Mapping spatiotemporal decisions for sustainable productivity of bamboo forest land. (6th January 2020)

• Record Type: Journal Article
• Authors: Li, Xuejian; Du, Huaqiang; Mao, Fangjie; Zhou, Guomo; Xing, Luqi; Liu, Tengyan; Han, Ning; Liu, Enbing; Ge, Hongli; Liu, Yuli; Li, Yangguang; Zhu, Di'en; Zheng, Junlong; Dong, Luofan; Zhang, Meng
• Is Part Of: Land degradation & development. Volume 31:Number 8(2020)
• Page Start: 939
• Page End: 958
• Publication Date: 2020-01-06
• Subjects: bamboo forest productivity -- measured variable -- PLS path model -- sustainable index system -- sustainable management; Land degradation -- Periodicals; Soil conservation -- Periodicals; Reclamation of land -- Periodicals; Land use -- Periodicals; Economic development -- Environmental aspects -- Periodicals; 333.7315
• DOI: 10.1002/ldr.3509
• Languages: English
• ISSNs: 1085-3278

Abstract

Abstract: Properly mapping the sustainability of bamboo forest production plays an important role in providing basic strategies for decision makers to ensure sustainable use of bamboo resources. Understanding the response pattern of drought, poor management, elevation, and barren soil to bamboo forest ecosystem productivity is critical to formulating appropriate improvement strategies of sustainable management of bamboo forest productivity for addressing growing challenges of bamboo forest land degradation. The objectives of this study were to quantify differences in productivity, meteorological, topographical, soil, and bamboo distribution and structure factors under different sustainable management levels of bamboo forest ecosystem productivity in order to support management decision making in a spatiotemporally explicit context. We constructed an innovative three‐layer index system for the sustainable management of bamboo forest productivity by integrating productivity, meteorological, soil, topographic, bamboo distribution, and structure factors to promote sustainable management and spatiotemporal decision making, particularly in bamboo forest areas with low productivity. The partial least squares (PLS) path model was used to analyze the spatiotemporal effects of different factors on bamboo forest productivity and to create sustainable management maps that could be used for spatially informed decision making regarding bamboo forest production. The results showed the spatial and temporal variations in gross primary productivity (GPP), net primary productivity (NPP), and net ecosystem exchange (NEE) in bamboo forests. The sustainable management index was also mapped each year throughout the study area. We divided the index value range into five management‐friendly classes, which were shown to be directly related to GPP, NPP, NEE, Slope, Aspect, soil texture, hydrolytic nitrogen, and Abundance. We found that the areas with relatively high sustainable management levels (I and II) occupied only 18.94% of the bamboo forest area and exhibited a highly clustered distribution. Most of the other areas (78.67%) had relatively low levels of sustainable management (III and IV), and their distribution was rather scattered. The remaining 2.39% of the bamboo forest area that had the lowest sustainable management level (V) was small in area, fragmented, and not conducive to intensive management. The results of the present study can serve as a useful reference for bamboo forest management, which is of great importance for bamboo‐based ecosystems and economies.