Region constrained terrestrial areas of conservation importance for 2030
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This data repository contains updated layers of global terrestrial conservation importance based on the framework and feature data described in Jung et al. (2021). The purpose of these updated maps is to more closely support modelling efforts in global intercomparison exercises (e.g. Bending the Curve) as well as to align with Target 3 ("30x30") of the Kunming-Montreal Global Biodiversity Framework (source).Compared to the previous results published in Jung et al. (2021), a few updates have been made: The protected area dataset was updated to a WDPA snapshot collated in late November 2024. No hierachical rankings, instead only the solution for 30% global land "budget" are provided. Additional variants (see accompanying variant file) related to national responsibility and a more globally just distribution are provided. Specifically two variants that constrain the maximum allocation of land to 30% per country or 30% of terrestrial biome The global spatial-explicit database on Other Effective Conservation Areas (OECM) is considered in some variants so as to nudge (if there are sufficient benefits) areas of conservation importance towards those places where such management occurs. Data properties: Format Gridded geoTiff Spatial grain 10 x 10 km² and 50 x 50 km² Units Fractions of grid [0-1] x 10000 Geographic projection World Mollweide (https://epsg.io/54009) Reference period 2024 (WDPA) Spatial extent Global (excluding Antarctica) Number of variants / prioritization scenarios 18, See accompanying inventory.xlsx file. Additionally, a reporting protocol following the ODPSCP standard version 0.4 (see Jung et al.) is provided as overview and to allow relative comparisons with other prioritizations. Cautionary notes for interpretation: This analysis reveals areas of conservation importance, defined as those areas which would benefit from increased conservation actions (through whatever measure). They are not prescriptive with regards to the type and governance of conservation (e.g. protected areas) for any given area. This work builds primarily on the processed feature data (biodiversity and carbon) used in Jung et al. (2021). Since then several updates to IUCN range data have been made, which however are not considered in this work. Habitat changes since the production of the feature data, for example owing to land-use changes such as deforestation, were not considered or incorporated. Biodiversity data originates primarily from expert-based range maps, which can be prone to omission and comission errors. Although care was undertaken to geographically project and rasterize the protected area dataset to a gridded resolution, it is possible that not every protected area is captured in whole. There are known issues with publicly available WDPA data not being available for several countries including China (see protectedplanet.net and Bingham et al. 2019). Region-constrains added for those countries in particular thus likely result in more ambitious areas than what already is under conservation management. Several countries (but by far not all) have already made detailed commitments as part of National Biodiversity Strategies and Action Plans (NBSAPs) on which type and how much area they plan to conserve. These were however not taken into account for this work. Disclaimer: Any borders of countries used here as constraint do not necessarily represent the view of IIASA or it's National Member Organizations. All layers are provided as is and the authors takes no responsibility for errors or misuse and misinterpretation. References: Jung, M., Arnell, A., de Lamo, X. et al. Areas of global importance for conserving terrestrial biodiversity, carbon and water. Nat Ecol Evol 5, 1499–1509 (2021). https://doi.org/10.1038/s41559-021-01528-7Jung, M., Arnell, A., De Lamo, X., García-Rangelm, S., Lewis, M., Mark, J., Merow, C., Miles, L., Ondo, I., Pironon, S., Ravilious, C., Rivers, M., Schepashenko, D., Tallowin, O., van Soesbergen, A., Govaerts, R., Boyle, B. L., Enquist, B. J., Feng, X., … Visconti, P. (2021). Areas of global importance for conserving terrestrial biodiversity, carbon, and water (1.0) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.5006332
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 it