Using a social–ecological framework to inform the implementation of conservation plans

One of the key determinants of success in biodiversity conservation is how well conservation planning decisions account for the social system in which actions are to be implemented. Understanding elements of how the social and ecological systems interact can help identify opportunities for implementation. Utilizing data from a large‐scale conservation initiative in southwestern of Australia, we explored how a social–ecological system framework can be applied to identify how social and ecological factors interact to influence the opportunities for conservation. Using data from semistructured interviews, an online survey, and publicly available data, we developed a conceptual model of the social–ecological system associated with the conservation of the Fitz‐Stirling region. We used this model to identify the relevant variables (remnants of vegetation, stakeholder presence, collaboration between stakeholders, and their scale of management) that affect the implementation of conservation actions in the region. We combined measures for these variables to ascertain how areas associated with different levels of ecological importance coincided with areas associated with different levels of stakeholder presence, stakeholder collaboration, and scales of management. We identified areas that could benefit from different implementation strategies, from those suitable for immediate conservation action to areas requiring implementation over the long term to increase on‐the‐ground capacity and identify mechanisms to incentivize implementation. The application of a social–ecological framework can help conservation planners and practitioners facilitate the integration of ecological and social data to inform the translation of priorities for action into implementation strategies that account for the complexities of conservation problems in a focused way.     

Mapping Human and Social Dimensions of Conservation Opportunity for the Scheduling of Conservation Action on Private Land

Abstract Spatial prioritization techniques are applied in conservation‐planning initiatives to allocate conservation resources. Although typically they are based on ecological data (e.g., species, habitats, ecological processes), increasingly they also include nonecological data, mostly on the vulnerability of valued features and economic costs of implementation. Nevertheless, the effectiveness of conservation actions implemented through conservation‐planning initiatives is a function of the human and social dimensions of social‐ecological systems, such as stakeholders’ willingness and capacity to participate. We assessed human and social factors hypothesized to define opportunities for implementing effective conservation action by individual land managers (those responsible for making day‐to‐day decisions on land use) and mapped these to schedule implementation of a private land conservation program. We surveyed 48 land managers who owned 301 land parcels in the Makana Municipality of the Eastern Cape province in South Africa. Psychometric statistical and cluster analyses were applied to the interview data so as to map human and social factors of conservation opportunity across a landscape of regional conservation importance. Four groups of landowners were identified, in rank order, for a phased implementation process. Furthermore, using psychometric statistical techniques, we reduced the number of interview questions from 165 to 45, which is a preliminary step toward developing surrogates for human and social factors that can be developed rapidly and complemented with measures of conservation value, vulnerability, and economic cost to more‐effectively schedule conservation actions. This work provides conservation and land management professionals direction on where and how implementation of local‐scale conservation should be undertaken to ensure it is feasible.     

Putting People on the Map through an Approach That Integrates Social Data in Conservation Planning

Conservation planning is integral to strategic and effective operations of conservation organizations. Drawing upon biological sciences, conservation planning has historically made limited use of social data. We offer an approach for integrating data on social well‐being into conservation planning that captures and places into context the spatial patterns and trends in human needs and capacities. This hierarchical approach provides a nested framework for characterizing and mapping data on social well‐being in 5 domains: economic well‐being, health, political empowerment, education, and culture. These 5 domains each have multiple attributes; each attribute may be characterized by one or more indicators. Through existing or novel data that display spatial and temporal heterogeneity in social well‐being, conservation scientists, planners, and decision makers may measure, benchmark, map, and integrate these data within conservation planning processes. Selecting indicators and integrating these data into conservation planning is an iterative, participatory process tailored to the local context and planning goals. Social well‐being data complement biophysical and threat‐oriented social data within conservation planning processes to inform decisions regarding where and how to conserve biodiversity, provide a structure for exploring socioecological relationships, and to foster adaptive management. Building upon existing conservation planning methods and insights from multiple disciplines, this approach to putting people on the map can readily merge with current planning practices to facilitate more rigorous decision making. Poner a la Gente en el Mapa por Medio de una Estrategia que Integra Información Social en la Planeación de la Conservación     

Understanding the effects of different social data on selecting priority conservation areas

