Role of landscape composition and geographical location on breeding philopatry in grassland passerines : a stable isotope approach
Bibliographic record
Abstract
Grassland bird populations in North America are in steady decline.Despite declining faster and more consistently than any other group of birds, grassland songbird populations are relatively understudied and little is known about factors driving breeding-site philopatry and dispersal.Landscape and habitat composition may influence fidelity of grassland songbirds to a breeding area.As predicted by the theory of the Ideal Free Distribution, high-quality sites are likely to have a higher percentage of return breeders than low-quality sites because higher quality sites should have more or better-quality resources birds need for improved fitness.Using stable hydrogen isotope (δD) analysis, I approximated minimum fidelity rates of two grassland songbirds to two landscape (grass-vs crop-dominated landscapes) and two habitat (native grass vs planted grass) types.I hypothesized that grassland songbirds would return more readily to higher quality sites.For Sprague's Pipit (Anthus spragueii), a habitat specialist, this would mean returning more readily to native grass habitat in grass dominated landscapes.I expected no difference in return rate of Savannah Sparrow (Passerculus sandwichensis), a habitat generalist, to either habitat or landscape.However, I found that the proportion of non-returning breeders was not influenced by landscape or habitat for either species.Furthermore, I examined attributes (distance from capture point to nearest crop and to the nearest road, as well as the percentage of native grass, planted grass, water and woody vegetation within landscape and territory buffers around the capture point) of the landscape and territory of each individual to determine if specific landscape or territory characteristics influenced their return rate to a breeding area.Neither species showed an affinity or aversion to any of the landscape or territory characteristics considered.At a larger scale, geographical position within the breeding range may influence dispersal rates of migratory songbirds.Given that environmental factors often change in a clinal manner, iii central populations presumably experience the most favorable environmental conditions and peripheral populations the least favorable.Therefore, geographically peripheral locations likely occur in ecologically marginal or stressful conditions, resulting in higher dispersal rates of migratory birds.I examined the differences in dispersal rates of two grassland songbirds at two geographically distinct locations; one centrally located in the Sprague's Pipit breeding range (Last Mountain Lake area, SK, Canada) and one at the periphery (Bowdoin National Wildlife Refuge, MT, USA).As expected, Sprague's Pipits at the Bowdoin National Wildlife Refuge had a significantly larger dispersal rate than at the Last Mountain Lake area.Savannah Sparrow dispersal rates did not differ between locations at the more conservative outlier classification.These results provide some limited evidence that geographical position within the breeding range can influence dispersal rates.Using δD analysis, I found that local amount-weighted growing-season deuterium in precipitation (δD p ) at locations within grassland ecosystems differed from those long-term (45+ year) models described by stable hydrogen isotope ratio basemaps, illustrated in Hobson and Wassenaar (1997), Meehan et al. (2004) and Bowen et al. (2005).Therefore, I describe how δD p values were corrected from the long-term isoscape value predicted by Bowen et al. (2005).This method of determining year-specific local weighted growing-season δD p is an improvement upon the currently used Bowen et al. (2005) isoscape that is based on long-term precipitation patterns.To improve assignment of individuals to origins based on their δD f values, future research should incorporate year-to-year variation by applying year-specific corrections to the Bowen et al. (2005) isoscape.More research is needed to determine the factors affecting the philopatry and dispersal of grassland songbirds in order to conserve them.I thank my committee member
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".