Incorporating abiotic controls on animal movements in metacommunities
Bibliographic record
Abstract
Local dynamics are influenced by regional processes. Meta-ecology, or the study of spatial flows of energy, materials, and species between local systems, is becoming increasingly concerned with accurate depictions of species movements and the impacts of this movement on landscape-level ecosystem function. Indeed, incorporating diverse types of movement is a major frontier in metacommunity theory. Here, we synthesize literature to demonstrate that the movement of organisms between patches is governed by the interplay between both a species' ability to move and the combined effects of landscape structure and physical flows (termed abiotic controls), which together we refer to as abiotic-dependent species connectivity. For example, two lakes that share geographic proximity may be inaccessible for mobile fish species because they lack a river connecting them (landscape structure), but wind currents may disperse insects between them (physical flows). Empirical evidence suggests that abiotic controls, such as ocean currents, lead to abiotic-dependent species connectivity and that, in nature, this type of connectivity is the rule rather than the exception. Based on this empirical evidence, we introduce a novel mathematical framework to demonstrate how species movement capabilities and abiotic conditions, can interact to influence metacommunity stability. We apply this framework to predict how incorporating abiotic-dependent species connectivity applies to classic empirical examples of aquatic, aquatic-terrestrial, and terrestrial experimental metacommunities. We demonstrate that incorporating abiotic-dependent species connectivity into metacommunity models can lead to a much broader range of dynamics than models previously predicted, including a wider range of metacommunity stability. Our framework fills critical gaps in our basic understanding of organismal movement across landscapes and provides testable predictions for how such common natural phenomena impact landscape-level ecosystem function. Finally, we present future perspectives for further development of meta-ecological theory from questions about fragmentation to ecosystems. Anthropogenic change is not only leading to habitat loss from the damming of rivers to denuding the landscape, but altering the physical flows that have historically connected communities. Thus, recognizing the importance of these processes in tandem with species' movement abilities is critical for predicting and preserving the structure and function of ecological communities.
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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) | 0.002 | 0.001 |
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".