Finding Common Ground between Adaptive Management and Evidence-Based Approaches to Biodiversity Conservation

Language inclusion in ecological systematic reviews and maps: Barriers and perspectives

Systematic reviews and maps are considered a reliable form of research evidence, but often neglect non-English-language literature, which can be a source of important evidence. To understand the barriers that might limit authors' ability or intent to find and include non-English-language literature, we assessed factors that may predict the inclusion of non-English-language literature in ecological systematic reviews and maps, as well as the review authors' perspectives. We assessed systematic reviews and maps published in Environmental Evidence (n = 72). We also surveyed authors from each paper (n = 32 responses), gathering information on the barriers to the inclusion of non-English language literature. 44% of the reviewed papers (32/72) excluded non-English literature from their searches and inclusions. Commonly cited reasons included constraints related to resources and time. Regression analysis revealed that reviews with larger author teams, authors from diverse countries, especially those with non-English primary languages, and teams with multilingual capabilities searched in a significantly greater number of non-English languages. Our survey exposed limited language diversity within the review teams and inadequate funding as the principal barriers to incorporating non-English language literature. To improve language inclusion and reduce bias in systematic reviews and maps, our study suggests increasing language diversity within review teams. Combining machine translation with language skills can alleviate the financial and resource burdens of translation. Funding applications could also include translation costs. Additionally, establishing language exchange systems would enable access to information in more languages. Further studies investigating language inclusion in other journals would strengthen these conclusions.

Scaling artificial light at night and disease vector interactions into socio-ecological systems: a conceptual appraisal

There is burgeoning interest in how artificial light at night (ALAN) interacts with disease vectors, particularly mosquitoes. ALAN can alter mosquito behaviour and biting propensity, and so must alter disease transfer rates. However, most studies to date have been laboratory-based, and it remains unclear how ALAN modulates disease vector risk. Here, we identify five priorities to assess how artificial light can influence disease vectors in socio-ecological systems. These are to (i) clarify the mechanistic role of artificial light on mosquitoes, (ii) determine how ALAN interacts with other drivers of global change to influence vector disease dynamics across species, (iii) determine how ALAN interacts with other vector suppression strategies, (iv) measure and quantify the impact of ALAN at scales relevant for vectors, and (v) overcome the political and social barriers in implementing it as a novel vector suppression strategy. These priorities must be addressed to evaluate the costs and benefits of employing appropriate ALAN regimes in complex socio-ecological systems if it is to reduce disease burdens, especially in the developing world. This article is part of the theme issue 'Light pollution in complex ecological systems'.

Bayesian areal disaggregation regression to predict wildlife distribution and relative density with low-resolution data

For species of conservation concern and human-wildlife conflict, it is imperative that spatial population data be available to design adaptive-management strategies and be prepared to meet challenges such as land use and climate change, disease outbreaks, and invasive species spread. This can be difficult, perhaps impossible, if spatially explicit wildlife data are not available. Low-resolution areal counts, however, are common in wildlife monitoring, that is, the number of animals reported for a region, usually corresponding to administrative subdivisions, for example, region, province, county, departments, or cantons. Bayesian areal disaggregation regression is a solution to exploit areal counts and provide conservation biologists with high-resolution species distribution predictive models. This method originated in epidemiology but lacks experimentation in ecology. It provides a plethora of applications to change the way we collect and analyze data for wildlife populations. Based on high-resolution environmental rasters, the disaggregation method disaggregates the number of individuals observed in a region and distributes them at the pixel level (e.g., 5 × 5 km or finer resolution), thereby converting low-resolution data into a high-resolution distribution and indices of relative density. In our demonstrative study, we disaggregated areal count data from hunting bag returns to disentangle the changing distribution and population dynamics of three deer species (red, sika, and fallow) in Ireland from 2000 to 2018. We show an application of the Bayesian areal disaggregation regression method and document marked increases in relative population density and extensive range expansion for each of the three deer species across Ireland. We challenged our disaggregated model predictions by correlating them with independent deer surveys carried out in field sites and alternative deer distribution models built using presence-only and presence-absence data. Finding a high correlation with both independent data sets, we highlighted the ability of Bayesian areal disaggregation regression to accurately capture fine-scale spatial patterns of animal distribution. This study uncovers new scenarios for wildlife managers and conservation biologists to reliably use regional count data disregarded so far in species distribution modeling. Thus, it represents a step forward in our ability to monitor wildlife population and meet challenges in our changing world.

