Construction of avian biodiversity conservation patterns and optimization of ecological corridors in Jiangsu province
Bibliographic record
Abstract
The Kunming-Montreal Global Biodiversity Framework heralds a transformative vision for global biodiversity governance extending beyond 2030. In alignment with this framework, China has formulated its strategic approach and action plan for biodiversity conservation in the contemporary era. Taking Jiangsu province as a case study, our study explores the methodology of constructing avian diversity conservation patterns and optimizing ecological corridors at a provincial scale. We employed an integrated ecosystem structure and function evaluation method to identify the ecological sources, followed by the utilization of the MaxEnt model to focus on identifying the habitats of 64 species of rare forest birds and water birds within these sources. Based on the landscape resistance surface and least-cost path, we used the kernel analysis method to classify the habitat groups according to patch density. To delineate the spatial extent of ecological corridors, we applied the LSCorridors software package to optimize the proposed ecological corridors by identifying stepping-stones, barriers, and pinch points. Our results show that: (1) Ecological source areas showed a tendency to aggregate locally while remaining regionally isolated. The dominant landscape components included water bodies along with cultivated lands possessing high ecological value. (2) The habitat network for target species comprised 692 least-cost paths, 25 of which extended over 100 km, accounting for 36.72% of the total length, predominantly oriented in an east-west direction. (3) Spatial analysis identified ten distinct habitat groups within the study area, with four concentrated in southern Jiangsu and the others highly isolated. (4) The twelve identified crucial ecological corridors between these groups typically displayed cross-regional characteristics with multiple potential migration routes. For instance, one corridor required optimization at 114 strategic points, including 19 stepping stones, 45 barriers, and 50 pinch points. Our study offers valuable insights for the practical implementation of the Convention on Biological Diversity in China. It supports the comprehensive promotion of mainstreaming biodiversity conservation into ecological protection and restoration planning, serving as a reference for advancing these 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) | 0.001 | 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 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".