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Record W2276438573 · doi:10.2172/947113

Habitat Evaluation Procedure (HEP) Report for the Pend Oreille Wetlands Wildlife II Project, Technical Report 2002.

2003· report· en· W2276438573 on OpenAlexaboutno aff
Darren Holmes

Bibliographic record

Venuenot available
Typereport
Languageen
FieldEnvironmental Science
TopicRangeland and Wildlife Management
Canadian institutionsnot available
Fundersnot available
KeywordsWildlifeHabitatGeographyWetlandHydroelectricityDrainage basinFisheryCritical habitatEcologyEndangered speciesCartographyBiology

Abstract

fetched live from OpenAlex

The Habitat Evaluation Procedure (HEP), developed in 1980 by the U.S. Fish and Wildlife Service (USFWS 1980a, USFWS 1980b), uses a habitat/species based approach to assessing project impacts, and is a convenient tool to document the predicted effects of proposed management actions. The Northwest Power Planning Council (NPPC) endorsed the use of HEP in its Columbia River Basin Fish and Wildlife Program to evaluate wildlife benefits and impacts associated with the development and operation of the federal Columbia River Basin hydroelectric system (NPPC 1994). The Albeni Falls Interagency Work Group (AFIWG) used HEP in 1987 to evaluate wildlife habitat losses attributed to the Albeni Falls hydroelectric facility (Martin et al. 1988). In 1992, the AFIWG (Idaho Department of Fish and Game; Kalispel, Coeur d'Alene, and Kootenai Tribes) began implementing activities to mitigate these losses. Implementation activities include protecting, restoring and enhancing wildlife habitat. HEPs are used extensively within the NPPC's Columbia River Basin Fish and Wildlife Program. Wildlife managers use HEP to determine habitat lost from the construction of the federal hydroelectric projects and habitat gained through NPPC mitigation program. Habitat Suitability Index (HSI) models for each of the seven target species are used to determine habitat quality and quantity losses for representative habitat cover types for this project. Target species include Bald Eagle, black-capped chickadee, Canada goose, mallard, muskrat, white-tailed deer and yellow warbler. In 2002, a HEP team determined the habitat condition of the 164-acre Pend Oreille Wetlands Wildlife II Project (Figure 1). The HEP team consisted of the following members and agencies: Roy Finley, Kalispel Natural Resource Department (KNRD); Neil Lockwood, KNRD; Brian Merson, KNRD; Sonny Finley, KNRD; Darren Holmes, KNRD; Anna, Washington Dept. of Fish and Game (WDFW); and Scott, WDFW. Baseline Habitat Units (HU) will be credited to Bonneville Power Administration (BPA) for protection of habitats within the project area. The HSI models used were identical to those modified for use in 1991 (Appendix 2). The objective of using HEP as an assessment tool is two-fold. First, it provides an unbiased and measured assessment of wildlife habitats within the mitigation parcel. This data is used to offset the Albeni Falls Dam HU loss ledger. That ledger accounts for the loss of wildlife habitat that resulted from the construction and inundation of Albeni Falls hydroelectric project and the extent to which those losses have been mitigated. Additionally, the baseline HEP evaluation describes existing habitat conditions on the property and will be used, along with other tools, to determine initial management, restoration, and enhancement activities. HEP analyses will be completed every five years to quantitatively evaluate the effectiveness of management strategies in improving and maintaining habitat conditions while providing additional HU crediting to BPA for enhanced habitat values.

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)0.011
metaresearch head score (Gemma)0.018
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.056
Threshold uncertainty score0.186

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.018
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.004
Science and technology studies0.0010.000
Scholarly communication0.0020.002
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0560.030

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 head0.043
GPT teacher head0.320
Teacher spread0.277 · 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
Published2003
Admission routes1
Has abstractyes

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