Seasonality, species richness and poor dispersion mediate intraspecific trait variability in stonefly community responses along an elevational gradient
Bibliographic record
Abstract
Summary Across environmental gradients, some functional strategies are favoured over others resulting in differences in local species composition and distribution of any given functional trait. This generates among‐Species Trait Variability ( STV ) across the gradient (reflecting species turnover), as well as spatial Intraspecific Trait Variability ( ITV ), which together contribute to Community Trait Variability ( CTV ). Understanding functional trait responses of freshwater biota is critical for elucidating the mechanisms that operate during community assembly and addressing community level responses to climate warming. In freshwater insects, temperature and ecological conditions regulate growth rates. Here, we examined size‐related trait variability components of short‐dispersing stoneflies (Insecta: Plecoptera) within and among multispecies stonefly assemblages (henceforth referred to as communities ), located along an elevational gradient in Sierra Nevada (Spain) to assess the components of trait‐elevation matching ( STV , ITV , CTV ). Relative to downstream reaches, headwaters hypothetically show greater internal physical habitat heterogeneity (large exposed rocks, tree roots, woody debris) and greater local species richness of cool‐water adapted stoneflies. As a result, we expected CTV to increase with elevation, with a higher contribution of STV than ITV in upper reaches due to higher species richness and trait divergence among them. In contrast, the pattern of ITV should vary depending on whether the main driver across elevation is species richness (decrease due to niche partitioning) or ecological conditions (increase associated to physical habitat heterogeneity). Eleven streams were sampled every 2 weeks over 1 year and five size‐related traits were measured on 6,893 individuals belonging to 16 species. Overall, STV made a much larger contribution to CTV than ITV , which only became an important contributor in species‐poor assemblages, especially in winter and autumn. Within each season, the trait‐elevation matching was weak. Functional species‐specific responses to the elevational gradient most often did not mirror the response of the entire communities, since highly variable (and even opposed or discontinuous) contributions to ITV were found across species. Overall, ITV contributed little to trait‐elevation matching, which suggests high vulnerability of short‐dispersing stoneflies to habitat shifting associated to future climate warming due to limited phenotypic plasticity. Moreover, varying functional trait patterns across species emphasise species‐specific responses to climate change as opposed to a unique whole community response. However, further trait‐based macroecological studies across freshwater macroinvertebrates lineages are needed to compare patterns and establish generalisations.
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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 | 0.002 | 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 | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".