Preservation of spatial and environmental gradients by death assemblages
Bibliographic record
Abstract
Although only a few studies have explicitly evaluated live-dead agreement of species and community responses to environmental and spatial gradients, paleoecological analyses implicitly assume that death assemblages capture these gradients accurately. We use nine data sets from modern, relatively undisturbed coastal study areas to evaluate how the response of living molluscan assemblages to environmental gradients (water depth and seafloor type; “environmental component” of a gradient) and geographic separation (“spatial component”) is captured by their death assemblages. We find that: 1. Living assemblages vary in composition either in response to environmental gradients alone (consistent with a species-sorting model) or in response to a combination of environmental and spatial gradients (mass-effect model). None of the living assemblages support the neutral model (or the patch-dynamic model), in which variation in species abundance is related to the spatial configuration of stations alone. These findings also support assumptions that mollusk species consistently differ in responses to environmental gradients, and suggest that in the absence of postmortem bias, environmental gradients might be accurately captured by variation in species composition among death assemblages. Death assemblages do in fact respond uniquely to environmental gradients, and show a stronger response when abundances are square-root transformed to downplay the impact of numerically abundant species and increase the effect of rare species. 2. Species' niche positions (position of maximum abundance) along bathymetric and sedimentary gradients in death assemblages show significantly positive rank correlations to species positions in living assemblages in seven of nine data sets (both square-root-transformed and presence-absence data). 3. The proportion of compositional variation explained by environmental gradients in death assemblages is similar to that of counterpart living assemblages. Death assemblages thus show the same ability to capture environmental gradients as do living assemblages. In some instances compositional dissimilarities in death assemblages show higher rank correlation with spatial distances than with environmental gradients, but spatial structure in community composition is mainly driven by spatially structured environmental gradients. 4. Death assemblages correctly identify the dominance of niche metacommunity models in mollusk communities, as revealed by counterpart living assemblages. This analysis of the environmental resolution of death assemblages thus supports fine-scale niche and paleoenvironmental analyses using molluscan fossil records. In spite of taphonomic processes and time-averaging effects that modify community composition, death assemblages largely capture the response of living communities to environmental gradients, partly because of redundancy in community structure that is inherently associated with multispecies assemblages. The molluscan data sets show some degree of redundancy as evidenced by the presence of at least two mutually exclusive subsets of species that replicate the community structure, and simple simulations show that between-sample relationships can be preserved and remain significant even when a large proportion of species is randomly removed from data sets.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".