AIMS for wildlife: Developing an automated interactive monitoring system to integrate real-time movement and environmental data for true adaptive management

To effectively manage species and habitats at multiple scales, population and land managers require rapid information on wildlife use of managed areas and responses to landscape conditions and management actions. GPS tracking studies of wildlife are particularly informative to species ecology, habitat use, and conservation. Combining GPS data with administrative data and a diverse suite of remotely sensed, geo-referenced environmental (e.g., climatic) data, would more comprehensively inform how animals interact with and utilize habitats and ecosystems and our goal was to create a conceptual model for a system that would accomplish this - the 'Automated Interactive Monitoring System (AIMS) for Wildlife'. Our objective for this study was to develop a Customized Wildlife Report (CWR) - the first AIMS for Wildlife deliverable product. CWRs collate and summarize our 8-year GPS tracking dataset of ∼11 million locations from 1338 individual (16 species) avifauna and make actionable, real-time data on animal movements and trends in a specific area of interest available to managers and stakeholders for rapid application in day-to-day management. The CWR exemplar presented in this paper was developed to address needs identified by habitat managers of Sacramento National Wildlife Refuge and illustrates the highly specific, information offered and how it contributes to assessing the efficacy of conservation actions while allowing for near real-time adaptive management. The report can be easily customized for any of the thousands of wildlife refuges or regional areas of interest in the United States, emphasizing the broad application of an animal movement data stream. Utilizing diverse, extensive telemetry data streams through scientific collaboration can aid managers and conservation stakeholders with short and long-term research and conservation planning and help address a cadre of issues from local-scale habitat management to improving the understanding of landscape level impacts like drought, wildfire, and climate change on wildlife populations.

Diversity of perspectives in biodiversity conservation: A case study of port land use in Antwerp and Rotterdam

Conflicts of interest often undermine conservation initiatives against biodiversity decline. Effective decision-making requires a deeper understanding of the positions, criteria, concerns, and perspectives of stakeholders. However, managing so many perspectives can be difficult, and if not done well, conflicts arise which make it difficult to achieve conservation goals. The purpose of this study is to demonstrate that identifying areas of consensus is a good starting point to generate more effective debates and address complex issues. To do this, we investigate the diversity of perspectives regarding biodiversity conservation schemes among stakeholders in the studied ports of Antwerp and Rotterdam. Using Q-methodology, a semi-quantitative technique that enables us to systematically study the subjective views of stakeholders involved in a topic, we identified and organized a range of shared perspectives into three groups, known as factors. A total of 20 participants sorted 45 statements according to their perceptions and objectives, from -4 'most disagreeable' to 4 'most agreeable'. Then, respondents explained their rankings in a post-sorting interview. Next, the data was analyzed quantitatively and qualitatively. The quantitative analysis was conducted in two parts: (i) Dividing respondents into groups based on similar perspectives and (ii) coupling distinguishing statements with one of the factors characteristic of that viewpoint. Finally, in a qualitative analysis, we used the distinguishing statements and insights from interviews to create narratives and titles for the three factors: (1) Ports are key for our economic wealth, hence port development should continue, (2) Nature first, and (3) Multi-actor governance. Our findings confirm consensuses in three areas: policy, land use, and mitigation tactics. Interestingly, all narratives unanimously agreed on the importance of regulating port development and land use changes via legislation and environmental impact assessments. However, they debated the rigidity of legislation and whether offsetting port expansion (and associated land and resource use claims) should take place locally or internationally. We also found that decision-making mostly followed a human-centered perspective, where economic values were more relevant than intrinsic ones. These insights can serve as a baseline for stakeholders to form coalitions around areas of consensus to depolarize debates and avoid decision-making gridlocks.

