The impacts of climate change on livestock: An interdisciplinary, scoping review of health, production, and adaptation strategies
Bibliographic record
Abstract
Climate change has been recognized to negatively affect livestock animals, as it can severely impair their health and productivity by disrupting homeostasis. This study aims to linearly compile the sources of environmental stress on livestock animals into a more comprehensible format, which can be of great value to new policymakers, practitioners, or researchers alike. Literature curation was performed using online databases while focusing on publications made in the last 25 years. Unlike conventional reviews that tend to address single species or regional case studies, this paper integrates cross-species comparisons to identify shared physiological responses to heat stress and other climate-related stressors. It also contrasts the different temperature–humidity index (THI) standardization methods applied across livestock systems, providing one of the first interdisciplinary syntheses that unify animal physiology, biochemistry, and environmental physics under a single analytical framework. The main research gap addressed by our paper is the relative lack of acknowledgement in terms of the extent of climate stressors affecting livestock in the current literature. Previous work, to the best of our knowledge, does not address the entire radius of environmental stressors, which can range from increased temperatures to region-specific extreme weather events, such as dust storms. By linearly integrating insights from various fields of study, this paper serves as a valuable resource for any reader in the industry who is seeking to learn more about the challenges posed by climate change in the livestock sector, regardless of their experience or tenure. • Climate change affects livestock by disrupting their physiological homeostasis. • Heat stress is caused by periods of highly elevated temperatures. • Global warming shifts disease vectors northward, posing a risk to livestock. • Adaptation and resilience can be enhanced via climate-smart agricultural practices.
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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 | 0.001 | 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".