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

Abstract

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.

Keywords: biodiversity conservation; capacity building; colaboración; collaboration; conservación de la biodiversidad; desarrollo de capacidad; encuesta mundial; financiamiento; funding; global survey; innovación; innovation; monitoreo de fauna; technology; tecnología; wildlife monitoring.

FIGURE 1

Conservation technologies frequently used by survey respondents and mean proficiency scores for each (GIS, geographic information systems; ML, machine learning; UAVs, unmanned aerial vehicles; PA mgmt, protected area management; eDNA, environmental DNA). Respondents reported proficiency levels for each technology they selected on a scale from 1 to 5, with 1 being novice and 5 being expert

FIGURE 2

Survey respondent ratings of (a) overall performance of conservation technology groups and (b) their capacity to advance conservation if current problems were addressed (abbreviations defined in Figure 1)

FIGURE 3

Key constraints affecting engagement with conservation technology reported by (a) end users and (b) developers or testers

FIGURE 4

Survey respondent rankings of the greatest challenges facing the field of conservation technology (1, most important; 9, least important)