Adaptive Management of Flows in a Regulated River: Flow-ecology Relationships Revealed by a 26-year, Five-treatment Flow Experiment

Adaptive management (AM) is often proposed as a means to resolve uncertainty in the management of socio-ecological systems but successful implementation of AM is rare. We report results from a 26 year, five-treatment, AM experiment designed to inform decision makers about the response of juvenile salmonids (Oncorhynchus spp.) to flow releases from a dam on the regulated Bridge River, British Columbia, Canada. Treatments consisted of a baseline (no dam release) and four different dam release regimes that followed a semi-natural hydrograph but varied in the magnitude of spring-summer freshet flows. We found total salmonid biomass was highest at the lowest flow release, and decreased with increasing flow, consistent with a priori predictions made by an expert solicitation process. Species-specific responses were observed that in some cases could be attributed to interactions between the flow regime and life history. The relationship between juvenile biomass and flow resulting from the experiment can inform decisions on water management for this river. The documentation of successful AM experiments is sorely needed to allow for reflection on the circumstances when AM is likely to deliver desirable outcomes, and to improve other decision processes that require fewer resources and less time to implement.

Understanding and overcoming obstacles in adaptive management

Adaptive management (AM) is widely promoted to improve management of natural resources, yet its implementation is challenging. We show that obstacles to the implementation of AM are related not only to the AM process per se but also to external factors such as ecosystem properties and governance systems. To overcome obstacles, there is a need to build capacities within the AM process by ensuring adequate resources, management tools, collaboration, and learning. Additionally, building capacities in the legal and institutional frames can enable the necessary flexibility in the governance system. Furthermore, in systems experiencing profound changes in wildlife populations, building such capacities may be even more critical as more flexibility will be needed to cope with increased uncertainty and changed environmental conditions.

Loss of temporal structure of tropical soundscapes with intensifying land use in Borneo

Conservation and sustainable management efforts in tropical forests often lack reliable, effective, and easily-communicated ways to measure the biodiversity status of a protected or managed landscape. The sounds that many tropical species make can be recorded by pre-programmed devices and analysed to yield measures of biodiversity. Interpreting the resulting soundscapes has developed along two paths: analysing the whole soundscape using acoustic indices, used as a proxy of biodiversity, or focusing on individual species that can be either manually or automatically recognized from the soundscape. Here we develop an intermediate approach to divide the soundscape into frequency categories belonging to broad taxonomic groups of vocalizing animals. While the method was unable to distinguish between amphibian and mammal communities, it was successful in assigning parts of the soundscape as likely produced by birds and insects. Applying the approach in Borneo revealed that, with increasing land use intensity, i) the spectral saturation of the soundscape, a proxy of species richness, loses dawn and dusk peaks, ii) bird acoustic communities lose recurrent diurnal patterns, becoming less synchronized across sites, and that iii) insect Soundscape Saturation increases at night. If soundscapes are partitioned similarly in different regions, our method could be used to bridge soundscape-level and individual-species level analyses. Regaining dawn and dusk peaks, the synchrony of bird acoustic communities, and losing nocturnal dominance of insect could be used as a set of simple indicators of tropical forest retaining high levels of biodiversity.

