Using GIS to relate small mammal abundance and landscape structure at multiple spatial extents: the northern flying squirrel in Alberta, Canada
Bibliographic record
Abstract
Summary It is common practice to evaluate the potential effects of management scenarios on animal populations using geographical information systems (GIS) that relate proximate landscape structure or general habitat types to indices of animal abundance. Implicit in this approach is that the animal population responds to landscape features at the spatial grain and extent represented in available digital map inventories. The northern flying squirrel Glaucomys sabrinus is of particular interest in North American forest management because it is known from the Pacific North‐West as a habitat specialist, a keystone species of old‐growth coniferous forest and an important disperser of hypogeous, mycorrhizal fungal spores. Using a GIS approach we tested whether the relative abundance of flying squirrel in northern Alberta, Canada, is related to old forest, conifer forest and relevant landscape features as quantified from management‐based digital forest inventories. We related squirrel abundance, estimated through live trapping, to habitat type (forest composition: conifer, mixed‐wood and deciduous) and landscape structure (stand height, stand age, stand heterogeneity and anthropogenic disturbance) at three spatial extents (50 m, 150 m and 300 m) around each site. Relative abundances of northern flying squirrel populations in northern and western Alberta were similar to those previously reported from other regions of North America. Capture rates were variable among sites, but showed no trends with respect to year or provincial natural region (foothills vs. boreal). Average flying squirrel abundance was similar in all habitats, with increased values within mixed‐wood stands at large spatial extents (300 m) and within deciduous‐dominated stands at smaller spatial extents (50 m). No relationship was found between squirrel abundance and conifer composition or stand age at any spatial extent. None of the landscape variables calculated from GIS forest inventories predicted squirrel abundance at the 50‐m or 150‐m spatial extents. However, at the 300‐m spatial extent we found a negative, significant relationship between average stand height and squirrel abundance. Synthesis and applications. Boreal and foothill populations of northern flying squirrel in Canada appear unrelated to landscape composition at the relatively large spatial resolutions characteristic of resource inventory data commonly used for management and planning in these regions. Flying squirrel populations do not appear clearly associated with old‐aged or conifer forests; rather, they appear as habitat generalists. This study suggests that northern, interior populations of northern flying squirrel are probably more related to stand‐level components of forest structure, such as food, microclimate (e.g. moisture) and understorey complexity, variables not commonly available in large‐scale digital map inventories. We conclude that the available digital habitat data potentially exclude relevant, spatially dependent information and could be used inappropriately for predicting the abundance of some species in management decision making.
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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".