Water‐saving strategies in rice farming entail cascading effects in prey–predator interactions across ecosystem boundaries
Bibliographic record
Abstract
Abstract Water‐saving irrigation strategies have been globally promoted to mitigate the contribution of flooded rice farming to climate change. While the positive effect of those strategies in reducing greenhouse gas emissions is undeniable, their potential cascading effects across the aquatic–terrestrial interface remain completely unexplored. For instance, multiple drainages throughout the rice cycle associated with alternative irrigation practices may disrupt the emergence of semiaquatic insects from rice fields, reducing prey availability for terrestrial predators and ultimately affecting their reproductive outcomes. Here, by using a 2‐year field‐scale experiment, we addressed these issues by comparing three irrigation strategies that represent a gradient of water use intensity throughout the rice growing season: Conventional permanent flooding (i.e. no drying periods) > mid‐season drainage (i.e. one single drying period; MSD) > alternate wetting and drying (i.e. multiple drying periods; AWD). Specifically, on each experimental plot, we quantified (i) the emergence of semiaquatic insects, (ii) the breeding activity (i.e. the breeding probability) of a jumping spider species (Bianor albobimaculatus, Salticidae) and (iii) its reproductive fitness (i.e. eggs/sac). Our results show that the emergence of semiaquatic insects and, therefore the availability of preys for spiders, were markedly reduced as water use decreased. In addition, while the breeding activity of jumping spiders did not differ among irrigation strategies, their reproductive fitness was severely compromised in the alternate wetting and drying strategy. Synthesis and applications. These results show that introducing multiple drainage periods in rice fields (i.e. AWD) indirectly hampers terrestrial spider reproduction through limiting the emergence of potential preys from the aquatic to terrestrial boundaries. MSD resulted in a more conciliatory strategy as it largely reduces methane emissions and does not affect predator–prey interactions; thus, it should be prioritized over AWD to minimize environmental trade‐offs. Our results highlight the need to account for potential trophic cascading effects when designing climate change mitigation strategies in agriculture to avoid undesirable side‐effects on agroecosystem functioning.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".