Modeling stem volume growth of Qinghai spruce (Picea crassifolia Kom.) in Qilian Mountains of Northwest China

Qinghai spruce (Picea crassifolia Kom.), the dominant species in Qilian Mountains of Northwest China, has an important role in ecological service function, especially in carbon sequestration. The current work simulated stem volume growth of Qinghai spruce at individual and stand levels using a widespread bio-geochemical cycle (BIOME-BGC) model and considering the crown projection area (CPA). CPA was introduced because photosynthesis was only carried out on the vegetation canopy. The results showed that: (1) the CPA-simulated stem volume of individual Qinghai spruce in the three sites fitted well with the observed stem volume; (2) the introduction of CPA corrected the over-predicted stem volume for relatively younger stands and the under-predicted stem volume for relatively older stands in BIOME-BGC; and (3) meteorological factors may be crucial parameters that influence the model accuracy, aside from CPA. Therefore, CPA should be considered in correcting the carbon simulated by BIOME-BGC, and the meteorological data should be improved to obtain high-accuracy BIOME-BGC outputs.

[1]  Li Haiku.  Design of a statistical and analytical software——FORSTAT and its application. , 2004 .

[2]  Juan Blanco,et al.  Generating reliable meteorological data in mountainous areas with scarce presence of weather records: The performance of MTCLIM in interior British Columbia, Canada , 2011, Environ. Model. Softw..

[3]  S. Running,et al.  FOREST-BGC, A general model of forest ecosystem processes for regional applications. II. Dynamic carbon allocation and nitrogen budgets. , 1991, Tree physiology.

[4]  Panel Intergubernamental sobre Cambio Climático.  Climate change 2007: Synthesis report , 2007 .

[5]  D. Paslier,et al.  Net Exchange of CO2 in a Mid-Latitude Forest , 1993, Science.

[6]  Ben Bond-Lamberty,et al.  Reimplementation of the Biome-BGC model to simulate successional change. , 2005, Tree physiology.

[7]  C. Peng,et al.  Changes in Forest Biomass Carbon Storage in China Between 1949 and 1998 , 2001, Science.

[8]  Peter E. Thornton,et al.  Regional ecosystem simulation: Combining surface- and satellite-based observations to study linkages between terrestrial energy and mass budgets , 1998 .

[9]  J. Fuglestvedt,et al.  Climate agreements based on responsibility for global warming: Periodic updating, policy choices, and regional costs , 2006 .

[10]  Richard H. Waring,et al.  Forest Ecosystems: Analysis at Multiple Scales , 1985 .

[11]  Marco Bindi,et al.  Application of BIOME-BGC to simulate Mediterranean forest processes , 2007 .

[12]  W. Sang,et al.  Simulating Picea schrenkiana forest productivity under climatic changes and atmospheric CO2 increase in Tianshan Mountains, Xinjiang Autonomous Region, China , 2007 .

[13]  D. Roberts,et al.  DESPOT, a process-based tree growth model that allocates carbon to maximize carbon gain. , 2006, Tree physiology.

[14]  Csiro Materials,et al.  Response of wood density of Picea crassifolia to climate change in Qilian Mountains of northwestern China , 2011 .

[15]  F. Houllier,et al.  Prediction of stem profile of Picea abies using a process-based tree growth model. , 1995, Tree physiology.

[16]  Zhaodong Feng,et al.  GIS-assisted modelling of the spatial distribution of Qinghai spruce (Picea crassifolia) in the Qilian Mountains, northwestern China based on biophysical parameters , 2006 .

[17]  S. Iniyan,et al.  A review of climate change, mitigation and adaptation , 2012 .

[18]  Masataka Watanabe,et al.  Simulation of water and carbon fluxes using BIOME-BGC model over crops in China , 2005 .

[19]  Chuanyan Zhao,et al.  [Spatial distribution characteristics of the biomass and carbon storage of Qinghai spruce (Picea crassifolia) forests in Qilian Mountains]. , 2011, Ying yong sheng tai xue bao = The journal of applied ecology.

[20]  Chuanyan Zhao,et al.  Restoration and conservation potential of destroyed Qinghai spruce (Picea crassifolia) forests in the Qilian Mountains of northwest China , 2016, Mitigation and Adaptation Strategies for Global Change.

[21]  John S. Kimball,et al.  BIOME-BGC simulations of stand hydrologic processes for BOREAS , 1997 .

[22]  D. Maguire,et al.  The effect of local stand structure on growth and growth efficiency in heterogeneous stands of ponderosa pine and lodgepole pine in central Oregon , 2004 .

[23]  J. Nycander,et al.  Combined effect of global warming and increased CO2-concentration on vegetation growth in water-limited conditions , 2013 .

[24]  C. Kroeze.  N2O from animal waste. Methodology according to IPCC Guidelines for National Greenhouse Gas Inventories. , 1997 .

[25]  M. Araújo,et al.  Exposure of global mountain systems to climate warming during the 21st Century , 2007 .

[26]  S. Schneider,et al.  Climate Change 2007 Synthesis report , 2008 .

[27]  Robert C. Wolpert,et al.  A Review of the , 1985 .

[28]  Annabel Porté,et al.  Modelling mixed forest growth: a review of models for forest management , 2002 .

[29]  S. Running,et al.  A general model of forest ecosystem processes for regional applications I. Hydrologic balance, canopy gas exchange and primary production processes , 1988 .

[30]  Peter E. Thornton,et al.  Parameterization and Sensitivity Analysis of the BIOME–BGC Terrestrial Ecosystem Model: Net Primary Production Controls , 2000 .

[31]  Emil Cienciala,et al.  Application of BIOME-BGC model to managed forests: 2. Comparison with long-term observations of stand production for major tree species , 2006 .

[32]  R. J. Olson,et al.  NET PRIMARY PRODUCTION AND CARBON ALLOCATION PATTERNS OF BOREAL FOREST ECOSYSTEMS , 2001 .