Spatiotemporal dynamics and forecasting of ecological security pattern under the consideration of protecting habitat: a case study of the Poyang Lake ecoregion
Bibliographic record
Abstract
The continuous expansion and development of anthropogenic activities pose considerable threats to the habitats of myriad species. Therefore, exploring how to protect and optimize species’ habitats to achieve harmony between humans and nature is particularly important. As a paradise for wildlife, Poyang Lake is the habitat and breeding ground for birds, fish, and other aquatic organisms. In this study, adopting a multi-level perspective of ‘point-line-area’, we had an appliance for habitat conservation by constructing an ecological security pattern (ESP) in the Poyang Lake Ecoregion (PYLE). We produced land use and land cover from 2000 to 2040 using the random forest and cellular automata-Markov model. Combining morphological spatial pattern analysis, landscape pattern index, and Linkage Mapper, we constructed a long-term ESP in the PYLE considering habitat protection. The spatiotemporal dynamics of ESP were compared and analyzed. The results show that PYLE's rapid economic development led to extensive urban growth, encroaching on surrounding bare land, which could undermine local species’ survival. Based on PYLE's predicted ESP in 2040, we propose an optimized ‘one area, two zones, and multiple points’ scheme to prioritize habitat protection. This comprehensive study provides innovative ideas and novel insights for future research and policy formulation in habitat protection.
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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".