The Value of Using Feasibility Models in Systematic Conservation Planning to Predict Landholder Management Uptake

Understanding the social dimensions of conservation opportunity is crucial for conservation planning in multiple‐use landscapes. However, factors that influence the feasibility of implementing conservation actions, such as the history of landscape management, and landholders’ willingness to engage are often difficult or time consuming to quantify and rarely incorporated into planning. We examined how conservation agencies could reduce costs of acquiring such data by developing predictive models of management feasibility parameterized with social and biophysical factors likely to influence landholders’ decisions to engage in management. To test the utility of our best‐supported model, we developed 4 alternative investment scenarios based on different input data for conservation planning: social data only; biological data only; potential conservation opportunity derived from modeled feasibility that incurs no social data collection costs; and existing conservation opportunity derived from feasibility data that incurred collection costs. Using spatially explicit information on biodiversity values, feasibility, and management costs, we prioritized locations in southwest Australia to control an invasive predator that is detrimental to both agriculture and natural ecosystems: the red fox (Vulpes vulpes). When social data collection costs were moderate to high, the most cost‐effective investment scenario resulted from a predictive model of feasibility. Combining empirical feasibility data with biological data was more cost‐effective for prioritizing management when social data collection costs were low (<4% of the total budget). Calls for more data to inform conservation planning should take into account the costs and benefits of collecting and using social data to ensure that limited funding for conservation is spent in the most cost‐efficient and effective manner.     

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.     

Global justice and the opportunity costs of conservation

Opportunity costs can represent a significant portion of the costs associated with conservation projects and frequently outstrip other kinds of cost. They are typically understood to refer to the benefits someone would have obtained if conservation projects had not required them to give up current activities, such as farming or hunting or if the land had been available for uses other than conservation. This familiar way of identifying opportunity costs is flawed, however, because it threatens to condone, or take advantage of, the injustices that many people face that affect their opportunities. I integrated ideas from the political theory of global justice to examine how the analysis of opportunity costs illustrates the importance of considering conservation and issues of global justice together, rather than thinking about them in isolation. I distinguish four baselines for defining opportunity costs. A status quo baseline defines opportunity costs by asking what people would have earned had a conservation project not happened. A willingness to accept baseline defines them by asking people what it would take to make them indifferent to whether a conservation project takes place or not. An antipoverty baseline suggests that opportunity costs have been met when people affected by a project are not left in poverty. An egalitarian baseline suggests opportunity costs have been met when people are not left in relative disadvantage, with worse than average opportunities. I argue that the egalitarian baseline is the most acceptable from the point of view of justice. Such a baseline would suggest that, in practice, many of the world's poor are being unjustly treated, or even exploited, as a result of conservation activities.     

Conservation Businesses and Conservation Planning in a Biological Diversity Hotspot

The allocation of land to biological diversity conservation competes with other land uses and the needs of society for development, food, and extraction of natural resources. Trade‐offs between biological diversity conservation and alternative land uses are unavoidable, given the realities of limited conservation resources and the competing demands of society. We developed a conservation‐planning assessment for the South African province of KwaZulu‐Natal, which forms the central component of the Maputaland–Pondoland–Albany biological diversity hotspot. Our objective was to enhance biological diversity protection while promoting sustainable development and providing spatial guidance in the resolution of potential policy conflicts over priority areas for conservation at risk of transformation. The conservation‐planning assessment combined spatial‐distribution models for 646 conservation features, spatial economic‐return models for 28 alternative land uses, and spatial maps for 4 threats. Nature‐based tourism businesses were competitive with other land uses and could provide revenues of >US$60 million/year to local stakeholders and simultaneously help meeting conservation goals for almost half the conservation features in the planning region. Accounting for opportunity costs substantially decreased conflicts between biological diversity, agricultural use, commercial forestry, and mining. Accounting for economic benefits arising from conservation and reducing potential policy conflicts with alternative plans for development can provide opportunities for successful strategies that combine conservation and sustainable development and facilitate conservation action. Negocios de Conservación y Planificación de la Conservación en un Sitio de Importancia para la Biodiversidad     

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.     

