Technology for nature conservation: An industry perspective

Ambio 2015, 44(Suppl. 4):S522–S526 DOI 10.1007/s13280-015-0702-4 Technology for nature conservation: An industry perspective Lucas N. Joppa Abstract Information age technology has the potential to change the game for conservation by continuously monitoring the pulse of the natural world. Whether or not it will depends on the ability of the conservation sector to build a community of practice, come together to define key technology challenges and work with a wide variety of partners to create, implement, and sustain solutions. I describe why these steps are necessary, outline the latest developments in the field and offer actionable ways forward for conservation agencies, universities, funding bodies, professional societies, and technology corporations to come together to realize the revolution that computational technologies can bring for biodiversity conservation. Keywords Biodiversity
Collaboration
Cross-sector partnerships
Information age
Nature conservation
Technology THE PROMISE We live at the intersection of two unprecedented ages. The first is the Information Age of laptops, tablets, smart phones, the internet, social networks, and innumerable miniaturized computing devices which permeate every aspect of daily life (Castells 2011). The second is the Anthropocene (Crutzen 2006; Steffen et al. 2007)—defined by an exceptionally rapid loss of biodiversity caused by human activity and changing climates. Conservation biology is the scientific discipline that addresses the ‘dynamics and problems of perturbed species, communities, and ecosystems’ (Soulé 1985). The practice of nature conservation has always been interdisciplinary: those dedicated to conserving the *9 million 123 species on Earth (Mora et al. 2011) are well aware that success often requires efficiently combining ‘mud on boots’ field science in remote areas of the world with the political acumen of a seasoned lobbyist. Now add to that the role of technologist. The role that computational tools and technology can play in helping monitor, model and respond to the challenges of global biodiversity loss is enormous. I take a broad definition of computational technology here—including the hardware, software, databases, algorithms, and programming languages that come together to turn data into insight. The breadth of this definition is partially out of necessity—in recent years the number of computational approaches to conservation has grown rapidly (Arts et al. 2015). The conservation community’s embrace of computational technology, and the passion, ingenuity and perseverance that a hugely diverse group of individuals and organizations have brought to this space is immensely inspirational, and the media and public have been paying attention. Stories on drone projects for anti-poaching (Wall 2014), GPS-tagged sharks tweeting their locations to nervous beach-goers (Yu 2014), species rediscovered by remote camera traps (AAP 2014), monitoring of illegal fishing (Craymer 2014), or a crowd-sourced bioblitz (Foderaro 2013) of a local park are a steady feed into the news cycle. With time to ponder the possibilities, a powerful vision appears: Information Age technology changing the game for conservation by continuously monitoring the pulse of the natural world. THE PROBLEM But there is a persistent concern: for every solidly planned and implemented project (e.g., iNaturalist, eBird—see Ó The Author(s) 2015. This article is published with open access at Springerlink.com www.kva.se/en Ambio 2015, 44(Suppl. 4):S522–S526 Wood et al. 2011) there are a host of scattered and inconsistent approaches to using computational technology to solve real conservation problems. The current general approach is a patchwork of one-off projects and partnerships. This wastes time, money, and resources in a discipline that can ill-afford to do so. Digging beyond the news stories one often finds that the drone has been crippled by a lack of funds and engineering expertise. The new app has a bug—and the intern who wrote it has moved on. The machine-learning algorithm works perfectly on a small dataset—but is missing the infrastructure to scale it beyond the desktop. Camera traps are indeed taking pictures—now the problem is not a lack of images but an avalanche of them (Swinnen et al. 2014). Who, or what, is going to sort through them all? And it turns out that the smartphones used at the bioblitz—and the power and connectivity they require—are not available where ecological surveys are most needed. These difficulties are partly explained by the different motivations driving the technology and nature conservation domains (Maffey et al. 2015). In technology research the motivations are often academic—proving what is possible and pushing back the research frontiers. Many exciting results emerge, but these mostly end up in published papers, demonstrations or prototypes, after which the researchers move on to the next problem. Technology firms take a few of those results and turn them into products for consumers or enterprise, often losing the features most critical to the conservation community’s needs (like durability, power efficiency, cost, or other important factors). As a result, those working to conserve nature are often inspired by the vision produced by technology research, but left without the tools needed for effective nature conservation. For example, unmanned aerial vehicles (UAVs or ‘drones’) with sustained flight times in harsh environments, capable of being operated by unskilled workers and performing custom tasks like autonomous monitoring of wildlife poaching via computer vision and acoustic recognition technologies, are still lacking. It is possible to build such an integrated system, but the UAV research community has not seen fit to engineer it (although the Wildlife Conservation UAV Challenge1 is working to change that). A wide range of issues—of scale, limited funds, attention, expertise, and unforeseen engineering challenges—needs addressing when adapting computational technology to the needs of nature conservation, a problem not unique to the intersection of conservation and technology (King and Crewe 2013). But these issues of implementation must be overcome in a systematic way if technological approaches are to help, not hinder, S523 conservation practices. This is possible by establishing a common core of required technology and partnering with academic institutions, funding bodies and the private technology sector in a sustainable manner to create a community of practice in conservation technology (see Galán-Dı́az et al. 2015 for a cost-benefit evaluation of digital innovation in nature conservation through partnerships working with academics). BUILDING A CONSERVATION TECHNOLOGY COMMUNITY The International Union for the Conservation of Nature’s (IUCN) Red List combines information from over ten thousand scientists to classify species by the levels of conservation concern attached to them.2 Thi (...truncated)