The role of local and regional processes on population synchrony along the gradients of habitat specialization
Bibliographic record
Abstract
Abstract Metacommunity perspective highlights the role of space as a factor contributing to local community structure and dynamics. Often tests of metacommunity models rely on snapshot patterns of species distribution and abundance. Such patterns may introduce biases because they overlook differences in responses of constituent species to changing environmental conditions, particularly when such responses override patterns predicted from dispersal and biotic interactions alone. This applies, for example, to habitat generalists, whose responses to environmental variations differ from those of habitat specialists, resulting in different snapshot patterns at different times. Synchronized (i.e., correlated among sites) environmental variation is perhaps the most obvious case of environmental variation that could generate regular differences among species of different specialization. We hypothesized that synchronized environmental variation synchronizes local populations of habitat specialists to a greater degree than it does for habitat generalists as experiments have shown that habitat generalists are less sensitive to changing environmental conditions. To test this in an empirical system, we used time series data (nine annual surveys) on an invertebrate metacommunity of 49 rock pools on the coast of Jamaica. We found that population synchrony of a significant portion of 24 species sharing these rock pools increased with habitat specialization in response to environmental synchrony (represented by synchrony of environment). However, distance among rock pools, which may affect dispersal or shared perturbations, was negatively correlated with population synchrony of individual species, irrespective of their specialization. As only habitat specialists showed increasing synchrony with environmental synchrony, and both generalist and specialist synchrony were negatively correlated with distance, we infer that habitat generalists must be synchronized more by space‐related processes while habitat specialists by a combination of environmental forcing and dispersal. Overall, the study suggests that species of different habitat specialization show consistent differences with respect to local processes involving environmental variations but show fewer differences with respect to regional processes involving distance, at least when long‐term dynamics are concerned. Furthermore, the study identifies a rarely recognized link between variation in space and its consequences for variation in time—a link much more expressed among spatially restricted species such as habitat specialists.
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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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".