Ranger patrols are a cornerstone of wildlife protection efforts around the world and occur across all ecological governance systems. Evidence that patrols reduce threats to wildlife and enable their recovery has not been systematically examined previously. Without evidence of patrol effectiveness in varying contexts, protected area managers risk wasting limited conservation resources and lack information required to improve the effectiveness of patrols. We conducted a meta-analysis evaluating the effectiveness of terrestrial patrols for conserving African, Asian, and Latin American wildlife directly threatened by exploitation. After filtering 57 studies, we calculated effect sizes from each of the remaining 15 studies that included a comparator and measurement of wildlife abundance and calculated standardised mean difference and % change in wildlife species abundance. Results suggest tentative support that areas implementing patrols (alongside other interventions) were associated with higher wildlife abundance levels compared to time periods or locations without patrols. We were unable to confirm causality between patrols and changes in wildlife population abundance because studies were inadequately designed to evaluate and report on effectiveness. Studies commonly lacked a comparator or counterfactual event, temporal or spatial replication, and consistent and/or long-term monitoring of population abundance, and had study designs that confounded conservation actions. Further, of the 15 included studies linking wildlife abundance to patrol efforts, five also reported a reduction in a poaching threat, but only three of these used a comparator in the threat reduction evaluation. Without monitoring threat trends alongside wildlife abundance, it is difficult to be confident that patrols resulted in increases in wildlife abundance. To help evaluate patrol interventions (i.e. not only whether they work but where and under what conditions they work), we identify opportunities to improve future patrol effectiveness research and provide recommendations on how to improve the evidence base.

ABSTRACTGlobally, hundreds of thousands of rangers patrol protected areas every day. The data they collect have immense potential for monitoring biodiversity and threats to it. Technologies like SMART (Spatial Monitoring and Reporting Tool), which facilitate the management of ranger‐collected data, have enhanced this potential. However, based on our experience across diverse use cases and geographies, we have found that ranger‐based monitoring is often implemented without a clear plan for how the data will inform management and without critical evaluation of whether the data are reliable enough to meet specific monitoring goals. Here we distill six key lessons and present a decision framework to guide funders, governments, protected area managers, and NGOs toward more effective use of ranger‐based monitoring for protected area management and suggest when alternative monitoring approaches may add value. Essential considerations include the welfare and motivation of rangers, biases in patrol coverage and detectability, the capacity to analyze data, and the buy‐in of those tasked with using the data to inform management decisions. When implemented well, ranger‐based monitoring can help improve conservation outcomes through evaluating management interventions, more efficient deployment of limited law enforcement budgets to optimize the deterrence of illegal activities, and basic ecological monitoring.

Ranger‐led law enforcement patrols are the primary, site‐level response to – and the most common source of data on – illegal activity threatening wildlife in protected areas. Yet evidence that patrols effectively deter rule‐breaking is limited, and common management metrics for evaluating deterrence, which use ranger‐collected data, are particularly vulnerable to bias. “Differenced plots” (of the association between change in patrol effort and subsequent change in illegal activity) were recently proposed as a simple, new metric for deterrence, which, in tests with simulated patrol data, were more robust than the common alternatives. Here, we trial application of differenced plots to real patrol data collected in four protected areas, and explore methods for applying the metric in practice, using two indicators of rule‐breaking: snares, and people. We find evidence which is consistent with deterrence in some but not all sites, over shorter timescales than observed hitherto: increases in patrol effort were associated with subsequent reductions in snaring in one site, and in the presence of people in two sites. However, whether pressure on wildlife had been reduced or merely displaced was unclear from differenced plots, nor could the metric confirm absence of deterrence, raising questions for future applications. Our findings suggest differenced plots can be a useful metric, particularly for exploring variation in deterrence within sites, but should be applied and interpreted with care, and further work is urgently needed to determine whether and how patrols deter illegal activity, and to evaluate the effect reliably.

Conservation technology holds the potential to vastly increase conservationists' ability to understand and address critical environmental challenges, but systemic constraints appear to hamper its development and adoption. Understanding of these constraints and opportunities for advancement remains limited. We conducted a global online survey of 248 conservation technology users and developers to identify perceptions of existing tools' current performance and potential impact, user and developer constraints, and key opportunities for growth. We also conducted focus groups with 45 leading experts to triangulate findings. The technologies with the highest perceived potential were machine learning and computer vision, eDNA and genomics, and networked sensors. A total of 95%, 94%, and 92% respondents, respectively, rated them as very helpful or game changers. The most pressing challenges affecting the field as a whole were competition for limited funding, duplication of efforts, and inadequate capacity building. A total of 76%, 67%, and 55% respondents, respectively, identified these as primary concerns. The key opportunities for growth identified in focus groups were increasing collaboration and information sharing, improving the interoperability of tools, and enhancing capacity for data analyses at scale. Some constraints appeared to disproportionately affect marginalized groups. Respondents in countries with developing economies were more likely to report being constrained by upfront costs, maintenance costs, and development funding (p = 0.048, odds ratio [OR] = 2.78; p = 0.005, OR = 4.23; p = 0.024, OR = 4.26), and female respondents were more likely to report being constrained by development funding and perceived technical skills (p = 0.027, OR = 3.98; p = 0.048, OR = 2.33). To our knowledge, this is the first attempt to formally capture the perspectives and needs of the global conservation technology community, providing foundational data that can serve as a benchmark to measure progress. We see tremendous potential for this community to further the vision they define, in which collaboration trumps competition; solutions are open, accessible, and interoperable; and user-friendly processing tools empower the rapid translation of data into conservation action. Article impact statement: Addressing financing, coordination, and capacity-building constraints is critical to the development and adoption of conservation technology.

