生态补偿机制中若干关键科学问题——以甘南藏族自治州草地生态系统为例

以甘南州草地生态系统水源涵养服务为例,构建以机会成本、交易成本和实施成本为参数的参与成本模型确定生态补偿标准。基于生态补偿资金效率的考虑,构建以土地所有者提供的生态系统服务、土地所有者的参与成本和生态系统服务受损风险为参数的空间选择模型,以乡镇为研究单元,对生态补偿区域进行选择,采用聚类分析将全州划为5大等级补偿区:优先补偿区、次级优先补偿区、次级补偿区、临界补偿区和潜在补偿区或可能补偿区,并对各类补偿区的特征进行了分析。构建生态补偿额基尼系数与生态补偿资金效率评价模型,分别评价了补偿额在受偿群体和补偿区域中分配的公平性、合理性与不同等级补偿区的补偿效率。结果表明:①以草地生态系统服务功能的价值(4776.4元/hm²·a)和机会成本(621.3元/m²·a)作为补偿标准的上下限,结合参与成本确定甘南州草地生态系统补偿标准为1999.8元/hm²·a;②草地生态系统的补偿优先度与生态重要性、生态脆弱性呈现出吻合趋同的状态,即草地生态系统优先补偿区既是高效补偿区,又是重要生态区和生态脆弱区;③受偿者(草地生态系统水源涵养服务供给者)得到的补偿额有明显不均衡状态,而在补偿区域(草地生态系统)上的分配却处于绝对平均范围内;④草地生态系统补偿区的优先等级次序与补偿效率吻合,即草地生态系统的优先补偿区的补偿效率最高,每元获取的草地生态系统水源涵养服务为38.18,是临界补偿区的14.68倍;次级优先补偿区的效率仅次于优先补偿区,每元补偿的生态系统服务为21.02。     

陇中黄土丘陵沟壑区人工草地土壤水蚀预测模型

针对陇中黄土丘陵沟壑区土壤水蚀过程复杂且难以有效预测的问题,以定西市安家沟水土保持试验站2005—2016年1~12月人工草地径流场试验数据为主要来源,将流域月降雨量、月侵蚀性降雨量、月径流量、月降雨强度、径流场面积、径流场坡度、土壤砂粒含量、土壤粘粒含量8个因子作为输入因子,月土壤水蚀量作为输出,运用偏最小二乘法(Partial Least-Squares Regression,PLSR)和长短期记忆(Long Short-Term Memory,LSTM)循环神经网络建立人工草地土壤水蚀预测模型,并利用BP(Back Propagation)、RNN(Recurrent Neural Network)、LSTM常见神经网络模型,对模型的有效性进行评估。结果表明：PLSR将模型8个输入因子减少为4个,从而有效解决LSTM神经网络模型对样本数量要求过高的问题; PLSR和LSTM神经网络模型的结合可以有效提高模型对人工草地土壤水蚀过程的预测精度和收敛速度,预测结果的平均相对误差小于4%,相关系数高于其他3种神经网络模型,而迭代次数、均方根误差和平均绝对误差均低于其他3种模型;研究发现坡度对人工草地土壤水蚀过程影响较为明显,降雨量小于25 mm时,人工草地土壤水蚀量不会随坡度增加而明显增长,但当降雨量超过25 mm时,人工草地土壤水蚀量会随坡度明显增加。 PLSR LSTM神经网络土壤水蚀预测模型可以准确预测陇中黄土丘陵沟壑区人工草地土壤水蚀量,为该地区水土流失的准确预报提供新的思路和方法。     

遥感和GIS支持下的云南省退耕还林还草决策分析

以云南省为例，探讨利用地理信息系统技术来确定需要退耕还林还草的耕地数量及其空间分布，其中包括4个步骤，首行,建立土地利用，土壤侵蚀，坡度，植被指数，水体，降雨和温度等数据库，其次，从土地利用数据库中提取旱地的数据，并与坡度数据，土壤侵蚀数据，植被指数数据进行叠架分析，对水体建立缓冲区，并与耕地数据进行叠加分析，再次，退耕还林还草的原则，并在GIS的支持下，确定需要退耕还林还草的空间分布及其面积，最后，利用降雨和温度数据进一步确定分别退耕还林和还草的空间分布及其面积，研究结果可以为云南省的生态环境建设提供科学的依据。     

影响草地土壤呼吸的主要自然因子研究现状

草地生态系统作为陆地生态系统的主体生态类型之一,脆弱的生态环境与频繁的人类活动使之较其他生态系统对全球气候与环境变化的响应更为迅速。草地土壤通过土壤呼吸作用向大气释放CO2是草地生态系统碳循环中最主要的一个环节,土壤呼吸量直接决定了土壤中碳素周转的速度。综合介绍了国内外草地土壤呼吸的研究现状,特别分析了一些自然因素对草地土壤呼吸的影响,对未来测定土壤呼吸的方法提出建议。     

西藏自治区那曲地区草地资源现状与可持续发展

本文简要介绍了西藏自治区那曲地区草地资源基本概况和草地类型、分布等特征,综合分析了影响其可持续发展的三大因子,在现有的基础上提出了该区实现草地可持续发展的途径与对策。     

