Écologie fonctionnelle du phytoplancton des lacs tempérés et boréaux : le rôle des facteurs environnementaux sur les communautés nanophytoplanctoniques et la prévalence des stratégies d’acquisition de ressources alternatives
Bibliographic record
Abstract
The diversity of lake nanoplankton communities is controlled by a variety of biotic and abiotic factors, including interspecific resource competition. Community diversity is maintained when taxa can avoid competitive exclusion, which can be accomplished by alleviating interspecific competition within the community. In theory, taxa can reduce competition by occupying different spatial niches, i.e., by segregating over the vertical resource gradients usually present in stratified systems. Some taxa also use alternative resource acquisition strategies, in particular phago-mixotrophy, to complement their intake of carbon and nutrients. However, those two mechanisms are not well studied in lakes. Lake physical structure controls nanophytoplankton spatial repartition, and community diversity is driven by a variety of biotic and abiotic factors in addition to resource competition. This limits our ability to investigate whether the vertical distribution of the community truly affects diversity in natural systems without dedicated whole-lake experiments. Our understanding of nanophytoplankton phago-mixotrophy is also incomplete. At a basic theoretical level, it is still unclear how a generalist nutrition strategy like mixotrophy can be viable against specialist phago-heterotrophs and photo-autotrophs. We also know little of the biotic and abiotic drivers that shape nanoplankton assemblages of resource acquisition strategies in freshwater systems. The goal of this thesis work is thus to further our understanding of the effects of those processes for community assembly. In the first chapter of this thesis, we investigated how nanophytoplankton spatial overlap shapes taxonomic and functional community diversity in conjunction with the stratification structure of the water column and top-down interactions (i.e., zooplankton grazing). The degree of spatial overlap within the nanophytoplankton community of a stratified lake was altered by disrupting the thermal structure of the lake. Structural equation models did not reveal an effect of increased levels of spatial overlap h on taxonomic and functional diversity within the community. Overall, the effect interspecific competition induced by increased spatial aggregation on community diversity was marginal compared to the effect of the zooplankton community composition and to water column stratification.In a second study, we tested the viability of nanoplankton phago-mixotrophy as a resource acquisition strategy from a pure resource competition standpoint. We developed a mathematical model of spatial resource competition between three nanoplankton strategies of resource acquisition (pure phagotrophy, mixotrophy and pure phototrophy) and investigated the trophic assemblages predicted by the model for a variability of conditions of light and nutrient availability. Our results show that a generalist mixotrophic trophic strategy is viable against specialist trophic strategies and that a mixotrophs can dominate the community if it displays the adequate mixotrophic functional balance. The vertical position of the competitors was also spatially contrasted, and the mixotroph can grow over a larger portion of the water column relative to specialists. Functional variability within the mixotrophic trait could explain why alternative trophic strategies are ubiquitous in aquatic environments.In the final chapter of this dissertation, we will present an analyse of nanophytoplankton community data from two large scale lake surveys, the EPA National Lake Assessment in the continental US and the NSERC Canadian Lake Pulse Network project in Canada. After assessing the potential for mixotrophy of the various nanophytoplankton genera identified in the two surveys, we assessed the prevalence of mixotrophy in hundreds of lakes using microscopic taxonomic assessment. Mixotrophs were found to ubiquitous across North American temperate and boreal lakes, although it was not uniformly distributed across the sampled ecoregions. Nutrient availability was identified as the main driver of nanophytoplankton trophic assemblages in surface waters, with higher prevalence of mixotrophy in more oligotrophic lakes. Lake trophic state also the controlled the composition and diversity of the mixotrophic portion of the composition. The effect of light availability on resource acquisition strategy assemblages appears to be marginal compared to the effect of nutrient availability. The vertical distribution of taxa and mixotrophy are understudied feature of nanoplankton communities in lakes, those results are thus important contributions to understand the mechanisms controlling the assembly of those communities in lakes. This work made use of a variety of numerical methods, from mechanistic mathematical modelling to in-depth multivariate analyses of large ecological datasets, highlighting the importance of numerical tools for ecological studies.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".