Effects of cost metric on cost‐effectiveness of protected‐area network design in urban landscapes

A common goal in conservation planning is to acquire areas that are critical to realizing biodiversity goals in the most cost‐effective manner. The way monetary acquisition costs are represented in such planning is an understudied but vital component to realizing cost efficiencies. We sought to design a protected‐area network within a forested urban region that would protect 17 birds of conservation concern. We compared the total costs and spatial structure of the optimal protected‐area networks produced using three acquisition‐cost surrogates (area, agricultural land value, and tax‐assessed land value). Using the tax‐assessed land values there was a 73% and 78% cost savings relative to networks derived using area or agricultural land value, respectively. This cost reduction was due to the considerable heterogeneity in acquisition costs revealed in tax‐assessed land values, especially for small land parcels, and the corresponding ability of the optimization algorithm to identify lower‐cost parcels for inclusion that had equal value to our target species. Tax‐assessed land values also reflected the strong spatial differences in acquisition costs (US$0.33/m²–$55/m²) and thus allowed the algorithm to avoid inclusion of high‐cost parcels when possible. Our results add to a nascent but growing literature that suggests conservation planners must consider the cost surrogate they use when designing protected‐area networks. We suggest that choosing cost surrogates that capture spatial‐ and size‐dependent heterogeneity in acquisition costs may be relevant to establishing protected areas in urbanizing ecosystems.     

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.     

Building robust conservation plans

Systematic conservation planning optimizes trade‐offs between biodiversity conservation and human activities by accounting for socioeconomic costs while aiming to achieve prescribed conservation objectives. However, the most cost‐efficient conservation plan can be very dissimilar to any other plan achieving the set of conservation objectives. This is problematic under conditions of implementation uncertainty (e.g., if all or part of the plan becomes unattainable). We determined through simulations of parallel implementation of conservation plans and habitat loss the conditions under which optimal plans have limited chances of implementation and where implementation attempts would fail to meet objectives. We then devised a new, flexible method for identifying conservation priorities and scheduling conservation actions. This method entails generating a number of alternative plans, calculating the similarity in site composition among all plans, and selecting the plan with the highest density of neighboring plans in similarity space. We compared our method with the classic method that maximizes cost efficiency with synthetic and real data sets. When implementation was uncertain—a common reality—our method provided higher likelihood of achieving conservation targets. We found that χ, a measure of the shortfall in objectives achieved by a conservation plan if the plan could not be implemented entirely, was the main factor determining the relative performance of a flexibility enhanced approach to conservation prioritization. Our findings should help planning authorities prioritize conservation efforts in the face of uncertainty about future condition and availability of sites.     

Conservation Planning when Costs Are Uncertain

Abstract: Spatially explicit information on the financial costs of conservation actions can improve the ability of conservation planning to achieve ecological and economic objectives, but the magnitude of this improvement may depend on the accuracy of the cost estimates. Data on costs of conservation actions are inherently uncertain. For example, the cost of purchasing a property for addition to a protected‐area network depends on the individual landholder's preferences, values, and aspirations, all of which vary in space and time, and the effect of this uncertainty on the conservation priority of a site is relatively untested. We investigated the sensitivity of the conservation priority of sites to uncertainty in cost estimates. We explored scenarios for expanding (four‐fold) the protected‐area network in Queensland, Australia to represent a range of vegetation types, species, and abiotic environments, while minimizing the cost of purchasing new properties. We estimated property costs for 17, 790 10 × 10 km sites with data on unimproved land values. We systematically changed property costs and noted how these changes affected conservation priority of a site. The sensitivity of the priority of a site to changes in cost data was largely dependent on a site's importance for meeting conservation targets. Sites that were essential or unimportant for meeting targets maintained high or low priorities, respectively, regardless of cost estimates. Sites of intermediate conservation priority were sensitive to property costs and represented the best option for efficiency gains, especially if they could be purchased at a lower price than anticipated. Thus, uncertainty in cost estimates did not impede the use of cost data in conservation planning, and information on the sensitivity of the conservation priority of a site to estimates of the price of land can be used to inform strategic conservation planning before the actual price of the land is known.     

