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Record W1987263018 · doi:10.1111/avsc.12143

Climatic characterization of forest zones across administrative boundaries improves conservation planning

2014· article· en· W1987263018 on OpenAlexaffabout
Heather Klassen, Philip J. Burton

Bibliographic record

VenueApplied Vegetation Science · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicSpecies Distribution and Climate Change
Canadian institutionsUniversity of Northern British ColumbiaMinistry of Forests
FundersU.S. Forest Service
KeywordsBaseline (sea)GeographyClimate changeEcosystemVegetation (pathology)Forest ecologyEcosystem servicesPhysical geographyEcologyEnvironmental scienceGeologyOceanography

Abstract

fetched live from OpenAlex

Abstract Aim This paper demonstrates methods to extend standardized vegetation zone descriptions and mapped distributions across political boundaries. An extended climate niche for North America's Coastal Douglas‐fir ( CDF ) forest zone is determined and projected to evaluate its potential distribution under a changing climate and to identify climate refugia for conservation planning. Location Pacific Northwest temperate rain forest in British Columbia ( BC ), CA , and nearby Washington ( WA ) and Oregon ( OR ), US . Methods Using a combination of ecosystem polygon mapping and ecological plot data with climate interpolation tools, forests characterized as CDF under BC 's biogeoclimatic ecosystem classification system were identified in the neighbouring US . Current (baseline) limits to CDF distribution were identified and used to map its potential distribution and climate refugia under future climate conditions using ensemble Global Climate Model projections. Results The extended CDF climate niche covers 76 725 km 2 under baseline conditions, with the majority of the area in the Pacific Northwest US . The extended CDF forest zone includes a vegetation assemblage consistent with existing definitions of BC 's CDF moist maritime subzone, but also an additional vegetation assemblage representing a drier maritime subzone. Projections of future climate suggest a northerly shift (~150 km) and a decrease (−91.5%) in overall CDF area. Climate refugia are projected for discontinuous patches of CDF forest on Vancouver Island and adjacent mainland. Conclusions This project combined georeferenced ecological plot data and digital maps, thereby facilitating the international mapping of ecosystem distributions in adjacent administrative areas that do not currently use the same ecosystem classification and mapping systems. This approach and the concept of climate niche definition, distribution and persistence are applicable to the management, restoration and conservation of plant communities, particularly in evaluating future ecosystem range shifts and disruptions associated with a changing climate. The potential for dramatic reductions in the range of the Coastal Douglas‐fir zone, with persistence in <15% of its current area, suggest that most of the extended CDF zone is marginally suitable for the characteristic CDF ecosystems and that slight shifts in climate or disturbance regime may greatly alter the character of the vegetation. The full climatic niche for British Columbia's Coastal Douglas‐fir forest zone is determined from its mapped distribution and georeferenced plot data in the neighbouring USA . A new subzone is characterized, and the potential distribution of the extended zone is projected under a changing climate to identify climate refugia. For sensitive ecosystems with multi‐jurisdictional distributions, this approach helps focus conservation efforts.

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)0.002
metaresearch head score (Gemma)0.007
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 score0.018
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0010.000
Scholarly communication0.0020.002
Open science0.0000.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.001

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 head0.035
GPT teacher head0.304
Teacher spread0.269 · 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

Citations7
Published2014
Admission routes2
Has abstractyes

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