Conservation success is contingent on assessing social and environmental factors so that cost‐effective implementation of strategies and actions can be placed in a broad social–ecological context. Until now, the focus has been on how to include spatially explicit social data in conservation planning, whereas the value of different kinds of social data has received limited attention. In a regional systematic conservation planning case study in Australia, we examined the spatial concurrence of a range of spatially explicit social values and land‐use preferences collected using a public participation geographic information system and biological data. We used Zonation to integrate the social data with the biological data in a series of spatial‐prioritization scenarios to determine the effect of the different types of social data on spatial prioritization compared with biological data alone. The type of social data (i.e., conservation opportunities or constraints) significantly affected spatial prioritization outcomes. The integration of social values and land‐use preferences under different scenarios was highly variable and generated spatial prioritizations 1.2–51% different from those based on biological data alone. The inclusion of conservation‐compatible values and preferences added relatively few new areas to conservation priorities, whereas including noncompatible economic values and development preferences as costs significantly changed conservation priority areas (48.2% and 47.4%, respectively). Based on our results, a multifaceted conservation prioritization approach that combines spatially explicit social data with biological data can help conservation planners identify the type of social data to collect for more effective and feasible conservation actions.     

Conservation Planning as a Transdisciplinary Process

Abstract: Despite substantial growth in the field of conservation planning, the speed and success with which conservation plans are converted into conservation action remains limited. This gap between science and action extends beyond conservation planning into many other applied sciences and has been linked to complexity of current societal problems, compartmentalization of knowledge and management sectors, and limited collaboration between scientists and decision makers. Transdisciplinary approaches have been proposed as a possible way to address these challenges and to bridge the gap between science and action. These approaches move beyond the bridging of disciplines to an approach in which science becomes a social process resolving problems through the participation and mutual learning of stakeholders. We explored the principles of transdisciplinarity, in light of our experiences as conservation‐planning researchers working in South Africa, to better understand what is required to make conservation planning transdisciplinary and therefore more effective. Using the transdisciplinary hierarchy of knowledge (empirical, pragmatic, normative, and purposive), we found that conservation planning has succeeded in integrating many empirical disciplines into the pragmatic stakeholder‐engaged process of strategy development and implementation. Nevertheless, challenges remain in engagement of the social sciences and in understanding the social context of implementation. Farther up this knowledge hierarchy, at the normative and purposive levels, we found that a lack of integrated land‐use planning and policies (normative) and the dominant effect of national values (purposive) that prioritize growth and development limit the effectiveness and relevance of conservation plans. The transdisciplinary hierarchy of knowledge highlighted that we need to move beyond bridging the empirical and pragmatic disciplines into the complex normative world of laws, policies, and planning and become engaged in the purposive processes of decision making, behavior change, and value transfer. Although there are indications of progress in this direction, working at the normative and purposive levels requires time, leadership, resources, skills that are absent in conservation training and practice, and new forms of recognition in systems of scientific reward and funding.     

Conservation Success as a Function of Good Alignment of Social and Ecological Structures and Processes

How to create and adjust governing institutions so that they align (fit) with complex ecosystem processes and structures across scales is an issue of increasing concern in conservation. It is argued that lack of such social‐ecological fit makes governance and conservation difficult, yet progress in explicitly defining and rigorously testing what constitutes a good fit has been limited. We used a novel modeling approach and data from case studies of fishery and forest conservation to empirically test presumed relationships between conservation outcomes and certain patterns of alignment of social‐ecological interdependences. Our approach made it possible to analyze conservation outcome on a systems level while also providing information on how individual actors are positioned in the complex web of social‐ecological interdependencies. We found that when actors who shared resources were also socially linked, conservation at the level of the whole social‐ecological system was positively affected. When the scales at which individual actors used resources and the scale at which ecological resources were interconnected to other ecological resources were aligned through tightened feedback loops, conservation outcome was better than when they were not aligned. The analysis of individual actors’ positions in the web of social‐ecological interdependencies was helpful in understanding why a system has a certain level of social‐ecological fit. Results of analysis of positions showed that different actors contributed in very different ways to achieve a certain fit and revealed some underlying difference between the actors, for example in terms of actors’ varying rights to access and use different ecological resources. El Éxito de la Conservación como Función de una Buena Alineación de Estructuras y Procesos Sociales y Ecológicos     

