Improving inferences about private land conservation by accounting for incomplete reporting

Private lands provide key habitat for imperiled species and are core components of function protectected area networks; yet, their incorporation into national and regional conservation planning has been challenging. Identifying locations where private landowners are likely to participate in conservation initiatives can help avoid conflict and clarify trade-offs between ecological benefits and sociopolitical costs. Empirical, spatially explicit assessment of the factors associated with conservation on private land is an emerging tool for identifying future conservation opportunities. However, most data on private land conservation are voluntarily reported and incomplete, which complicates these assessments. We used a novel application of occupancy models to analyze the occurrence of conservation easements on private land. We compared multiple formulations of occupancy models with a logistic regression model to predict the locations of conservation easements based on a spatially explicit social–ecological systems framework. We combined a simulation experiment with a case study of easement data in Idaho and Montana (United States) to illustrate the utility of the occupancy framework for modeling conservation on private land. Occupancy models that explicitly accounted for variation in reporting produced estimates of predictors that were substantially less biased than estimates produced by logistic regression under all simulated conditions. Occupancy models produced estimates for the 6 predictors we evaluated in our case study that were larger in magnitude, but less certain than those produced by logistic regression. These results suggest that occupancy models result in qualitatively different inferences regarding the effects of predictors on conservation easement occurrence than logistic regression and highlight the importance of integrating variable and incomplete reporting of participation in empirical analysis of conservation initiatives. Failure to do so can lead to emphasizing the wrong social, institutional, and environmental factors that enable conservation and underestimating conservation opportunities in landscapes where social norms or institutional constraints inhibit reporting.     

How decisions about fitting species distribution models affect conservation outcomes

Species distribution models (SDMs) are increasingly used in conservation and land-use planning as inputs to describe biodiversity patterns. These models can be built in different ways, and decisions about data preparation, selection of predictor variables, model fitting, and evaluation all alter the resulting predictions. Commonly, the true distribution of species is unknown and independent data to verify which SDM variant to choose are lacking. Such model uncertainty is of concern to planners. We analyzed how 11 routine decisions about model complexity, predictors, bias treatment, and setting thresholds for predicted values altered conservation priority patterns across 25 species. Models were created with MaxEnt and run through Zonation to determine the priority rank of sites. Although all SDM variants performed well (area under the curve >0.7), they produced spatially different predictions for species and different conservation priority solutions. Priorities were most strongly altered by decisions to not address bias or to apply binary thresholds to predicted values; on average 40% and 35%, respectively, of all grid cells received an opposite priority ranking. Forcing high model complexity altered conservation solutions less than forcing simplicity (14% and 24% of cells with opposite rank values, respectively). Use of fewer species records to build models or choosing alternative bias treatments had intermediate effects (25% and 23%, respectively). Depending on modeling choices, priority areas overlapped as little as 10–20% with the baseline solution, affecting top and bottom priorities differently. Our results demonstrate the extent of model-based uncertainty and quantify the relative impacts of SDM building decisions. When it is uncertain what the best SDM approach and conservation plan is, solving uncertainty or considering alterative options is most important for those decisions that change plans the most.     

Using expert knowledge to support Endangered Species Act decision-making for data-deficient species

Many questions relevant to conservation decision-making are characterized by extreme uncertainty due to lack of empirical data and complexity of the underlying ecologic processes, leading to a rapid increase in the use of structured protocols to elicit expert knowledge. Published ecologic applications often employ a modified Delphi method, where experts provide judgments anonymously and mathematical aggregation techniques are used to combine judgments. The Sheffield elicitation framework (SHELF) differs in its behavioral approach to synthesizing individual judgments into a fully specified probability distribution for an unknown quantity. We used the SHELF protocol remotely to assess extinction risk of three subterranean aquatic species that are being considered for listing under the U.S. Endangered Species Act. We provided experts an empirical threat assessment for each known locality over a video conference and recorded judgments on the probability of population persistence over four generations with online submission forms and R-shiny apps available through the SHELF package. Despite large uncertainty for all populations, there were key differences between species’ risk of extirpation based on spatial variation in dominant threats, local land use and management practices, and species’ microhabitat. The resulting probability distributions provided decision makers with a full picture of uncertainty that was consistent with the probabilistic nature of risk assessments. Discussion among experts during SHELF's behavioral aggregation stage clearly documented dominant threats (e.g., development, timber harvest, animal agriculture, and cave visitation) and their interactions with local cave geology and species’ habitat. Our virtual implementation of the SHELF protocol demonstrated the flexibility of the approach for conservation applications operating on budgets and time lines that can limit in-person meetings of geographically dispersed experts.     

