武功山高山草甸土壤微生物生物量碳及其影响因素

研究了武功山高山草甸3个不同坡向土壤微生物生物量碳及其影响因素,结果表明：东坡土壤微生物生物量碳含量与土壤有机质含量显著高于南坡和北坡土壤,南坡土壤高于北坡;土壤速效钾（K）浓度以东坡土壤最高,南坡土壤次之,北坡土壤最低,但3个坡面土壤速效钾K含量之间的差异不显著;东坡土壤有效磷（P）的浓度极显著地高于南坡土壤和北坡土壤有效P浓度;不同坡面土壤铵态氮含量依次为北坡〉南坡〉东坡。土壤土壤微生物量生物量碳与土壤有机质含量和P浓度之间存在显著的正相关性,与速效钾K浓度之间相关性不显著,土壤微生物量生物量碳随着土壤铵态氮含量的升高而减小。     

高寒草地放牧管理最优控制模式

通过对高寒草地植物多样性与生产力对不同放牧强度响应机制的研究表明:多样性与生产力随放牧强度的增加均呈现显著性下降趋势,其中不放牧、轻牧、中牧和重牧下的Shannon指数的平均值分别为4.35,3.89,3.66,3.01,生产力指标(地上生物量均值)分别为987.6,826.8,660.7,535.8 g/m2(鲜重).这表明多样性与生产力对放牧的响应呈现同步性,中牧和重牧是导致二者大幅度下降的主要动'因.应用生物控制论方法,组建了草地放牧管理的最大持续产量模型和最优控制模型.实例计算结果表明:样区滩地、阳坡与阴坡地等三类牧场的牧草保护指标分别为468.1,564.3,614.7 g/m2(鲜重),相应的最大持续产量分别为390.9,471.2,513.3 g/m2(鲜重).确定了草地放牧管理的最优牧草资源种群水平和最优控制量,提出了草地放牧管理的控制对策,为高寒草地保护与可持续利用提供了优化模式和定量依据.     

Relations between the underground biomass and soil organic carbon and nitrogen of the alpine meadow at the Eastern Margin of the Qinghai-Tibet Plateau

This article, by combining field investigation with laboratorial analysis, studies diverse alpine meadow at the Eastern Margin of the Qinghai-Tibet Plateau for the underground biomass dynamics, vertical distribution of the content of soil carbon and nitrogen, the connection between the biomass and the content of carbon and nitrogen. The studies show that underground biomass in the herb layer of upland meadow is more than that in the terrace meadow, while underground biomass in the upland shrubland is the most. The vertical distribution of underground biomass of each type is obvious as in shape of＂T＂. As to the distribution of the content of soil organic carbon in the three sample grounds, it showed that the deeper the soil the less the content of soil organic carbon. In May, unlike at terrace meadow, the underground biomass and the content of soil organic carbon in positive proportion, such revelation at upland meadow and upland shrubland is not apparent. In July, at upland meadow and terrace meadow the underground biomass and the content of soil total nitrogen in positive proportion, such revelation at upland shrubland is not apparent either.     

刈割及放牧对牧草生长的补偿效应

通过研究青海环湖区高寒草甸草场刈割及放牧对牧草的补偿性生长效应,发现轻度刈割和中度刈割后牧草为超补偿生长,重度刈割后为欠补偿生长;轻度放牧条件下可显著提高牧草总产量,中度放牧条件下基本能保持牧草总产量。     

