Jiménez-Franco María V, Kéry Marc, León-Ortega Mario, Robledano Francisco, Esteve Miguel A, Calvo José F
Departamento de Biología Aplicada Universidad Miguel Hernández de Elche Elche Spain.
Departamento de Ecología e Hidrología Universidad de Murcia Murcia Spain.
Ecol Evol. 2019 Feb 5;9(2):825-835. doi: 10.1002/ece3.4829. eCollection 2019 Jan.
New monitoring programs are often designed with some form of temporal replication to deal with imperfect detection by means of occupancy models. However, classical bird census data from earlier times often lack temporal replication, precluding detection-corrected inferences about occupancy. Historical data have a key role in many ecological studies intended to document range shifts, and so need to be made comparable with present-day data by accounting for detection probability. We analyze a classical bird census conducted in the region of Murcia (SE Spain) in 1991 and 1992 and propose a solution to estimating detection probability for such historical data when used in a community occupancy model: the spatial replication of subplots nested within larger plots allows estimation of detection probability. In our study, the basic sample units were 1-km transects, which were considered spatial replicates in two aggregation schemes. We fit two Bayesian multispecies occupancy models, one for each aggregation scheme, and evaluated the linear and quadratic effect of forest cover and temperature, and a linear effect of precipitation on species occupancy probabilities. Using spatial rather than temporal replicates allowed us to obtain individual species occupancy probabilities and species richness accounting for imperfect detection. Species-specific occupancy and community size decreased with increasing annual mean temperature. Both aggregation schemes yielded estimates of occupancy and detectability that were highly correlated for each species, so in the design of future surveys ecological reasons and cost-effective sampling designs should be considered to select the most suitable aggregation scheme. In conclusion, the use of spatial replication may often allow historical survey data to be applied formally hierarchical occupancy models and be compared with modern-day data of the species community to analyze global change process.
新的监测项目通常采用某种形式的时间重复设计，以借助占有率模型应对不完全检测的问题。然而，早期的经典鸟类普查数据往往缺乏时间重复，这使得无法进行关于占有率的检测校正推断。历史数据在许多旨在记录范围变化的生态研究中起着关键作用，因此需要通过考虑检测概率使其与当今数据具有可比性。我们分析了1991年和1992年在穆尔西亚地区（西班牙东南部）进行的一次经典鸟类普查，并提出了一种在群落占有率模型中使用此类历史数据时估计检测概率的解决方案：嵌套在较大样地内的子样地的空间重复允许估计检测概率。在我们研究中，基本样本单位是1公里的样带，在两种聚集方案中被视为空间重复。我们拟合了两个贝叶斯多物种占有率模型，每种聚集方案一个，并评估了森林覆盖和温度的线性和二次效应，以及降水对物种占有率概率的线性效应。使用空间重复而非时间重复使我们能够获得考虑不完全检测情况下的单个物种占有率概率和物种丰富度。特定物种的占有率和群落规模随年平均温度升高而降低。两种聚集方案得出的每个物种的占有率和可检测性估计值高度相关，因此在未来调查设计中，应考虑生态原因和具有成本效益的抽样设计，以选择最合适的聚集方案。总之，使用空间重复通常可能使历史调查数据能够应用于正式的分层占有率模型，并与物种群落的现代数据进行比较，以分析全球变化过程。
