A shift from individual species to ecosystem services effect: Introducing the Eco-indicator Sensitivity Distribution (EcoSD) as an ecosystem services approach to redefining the species sensitivity distribution (SSD) for soil ecological risk assessment
Bibliographic record
Abstract
Abstract Incorporating the ecosystem services (ES) approach into soil ecological risk assessment (ERA) has been advocated over the years, but implementing the approach in ERA faces some challenges. However, several researchers have made significant improvements to the soil ERA, such as applying the species sensitivity distribution (SSD) to discern chemical effects on the soil ecosystem. Despite the considerable contributions of SSD to ERA, SSD fails to relate chemical impact on individual species to ES and account for functional redundancy as well as soil ecosystem complexity. Here, we introduce the Eco-indicator Sensitivity Distribution (EcoSD). An EcoSD fits ecological functional groups and soil processes, termed “eco-indicators,” instead of individual species responses to a statistical distribution. These eco-indicators are related directly to critical ecosystem functions that drive ES. We derived an EcoSD for cadmium as a model chemical and estimated a soil ecosystem protection value (EcoPVSoil) based on the eco-indicator dataset for cadmium from the literature. The EcoSD identified nitrogen cycling as the critical process disrupted by cadmium. A key advantage of EcoSD is that it identifies key ecological and chemical indicators of an ES effect. In doing so, it links chemical monitoring results to sensitive ecological functions. The estimated EcoPVSoil for cadmium was slightly more protective of the soil ecosystem than most regional soil values derived from this study's dataset and soil guideline values from the literature. Thus, EcoSD has proven to be a practical and valuable ES concept with the potential to serve as an initial step of the tiered ERA approach. Integr Environ Assess Manag 2024;20:1166–1179. © 2023 SETAC Key Points The proposed Eco-indicator Sensitivity Distribution (EcoSD) demonstrated that cadmium significantly affected soil's eco-indicators of nitrogen cycling. Soil processes were the most sensitive eco-indicators of cadmium toxicity in soil. The EcoSD approach should be adopted to better understand the soil ecological pathways of chemical effects on ecosystem function and service delivery.
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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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 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 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".