黄土丘陵区林草景观界面雨后土壤水分空间变异规律

对黄土丘陵区刺槐林 草地景观界面上雨后土壤表层(0～10 cm)和亚表层(10～20 cm)水分的空间变异规律进行了研究.经典统计学分析表明,草地两层的土壤含水量分别高于林地;林草界面两层的土壤含水量均为弱变异程度,并具有明显的生态梯度.移动窗口法分析表明,林草界面对土壤表层和亚表层的水分影响范围为边界两侧4 m、3 m,影响域分别为8 m、6 m.地统计学分析表明,草地两层土壤含水量空间分布均表现为纯块金效应,林地两层均可拟合成线性模型,而林草界面两层均可拟合成球状模型;林草界面土壤表层、亚表层水分空间依赖性和空间自相关较强,其空间结构异质性明显高于林地和草地.克立格制图描述的林草界面土壤水分的空间分布格局为从边界处向两侧的一定距离范围内,土壤含水量呈条带状分布,而在较远的距离,水分的空间分布呈现出几个明显的斑块状.     

土地利用变化对沙地土壤全氮空间分布格局的影响

利用经典统计学和地统计学相结合的方法,分析了科尔沁沙地东南缘草地和8年前开垦的耕地土壤全氮含量和空间分布格局．结果表明,草地与耕地表层(O～10cm)土壤全氮含量差异不显著,亚表层(10～20cm)含量差异显著(P     

长白山阔叶红松林表层土壤水分空间异质性的地统计学分析

采用时域反射仪对长白山原始阔叶红松林3块50m×50m样地表层土壤(0～7.5cm)水分进行测定,应用地统计学的理论与方法对表层土壤水分的空间异质性进行分析.结果表明:研究区3块样地表层土壤水分变异系数分别为24.32%(样地1)、24.11%(样地2)和23.60%(样地3),均属于中等变异性;该区表层土壤水分的理论变异模型为球状模型,具有高度的空间异质性,其空间异质性以空间自相关部分为主;表层土壤水分的结构比分别为57.9%(样地1,属中等相关性)、83.3%和90.0%(样地2和3,属强烈的空间相关性);研究区表层土壤水分的变程在5.5～13.1m,与贝叶斯方法估计的变程相差不大;通过克立格插值估计,研究区表层土壤水分含量的平均值分别为49.3%(样地1)、52.8%(样地2)和42.6%(样地3).     

喀斯特坡面表层土壤含水量、容重和饱和导水率的空间变异特征

表层土壤水分物理性质对深层土壤水分的动态变化具有重要的作用,研究其空间变化特征有助于深入理解坡地降雨入渗及产流规律,实现土壤水资源的合理利用.基于网格(10m×10 m)取样,用地统计学方法研究了桂西北喀斯特地区典型灌丛坡地90 m×120 m(投影长)表层(0~10 cm)土壤含水量、容重和饱和导水率的空间变异特征.结果表明:研究区土壤含水量、容重和饱和导水率均具有明显的空间依赖性和空间结构.土壤水分含量半变异函数用高斯模型模拟较好,土壤容重与饱和导水率用指数模型拟合较好.土壤含水量表现为强烈的空间自相关性,土壤容重和导水率表现为中等的空间自相关性.土壤含水量与饱和导水率空间连续性的尺度范围较小,而土壤容重空间连续性的尺度范围较大.总体上土壤含水量沿坡向下呈递增趋势,土壤容重呈递减趋势,而土壤饱和导水率沿坡面没有明显变化规律,斑块小而多,表现为高异质性.土壤含水量与土壤容重、饱和导水率均呈极显著负相关,而土壤容重与饱和导水率之间没有明显的相关性.     

