Teacher spread0.191 · 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

Citations19
Published2011
Admission routes1
Has abstractyes

Explore more

Same venueAustralian ForestrySame topicWildlife Ecology and ConservationFrench-language works237,207