Pronghorn resource selection and habitat fragmentation in North Dakota
Bibliographic record
Abstract
ABSTRACT Pronghorn ( Antilocapra americana ) in North Dakota have experienced habitat fragmentation due to agricultural practices, roads, and oil development. We analyzed patterns of female pronghorn habitat selection in 2006 and 2014, years with contrasting pronghorn density and oil production in western North Dakota. We quantified resource selection and fawn:female ratios relative to proximity to active wells, road density, land cover, development, normalized difference vegetation index (NDVI), and agricultural practices. We also assessed patterns of well placement relative to the same environmental variables. Pronghorn selected sagebrush and areas with low NDVI but avoided developed areas, roads, forests, and wetlands. Pronghorn selected areas close to oil and gas wells because wells were located in high‐value habitats (e.g., native sagebrush‐steppe ecosystems selected by pronghorn). For the majority of variables tested, selection was stronger when pronghorn density was low, consistent with current resource selection theory. Although females selected relatively open habitats, fawn:female ratios within areas selected by females were positively correlated with NDVI. Our results demonstrate that pronghorn avoid human development and roads but not oil and gas wells. Although wells are not actively avoided by pronghorn, their placement in high‐value habitat for this species leads to significant habitat fragmentation. In light of these results, we recommend efforts to conserve pronghorn habitat such as constructing wells away from sagebrush, using existing roads to service newly constructed wells, and re‐vegetating well pads with sagebrush plantings once they are no longer in use. © 2016 The Wildlife Society.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".