Identifying and prioritising climate change adaptation actions for greater one-horned rhinoceros (Rhinoceros unicornis) conservation in Nepal

Climate change has started impacting species, ecosystems, genetic diversity within species, and ecological interactions and is thus a serious threat to conserving biodiversity globally. In the absence of adequate adaptation measures, biodiversity may continue to decline, and many species will possibly become extinct. Given that global temperature continues to increase, climate change adaptation has emerged as an overarching framework for conservation planning. We identified both ongoing and probable climate change adaptation actions for greater one-horned rhinoceros conservation in Nepal through a combination of literature review, key informant surveys (n = 53), focus group discussions (n = 37) and expert consultation (n = 9), and prioritised the identified adaptation actions through stakeholder consultation (n = 17). The majority of key informants (>80%) reported that climate change has been impacting rhinoceros, and more than 65% of them believe that rhinoceros habitat suitability in Nepal has been shifting westwards. Despite these perceived risks, climate change impacts have not been incorporated well into formal conservation planning for rhinoceros. Out of 20 identified adaptation actions under nine adaptation strategies, identifying and protecting climate refugia, restoring the existing habitats through wetland and grassland management, creating artificial highlands in floodplains to provide rhinoceros with refuge during severe floods, and translocating them to other suitable habitats received higher priority. These adaptation actions may contribute to reducing the vulnerability of rhinoceros to the likely impacts of climate change. This study is the first of its kind in Nepal and is expected to provide a guideline to align ongoing conservation measures into climate change adaptation planning for rhinoceros. Further, we emphasise the need to integrating likely climate change impacts while planning for rhinoceros conservation and initiating experimental research and monitoring programs to better inform adaptation planning in the future.

Appraising strategic adaptive management as a process of organizational learning

Adaptive management is a systematic approach for linking learning with implementation to facilitate ongoing improvement in natural resource management. The idea of learning from experience and adapting subsequent policies, strategies and actions, is intuitively appealing. However, application of adaptive management has been hindered by several obstacles, including a paucity of documented lessons from existing adaptive management practices and inadequate attention to the complex social aspects of learning. Here we address these two impediments through (i) a case study of an established version of adaptive management and its application in the context of protected area management plans, and (ii) its critical comparison and conceptual integration with the seminal theory of organizational knowledge creation (TOKC), which emphasizes the social aspects of learning. As case study, we focus on Strategic Adaptive Management (SAM), which has been iteratively developed and implemented by South African National Parks for more than 20 years. We used TOKC as a conceptual sounding board to reflect on and appraise the learning that takes place through SAM. A comparison of the main steps of the SAM cycle with corresponding stages outlined by TOKC revealed remarkable complementarity between these two approaches, but also important differences. The conceptual comparison deepened our understanding of SAM's learning performance as well as potential, revealing strengths, weaknesses and opportunities for improvement. Key insights include that valuable and different forms of learning takes place during each step of the SAM cycle. This learning can be enhanced through careful attention to approaches for creating, sharing and making explicit the tacit knowledge of individuals. Furthermore, dialogue and co-learning with stakeholders should be maintained beyond the visioning and objectives setting step of SAM. Based on insights gained, we developed a new and complementary conceptualization of SAM, as a spiraling process of organizational learning enabled by the interplay between tacit and explicit forms of knowledge, which in turn is mediated by different types of social interactions, media and engagement with practice. We believe that this conceptualization can help to better acknowledge and enable learning as one of the most fundamental purposes and outcomes of SAM, and adaptive management more generally.