Five approaches to producing actionable science in conservation

The knowledge produced by conservation scientists must be actionable in order to address urgent conservation challenges. To understand the process of creating actionable science, we interviewed 71 conservation scientists who had participated in 1 of 3 fellowship programs focused on training scientists to become agents of change. Using a grounded theory approach, we identified 16 activities that these researchers employed to make their scientific products more actionable. Some activities were more common than others and, arguably, more foundational. We organized these activities into 3 nested categories (motivations, strategies, and tactics). Using a co-occurrence matrix, we found that most activities were positively correlated. These correlations allowed us to identify 5 approaches, framed as profiles, to actionable science: the discloser, focused on open access; the educator, focused on science communication; the networker, focused on user needs and building relationships; the collaborator, focused on boundary spanning; and the pluralist, focused on knowledge coproduction resulting in valuable outcomes for all parties. These profiles build on one another in a hierarchy determined by their complexity and level of engagement, their potential to support actionable science, and their proximity to ideal coproduction with knowledge users. Our results provide clear guidance for conservation scientists to generate actionable science to address the global biodiversity conservation challenge.     

A new method for broad-scale modeling and projection of plant assemblages under climatic,biotic, and environmental cofiltering

There is increasing interestin broad-scale analysis, modeling, and prediction of the distribution and composition of plant species assemblages under climatic, environmental, and biotic change, particularly for conservation purposes. We devised a method to reliably predict the impact of climate change on large assemblages of plant communities, while also considering competing biotic and environmental factors. To this purpose, we first used multilabel algorithms in order to convert the task of explaining a large assemblage of plant communities into a classification framework able to capture with high cross-validated accuracy the pattern of species distributions under a composite set of biotic and abiotic factors. We applied our model to a large set of plant communities in the Swiss Alps. Our model explained presences and absences of 175 plant species in 608 plots with >87% cross-validated accuracy, predicted decreases in α, β, and γ diversity by 2040 under both moderate and extreme climate scenarios, and identified likely advantaged and disadvantaged plant species under climate change. Multilabel variable selection revealed the overriding importance of topography, soils, and temperature extremes (rather than averages) in determining the distribution of plant species in the study area and their response to climate change. Our method addressed a number of challenging research problems, such as scaling to large numbers of species, considering species relationships and rarity, and addressing an overwhelming proportion of absences in presence–absence matrices. By handling hundreds to thousands of plants and plots simultaneously over large areas, our method can inform broad-scale conservation of plant species under climate change because it allows species that require urgent conservation action (assisted migration, seed conservation, and ex situ conservation) to be detected and prioritized. Our method also increases the practicality of assisted colonization of plant species by helping to prevent ill-advised introduction of plant species with limited future survival probability.     

