Animal responses to environmental variation: physiological mechanisms in ecological models of performance in deer (Cervidae)
Bibliographic record
Abstract
Context Proper assessment of the consequences of environmental variation on animals depends on our ability to predict how they will perform under different circumstances. This requires two kinds of information. We need to know which environmental factors influence animal performance and their mode of action, i.e. whether a given factor acts alone or through interaction with other factors, directly or indirectly, instantaneously or after a delay and so on. This essentially correlative process falls within the domain of ecology. We also need to know what determines the direction, amplitude and limits of animal responses to environmental variation and change. This essentially experimental process falls within the domain of physiology. Physiological mechanisms are frequently poorly integrated within the correlative framework of ecological models. This is evident where programmed responses are attributed to environmental forcing and where the effect of environmental factors is evaluated without reference to the physiological state and regulatory capacity of the animal on which they act. Aims Here we examine ways in which the impacts of external (environmental) stimuli and constraints on performance are moderated by the animals (deer) on which they impinge. Key results The analysis shows (1) how trade-offs in foraging behaviour, illustrated by the timing of activity under the threat of predation, are modulated by integration of short-term metabolic feedback and animal emotions that influence the motivation to feed, (2) how the influence of thermal and nutritional challenges on performance, illustrated by the effect of weather conditions during gestation on the body mass of reindeer (Rangifer tarandus) calves at weaning, depends on the metabolic state of the female at the time the challenge occurs and (3) how annual cycles of growth, appetite and reproduction in seasonal species of deer are governed by innate circannual timers, such that their responses to seasonal changes in food supply are anticipatory and governed by rheostatic systems that adjust homeostatic set- points, rather than being purely reactive. Conclusions Concepts like ‘maintenance’ and ‘energy balance’, which were originally derived from non-seasonal domestic ruminants, are unable to account for annual cycles in metabolic and nutritional status in seasonal deer. Contrasting seasonal phenotypes (fat and anoestrous in summer, lean and oestrous in winter) represent adaptive solutions to the predictable challenges presented by contrasting seasonal environments, not failure of homeostasis in one season and its success in another. Implications The analysis and interpretation of responses to environment in terms of interaction between the external stimuli and the internal systems that govern them offer a more comprehensive, multifaceted understanding of the influence of environmental variation on performance in deer and open lines of ecological enquiry defined by non-intuitive aspects of animal function.
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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 | 0.001 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".