Assessing conservation regionalization schemes: employing a beta diversity metric to test the environmental surrogacy approach
Bibliographic record
Abstract
Abstract Aim Systematic conservation planning often involves the application of a regionalization scheme, which is assumed to delineate distinct ecological communities of target species. Commonly, such schemes are constructed using environmental surrogates; however, their effectiveness with regard to community delineation has been questioned in previous studies. Here, we aim to assess multiple environmental regionalization schemes' ability to delineate avian communities and to evaluate these schemes against a regionalization scheme built using species data directly. Location British C olumbia, C anada. Methods We employed a beta diversity metric using community data from the BC Breeding B ird Atlas in multiple analysis of similarity ( ANOSIM ) tests, to assess the ability of a number of environmental regionalization schemes to delineate species turnover. We also developed a new species‐based scheme using kriged local beta diversity values and a thematic resolution optimized through ANOSIM testing, which was then evaluated against the previously tested schemes. Results All regionalization schemes delineated significant patterns in community structure, with the Bird Conservation Regions performing most similarly to the species‐based regionalization. Regionalizations that required regions to be spatially contiguous outperformed non‐contiguous regionalizations. Increasing thematic resolution (the number of regions within a regionalization) improved a regionalization's overall performance; however, regional redundancy also increased. Main conclusions We argue that environmental regionalizations can function as effective alternatives to species‐based regionalizations, particularly in areas with poor availability of species data. Also, we conclude that spatially contiguous regionalizations are superior to non‐contiguous ones for delineating distinct communities. Lastly, we demonstrate how thematic resolution represents a trade‐off between overall regionalization performance and regional redundancy, and how differing thematic resolutions can be employed depending upon the goals of the user.
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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 | 0.006 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.002 |
| 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".