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 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     

How economics can further the success of ecological restoration

Restoration scientists and practitioners have recently begun to include economic and social aspects in the design and investment decisions for restoration projects. With few exceptions, ecological restoration studies that include economics focus solely on evaluating costs of restoration projects. However, economic principles, tools, and instruments can be applied to a range of other factors that affect project success. We considered the relevance of applying economics to address 4 key challenges of ecological restoration: assessing social and economic benefits, estimating overall costs, project prioritization and selection, and long‐term financing of restoration programs. We found it is uncommon to consider all types of benefits (such as nonmarket values) and costs (such as transaction costs) in restoration programs. Total benefit of a restoration project can be estimated using market prices and various nonmarket valuation techniques. Total cost of a project can be estimated using methods based on property or land‐sale prices, such as hedonic pricing method and organizational surveys. Securing continuous (or long‐term) funding is also vital to accomplishing restoration goals and can be achieved by establishing synergy with existing programs, public–private partnerships, and financing through taxation.     

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.     

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.     

Costs of expanding the network of protected areas as a response to climate change in the Cape Floristic Region

The expansion of protected areas is a critical component of strategies to promote the continued existence of biodiversity (i.e., life at all levels of biological organization) as climate changes, but scientific, social, and economic uncertainties associated with climate change are some of the major obstacles preventing such expansion. New models of climate change and species distribution and new methods of conservation planning now make it possible to explore the uncertainties associated with climate changes and species responses. Yet few reliable estimates of the costs of expanding protected areas and methods for determining these costs exist, largely because of the many (and uncertain) determinants of these costs. We developed a cost-accounting model to estimate the range in costs of various options for expanding protected areas and to explore the variables that drive these costs. Model development was informed by an existing plan to expand protected areas in the Cape Floristic Region of South Africa to address species conservation under a scenario of climate change. The 50-year present value of total costs varied from US$260 million ($1077/ha) for an off-reserve option that involves agreements with landowners and no compensation of forgone production and associated revenue to $1020 million ($4228/ha) for an on-reserve option that involves land acquisition and protection. The costs of acquiring land or compensating landowners for forgone production and development opportunities were the major drivers of the total costs across all options because most of the area identified in the protected-area expansion plan consisted of urban and high-quality agricultural lands. Total costs were also affected by changes in protected area extent and discount rate. Model-generated outputs such as these may be useful for informing implementation strategies and the allocation of future efforts in monitoring, data collection, and model development.     

Knowledge co‐production and boundary work to promote implementation of conservation plans

Knowledge co‐production and boundary work offer planners a new frame for critically designing a social process that fosters collaborative implementation of resulting plans. Knowledge co‐production involves stakeholders from diverse knowledge systems working iteratively toward common vision and action. Boundary work is a means of creating permeable knowledge boundaries that satisfy the needs of multiple social groups while guarding the functional integrity of contributing knowledge systems. Resulting products are boundary objects of mutual interest that maintain coherence across all knowledge boundaries. We examined how knowledge co‐production and boundary work can bridge the gap between planning and implementation and promote cross‐sectoral cooperation. We applied these concepts to well‐established stages in regional conservation planning within a national scale conservation planning project aimed at identifying areas for conserving rivers and wetlands of South Africa and developing an institutional environment for promoting their conservation. Knowledge co‐production occurred iteratively over 4 years in interactive stake‐holder workshops that included co‐development of national freshwater conservation goals and spatial data on freshwater biodiversity and local conservation feasibility; translation of goals into quantitative inputs that were used in Marxan to select draft priority conservation areas; review of draft priority areas; and packaging of resulting map products into an atlas and implementation manual to promote application of the priority area maps in 37 different decision‐making contexts. Knowledge co‐production stimulated dialogue and negotiation and built capacity for multi‐scale implementation beyond the project. The resulting maps and information integrated diverse knowledge types of over 450 stakeholders and represented >1000 years of collective experience. The maps provided a consistent national source of information on priority conservation areas for rivers and wetlands and have been applied in 25 of the 37 use contexts since their launch just over 3 years ago. When framed as a knowledge co‐production process supported by boundary work, regional conservation plans can be developed into valuable boundary objects that offer a tangible tool for multi‐agency cooperation around conservation. Our work provides practical guidance for promoting uptake of conservation science and contributes to an evidence base on how conservation efforts can be improved.     