A niche for null models in adaptive resource management

As global systems rapidly change, our collective ability to predict future ecological dynamics will become increasingly important for successful natural resource management. By merging stakeholder objectives with system uncertainty, and by adapting actions to changing systems and knowledge, adaptive resource management (ARM) provides a rigorous platform for making sound decisions in a changing world. Critically, however, applications of ARM could be improved by employing benchmarks (i.e., points of reference) for determining when learning is occurring through the cycle of monitoring, modeling, and decision-making steps in ARM. Many applications of ARM use multiple model-based hypotheses to identify and reduce systematic uncertainty over time, but generally lack benchmarks for gauging discovery of scientific evidence and learning. This creates the danger of thinking that directional changes in model weights or rankings are indicative of evidence for hypotheses, when possibly all competing models are inadequate. There is thus a somewhat obvious, but yet to be filled niche for including benchmarks for learning in ARM. We contend that carefully designed "ecological null models," which are structured to produce an expected ecological pattern in the absence of a hypothesized mechanism, can serve as suitable benchmarks. Using a classic case study of mallard harvest management that is often used to demonstrate the successes of ARM for learning about ecological mechanisms, we show that simple ecological null models, such as population persistence (Nt +1 = Nt ), provide more robust near-term forecasts of population abundance than the currently used mechanistic models. More broadly, ecological null models can be used as benchmarks for learning in ARM that trigger the need for discarding model parameterizations and developing new ones when prevailing models underperform the ecological null model. Identifying mechanistic models that surpass these benchmarks will improve learning through ARM and help decision-makers keep pace with a rapidly changing world.

Heuristics for the sustainable harvest of wildlife in stochastic social-ecological systems

Sustainable wildlife harvest is challenging due to the complexity of uncertain social-ecological systems, and diverse stakeholder perspectives of sustainability. In these systems, semi-complex stochastic simulation models can provide heuristics that bridge the gap between highly simplified theoretical models and highly context-specific case-studies. Such heuristics allow for more nuanced recommendations in low-knowledge contexts, and an improved understanding of model sensitivity and transferability to novel contexts. We develop semi-complex Management Strategy Evaluation (MSE) models capturing dynamics and variability in ecological processes, monitoring, decision-making, and harvest implementation, under a diverse range of contexts. Results reveal the fundamental challenges of achieving sustainability in wildlife harvest. Environmental contexts were important in determining optimal harvest parameters, but overall, evaluation contexts more strongly influenced perceived outcomes, optimal harvest parameters and optimal harvest strategies. Importantly, simple composite metrics popular in the theoretical literature (e.g. focusing on maximizing yield and population persistence only) often diverged from more holistic composite metrics that include a wider range of population and harvest objectives, and better reflect the trade-offs in real world applied contexts. While adaptive harvest strategies were most frequently preferred, particularly for more complex environmental contexts (e.g. high uncertainty or variability), our simulations map out cases where these heuristics may not hold. Despite not always being the optimal solution, overall adaptive harvest strategies resulted in the least value forgone, and are likely to give the best outcomes under future climatic variability and uncertainty. This demonstrates the potential value of heuristics for guiding applied management.

Integrating advances in population and evolutionary ecology with conservation strategy through long-term studies of red-billed choughs

Conceptual and methodological advances in population and evolutionary ecology are often pursued with the ambition that they will help identify demographic, ecological and genetic constraints on population growth rate (λ), and ultimately facilitate evidence-based conservation. However, such advances are often decoupled from conservation practice, impeding translation of scientific understanding into effective conservation and of conservation-motivated research into wider conceptual understanding. We summarise key outcomes from long-term studies of a red-billed chough Pyrrhocorax pyrrhocorax population of conservation concern, where we proactively aimed to achieve the dual and interacting objectives of advancing population and evolutionary ecology and advancing effective conservation. Estimation of means, variances and covariances in key vital rates from individual-based demographic data identified temporal and spatial variation in subadult survival as key constraints on λ, and simultaneously provided new insights into how vital rates can vary as functions of demographic structure, natal conditions and parental life history. Targeted analyses showed that first-year survival increased with prey abundance, implying that food limitation may constrain λ. First-year survival then decreased dramatically, threatening population viability and prompting emergency supplementary feeding interventions. Detailed evaluations suggested that the interventions successfully increased first-year survival in some years and additionally increased adult survival and successful reproduction, thereby feeding back to inform intervention refinements and understanding of complex ecological constraints on λ. Genetic analyses revealed novel evidence of expression of a lethal recessive allele, and demonstrated how critically small effective population size can arise, thereby increasing inbreeding and loss of genetic variation. Population viability analyses parameterised with all available demographic and genetic data showed how ecological and genetic constraints can interact to limit population viability, and identified ecological management as of primacy over genetic management to ensure short-term persistence of the focal population. This case study demonstrates a full iteration through the sequence of primary science, evidence-based intervention, quantitative evaluation and feedback that is advocated in conservation science but still infrequently achieved. It thereby illustrates how pure science advances informed conservation actions to ensure the (short-term) stability of the target population, and how conservation-motivated analyses fed back to advance fundamental understanding of population processes.

