Chabot Dominique, Craik Shawn R, Bird David M
Department of Natural Resource Sciences, McGill University, Ste-Anne-de-Bellevue, Québec, Canada; Avian Science and Conservation Centre of McGill University, Ste-Anne-de-Bellevue, Québec, Canada.
Département des Sciences, Université Sainte-Anne, Pointe-de-l'Église, Nova Scotia, Canada.
PLoS One. 2015 Apr 15;10(4):e0122588. doi: 10.1371/journal.pone.0122588. eCollection 2015.
Small unmanned aircraft systems (UAS) may be useful for conducting high-precision, low-disturbance waterbird surveys, but limited data exist on their effectiveness. We evaluated the capacity of a small UAS to census a large (>6,000 nests) coastal Common tern (Sterna hirundo) colony of which ground surveys are particularly disruptive and time-consuming. We compared aerial photographic tern counts to ground nest counts in 45 plots (5-m radius) throughout the colony at three intervals over a nine-day period in order to identify sources of variation and establish a coefficient to estimate nest numbers from UAS surveys. We also compared a full colony ground count to full counts from two UAS surveys conducted the following day. Finally, we compared colony disturbance levels over the course of UAS flights to matched control periods. Linear regressions between aerial and ground counts in plots had very strong correlations in all three comparison periods (R2 = 0.972-0.989, P < 0.001) and regression coefficients ranged from 0.928-0.977 terns/nest. Full colony aerial counts were 93.6% and 94.0%, respectively, of the ground count. Varying visibility of terns with ground cover, weather conditions and image quality, and changing nest attendance rates throughout incubation were likely sources of variation in aerial detection rates. Optimally timed UAS surveys of Common tern colonies following our method should yield population estimates in the 93-96% range of ground counts. Although the terns were initially disturbed by the UAS flying overhead, they rapidly habituated to it. Overall, we found no evidence of sustained disturbance to the colony by the UAS. We encourage colonial waterbird researchers and managers to consider taking advantage of this burgeoning technology.
小型无人机系统（UAS）可能有助于进行高精度、低干扰的水鸟调查，但关于其有效性的数据有限。我们评估了小型无人机系统对一个大型（超过6000个巢穴）沿海普通燕鸥（Sterna hirundo）繁殖地进行普查的能力，在这个繁殖地进行地面调查特别具有破坏性且耗时。我们在九天内的三个时间间隔，对整个繁殖地的45个地块（半径5米）中的空中摄影燕鸥数量与地面巢穴数量进行了比较，以确定变异来源并建立一个系数，用于根据无人机系统调查估算巢穴数量。我们还将整个繁殖地的地面计数与第二天进行的两次无人机系统调查的完整计数进行了比较。最后，我们将无人机系统飞行过程中的繁殖地干扰水平与匹配的对照期进行了比较。在所有三个比较期内，地块空中计数与地面计数之间的线性回归具有非常强的相关性（R2 = 0.972 - 0.989，P < 0.001），回归系数范围为0.928 - 0.977只燕鸥/巢穴。整个繁殖地的空中计数分别为地面计数的93.6%和94.0%。燕鸥在地面覆盖物、天气条件和图像质量下的可见度变化，以及整个孵化过程中巢穴出勤率的变化，可能是空中检测率变异的来源。按照我们的方法，对普通燕鸥繁殖地进行最佳时间的无人机系统调查，应能得出在地面计数的93% - 96%范围内的种群估计数。虽然燕鸥最初受到头顶上方无人机飞行的干扰，但它们很快就适应了。总体而言，我们没有发现无人机系统对繁殖地造成持续干扰的证据。我们鼓励研究和管理群居水鸟的人员考虑利用这项新兴技术。