Investigating cumulative effects across ecological scales

Species, habitats, and ecosystems are increasingly exposed to multiple anthropogenic stressors, fueling a rapidly expanding research program to understand the cumulative impacts of these environmental modifications. Since the 1970s, a growing set of methods has been developed through two parallel, sometimes connected, streams of research within the applied and academic realms to assess cumulative effects. Past reviews of cumulative effects assessment (CEA) methods focused on approaches used by practitioners. Academic research has developed several distinct and novel approaches to conducting CEA. Understanding the suite of methods that exist will help practitioners and academics better address various ecological foci (physiological responses, population impacts, ecosystem impacts) and ecological complexities (synergistic effects, impacts across space and time). We reviewed 6 categories of methods (experimental, meta-analysis, single-species modeling, mapping, qualitative modeling, and multispecies modeling) and examined the ability of those methods to address different levels of complexity. We focused on research gaps and emerging priorities. We found that no single method assessed impacts across the 4 ecological foci and 6 ecological complexities considered. We propose that methods can be used in combination to improve understanding such that multimodel inference can provide a suite of comparable outputs, mapping methods can help prioritize localized models or experimental gaps, and future experiments can be paired from the outset with models they will inform.     

Knowledge coproduction on the impact of decisions for waterbird habitat in a changing climate

Scientists, resource managers, and decision makers increasingly use knowledge coproduction to guide the stewardship of future landscapes under climate change. This process was applied in the California Central Valley (USA) to solve complex conservation problems, where managed wetlands and croplands are flooded between fall and spring to support some of the largest concentrations of shorebirds and waterfowl in the world. We coproduced scenario narratives, spatially explicit flooded waterbird habitat models, data products, and new knowledge about climate adaptation potential. We documented our coproduction process, and using the coproduced models, we determined when and where management actions make a difference and when climate overrides these actions. The outcomes of this process provide lessons learned on how to cocreate usable information and how to increase climate adaptive capacity in a highly managed landscape. Actions to restore wetlands and prioritize their water supply created habitat outcomes resilient to climate change impacts particularly in March, when habitat was most limited; land protection combined with management can increase the ecosystem's resilience to climate change; and uptake and use of this information was influenced by the roles of different stakeholders, rapidly changing water policies, discrepancies in decision-making time frames, and immediate crises of extreme drought. Although a broad stakeholder group contributed knowledge to scenario narratives and model development, to coproduce usable information, data products were tailored to a small set of decision contexts, leading to fewer stakeholder participants over time. A boundary organization convened stakeholders across a large landscape, and early adopters helped build legitimacy. Yet, broadscale use of climate adaptation knowledge depends on state and local policies, engagement with decision makers that have legislative and budgetary authority, and the capacity to fit data products to specific decision needs.     

Adapting participatory processes to fine-tune conservation approaches in multiactor decision settings

Conservation decisions are typically made in complex, dynamic, and uncertain settings, where multiple actors raise diverse and potentially conflicting claims, champion different and sometimes contradictory values, and enjoy varying degrees of freedom and power to act and influence collective decisions. Therefore, effective conservation actions require conservation scientists and practitioners to take into account the complexity of multiactor settings. We devised a framework to help conservation biologists and practitioners in this task. Institutional economic theories, which are insufficiently cited in the conservation literature, contain useful insights for conservation. Among these theories, the economies of worth can significantly contribute to conservation because it can be used to classify the types of values peoples or groups refer to when they interact during the elaboration and implementation of conservation projects. Refining this approach, we designed a framework to help conservation professionals grasp the relevant differences among settings in which decisions related to conservation actions are to be made, so that they can adapt their approaches to the features of the settings they encounter. This framework distinguishes 6 types of agreements and disagreements that can occur between actors involved in a conservation project (harmony, stricto sensu arrangement, deliberated arrangement, unilateral and reciprocal compromise, and locked-in), depending on whether they disagree on values or on their applications and on whether they can converge toward common values by working together. We identified key questions that conservationists should answer to adapt their strategy to the disagreements they encounter and identified relevant participatory processes to complete the adaptation.     