Adaptive social impact management for conservation and environmental management

Concerns about the social consequences of conservation have spurred increased attention the monitoring and evaluation of the social impacts of conservation projects. This has resulted in a growing body of research that demonstrates how conservation can produce both positive and negative social, economic, cultural, health, and governance consequences for local communities. Yet, the results of social monitoring efforts are seldom applied to adaptively manage conservation projects. Greater attention is needed to incorporating the results of social impact assessments in long‐term conservation management to minimize negative social consequences and maximize social benefits. We bring together insights from social impact assessment, adaptive management, social learning, knowledge coproduction, cross‐scale governance, and environmental planning to propose a definition and framework for adaptive social impact management (ASIM). We define ASIM as the cyclical process of monitoring and adaptively managing social impacts over the life‐span of an initiative through the 4 stages of profiling, learning, planning, and implementing. We outline 14 steps associated with the 4 stages of the ASIM cycle and provide guidance and potential methods for social‐indicator development, predictive assessments of social impacts, monitoring and evaluation, communication of results, and identification and prioritization of management responses. Successful ASIM will be aided by engaging with best practices – including local engagement and collaboration in the process, transparent communication of results to stakeholders, collective deliberation on and choice of interventions, documentation of shared learning at the site level, and the scaling up of insights to inform higher‐level conservation policies‐to increase accountability, trust, and perceived legitimacy among stakeholders. The ASIM process is broadly applicable to conservation, environmental management, and development initiatives at various scales and in different contexts.     

Mainstreaming the social sciences in conservation

Despite broad recognition of the value of social sciences and increasingly vocal calls for better engagement with the human element of conservation, the conservation social sciences remain misunderstood and underutilized in practice. The conservation social sciences can provide unique and important contributions to society's understanding of the relationships between humans and nature and to improving conservation practice and outcomes. There are 4 barriers—ideological, institutional, knowledge, and capacity—to meaningful integration of the social sciences into conservation. We provide practical guidance on overcoming these barriers to mainstream the social sciences in conservation science, practice, and policy. Broadly, we recommend fostering knowledge on the scope and contributions of the social sciences to conservation, including social scientists from the inception of interdisciplinary research projects, incorporating social science research and insights during all stages of conservation planning and implementation, building social science capacity at all scales in conservation organizations and agencies, and promoting engagement with the social sciences in and through global conservation policy‐influencing organizations. Conservation social scientists, too, need to be willing to engage with natural science knowledge and to communicate insights and recommendations clearly. We urge the conservation community to move beyond superficial engagement with the conservation social sciences. A more inclusive and integrative conservation science—one that includes the natural and social sciences—will enable more ecologically effective and socially just conservation. Better collaboration among social scientists, natural scientists, practitioners, and policy makers will facilitate a renewed and more robust conservation. Mainstreaming the conservation social sciences will facilitate the uptake of the full range of insights and contributions from these fields into conservation policy and practice.     

Investment and the Policy Process in Conservation Monitoring

Despite decades of discussion and implementation, conservation monitoring remains a challenge. Many current solutions in the literature focus on improving the science or making more structured decisions. These insights are important but incomplete in accounting for the politics and economics of the conservation decisions informed by monitoring. Our novel depiction of the monitoring enterprise unifies insights from multiple disciplines (conservation, operations research, economics, and policy) and highlights many underappreciated factors that affect the expected benefits of monitoring. For example, there must be a strong link between the specific needs of decision makers and information gathering. Furthermore, the involvement of stakeholders other than scientists and research managers means that new information may not be interpreted and acted upon as expected. While answering calls for sharply delineated objectives will clearly add focus to monitoring efforts, for practical reasons, high‐level goals may purposefully be left vague, to facilitate other necessary steps in the policy process. We use the expanded depiction of the monitoring process to highlight problems of cooperation and conflict. We critique calls to invest in monitoring for the greater good by arguing that incentives are typically lacking. Although the benefits of learning accrued within a project (e.g., improving management) provide incentives for investing in some monitoring, it is unrealistic, in general, to expect managers to add potentially costly measures to generate shared benefits. In the traditional linear model of the role of science in policy decisions, monitoring reduces uncertainty and decision makers are rational, unbiased consumers of the science. However, conservation actions increasingly involve social conflict. Drawing insights from political science, we argue that in high‐conflict situations, it is necessary to address the conflict prior to monitoring. Las Inversiones y el Proceso de Políticas en el Monitoreo de la Conservación Sanchirico et al.     

