Closing the gap between existing large-area imaging research and marine conservation needs

Emerging technology has immense potential to increase the scale and efficiency of marine conservation. One such technology is large-area imaging (LAI), which relies on structure-from-motion photogrammetry to create composite products, including 3-dimensional (3-D) environmental models, that are larger in spatial extent than the individual images used to create them. Use of LAI has become widespread in certain fields of marine science, primarily to measure the 3D structure of benthic ecosystems and track change over time. However, the use of LAI in the field of marine conservation appears limited. We conducted a review of the coral reef literature on the use of LAI to identify research themes and regional trends in applications of this technology. We also surveyed 135 coral reef scientists and conservation practitioners to determine community familiarity with LAI, evaluate barriers practitioners face in using LAI, and identify applications of LAI believed to be most exciting or relevant to coral conservation. Adoption of LAI was limited primarily to researchers at institutions based in advanced economies and was applied infrequently to conservation, although conservation practitioners and survey respondents from emerging economies indicated they expect to use LAI in the future. Our results revealed disconnect between current LAI research topics and conservation priorities identified by practitioners, highlighting the need for more diverse, conservation-relevant research using LAI. We provide recommendations for how early adopters of LAI (typically Global North scientists from well-resourced institutions) can facilitate access to this conservation technology. These recommendations include developing training resources, creating partnerships for data storage and analysis, publishing standard operating procedures for LAI workflows, standardizing methods, developing tools for efficient data extraction from LAI products, and conducting conservation-relevant research using LAI.

A global community-sourced assessment of the state of conservation technology

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.

A framework to integrate innovations in invasion science for proactive management

Invasive alien species (IAS) are a rising threat to biodiversity, national security, and regional economies, with impacts in the hundreds of billions of U.S. dollars annually. Proactive or predictive approaches guided by scientific knowledge are essential to keeping pace with growing impacts of invasions under climate change. Although the rapid development of diverse technologies and approaches has produced tools with the potential to greatly accelerate invasion research and management, innovation has far outpaced implementation and coordination. Technological and methodological syntheses are urgently needed to close the growing implementation gap and facilitate interdisciplinary collaboration and synergy among evolving disciplines. A broad review is necessary to demonstrate the utility and relevance of work in diverse fields to generate actionable science for the ongoing invasion crisis. Here, we review such advances in relevant fields including remote sensing, epidemiology, big data analytics, environmental DNA (eDNA) sampling, genomics, and others, and present a generalized framework for distilling existing and emerging data into products for proactive IAS research and management. This integrated workflow provides a pathway for scientists and practitioners in diverse disciplines to contribute to applied invasion biology in a coordinated, synergistic, and scalable manner.

Identifying conservation technology needs, barriers, and opportunities

Amid accelerating threats to species and ecosystems, technology advancements to monitor, protect, and conserve biodiversity have taken on increased importance. While most innovations stem from adaptation of off-the-shelf devices, these tools can fail to meet the specialized needs of conservation and research or lack the support to scale beyond a single site. Despite calls from the conservation community for its importance, a shift to bottom-up innovation driven by conservation professionals remains limited. We surveyed practitioners, academic researchers, and technologists to understand the factors contributing to or inhibiting engagement in the collaborative process of technology development and adoption for field use and identify emerging technology needs. High cost was the main barrier to technology use across occupations, while development of new technologies faced barriers of cost and partner communication. Automated processing of data streams was the largest emerging need, and respondents focused mainly on applications for individual-level monitoring and automated image processing. Cross-discipline collaborations and expanded funding networks that encourage cyclical development and continued technical support are needed to address current limitations and meet the growing need for conservation technologies.

