Aerial surveys are an efficient technique for counting animals over large geographic areas such as rangelands. In southwestern rangelands, aerial surveys are routinely conducted for ungulates, with the implicit understanding that abundance estimates represent an undercount. Distance sampling can correct for visibility bias, but assumes perfect detection on the survey line, a condition often violated in aerial surveys of ungulates. The incorporation of mark‐resight methods into the distance‐sampling framework, termed mark‐recapture distance sampling (MRDS), corrects for both visibility bias and imperfect detection on the survey line. However, the use of MRDS introduces logistical and technical constraints that may not be practical for aerial surveys. We conducted aerial surveys of ungulates on rangelands in south Texas, USA, to evaluate the feasibility and performance of MRDS relative to conventional distance sampling (CDS) and multiple covariate distance sampling (MCDS). We conducted surveys prior to and after leaf‐fall in 2013–2015 to test the hypothesis that distance sampling corrected for changes in visibility bias. We surveyed white‐tailed deer (Odocoileus virginianus), nilgai (Boselaphus tragocamelus), collared peccary (Pecari tajacu), and feral swine (Sus scrofa) on 4 sites. Each site was surveyed seasonally for 2 years; twice both prior to (Nov) and after leaf‐fall (Feb). Probability of detection on survey lines for each species was high (range = 0.82–0.97) and the average for each species was similar between seasons (0.89 and 0.92 during pre and post leaf‐fall, respectively). The MRDS density estimates often were only ~10% greater than CDS and MCDS estimates; all population estimates had overlapping 95% confidence intervals. Further, CDS and MCDS estimates were similar indicating that measured covariates (seat position, vegetation type, and cluster size) contributed little towards detection probabilities. Despite similar average probability of detection for all species before and after leaf‐fall (0.47 and 0.51, respectively), deer and nilgai population estimates were 22–59% lower during fall surveys than winter surveys. The discrepancy between consistent probability of detections with different population estimates suggests that availability bias, which cannot be addressed with distance sampling, was an issue. Overall, the MRDS technique addressed imperfect detection on the survey line and generated probabilities of detection in the survey area consistent with previous studies done in Texas. However, the extra costs (~US$13,000) and logistical hurdles to preserve observer independence for a small increase in precision of population estimates may not be justifiable. © 2020 The Wildlife Society.

中文翻译：

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牧场重地航空测绘的标记重获距离采样

航测是一种有效的技术，可用于在广阔的地理区域（例如牧场）上对动物进行计数。在西南牧场，例行地对有蹄类动物进行空中调查，但隐含的理解是丰度估计值不足。距离采样可以纠正可见性偏差，但是可以假设在测量线上可以完美检测，这种情况在有蹄类动物的空中测量中经常被违反。将标记审核方法并入距离采样框架中（称为标记重新捕获距离采样（MRDS）），可以对可见性偏差和测量线上的缺陷检测进行校正。但是，MRDS的使用引入了后勤和技术上的限制，对于航空勘测来说可能不切实际。我们对美国得克萨斯州南部牧场的有蹄类动物进行了航空调查，相对于常规距离采样（CDS）和多协变量距离采样（MCDS）来评估MRDS的可行性和性能。我们在2013-2015年落叶前后进行了调查，以检验以下假设：距离采样可校正可见度偏差的变化。我们调查了白尾鹿（Odocoileus virginianus），nilgai（Boselaphus tragocamelus），领野猪（Pecari tajacu）和野猪（Sus scrofa）在4个网站上。每个站点都进行了为期2年的季节性调查；落叶前（11月）和落叶后（2月）两次。在每个物种的调查线中检测的可能性很高（范围= 0.82-0.97），并且每个物种的平均值在季节之间是相似的（在落叶前后，分别为0.89和0.92）。MRDS密度估算值通常仅比CDS和MCDS估算值高约10％；所有人口估计的重叠置信区间为95％。此外，CDS和MCDS估计值相似，表明所测量的协变量（座位位置，植被类型和簇大小）对检测概率的贡献很小。尽管在落叶之前和之后所有物种的平均检出概率相似（分别为0.47和0.51），秋季调查中，鹿和尼拉河的人口估计数比冬季调查低22-59％。不同人口估计数的一致检测概率之间的差异表明，可用距离偏差无法解决的可用性偏差是一个问题。总体而言，MRDS技术解决了调查线上的不完善检测，并在调查区域内产生了与德克萨斯州以前的研究一致的检测概率。但是，为维护观察员的独立性而略微增加人口估计的准确性，可能会没有理由付出额外的费用（约13,000美元）和后勤障碍。©2020野生动物协会。问题是距离采样无法解决。总体而言，MRDS技术解决了在勘测线上的不完善检测，并产生了与先前在德克萨斯州进行的研究相一致的在勘测区域中进行检测的概率。但是，为维护观察员的独立性而略微增加人口估计的准确性，可能会没有理由付出额外的费用（约13,000美元）和后勤障碍。©2020野生动物协会。问题是距离采样无法解决。总体而言，MRDS技术解决了在勘测线上的不完善检测，并产生了与先前在德克萨斯州进行的研究相一致的在勘测区域中进行检测的概率。但是，为维护观察员的独立性而略微增加人口估计的准确性，可能会没有理由付出额外的费用（约13,000美元）和后勤障碍。©2020野生动物协会。