Climate and vegetation in a semi-arid savanna: Development of a climate–vegetation response model linking plant metabolic performance to climate and the effects on forage availability for large herbivores
Bibliographic record
Abstract
A framework to establish the expected effects of climate on forage quantity and quality in a local savanna system was developed to interpret large herbivore population performance patterns in the Kruger National Park. We developed a climate–vegetation response model based on interpretation and synthesis of existing knowledge (literature review) and supported by investigation and analyses of local patterns of climate effects on forage plant performance and chemical composition.Developing the climate–vegetation response model involved three main components, namely (1) defining indicators of forage availability to herbivores (nitrogen productivity, nitrogen quality, carbon-nutrient quality), (2) identifying herbivore species guilds of similar nutritional requirements with respect to these indicators [bulk feeders with tolerance to fibrous herbage (buffalo, waterbuck), bulk feeders with preference for high nitrogen quality forage (short grass preference grazers: blue wildebeest and zebra) and selective feeders where dietary items of relatively high carbon-nutrient quality represented key forage resources (selective grazers: sable antelope, roan antelope, tsessebe, eland)] and (3) developing a process model where the expected effects of plant metabolic responses to climate on key forage resources were made explicit.According to the climate–vegetation response model both shorter-term transient temperature acclimation pulses and longer-term shifts in plant metabolic functionality settings were predicted to have occurred in response to temperature trends over the past century. These temperature acclimation responses were expected to have resulted in transient pulses of increased forage availability (increased nitrogen- and carbon-nutrient quality), as well as the progressive long-term decline of the carbon-nutrient quality of forage.Conservation implications: The climate–vegetation response model represents a research framework for further studies contributing towards the enhanced understanding of landscape-scale functioning of savanna systems with reference to the interplay between climate, vegetation and herbivore population dynamics. Gains in such understanding can support sound conservation management.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".