Disturbance‐Mediated Apparent Competition Decouples in a Northern Boreal Caribou Range
Bibliographic record
Abstract
ABSTRACT The most widely reported threat to boreal and mountain populations of woodland caribou ( Rangifer tarandus caribou ; caribou) involves habitat‐ or disturbance‐mediated apparent competition (DMAC). With DMAC, natural and anthropogenic disturbances that increase the abundance of deciduous‐browsing cervids (e.g., moose [ Alces alces ], deer [ Odocoileus spp.]) are thought to promote predator (especially wolf [ Canis lupus ]) numbers, which heightens predation risk to caribou. We know most about the effects of DMAC on caribou where the species is under threat by anthropogenic activities in relatively productive southern boreal and mountain systems. Yet, >60% of extant boreal caribou range in North America consists of northern shield and taiga ecoregions of low productivity where caribou may compete with only 1 ungulate species (moose) in the context of DMAC. In this environment, we know very little of how DMAC acts as a limiting factor to caribou. In Saskatchewan, Canada, from 2014–2018, using a combination of vegetation sampling, aerial surveys, and telemetry data ( n = 38 wolves), we searched for evidence of DMAC (trends in data consistent with the hypothesis) in an 87,193‐km 2 section of the Western Boreal Shield, a poorly productive but pristine region (0.18% of land cover classed as an anthropogenic feature) with a historically high fire‐return interval (47% of stands aged <40 years). Despite the high levels of disturbance, moose density was relatively low (47 moose/1,000 km 2 ), likely because of the scarcity of deciduous or mixed‐wood stands and low abundance of deciduous browse in the young conifer stands that dominated the landscape. In contrast, boreal caribou density was relatively high for the species (37 caribou/1,000 km 2 ). Wolf density (3.1 wolves/1,000 km 2 ) and pack sizes ( = 4.0 wolves/pack) were low and resident (established) territories were large ( = 4,360 km 2 ; 100% minimum convex polygon). The low density of wolves mirrored the low (standardized) ungulate biomass index (UBI; moose + boreal caribou) of the study area (0.36 UBI/km 2 ). We conclude that wolf and hence caribou populations were not responding in accordance with the outcomes generally predicted by DMAC in our study area because the requisite strong, positive response to fire of deciduous‐browse and alternate‐prey abundance was lacking. As a limiting factor to caribou, DMAC is likely modulated at a macroecological scale by factors such as net primary productivity, a corollary to the general hypothesis that we advance here (i.e., primary productivity hypothesis of DMAC). We caution against managing for caribou based on the presumption of DMAC where the mechanism does not apply, which may include much of boreal caribou range in the north. © 2020 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".