Consequences of parasite invasion and land use on the spatial dynamics of host populations
Bibliographic record
Abstract
1 Conversion of natural habitats to human use can affect the abundance and distribution of predators and parasites, create population sinks, and reduce the viability of valued prey and host species. We asked how the distribution of brown-headed cowbirds Molothrus ater, a generalist brood parasite, has influenced the source–sink dynamics of song sparrow Melospiza melodia populations and their regional population trends. 2 We intensively studied 17 host populations subject to varying levels of parasitism for 1–36 years. We linked these data to spatial and demographic models to predict growth rate in song sparrow populations in the Southern Gulf Islands, BC, Canada. 3 Patterns of growth in song sparrow populations were closely related to cowbird distribution, which in turn depended on land use patterns at landscape scales. Locally, sparrow populations were expected to increase in areas far from cowbird feeding areas, where parasitism was low, but to decline where parasitism exceeded 20%. The predicted population trends were similar to those recorded locally and via the North American Breeding Bird Survey. 4 Synthesis and applications. We show that the distribution of habitats favourable to brood parasites can affect whether host populations grow or decline regionally. In highly sedentary hosts like the sparrows in this study, density-dependent juvenile dispersal and marked spatial variation in the probability of parasitism can give rise to source-and-sink dynamics. Our results illustrate how the application of spatial models and empirical data can predict how land use decisions may influence host dynamics. We identify ways in which applied ecologists might influence land use to enhance the persistence of valued hosts, and suggest that our approach provides a promising framework for exploring regional-scale spatial dynamics of species in order to identify critical habitat and prioritize investments in conservation.
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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 | 0.001 | 0.004 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 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".