BIOLOGICAL INVASIONS: RECOMMENDATIONS FOR U.S. POLICY AND MANAGEMENT
Bibliographic record
Abstract
The Ecological Society of America has evaluated current U.S. national policies and practices on biological invasions in light of current scientific knowledge. Invasions by harmful nonnative species are increasing in number and area affected; the damages to ecosystems, economic activity, and human welfare are accumulating. Without improved strategies based on recent scientific advances and increased investments to counter invasions, harm from invasive species is likely to accelerate. Federal leadership, with the cooperation of state and local governments, is required to increase the effectiveness of prevention of invasions, detect and respond quickly to new potentially harmful invasions, control and slow the spread of existing invasions, and provide a national center to ensure that these efforts are coordinated and cost effective. Specifically, the Ecological Society of America recommends that the federal government take the following six actions: (1) Use new information and practices to better manage commercial and other pathways to reduce the transport and release of potentially harmful species; (2) Adopt more quantitative procedures for risk analysis and apply them to every species proposed for importation into the country; (3) Use new cost-effective diagnostic technologies to increase active surveillance and sharing of information about invasive species so that responses to new invasions can be more rapid and effective; (4) Create new legal authority and provide emergency funding to support rapid responses to emerging invasions; (5) Provide funding and incentives for cost-effective programs to slow the spread of existing invasive species in order to protect still uninvaded ecosystems, social and industrial infrastructure, and human welfare; and (6) Establish a National Center for Invasive Species Management (under the existing National Invasive Species Council) to coordinate and lead improvements in federal, state, and international policies on invasive species. Recent scientific and technical advances provide a sound basis for more cost-effective national responses to invasive species. Greater investments in improved technology and management practices would be more than repaid by reduced damages from current and future invasive species. The Ecological Society of America is committed to assist all levels of government and provide scientific advice to improve all aspects of invasive-species management.
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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 | 0.015 | 0.027 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.010 | 0.010 |
| Open science | 0.008 | 0.005 |
| Research integrity | 0.030 | 0.014 |
| Insufficient payload (model declined to judge) | 0.052 | 0.037 |
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".