Análise da estrutura vertical do dossel em fragmentos de florestas nativas e plantações de Eucalyptus para detectar efeitos de borda
Bibliographic record
Abstract
There is a range of detailed research on edge effects using field data at local scales. However, the scientific literature lacks studies that aim to understand its characteristics in forest fragments using larger scales. Also, few works have considered the influences that each fragment of the landscape imposes on its neighbour. Since biological processes linked to fragmentation and degradation commonly start at edges and influence the dynamics of forest communities, studies on edge effects are crucial for the development of management and conservation plans. Lidar technologies have been used in several studies on forest structure, but few have investigated edge effects. This dissertation presents two distinct applications of lidar for studying anthropogenic-caused edges in different scenarios and ecosystems. In the first study, edge effects in commercial Eucalyptus plantations and fragments of the Atlantic Forest, located in the State of São Paulo, were evaluated by quantifying the differences in height and understory density in the edge vegetation vs core. We also sought to understand the influences that each type of adjacent fragment (Eucalyptus, native forest or pasture) imposes on the neighbouring vegetation. Edge effects, regarding height and understory density, on fragments of native vegetation adjacent to Eucalyptus plantations and vice-versa were more attenuated than nearby pastures. The results indicated that the protection of native forests in silviculture areas besides favouring the maintenance of local ecosystem services (provision and maintenance of water flow, diversity of flora and fauna species, natural pest control, etc.) could help maintain the homogeneity of the stands due to their ability to minimise edge effects. This protection could favour the occurrence of border Eucalyptus more similar to the ones in the core. In the second study, edge effects caused by seismic lines, i.e. corridors cut through the forest during the process of exploration of gas and oil, in areas of Boreal Forest in the central region of Alberta is addressed. Besides quantifying the effects of distance from seismic lines over height and fractional cover on the neighbouring vegetation, the interactions between these variables and primary vegetation growth factors related to the topographic position, incident radiation and surface geology were evaluated. The results showed that significant changes in vegetation structure adjacent to forest edge occur close to seismic lines, including reduced tree height and cover. Random Forest analyses revealed that the distance from the seismic line, incident radiation and surface water accumulation potential (inferred from the topographic position index) are the most critical variables for height and fractional cover prediction. Overall, lidar proved to be a robust tool for assessing the spatial and ecological dimensions of edge effects in different scenarios. With this in mind, management and conservation strategies for fragmented areas could benefit from this technology to reduce the impact from edge effects on ecosystems.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".