Species portfolio effects dominate seasonal zooplankton stabilization within a large temperate lake
Bibliographic record
Abstract
Portfolio effects (PEs) in ecology refer to the suite of phenomenon where the temporal variation of aggregate ecosystem properties (i.e., abundance) is lower than that of their ecosystem components. An example of this is where differential responses of species to environmental variation generate stability at higher levels of ecological organization (e.g., local community, metapopulation, metacommunity). Most of the research examining such PEs has focused on spatial or interannual variation of ecosystems; however, as global change continues to alter seasonality and ecosystem functioning, understanding the underlying food web structures that help maintain stability at multiple spatial and temporal scales is critical to managing ecological systems. Recent advances investigating diversity-stability relationships has led to the development of frameworks that incorporate a metacommunity perspective which allows for the partitioning of PEs across organizational scales (i.e., local community, metapopulation, cross-community, metacommunity) from local population dynamics (total). This partitioning yields insights into the mechanisms that generate observed PEs in nature. Here, we employed one of these recently developed frameworks on a temporally (1986-1999, 2008-2019) and spatially (five sampling stations, local communities) extensive data set of zooplankton abundance (e.g., density) within a large temperate lake to investigate how temporal (seasonal) and spatial (among site) PEs influence stability within the zooplankton metacommunity. We found that seasonal asynchrony of different zooplankton species within local communities and across communities generated the vast majority of stabilization, while spatial (i.e., metapopulation) dynamics were more synchronous and contributed little to overall system stability. Furthermore, significantly positive diversity-asynchrony relationships at the total, local- and cross-community scales were found as asynchrony was positively correlated with local Shannon diversity. Last, a comparison of PEs over the time periods, during which significant local and global changes (i.e., climate warming, invasive species) have occurred suggests that PEs may be eroding, as increasingly synchronous dynamics and declining diversity in recent years have led to a rise in metacommunity variability. We end by arguing for the critical importance of understanding seasonally driven stabilizing mechanisms as local and global changes threaten to fundamentally alter seasonal signals with potentially strong implications for the structures that lend stability to ecosystems.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".