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广东边际性土地能源植物种植潜力适宜性评价
引用本文:王 芳,卓 莉,覃新导,李少英,杨朝辉,黄鸿健.广东边际性土地能源植物种植潜力适宜性评价[J].农业工程学报,2015,31(19):276-284.
作者姓名:王 芳  卓 莉  覃新导  李少英  杨朝辉  黄鸿健
作者单位:1.广州大学地理科学学院,广州5100062.广东省城市化与地理环境空间模拟重点实验室,广州 510275,2.广东省城市化与地理环境空间模拟重点实验室,广州 5102753.中山大学地理科学与规划学院综合地理信息研究中心,广州 510275,4.中国热带农业科学院广州实验站,广州 510140,1.广州大学地理科学学院,广州5100062.广东省城市化与地理环境空间模拟重点实验室,广州 510275,5.苏州科技大学城市与环境学系,苏州 215011,1.广州大学地理科学学院,广州510006
基金项目:国家自然科学基金面上项目(41371499);国家自然科学基金青年基金(41401432);广东省自然科学基金(2015A030313505);广东省教育高校特色创新项目(2014KTSCX088)
摘    要:利用边际性土地种植能源植物是发展液体生物能源产业,解决产业原料供应瓶颈问题和缓解碳减排压力,保护环境的重要途径。准确评价边际土地能源植物的种植潜力是合理利用边际性土地的重要环节。针对目前边际性土地能源植物适宜性评价模型多以线性为主,容易造成单生态因子的评价结果的高估或低估问题。该文建立了边际土地开发非线性生态位适宜度评价模型,该模型引入了专家知识,利用高斯曲线去拟合边际土地利用的现实生态位与能源植物种植需求生态位的匹配关系,利用最佳生态位值及限制性生态因子,以贴近度作为适宜性划分的标准测度各评价单元的生态位适宜度指数,来界定能源作物的边际土地的种植潜力。将模型应用于广东省,选取木薯、麻疯树、油桐和黄连木4种广东省最具潜力的液体生物能源植物进行边际土地适宜性分析,结果表明:广东省边际性土地资源丰富,良好的水热,土壤等生境条件使得其具有较高开发适宜性。适合4种能源植物的边际土地为62.15×104 hm2,占总边际土地面积的58.44%。麻疯树和黄连木2种植物生态适宜度最高,并且具有相似的生态位,在空间上存在竞争关系;其次是油桐树;木薯在4种能源植物中高适宜度范围最小,主要适合种植在粤西台地平原和粤东滨海丘陵台地地区。

关 键 词:植物  种植  土地利用  边际性土地  生态适宜度模型  适宜性评价
收稿时间:2015/3/15 0:00:00
修稿时间:2015/7/21 0:00:00

Evaluation on suitability of planting potential of energy plants on marginal land of Guangdong Province
Wang Fang,Zhuo Li,Qin Xindao,Li Shaoying,Yang Zhaohui and Huang Hongjian.Evaluation on suitability of planting potential of energy plants on marginal land of Guangdong Province[J].Transactions of the Chinese Society of Agricultural Engineering,2015,31(19):276-284.
Authors:Wang Fang  Zhuo Li  Qin Xindao  Li Shaoying  Yang Zhaohui and Huang Hongjian
Institution:1. School of Geographical Sciences, Guangzhou University, Guangzhou 510006, China2. Guangdong Key Laboratory for Urbanization and Geo-simulation, Guangzhou 510275, China,2. Guangdong Key Laboratory for Urbanization and Geo-simulation, Guangzhou 510275, China3. Center of Integrated Geographic Information Analysis, School of Geography and Planning, Sun Yat-sen University, Guangzhou 510275, China,4.Guangzhou Experimental Station of Chinese Academy of Tropical Agricultural Sciences, Guangzhou, 510140, China,1. School of Geographical Sciences, Guangzhou University, Guangzhou 510006, China2. Guangdong Key Laboratory for Urbanization and Geo-simulation, Guangzhou 510275, China,5. Department of Urban and Environmental Science, USTS, Suzhou 215011,China and 1. School of Geographical Sciences, Guangzhou University, Guangzhou 510006, China
Abstract:Abstract: Liquid bioenergy from energy plants is a promising sustainable energy source in China. But, due to a huge population, it is impossible to use many cultivated lands to expand the planting area of liquid bioenergy to safeguard food security and meet rapidly increasing energy demand. Planting the energy plants on marginal lands in China is an important approach to develop liquid bioenergy industry and solve the supply problem of raw materials. It can be also helpful to relieve the pressure of carbon emission reduction and protect the environment. However, the availability and the multi-suitability of marginal lands, especially at a regional scale, remain uncertain. Accurate evaluation of marginal land potential for energy plants growing is a serious part for rational planning and utilization of marginal lands. Existing land multi-suitability evaluation models are mostly linear models, which often cause overestimation or underestimation of single ecological factor. A nonlinear ecological multi-suitability evaluation model was developed in this study, which introduces expert knowledge and uses Gauss curve to match the optimum ecological niche of the marginal land based on the demand of ecological niche of the energy plant. Matching degree is used as fitness value to measure the multi-suitability and potential of the marginal land for planting energy plants. Taking Guangdong Province as an example, 4 species of liquid energy plants, namely Cassava, Vernicia fordii, Jatropha curcas L. and Pistacia chinensis, were chosen to evaluate the potential of liquid bioenergy. Using a supervised classification process, we identified the marginal lands from the Landsat TM/ ETM satellite images with a 30 m resolution that cover Guangdong. The multi-suitability of the marginal lands for planting the 4 species was evaluated using the ecological niche models (ENMs), which incorporate local temperature, precipitation, soil, terrain and traffic. Our modeling consisted of 2 steps, one at the individual ecological factor level, and the other at the habitat level that integrated the outputs from the individual factors. Three kinds of situations were considered, which were represented by 3 types of function curves, namely the S-shaped, Bell-shaped, and Z-shaped curve. The S-shaped curve characterizes the situation that large ecological factor values favor the crop. The Z-shaped curve indicates that small factor values favor the crop. The Bell-shaped curve defines a most optimal range in the factor value, and the optimality drops as the factor value deviates from this range. The results support the following conclusions: the total area of the marginal land in Guangdong is 106.35×104 hm2, and the shrub land, open forest land, and grassland account for 31.36%, 43.86% and 22.43%, respectively. The shoal/bottomland and unused land only account for very small proportion. With abundant heat and water resources, good soil condition and rich marginal land resource, Guangdong Province has high multi-suitability of planting energy plants and great potential of developing liquid bioenergy industry. The area of marginal land suitable for planting the 4 species is 62.15×104 hm2, which accounts for 58.44% of the total marginal land. Ecological niche fitness value for Jatropha curcas L. and Pistacia chinensis is the highest, and for these 2 species have similar ecological niche, there is a competition between them for development space; the second is Vernicia fordii; Cassava has the lowest niche fitness value, which is suitable for growing on the west terrace plain and east coastal hilly tableland in Guangdong Province.
Keywords:plants  cultivation  land use  marginal land  niche fitness model  suitability evaluation
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