Forest Disturbance and Occupancy Patterns of Carnivores: Results of a Large-scale Field Study in Maine, USA
Bibliographic record
Abstract
Understanding trends in the abundance and distribution of carnivores is important at global, regional and local scales due to their ecological role, their aesthetic and economic value, and the numerous threats to their populations. Carnivores in Maine range from the American black bear (Ursus americanus), to numerous native mesocarnivore species, such as American marten (Martes americana), fisher (Pekania pennanti), coyote (Canis latrans), red fox (Vulpes vulpes), bobcat (Lynx rufus), Canada lynx (Lynx canadensis) and to two small weasel species (Mustela erminea and Neogale frenata). Though smaller than their apex carnivore cousins, Mesocarnivores are essential components of ecosystems and have complex impacts on prey species and intraguild dynamics. However, these species can vary in how they respond to human disturbances, from direct declines due to unregulated harvest and habitat loss, and their ability to adapt to land-use change. Maine is a working landscape which provides habitat for diverse wildlife species coincident with extensive forest harvest industries, as well as tourism and recreation. The intensity, timing, and configuration of harvest activities all interact to modify the landscape, with cascading impacts on the distribution of many animals. Forest management practices have changed through time (Maine Forest Service 2003) with potentially unpredictable outcomes (e.g. Simons 2009). However, the extent to which carnivore species adapt to land use change is a key knowledge gap that needs to be addressed to ensure proper management and conservation going forward. I investigated these patterns by designing a natural experiment across the forested landscape of Maine, and by collecting detection data on multiple species at camera trapping survey stations deployed along a gradient of forest disturbance. My dissertation aims to collect broad-scale, relevant information for carnivore management and conservation, and assess the efficacy of motion-triggered trail cameras for long-term monitoring. My work is divided into four sections, reflected by the four chapters included in the dissertation. My first goal was to determine the optimal number and configuration of camera-trap transects, to balance between reasonable effort expended and high-quality data collection. I used multi-method occupancy analyses to compare between one, two or three camera units spaced either 100 m or 150 m apart. We found that a design with three cameras spaced 100 m apart increased detection probabilities up to five-fold over a single camera trap, and thus used this configuration for the duration of the following research. Once the survey unit was selected, I established a large-scale, multi-year camera trapping regimen across the northern two-thirds of Maine. Survey sites were selected in compliance with a natural experimental design, replicating across all combinations of a) forest disturbance intensity, b) latitude, and c) fur trapping harvest reports for key furbearing species. In the second chapter I present this study design in more detail, and use the resulting data to investigate the interspecies dynamics of marten and fisher, two species of interest to the state of Maine that co-exist in several geographic areas and partition habitat in distinct ways. Both species are sensitive to habitat change resulting from timber harvest, which was a more important factor in occupancy patterns than intraguild dynamics. In chapter three, I took advantage of the large data set I collected to provide a landscape scale understanding of long-tailed and short-tailed weasel distribution patterns in the face of habitat change. Both of these species are poorly studied, and may be in decline in North American. My results indicate that short-tailed weasel are widespread in Maine and do not appear limited by forest harvest practices, while long-tailed weasel are rarer and more apt to be present in southern Maine. Finally in chapter four I ran models incorporating multiple states for species occupancy, beyond mere present or absent, to understand the dynamics of black bears and of black bear reproduction across managed forests in Maine. I found that generally disturbance at a small scale was positively associated with both occupancy and probability of reproduction, while the availability of hardwood trees (an important food source for bears) was also positively linked to the probability of female bears being with cubs. In addition to meeting our stake holder needs for informed management guidelines, I hope that many of my findings will be directly relevant to the broader research community—as camera trapping equipment becomes more affordable, it will become feasible to both monitor and rigorously study wildlife populations in remote locations and under many scenarios of human land-use.
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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 | 0.001 |
| 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".