Restoration of impaired ecosystems: An ounce of prevention or a pound of cure? Introduction, overview, and key messages from a SETAC-SER workshop
Bibliographic record
Abstract
Abstract A workshop on Restoration of Impaired Ecosystems was held in Jackson, Wyoming, in June 2014. Experts from Australia, Canada, Mexico, the United Kingdom, and the United States in ecotoxicology, restoration, and related fields from both the Society of Environmental Toxicology and Chemistry and the Society for Ecological Restoration convened to advance the practice of restoring ecosystems that have been contaminated or impaired from industrial activities. The overall goal of this workshop was to provide a forum for ecotoxicologists and restoration ecologists to define the best scientific practices to achieve ecological restoration while addressing contaminant concerns. To meet this goal, participants addressed 5 areas: 1) links between ecological risk assessment and ecological restoration, 2) restoration goals, 3) restoration design, 4) monitoring for restoration effectiveness and 5) recognizing opportunities and challenges. Definitions are provided to establish a common language across the varied disciplines. The current practice for addressing restoration of impaired ecosystems tends to be done sequentially to remediate contaminants, then to restore ecological structure and function. A better approach would anticipate or plan for restoration throughout the process. By bringing goals to the forefront, we may avoid intrusive remediation activities that close off options for the desired restoration. Participants realized that perceived limitations in the site assessment process hinder consideration of restoration goals; contaminant presence will influence restoration goal choices; social, economic, and cultural concerns can factor into goal setting; restoration options and design should be considered early during site assessment and management; restoration of both structure and function is encouraged; creative solutions can overcome limitations; a regional focus is imperative; monitoring must occur throughout the restoration process; and reciprocal transfer of knowledge is needed among theorists, practitioners, and stakeholders and among varied disciplines. Integr Environ Assess Manag 2016;12:247–252. © 2015 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals, Inc. on behalf of SETAC Key Points This work summarizes key messages from a workshop supported by SETAC and the Society of Ecological Restoration. Restoration of contaminated sites has traditionally been a compartmentalized and sequential process, we propose a shift to a restoration continuum. This continuum involves more reciprocal transfer of knowledge among varied disciplines, bringing restoration planning and goals to the forefront during assessments and remediation, conducting monitoring throughout the process, and taking a more regional focus during the restoration. Social, economic and cultural concerns must be factored in to the restoration goalsetting process and unique goals may be needed for contaminated 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".