Bioclimatic Ecosystem Resilience Index (BERI) for Australia
Bibliographic record
Abstract
The CSIRO Bioclimatic Ecosystem Resilience Index (BERI) for Australia is a spatial layer representing the estimated capacity of ecosystems to retain biological diversity in the face of ongoing, and uncertain, climate change (Ferrier et al. 2020). The BERI assesses the extent to which any given spatial configuration of natural habitat across a landscape will promote or hinder climate-induced shifts in biological distributions. It does this by analysing the functional connectivity of each grid cell to areas of habitat in the surrounding landscape which are projected to support a similar assemblage of species under climate change to that currently associated with the grid cell. BERI is a Component indicator for Target 8 of the Convention on Biological Diversity Kunming-Montreal Global Biodiversity Framework (CBD 2022): “Minimize the Impacts of Climate Change on Biodiversity and Build Resilience”. The analysis to derive the BERI accounts for: (1) current spatial patterns in species assemblage turnover; (2) projected change in species assemblage turnover over space and time associated with one or more climate change scenarios; (3) spatial patterns in ecosystem condition as available habitat for biodiversity; (4) connectivity over space and time, accounting for ecosystem condition and environmental conditions. The BERI values for each grid cell in the layer provided contain a value between 0, equating to estimated complete loss of accessible (connected) habitat suitable for native species originally associated with that cell (low resilience), and 1, equating to estimated complete retention of the amount of this accessible habitat (high resilience). BERI values are often in the lower range, due to the combined effects of climate change and degradation of ecosystem condition, with areas of lower ecosystem condition affecting biodiversity through both direct habitat loss and reduced connectivity. BERI spatial layers are provided for two different taxonomic groups: vascular plants and reptiles (‘BERI_Australia_.tif’). Also provided are layers for each taxon (‘SumSimilarity_Australia_.tif’) representing the relative area of compositionally similar habitat when all locations were in a pre-intensification reference state without climate change (i.e. ecosystem condition = 100 %). These layers enable BERI to be aggregated and summarised for any reporting region within Australia, accounting for spatial variation in the composition of species assemblages, using the method described in the associated document (‘BERI_regional_summary_method.docx’), including example code (‘BILBI_regional_summary_function.R’).
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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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".