The effect of forest fragmentation on aboveground carbon stocks and tree diversity: a case study of the Montérégie, Québec
Bibliographic record
Abstract
Habitat fragmentation is ubiquitous in temperate forests, and affects ecosystem functions and services through decreased area, increased isolation, and greater exposure to forest edges. While fragmentation has been extensively studied, the effect of fragmentation on the relationship between biodiversity and ecosystem services is not well documented or understood. Alterations to forest fragment size and connectivity are increasingly linked to changes in ecosystem function via changes to dispersal patterns and other spatial processes. However, whether or not these functional implications of fragmentation extend to carbon storage, and thus the ability of a forested landscape to regulate climate, is uncertain, especially in temperate systems. In this thesis, I investigated the effects of forest fragment size, isolation, and management intensity on the relationship between aboveground carbon (AGC) stocks and tree biodiversity in 24 small forest fragments in the Montérégie, QC. I also examined whether forest edge effects influenced AGC stocks and tree species composition. I found that forest fragments in the Montérégie differed with respect to AGC stocks, and that these differences were mediated by functional diversity, forest management, and connectivity. Unmanaged fragments stored less carbon on average than managed, but demonstrated a significant positive relationship between functional diversity and AGC stocks, with the slope of the relationship significantly greater in connected fragments than isolated. Small (10ha) fragments performed on par with their larger (100ha) counterparts. Managed stands exhibited a negative relationship between functional diversity and AGC stocks, demonstrating that anthropogenic influence can alter the link between biodiversity and AGC stocks in forested systems. Contrary to observations in tropical forests, proximity to the forest edge did not alter AGC stocks; rather, AGC stocks remained constant across a 100m edge to interior gradient in forest fragments of all types, despite changes in tree community composition and relative abundance consistent with expectations of forest edge effects. My results suggest that taking into account aspects of forest heterogeneity, such as structural connectivity, and gradients in diversity and management intensity may increase accuracy in estimating landscape level carbon stocks. Additionally, these results have implications for conservation. Like many other peri-urban, agricultural areas in North America, the Montérégie contains a high number of small forest fragments, likely to increase as fragmentation becomes more prevalent with development. The ecological importance of small fragments is often questioned. Here, I show that small forest fragments are likely to demonstrate "win-win" conservation scenarios with respect to AGC stocks and tree biodiversity, and that AGC stocks are constant across even very small and irregularly shaped fragments. If we consider the number of small forest fragments throughout this region, combined with their contributions to regional biodiversity and service provision, it is clear that the continued loss of small forest fragments in the Montérégie would be to the detriment of conservation efforts.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".