The Ecosystem Integrity Index: a novel measure of terrestrial ecosystem integrity
Bibliographic record
Abstract
Abstract While the importance of ecosystem integrity has long been recognised (Leopold, 1949), conservation science has tended to focus on measuring and monitoring species and habitats, avoiding the complexities of working at the ecosystem level. Ecosystems are highly dynamic, defined by both living and non-living components as well as their interactions (CBD, 1992), making it difficult to assess baseline levels of integrity. We present a novel index that represents the integrity of all terrestrial ecosystems globally at 1km 2 resolution: the Ecosystem Integrity Index (EII). The index provides a simple, yet scientifically robust, way of measuring, monitoring and reporting on ecosystem integrity. It is formed of three components; structural, compositional and functional integrity, and measured against a natural (current potential) baseline on a scale of 0 to 1. We find that ecosystem integrity is severely impacted in terrestrial areas across the globe with approximately one fifth of all ecosystems and one quarter of all ecoregions having lost, on average, over half of their ecosystem integrity. At a national scale, we estimate similar challenges with 115 nations or territories having lost, on average, over half of their ecosystem integrity. This presents a significant threat for humanity as such levels of degradation are likely to be linked to substantial declines in the ecosystem services on which humanity is reliant. The EII has been developed principally to help national governments measure and report on Goal A of the Kunming-Montreal Global Biodiversity Framework (GBF) (CBD, 2022a), for which it has been listed as a Component Indicator. The EII will also be useful in helping non-state actors measure and report their contributions to the GBF and is listed as an indicator by both the Taskforce for Nature-Related Financial Disclosures (TNFD) (TNFD, 2023) and the Science Based Targets Network (SBTN) (SBTN, 2023). The EII aims to enable these actors to make informed decisions on the conservation, restoration and sustainable use of ecosystems for which they are wholly or partly responsible. We propose that with sufficient effort, ecosystem integrity can be restored and contribute towards the GBF’s vision of living in harmony with nature, resulting in the safeguarding of the ecosystem services on which humanity depends.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".