Occurrence patterns and trends of frogs in coastal wetlands of the Great Lakes call for further habitat restoration
Bibliographic record
Abstract
Abstract Countless wetlands have been lost and degraded globally, making amphibians the most threatened vertebrate class. However, despite facing extensive threats and stressors, coastal wetlands of the Laurentian Great Lakes of North America (lakes Superior, Michigan, Huron, Erie, and Ontario) still support sizable populations of frogs (order Anura, including toads). We used data from the Great Lakes Coastal Wetland Monitoring Program to quantify the first‐ever annual occurrence probabilities and trends (2011–2023) of eight marsh‐breeding frog species, or groups of species, at 1550 point count locations in 747 coastal wetlands throughout the Great Lakes, and to assess 11 potential drivers of occurrence. Sampled wetlands were marshes greater than 4 ha in area with a permanent or periodic surface‐water connection to an adjacent Great Lake or their connecting river systems. Across our study area, green frog ( Lithobates clamitans ) occurrence increased by 8% per year, whereas chorus frog ( Pseudacris maculata , Pseudacris triseriata ) occurrence decreased by 14% per year. We found more positive or stable trends in occurrence among lakes and species (85%) than negative trends (15%). Occurrence of all species was negatively associated with one or two indicators of poor water quality: specific conductance, ammonium nitrogen, nitrate nitrogen, and urban and agricultural land cover in the surrounding watershed (median area: 12 km 2 ). Occurrence of multiple species was positively associated with high lake levels and surrounding wetland (<250 m) and forest (<2.5 km) land cover and negatively associated with surrounding road density (<2.5 km). Even though occurrence of most species was increasing or stable and was relatively high (>50%), all will likely benefit from conservation actions because 50%–90% of Great Lakes coastal wetlands have been lost and converted to anthropogenic land uses, leaving frog populations at a fraction of their former, original sizes. Therefore, extra precaution is critical to help ensure their growth and persistence. Improving water quality, increasing natural forest and wetland land cover within 2.5 km, and reducing roads within 2.5 km of Great Lakes coastal wetlands will help conserve these important indicator species in this globally recognized but imperiled ecosystem.
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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".