Efficient and equitable design of marine protected areas in Fiji through inclusion of stakeholder‐specific objectives in conservation planning

The efficacy of protected areas varies, partly because socioeconomic factors are not sufficiently considered in planning and management. Although integrating socioeconomic factors into systematic conservation planning is increasingly advocated, research is needed to progress from recognition of these factors to incorporating them effectively in spatial prioritization of protected areas. We evaluated 2 key aspects of incorporating socioeconomic factors into spatial prioritization: treatment of socioeconomic factors as costs or objectives and treatment of stakeholders as a single group or multiple groups. Using as a case study the design of a system of no‐take marine protected areas (MPAs) in Kubulau, Fiji, we assessed how these aspects affected the configuration of no‐take MPAs in terms of trade‐offs between biodiversity objectives, fisheries objectives, and equity in catch losses among fisher stakeholder groups. The achievement of fisheries objectives and equity tended to trade‐off concavely with increasing biodiversity objectives, indicating that it is possible to achieve low to mid‐range biodiversity objectives with relatively small losses to fisheries and equity. Importantly, the extent of trade‐offs depended on the method used to incorporate socioeconomic data and was least severe when objectives were set for each fisher stakeholder group explicitly. We found that using different methods to incorporate socioeconomic factors that require similar data and expertise can result in plans with very different impacts on local stakeholders.     

The Grain of Spatially Referenced Economic Cost and Biodiversity Benefit Data and the Effectiveness of a Cost Targeting Strategy

Facing tight resource constraints, conservation organizations must allocate funds available for habitat protection as effectively as possible. Often, they combine spatially referenced economic and biodiversity data to prioritize land for protection. We tested how sensitive these prioritizations could be to differences in the spatial grain of these data by demonstrating how the conclusion of a classic debate in conservation planning between cost and benefit targeting was altered based on the available information. As a case study, we determined parcel‐level acquisition costs and biodiversity benefits of land transactions recently undertaken by a nonprofit conservation organization that seeks to protect forests in the eastern United States. Then, we used hypothetical conservation plans to simulate the types of ex ante priorities that an organization could use to prioritize areas for protection. We found the apparent effectiveness of cost and benefit targeting depended on the spatial grain of the data used when prioritizing parcels based on local species richness. However, when accounting for complementarity, benefit targeting consistently was more efficient than a cost targeting strategy regardless of the spatial grain of the data involved. More pertinently for other studies, we found that combining data collected over different spatial grains inflated the apparent effectiveness of a cost targeting strategy and led to overestimation of the efficiency gain offered by adopting a more integrative return‐on‐investment approach.     

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.     

Expanding Kenya's protected areas under the Convention on Biological Diversity to maximize coverage of plant diversity

Biodiversity is highly valuable and critically threatened by anthropogenic degradation of the natural environment. In response, governments have pledged enhanced protected‐area coverage, which requires scarce biological data to identify conservation priorities. To assist this effort, we mapped conservation priorities in Kenya based on maximizing alpha (species richness) and beta diversity (species turnover) of plant communities while minimizing economic costs. We used plant‐cover percentages from vegetation surveys of over 2000 plots to build separate models for each type of diversity. Opportunity and management costs were based on literature data and interviews with conservation organizations. Species richness was predicted to be highest in a belt from Lake Turkana through Mount Kenya and in a belt parallel to the coast, and species turnover was predicted to be highest in western Kenya and along the coast. Our results suggest the expanding reserve network should focus on the coast and northeastern provinces of Kenya, where new biological surveys would also fill biological data gaps. Meeting the Convention on Biological Diversity target of 17% terrestrial coverage by 2020 would increase representation of Kenya's plant communities by 75%. However, this would require about 50 times more funds than Kenya has received thus far from the Global Environment Facility.     

Divergent effects of climate change on the egg-laying opportunity of species in cold and warm regions

Climate warming can substantially impact embryonic development and juvenile growth in oviparous species. Estimating the overall impacts of climate warming on oviparous reproduction is difficult because egg-laying events happen throughout the reproductive season. Successful egg laying requires the completion of embryonic development as well as hatching timing conducive to offspring survival and energy accumulation. We propose a new metric—egg-laying opportunity (EO)—to estimate the annual hours during which a clutch of freshly laid eggs yields surviving offspring that store sufficient energy for overwintering. We estimated the EO within the distribution of a model species, Sceloporus undulatus, under recent climate condition and a climate-warming scenario by combining microclimate data, developmental functions, and biophysical models. We predicted that EO will decline as the climate warms at 74.8% of 11,407 sites. Decreasing hatching success and offspring energy accounted for more lost EO hours (72.6% and 72.9%) than the occurrence of offspring heat stress (59.9%). Nesting deeper (at a depth of 12 cm) may be a more effective behavioral adjustment for retaining EO than using shadier (50% shade) nests because the former fully mitigated the decline of EO under the considered warming scenario at more sites (66.1%) than the latter (28.3%). We advocate for the use of EO in predicting the impacts of climate warming on oviparous animals because it encapsulates the integrative impacts of climate warming on all stages of reproductive life history.