Determinants of the detrital arthropod community structure: the effects of temperature and resources along an environmental gradient
Bibliographic record
Abstract
Understanding the factors that shape community structure, and whether those factors vary geographically, has a long history in ecology. Because the abiotic environment often varies in predictable ways along elevational gradients, montane systems are ideal to study geographic variation in the determinants of community structure. In this study, we first examined the relative importance of environmental gradients, microclimate, and food resources in driving spatial variation in the structure of detrital communities in forests of the southeastern USA. Then, in order to assess whether the determinants of detrital community structure varied along a climatic gradient, we manipulated resource availability and microclimatic conditions at 15 sites along a well‐studied elevational gradient. We found that arthropod abundance and richness generally declined with increasing elevation, though the shape of the relationship varied among taxa. Overall community composition and species evenness also varied systematically along the climatic gradient, suggesting that broad‐scale variation in the abiotic environment drives geographic variation in both patterns of diversity and community composition. After controlling for the effect of climatic variation along the elevational gradient, food resource addition and microclimate alteration influenced the richness and abundance of some taxa. However, the effect of food resource addition and microclimate alteration on the richness and abundance of arthropods did not vary with elevation. In addition, the degree of community similarity between control plots and either resource‐added or microclimate‐altered plots did not vary with elevation suggesting a consistent influence of microclimate and food addition on detrital arthropod community structure. We conclude that using manipulative experiments along environmental gradients can help tease apart the relative importance and detect the interactive effects of local‐scale factors and broad‐scale climatic variation in shaping communities.
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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 | 0.001 |
| 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 | 0.001 | 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".