洞庭湖退田还湖区钱粮湖垸景观格局、土壤质量与土地承载力研究
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摘要
洞庭湖位于湖南省北部,是我国第二大淡水湖泊和承纳湘、资、沅、澧四水,吞吐长江的洪道型湖泊。由于人为的围湖造田以及自然的泥沙淤积,其面积已由秦汉时期超过6000 km2骤减到目前天然湖泊面积仅2625 km2。洞庭湖水体面积大幅减少的同时,也造成调蓄洪功能严重下降,血吸虫蔓延,生物多样性丧失和湖区生态环境退化。自退田还湖工程实施后,洞庭湖原有生态功能得到一定恢复和改善,但同时洞庭湖区景观格局、土地利用结构与方式发生了一系列的变化与响应,尤其是在非畜洪年份,各种土地资源依然采用集约化经营,土壤质量、土地承载力及可持续性利用都受到不同程度的影响。论文以钱粮湖垸为例,通过定位研究与随机取样,野外调查与室内分析、定性分析与定量研究相结合等方法,在退田还湖对其景观格局变化影响分析的基础上,研究了退田还湖区林地(Ⅰ)、园地(Ⅱ)、旱地(Ⅲ)、水田(Ⅳ)、荒地(Ⅴ)等不同土地利用方式下的土壤水分物理性质、土壤养分库、土壤微量元素有效性、土壤微生物数量与酶活性、土壤重金属空间分布与污染累积、土壤综合质量,并结合钱粮湖垸安全圈的建设,提出了土地利用格局优化与土地承载力可持续性的对策,旨在为洞庭湖退田还湖区土壤质量调控、土地利用方式优化、土地可持续利用和区域景观规划设计提供依据。
     1、从斑块类型和景观水平上对钱粮湖垸1987年、1996年、2008年的景观格局动态变化的分析显示,其景观格局总体变化趋势是景观多样性增加、均匀度增加、破碎度增大、景观形状由简单趋于复杂。景观要素转移矩阵及转移贡献率分析表明人口增长、城镇化建设与退田还湖工程实施是导致景观格局发生变化的主要驱动力。
     2、不同土地利用方式下土壤水分物理性质分析结果表明,0-50 cm土层土壤密度为1.02-1.65 g·cm-3,毛管孔隙度为33.04%~61.70%,非毛管孔隙度为2.15%-25.35%,总孔隙度为38.40%-64.96%,自然含水量为17.07%~38.33%,毛管持水量为23.22%-64.00%,土壤团聚体平均重量直径、分形维数分别为1.76-5.09 mm、2.2728~2.6388;灰色关联分析显示,不同土地利用方式土壤水分物理性质以荒地类型最差,园地最好,关联度排序为Ⅱ>Ⅳ>Ⅰ>Ⅲ>Ⅴ。
     3、不同土地利用方式土壤养分库差异显著。其中,林地土壤全氮含量最高、有机质含量最低,水田有机质、全钾及速效磷含量均最高,旱地水解氮含量最高,而荒地土壤全氮、全磷、全钾、水解氮及水解磷均最低。不同土地利用方式下土壤养分库综合指数变化范围为24.33-295.93,排序为IⅣ(231.96)>IⅢ(193.46)>IⅡ(70.90)>IⅠ(59.57)>Iv(35.59)。
     4、运用均方根法研究了不同土地利用方式下土壤微量元素Cu、Zn、Fe、Mn、Mo的单项有效指数和综合有效指数,大小排序分别为EMo(15.5933)>EZn(4.7767)>EFe(3.1898)>ECu(1.7160)>EMn(1.1913)和EⅠ(10.9020)>EⅡ(8.2198)>EⅣ(7.7335)>EⅤ(5.1726)>EⅢ(4.2006)。通过双重筛选逐步回归,建立了土壤有效微量元素主导因子方程,土壤有效Cu、Zn含量主要影响因素为土壤密度、毛管孔隙度、毛管持水量、pH值、有机质、全氮和速效钾;有效Fe主要受毛管持水量和全钾的影响;有效Mn、Mo主要分别受速效钾、全氮的影响。
     5、不同土地利用方式下土壤细菌、放线菌数量均以旱地最高,真菌数量以荒地最高;细菌是土壤微生物的主要类群,占全部微生物比例为44.42%~92.93%;其次为真菌数量,所占比例为4.89%~42.76%;放线菌数量最少,仅占1.71%-24.52%。土壤磷酸酶、脲酶、脱氢酶活性分别以园地、荒地、水田最低,而旱地土壤蛋白酶活性总体最低。典范相关分析表明,土壤微生物典范变量(U)正效应作用最大的是放线菌数量,其次为细菌数量,真菌数量表现为负效应;土壤酶活性典范变量(V)正效应作用最大的是脲酶活性,其次为脱氢酶活性,磷酸酶与蛋白酶活性则表现为负效应。
     6、土壤重金属Cu、Zn、Mn、Pb、Cd、As、Hg全量的空间分布与污染累积分析显示,单项污染指数以Cd较高,且林地(Ⅰ2、Ⅰ3)、旱地(Ⅲ2)、水田(Ⅳ)已受到Cd污染;除As及部分土壤Zn也未发生累积外,各土地利用方式下均存在重金属累积现象。不同土地利用方式综合污染指数、综合累积指数均以水田(Ⅳ)最高(0.8372、5.9528),荒地最低(0.6566,4.6928)。主成分分析和双重筛选逐步回归表明,Cu主要受毛管持水量、全钾的影响;Zn主要受毛管孔隙度、全氮、速效磷、全钾和速效钾的影响;Mn主要受非毛管孔隙度、全氮和速效钾的影响;Pb、Cd及As受相同自变量影响,主要影响因素为非毛管孔隙度、毛管持水量、有机质、全氮、全磷、速效磷和速效钾;Hg主要受土壤密度、总孔隙度、全磷和全钾的影响。
     7、运用层次分析法构建了涵盖土壤物理、土壤化学、土壤生物学以及土壤重金属污染累积4类28个指标的土壤质量评价指标体系。不同土地利用方式土壤综合质量以水田最高,荒地最低,其排序为Ⅳ(0.6479)>Ⅲ(0.5386)>Ⅱ(0.4373)>Ⅰ(0.4364)>Ⅴ(0.2546)。指标权重大小表明土壤总孔隙度、有机质、细菌数量和重金属综合污染指数分别是各类指标中对土壤质量贡献最大的4个指标。
     8、根据钱粮湖垸安全区建设规划,结合不同土地利用方式下土壤质量变化研究结果,运用马尔柯夫模型对土地利用结构与景观格局进行了优化、预测。以1987-2008年间总人口数和粮食产量的统计数据为基础,选择趋势外推法,预测评估了温饱型、宽裕型、小康型、富裕型四级不同消费标准下该地区2010年、2015年、2020年、2025年和2030年的土地人口承载力,并从景观格局优化、生态农业模式选择和土地利用制度完善上提出了钱粮湖垸土地资源可持续性利用对策。
