Nimble code and dataset for: Estimating true density in large, alpine herbivores using Google Earth imagery

This nimble code will estimate elk density from the count data (DO_data_list.RData) and covariates (DO_constants_list.RData).  Data and covariates include: a 'y' matrix of double observer counts with 3315 rows (1 for each 250 m square plot) and 3 columns for the observer 1's exclusive counts, observer 2's exclusive counts, and the count of elk detected by both observers. The double-observe protocol was only employed in 372 random cells. 'n' is a vector of total counts – the total number of uniquely detected elk in each plot.  'obs1tot' is a vector of the total count of elk by just observer 1, who counted elk in all 3315 cells. There are two dummy indicator variables that are all 1's ('obs1constraint' and 'obs2constraint') to constrain unobserved but estimated counts to sum to expected totals. For example, observer 1 was the only observer in 2943 plots. This single count would be the equivalent of the sum of the exclusive observer 1 counts and the joint observer 1 and 2 counts in a doubl..., Counts and covariates were obtained according to the methods outlined in \"Estimating true density in large, alpine herbivores using Google Earth imagery.\" by Christianson, David; Winnie, John, Wildlife Biology 10.1002/wlb3.01089. The nimble code for the double-observer model of counts and model fitting was based partly on excerpts from Kery and Royle 2016. Code was adapted to accommodate the partial application of double-observer to the study area., This code was built in R version 4.2.2 and nimble version 0.13.1.

本nimble代码可基于计数数据（DO_data_list.RData）与协变量数据（DO_constants_list.RData）估算马鹿种群密度。数据与协变量内容如下：包含双观察者计数矩阵`y`，共3315行（对应每一个250米见方的样方），3列分别对应观察者1单独计数、观察者2单独计数，以及两名观察者共同检测到的马鹿数量。双观察者观测方案仅在372个随机样方中实施。`n`为总计数值向量，即每个样方中唯一被检测到的马鹿总数量。`obs1tot`为仅由观察者1统计得到的马鹿总数量向量，该观察者对全部3315个样方均进行了计数。另有两个全1虚拟指示变量`obs1constraint`与`obs2constraint`，用于约束未观测但需估算的计数之和符合预期总数值。例如，在2943个样方中仅观察者1参与计数，此类单一计数结果等价于双观察者方案中观察者1单独计数与两名观察者共同计数之和。本研究的计数数据与协变量均基于Christianson与Winnie于《Wildlife Biology》发表的论文《Estimating true density in large, alpine herbivores using Google Earth imagery》（DOI: 10.1002/wlb3.01089）中所述方法获取。本研究中用于双观察者计数模型与模型拟合的nimble代码，部分改编自Kery与Royle 2016年的相关内容，并针对研究区域仅部分样方采用双观察者方案的情况进行了适配调整。本代码基于R 4.2.2版本与nimble 0.13.1版本编写。