Disturbance, species loss and compensation: Wildfire and grazing effects on the avian community and its food supply in the Serengeti Ecosystem, Tanzania
Bibliographic record
Abstract
Abstract An important question in biodiversity studies is whether disturbances in ecosystems will cause a net loss of species or whether such losses can be compensated by replacement of other species. We use two natural disturbances, fire and grazing, to examine the response of bird and arthropod communities in grasslands of Serengeti, Tanzania. Both burning and grazing by migrant ungulates take place at the end of the rains in June–July. We documented the communities before disturbance, then 1, 4 and 20 weeks after disturbance on three replicate plots and compared them with three undisturbed plots. Birds were recorded by observation, arthropods from pitfall, tray trap and sweepnet samples. We expected that as the grass biomass was reduced by either disturbance, bird communities would change with concomitant change in arthropod food abundance. Alternatively, bird communities would change not with the absolute amount of food but with the greater accessibility of food as the grass structure changed from long to short grass. Results showed first that both bird species richness and abundance increased after both types of disturbance, but burnt sites showed a greater increase than that for grazed sites. Second, there was a change in bird species composition with disturbance. The functionally equivalent athi short‐toed lark (Calandrella athensis) was replaced by the red‐capped lark (Calandrella cinerea). Third, the abundance of most groups of arthropods was lower on disturbed sites than those on undisturbed sites, and the reduction of arthropod numbers was greatest on burnt sites. These results imply that bird abundance did not occur through an increase in arthropod abundance but rather through a change in the grass structure making food more accessible; and the higher predation could have caused the lower arthropod abundance. In addition, some bird species replaced others thus functionally compensating for their loss.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".