The implications of climate change for positive contributions of invertebrates to world agriculture.
Bibliographic record
Abstract
Abstract Terrestrial invertebrate species play a dominant role in the trophic dynamics of agricultural ecosystems. Subtle changes in the composition of communities and species interactions at different trophic levels, and role of ecosystem engineers can dramatically modify the effects of invertebrates on plant productivity in agricultural systems. The effect of climate change on relevant invertebrates in agricultural systems, and their potential to adapt or move is discussed. All terrestrial systems (including forestry and pasture) are considered, although the main focus is on crop production systems. Our treatise centres on whole organisms (as opposed to genetic information from invertebrates) that play key roles in agricultural systems. We start with an overview of current thinking on how climate change may affect invertebrates. Then, recognizing the great invertebrate biodiversity associated with agro-ecosystems, the review focuses on three key groups - soil invertebrates, biological control agents and pollinators. A variety of research gaps became apparent during the course of our review. Specific conclusions regarding the impact of climate change on particular elements of invertebrate genetic resources in agriculture are not possible yet. Existing evidence suggests that three general assumptions can be made. First, it is probable that climate change will disrupt to varying degrees the role and use of invertebrates in agriculture, especially sustainable agriculture, even though the precise nature of the disruptions is not yet known. Second, without intervention, these disruptions will result in production losses particularly in sustainable agriculture, even though the scale and extent of the losses is not yet known. Third, the extent of some of the losses will justify intervention to facilitate adaptations of the invertebrates, even though the methods with which to intervene and policies to facilitate this intervention are not yet in place.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".