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      Spatial Overlap between Environmental Policy Instruments and Areas of High Conservation Value in Forest

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          In order to safeguard biodiversity in forest we need to know how forest policy instruments work. Here we use a nationwide network of 9400 plots in productive forest to analyze to what extent large-scale policy instruments, individually and together, target forest of high conservation value in Norway. We studied both instruments working through direct regulation; Strict Protection and Landscape Protection, and instruments working through management planning and voluntary schemes of forest certification; Wilderness Area and Mountain Forest. As forest of high conservation value (HCV-forest) we considered the extent of 12 Biodiversity Habitats and the extent of Old-Age Forest. We found that 22% of productive forest area contained Biodiversity Habitats. More than 70% of this area was not covered by any large-scale instruments. Mountain Forest covered 23%, while Strict Protection and Wilderness both covered 5% of the Biodiversity Habitat area. A total of 9% of productive forest area contained Old-Age Forest, and the relative coverage of the four instruments was similar as for Biodiversity Habitats. For all instruments, except Landscape Protection, the targeted areas contained significantly higher proportions of HCV-forest than areas not targeted by these instruments. Areas targeted by Strict Protection had higher proportions of HCV-forest than areas targeted by other instruments, except for areas targeted by Wilderness Area which showed similar proportions of Biodiversity Habitats. There was a substantial amount of spatial overlap between the policy tools, but no incremental conservation effect of overlapping instruments in terms of contributing to higher percentages of targeted HCV-forest. Our results reveal that although the current policy mix has an above average representation of forest of high conservation value, the targeting efficiency in terms of area overlap is limited. There is a need to improve forest conservation and a potential to cover this need by better targeting high conservation value areas.

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          Measuring the effectiveness of protected area networks in reducing deforestation.

          Global efforts to reduce tropical deforestation rely heavily on the establishment of protected areas. Measuring the effectiveness of these areas is difficult because the amount of deforestation that would have occurred in the absence of legal protection cannot be directly observed. Conventional methods of evaluating the effectiveness of protected areas can be biased because protection is not randomly assigned and because protection can induce deforestation spillovers (displacement) to neighboring forests. We demonstrate that estimates of effectiveness can be substantially improved by controlling for biases along dimensions that are observable, measuring spatial spillovers, and testing the sensitivity of estimates to potential hidden biases. We apply matching methods to evaluate the impact on deforestation of Costa Rica's renowned protected-area system between 1960 and 1997. We find that protection reduced deforestation: approximately 10% of the protected forests would have been deforested had they not been protected. Conventional approaches to evaluating conservation impact, which fail to control for observable covariates correlated with both protection and deforestation, substantially overestimate avoided deforestation (by over 65%, based on our estimates). We also find that deforestation spillovers from protected to unprotected forests are negligible. Our conclusions are robust to potential hidden bias, as well as to changes in modeling assumptions. Our results show that, with appropriate empirical methods, conservation scientists and policy makers can better understand the relationships between human and natural systems and can use this to guide their attempts to protect critical ecosystem services.
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            Designing large-scale conservation corridors for pattern and process.

            A major challenge for conservation assessments is to identify priority areas that incorporate biological patterns and processes. Because large-scale processes are mostly oriented along environmental gradients, we propose to accommodate them by designing regional-scale corridors to capture these gradients. Based on systematic conservation planning principles such as representation and persistence, we identified large tracts of untransformed land (i.e., conservation corridors) for conservation that would achieve biodiversity targets for pattern and process in the Subtropical Thicket Biome of South Africa. We combined least-cost path analysis with a target-driven algorithm to identify the best option for capturing key environmental gradients while considering biodiversity targets and conservation opportunities and constraints. We identified seven conservation corridors on the basis of subtropical thicket representation, habitat transformation and degradation, wildlife suitability, irreplaceability of vegetation types, protected area networks, and future land-use pressures. These conservation corridors covered 21.1% of the planning region (ranging from 600 to 5200 km2) and successfully achieved targets for biological processes and to a lesser extent for vegetation types. The corridors we identified are intended to promote the persistence of ecological processes (gradients and fixed processes) and fulfill half of the biodiversity pattern target. We compared the conservation corridors with a simplified corridor design consisting of a fixed-width buffer along major rivers. Conservation corridors outperformed river buffers in seven out of eight criteria. Our corridor design can provide a tool for quantifying trade-offs between various criteria (biodiversity pattern and process, implementation constraints and opportunities). A land-use management model was developed to facilitate implementation of conservation actions within these corridors.
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              The Nature Index: A General Framework for Synthesizing Knowledge on the State of Biodiversity

              The magnitude and urgency of the biodiversity crisis is widely recognized within scientific and political organizations. However, a lack of integrated measures for biodiversity has greatly constrained the national and international response to the biodiversity crisis. Thus, integrated biodiversity indexes will greatly facilitate information transfer from science toward other areas of human society. The Nature Index framework samples scientific information on biodiversity from a variety of sources, synthesizes this information, and then transmits it in a simplified form to environmental managers, policymakers, and the public. The Nature Index optimizes information use by incorporating expert judgment, monitoring-based estimates, and model-based estimates. The index relies on a network of scientific experts, each of whom is responsible for one or more biodiversity indicators. The resulting set of indicators is supposed to represent the best available knowledge on the state of biodiversity and ecosystems in any given area. The value of each indicator is scaled relative to a reference state, i.e., a predicted value assessed by each expert for a hypothetical undisturbed or sustainably managed ecosystem. Scaled indicator values can be aggregated or disaggregated over different axes representing spatiotemporal dimensions or thematic groups. A range of scaling models can be applied to allow for different ways of interpreting the reference states, e.g., optimal situations or minimum sustainable levels. Statistical testing for differences in space or time can be implemented using Monte-Carlo simulations. This study presents the Nature Index framework and details its implementation in Norway. The results suggest that the framework is a functional, efficient, and pragmatic approach for gathering and synthesizing scientific knowledge on the state of biodiversity in any marine or terrestrial ecosystem and has general applicability worldwide.

                Author and article information

                Role: Editor
                PLoS One
                PLoS ONE
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                11 December 2014
                : 9
                : 12
                [1 ]Norwegian University of Life Sciences, Department of Ecology and Natural Resource Management, Aas, Norway
                [2 ]Norwegian Institute for Nature Research (NINA), Oslo, Norway
                [3 ]Norwegian Forest and Landscape Institute (NFLI), Ås, Norway
                [4 ]Norwegian Institute for Nature Research, Trondheim, Norway
                University of Waikato (National Institute of Water and Atmospheric Research), New Zealand
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Conceived and designed the experiments: GS DNB AST GMR. Analyzed the data: AST GS. Contributed reagents/materials/analysis tools: GS. Wrote the paper: AST GS GMR DNB.


                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                Page count
                Pages: 18
                The POLICYMIX project ( has received funding from the European Union's Seventh Programme for research, technological development and demonstration under grant agreement No. 244065. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Research Article
                Biology and Life Sciences
                Agricultural Methods
                Sustainable Agriculture
                Ecological Economics
                Spatial and Landscape Ecology
                Ecology and Environmental Sciences
                Conservation Science
                Environmental Economics
                Sustainability Science
                Terrestrial Environments
                Science Policy
                Science Policy and Economics
                Custom metadata
                The authors confirm that all data underlying the findings are fully available without restriction. All data are available from The Norwegian Forest and Landscape Institute, accessible at and by contacting the institute through Gunnhild Søgaard ( GUS@ ).



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