南亚热带次生林土壤pH值与含水量的空间异质性

在广西青秀山南坡和北坡的次生林内各建立1块50 m×50 m样地,进行表层土壤(0—10 cm)网格取样,并利用经典统计学与地统计学方法对土壤pH值和含水量的空间异质性进行了分析。结果表明,北坡和南坡的土壤pH值均属弱变异性,而土壤含水量均表现为中等程度变异。除北坡土壤水分含量的理论变异模型为指数模型外,其余土壤指标均为球状模型。两块样地的土壤pH值和含水量表现为中等程度的空间自相关,这是由结构性和随机性因素共同作用的结果。Kriging等值线图显示,北坡土壤pH值的空间变异格局呈现由左向右逐渐递增的趋势,而南坡呈现从左到右逐渐递减的趋势;北坡表土水分含量的最高值出现在样地的左上角和右下角区域,而南坡土壤水分为从左到右逐渐递增。微地貌、群落盖度以及物种分布差异等是影响青秀山南亚热带次生林土壤pH值和含水量空间变异和分布格局的主要因素。     

黄土高原小流域土壤养分的空间异质性

利用地理信息系统的空间分析功能,通过地统计学的半变异函数定量研究了黄土高原典型小流域土壤养分的空间异质性特征。结果表明;土壤有机质,全氮,有效氮,全磷和有效磷的理论模型均为球状模型,由随机因素引起的空间变异占空间总变异的比例小,其值分别为13.333%,10.938%,22.000%,9.091%和27.536%,反映5种养分具有较强的空间自相关格局,但它们的空间自相关范围具有明显的差异。土壤全氮和有效氮变程小,分别是90m和110m,有机质次之,变程是120m,而土壤全磷和有效磷的变程最大为160m,研究成果将有效地指导土壤的取样设计,以及进行土壤养分的空间内插和制图。     

西南峡谷型喀斯特坡地土壤养分的空间变异特征

基于网格(20 m×20 m)取样,采用经典统计学和地统计学方法,研究了西南峡谷型喀斯特坡地土壤养分的空间异质性和分布格局.结果表明:峡谷型喀斯特坡地土壤养分含量为中等和强变异,变异性大小顺序为:速效磷全钾有机质碱解氮全氮全磷速效钾,pH值表现为弱变异,有机质表现为中等程度的变异;不同土壤养分具有良好的空间自相关性,其自相关函数均表现出由正相关向负相关方向发展,拐点为80~100 m,其中全钾和速效磷的Moran I较小,其他指标较大;不同土壤养分的空间变异特征不同,全钾和速效磷最佳拟合模型为指数模型,块金值与基台值的比值[C0/(C0+C)]和变程(A)很小,分形维数(D)较高,空间相关性强烈;其他土壤养分指标的最佳拟合模型均为球状模型,C0/(C0+C)、A和D均呈中等程度的空间相关;Kriging分析表明,pH值、有机质、全氮、全磷和碱解氮呈凹型分布,速效磷和速效钾呈斑块状分布.植被、地形、人为干扰和高异质性的微生境是造成峡谷型喀斯特坡地土壤养分格局差异的主要因素.     

半干旱黄土区沟间天然草地植被空间分异特征

选取陕北黄土高原半干旱丘陵沟壑区梁峁坡作为研究区,以40 m为间隔,调查了31个草本样方,采用传统统计方法和地统计学方法分析了天然草地植被空间分异特征.线性相关和秩相关分析表明:坡位是影响草本植物盖度及干鲜比的重要因子,坡向是影响草本植物平均高度和生物量的重要因子,坡度对草本植物空间分布没有显著影响.使用莫兰指数(Moran氏Ⅰ指数)进行空间相关分析表明:草本植物盖度、高度和干鲜比在60 m间隔距离内呈空间正相关,生物量在180 m内存在显著空间相关性.半方差分析表明,球状理论变异函数模型能够很好地模拟草本植物高度和生物量的空间变异,其变程分别为99.3和66.6 m,且均具有强烈的空间自相关性.干鲜比的理论变异函数模型为高斯模型,变程为78.4 m,具有强烈的空间自相关性;盖度的理论变异函数模型为线性模型.     