Evaluating Private Land Conservation in the Cape Lowlands,South Africa

Abstract: Evaluation is important for judiciously allocating limited conservation resources and for improving conservation success through learning and strategy adjustment. We evaluated the application of systematic conservation planning goals and conservation gains from incentive‐based stewardship interventions on private land in the Cape Lowlands and Cape Floristic Region, South Africa. We collected spatial and nonspatial data (2003–2007) to determine the number of hectares of vegetation protected through voluntary contractual and legally nonbinding (informal) agreements with landowners; resources spent on these interventions; contribution of the agreements to 5‐ and 20‐year conservation goals for representation and persistence in the Cape Lowlands of species and ecosystems; and time and staff required to meet these goals. Conservation gains on private lands across the Cape Floristic Region were relatively high. In 5 years, 22,078 ha (27,800 ha of land) and 46,526 ha (90,000 ha of land) of native vegetation were protected through contracts and informal agreements, respectively. Informal agreements often were opportunity driven and cheaper and faster to execute than contracts. All contractual agreements in the Cape Lowlands were within areas of high conservation priority (identified through systematic conservation planning), which demonstrated the conservation plan's practical application and a high level of overlap between resource investment (approximately R1.14 million/year in the lowlands) and priority conservation areas. Nevertheless, conservation agreements met only 11% of 5‐year and 9% of 20‐year conservation goals for Cape Lowlands and have made only a moderate contribution to regional persistence of flora to date. Meeting the plan's conservation goals will take three to five times longer and many more staff members to maintain agreements than initially envisaged.     

Balancing Forest‐Regeneration Probabilities and Maintenance Costs in Dry Grasslands of High Conservation Priority

Abstract: Abandonment of agricultural land has resulted in forest regeneration in species‐rich dry grasslands across European mountain regions and threatens conservation efforts in this vegetation type. To support national conservation strategies, we used a site‐selection algorithm (MARXAN) to find optimum sets of floristic regions (reporting units) that contain grasslands of high conservation priority. We sought optimum sets that would accommodate 136 important dry‐grassland species and that would minimize forest regeneration and costs of management needed to forestall predicted forest regeneration. We did not consider other conservation elements of dry grasslands, such as animal species richness, cultural heritage, and changes due to climate change. Optimal sets that included 95–100% of the dry grassland species encompassed an average of 56–59 floristic regions (standard deviation, SD 5). This is about 15% of approximately 400 floristic regions that contain dry‐grassland sites and translates to 4800–5300 ha of dry grassland out of a total of approximately 23,000 ha for the entire study area. Projected costs to manage the grasslands in these optimum sets ranged from CHF (Swiss francs) 5.2 to 6.0 million/year. This is only 15–20% of the current total estimated cost of approximately CHF30–45 million/year required if all dry grasslands were to be protected. The grasslands of the optimal sets may be viewed as core sites in a national conservation strategy.     

Safeguarding Biodiversity and Ecosystem Services in the Little Karoo,South Africa

Abstract: Global declines in biodiversity and the widespread degradation of ecosystem services have led to urgent calls to safeguard both. Responses to this urgency include calls to integrate the needs of ecosystem services and biodiversity into the design of conservation interventions. The benefits of such integration are purported to include improvements in the justification and resources available for these interventions. Nevertheless, additional costs and potential trade‐offs remain poorly understood in the design of interventions that seek to conserve biodiversity and ecosystem services. We sought to investigate the synergies and trade‐offs in safeguarding ecosystem services and biodiversity in South Africa's Little Karoo. We used data on three ecosystem services—carbon storage, water recharge, and fodder provision—and data on biodiversity to examine several conservation planning scenarios. First, we investigated the amount of each ecosystem service captured incidentally by a conservation plan to meet targets for biodiversity only while minimizing opportunity costs. We then examined the costs of adding targets for ecosystem services into this conservation plan. Finally, we explored trade‐offs between biodiversity and ecosystem service targets at a fixed cost. At least 30% of each ecosystem service was captured incidentally when all of biodiversity targets were met. By including data on ecosystem services, we increased the amount of services captured by at least 20% for all three services without additional costs. When biodiversity targets were reduced by 8%, an extra 40% of fodder provision and water recharge were obtained and 58% of carbon could be captured for the same cost. The opportunity cost (in terms of forgone production) of safeguarding 100% of the biodiversity targets was about US$500 million. Our results showed that with a small decrease in biodiversity target achievement, substantial gains for the conservation of ecosystem services can be achieved within our biodiversity priority areas for no extra cost.     

