Microbial communities and nutrient dynamics in experimental microcosms are altered after the application of a high dose of <i>Bti</i>
Bibliographic record
Abstract
Summary Bacillus thuringiensis subsp. israelensis ( Bti ) is the most widely used biopesticide against mosquitoes and blackflies, with a history of high specificity and efficacy. High doses of Bti have been suggested for extended vector control in some environments; however, the effects of Bti application on the native microfauna in the environment are poorly understood. Two Bti (VectoBac G) treatments (high = 48·1 kg ha −1 ; low = 0·6 kg ha −1 ), in addition to an untreated control, were assigned to replicate 300 L microcosms. Culex abundance, phytoplankton biomass, sestonic particulates and nutrients were reduced significantly in the high Bti treatment. These changes affected other physicochemical variables in the water column during the 44‐day field study. Bacterial communities present in the water column were assessed by Illumina sequencing of 16S rRNA genes. The most abundant aquatic bacteria in microcosms subject to a low dose of Bti and untreated control, Cyanobacteria , Cytophagales , Cyclobacteriaceae (phylum Bacteroidetes ) and Sphingomonas (class Alphaproteobacteria ) , were suppressed in microcosms subject to a high dose of Bti . Bacteria in the high Bti treatment were dominated by Mucilaginibacter , Sediminibacterium (phylum Sphingobacteria ) and Polaromonas (class Betaproteobacteria ) and were more diverse than in the other treatments. Synthesis and applications . The biotic and abiotic changes resulting from a biopesticide application that significantly reduced mosquito abundance by more than 50% persisted longer than the period during which larval mosquito numbers were reduced. This warranted further investigation into the ecosystem‐level effects of Bti application rates used routinely for mosquito control. Application rates greater than the label rate for a Bti biopesticide can reduce mosquito abundance for an extended period of time and therefore lessen the operational cost of repeated application, but they could exceed manufacturer's recommendations and might violate country‐specific regulations governing biopesticide applications in natural habitats. Results of our study suggest that the widespread adoption of Bti application above the recommended label rate should be discouraged in habitats where algal abundance and its effect on primary production, microbial communities and nutrient cycling could affect the functioning of aquatic 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 | 0.000 |
| 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".