Rivers worldwide are now acting as major transport pathways for plastic pollution and discharge large quantities of waste into the ocean. Previous oceanographic modelling and current drifter data have been used to predict the movement and accumulation of plastic pollution in the marine environment, but our understanding of the transport and fate through riparian systems is still largely unknown. Here we undertook a proof of concept study by applying open source tracking technology (both GPS (Global Positing System) cellular networks and satellite technology), which have been successfully used in many animal movement studies, to track the movements of individual plastic litter items (500 ml PET (polyethylene terephthalate) drinks bottles) through the Ganges River system (known as the Ganga in India and the Padma and Meghna in Bangladesh, hereafter known as the Ganges) and the Bay of Bengal. Deployed tags were successfully tracked through the Ganges river system and into the Bay of Bengal marine system. The “bottle tags” were designed and built (e.g. shape, size, buoyancy) to replicate true movement patterns of a plastic bottle. The maximum distance tracked to date is 2845 km over a period of 94 days. We discuss lessons learnt from the development of these plastic litter tags, and outline how the potential widespread use of this open source technology has the ability to significantly increase understanding of the location of accumulation areas and the timing of large inputs of plastic pollution into the aquatic system. Furthermore, “bottle tags” may act as a powerful tool for stimulating social behaviour change, informing science-based policy, and as valuable educational outreach tools for public awareness.

Advancing technology represents an unprecedented opportunity to enhance our capacity to conserve the Earth's biodiversity. However, this great potential is failing to materialize and rarely endures. We contend that unleashing the power of technology for conservation requires an internationally coordinated strategy that connects the conservation community and policy-makers with technologists. We argue an international conservation technology entity could (1) provide vision and leadership, (2) coordinate and deliver key services necessary to ensure translation from innovation to effective deployment and use of technology for on-the-ground conservation across the planet, and (3) help integrate innovation into biodiversity conservation policy from local to global scales, providing tools to monitor outcomes of conservation action and progress towards national and international biodiversity targets. This proposed entity could take the shape of an international alliance of conservation institutions or a formal intergovernmental institution. Active and targeted uptake of emerging technology can help society achieve biodiversity conservation goals.

Surveillance of animal movements using electronic tags (i.e., biotelemetry) has emerged as an essential tool for both basic and applied ecological research and monitoring. Advances in animal tracking are occurring simultaneously with changes to technology, in an evolving global scientific culture that increasingly promotes data sharing and transparency. However, there is a risk that misuse of biotelemetry data could increase the vulnerability of animals to human disturbance or exploitation. For the most part, telemetry data security is not a danger to animals or their ecosystems, but for some high-risk cases, as with species’ with high economic value or at-risk populations, available knowledge of their movements may promote active disturbance or worse, potential poaching. We suggest that when designing animal tracking studies it is incumbent on scientists to consider the vulnerability of their study animals to risks arising from the implementation of the proposed program, and to take preventative measures.

Data collection by conservation biologists is undergoing radical change, with researchers collaborating across disciplines to create bespoke, low‐cost monitoring equipment from open‐source hardware (OSH). Compared to commercial hardware, OSH dramatically reduces participation costs. Four barriers currently hold back its wide adoption: (1) user inexperience inhibits initial uptake; (2) complex and costly manufacturing/distribution procedures impede global dissemination; (3) lack of creator support results in lapsed projects; and (4) lack of user support degrades continued utility in the field. Here, we propose a framework to address these barriers, illustrating how OSH offers a route to rapid expansion of community‐driven conservation action.

Innovation has the potential to enable conservation science and practice to keep pace with the escalating threats to global biodiversity, but this potential will only be realized if such innovations are designed and developed to fulfill specific needs and solve well‐defined conservation problems. We propose that business‐world strategies for assessing the practicality of innovation can be applied to assess the viability of innovations, such as new technology, for addressing biodiversity conservation challenges. Here, we outline a five‐step, “lean start‐up” based approach for considering conservation innovation from a business‐planning perspective. Then, using three prominent conservation initiatives – Marxan (software), Conservation Drones (technology support), and Mataki (wildlife‐tracking devices) – as case studies, we show how considering proposed initiatives from the perspective of a conceptual business model can support innovative technologies in achieving desired conservation outcomes.

We are in the midst of a revolution in satellite technology, with the rapid development and advancement of small satellites (or SmallSats, i.e., satellites <180 kg). Here, we review the opportunities and challenges that such technology might afford in the field of conservation and ecology. SmallSat constellations may yield higher resolutions than those that are currently available to scientists and practitioners, increasing opportunities to improve environmentalmonitoring and animal-tracking capabilities. They may cut access costs to end users, by reducing operational costs and bringing increased competition to the existing market. Their greater flexibility and affordability may moreover enable the development of bespoke constellations for specific conservation and ecological applications, and provide greater interoperability with ground-based sensors, such as tracking devices and camera traps. In addition, SmallSats may serve as cost-effective research and development platforms for new components and products. Combined, these benefits could significantly improve our ability to monitor threats to the environment as they unfold, while enhancing our understanding of animal ecology and ecosystem dynamics. However, significant hardware and software developments are required before such technology is able to produce, process and handle reliable and cost-effective data, and the initial research and development costs still represent a major challenge. Further, we argue that much remains to be done to ensure these new data products become accessible, equitable and sustainable.

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.

Many of the species in decline around the world are subject to different environmental stressors across their range, so replicated large-scale monitoring programmes, are necessary to disentangle the relative impacts of these threats. At the same time as funding for long-term monitoring is being cut, studies are increasingly being criticised for lacking statistical power. For those taxa or environments where a single vantage point can observe individuals or ecological processes, time-lapse cameras can provide a cost-effective way of collecting time series data replicated at large spatial scales that would otherwise be impossible. However, networks of time-lapse cameras needed to cover the range of species or processes create a problem in that the scale of data collection easily exceeds our ability to process the raw imagery manually. Citizen science and machine learning provide solutions to scaling up data extraction (such as locating all animals in an image). Crucially, citizen science, machine learning-derived classifiers, and the intersection between them, are key to understanding how to establish monitoring systems that are sensitive to – and sufficiently powerful to detect –changes in the study system. Citizen science works relatively ‘out of the box’, and we regard it as a first step for many systems until machine learning algorithms are sufficiently trained to automate the process. Using Penguin Watch (www.penguinwatch.org) data as a case study, we discuss a complete workflow from images to parameter estimation and interpretation: the use of citizen science and computer vision for image processing, and parameter estimation and individual recognition for investigating biological questions. We discuss which techniques are easily generalizable to a range of questions, and where more work is needed to supplement ‘out of the box’ tools. We conclude with a horizon scan of the advances in camera technology, such as on-board computer vision and decision making.