Threatened Species Initiative: Empowering conservation action using genomic resources

Globally, 15,521 animal species are listed as threatened by the International Union for the Conservation of Nature, and of these less than 3% have genomic resources that can inform conservation management. To combat this, global genome initiatives are developing genomic resources, yet production of a reference genome alone does not conserve a species. The reference genome allows us to develop a suite of tools to understand both genome-wide and functional diversity within and between species. Conservation practitioners can use these tools to inform their decision-making. But, at present there is an implementation gap between the release of genome information and the use of genomic data in applied conservation by conservation practitioners. In May 2020, we launched the Threatened Species Initiative and brought a consortium of genome biologists, population biologists, bioinformaticians, population geneticists, and ecologists together with conservation agencies across Australia, including government, zoos, and nongovernment organizations. Our objective is to create a foundation of genomic data to advance our understanding of key Australian threatened species, and ultimately empower conservation practitioners to access and apply genomic data to their decision-making processes through a web-based portal. Currently, we are developing genomic resources for 61 threatened species from a range of taxa, across Australia, with more than 130 collaborators from government, academia, and conservation organizations. Developed in direct consultation with government threatened-species managers and other conservation practitioners, herein we present our framework for meeting their needs and our systematic approach to integrating genomics into threatened species recovery.

Multispecies facial detection for individual identification of wildlife: a case study across ursids

To address biodiversity decline in the era of big data, replicable methods of data processing are needed. Automated methods of individual identification (ID) via computer vision are valuable in conservation research and wildlife management. Rapid and systematic methods of image processing and analysis are fundamental to an ever-growing need for effective conservation research and practice. Bears (ursids) are an interesting test system for examining computer vision techniques for wildlife, as they have variable facial morphology, variable presence of individual markings, and are challenging to research and monitor. We leveraged existing imagery of bears living under human care to develop a multispecies bear face detector, a critical part of individual ID pipelines. We compared its performance across species and on a pre-existing wild brown bear Ursus arctos dataset (BearID), to examine the robustness of convolutional neural networks trained on animals under human care. Using the multispecies bear face detector and retrained sub-applications of BearID, we prototyped an end-to-end individual ID pipeline for the declining Andean bear Tremarctos ornatus. Our multispecies face detector had an average precision of 0.91-1.00 across all eight bear species, was transferable to images of wild brown bears (AP = 0.93), and correctly identified individual Andean bears in 86% of test images. These preliminary results indicate that a multispecies-trained network can detect faces of a single species sufficiently to achieve high-performance individual classification, which could speed-up the transferability and application of automated individual ID to a wider range of taxa.

Supplementary Information

The online version contains supplementary material available at 10.1007/s42991-021-00168-5.

Connecting to the oceans: supporting ocean literacy and public engagement

Improved public understanding of the ocean and the importance of sustainable ocean use, or ocean literacy, is essential for achieving global commitments to sustainable development by 2030 and beyond. However, growing human populations (particularly in mega-cities), urbanisation and socio-economic disparity threaten opportunities for people to engage and connect directly with ocean environments. Thus, a major challenge in engaging the whole of society in achieving ocean sustainability by 2030 is to develop strategies to improve societal connections to the ocean. The concept of ocean literacy reflects public understanding of the ocean, but is also an indication of connections to, and attitudes and behaviours towards, the ocean. Improving and progressing global ocean literacy has potential to catalyse the behaviour changes necessary for achieving a sustainable future. As part of the Future Seas project (https://futureseas2030.org/), this paper aims to synthesise knowledge and perspectives on ocean literacy from a range of disciplines, including but not exclusive to marine biology, socio-ecology, philosophy, technology, psychology, oceanography and human health. Using examples from the literature, we outline the potential for positive change towards a sustainable future based on knowledge that already exists. We focus on four drivers that can influence and improve ocean literacy and societal connections to the ocean: (1) education, (2) cultural connections, (3) technological developments, and (4) knowledge exchange and science-policy interconnections. We explore how each driver plays a role in improving perceptions of the ocean to engender more widespread societal support for effective ocean management and conservation. In doing so, we develop an ocean literacy toolkit, a practical resource for enhancing ocean connections across a broad range of contexts worldwide.

