Impact of stand variables on characteristics of avian soundscape in common oak (Quercus robur L.) forests

Q4 Agricultural and Biological Sciences Forestry Studies Pub Date : 2019-06-01 DOI:10.2478/fsmu-2019-0006
A. Atemasov, T. Atemasova
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引用次数: 3

Abstract

Abstract One of the problems that may arise when conducting long-term monitoring of bird populations in forest landscapes may be discrepancies between data obtained by different researchers. Using acoustic monitoring may solve this problem. To establish the suitability of the acoustic method for monitoring the state of forest ecosystems, studies were conducted in May and June 2018 on seven plots different from each other by stand age and species composition in a maple-linden-oak forest in northeastern Ukraine. The species composition of birds, the structure and composition of the stand and the values of six acoustic indices were calculated. Differences were found in all acoustic indices at different sites. The smallest values of the indices were noted in the overgrown clear-cut. Four acoustic indices in the May survey and five of the six in the June survey show significant correlations with the species richness of birds. All indices correlate with the values of several stand variables, which characterize the size and species composition of the stand, understorey and field vegetation, the closeness of various vegetation tiers, and with the distance to the edges and the nearest populated areas. The results suggest the possibility of using an acoustic approach to monitoring the bird population and the state of forest ecosystems.
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林分变量对栎林鸟类声景观特征的影响
在对森林景观中鸟类种群进行长期监测时,可能出现的问题之一是不同研究人员获得的数据之间存在差异。声学监测可以解决这一问题。为了确定声学方法监测森林生态系统状态的适用性,研究人员于2018年5月和6月在乌克兰东北部枫树栎林的7个样地进行了研究,这些样地的林龄和物种组成各不相同。计算了鸟类的种类组成、林分结构和组成以及6项声学指标的值。不同部位的声学指标存在差异。这些指标的最小值出现在杂草丛生的清林中。5月调查的4项声学指数和6月调查的5项声学指数与鸟类物种丰富度呈显著相关。所有指数都与几个林分变量的值相关,这些变量表征了林分的大小和物种组成、林下植被和野外植被、各植被层的紧密程度以及与边缘和最近的人口密集区的距离。研究结果表明,利用声学方法监测鸟类种群和森林生态系统状况是可行的。
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来源期刊
Forestry Studies
Forestry Studies Agricultural and Biological Sciences-Forestry
CiteScore
0.70
自引率
0.00%
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0
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