基于CART模型的鄱阳湖草滩苔草分布与水位波动要素关系

水位波动对鄱阳湖草滩湿地的形成与分布至关重要,但不同要素对湿地植物种的具体影响不尽相同.本研究以湿地优势植被苔草群落为研究对象,通过环湖区样带设置和植被调查得到较大尺度上的苔草分布数据,以不同水文站水文数据结合湖区DEM插值得出各样点水位波动要素数据：年内最大水位差R,年内淹没出露频次F,年平均水位M,最长淹没的出露日期D,年内总出露时间T,用CART模型进行分析.结果表明：1）影响鄱阳湖区草滩湿地苔草群落分布的最直接的水位波动要素为T和R;2）年内总出露时间大于84天（T ≥ 4.619）,年极差水位大于11.3 m（R ≥ 10.41）时,苔草群落的综合分布情况最佳.进一步探讨认为：其他水位波动要素未能被CART模型选为分类依据,可能是因为彼此之间存在相关性;高程决定植被分布,实际上是多种水位波动要素综合影响的结果,精度要求不高时,可以用高程替代水位波动各要素进行简略分析.本研究相关结论可以为鄱阳湖控湖工程今后的运行,提供一定的参考,以维持草滩湿地生态系统的稳定,更好地实现其生态价值.     

Characteristics of Momentum and Heat Transfer over Semiarid Grasslands with Different Grazing Intensities in Inner Mongolia, China

The drag coefficient (C d) and heat transfer coefficient (C h) with the bulk transfer scheme are usually used to calculate the momentum and heat fluxes in meteorological models.The aerodynamic roughness length (z 0m) and thermal roughness length (z 0h) are two crucial parameters for bulk transfer equations.To improve the meteorological models,the seasonal and interannual variations of z 0m,z 0h,coefficient kB 1,C d,and C h were investigated based on eddy covariance data over different grazed semiarid grasslands of Inner Mongolia during the growing seasons (May to September) from 2005 to 2008.For an ungrazed Leymus chinensis grassland (ungrazed since 1979),z 0m and z 0h had significant seasonal and interannual variations.z 0m was affected by the amount and distribution of rainfall.kB 1 exhibited a relatively negative variation compared with z 0h,which indicates that the seasonal variation of z 0h cannot be described by kB 1.To parameterize z 0m and z 0h,the linear regressions between ln(z 0m),ln(z 0h),and the leaf area index (LAI) were performed with R 2 =0.71 and 0.83.The monthly average kB 1 was found to decrease linearly with LAI.The four-year averaged values of C d and C h were 4.5×10 3 and 3.9×10 3,respectively.The monthly average C d only varied by 8% while the variation of C h was 18%,which reflects the different impacts of dead vegetation on momentum and heat transfer at this natural grassland.Moreover,with the removal of vegetation cover,grazing intensities reduced z 0m,z 0h,C d,and C h.     

2000—2009年锡林郭勒典型草原植被对气象因子的响应

应用MODIS数据对2000—2009年植被变化情况及其与气温、降水量进行相关分析。2007年年均气温最高,降水最少,NDVI最大值和生长季平均值最低;在降水量最大的2003年NDVI最大值和生长季平均值最高。全生长季中气温和降水量与NDVI值具有显著或极显著相关,相对于气温、降水量对NDVI值影响更大;前一个月的气温和降水量对NDVI值的影响最大,植被对气象因子的响应具有时滞性。     

Ozone Dry Deposition and Resistances onto Green Grassland in Summer in Central Spain

Measurements of ozone concentrations, and meteorological and surface parameters were carried out over a flat green grassland in northwest Spain, in July 1995. Turbulent parameters and sensible and latent heat fluxes were calculated using the gradient technique. Fluxes and deposition velocity and resistances were evaluated assuming that the diffusivity for heat fluxes was equal to pollutant diffusivity. The daily average value of dry deposition velocity was 6 mm s^-1 but it was influenced by wind velocity and atmospheric stability. Resistances have been calculated according to a simple resistance model and a comparison between theoretical and measured values has been made.     

Mechanisms,monitoring and modeling of shrub encroachment into grassland: a review

Shrub encroachment into arid and semi-arid grasslands has elicited extensive research attention worldwide under the background of climate change and increasing anthropogenic activities. Shrub encroachment may considerably impact local ecosystems and economies, including the conversion of the structure and function of ecosystems, the shift in ambient conditions, and the weakness of local stock farming capacity. This article reviews recent research progresses on the shrub encroachment process and mechanism, shrub identification and dynamic monitoring using remote sensing, and modeling and simulation of the shrub encroachment process and dynamics. These studies can help to evaluate the ecological effect of shrub encroachment, and thus, practically manage and recover the ecological environment of degraded areas. However, the lack of effective measures and data for monitoring shrub encroachment at a large spatial scale severely limits research on the mechanism, modeling, and simulation of shrub encroachment, and the shrub encroachment stages can hardly be quantitatively defined, resulting in insufficient analysis and simulation of shrub encroachment for different spatiotemporal scales and stages shift. Improvement in remote sensing-based shrub encroachment dynamic monitoring might be crucial for analyzing and understanding the process and mechanism of shrub encroachment, and multi-disciplinary and multi-partnerships are required in the shrub encroachment studies.