Mitigation translocation as a management tool

Mitigation translocation is a subgroup of conservation translocation, categorized by a crisis-responsive time frame and the immediate goal of relocating individuals threatened with death. However, the relative successes of conservation translocations with longer time frames and broader metapopulation- and ecosystem-level considerations have been used to justify the continued implementation of mitigation translocations without adequate post hoc monitoring to confirm their effectiveness as a conservation tool. Mitigation translocations now outnumber other conservation translocations, and understanding the effectiveness of mitigation translocations is critical given limited global conservation funding especially if the mitigation translocations undermine biodiversity conservation by failing to save individuals. We assessed the effectiveness of mitigation translocations by conducting a quantitative review of the global literature. A total of 59 mitigation translocations were reviewed for their adherence to the adaptive scientific approach expected of other conservation translocations and for the testing of management options to continue improving techniques for the future. We found that mitigation translocations have not achieved their potential as an effective applied science. Most translocations focused predominantly on population establishment- and persistence-level questions, as is often seen in translocations more broadly, and less on metapopulation and ecosystem outcomes. Questions regarding the long-term impacts to the recipient ecosystem (12% of articles) and the carrying capacity of translocation sites (24% of articles) were addressed least often, despite these factors being more likely to influence ultimate success. Less than half (47%) of studies included comparison of different management techniques to facilitate practitioners selecting the most effective management actions for the future. To align mitigation translocations with the relative success of other conservation translocations, it is critical that future mitigation translocations conform to an established experimental approach to improve their effectiveness. Effective mitigation translocations will require significantly greater investment of time, expertise, and resources in the future.     

The case for embedding researchers in conservation agencies

Although protected areas represent a pivotal response to escalating anthropogenic threats, they face many pressures, inside and outside their boundaries. Amid these challenges, effective conservation is guided by evidence-based decision making supported by dynamic processes of learning and knowledge exchange. Although different models promote knowledge exchange, embedding research scientists within conservation agencies is best suited to supporting evidence-based conservation. Based on available literature and our experiences on several continents, we considered the benefits, challenges, and opportunities associated with embedding research scientists within conservation agencies and the research required to better understand the effectiveness of the embedding model for evidence-based conservation. Embedded researchers provide long-term commitment to building social capital among academic and nonacademic stakeholders; act as skilled gatekeepers who increase 2-way flow of knowledge between scientists and managers; attract, coordinate, and support management-relevant external research projects; drive the design and maintenance of long-term monitoring; and align their research with information needs. Notwithstanding the many benefits, research capacity of conservation agencies is declining worldwide. A significant challenge is that the values, structures, functions, and effectiveness of the embedding model of knowledge exchange remain poorly evaluated and documented. Also, embedded researchers have to balance their desire for creativity and flexibility with the standardization and quality control required by their public sector agencies; may be perceived as not credible because they are not truly independent of their agency; and have to couple scientific productivity with skills for transdisciplinary research, social facilitation, and stakeholder engagement. Systematic research on embedding and other models of knowledge exchange, across different world contexts, is required to better understand the benefits, costs, and institutional arrangements associated with different models.     

Reserve design to optimize functional connectivity and animal density

Ecological distance-based spatial capture–recapture models (SCR) are a promising approach for simultaneously estimating animal density and connectivity, both of which affect spatial population processes and ultimately species persistence. We explored how SCR models can be integrated into reserve-design frameworks that explicitly acknowledge both the spatial distribution of individuals and their space use resulting from landscape structure. We formulated the design of wildlife reserves as a budget-constrained optimization problem and conducted a simulation to explore 3 different SCR-informed optimization objectives that prioritized different conservation goals by maximizing the number of protected individuals, reserve connectivity, and density-weighted connectivity. We also studied the effect on our 3 objectives of enforcing that the space-use requirements of individuals be met by the reserve for individuals to be considered conserved (referred to as home-range constraints). Maximizing local population density resulted in fragmented reserves that would likely not aid long-term population persistence, and maximizing the connectivity objective yielded reserves that protected the fewest individuals. However, maximizing density-weighted connectivity or preemptively imposing home-range constraints on reserve design yielded reserves of largely spatially compact sets of parcels covering high-density areas in the landscape with high functional connectivity between them. Our results quantify the extent to which reserve design is constrained by individual home-range requirements and highlight that accounting for individual space use in the objective and constraints can help in the design of reserves that balance abundance and connectivity in a biologically relevant manner.     

