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Record W3081687764

Elk-agriculture conflicts in the Greater Riding Mountain Ecosystem : building bridges between the natural and social sciences to promote sustainability

2008· dissertation· en· W3081687764 on OpenAlexaboutno aff
Ryan K. Brook

Bibliographic record

VenueMspace (University of Manitoba) · 2008
Typedissertation
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsnot available
Fundersnot available
KeywordsSustainabilityNatural (archaeology)AgricultureEcosystemBusinessNatural resource economicsEnvironmental resource managementEnvironmental planningEnvironmental scienceGeographyEcologyEconomicsBiology
DOInot available

Abstract

fetched live from OpenAlex

Successful mitigation of human-wildlife conflicts requires an approach that incorporates both the ecological aspects of wildlife and the social considerations of the affected stakeholders and these must be considered in an integrated fashion at multiple temporal and spatial scales. In this dissertation, I examine the relationship between farmers around Riding Mountain National Park (RMNP) in southwestern Manitoba and the regional elk (Cervus elaphus) population, in order to better understand and resolve these long-standing conflicts more effectively. Local perspectives were documented throughout this study, initially through 40 community meetings in 2000 and 2001 prior to formal data collection, then through a mail-out survey in 2002, and later through participatory mapping exercises from 2003 to 2006. A longitudinal analysis of historical information regarding elk-agriculture conflicts using the interviews and government letter files indicated that diverse types of conflicts have occurred annually for the last 127 years. Issues related to bovine tuberculosis (TB) in elk in the last 15 years have been some of the most intense conflicts ever occurring, but these are based on previous conflicts and they have further undermined the already strained relationship between farmers and RMNP. The most important factor associated with high concern regarding bovine TB was the frequency that farmers observed elk on their land. To examine the biophysical aspects of elk interactions with agriculture, 212 wild elk were captured from 2002-2005 using a net-gun fired from a helicopter and given a GPS satellite collar (n=25) of VHF transmitter (n=187). Overlap in space use between elk and cattle was high in summer and low in winter based on both the collar data and local knowledge, though farmers identified higher levels of overlap throughout the year. During the spring elk calving period, the home ranges of 73% of the parturient elk remained entirely within protected areas, while 6% were exclusively on farmland, and 21% included both. The proportion of the elk population calving on farmland continues to increase from near zero in the 1970s. Hay yard barrier fences are the most effective and widely accepted management tool in use to mitigate elk-agriculture conflict, but modifications to the process of allocating and monitoring fences are needed. Indeed, all aspects of the management of elk-agriculture interactions require greater levels of communication and collaboration between government agencies and local stakeholders. I also advocate taking an adaptive, science-based approach to managing human-wildlife conflicts that focuses on both the social and natural sciences as mutally contributing to our understanding of the problems and generating meaningful solutions. This is one of few studies that makes use of local knowledge and conventional ecological data together, and demonstrates the contributions of both in better understanding the temporospatial aspects of wildlife-human conflicts and their socioeconomic and conservation implications.

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)0.003
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.976
Threshold uncertainty score0.048

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0070.006
Scholarly communication0.0090.005
Open science0.0010.007
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.031
GPT teacher head0.305
Teacher spread0.275 · 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 designQualitative
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

Citations24
Published2008
Admission routes1
Has abstractyes

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