Dongting Lake is the second largest fresh-water and flood channel type lake in China which is situated in the north of Hunan province and connecting four rivers of Xiang, Zi, Yuan and Li with Yangtzer River. For land reclamating from lake by people and natural sediment depositing, however, its natural lake area has decreased form more than 6 000 km2 in Qinhan dynasty to 2 625 km2 now. When lake area decreased sharply, there also resulted in other questions which included capalities of controlling and storaging flood weakening, schistosome japonicum overspreading, biodiversity lossing and environment degradating. In order to improve this conditon, the project of converting polders back into wetlands had been enacted, and original ecological functions had been restored and enhanced to some extent. At the same time, there existed a series of changes and responses of landscape patterns, structures and styles of land use in Dongting Lake. Soil qualities, land carrying capacities and sustainable utilization were effected differently under intensive management especially in non-flooding years.
     Through comprehensive study methods of oriented researching and random sampling, field surveying and laboratory analyzing, qualitative analyzing and quantitative studying, the effections of converting polders back into wetlands on the landscape pattern changing were studied on the case of Qianlianghu polder, Dongting Lake Area. Based on these results and plot data of poplar forestland soil (Ⅰ1,9a;Ⅰ2,6a;Ⅰ3,4a;Ⅰ4,2a) (Ⅰ), garden-land soil (vegetable soil and fruit soil) (Ⅱ), nonirrigated farmland soil (Ⅲ1, cotton soil;Ⅲ2, sugar cane soil;Ⅲ3, maize soil) (Ⅲ), irrigated farmland soil (rice soil) (Ⅳ) and wasteland soil (Ⅴ), a research had been carried out into soil physical properties, soil nutrient pools, soil microelement availabilities, soil microbe quantities and enzyme activities, distribution, pollution and accumulation of soil heavy metals, soil syntheical qualities in above five typical land use patterns. Combination with the flood safety contructed of Qianlianghu polder, moveover, optimizational measures of land use patterns and sustainable countermeasures were discussed and put forward in order that offerred some suggestions for regulating soil qualities, optimizing land use patterns, utilizing sustainably land resource and planning and designing regional landscape.
     (1) The dynamic changes of landscape patterns in the years of 1987,1996 and 2008 were analyzed in the patch level and landscape level, respectively. The total changing tendencies of landscape patterns were that diversity, evenness, fragmentation indexes were increasing, and landscape shapes were changing for simplicity to complexity. Through markov transferring matrix and contribution rate of landscpae elements analyzed, it was the main driving forces for landscape pattern changing that were increasing population, constructing urbanization and converting polders back into wetlands.