Evaluating Perceived Benefits of Ecoregional Assessments

Abstract: The outcomes of systematic conservation planning (process of assessing, implementing, and managing conservation areas) are rarely reported or measured formally. A lack of consistent or rigorous evaluation in conservation planning has fueled debate about the extent to which conservation assessment (identification, design, and prioritization of potential conservation areas) ultimately influences actions on the ground. We interviewed staff members of a nongovernmental organization, who were involved in 5 ecoregional assessments across North and South America and the Asia‐Pacific region. We conducted 17 semistructured interviews with open and closed questions about the perceived purpose, outputs, and outcomes of the ecoregional assessments in which respondents were involved. Using qualitative data collected from those interviews, we investigated the types and frequency of benefits perceived to have emerged from the ecoregional assessments and explored factors that might facilitate or constrain the flow of benefits. Some benefits reflected the intended purpose of ecoregional assessments. Other benefits included improvements in social interactions, attitudes, and institutional knowledge. Our results suggest the latter types of benefits enable ultimate benefits of assessments, such as guiding investments by institutional partners. Our results also showed a clear divergence between the respondents’ expectations and perceived outcomes of implementation of conservation actions arising from ecoregional assessments. Our findings suggest the need for both a broader perspective on the contribution of assessments to planning goals and further evaluation of conservation assessments.     

Using perceptions as evidence to improve conservation and environmental management

The conservation community is increasingly focusing on the monitoring and evaluation of management, governance, ecological, and social considerations as part of a broader move toward adaptive management and evidence‐based conservation. Evidence is any information that can be used to come to a conclusion and support a judgment or, in this case, to make decisions that will improve conservation policies, actions, and outcomes. Perceptions are one type of information that is often dismissed as anecdotal by those arguing for evidence‐based conservation. In this paper, I clarify the contributions of research on perceptions of conservation to improving adaptive and evidence‐based conservation. Studies of the perceptions of local people can provide important insights into observations, understandings and interpretations of the social impacts, and ecological outcomes of conservation; the legitimacy of conservation governance; and the social acceptability of environmental management. Perceptions of these factors contribute to positive or negative local evaluations of conservation initiatives. It is positive perceptions, not just objective scientific evidence of effectiveness, that ultimately ensure the support of local constituents thus enabling the long‐term success of conservation. Research on perceptions can inform courses of action to improve conservation and governance at scales ranging from individual initiatives to national and international policies. Better incorporation of evidence from across the social and natural sciences and integration of a plurality of methods into monitoring and evaluation will provide a more complete picture on which to base conservation decisions and environmental management.     

Economic and Ecological Outcomes of Flexible Biodiversity Offset Systems

The commonly expressed goal of biodiversity offsets is to achieve no net loss of specific biological features affected by development. However, strict equivalency requirements may complicate trading of offset credits, increase costs due to restricted offset placement options, and force offset activities to focus on features that may not represent regional conservation priorities. Using the oil sands industry of Alberta, Canada, as a case study, we evaluated the economic and ecological performance of alternative offset systems targeting either ecologically equivalent areas (vegetation types) or regional conservation priorities (caribou and the Dry Mixedwood natural subregion). Exchanging dissimilar biodiversity elements requires assessment via a generalized metric; we used an empirically derived index of biodiversity intactness to link offsets with losses incurred by development. We considered 2 offset activities: land protection, with costs estimated as the net present value of profits of petroleum and timber resources to be paid as compensation to resource tenure holders, and restoration of anthropogenic footprint, with costs estimated from existing restoration projects. We used the spatial optimization tool MARXAN to develop hypothetical offset networks that met either the equivalent‐vegetation or conservation‐priority targets. Networks that required offsetting equivalent vegetation cost 2–17 times more than priority‐focused networks. This finding calls into question the prudence of equivalency‐based systems, particularly in relatively undeveloped jurisdictions, where conservation focuses on limiting and directing future losses. Priority‐focused offsets may offer benefits to industry and environmental stakeholders by allowing for lower‐cost conservation of valued ecological features and may invite discussion on what land‐use trade‐offs are acceptable when trading biodiversity via offsets. Resultados Económicos y Ecológicos de Sistemas de Compensación de Biodiversidad Flexible Habib et al.     