An introduction to decision science for conservation

Biodiversity conservation decisions are difficult, especially when they involve differing values, complex multidimensional objectives, scarce resources, urgency, and considerable uncertainty. Decision science embodies a theory about how to make difficult decisions and an extensive array of frameworks and tools that make that theory practical. We sought to improve conceptual clarity and practical application of decision science to help decision makers apply decision science to conservation problems. We addressed barriers to the uptake of decision science, including a lack of training and awareness of decision science; confusion over common terminology and which tools and frameworks to apply; and the mistaken impression that applying decision science must be time consuming, expensive, and complex. To aid in navigating the extensive and disparate decision science literature, we clarify meaning of common terms: decision science, decision theory, decision analysis, structured decision-making, and decision-support tools. Applying decision science does not have to be complex or time consuming; rather, it begins with knowing how to think through the components of a decision utilizing decision analysis (i.e., define the problem, elicit objectives, develop alternatives, estimate consequences, and perform trade-offs). This is best achieved by applying a rapid-prototyping approach. At each step, decision-support tools can provide additional insight and clarity, whereas decision-support frameworks (e.g., priority threat management and systematic conservation planning) can aid navigation of multiple steps of a decision analysis for particular contexts. We summarize key decision-support frameworks and tools and describe to which step of a decision analysis, and to which contexts, each is most useful to apply. Our introduction to decision science will aid in contextualizing current approaches and new developments, and help decision makers begin to apply decision science to conservation problems.     

Shared ways of thinking in Brazil about the science–practice interface in ecology and conservation

The debate in the literature on the science–practice interface suggests a diversity of opinions on how to link science and practice to improve conservation. Understanding this diversity is key to addressing unequal power relations, avoiding the consideration of only dominant views, and identifying strategies to link science and practice. In turn, linking science and practice should promote conservation decisions that are socially robust and scientifically informed. To identify and describe the viewpoints of scientists and decision makers on how the science–practice interface should work in order to improve conservation decisions, we interviewed Brazilian scientists (ecologists and conservation scientists, n = 11) and decision makers (n = 11). We used Q methodology and asked participants to rank their agreement with 48 statements on how the science–practice interface should work in order to improve conservation decisions. We used principal component analysis to identify shared viewpoints. The predominant viewpoint, shared by scientists and decision makers, was characterized by valuing the integration of scientific and strategic knowledge to address environmental problems. The second viewpoint, held mostly by decision makers, was distinguished by assigning great importance to science in the decision-making process and calling for problem-relevant research. The third viewpoint, shared only by scientists, was characterized by an unwillingness to collaborate and a perception of scientists as producers of knowledge that may help decision makers. Most participants agreed organizations should promote collaboration and that actors and knowledge from both science and practice are relevant. Disagreements concerned specific roles assigned to actors, willingness to collaborate, and organizational and institutional arrangements considered effective to link science and practice. Our results suggest there is ample room for collaborations and that impediments lie mainly in existing organizations and formal institutional arrangements rather than in negative attitudes between scientists and decision makers.     

Understanding conflicting cultural models of outdoor cats to overcome conservation impasse