Connecting to the oceans: supporting ocean literacy and public engagement

Improved public understanding of the ocean and the importance of sustainable ocean use, or ocean literacy, is essential for achieving global commitments to sustainable development by 2030 and beyond. However, growing human populations (particularly in mega-cities), urbanisation and socio-economic disparity threaten opportunities for people to engage and connect directly with ocean environments. Thus, a major challenge in engaging the whole of society in achieving ocean sustainability by 2030 is to develop strategies to improve societal connections to the ocean. The concept of ocean literacy reflects public understanding of the ocean, but is also an indication of connections to, and attitudes and behaviours towards, the ocean. Improving and progressing global ocean literacy has potential to catalyse the behaviour changes necessary for achieving a sustainable future. As part of the Future Seas project (https://futureseas2030.org/), this paper aims to synthesise knowledge and perspectives on ocean literacy from a range of disciplines, including but not exclusive to marine biology, socio-ecology, philosophy, technology, psychology, oceanography and human health. Using examples from the literature, we outline the potential for positive change towards a sustainable future based on knowledge that already exists. We focus on four drivers that can influence and improve ocean literacy and societal connections to the ocean: (1) education, (2) cultural connections, (3) technological developments, and (4) knowledge exchange and science-policy interconnections. We explore how each driver plays a role in improving perceptions of the ocean to engender more widespread societal support for effective ocean management and conservation. In doing so, we develop an ocean literacy toolkit, a practical resource for enhancing ocean connections across a broad range of contexts worldwide.

A Comprehensive Overview of Technologies for Species and Habitat Monitoring and Conservation

The range of technologies currently used in biodiversity conservation is staggering, with innovative uses often adopted from other disciplines and being trialed in the field. We provide the first comprehensive overview of the current (2020) landscape of conservation technology, encompassing technologies for monitoring wildlife and habitats, as well as for on-the-ground conservation management (e.g., fighting illegal activities). We cover both established technologies (routinely deployed in conservation, backed by substantial field experience and scientific literature) and novel technologies or technology applications (typically at trial stage, only recently used in conservation), providing examples of conservation applications for both types. We describe technologies that deploy sensors that are fixed or portable, attached to vehicles (terrestrial, aquatic, or airborne) or to animals (biologging), complemented with a section on wildlife tracking. The last two sections cover actuators and computing (including web platforms, algorithms, and artificial intelligence).

Understanding and Assisting Reproduction in Wildlife Species Using Microfluidics

Conservation breeding and assisted reproductive technologies (ARTs) are invaluable tools to save wild animal species that are on the brink of extinction. Microfluidic devices recently developed for human or domestic animal reproductive medicine could significantly help to increase knowledge about fertility and contribute to the success of ART in wildlife. Some of these microfluidic tools could be applied to wild species, but dedicated efforts will be necessary to meet specific needs in animal conservation; for example, they need to be cost-effective, applicable to multiple species, and field-friendly. Microfluidics represents only one powerful technology in a complex toolbox and must be integrated with other approaches to be impactful in managing wildlife reproduction.

Integrating drone-borne thermal imaging with artificial intelligence to locate bird nests on agricultural land

In conservation, the use of unmanned aerial vehicles (drones) carrying various sensors and the use of deep learning are increasing, but they are typically used independently of each other. Untapping their large potential requires integrating these tools. We combine drone-borne thermal imaging with artificial intelligence to locate ground-nests of birds on agricultural land. We show, for the first time, that this semi-automated system can identify nests with a high performance. However, local weather, type of arable field and height of the drone can affect performance. The results' implications are particularly relevant to conservation practitioners working across sectors, such as biodiversity conservation and food production in farmland. Under a rapidly changing world, studies like this can help uncover the potential of technology for conservation and embrace cross-sectoral transformations from the onset; for example, by integrating nest detection within the precision agriculture system that heavily relies on drone-borne sensors.