From species to genes: ecological and evolutionary mechanisms structuring diversity in space and time
Bibliographic record
Abstract
My Ph.D. thesis addresses three foundational questions in conservation biology: i) what is biodiversity and how is it best measured? ii) how does variation in habitat configuration, habitat composition, and environmental conditions affect emergent patterns of species diversity? and iii) how do these same factors relate to genomic variation within single species? Our analyses of temporal patterns of butterfly species diversity resolved that negative relationships between species richness (total number of species) and species evenness (relative abundances of species) may compromise the efficacy of many diversity indices. As environmental conditions become more favorable, richness often increases while evenness decreases, meaning indices that conflate these two components of diversity (e.g., information entropies) show little change through time. Based on these findings, we outline analytical recommendations for citizen-science and long-term monitoring programmes.Building on this work, we established a series of research projects that utilized lake islands as a naturally fragmented landscape for investigating effects of habitat configuration and composition on the diversity of butterflies and vascular plants. Overall, species richness was generally unrelated to degree of fragmentation, supporting stochastic assembly of species consistent with the sample-area effect. However, by developing a novel modelling framework that addresses abundances and occurrences of individual species, we were able to resolve that, after controlling for the sample-area effect, variation in island area and isolation disproportionately affect smaller, less-mobile butterfly species. Importantly, these analyses clearly demonstrate how emergent patterns of species richness can obscure important, species-specific responses to fragmentation. Our findings question previous, richness-based support for the recently proposed and widely debated habitat amount hypothesis, which posits that conservation efforts should focus solely on preserving the maximum amount of habitat irrespective of its degree of fragmentation. Additionally, we carried out a series of experimental releases of butterflies in the lake-island matrix. Tracking movements of released individuals suggested there is significant disparity in species’ ability to navigate fragmented landscapes and that visual senses play a primary role in habitat detection.The last section of my thesis addresses gene flow and climate-associated genomic variation within Dod’s Old World swallowtail butterfly, Papilio machaon dodi, throughout its Canadian range. Using a combination of genomic analyses and habitat suitability models, we identified two distinct evolutionary lineages (north vs south) that are genetically and ecologically divergent, maintained by local adaptation to climatic conditions. Based on climate change projections, we predicted that the northern lineage is likely to be extirpated and displaced by the southern lineage within 50 years. After controlling for climate-associated genetic variation, configurations of suitable habitat were unrelated to genetic connectivity within P. m. dodi. This result challenges a foundational method in ecology: the use of habitat suitability models to infer patterns of connectivity between isolated populations when genetic data are unavailable.The combination of these thesis projects demonstrates clear utility for integrating biogeography, landscape ecology, and population genomics to address cumulative effects of habitat fragmentation, habitat loss, and climate change on the ecology and evolution of species. Much of my thesis work suggests that an autecological approach, addressing responses of individual species to geographic and environmental factors, may be most sensible from a theoretical perspective and most effective from a conservation perspective. However, continued work and consilience among biogeography, landscape ecology, and population genomics are required to resolve whether generalizations across taxa are viable and applicable to conservation practice.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".