Tamarisk biocontrol alters bird community composition in the absence of cottonwood and willow vegetation
Bibliographic record
Abstract
Abstract Invasive plants threaten biodiversity worldwide, but control of non-native species may affect native species in complex ways. Non-native tamarisk (Tamarix spp.) is widespread in western U.S. riparian environments, and tamarisk beetles (Diorhabda spp.), a tamarisk-specific herbivore, were subsequently introduced as biocontrol. The primary effect of biocontrol is defoliation and branch dieback, with repeated defoliation killing the plant. We investigated the initial stages of site recovery after biocontrol and how tamarisk decline affected birds, their arthropod prey, and microclimate. We compared avian community diversity and composition, arthropod abundance, humidity, and temperature at sites along the Virgin River in Nevada and Arizona, USA characterized as either mixed native vegetation, tamarisk-dominated, or tamarisk-dominated where the majority of tamarisk died from biocontrol. We compared avian communities sampled after biocontrol to counts at the same locations before biocontrol. Prior to biocontrol, community compositions of all but one site grouped together using unbiased clustering algorithms. Following biocontrol, tamarisk-dominated sites grouped separately, and mixed sites grouped with the pre-biocontrol cluster. Comparison of pre- and post-biocontrol communities showed 7 common species declined by ≥30% in dead tamarisk sites, while one species did so at mixed sites and 3 at tamarisk-dominated sites. Individual census points in dead tamarisk had significantly lower Simpson diversity than the same points censused before biocontrol, unless native vegetation was present, suggesting tamarisk death was the cause of dominant species abundance changes. Tamarisk-dominated sites were hotter and drier than sites with native vegetation and supported fewer non-tamarisk-obligate arthropods, consistent with the hypothesis that bird reductions were driven by changes in microclimate and prey abundance. How long these effects last will depend upon the rate of native vegetation recovery after biocontrol, therefore we recommend monitoring sites to determine the trajectory of vegetative recovery and considering the need and feasibility of active restoration in those sites with slow or no native regeneration.
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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 | 0.000 | 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) | 0.001 | 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".