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Record W7035881327

Assessing climate change induced declines in ponds in British Columbia's semi-arid grasslands

2015· article· en· W7035881327 on OpenAlexaboutno aff

Bibliographic record

VenueArca (British Columbia Electronic Library Network) · 2015
Typearticle
Languageen
FieldComputer Science
TopicMathematics, Computing, and Information Processing
Canadian institutionsnot available
Fundersnot available
KeywordsSnowmeltEvapotranspirationPrecipitationWetlandClimate changeHydrology (agriculture)GrasslandSnow
DOInot available

Abstract

fetched live from OpenAlex

In British Columbia (BC), the ranching community has expressed a concern with observed declines in the number and surface area of grassland ponds used as drinking water sources for cattle during grazing. This study evaluates the extent of the observed declines in BC’s southern interior grasslands and determines the differences in groundwater – surface water (GW-SW) interactions between perennially and seasonally inundated ponds in the Lac du Bois grasslands. Using remote sensing techniques to compare historic and modern imagery, ponds from eight 100 km2 sites were evaluated. From 1992 – 2012, the total number and surface water area of ponds decreased by 63% and 54%, respectively within the eight sites. Due to the effects of climate change on wetlands worldwide it is expected that changes in climate are responsible for these declines. A climate data analysis of ClimateWNA modelled data for the eight sites showed a significant increase in air temperature and potential evapotranspiration (PET) from 1900 – 2012 implying an increased evaporative demand on surface water. Precipitation also increased significantly over this time period. However, low snowfall is reported for the 1992 – 2012 time period showing that there have been decreased snowmelt inputs available for GW - SW recharge. The field study in Lac du Bois highlighted the importance of GW - SW interactions in maintaining pond surface water. Wells and piezometers were installed in and around two perennially inundated ponds and two seasonally inundated ponds. It was determined that the perennially inundated ponds receive a persistent input from the local groundwater system allowing them to sustain surface water despite high evapotranspiration rates in the summer months. Conversely, groundwater inputs to seasonally inundated ponds are either temporary or non-existent and therefore they are highly dependent on the amount of input from the spring melt and are more vulnerable to summertime evapotranspiration. Our results are consistent with other studies that show that climate change has contributed to significant losses in wetlands worldwide.

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)0.001
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 score0.050
Threshold uncertainty score0.101

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
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 head0.026
GPT teacher head0.240
Teacher spread0.214 · 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

Citations0
Published2015
Admission routes1
Has abstractyes

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