Patch-burn grazing provides resources for upland-nesting ducks
Bibliographic record
Abstract
Contemporary rangeland management has expanded from a focus on forage and livestock production to multi-use management practices that include concepts like biodiversity and natural disturbance regimes. Patch-burn grazing (PBG) has been promoted as a multi-use land management practice that can restore vegetation structural heterogeneity and subsequently increase diversity of higher trophic levels, such as grassland birds. However, little is known about how the diverse assemblage of upland-nesting ducks responds to disturbances like interacting fire and grazing within a PBG framework. PBG divides a pasture into equal proportions (i.e., patches) and burns an individual patch annually to reduce residual vegetation and attract livestock grazing. Upland-nesting ducks are generally thought to require dense vegetation structure associated with areas of low disturbance for nesting. However, prescribed fire and grazing are essential for the conservation and management of grasslands. PBG may negatively affect ducks in recently burned patches, but may also support ducks through the provisioning of greater structure in patches with greater year(s) since fire (YSF) and could be a viable management strategy to meet grassland and duck conservation objectives. To assess the compatibility of PBG with duck conservation, we estimated nest site selection and survival of duck nests on private lands managed with PBG in the unglaciated plains and prairie pothole region of North Dakota, USA. We located 478 duck nests of four species: 230 Blue-winged Teal (Spatula discors), 72 Gadwall (Mareca strepera), 71 Mallard (Anas platyrhynchos), and 105 Northern Pintail (A. acuta). Blue-winged Teal, Gadwall, and Mallard selected for ≥ 2 YSF and avoided ≤ 1 YSF patches. Northern Pintail selected for 1 YSF and 2 YSF patches. Year(s) since fire affected survival differently for Blue-winged Teal and Gadwall, indicating the importance of variable structure resulting from disturbance regimes. Additionally, nest survival decreased as litter accumulation increased for Blue-winged Teal and Gadwall. Our findings indicate that PBG created nesting areas for ducks in later YSF patches. However, we found contrasting effects of survival in selected patches for certain species. High selection but low survival was limited to a single patch and does not necessarily limit duck nesting activity with adjacent patches having high selection and survival. Additional management strategies may be required to ensure > 1 YSF patch consists of vegetation characteristics that will attract duck nesting activity. Given our results, it appears that variable structure resulting from PBG is in line with conservation objectives, and given the need for multi-objective management, this may be a good choice for land managers interested in game and non-game conservation goals.
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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 | 0.000 | 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) | 0.001 | 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".