Wildlife species worldwide are under threat from a range of anthropogenic threats, with declines primarily caused by overexploitation and habitat loss associated with an increasing human population and per capita resource use. Exploitation is driven by numerous factors, but is often the result of illegal activities, such as hunting, logging, and wildlife trade. Protected areas, designed to safeguard threatened species and their habitats, are the foundation of biodiversity conservation, and several analyses have demonstrated that effective protected areas are critical to the maintenance of biodiversity. However, other analyses show that most protected areas suffer from a lack of resources and poor management. Numerous technologies have been developed to address these challenges by facilitating adaptive management via ranger-based data collection, data analysis and visualization, and strategic planning. This chapter reviews the Spatial Monitoring and Reporting Tool (SMART) platform, with a particular emphasis on conservation law enforcement monitoring, and demonstrates both how SMART has been used to improve management of conservation areas, and how complementary systems and emerging technologies can be integrated into a single unified platform for conservation area management. In a relatively short period of time, SMART has grown to become the global standard for conservation area management. More than 800 national parks and other conservation areas are currently using SMART in more than 65 countries worldwide. SMART sites have seen improvements in patrol effectiveness, increases in populations of critically endangered species like tigers, and reductions in threats from poaching and habitat loss.

Protected areas are key to biodiversity conservation and ranger-based monitoring, and law enforcement is the cornerstone upon which effective protected areas are built. Frontline practitioners, however, are often asked to protect large swathes of land or sea with limited resources, support, infrastructure, capacity, and/or training. Technology, when applied effectively and appropriately, has the capacity to empower practitioners, revolutionize ranger operations, improve ranger safety, and enhance wildlife protection and conservation outcomes. To do so, technology must be recognized, from the frontlines through to key decisionmakers, as a force multiplier, but only when it is fit for purpose, accessible, cost-effective, and supportive of rangers’ needs. In this paper we detail the general state of conservation technology and innovation within the ranger context and provide a series of detailed recommendations to help the Universal Ranger Support Alliance (URSA) meet the needs of rangers around the world, including: demystifying technology and clarifying what it can and cannot do, connecting the right technology with the right people and places, focusing technology development and investment on substantive improvements and support, broadening ranger familiarization with technology, building technology capacity in rangers, fostering greater community building and creating opportunities around technologies, engaging the technology sector to innovate and design technology to support rangers, and supporting technology as a complement to traditional knowledge and skills, rather than a replacement. These recommendations constitute an ambitious vision which cannot be delivered by URSA in isolation. Rather, we propose URSA leverages existing efforts to ensure rangers are supported around the world.

Conservationists increasingly use unstructured observational data, such as citizen science records or ranger patrol observations, to guide decision making. These datasets are often large and relatively cheap to collect, and they have enormous potential. However, the resulting data are generally "messy,'' and their use can incur considerable costs, some of which are hidden. We present an overview of the opportunities and limitations associated with messy data by explaining how the preferences, skills, and incentives of data collectors affect the quality of the information they contain and the investment required to unlock their potential. Drawing widely from across the sciences, we break down elements of the observation process in order to highlight likely sources of bias and error while emphasizing the importance of cross-disciplinary collaboration. We propose a framework for appraising messy data to guide those engaging with these types of dataset and make them work for conservation and broader sustainability applications.

SummaryWildlife is an essential component of all ecosystems. Most places in the globe do not have local, timely information on which species are present or how their populations are changing. With the arrival of new technologies, camera traps have become a popular way to collect wildlife data. However, data collection has increased at a much faster rate than the development of tools to manage, process and analyse these data. Without these tools, wildlife managers and other stakeholders have little information to effectively manage, understand and monitor wildlife populations. We identify four barriers that are hindering the widespread use of camera trap data for conservation. We propose specific solutions to remove these barriers integrated in a modern technology platform called Wildlife Insights. We present an architecture for this platform and describe its main components. We recognize and discuss the potential risks of publishing shared biodiversity data and a framework to mitigate those risks. Finally, we discuss a strategy to ensure platforms like Wildlife Insights are sustainable and have an enduring impact on the conservation of wildlife.