基于时间函数的高寒矿区地表动态下沉规律研究

高寒地区因为其冻土的特殊性质导致其经历开采后随着季节变化易导致上覆岩层破坏,因此,为准确预测高寒地区矿区上覆岩层的动态沉降的发展趋势,本文选取高寒矿区地表富水区作为研究对象,基于Weibull时间函数与分段函数的思路,结合矿区地表InSAR监测数据建立高寒矿区地表动态沉降模型,讨论了该函数模型的适用性。结果表明:高寒矿区冻胀地表沉降的三个阶段沉降量与时间的关系曲线与Weibull时间函数模型对应曲线相符;对Weibull时间函数的双参数取值进行探讨并优化,最终确定当初始、加速阶段的λ取值2.5,η取值0.068,稳定阶段λ取值2.3,η取值0.048时误差处于限差范围内,能较为准确地模拟预测地表的动态沉降过程,该研究可为高寒矿区的防灾减灾及治理工程提供参考。     

若尔盖高寒草甸不同功能群植物数量特征对退化演替的响应

为了查明若尔盖高寒草甸退化过程中植物群落各功能群数量特征的变化趋势,2013年8月利用样方法对若尔盖县境内的沼泽草甸、草原草甸、中度退化草甸和重度退化草甸的植物群落和土壤环境进行了调查.结果为:草地退化过程中,禾本科植物密度、高度和重要值均无显著变化,仅盖度呈显著波动性变化;莎草科植物密度、高度、盖度在中度退化前均无显著变化,重度退化阶段显著降低,重要值呈持续显著下降趋势;豆科植物高度和盖度以中度退化阶段最高,但密度和重要值以草原草甸最高,重度退化阶段最低;蓼科植物密度、高度、盖度和重要值从沼泽草甸到中度退化阶段均显著增加,重度退化阶段消失;杂类草植物密度和盖度在退化过程中呈波动变化,高度和重要值呈波动性增加趋势.结果表明:高寒草甸不同退化阶段功能群植物的生长规律不尽相同,但严重退化可显著影响莎草科、豆科、蓼科和禾本科的生长.回归分析表明土壤氮、磷、钾含量是莎草科、豆科和蓼科的主要限制因子,这意味着向退化高寒草甸中同时施加氮、磷、钾三种肥料将可以促进莎草科、豆科和蓼科植物的生长,有利于高寒草甸生态恢复.     

近2000年来太白山高山带不同海拔植被对气候变化的响应

根据西佛爷池(海拔3410 m)剖面的有机地球化学指标, 重建太白山高山带过去2000年的气候变化。对采自该剖面的样品进行孢粉分析, 并结合太白山跑马梁(海拔3556 m)、三清池(海拔3080 m)和芳香寺(海拔3000 m)剖面的孢粉数据, 进行聚类分析, 探讨高山带不同海拔植被对气候变化响应规律。结果表明, 不同海拔植被对相对冷干气候的响应有更好的一致性, 且林线过渡带内这种一致性更明显。随着现代升温期的到来, 植被对气候的响应主要受高程影响。研究结果可为认识晚全新世以来高山环境系统的气候?植被耦合关系提供一定的参考。     

太白山高山带距今5520年以来气候-环境变化——佛爷池沉积物的多指标记录及其结果的解译

佛爷池为秦岭主峰太白山南坡高山带的冰蚀湖。在其干涸的底床挖掘一条深70 cm的探坑,自坑壁取得沉积物样品。对这一剖面的3个样品做加速器质谱(AMS)14C测年,56个样品做总有机碳含量(TOC)和碳/氮比值(C/N)分析、低频磁化率(?lf)和非滞后性剩磁(ARM)测试、粒度分析和孢粉分析,并计算ARM/?lf。利用这些测年结果建立这一剖面的年代框架,并对TOC和C/N,?lf,ARM和ARM/?lf,平均粒径及栎属孢粉(Qucercus)含量在剖面中的变化进行解译,由此初步推测佛爷池周边距今5520年以来的气候及环境变化。在5520~3800 a BP,气候为冷干,在其中的5100~4300 a BP冷干程度可能最强。在3800~2300 a BP,气候渐转暖湿。在2300~1300 a BP,气候更为湿润。在1300~700 a BP,气候更为温暖,可能是过去5500多年中最温暖的时期。在700~500 a BP,气候再度变冷、变干。由于共同受到东亚季风的影响,太白山高山带中、晚全新世这一气候-环境变化与中国东亚季风区一些地点的变化趋势颇为相似。     

