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Record W6948246967 · doi:10.5061/dryad.31zcrjdhr

Plant Biomass data from: Bottom-up Herbivore-Plant Feedbacks Trump Trophic Cascades in a Wolf-Elk-Grassland System

2020· dataset· en· W6948246967 on OpenAlexaffabout

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2020
Typedataset
Languageen
FieldChemistry
TopicWood and Agarwood Research
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsTrophic levelBiomass (ecology)GrasslandTrophic cascadeGrazingEcosystemFood webApex predator

Abstract

fetched live from OpenAlex

Top-down predator-prey effects that alter the abundance, biomass, or productivity of a population community across more than one link in a food web are referred to as trophic cascades. While these effects have been extensively studied in aquatic environments, fewer studies have examined trophic cascades in terrestrial ecosystems. And fewer still terrestrial studies have tested for trophic cascades between vertebrates and grassland vegetation. Across the globe, grassland plant biomass is driven by both precipitation and non-linear positive feedbacks between grazing and plant productivity, as predicted by the Intermediate Grazing Hypothesis. Yet little is known about the role that apex carnivores play in regard to trophic impacts on grassland biomass. We utilized a long-term dataset collected over the last two decades on a montane rough-fescue grassland adjacent to Banff National Park, Alberta, to test whether top-down effects regulate grassland biomass in a wolf-elk system. First, we measured annual growing season plant biomass from 2006 – 2018 at 61 repeat sampled plots in the grassland. Next, we measured wolf predation risk using a previously developed wolf resource selection function created from GPS radiocollar data from 5 wolf packs. Finally, we measured grazing intensity using Brownian Bridge Movement Models derived from GPS radiocollar data from 131 unique elk. We then tested top-down, bottom-up and abiotic hypotheses for grassland biomass over time in program R. The top model incorporated precipitation and positive non-linear effects of elk use, excluding predator effects and thus failing to support the trophic cascade hypothesis. This may be due to the observational nature of this study, or predation effects in this system may be obscured by human use. Alternatively, our results also support the hypothesis that intermediate grazing may outweigh the benefits of predation in grassland systems. Our study serves to help fill a gap in trophic cascade literature, and emphasizes that positive feedback between grazers and grasslands may trump top-down effects. Understanding when trophic cascade theory is or is not applicable is vital for carnivore management, conservation, and reintroduction efforts across North America.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Open science, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.017
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0020.000
Open science0.0060.006
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0130.022

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 head0.054
GPT teacher head0.256
Teacher spread0.202 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreDataset

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
Published2020
Admission routes2
Has abstractyes

Explore more

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