Druce Dave J, Shannon Graeme, Page Bruce R, Grant Rina, Slotow Rob
Amarula Elephant Research Programme, Biological and Conservation Sciences, Westville Campus, University of KwaZulu-Natal, Durban, South Africa.
PLoS One. 2008;3(12):e3979. doi: 10.1371/journal.pone.0003979. Epub 2008 Dec 18.
Acquiring greater understanding of the factors causing changes in vegetation structure -- particularly with the potential to cause regime shifts -- is important in adaptively managed conservation areas. Large trees (> or =5 m in height) play an important ecosystem function, and are associated with a stable ecological state in the African savanna. There is concern that large tree densities are declining in a number of protected areas, including the Kruger National Park, South Africa. In this paper the results of a field study designed to monitor change in a savanna system are presented and discussed.
METHODOLOGY/PRINCIPAL FINDINGS: Developing the first phase of a monitoring protocol to measure the change in tree species composition, density and size distribution, whilst also identifying factors driving change. A central issue is the discrete spatial distribution of large trees in the landscape, making point sampling approaches relatively ineffective. Accordingly, fourteen 10 m wide transects were aligned perpendicular to large rivers (3.0-6.6 km in length) and eight transects were located at fixed-point photographic locations (1.0-1.6 km in length). Using accumulation curves, we established that the majority of tree species were sampled within 3 km. Furthermore, the key ecological drivers (e.g. fire, herbivory, drought and disease) which influence large tree use and impact were also recorded within 3 km.
CONCLUSIONS/SIGNIFICANCE: The technique presented provides an effective method for monitoring changes in large tree abundance, size distribution and use by the main ecological drivers across the savanna landscape. However, the monitoring of rare tree species would require individual marking approaches due to their low densities and specific habitat requirements. Repeat sampling intervals would vary depending on the factor of concern and proposed management mitigation. Once a monitoring protocol has been identified and evaluated, the next stage is to integrate that protocol into a decision-making system, which highlights potential leading indicators of change. Frequent monitoring would be required to establish the rate and direction of change. This approach may be useful in generating monitoring protocols for other dynamic systems.
在适应性管理的保护区中，更深入了解导致植被结构变化的因素——尤其是那些可能引发状态转变的因素——至关重要。大树（高度≥5米）发挥着重要的生态系统功能，并且与非洲稀树草原的稳定生态状态相关联。人们担心包括南非克鲁格国家公园在内的一些保护区内大树密度正在下降。本文展示并讨论了一项旨在监测稀树草原系统变化的实地研究结果。
方法/主要发现：制定监测方案的第一阶段，以测量树种组成、密度和大小分布的变化，同时确定驱动变化的因素。一个核心问题是大树在景观中的离散空间分布，这使得点抽样方法相对无效。因此，十四条10米宽的样带垂直于大河流布设（长度为3.0 - 6.6千米），八条样带位于定点拍照位置（长度为1.0 - 1.6千米）。通过累积曲线，我们确定大多数树种在3千米范围内被采样。此外，影响大树利用和影响的关键生态驱动因素（如火灾、食草作用、干旱和疾病）也在3千米范围内被记录。
结论/意义：所提出的技术为监测稀树草原景观中大树丰度、大小分布以及主要生态驱动因素的利用变化提供了一种有效方法。然而，由于稀有树种密度低且有特定的栖息地要求，对其监测需要采用个体标记方法。重复采样间隔将根据关注因素和提议的管理缓解措施而有所不同。一旦确定并评估了监测方案，下一阶段是将该方案纳入决策系统，该系统突出潜在的变化领先指标。需要频繁监测以确定变化的速率和方向。这种方法可能有助于为其他动态系统生成监测方案。