Cloud-Based Environmental Monitoring to Streamline Remote Sensing Analysis for Biologists

Timely, policy-relevant monitoring data are essential for evaluating the effectiveness of environmental policies and conservation measures. Satellite and aerial imagery can fill data gaps at low cost but are often underused for ongoing environmental monitoring. Barriers include a lack of expertise or computational resources and the lag time between image acquisition and information delivery. Online image repositories and cloud computing platforms are increasingly used by researchers because they offer near-real-time, centralized access to local-to-global-scale data sets and analytics with minimal in-house computational requirements. We aim to broaden knowledge of these open access resources for biologists whose work routinely informs policy and management. To illustrate potential applications of cloud-based environmental monitoring (CBEM), we developed an adaptable approach to detect changes in natural vegetative cover in an agricultural watershed. The steps we describe can be applied to identify opportunities and caveats for applying CBEM in a wide variety of monitoring programs.

Managing Groundwater to Ensure Ecosystem Function

Groundwater is a critical resource not only for human communities but also for many terrestrial, riparian, and aquatic ecosystems and species. Yet groundwater planning and management decisions frequently ignore or inadequately address the needs of these natural systems. As a consequence, ecosystems dependent on groundwater have been threatened, degraded, or eliminated, especially in arid regions. There is growing acknowledgment that governmental protections for these ecological resources are necessary, but current legal, regulatory and voluntary provisions are often inadequate. Groundwater management premised on "safe yield," which aims to balance human withdrawals with natural recharge rates, typically provides little to no consideration for water needed by ecosystems. Alternatively, the "sustainable yield" concept aims to integrate social, economic and environmental needs for groundwater, but the complexity of groundwater systems creates substantial uncertainty about the impact that current or future groundwater withdrawals will have on ecosystems. Regardless of the legal or regulatory framework, guidance is needed to help ensure environmental water needs will be met, especially in the face of pressure to increase human uses of groundwater resources. In this paper, we describe minimum provisions for planning, managing, and monitoring groundwater that collectively can lower the risk of harm to groundwater-dependent ecosystems and species, with a special emphasis on arid systems, where ecosystems and species may be especially reliant upon and sensitive to groundwater dynamics.

"Health in" and "Health of" Social-Ecological Systems: A Practical Framework for the Management of Healthy and Resilient Agricultural and Natural Ecosystems

The past two decades have seen an accumulation of theoretical and empirical evidence for the interlinkages between human health and well-being, biodiversity and ecosystem services, and agriculture. The COVID-19 pandemic has highlighted the devastating impacts that an emerging pathogen, of animal origin, can have on human societies and economies. A number of scholars have called for the wider adoption of “One Health integrated approaches” to better prevent, and respond to, the threats of emerging zoonotic diseases. However, there are theoretical and practical challenges that have precluded the full development and practical implementation of this approach. Whilst integrated approaches to health are increasingly adopting a social-ecological system framework (SES), the lack of clarity in framing the key concept of resilience in health contexts remains a major barrier to its implementation by scientists and practitioners. We propose an operational framework, based on a transdisciplinary definition of Socio-Ecological System Health (SESH) that explicitly links health and ecosystem management with the resilience of SES, and the adaptive capacity of the actors and agents within SES, to prevent and cope with emerging health and environmental risks. We focus on agricultural transitions that play a critical role in disease emergence and biodiversity conservation, to illustrate the proposed participatory framework to frame and co-design SESH interventions. Finally, we highlight critical changes that are needed from researchers, policy makers and donors, in order to engage communities and other stakeholders involved in the management of their own health and that of the underpinning ecosystems.

