How does macroinvertebrate taxonomic resolution influence ecohydrological relationships in riverine ecosystems
Bibliographic record
Abstract
Abstract The taxonomic resolution of macroinvertebrate community data needs careful consideration, to ensure that research objectives in pure and applied freshwater scientific research are met. The level of taxonomy used may be driven by time and financial restrictions associated with the increasing resources and effort needed to identify organisms to a lower taxonomic resolution. This paper aims to assess the influence of taxonomic resolution on the understanding of long‐term (1985–2006) benthic macroinvertebrate community response to changes in the hydrological regime. There were marked differences in the number of taxa included in the analysis when comparing ‘species’‐ and ‘family’‐level data used to derive lotic‐invertebrate index for flow evaluation (LIFE) scores, particularly among species rich orders, such as Ephemeroptera, Plecoptera, Trichoptera and Coleoptera. The performance of the partial least squares (PLS) regression models of hydrological variables and the LIFE scores derived for different taxonomic levels were compared. Coefficients of determination were higher for species‐level LIFE data than for the same data resolved to family level. Results demonstrate that the species‐level LIFE data produced significant model components while those derived from family‐level data were not; although both models indicated the dominance of hydrological indices quantifying the duration and magnitude of the hydrological events. We conclude that there is a growing need to resolve faunal data to species level to adequately fulfil operational and legislative obligations for river management and conservation purposes. Copyright © 2011 John Wiley & Sons, Ltd.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.004 |
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; both teacher heads agree on what is shown here.
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".