Impacts of climate change on forest growth in saline-alkali land of Yellow River Delta,North China |
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| Affiliation: | 1. Institute of Subtropical Forestry, Chinese Academy of Forestry, Hangzhou 311400, China;2. College of Architecture and Urban Planning, Tongji University, Shanghai 200092, China;3. Shandong Provincial Key Laboratory of Eco-Environmental Science for the Yellow River Delta, Binzhou University, Binzhou 256603, China;4. Shandong Academy of Forestry, Ji’nan 250014, China;1. Department of Geography, Environment and Geomatics, University of Guelph, 50 Stone Rd. E., Guelph ON, N1G 2W1, Canada;2. Universidad Nacional de Río Negro, Instituto de Investigaciones en Recursos Naturales, Agroecología y Desarrollo Rural (IRNAD), EL Bolsón 8430, Argentina;3. Consejo Nacional de Investigaciones Científicas y Técnicas, Instituto de Investigaciones en Recursos Naturales, Agroecología y Desarrollo Rural (IRNAD), EL Bolsón 8430, Argentina;4. Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales, CCT CONICET, Mendoza 5500 Argentina;5. Instituto Nacional de Tecnología Agropecuaria (INTA), San Carlos de Bariloche 8400, Argentina;1. Department of Wood Science and Wood Technology, Faculty of Forestry and Wood Technology, Mendel University in Brno, Brno 61300, Czech Republic;2. Global Change Research Institute of the Czech Academy of Sciences, Bělidla 986/4a, Brno 60300, Czech Republic;3. DendroLab Brno, Eliášova 37, Brno 61600, Czech Republic;1. School of Geography and Tourism, Shaanxi Normal University, Xi’an 710119, China;2. Key Laboratory of Soil Resource & Biotech Applications, Shaanxi Academy of Sciences, Shaanxi Engineering Research Centre for Conservation and Utilization of Botanical Resources, Xi’an Botanical Garden of Shaanxi Province (Institute of Botany of Shaanxi Province), Xi’an 710061, China;3. State Key Laboratory of Cryospheric Science, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China;4. State Key Laboratory of Loess and Quaternary Geology, Institute of Earth Environment, Chinese Academy of Sciences, Xi''an 710061, China;5. Institute of Earth Sciences, Heidelberg University, Im Neuenheimer Feld 234-236, 69120 Heidelberg, Germany;6. Swiss Federal Institute for Forest, Snow and Landscape Research WSL, Research Unit Forest Dynamics, Zürcherstrasse 111, CH-8903 Birmensdorf, Switzerland;7. Qinling National Botanical Garden, Xi''an 710061, China;8. Shaanxi Key Laboratory of Earth Surface System and Environmental Carrying Capacity, College of Urban and Environmental Sciences, Northwest University, Xi’an 710069, China;1. State key laboratory of vegetation and environmental change, Institute of Botany, Chinese Academy of Sciences, Xiangshan, Haidian District, Beijing 100093, China;2. University of the Chinese Academy of Sciences, Beijing, China;3. Linzhou Bureau of Meteorology, Linzhou, Lhasa, Tibet, China;4. Tibet Agricultural and Animal Husbandry University, Tibet, Linzhi, China;1. State Key Laboratory of Tree Genetics and Breeding, School of Forestry, Northeast Forestry University, Harbin 150040, PR China;2. Center for Ecological Research, Northeast Forestry University, Harbin 150040, PR China;3. Southern Swedish Forest Research Centre, Swedish University of Agricultural Sciences, Box 49, SE-230 52 Alnarp, Sweden |
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| Abstract: | Climate change is an important factor affecting forest growth. Therefore, approaching the impacts of climate change on forest growth is of great significance to ameliorate this degraded land and push up forestry development. This paper initially probes the impacts of climate change on tree growth in Yellow River Delta region and responds of different tree species on the change. In this study, five species of 22-year-old trees were selected, and the tree biomass was measured by standard site methods and tree ring sampling to pursue the impacts of climate change on forest growth. Besides, growth models of the different tree species were established and verified using Robinia pseudoacacia as an example. The results showed: (1) In the Yellow River Delta, the most adapted tree species are Fraxinus chinensis and R. pseudoacacia. (2) Precipitation is the main meteorological factor affecting tree growth, while temperature and air pressure are also significantly correlated with tree growth. (3) Linear and power function models can simulate tree growth well. From the verification results, the modified R. pseudoacacia biomass is 294.54 t/ha, and the simulated biomass of the linear function model is close to the value. It is expected that the research not only provides a theoretical basis for forestry development in saline lands, but also helps to rehabilitate saline-alkali lands and cope with climate change. |
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| Keywords: | Climate change Saline-alkali land Forest growth Yellow River Delta Tree growth model |
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