Moving from Landscape Connectivity Theory to Land Use Planning Practice: Ontario as a Case Study
Bibliographic record
Abstract
Landscape connectivity is a concept that refers to a landscape's structural and functional continuity, allowing for the flow of water, nutrients, energy, organisms, genes, and disturbances at many spatial and temporal scales. The loss of landscape connectivity leads to ecosystem fragmentation, which in turn contributes to a decline in biodiversity and threatens many species around the world. The importance of maintaining landscape connectivity is becoming recognized as a fundamental principle in land use planning. \nThe purpose of this dissertation is to examine how the theory of landscape connectivity has been applied in Ontario's land use planning policy and practice between 1970 and 2008. This includes evaluating the degree to which theory has been applied to practice in landscape connectivity planning. In addition, the work investigates the processes that facilitated the movement from theory to practice in planning for landscape connectivity. Broadly framed within the theories of conservation biology, the research approach is qualitative and the research design includes a literature review, content analysis, and case study research. \nThis research found that there has been an evolution of theory to practice in planning for landscape connectivity in Ontario between 1970 and 2008. The introduction of conservation biology principles created a growing public awareness, which contributed to rising pressure on the Government of Ontario to reform its land use planning policies. The theory of landscape connectivity is included in key land use planning legislation and policies and is now an accepted part of planning for natural heritage in the province. The Ontario Municipal Board has regard for landscape connectivity as a legitimate planning concern. In the majority of cases in the last decade in which landscape connectivity was identified as a deciding factor, the Ontario Municipal Board ruled in favour of protecting landscape connectivity. Planners in Ontario are expected to plan for landscape connectivity, but Ontario’s planning law and policy does not provide strong direction to planners on the issue of landscape connectivity. Recommendations for the Government of Ontario, based on the research findings, include planning for landscape connectivity at a provincial scale, creating a guidance document specifically for landscape connectivity and revising the Provincial Policy Statement.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.026 | 0.009 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".