Table_2_Next-Generation Camera Trapping: Systematic Review of Historic Trends Suggests Keys to Expanded Research Applications in Ecology and Conservation.docx

Camera trapping is an effective non-invasive method for collecting data on wildlife species to address questions of ecological and conservation interest. We reviewed 2,167 camera trap (CT) articles from 1994 to 2020. Through the lens of technological diffusion, we assessed trends in: (1) CT adoption measured by published research output, (2) topic, taxonomic, and geographic diversification and composition of CT applications, and (3) sampling effort, spatial extent, and temporal duration of CT studies. Annual publications of CT articles have grown 81-fold since 1994, increasing at a rate of 1.26 (SE = 0.068) per year since 2005, but with decelerating growth since 2017. Topic, taxonomic, and geographic richness of CT studies increased to encompass 100% of topics, 59.4% of ecoregions, and 6.4% of terrestrial vertebrates. However, declines in per article rates of accretion and plateaus in Shannon's H for topics and major taxa studied suggest upper limits to further diversification of CT research as currently practiced. Notable compositional changes of topics included a decrease in capture-recapture, recent decrease in spatial-capture-recapture, and increases in occupancy, interspecific interactions, and automated image classification. Mammals were the dominant taxon studied; within mammalian orders carnivores exhibited a unimodal peak whereas primates, rodents and lagomorphs steadily increased. Among biogeographic realms we observed decreases in Oceania and Nearctic, increases in Afrotropic and Palearctic, and unimodal peaks for Indomalayan and Neotropic. Camera days, temporal extent, and area sampled increased, with much greater rates for the 0.90 quantile of CT studies compared to the median. Next-generation CT studies are poised to expand knowledge valuable to wildlife ecology and conservation by posing previously infeasible questions at unprecedented spatiotemporal scales, on a greater array of species, and in a wider variety of environments. Converting potential into broad-based application will require transferable models of automated image classification, and data sharing among users across multiple platforms in a coordinated manner. Further taxonomic diversification likely will require technological modifications that permit more efficient sampling of smaller species and adoption of recent improvements in modeling of unmarked populations. Environmental diversification can benefit from engineering solutions that expand ease of CT sampling in traditionally challenging sites.

相机诱捕是一种有效的非侵入性方法，用于收集野生动物物种数据，以解决生态和保育领域的问题。我们回顾了1994年至2020年间发表的2,167篇相机诱捕（CT）相关文章。通过技术扩散的视角，我们分析了以下趋势：（1）通过已发表的研究成果衡量CT的采用率，（2）CT应用的主题、分类和地理多样性及其组成，（3）CT研究的采样努力、空间范围和时间跨度。自1994年以来，CT文章的年度发表量增长了81倍，自2005年以来，年增长率达到1.26（标准误=0.068），但自2017年以来增长速度有所放缓。CT研究的主题、分类和地理多样性已增长至涵盖100%的主题、59.4%的生态区域和6.4%的陆生脊椎动物。然而，每篇文章累积率下降以及Shannon熵在主题和主要分类群研究中的平台期表明，CT研究进一步多样化的上限已显现。值得注意的主题组成变化包括捕获-再捕获的减少、近期空间捕获-再捕获的减少以及占用率、种间相互作用和自动图像分类的增加。哺乳动物是研究的主要类群；在哺乳动物目中，食肉目表现出单峰分布，而灵长目、啮齿目和兔形目则稳步增长。在生物地理区域中，我们观察到大洋洲和近北极地区的减少、非洲热带和古北地区的增加，以及印度-马来区和新热带区的单峰分布。相机使用天数、时间跨度和采样面积均有所增加，与中位数相比，CT研究的0.90分位数增长率更高。下一代CT研究有望通过在前所未有的时空尺度上提出先前不可行的问题、在更广泛的物种和更多样化的环境中进行研究，来扩展对野生动物生态和保育具有重要价值的知识。将潜力转化为广泛应用需要可转移的自动图像分类模型，以及在不同平台间协调一致的数据共享。进一步的分类多样化可能需要技术改进，以允许更高效地采样小型物种，并采用未标记种群建模的最新进展。环境多样化可以从扩大传统上难以进行CT采样的地点的工程解决方案中受益。