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Record W2002051910 · doi:10.3390/d5020352

Biodiversity Indicators Show Climate Change Will Alter Vegetation in Parks and Protected Areas

2013· article· en· W2002051910 on OpenAlex

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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueDiversity · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicSpecies Distribution and Climate Change
Canadian institutionsNatural Resources CanadaCanadian Forest ServiceUniversity of British ColumbiaUniversity of Victoria
FundersCanadian Space AgencyU.S. Forest ServiceCanadian Forest ServiceUniversity of British ColumbiaBritish Columbia Innovation Council
KeywordsBiodiversityClimate changeVegetation (pathology)Environmental scienceGeographyEcosystemProductivityEnvironmental resource managementRange (aeronautics)EcologyBiology

Abstract

fetched live from OpenAlex

While multifaceted, a chief aim when designating parks and protected areas is to support the preservation of biological diversity, in part, through representing and conserving the full range of landscape conditions observed throughout a representative area. Parks and protected areas are, however, typically developed using a static interpretation of current biodiversity and landscape conditions. The observed and potential climate change impacts to biodiversity have created a need to also contemplate how parks and protected areas will respond to climate change and how these areas will represent the future range of landscape conditions. To assess change in biodiversity, broad-scale ecosystem information can be sourced from indirect remotely sensed indicators. Quantifying biodiversity through indirect indicators allows characterization of inter-relationships between climate and biodiversity. Such characterizations support the assessment of possible implications of climatic change, as the indicators can be generated using modeled forecasts of future climatic conditions. In this paper we model and map impacts of climate change on British Columbia’s parks and protected areas by quantifying change in a number of remotely sensed indicators of biodiversity. These indicators are based on the measured amount of incoming solar energy used by vegetation and map the overall annual energy utilization, variability (seasonality), and latent or baseline energy. We compare current conditions represented by parks and protected areas, to those forecasted in the year 2065. Our results indicate that parks and protected areas are forecasted to become more productive and less seasonal, due to increased vegetation productivity in higher elevation environments. While increased vegetation productivity may be beneficial for biodiversity overall, these changes will be particularly problematic for sensitive and specialist species. Future gaps in vegetation conditions protected by parks and protected areas are observed in the eastern edge of the Rocky Mountains and the central interior region of British Columbia. Protected areas along the Coast Mountains, Vancouver Island highlands, and the Rocky Mountains show the greatest levels of change in the biodiversity indicators, including decreasing seasonality, with the Mountain Hemlock ecozone most at risk. Examples of large parks that are predicted to experience rapid change in vegetation characteristics include Strathcona, Garabaldi, and Kitlope. Our maps of future spatial distributions of indirect biodiversity indicators fill a gap in information products available for adaptive parks management and provide an opportunity for dialogue and further research on the use of future scenarios of landscape conditions in conservation planning.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score1.000

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 communication0.0000.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0120.001

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 head0.022
GPT teacher head0.205
Teacher spread0.183 · 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