Amphibian Disease Ecology: Are We Just Scratching the Surface?
Bibliographic record
Abstract
Pathogen-induced population declines and extinction events have been recognized as main threats to amphibian species around the globe. However, the ecological drivers underlying epidemiological patterns are still poorly understood. In an attempt to assess the current knowledge on the ecological drivers of amphibian diseases, we identified 832 peer-reviewed publications on the ecology of amphibian pathogens and diseases published between 2009 and 2019. The vast majority of publications investigated either chytrid or ranavirus infections (79% of the articles), whereas other pathogens such as bacteria and helminths received considerably less attention. Just over half of the studies we reviewed included field research and 40% were experimental in nature, yet only 8% combined field and experimental approaches. More than half of the literature (56%) investigated postmetamorphic stages, whereas premetamorphic stages were considered in 23% of the reviewed studies, and only 13% included both life stages. Susceptibility and mortality have been assessed in almost every study (91%) whereas 37% of them tested for cellular, physiological, or immunological responses. However, other host characteristics such as growth/development, behavior, and specific mucosome/microbiome were considered in only one of four studies. Most research included at least one biotic factor (e.g., host and pathogen identity, species diversity, genetic adaptations), but only one-third considered environmental factors (e.g., temperature, landscape features, inorganic chemicals). Furthermore, there is no general consensus about the factors driving epidemiological patterns of pathogens in amphibian communities, and it is clear that the complexity and specificity of interactions between ecological factors and host–pathogen dynamics make conservation implications difficult and management decisions challenging. To this end, our review identifies some research gaps and proposes future directions to better understand one of the major threats to this class of vertebrates.
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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 | 0.007 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.006 | 0.015 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".