Six Common Mistakes in Conservation Priority Setting

A vast number of prioritization schemes have been developed to help conservation navigate tough decisions about the allocation of finite resources. However, the application of quantitative approaches to setting priorities in conservation frequently includes mistakes that can undermine their authors’ intention to be more rigorous and scientific in the way priorities are established and resources allocated. Drawing on well‐established principles of decision science, we highlight 6 mistakes commonly associated with setting priorities for conservation: not acknowledging conservation plans are prioritizations; trying to solve an ill‐defined problem; not prioritizing actions; arbitrariness; hidden value judgments; and not acknowledging risk of failure. We explain these mistakes and offer a path to help conservation planners avoid making the same mistakes in future prioritizations. Seis Errores Comunes en la Definición de Prioridades de Conservación     

Integrating Biological and Social Values When Prioritizing Places for Biodiversity Conservation

The consideration of information on social values in conjunction with biological data is critical for achieving both socially acceptable and scientifically defensible conservation planning outcomes. However, the influence of social values on spatial conservation priorities has received limited attention and is poorly understood. We present an approach that incorporates quantitative data on social values for conservation and social preferences for development into spatial conservation planning. We undertook a public participation GIS survey to spatially represent social values and development preferences and used species distribution models for 7 threatened fauna species to represent biological values. These spatially explicit data were simultaneously included in the conservation planning software Zonation to examine how conservation priorities changed with the inclusion of social data. Integrating spatially explicit information about social values and development preferences with biological data produced prioritizations that differed spatially from the solution based on only biological data. However, the integrated solutions protected a similar proportion of the species’ distributions, indicating that Zonation effectively combined the biological and social data to produce socially feasible conservation solutions of approximately equivalent biological value. We were able to identify areas of the landscape where synergies and conflicts between different value sets are likely to occur. Identification of these synergies and conflicts will allow decision makers to target communication strategies to specific areas and ensure effective community engagement and positive conservation outcomes. Integración de Valores Biológicos y Sociales al Priorizar Sitios para la Conservación de la Biodiversidad     

Wildlife Connectivity Approaches and Best Practices in U.S. State Wildlife Action Plans

As habitat loss and fragmentation threaten biodiversity on large geographic scales, creating and maintaining connectivity of wildlife populations is an increasingly common conservation objective. To assess the progress and success of large‐scale connectivity planning, conservation researchers need a set of plans that cover large geographic areas and can be analyzed as a single data set. The state wildlife action plans (SWAPs) fulfill these requirements. We examined 50 SWAPs to determine the extent to which wildlife connectivity planning, via linkages, is emphasized nationally. We defined linkage as connective land that enables wildlife movement. For our content analysis, we identified and quantified 6 keywords and 7 content criteria that ranged in specificity and were related to linkages for wide‐ranging terrestrial vertebrates and examined relations between content criteria and statewide data on focal wide‐ranging species, spending, revenue, and conserved land. Our results reflect nationwide disparities in linkage conservation priorities and highlight the continued need for wildlife linkage planning. Only 30% or less of the 50 SWAPs fulfilled highly specific content criteria (e.g., identifying geographic areas for linkage placement or management). We found positive correlations between our content criteria and statewide data on percent conserved land, total focal species, and spending on parks and recreation. We supplemented our content analysis with interviews with 17 conservation professionals to gain specific information about state‐specific context and future directions of linkage conservation. Based on our results, relevant literature, and interview responses, we suggest the following best practices for wildlife linkage conservation plans: collect ecologically meaningful background data; be specific; establish community‐wide partnerships; and incorporate sociopolitical and socioeconomic information. Acercamientos a la Conectividad de Vida Silvestre y las Mejores Prácticas en los Planes de Acción de Vida Silvestre Estatales en los Estados Unidos     

The challenge of implementing the European network of protected areas Natura 2000

