Metoder för att beskriva kumulativa effekter med avseende på biologisk mångfald och vägar
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Cumulative effects are seldom treated in Swedish Environmental Impact Assessments (EIA). This report treats these questions and which procedures and methods that can be used when assessing cumulative effects in EIA. \n \nThis report is a literature study where also a case study is a part. The case study shows how existing methods for cumulative effects can be used in practice. The report is concentrated on biology and treats cumulative effects on premises of biodiversity and roads. \n \nCumulative effects include both direct and indirect effects. Beyond the planned project also past, present and foreseeable future action shall be included. All impacts contributing to the effects on the environment shall be included, no matter who causes them. Besides cumulative effects from many different actions they can also be caused of many different environmental effects from one single project. One common procedure to describe cumulative effects is to make scoping, describe the affected environment and to establish the environmental consequences from cumulative effects. Methods that can be used in the procedure are questionnaires, interviews, panels, expert opinions, consultations, checklists, network- and system diagrams, modeling and trend analysis. These are often used in traditional EIA too. Methods that are more directly adapted to cumulative effects are overlay maps, carrying capacity, threshold analysis and ecosystem analysis. Which methods that should be used in the different steps of the procedure is better to decide during the process depending on the nature of the project, the natural resources and the effects. \n \nIn the two Swedish road EIAs, that have been examined, cumulative effects are not described even if it is most probable that they will occur. This is in conflict with the EU-directive 97/11/EC. The EIA:s could also have contained one part with cumulative effects where natural paths and reduced biotop are concerned. The two Canadian cumulative EIAs, that have been examined, handle cumulative effects very detailed. They show that good routines about describing cumulative effects exist in Canada. \n \nA case study has been made to test, in practice, the procedure and the methods that exist. It is located in an area east of the community Björklinge in Uppland. Five scenarios have been developed for the area. 1: A new E4 and a new road 700 are built. The other scenarios as 1 but: 2: the wildlife tunnel does not work, 3: one additional highway is built, 4: the moose population is wanted to increase, 5: moose hunting stopped. Methods that where used in the first step were expert opinion, interview (with hunter) and trend analysis. In the middle part trendanalysis and in the last part network diagram, carrying capacity and expert opinion (wildlife researcher) was used. Cumulative effects could be identified in scenario 3, 4 and 5. Scenario 1 is the most realistic one. \n \nIn Sweden there are political goals saying that both traffic and environment should be promoted. To reach these goals it is important to describe effects in an entirety perspective. In other countries there are experiences of how to describe cumulative effects. This means that it is not necessary to develop new procedures or methods, the same can be used in Sweden too. \n \nTo ensure good quality in the process of road planning, cumulative effects should be treated in both pilot study, road investigation and working plan. Only significant cumulative effects should be estimated. In such cases the county administration board should decide the project as a project that might give significant environmental effects, even if the project itself does not give significant effects.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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 it