Developing a system model for articulating the social-ecological impacts of species reintroduction
Bibliographic record
Abstract
Reintroducing locally extinct/extirpated species has been considered as an approach for restoring ecosystems. Although such projects share the same goals of rebuilding previously affected ecosystems, the overall impacts that such reintroductions generate on both ecosystems and human society, i.e., on the social-ecological system, are difficult to measure. We propose a system dynamics approach, a platform on which both natural and social scientists could collaborate to identify the social-ecological impacts of species reintroduction as well as factors that affect such decision making. We use cases in Japan to demonstrate the potential applicability of system dynamics in terms of (1) understanding the impacts of a previously reintroduced species, the Oriental Stork (Ciconia boyciana), and (2) predicting the impacts of reintroduction of wolves (Canis lupus). We present a causal loop diagram of the social and ecological effects of Oriental Stork reintroduction, and we discuss how the relationships between factors could be articulated based on empirical data and ongoing projects in Japan. The model demonstrates how local residents began to appreciate the rich biodiversity, including the Oriental Stork, following its reintroduction, and how public support toward such reintroduction enhanced further projects to reintroduce these species in different parts of Japan. A similar diagram, created to illustrate the social and ecological effects of the potential reintroduction of wolves to Japan, demonstrates how social factors such as environmental education and public attitudes could affect decision making as well as ecological factors such as predator-prey dynamics and overall biodiversity. Further, human-wolf conflicts could negatively affect the overall loop. Creating causal loop diagrams can help managers and stakeholders understand that species reintroduction projects need to be considered via an interdisciplinary approach. The models illustrate that these problems are dynamic and that the factors affecting or affected by such projects change over time, implying the importance of both the spatial and temporal scales in managing reintroduction projects.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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 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".