Spatial analyses of multi‐trophic terrestrial vertebrate assemblages in Europe
Bibliographic record
Abstract
Abstract Aim Although much has been said on the spatial distribution of taxonomic and phylogenetic diversity of vertebrates, how this diversity interacts in food webs and how these interactions change across space are largely unknown. Here, we analysed the spatial distribution of tetrapod food webs and asked whether the variation in local food web structure is driven by random processes or by natural and anthropogenic factors. Location Europe. Time period Present. Major taxa studied Tetrapods. Methods We combined an expert‐based food web (1,140 species and 70,601 links) of all European tetrapods with their respective spatial distributions. We mapped 17 different food web metrics representing complexity, chain length, vertical diversity and diet strategy across Europe and tested whether their distribution reflects the spatial structure of species richness using a null model of food web structure. To avoid multicollinearity issues, we defined composite descriptors of food web structure that we related to a set of environmental layers summarizing both natural and anthropogenic influences and tested their relative importance in explaining the spatial distribution of European terrestrial vertebrate food webs. Results Of the 17 metrics, 10 showed a non‐random spatial distribution across Europe and could be summarized along two major axes of variation in food web structure. The first was related to species richness, mean trophic level and the proportion of intermediate species, whereas the second was related to the connectance and proximity of species within the web. Both descriptors varied with latitudinal gradient. The best descriptors of food web structure were mean annual temperature and seasonality (negatively correlated with the first axis), and human footprint (positively correlated with the second axis). Main conclusions We demonstrate the importance of climate and anthropogenic pressure in shaping the spatial structure of European tetrapod food webs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".