高寒地区多年生禾草人工草地杂草种群动态研究

青藏高原高寒地区——甘肃省天祝县金强河地区多年生禾草人工草地杂草种群动态研究表明：该区多年生人工草地的主要杂草为灰绿藜(Chenopodium glaucum)、香薷(Elsholtzia patrini)、微孔草(Microula sikkimensis)和野胡萝卜(Osmorhiza aristata)，草地建植当年，高大杂草微孔草和野胡萝卜的生长速度动态呈7，8月中旬较高的双峰型，低矮杂草香薷和灰绿藜的生长速度动态呈7月下旬较高的单峰型，所有杂草群落的生物量生长率动态呈7月中下旬较高的单峰型；草地建植第2年，杂草的生长速度动态与第1年完全相同，微孔草和灰绿藜的生物量生长率动态呈6月下旬、8月上旬较高的双峰型，香薷的生物量生长率动态呈7月中下旬相对较高的单峰型，野胡萝卜的生物量生长率动态几乎呈截距为。的水平线．杂草与栽培禾草的生长速度、生物量生长率大小比较及人工草地群落的组分动态分析表明：对青藏高原高寒地区多年生人工草地而言，灰绿藜、香薷和微孔草等杂草是重点防除对象(杂草)，生长季初期是杂草防除的关键时期，建植第1年是杂草防除的关键年份．     

Modelling of Energy Flow, Rotational Grazing and Potential Productivity in an Alpine Meadow Grazing Ecosystem

An eight-compartment model of the energy dynamics of an alpine meadow-sheep grazing ecosystem was proposed based on SHIYOMI's system approach. The compartments were the above-ground plant portion, the underground live portion including roots, the underground dead portion including roots, the above-ground litter Ⅰ (degradable portion), the above-ground litter Ⅱ (undegradable portion), the sheep intake, the sheep liveweight, and the faeces. Energy flows between the eight compartments were described by eight simultaneous differential equations. All parameters in the model were determined from paddock experiments.The model was designed to provide a practical method for estimating the effects of the number of rotational grazing subplots, grazing period, and grazing pressure on the performance of grazing systems for perennial alpine meadow pasture. The model provides at least 28 different attributes for characterizing the performance of the grazing system. Analyses of 270 simulated rotational grazing systems of summer-autumn meadow pasture (grazing from 1st June to 30 October each year) provided an inference base to support two recommendations concerning management variables. First, with a three-paddock, 29-day grazing period and 30.14kJ·m-2·day-1 grazing pressure scheme, the system has the highest total grazing intake, 4250.44 kJ·m-2, during the grazing season. Secondly, with a three-paddock, 7-day grazing period and 28.89kJ·m-2·day-1 grazing pressure scheme, the accumulated graze is 4073.34kJ*m-2.The potential productivity of the alpine meadow under grazing is defined in this paper as the maximal dry biomass of herbage grazed by the grazing animals over the whole growing season. It has been analysed by applying optimal control theory to the model. The productivity is regarded as the objective function to be maximized through optimization of the time course of the grazing pressure, the control variable. The results show that: (1) under constant grazing pressure, the optimal grazing pressure is f16=25.90kJ·m-2·day-1 (f46=f56=0) with the highest accumulated intake of J(1)=3268.17kJ·m-2; and (2) the optimal grazing pressure is f16=25.94kJ·m-2·day-1 (f46≠0, f56≠0) with the maxial accumulated intake J(145)=3500.39kJ·m-2. Under variable grazing pressure, the dynamics of optimal grazing pressure is shown in Fig.6(a) and Eqs. (9)(11), while the potential productivity (the highest accumulated intake) is J(145)=8749.01kJ·m-2, 2.5 times the constant grazing pressure.