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估计疾病风险评估中的种群密度:以野猪为例理解陷阱影响区域的重要性。

Estimating population density for disease risk assessment: The importance of understanding the area of influence of traps using wild pigs as an example.

作者信息

Davis Amy J, Leland Bruce, Bodenchuk Michael, VerCauteren Kurt C, Pepin Kim M

机构信息

National Wildlife Research Center, Wildlife Services, Animal Plant Health Inspection Service, United States Department of Agriculture, 4101 Laporte Ave., Fort Collins, CO, USA.

Wildlife Services, United States Department of Agriculture, San Antonio, TX, USA.

出版信息

Prev Vet Med. 2017 Jun 1;141:33-37. doi: 10.1016/j.prevetmed.2017.04.004. Epub 2017 Apr 20.

Abstract

Population density is a key driver of disease dynamics in wildlife populations. Accurate disease risk assessment and determination of management impacts on wildlife populations requires an ability to estimate population density alongside management actions. A common management technique for controlling wildlife populations to monitor and mitigate disease transmission risk is trapping (e.g., box traps, corral traps, drop nets). Although abundance can be estimated from trapping actions using a variety of analytical approaches, inference is limited by the spatial extent to which a trap attracts animals on the landscape. If the "area of influence" were known, abundance estimates could be converted to densities. In addition to being an important predictor of contact rate and thus disease spread, density is more informative because it is comparable across sites of different sizes. The goal of our study is to demonstrate the importance of determining the area sampled by traps (area of influence) so that density can be estimated from management-based trapping designs which do not employ a trapping grid. To provide one example of how area of influence could be calculated alongside management, we conducted a small pilot study on wild pigs (Sus scrofa) using two removal methods 1) trapping followed by 2) aerial gunning, at three sites in northeast Texas in 2015. We estimated abundance from trapping data with a removal model. We calculated empirical densities as aerial counts divided by the area searched by air (based on aerial flight tracks). We inferred the area of influence of traps by assuming consistent densities across the larger spatial scale and then solving for area impacted by the traps. Based on our pilot study we estimated the area of influence for corral traps in late summer in Texas to be ∼8.6km. Future work showing the effects of behavioral and environmental factors on area of influence will help mangers obtain estimates of density from management data, and determine conditions where trap-attraction is strongest. The ability to estimate density alongside population control activities will improve risk assessment and response operations against disease outbreaks.

摘要

种群密度是野生动物种群疾病动态的关键驱动因素。准确的疾病风险评估以及确定管理措施对野生动物种群的影响,需要在采取管理行动的同时具备估计种群密度的能力。一种控制野生动物种群以监测和减轻疾病传播风险的常见管理技术是诱捕(例如,箱式陷阱、围栏陷阱、落网)。尽管可以使用多种分析方法从诱捕行动中估计种群数量,但推断受到陷阱在景观中吸引动物的空间范围的限制。如果“影响区域”已知,种群数量估计值就可以转换为密度。密度不仅是接触率进而疾病传播的重要预测指标,而且更具信息价值,因为它在不同大小的地点之间具有可比性。我们研究的目的是证明确定陷阱采样区域(影响区域)的重要性,以便能够从非网格化的基于管理的诱捕设计中估计密度。为了提供一个如何在管理过程中计算影响区域的示例,我们于2015年在得克萨斯州东北部的三个地点,对野猪(Sus scrofa)进行了一项小型试点研究,采用了两种捕杀方法:1)诱捕,随后2)空中枪击。我们使用去除模型从诱捕数据中估计种群数量。我们将经验密度计算为空中计数除以空中搜索的面积(基于空中飞行轨迹)。我们通过假设在较大空间尺度上密度一致,然后求解陷阱影响的面积,来推断陷阱的影响区域。基于我们的试点研究,我们估计得克萨斯州夏末围栏陷阱的影响区域约为8.6公里。未来关于行为和环境因素对影响区域影响的研究,将有助于管理人员从管理数据中获得密度估计值,并确定陷阱吸引力最强的条件。在进行种群控制活动的同时估计密度的能力,将改善对疾病爆发的风险评估和应对行动。

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