Use of provisioning ecosystem services drives loss of functional traits across land use intensification gradients in tropical forests in Madagascar
Bibliographic record
Abstract
Ecosystems services are threatened by the rapid degradation of tropical rainforests. In light of these threats, questions remain about how societies on the forest fringe who depend on provisioning services affect plant functional traits. This study assessed the relationship between plant functional traits, forest-dependent societies and provisioning ecosystem services along a forest–agriculture matrix gradient in tropical humid forests of Madagascar. Data were collected for six functional traits and six provisioning services. We evaluated functional diversity (FD) and utilitarian diversity (FD of provisioning services) along disturbance gradients. We also determined the traits most susceptible to loss along the gradient as well as the relationship between functional traits and provisioning services. The results showed that FD, utilitarian diversity and species richness decreased significantly across all modified habitats. There was a distinct suite of traits absent from intensely used habitats and those same traits were associated with the two most important provisioning services in the region (firewood and construction). The activities of people living on the forest fringe seem to be a strong selective force on trait loss in plant communities, which in turn will influence future species assembly and trait diversity and distribution. Moreover, this study suggests that it is possible to predict trait loss from plant communities in forests where degradation is mediated primarily through subsistence agriculture and resource extraction. Conservation efforts should recognize that forest degradation and deforestation are contextually specific, determined mostly by people’s efforts to maintain their basic livelihood, and therefore necessitate local-scale interventions that feed into landscape-scale policy initiatives.
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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 | 0.000 | 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".