Mechanisms of functional connectivity: the case of free-ranging bison in a forest landscape
Bibliographic record
Abstract
Functional connectivity is a key determinant of animal distributions in heterogeneous landscapes. Patch connectivity depends on both patch preference and accessibility, but few studies have integrated habitat selection and movement analyses to gain a general understanding of functional connectivity. In this paper, we define functional connectivity by identifying which factors influence the choice of the patch that is visited next, the location from which animals leave the current patch, and the inter-patch trajectory. Our study provides tools to anticipate movement trajectories and, therefore, animal distribution in patchy landscapes. We followed 23 radio-collared bison across the meadow network of Prince Albert National Park between 2005 and 2008. Selection of the next meadow visited over available meadows was assessed by comparing their characteristics and land cover composition of the area separating them from the departure meadow. Additionally, we used 196 bison trails originating from 29 meadows to evaluate movement rules during inter-patch travels. Bison preferred to travel in deciduous rather than in conifer stands during summer and fall but displayed no preference during winter and spring. They also selected meadows offering higher plant biomass in winter than in other seasons. Throughout the year, meadow proximity was an important determinant of meadow selection. Inter-patch trajectory was influenced by directional persistence, as well as movement biases toward the next meadow and toward canopy gaps. Unlike the choices individuals made in selecting their next meadow, bison displayed no preference between forest stands during inter-meadow travel, indicating that functional connectivity involves hierarchical movement decisions. We showed that the behavioral determinants of functional connectivity varied over spatiotemporal scales. First, forest stand composition between meadows influenced the next target, but not the trajectory during inter-meadow travels. Second, meadow selection varied among seasons. Therefore, although structural connectivity may be immutable to these behaviorally induced changes in inter-patch movements, functional connectivity would adequately account for such modifications in animal spatial dynamics.
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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) | 0.002 | 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".