Established under the European Union (EU) Birds and Habitats Directives, Natura 2000 is one of the largest international networks of protected areas. With the spatial designation of sites by the EU member states almost finalized, the biggest challenge still lying ahead is the appropriate management of the sites. To evaluate the cross‐scale functioning of Natura 2000 implementation, we analyzed 242 questionnaires completed by conservation scientists involved in the implementation of Natura 2000 in 24 EU member states. Respondents identified 7 key drivers of the quality of Natura 2000 implementation. Ordered in decreasing evaluation score, these drivers included: network design, use of external resources, legal frame, scientific input, procedural frame, social input, and national or local policy. Overall, conservation scientists were moderately satisfied with the implementation of Natura 2000. Tree modeling revealed that poor application of results of environmental impact assessments (EIA) was considered a major constraint. The main strengths of the network included the substantial increase of scientific knowledge of the sites, the contribution of nongovernmental organizations, the adequate network design in terms of area and representativeness, and the adequacy of the EU legal frame. The main weaknesses of Natura 2000 were the lack of political will from local and national governments toward effective implementation; the negative attitude of local stakeholders; the lack of background knowledge of local stakeholders, which prevented well‐informed policy decisions; and the understaffing of Natura 2000 management authorities. Top suggestions to improve Natura 2000 implementation were increase public awareness, provide environmental education to local communities, involve high‐quality conservation experts, strengthen quality control of EIA studies, and establish a specific Natura 2000 fund. El Reto de Implementar la Red Europea de Áreas Protegidas Natura 2000     

Improving effectiveness of systematic conservation planning with density data

Systematic conservation planning aims to design networks of protected areas that meet conservation goals across large landscapes. The optimal design of these conservation networks is most frequently based on the modeled habitat suitability or probability of occurrence of species, despite evidence that model predictions may not be highly correlated with species density. We hypothesized that conservation networks designed using species density distributions more efficiently conserve populations of all species considered than networks designed using probability of occurrence models. To test this hypothesis, we used the Zonation conservation prioritization algorithm to evaluate conservation network designs based on probability of occurrence versus density models for 26 land bird species in the U.S. Pacific Northwest. We assessed the efficacy of each conservation network based on predicted species densities and predicted species diversity. High‐density model Zonation rankings protected more individuals per species when networks protected the highest priority 10‐40% of the landscape. Compared with density‐based models, the occurrence‐based models protected more individuals in the lowest 50% priority areas of the landscape. The 2 approaches conserved species diversity in similar ways: predicted diversity was higher in higher priority locations in both conservation networks. We conclude that both density and probability of occurrence models can be useful for setting conservation priorities but that density‐based models are best suited for identifying the highest priority areas. Developing methods to aggregate species count data from unrelated monitoring efforts and making these data widely available through ecoinformatics portals such as the Avian Knowledge Network will enable species count data to be more widely incorporated into systematic conservation planning efforts.     

Use of Inverse Spatial Conservation Prioritization to Avoid Biological Diversity Loss Outside Protected Areas

Globally expanding human land use sets constantly increasing pressure for maintenance of biological diversity and functioning ecosystems. To fight the decline of biological diversity, conservation science has broken ground with methods such as the operational model of systematic conservation planning (SCP), which focuses on design and on‐the‐ground implementation of conservation areas. The most commonly used method in SCP is reserve selection that focuses on the spatial design of reserve networks and their expansion. We expanded these methods by introducing another form of spatial allocation of conservation effort relevant for land‐use zoning at the landscape scale that avoids negative ecological effects of human land use outside protected areas. We call our method inverse spatial conservation prioritization. It can be used to identify areas suitable for economic development while simultaneously limiting total ecological and environmental effects of that development at the landscape level by identifying areas with highest economic but lowest ecological value. Our method is not based on a priori targets, and as such it is applicable to cases where the effects of land use on, for example, individual species or ecosystem types are relatively small and would not lead to violation of regional or national conservation targets. We applied our method to land‐use allocation to peat mining. Our method identified a combination of profitable production areas that provides the needed area for peat production while retaining most of the landscape‐level ecological value of the ecosystem. The results of this inverse spatial conservation prioritization are being used in land‐use zoning in the province of Central Finland.