| Literature DB >> 28630904 |
Marie Fujitani1,2, Andrew McFall1, Christoph Randler3, Robert Arlinghaus1,4.
Abstract
Resolving uncertainties in managed social-ecological systems requires adaptive experimentation at whole-ecosystem levels. However, whether participatory adaptive management fosters ecological understanding among stakeholders beyond the sphere of science is unknown. We experimentally involved members of German angling clubs (n = 181 in workshops, n = 2483 in total) engaged in self-governance of freshwater fisheries resources in a large-scale ecological experiment of active adaptive management of fish stocking, which constitutes a controversial management practice for biodiversity and ecosystem functioning when conducted inappropriately. The collaborative ecological experiments spanned several years and manipulated fish densities in 24 lakes with two species. In parallel, we experimentally compared changes in ecological knowledge and antecedents of proenvironmental behavior in stakeholders and managers who were members of a participatory adaptive management treatment group, with those receiving only a standard lecture, relative to placebo controls. Using a within-subjects pretest-posttest control design, changes in ecological knowledge, environmental beliefs, attitudes, norms, and behavioral intentions were evaluated. Participants in adaptive management retained more knowledge of ecological topics after a period of 8 months compared to those receiving a standard lecture, both relative to controls. Involvement in adaptive management was also the only treatment that altered personal norms and beliefs related to stocking. Critically, only the stakeholders who participated in adaptive management reduced their behavioral intentions to engage in fish stocking in the future. Adaptive management is essential for robust ecological knowledge, and we show that involving stakeholders in adaptive management experiments is a powerful tool to enhance ecological literacy and build environmental capacity to move toward sustainability.Entities:
Keywords: evidence-based conservation; fisheries management; knowledge co-production; natural resources; participation; science communication; science education
Mesh:
Year: 2017 PMID: 28630904 PMCID: PMC5470829 DOI: 10.1126/sciadv.1602516
Source DB: PubMed Journal: Sci Adv ISSN: 2375-2548 Impact factor: 14.136
Fig. 1Cognitive hierarchy including the theorized influence of newly acquired factual scientific knowledge on behavioral precursors.
Fig. 2Experimental design.
AAM, active adaptive management.
Fig. 3Treatment effect coefficients relative to the placebo control lecture group.
Treatment effect coefficients with 95% confidence intervals (y axis) showing immediate effects of the stocking lecture versus the control group (gray) and long-term retention effects (8 months after the end of the respective treatment; black) on knowledge and cognitions for the lecture-only and lecture plus participatory active adaptive management treatments versus the control lecture group. Confidence intervals that do not overlap zero indicate statistically significant changes in knowledge and cognitions relative to the control group; treatment effect coefficients not significantly different from zero at the P < 0.05 level are shown in white.
Fig. 4Changes in behavioral intentions.
Plots of coefficients and 95% confidence intervals (x axis) from a linear mixed model comparing changes in behavioral intentions of the stocking lecture and active adaptive management groups versus the control lecture group. Black circles are treatment effects significantly different from zero in linear mixed model analyses that are also significant in linear probability model robustness checks. Gray circles are coefficients significantly different from zero in the linear mixed model but not in the robustness check. Confidence intervals that do not overlap zero indicate statistically significant changes in behavioral intention relative to the control; treatment effect coefficients not significantly different from zero for any of the models at the P < 0.05 level are shown in white.