Comparison of density and basal area estimation of mountain natural forests based on distance-based sampling methods in Zhejiang,China |
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| Institution: | 1. Research Institute of Forestry, Chinese Academy of Forestry, Key Laboratory of Tree Breeding and Cultivation of National Forestry and Grassland Administration, Box 1958, Beijing 100091, China;2. Administration of Fengyangshan National Nature Reserve, Longquan 323700, China;3. Forestry Academy of Longquan City, Longquan 323700, China;4. Wuyanling National Natural Reserve Management Bureau, Taishun 325500, China;1. Ethiopian Space Science and Technology Institute (ESSTI), Entoto Observatory and Research Center, Department of Remote Sensing, Addis Ababa, Ethiopia;2. Institute of Geomatics, University of Natural Resources and Life Sciences, Vienna (BOKU), Peter JordanStraße 82, 1190 Vienna, Austria;1. Federal Institute of Education, Science and Technology of Mato Grosso do Sul, Mato Grosso do Sul, Aquidauana, Brazil;2. Federal Institute of Education, Science and Technology of Mato Grosso do Sul, Mato Grosso do Sul, Campo Grande, Brazil;3. Dom Bosco Catholic University, Tamandaré Avenue, Campo Grande – MS, 79117-010, Brazil;4. Federal University of Mato Grosso do Sul, Costa e Silva Avenue, Campo Grande – MS, 79070-900, Brazil;5. State University of Mato Grosso do Sul, Dom Antonio Barbosa Avenue, Campo Grande – MS, 79115-898, Brazil;1. State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau, Northwest A&F University, Yangling, Shaanxi 712100, China;2. Institute of Soil and Water Conservation, Chinese Academy of Science and Ministry of Water Resource, Yangling, Shaanxi 712100, China;3. University of Missouri, Division of Plant Sciences and Technology, 108 Waters Hall, Columbia, MO 65211, USA |
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| Abstract: | ObjectiveThe sustainable development of forest ecology and forest management practices is inseparable from the support of forest surveys. Different sampling methods have an unavoidable impact on the collection of natural community characteristic information. An appropriate method reduces the cost of the investigation to the maximum degree under the premise of ensuring accuracy. Distance-based sampling methods are widely used because of their excellent performance in estimating forest population characteristics. The purpose of this study is to compare and find an efficient sampling method of natural broad-leaved forests in mountainous areas of Zhejiang, China, which is of great significance to large-scale field survey practice in similar areas.MethodOur study used census survey data from fixed monitoring sample plots of natural broad-leaved forest in Wuyanling National Nature Reserve, Zhejiang, China as an example and simulated different distance-based sampling methods, including n-tree distance (NTD), point-centered quarter (PCQ), and T-square (Ts), combined with several estimators to estimate the stand density and basal area. The results were compared with the actual mean values of the 100% survey.ResultWe found that different sampling methods and estimators significantly influenced the results. NTD1 overestimated both the stand density and basal area, while NTD2 performed the best, with the lowest RMSE. Secondary performance was obtained with Ts3, Ts5, and Ts6, with small RMSEs of density and basal area. The RMSEs of the PCQ and Ts sampling methods based on a single distance were all large.ConclusionThe NTD sampling method with the NTD2 estimator is recommended to estimate the stand density and basal area for field investigation of natural forests in the Zhejiang mountainous area. |
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