     (2) Soil physical properties had been studied and evaluated synthetically through gray incidence analysis in five typical land use patterns. The results were found that soil bulk densities, capillary porosities, non-capillary porosities, total porosities, soil natural water contents, soil capillary moisture capacities, mean weight diameters (MWD) and fractal dimensions (FD) of soil aggregates in 0~50 cm soil layers under different land use patterns were 1.02~1.65 g·cm-3,33.04%~61.70%,2.15%~25.35%,38.40%~64.96%,17.07%~38.33%,23.22%-64.00%,1.76-5.09 mm and 2.2728~2.6388 respectively. Soil physical properties were ordered by>Ⅳ>Ⅰ>Ⅲ>Ⅴ, which showed the soil physical characteristics was the poorest in waste landⅤ(0.6183) and the best in garden landⅡ(0.7763).
     (3) Base on synthetical index method, the effects of soil nutrient pool in different land use patterns had been studied. The highest contents of TN and the lowest OM occurred in patternⅠ, the highest contents of OM, TK and AP were in patternⅣ, and the highest AN were patternⅢ. However, the contents of TN, TP, TK, AN and AP were the lowest in pattern V. Soil nutrient pool synthetical indexes ranged from 24.33 to 295.93 in five land use patterns, which showed by regularities of IⅣ(231.96)>Im (193.46)>IⅡ(70.90)>IⅠ(59.57)>IⅤ(35.59)
     (4) Base on root mean square method, single and synthetical available indexes of soil microelements which included Cu、Zn、Fe、Mn、Mo were studied. There existed the regularities of EMo (15.5933)> EZn (4.7767)> EFe (3.1898)> ECu (1.7160)>EMn (1.1913) for single microelements and EⅠ(10.9020)>EⅡ(8.2198)> EⅣ(7.7335) >EⅤ(5.1726)> EⅢ(4.2006) for different land use patterns. Through double sieving stepwise regression analysis, it was found that the maily influence factors of available Cu and Zn were soil bulk density, capillary porosity, water storage in capillary porosity, pH value, organic matter, total N and available K, and for Fe were water storage in capillary porosity and total K. Available Mn and available Mo were mainly affected by available K and total N respectively.
     (5) The highest quantities of both bacteria and actinomycetes occurred in nonirrigated farmland soil (III), and the highest quantity of funguses in wasteland soil (V). Bacterium was the main category of the total soil microbe with the highest proportion of 44.42%-92.93%, fungus and actinomycete followed with the proportion of 4.89%-42.76% and 1.71%-24.52%, respectively. The lowest activities of phosphataese, urease and dehydrogenase appeared in garden-land soilⅡ, wasteland soil V and irrigated farmland soilⅣ, respectively, and proteinase activity was the lowest in nonirrigated farmland soilⅢ. According to canonical correlation analysis, there was a positive relationship between U and actinomycial number, bacterial number followed, but there was a negative relationship between U and fungus number. There was a positive relationship betweenⅤand urease with the largest regression coefficient, followed by dehydrogenas, but there was a negative relationship between V and phosphataese, as well as V and proteinase.
     (6) Distribution, pollution and accumulation evaluations of soil heavy metals (Cu, Zn, Mn, Pb, Cd, As and Hg) had been studied. Unfortunately, soils of patternⅠ2,Ⅰ3,Ⅲ2 andⅣhad been polluted Cd, and all heavy metals had been accumulated to some extent in all land use patterns except that As in the whole soil and Zn inⅠ4,Ⅱ,Ⅲ3 andⅤ. The highest integrated pollution index occurred in IV and the lowest one occurred inⅤ, and so for the integrated accumulation index. Through principal component analysis and double sieving stepwise regression analysis, it was found that the maily influence factors of Cu were water storage in capillary porosity and total K, and for Zn were capillary porosity, total N, available P, total K and available K, and for Mn were non-capillary porosity, total N and available K, and for Hg were soil bulk density, total porosity, total P and total K. For Pb, Cd and As, the same factors were non-capillary porosity, water storage in capillary porosity, organic matter, total N, total P, available P and available K.
     (7) Soil quality evaluation system had been found which contained 28 indexes that belonged to soil physical properties, soil chemical and biological characteristics, pollution and accumulation of soil heavy metals. The comprehensive soil qualities of different land use patterns wereⅣ(0.6479)>Ⅲ(0.5386)>Ⅱ(0.4373)>Ⅰ(0.4364)>V (0.2546) by analytic hierarchy process (AHP). It was proved by index weight vectors that the total porosity, organic matter, bacterium number and integrated pollution index of heavy metals had the closest relationship with soil qualities respectively in four categories indexes.
     (8) Based on the construction planning of safety area and soil quality results of different land use patterns in Qianlianghu polder, the land and landscape structures were optimized and predicted by using markov model. According with statistical data of population and grain yield during 1987~2008 year, land population carry capacities in the year of 2010,2015,2020,2025 and 2030 were also calculated and predicted under different live consume standards of simply adequate, spaciousness, well-off and prosperity through the tendency extrapolation method. Moreover, sustainable utilization countermeasures of land resources in Qianlianghu polder were put forward.
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