Human Dimensions of Natural Resources, Colorado State University, Fort Collins, Colorado, USA.
World Wildlife Fund, Washington, D.C., USA.
Conserv Biol. 2022 Jun;36(3):e13871. doi: 10.1111/cobi.13871. Epub 2022 Feb 3.
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.
保护技术具有极大地提高保护主义者理解和应对关键环境挑战的能力的潜力，但系统约束似乎阻碍了其发展和采用。对这些约束和发展机会的理解仍然有限。我们对 248 名保护技术用户和开发人员进行了全球在线调查，以确定对现有工具当前性能和潜在影响、用户和开发人员约束以及关键增长机会的看法。我们还与 45 名领先专家进行了焦点小组讨论，以对调查结果进行三角分析。被认为具有最高潜力的技术是机器学习和计算机视觉、环境 DNA 和基因组学以及联网传感器。分别有 95%、94%和 92%的受访者认为它们非常有帮助或具有变革性。影响整个领域的最紧迫挑战是对有限资金的竞争、工作重复和能力建设不足。分别有 76%、67%和 55%的受访者将这些问题视为主要关注点。焦点小组确定的主要增长机会是增加合作和信息共享、提高工具的互操作性以及增强大规模数据分析能力。一些限制似乎对边缘化群体有不成比例的影响。来自发展中经济体国家的受访者更有可能报告受到前期成本、维护成本和开发资金的限制(p=0.048，优势比[OR]=2.78;p=0.005，OR=4.23;p=0.024，OR=4.26)，女性受访者更有可能报告受到开发资金和感知技术技能的限制(p=0.027，OR=3.98;p=0.048，OR=2.33)。据我们所知，这是首次尝试正式捕捉全球保护技术界的观点和需求，提供基础数据，可作为衡量进展的基准。我们看到这个社区有巨大的潜力进一步实现他们定义的愿景，在这个愿景中，合作胜过竞争；解决方案是开放、可访问和互操作的；用户友好的处理工具使数据快速转化为保护行动成为可能。文章影响声明：解决资金、协调和能力建设方面的制约因素对于保护技术的发展和采用至关重要。
