Spatial ecology and variables influencing habitat use and fitness proxies of Eastern hog-nosed snakes (Heterodon Platirhinos) within an anthropogenic landscape
Bibliographic record
Abstract
Changes in environmental conditions and threats from human activities present unique challenges to persistence and management of wildlife populations at range peripheries. For successful recovery and conservation of reptile species at risk (SAR), basic knowledge of their life histories and ecologies must be understood. Such basic information was lacking for a recently reported population of eastern hog-nosed snakes (Heterodon platirhinos) in southwestern Ontario. To successfully meet government-mandated recovery actions for the population of Threatened snakes, I investigated whether hog-nosed snakes’ space use, habitat preferences, and proxies of fitness were impacted by widespread anthropogenic activity in Huron County, Ontario. I estimated movement and home range size (mean ± SD) from locations of hognosed snakes (n = 10) outfitted with radio transmitters from the 2018 to 2020 active seasons, and then calculated using kernel density estimates (KDE) and minimum convex polygons (MCP). I evaluated habitat selection at three scales (i.e., exact, local, and landscape) using resource selection function models and ranked models using Akaike’s Information Criterion corrected for small sample sizes. Proxies of fitness I assessed included quantification of thermal habitat from hourly ground temperatures and snake body condition estimated from residuals of body mass on snout-vent length regressions. I found that when compared to conspecific populations throughout their range, Huron County snakes moved greater distances (49 ± 13 m per day, 127 ± 41 m per move) within larger-sized home ranges (64 ± 30 ha), as well as were heavier and in better body condition compared to conspecific populations near Point Pelee, Ontario. At the coarsest scale, I found that occurrence of snakes in Huron County was positively associated with forest, beach, and old field habitats, while at finer scales, habitat characteristics with structural complexity, cover, and thermal suitability influenced snake occurrence. While proxies of snake fitness did not appear imminently impacted by human activity in Huron County, widespread disturbance did influence how hog-nosed snakes used the landscape: snakes moved greater distances (than those in conspecific populations) to use pockets of natural habitats that were thermally suitable and structurally complex. To ensure effective management of the population stewardship efforts should focus on protection and enhancement of snake habitat and have such actions follow recommendations from this study. My study exemplifies the complex nature of SAR management in Ontario and how understanding space use, habitat selection, and fitness proxies are important to successfully conserving and recovering a snake species at risk.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".