Should biomass be considered more frequently as a currency in terrestrial arthropod community analyses?
Bibliographic record
Abstract
Summary Community structure involving large taxonomical groups is frequently used to assess changes in ecosystems along environmental gradients or in response to disturbance. For terrestrial arthropods, abundance is generally used as the response variable in community data analyses; biomass, however, is generally a better indicator of the functionality of a species within a community, as it is strongly correlated with metabolism. In this study, we considered whether biomass should be used more often in community analyses with terrestrial arthropod biodiversity data, particularly when asking questions involving strong functional components. We selected 10 previously published and five unpublished Coleoptera abundance data sets, and produced biomass species‐by‐sample matrices using body length to body mass conversion equations, and then compared the results obtained using commonly used ecological analyses. Correlations between species abundance and biomass varied from strong to poor, depending on the taxa considered and on the sampling method used. We show that abundance and biomass can produce different results in community data analysis and lead to alternative interpretations for data sets with poor abundance to biomass correlations. Synthesis and applications . When dealing with databases showing poor abundance to biomass relationships, the question of the relevance of using biomass instead of abundance emerges, and the choice of the response variable to be used in analyses should be considered carefully. At the very least, when studying terrestrial arthropod biodiversity, one should consider the use of biomass with simple conversion equations that do not require obtaining the mass of individual specimens. This approach may lead to different interpretations. For research questions in which trophic interactions may play an important role, biomass may provide a broader and more accurate picture of the processes driving changes in community structure.
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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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".