Gigliotti Franco N, Franzem Thomas P, Ferguson Paige F B
Department of Biological Sciences, University of Alabama, Tuscaloosa, Alabama, USA.
Department of Ecology and Evolutionary Biology, University of Connecticut, Storrs, Connecticut, USA.
Conserv Biol. 2023 Apr;37(2):e13996. doi: 10.1111/cobi.13996. Epub 2023 Jan 20.
A bioblitz inexpensively and quickly generates biodiversity data, but bioblitzes are often conducted with haphazard, unreplicated sampling. Results tend to be taxonomically, geographically, or temporally biased, lack metadata, and consist of lists of observed taxa that do not enable further analyses or correction for imperfect detection. A rapid, recurring, structured survey (RRSS) uses a structured sampling design and temporal and spatial replication to survey randomly selected sites on a conservation property. We participated in a loosely structured bioblitz and a subsequent RRSS at Big Canoe Creek Nature Preserve in Springville (St. Clair County), Alabama (USA) to compare observed richness derived from the 2 survey approaches. The RRSS data structure enabled us to fit models that accounted for imperfect detection to estimate abundances, occupancy probabilities, and habitat associations. The loosely structured bioblitz data could not be used in such models. We present a new integrated multispecies abundance model that we applied to avian RRSS data. Our model extension enables estimation for the community, employs data augmentation to estimate the number of undetected species, and incorporates covariates. The RRSS generated a more comprehensive and less biased list of observed taxonomic richness than the loosely structured bioblitz (e.g., 73 vs. 45 bird species and 104 vs. 63 insect families from the RRSS vs. loosely structured bioblitz, respectively). Models fit to the RRSS data identified seasonal patterns in avian community composition and allowed for estimation of habitat-occupancy relationships for insect taxa. The RRSS protocol has potential for broad transferability as a standardized, quick, and inexpensive way to inventory biodiversity and estimate ecological parameters while providing an outreach opportunity.
生物多样性速查能以低成本快速生成生物多样性数据，但生物多样性速查往往采用随意、无重复的抽样方式。结果往往在分类学、地理或时间上存在偏差，缺乏元数据，且仅为观察到的分类单元列表，无法进行进一步分析或对不完美检测进行校正。快速、定期、结构化调查（RRSS）采用结构化抽样设计以及时间和空间重复，对保护区内随机选择的地点进行调查。我们在美国阿拉巴马州斯普林维尔（圣克莱尔县）的大独木舟溪自然保护区参与了一次结构松散的生物多样性速查以及随后的RRSS，以比较两种调查方法所观察到的物种丰富度。RRSS的数据结构使我们能够拟合考虑了不完美检测的模型，以估计物种数量、占据概率和栖息地关联。结构松散的生物多样性速查数据无法用于此类模型。我们提出了一种新的综合多物种丰度模型，并将其应用于鸟类RRSS数据。我们的模型扩展能够对群落进行估计，采用数据增强来估计未检测到的物种数量，并纳入协变量。与结构松散的生物多样性速查相比，RRSS生成的观察到的分类学丰富度列表更全面且偏差更小（例如，RRSS分别记录了73种鸟类和104个昆虫科，而结构松散的生物多样性速查分别记录了45种鸟类和63个昆虫科）。拟合RRSS数据的模型确定了鸟类群落组成的季节性模式，并能够估计昆虫类群的栖息地占据关系。RRSS方案具有广泛的可转移性潜力，可作为一种标准化、快速且低成本的方法来清查生物多样性和估计生态参数，同时提供一个推广机会。
