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Management and conservation implications of Blakiston's fish owl (Ketupa blakistoni) resource selection in Primorye, Russia.

机译:俄罗斯滨海边疆区布拉基斯顿鱼(Ketupa blakistoni)资源选择的管理和保护意义。

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摘要

The Blakiston's fish owl (Ketupa blakistoni) is a large owl associated with riparian old-growth forests in northeast Asia. Despite its status as a charismatic endangered species, specific conservation and management efforts for the species in Russia are limited. This is because resource use by these secretive owls is poorly known. To address this information deficit, I analyzed resource selection by these owls within a 20,213 km 2 study area in Primorye, Russia. Resource selection studies often begin by defining the spatial extent of a home range and then quantifying use of available resources within that home range. For animals that use habitat that are defined by linear environmental features, such as Blakiston's fish owl, traditional home range estimators often overestimate home range size, which can lead to spurious conclusions about resource availability and selection. I used a synoptic model of space use to define Blakiston's fish owl seasonal and annual home range size and within-home range resource selection, and compared results to traditional home range estimators. I also examined nest tree and foraging site selection at 14 nest and 14 foraging sites using linear discriminant analysis. I then identified areas with the highest predicted probability of use by owls to prioritize areas for conservation and management. Fish owl home range was different among most seasons, and estimated home range sizes based on the synoptic model were more biologically-realistic than kernel density-based home range estimators. Mean annual home range size (+/- standard error) for all fish owls was 15.0 +/- 3.7 km 2 (n = 7) using the synoptic model, and 38.8 +/- 15.4 km2 using kernel density estimators. By season, winter home range was 7.0 +/- 3.3 km2 vs. 5.9 +/- 2.3 km2 (n = 3 owls; synoptic model vs. kernel density estimator); in spring 13.9 +/- 5.2 km2 vs. 29.5 +/- 20.4 km2 (n = 7); in summer 11.6 +/- 2.8 km2 vs. 33.2 +/- 11.9 km2 (n = 6); and in autumn 25.2 +/- 13.4 km2 vs. 85.1 +/- 56.0 km2 (n = 5). Fish owls selected home ranges that were within valleys, were close to water, and had a greater number of river channels than available sites. Old trees and riparian old-growth forest were the primary discriminating characteristics at both nest and foraging sites, respectively. Large trees were likely necessary as owl nest sites because of the bird's large body size. Moreover, old forests have many large trees that facilitated recruitment of large woody debris in rivers, which created suitable habitat for the owl's primary prey: salmonid fish. Based on resource selection functions I predicted that 54 fish owl territories could occur within my study area. I found that the reserve network contained only 21% of primary fish owl habitat and potentially contained only 7 fish owl territories. I also found that 39% of primary habitat was within current logging leases, which was capable of supporting habitat equivalent to 18 fish owl territories. The remainder of primary habitat (40%) was on federal land not presently protected or within logging leases, and potentially contained 29 fish owl territories. The current protected area network, by itself, will be insufficient to conserve fish owls because so few owl territories are actually protected. Therefore, I developed specific conservation recommendations within logging leases based on the observed resource selection patterns by the owls. My recommendations include protecting specific locations within potential territories, maintaining integrity of riparian areas, modifying road construction techniques, and closing old logging roads to reduce human access. These simple measures have the potential not only to conserve fish owls but also many other species, making this owl an effective umbrella species for the riparian ecosystems of the region.
机译:Blakiston的鱼owl(Ketupa blakistoni)是与东北亚河岸老龄林有关的大large。尽管它是极具魅力的濒危物种,但在俄罗斯对该物种的特殊保护和管理工作仍然有限。这是因为这些秘密猫头鹰对资源的使用知之甚少。为了解决此信息不足的问题,我分析了俄罗斯Primorye的20213 km 2研究区内这些猫头鹰的资源选择。资源选择研究通常从定义家庭范围的空间范围开始,然后量化该家庭范围内可用资源的使用。对于使用由线性环境特征定义的栖息地的动物,例如布拉基斯顿的鱼,传统的家庭范围估计器通常会高估家庭范围的大小,这可能导致有关资源可用性和选择的虚假结论。我使用空间使用的天气模型来定义Blakiston的鱼的季节和年度家庭范围大小以及家庭范围内的资源选择,并将结果与​​传统家庭范围估计器进行比较。我还使用线性判别分析研究了14个巢和14个觅食点的巢树和觅食点选择。然后,我确定了猫头鹰预测使用概率最高的区域,以对保护和管理区域进行优先排序。在大多数季节中,鱼的居所范围均不同,并且基于天气概貌模型估算的居所范围要比基于果粒密度的居所估计值更具生物学现实性。使用天气学模型,所有鱼猫头鹰的平均年均栖息地大小(+/-标准误差)为15.0 +/- 3.7 km 2(n = 7),而使用仁密度估计器为38.8 +/- 15.4 km2。按季节划分,冬季居家范围为7.0 +/- 3.3 km2与5.9 +/- 2.3 km2(n = 3头猫头鹰;天气模型与籽粒密度估算器);在春季13.9 +/- 5.2 km2对29.5 +/- 20.4 km2(n = 7);夏季为11.6 +/- 2.8 km2,而33.2 +/- 11.9 km2(n = 6);秋季为25.2 +/- 13.4平方公里,而85.1 +/- 56.0平方公里(n = 5)。鱼选择了位于山谷内,靠近水且河道数量多于可利用地点的家园。在巢穴和觅食处,老树和河岸老树森林分别是主要的鉴别特征。由于鸟的体型较大,可能需要大树作为猫头鹰的巢穴。此外,古老的森林中有许多大树,这些大树有助于在河流中募集大块木屑,这为猫头鹰的主要猎物鲑鱼创造了合适的栖息地。基于资源选择功能,我预测我的研究区域内可能会出现54个鱼地区。我发现保护区网络仅包含21%的原住民猫头鹰栖息地,并且可能仅包含7个猫头鹰栖息地。我还发现39%的主要栖息地在当前的伐木租约内,能够支持相当于18个鱼猫头鹰的栖息地。其余的主要栖息地(40%)位于目前未受保护的联邦土地上或在伐木租约内,并可能包含29个鱼领地。目前的保护区网络本身不足以保护鱼猫头鹰,因为实际上很少有猫头鹰地区受到保护。因此,我根据猫头鹰观察到的资源选择模式在伐木租约中提出了具体的保护建议。我的建议包括保护潜在领土内的特定位置,保持河岸地区的完整性,修改道路施工技术以及关闭旧的伐木道路以减少人员进入。这些简单的措施不仅有可能保护鱼类猫头鹰,而且还有许多其他物种的潜力,使这种猫头鹰成为该地区河岸生态系统的有效保护伞物种。

著录项

  • 作者

    Slaght, Jonathan C.;

  • 作者单位

    University of Minnesota.;

  • 授予单位 University of Minnesota.;
  • 学科 Agriculture Wildlife Conservation.;Agriculture Forestry and Wildlife.;Statistics.
  • 学位 Ph.D.
  • 年度 2011
  • 页码 166 p.
  • 总页数 166
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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