UNEP-SETAC guideline on global land use impact assessment on biodiversity and ecosystem services in LCA
Bibliographic record
Abstract
As a consequence of the multi-functionality of land, the impact assessment of land use in Life Cycle Impact Assessment requires the modelling of several impact pathways covering biodiversity and ecosystem services. To provide consistency amongst these separate impact pathways, general principles for their modelling are provided in this paper. These are refinements to the principles that have already been proposed in publications by the UNEP-SETAC Life Cycle Initiative. In particular, this paper addresses the calculation of land use interventions and land use impacts, the issue of impact reversibility, the spatial and temporal distribution of such impacts and the assessment of absolute or relative ecosystem quality changes. Based on this, we propose a guideline to build methods for land use impact assessment in Life Cycle Assessment (LCA). Recommendations are given for the development of new characterization models and for which a series of key elements should explicitly be stated, such as the modelled land use impact pathways, the land use/cover typology covered, the level of biogeographical differentiation used for the characterization factors, the reference land use situation used and if relative or absolute quality changes are used to calculate land use impacts. Moreover, for an application of the characterisation factors (CFs) in an LCA study, data collection should be transparent with respect to the data input required from the land use inventory and the regeneration times. Indications on how generic CFs can be used for the background system as well as how spatial-based CFs can be calculated for the foreground system in a specific LCA study and how land use change is to be allocated should be detailed. Finally, it becomes necessary to justify the modelling period for which land use impacts of land transformation and occupation are calculated and how uncertainty is accounted for. The presented guideline is based on a number of assumptions: Discrete land use types are sufficient for an assessment of land use impacts; ecosystem quality remains constant over time of occupation; time and area of occupation are substitutable; transformation time is negligible; regeneration is linear and independent from land use history and landscape configuration; biodiversity and multiple ecosystem services are independent; the ecological impact is linearly increasing with the intervention; and there is no interaction between land use and other drivers such as climate change. These assumptions might influence the results of land use Life Cycle Impact Assessment and need to be critically reflected. In this and the other papers of the special issue, we presented the principles and recommendations for the calculation of land use impacts on biodiversity and ecosystem services on a global scale. In the framework of LCA, they are mainly used for the assessment of land use impacts in the background system. The main areas for further development are the link to regional ecological models running in the foreground system, relative weighting of the ecosystem services midpoints and indirect land use.
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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 | 0.015 | 0.020 |
| Meta-epidemiology (narrow) | 0.005 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.009 | 0.012 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.010 | 0.005 |
| Research integrity | 0.010 | 0.010 |
| Insufficient payload (model declined to judge) | 0.011 | 0.011 |
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".