Fostering a Wildlife-Friendly Program for Sustainable Coffee Farming: The Case of Small-Holder Farmers in Indonesia

There is an urgent need for a global transition to sustainable and wildlife-friendly farming systems that provide social and economic equity and protect ecosystem services on which agriculture depends. Java is home to 60% of Indonesia’s population and harbors many endemic species; thus, managing agriculture alongside human well-being and biodiversity is vital. Within a community of ~400 coffee farmers in the province of West Java, we assessed the steps to develop a wildlife-friendly program until reaching certification between February 2019 and October 2020. We adopted an adaptive management approach that included developing common objectives through a process of stakeholder consultation and co-learning. We firstly investigated via interviews the expectations and the issues encountered by 25 farmers who converted to organic production in 2016. Their main expectations were an increase in income and an increase in coffee quality, while they had issues mainly in finding high quality fertilizers, reducing pests, and increasing productivity. We used this information to establish a problem-solving plan for the transition to community-wide wildlife-friendly practices. As part of the adaptive evaluation, we assessed the quality of coffee plantations before and after the implementation of coproduced actions. The quality of coffee significantly improved after our interventions to reduce the coffee berry borer, especially in the fields that started as inorganic and converted to organic. We uncovered additional issues to meet the standards for certification, including banning hunting and trapping activities and increasing coffee quality for international export. We describe the coproduced actions (agroforestry, conservation education, local law, organic alternatives) and phases of the program and discuss the potential barriers. We provide novel evidence of adaptive management framework successfully used to implement management actions and reach shared goals.

Horizon scanning for South African biodiversity: A need for social engagement as well as science

A horizon scan was conducted to identify emerging and intensifying issues for biodiversity conservation in South Africa over the next 5-10 years. South African biodiversity experts submitted 63 issues of which ten were identified as priorities using the Delphi method. These priority issues were then plotted along axes of social agreement and scientific certainty, to ascertain whether issues might be "simple" (amenable to solutions from science alone), "complicated" (socially agreed upon but technically complicated), "complex" (scientifically challenging and significant levels of social disagreement) or "chaotic" (high social disagreement and highly scientifically challenging). Only three of the issues were likely to be resolved by improved science alone, while the remainder require engagement with social, economic and political factors. Fortunately, none of the issues were considered chaotic. Nevertheless, strategic communication, education and engagement with the populace and policy makers were considered vital for addressing emerging issues.

What role should randomized control trials play in providing the evidence base for conservation?

The effectiveness of many widely used conservation interventions is poorly understood because of a lack of high-quality impact evaluations. Randomized control trials (RCTs), in which experimental units are randomly allocated to treatment or control groups, offer an intuitive way to calculate the impact of an intervention by establishing a reliable counterfactual scenario. As many conservation interventions depend on changing people's behaviour, conservation impact evaluation can learn a great deal from RCTs in fields such as development economics, where RCTs have become widely used but are controversial. We build on relevant literature from other fields to discuss how RCTs, despite their potential, are just one of a number of ways to evaluate impact, are not feasible in all circumstances, and how factors such as spillover between units and behavioural effects must be considered in their design. We offer guidance and a set of criteria for deciding when RCTs may be an appropriate approach for evaluating conservation interventions, and factors to consider to ensure an RCT is of high quality. We illustrate this with examples from one of the few concluded RCTs of a large-scale conservation intervention: an incentive-based conservation programme in the Bolivian Andes. We argue that conservation should aim to avoid a rerun of the polarized debate surrounding the use of RCTs in other fields. Randomized control trials will not be feasible or appropriate in many circumstances, but if used carefully they can be useful and could become a more widely used tool for the evaluation of conservation impact.