Many conservation conflicts are scientifically complex yet are rooted in value conflicts, which result in an impasse. Additional biological information alone is insufficient to resolve this type of conflict. Conceptual models that articulate the material aspects of a system are increasingly used to identify areas where parties disagree. Yet, modeling processes typically follow the conveners’ rules for discussing and assessing the topic, which can exacerbate conflict. Researchers have identified a need for processes that require participants to reflect on the limits of their own philosophical assumptions and acknowledge other perspectives. Cultural models are a promising tool for this purpose because they include nonmaterial beliefs, morals, and values that guide people's understanding of how to interact with an issue, sometimes subconsciously. We explored how cultural models used with conceptual models can improve understanding of value conflicts and used outdoor cat management as a case study. We conducted interviews and focus group discussions with wildlife conservation and cat welfare professionals involved in outdoor cat policy discussions in Hawaii and Washington, D.C. From these conversations, we developed a conceptual model of the outdoor cat management system and cultural models that led stakeholders to weigh elements of the conceptual model differently. Although wildlife conservation professionals generally spoke about outdoor cats as invasive species, cat welfare professionals spoke about them as homeless pets. These conflicting conceptualizations of what an outdoor cat is may help explain the root of many long-standing disagreements. Examining how and when stakeholders invoke different cultural models allowed us to identify management actions that work with, rather than challenge, those models. Dialogue that embraces conflicting cultural models can be difficult and uncomfortable, but has great potential to overcome conservation impasse and achieve lasting conservation results.     

Quantifying the probability of detection of wild ungulates with the Judas technique

The Judas technique is often used in control or eradication of particular vertebrate pests. The technique exploits the tendency of individuals to form social groups. A radio collar is affixed to an individual and its subsequent monitoring facilitates the detection of other conspecifics. Efficacy of this technique would be improved if managers could estimate the probability that a Judas individual would detect conspecifics. To calculate this probability, we estimated association rates of Judas individuals with other Judas individuals, given the length of time the Judas has been deployed. We developed a simple model of space-use for individual Judas animals and constrained detection probabilities to those specific areas. We then combined estimates for individual Judas animals to infer the probability that a wild individual could be detected in an area of interest via Judas surveillance. We illustrated the method by using data from a feral goat eradication program on Isla Santiago, Galápagos, and a feral pig eradication program on Santa Cruz Island, California. Association probabilities declined as the proximity between individual areas of use of a Judas pair decreased. Unconditional probabilities of detection within individual areas of use averaged 0.09 per month for feral pigs and 0.11 per month for feral goats. Probabilities that eradication had been achieved, given no detections of wild conspecifics, and an uninformative prior probability of eradication were 0.79 (90% CI 0.22–0.99) for feral goats and 0.87 (90% CI 0.44–1.0) for feral pigs. We envisage several additions to the analyses used that could improve estimates of Judas detection probability. Analyses such as these can help managers increase the efficacy of eradication efforts, leading to more effective effects to restore native biodiversity.     

Evaluating Children's Conservation Biology Learning at the Zoo

Millions of children visit zoos every year with parents or schools to encounter wildlife firsthand. Public conservation education is a requirement for membership in professional zoo associations. However, in recent years zoos have been criticized for failing to educate the public on conservation issues and related biological concepts, such as animal adaptation to habitats. I used matched pre‐ and postvisit mixed methods questionnaires to investigate the educational value of zoo visits for children aged 7–15 years. The questionnaires gathered qualitative data from these individuals, including zoo‐related thoughts and an annotated drawing of a habitat. A content analysis of these qualitative data produced the quantitative data reported in this article. I evaluated the relative learning outcomes of educator‐guided and unguided zoo visits at London Zoo, both in terms of learning about conservation biology (measured by annotated drawings) and changing attitudes toward wildlife conservation (measured using thought‐listing data). Forty‐one percent of educator‐guided visits and 34% of unguided visits resulted in conservation biology‐related learning. Negative changes in children's understanding of animals and their habitats were more prevalent in unguided zoo visits. Overall, my results show the potential educational value of visiting zoos for children. However, they also suggest that zoos’ standard unguided interpretive materials are insufficient for achieving the best outcomes for visiting children. These results support a theoretical model of conservation biology learning that frames conservation educators as toolmakers who develop conceptual resources to enhance children's understanding of science. Evaluación del Aprendizaje de Biología de la Conservación por Niños en el Zoológico Jensen     

Applying a values-based decision process to facilitate comanagement of threatened species in Aotearoa New Zealand

