Assessing the Effects of Land-use Change on Plant Traits, Communities and Ecosystem Functioning in Grasslands: A Standardized Methodology and Lessons from an Application to 11 European Sites
Bibliographic record
Abstract
BACKGROUND AND AIMS: A standardized methodology to assess the impacts of land-use changes on vegetation and ecosystem functioning is presented. It assumes that species traits are central to these impacts, and is designed to be applicable in different historical, climatic contexts and local settings. Preliminary results are presented to show its applicability. METHODS: Eleven sites, representative of various types of land-use changes occurring in marginal agro-ecosystems across Europe and Israel, were selected. Climatic data were obtained at the site level; soil data, disturbance and nutrition indices were described at the plot level within sites. Sixteen traits describing plant stature, leaf characteristics and reproductive phase were recorded on the most abundant species of each treatment. These data were combined with species abundance to calculate trait values weighed by the abundance of species in the communities. The ecosystem properties selected were components of above-ground net primary productivity and decomposition of litter. KEY RESULTS: The wide variety of land-use systems that characterize marginal landscapes across Europe was reflected by the different disturbance indices, and were also reflected in soil and/or nutrient availability gradients. The trait toolkit allowed us to describe adequately the functional response of vegetation to land-use changes, but we suggest that some traits (vegetative plant height, stem dry matter content) should be omitted in studies involving mainly herbaceous species. Using the example of the relationship between leaf dry matter content and above-ground dead material, we demonstrate how the data collected may be used to analyse direct effects of climate and land use on ecosystem properties vs. indirect effects via changes in plant traits. CONCLUSIONS: This work shows the applicability of a set of protocols that can be widely applied to assess the impacts of global change drivers on species, communities and ecosystems.
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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 | 0.014 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".