Usually hated, sometimes loved: A review of wild ungulates' contributions to people
Bibliographic record
Abstract
Nature's contributions to people (NCP) may be both beneficial and detrimental to humans' quality of life. Since our origins, humans have been closely related to wild ungulates, which have traditionally played an outstanding role as a source of food or raw materials. Currently, wild ungulates are declining in some regions, but recovering in others throughout passive rewilding processes. This is reshaping human-ungulate interactions. Thus, adequately understanding the benefits and detriments associated with wild ungulate populations is necessary to promote human-ungulate co-existence. Here, we reviewed 575 articles (2000-2019) on human-wild ungulate interactions to identify key knowledge gaps on NCP associated with wild ungulates. Wild ungulate research was mainly distributed into seven research clusters focussing on: (1) silvicultural damage in Eurasia; (2) herbivory and natural vegetation; (3) conflicts in urban areas of North America; (4) agricultural damage in Mediterranean agro-ecosystems; (5) social research in Africa and Asia; (6) agricultural damage in North America; (7) research in natural American Northwest areas. Research mostly focused on detrimental NCP. However, the number of publications mentioning beneficial contributions increased after the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services conceptual framework was implemented. Human-ungulate interactions' research was biased towards the Global North and Cervidae, Suidae and Bovidae families. Regarding detrimental NCP, most publications referred to production damage (e.g. crops), followed by biodiversity damage, and material damage (e.g. traffic collisions). Regarding beneficial NCP, publications mainly highlighted non-material contributions (e.g. recreational hunting), followed by material NCP and regulating contributions (e.g. habitat creation). The main actions taken to manage wild ungulate populations were lethal control and using deterrents and barriers (e.g. fencing), which effectiveness was rarely assessed. Increasing research and awareness about beneficial NCP and effective management tools may help to improve the conservation of wild ungulates and the ecosystems they inhabit to facilitate people-ungulate co-existence in the Anthropocene.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.012 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| 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".