Monitoring moose in Montana using hunter observations to count moose by district

During 2012–2016, we queried hunters of deer and elk for observations of
groups of a non-target species, moose, across their statewide distribution
in Montana.  We used buffer analyses to filter data according to
independent observations in space and time and then tallied observations
of groups by hunting district.  We then analyzed data in an
abundance-detection framework with n-mixture models and evaluated the
effects of covariates such as hunter effort, survey response totals,
weekly session, and forest cover on detection probability before using
models to predict moose abundance.  Lastly, we converted model
predictions of group abundnace to total abundance by multiplying number of
groups by average group size per administrative region.

2012年至2016年间，我们针对蒙大拿州全域范围内的鹿与麋鹿猎人开展调研，收集其对非目标物种驼鹿（moose）种群群的观测数据。我们采用缓冲区分析（buffer analyses），依据时空独立观测标准对数据进行筛选，随后按狩猎分区统计种群群的观测频次。随后，我们基于丰度-检测框架，结合n混合模型（n-mixture models）开展数据分析，评估了猎人狩猎强度、调查响应总量、每周调查时段以及森林覆盖率等协变量对检测概率的影响，并借助模型预测驼鹿种群丰度。最终，我们将各行政区域内的种群群数量乘以平均种群群规模，将模型预测的种群群丰度转换为总种群丰度。