Wetland- and landscape-level effects on scoter (Melanitta spp.), scaup (Aythya spp.), and macroinvertebrates in wetlands of the Central Mackenzie Valley, Northwest Territories
Bibliographic record
Abstract
North American breeding populations of scoters (Melanitta spp.) and scaup (Aythya spp.), which nest predominantly in the rapidly changing boreal forest, were over 20% lower 2005–2014 in the western boreal forest compared to long-term averages (1955–2014), yet habitat needs for these duck species remain poorly documented. The purpose of my research is to predict impacts of ongoing environmental changes on waterfowl food supplies in northern areas and to prioritize key habitats for conservation of these species. At a key waterfowl breeding site in Canada’s boreal forest, I tested three main hypotheses: (i) trophic enrichment – Wetlands located in areas burned by recent wildfires would be characterized by higher nutrient and productivity levels, and unique macroinvertebrate communities, versus those wetlands in unburned areas; (ii) foraging habitat limitation – Variables describing foraging habitat availability would be the best predictors of scoter and scaup occurrence; and (iii) scale dependency – The spatial scales at which landscape variables affected duck occurrence would correspond with home range size.\n\nTo test my first hypothesis, I measured levels of nitrogen, phosphorous, and chlorophyll-a concentrations, as well as macroinvertebrate community characteristics, in burned and unburned wetlands. Consistent with my predictions, total phosphorous and chlorophyll-a levels were approximately two-fold higher in burned than in unburned wetlands, although this effect was seasonally variable. Conversely, total nitrogen levels were similar in burned and unburned wetlands. For macroinvertebrate community composition, results were not as expected – on average, samples from burned and unburned wetlands contained similar taxa in similar abundances. To test my second and third hypotheses, I applied a multi-scale regression approach, using aerial breeding waterfowl survey data and remotely sensed landscape composition variables on unburned wetlands to evaluate relationships between landscape variables and habitat use. As predicted, wetland size correlated strongly and positively with scoter and scaup occurrence. In contrast, the amount of different land cover types correlated only weakly with occurrence. For scoters, the most important landscape variables were total number and area of waterbodies/km2, while the proportion wetland cover was the most important landscape variable for scaup followed by total waterbody area/km2. However, for both scoter and scaup, some of these relationships were negative, contrary to my predictions. I also found that scoters had a larger average scale of effect than scaup, as expected based on the size of their home ranges.\n\nTaken together, these results suggest that wetland ecosystems in the northwestern boreal forest are resilient to, and may even benefit from, moderate to severe fires under current climate conditions. However, fire impacts on aquatic ecosystems are likely to intensify as the climate warms, such that this resilience may not be maintained in coming decades. The results also suggest that scoter and scaup foraging habitat is limited in the study site and that wetland-level conservation for scoter and scaup pairs should be informed primarily by wetland characteristics (e.g., wetland size and amphipod abundance) and less so by landscape composition (e.g., proportion coniferous forest cover) surrounding wetlands. In addition, the findings indicate that future landscape-level predictive modelling for these duck species should include species-specific, scale-optimized variables and should focus on home range selection.
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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".