Current nature reserve management in China and effective conservation of threatened pheasant species
Bibliographic record
Abstract
Protected areas, such as nature reserves, are essential for effective conservation of threatened species through protection and management of populations and habitats. Habitat evaluation is a key method that has been frequently used to assess the effectiveness of protected areas. Previous research has mainly focused on species conservation related to changes in land cover and habitat fragmentation while few studies have examined changes in microhabitat structure. Using a multi‐scale habitat change analysis (i.e. regional, macro‐ and microhabitat) in a temporal framework, we assessed the effectiveness of current nature reserve management for the habitat protection of the Reeves's pheasant Syrmaticus reevesii, a vulnerable, forest‐dwelling species. We measured land use/land cover changes inside and outside the Dongzhai National Nature Reserve (DNNR), in 2002 and 2013 corresponding to the times at and after the establishment of the DNNR. We also compared differences in habitat fragmentation patterns and microhabitat structure and composition between the two periods. Results show that the forest coverage has slightly increased both inside and outside DNNR, and habitat fragmentation metrics have not changed substantially since the establishment of DNNR. Significant differences were detected in microhabitat structure and composition between 2002 and 2013. After more than 10 years of no disturbance, canopy cover and density of the shrub layer increased, while herbaceous plant height declined. The observed changes reduced resource availability resulting in increased foraging time for pheasants and increased predation rates. This suggests that current nature reserve management systems may have negative impacts on the conservation of the Reeves's pheasant. We propose that the Regulations of Nature Reserves in China should be revised to account for the habitat requirements of different threatened species with varied life history traits.
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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".