Ko koe ki tēnā, ko ahau ki tēnai kīwai o te kete (you at that, and I at this handle of the basket). This Māori (New Zealanders of indigenous descent) saying conveys the principle of cooperation—we achieve more through working together, rather than separately. Despite decades of calls to rectify cultural imbalance in conservation, threatened species management still relies overwhelmingly on ideas from Western science and on top-down implementation. Values-based approaches to decision making can be used to integrate indigenous peoples’ values into species conservation in a more meaningful way. We used such a values-based method, structured decision making, to develop comanagement of pekapeka (Mystacina tuberculata) (short-tailed bat) and tara iti (Sternula nereis davisae) (Fairy Tern) between Māori and Pākehā (New Zealanders of European descent). We implemented this framework in a series of workshops in which facilitated discussions were used to gather expert knowledge to predict outcomes and make management recommendations. For both species, stakeholders clearly stated their values as fundamental objectives from the start, which allowed alternative strategies to be devised that naturally addressed their diverse values, including mātauranga Māori (Māori knowledge and perspectives). On this shared basis, all partners willingly engaged in the process, and decisions were largely agreed to by all. Most expectations of conflicts between values of Western science and Māori culture were unfounded. Where required, positive compromises were made by jointly developing alternative strategies. The values-based process successfully taha wairua taha tangata (brought both worlds together to achieve the objective) through codeveloped recovery strategies. This approach challenges the traditional model of scientists first preparing management plans focused on biological objectives, then consulting indigenous groups for approval. We recommend values-based approaches, such as structured decision making, as powerful methods for development of comanagement conservation plans between different peoples.     

Climate suitability as a predictor of conservation translocation failure

The continuing decline and loss of biodiversity has caused an increase in the use of interventionist conservation tools, such as translocation. However, many translocation attempts fail to establish viable populations, with poor release site selection often flagged as an inhibitor of success. We used species distribution models (SDMs) to predict the climate suitability of 102 release sites for amphibians, reptiles, and terrestrial insects and compared suitability predictions between successful and failed attempts. We then quantified the importance of climate suitability relative to 5 other variables frequently considered in the literature as important determinants of translocation success: number of release years, number of individuals released, life stage released, origin of the source population, and position of the release site relative to the species’ range. Probability of translocation success increased as predicted climate suitability increased and this effect was the strongest among the variables we considered, accounting for 48.3% of the variation in translocation outcome. These findings should encourage greater consideration of climate suitability when selecting release sites for conservation translocations and we advocate the use of SDMs as an effective way to do this.     

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.     

Conservation and Adaptation to Climate Change

Abstract: The need to adapt to climate change has become increasingly apparent, and many believe the practice of biodiversity conservation will need to alter to face this challenge. Conservation organizations are eager to determine how they should adapt their practices to climate change. This involves asking the fundamental question of what adaptation to climate change means. Most studies on climate change and conservation, if they consider adaptation at all, assume it is equivalent to the ability of species to adapt naturally to climate change as stated in Article 2 of the United Nations Framework Convention on Climate Change. Adaptation, however, can refer to an array of activities that range from natural adaptation, at one end of the spectrum, to sustainability science in coupled human and natural systems at the other. Most conservation organizations deal with complex systems in which adaptation to climate change involves making decisions on priorities for biodiversity conservation in the face of dynamic risks and involving the public in these decisions. Discursive methods such as analytic deliberation are useful for integrating scientific knowledge with public perceptions and values, particularly when large uncertainties and risks are involved. The use of scenarios in conservation planning is a useful way to build shared understanding at the science–policy interface. Similarly, boundary organizations—organizations or institutions that bridge different scales or mediate the relationship between science and policy—could prove useful for managing the transdisciplinary nature of adaptation to climate change, providing communication and brokerage services and helping to build adaptive capacity. The fact that some nongovernmental organizations (NGOs) are active across the areas of science, policy, and practice makes them well placed to fulfill this role in integrated assessments of biodiversity conservation and adaptation to climate change.