Carbon Payments and Low‐Cost Conservation

Abstract: A price on carbon is expected to generate demand for carbon offset schemes. This demand could drive investment in tree‐based monocultures that provide higher carbon yields than diverse plantings of native tree and shrub species, which sequester less carbon but provide greater variation in vegetation structure and composition. Economic instruments such as species conservation banking, the creation and trading of credits that represent biological‐diversity values on private land, could close the financial gap between monocultures and more diverse plantings by providing payments to individuals who plant diverse species in locations that contribute to conservation and restoration goals. We studied a highly modified agricultural system in southern Australia that is typical of many temperate agriculture zones globally (i.e., has a high proportion of endangered species, high levels of habitat fragmentation, and presence of non‐native species). We quantified the economic returns from agriculture and from carbon plantings (monoculture and mixed tree and shrubs) under six carbon‐price scenarios. We also identified high‐priority locations for restoration of cleared landscapes with mixed tree and shrub carbon plantings. Depending on the price of carbon, direct annual payments to landowners of AU$7/ha/year to $125/ha/year (US$6–120/ha/year) may be sufficient to augment economic returns from a carbon market and encourage tree plantings that contribute more to the restoration of natural systems and endangered species habitats than monocultures. Thus, areas of high priority for conservation and restoration may be restored relatively cheaply in the presence of a carbon market. Overall, however, less carbon is sequestered by mixed native tree and shrub plantings.     

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.     

Economics of Grassland Conversion to Cropland in the Prairie Pothole Region

Abstract: Much of the remaining grassland, particularly in North America, is privately owned, and its conversion to cultivated cropland is largely driven by economics. An understanding of why landowners convert grassland to cropland could facilitate more effective design of grassland‐conservation programs. We built an empirical model of land‐use change in the Prairie Pothole Region (north‐central United States) to estimate the probability of grassland conversion to alternative agricultural land uses, including cultivated crops. Conversion was largely driven by landscape characteristics and the economic returns of alternative uses. Our estimate of the probability of grassland conversion to cultivated crops (1.33% on average from 1979 to 1997) was higher than past estimates (0.4%). Our model also predicted that grassland‐conversion probabilities will increase if agricultural commodity prices continue to follow the trends observed from 2001 to 2006 (0.93% probability of grassland conversion to cultivated crops in 2006 to 1.5% in 2011). Thus, nearly 121 million ha (30 million acres) of grassland could be converted by 2011. Conversion probabilities, however, are spatially heterogeneous (range 0.2% to 3%), depending on characteristics of a parcel (e.g., soil quality and economic returns). Grassland parcels with relatively high‐quality land for agricultural production are more likely to be converted to cultivated crops than lower‐quality parcels and are more responsive to changes in the economic returns on alternative agricultural land uses (i.e., conversion probability increases by a larger magnitude for high‐quality parcels when economics returns to alternative uses increase). Our results suggest that grassland conservation programs could be proactively targeted toward high‐risk parcels by anticipating changes in economic returns, such as could occur if a new biofuel processing plant were to be built in an area.     

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.     

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.     

Connectivity Planning to Address Climate Change

As the climate changes, human land use may impede species from tracking areas with suitable climates. Maintaining connectivity between areas of different temperatures could allow organisms to move along temperature gradients and allow species to continue to occupy the same temperature space as the climate warms. We used a coarse‐filter approach to identify broad corridors for movement between areas where human influence is low while simultaneously routing the corridors along present‐day spatial gradients of temperature. We modified a cost–distance algorithm to model these corridors and tested the model with data on current land‐use and climate patterns in the Pacific Northwest of the United States. The resulting maps identified a network of patches and corridors across which species may move as climates change. The corridors are likely to be robust to uncertainty in the magnitude and direction of future climate change because they are derived from gradients and land‐use patterns. The assumptions we applied in our model simplified the stability of temperature gradients and species responses to climate change and land use, but the model is flexible enough to be tailored to specific regions by incorporating other climate variables or movement costs. When used at appropriate resolutions, our approach may be of value to local, regional, and continental conservation initiatives seeking to promote species movements in a changing climate. Planificación de Conectividad para Atender el Cambio Climático