Historical Contingencies in the Ecology and Evolution of Species Diversity
Bibliographic record
Abstract
Ecologists have long-sought to explain the high diversity of species in biological communities, given that classic theory predicts that diversity is limited by available niche space. In recent years, ecologists have looked towards â historical contingenciesâ , the persistent effects of past ecological and evolutionary processes, as possible mechanisms that maintain diverse communities, either by relaxing the constraints of niche availability or by adding temporal dimensions to speciesâ niches. In this thesis, I use field and greenhouse experiments to explore three ways in which historical contingencies manifest in annual plant communities. First, my work on maternal effects shows that abiotic (ch. 2) and biotic (ch.3) conditions in the maternal generation have diverse effects on offspring phenotypes across an assemblage of species. Because species differences in environmental responses can facilitate coexistence, these studies suggest that maternal effects could act as a form of niche differentiation, and motivate future research to clarify their influences on coexistence outcomes. Second, I performed, to my knowledge, the first experimental decoupling of dispersal limitation and environmental sorting in a natural landscape by manipulating entire seed pools of annual plants (ch. 4). In doing so, I was able to identify the pervasive and scale-specific influences of dispersal limitation that constrain species distributions in plant communities. Lastly, I used competitive trials to identify macroevolutionary divergence in competitive interactions among species (ch. 5), and found evidence that divergence is contingent on historical competitive interactions in ways that are consistent with character displacement. In sum, my dissertation work has expanded our understanding of (i) the number of potential niche dimensions that might allow species to differentiate, (ii) how this differentiation can arise over evolutionary time, and (iii) the interplay of current and historical conditions in the maintenance of species diversity, and the timescales over which they play out.
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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 | 0.002 | 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 | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".