喀斯特木论自然保护区旱季土壤水分的空间异质性

采用经典统计学和地统计学方法,分段研究了喀斯特木论自然保护区典型峰丛坡地和洼地旱季表层土壤水分（0～5 cm和5～10 cm）的空间异质性.结果表明：研究区旱季表层土壤水分仍然较高,总体上具有良好的半方差结构;坡地和洼地0～5 cm和5～10 cm土层土壤水分的空间分布均符合指数模型,同一立地条件下两土层土壤含水量具有相似的空间结构和分布格局,相同土层不同立地条件下的差异明显;坡地土壤水分含量的空间相关性中等且连续性好,具有明显的斑块分布格局,其Moran I值的变化相对缓慢;洼地土壤水分含量具有强烈的空间自相关,但变程很短,其Moran I值的波动较大,斑块比较破碎.地形、微地貌、降雨、人为干扰特别是植被是保护区土壤含水量空间变异的重要影响因素,保存完好的原始森林对土壤水分空间异质性具有良好的调控作用.     

长鞘卷叶甲种群空间分布格局的生物地理统计学分析

应用生物地理统计学方法分析了长鞘卷叶甲成虫种群的空间分布格局,在3 m×3 m样方下建立东南→西北方向的半方差函数理论模型,并应用克立格插值方法对其种群密度和空间结构进行估计和模拟。结果表明:球状模型对长鞘卷叶甲成虫种群在该方向上的理论半方差函数有较好拟合效果,其空间分布格局为弱聚集型;成虫在山坡竹林与河岸竹林的变程分别为21.2157和38.8266 m,空间聚集分布的连续性强度分别只有0.3633和0.1758,说明种群在研究区内由空间自相关而产生的结构性变异在总变异中所占比例较小,即变异主要由种群结构的随机性成分引起。     

Doubling protected land area may be inefficient at preserving the extent of undeveloped land and could cause substantial regional shifts in land use

Projection of land use and land-cover change is highly uncertain yet drives critical estimates of carbon emissions, climate change, and food and bioenergy production. We use new, spatially explicit land availability data in conjunction with a model sensitivity analysis to estimate the effects of additional land protection on land use and land cover. The land availability data include protected land and agricultural suitability and is incorporated into the Moirai land data system for initializing the Global Change Analysis Model. Overall, decreasing land availability is relatively inefficient at preserving undeveloped land while having considerable regional land-use impacts. Current amounts of protected area have little effect on land and crop production estimates, but including the spatial distribution of unsuitable (i.e., unavailable) land dramatically shifts bioenergy production from high northern latitudes to the rest of the world, compared with uniform availability. This highlights the importance of spatial heterogeneity in understanding and managing land change. Approximately doubling the current protected area to emulate a 30% protected area target may avoid land conversion by 2050 of less than half the newly protected extent while reducing bioenergy feedstock land by 10.4% and cropland and grazed pasture by over 3%. Regional bioenergy land may be reduced (increased) by up to 46% (36%), cropland reduced by up to 61%, pasture reduced by up to 100%, and harvested forest reduced by up to 35%. Only a few regions show notable gains in some undeveloped land types of up to 36%. Half of the regions can reach the target using only unsuitable land, which would minimize impacts on agriculture but may not meet conservation goals. Rather than focusing on an area target, a more robust approach may be to carefully select newly protected land to meet well-defined conservation goals while minimizing impacts to agriculture.     

Competition for land

A key challenge for humanity is how a future global population of 9 billion can all be fed healthily and sustainably. Here, we review how competition for land is influenced by other drivers and pressures, examine land-use change over the past 20 years and consider future changes over the next 40 years.Competition for land, in itself, is not a driver affecting food and farming in the future, but is an emergent property of other drivers and pressures. Modelling studies suggest that future policy decisions in the agriculture, forestry, energy and conservation sectors could have profound effects, with different demands for land to supply multiple ecosystem services usually intensifying competition for land in the future.In addition to policies addressing agriculture and food production, further policies addressing the primary drivers of competition for land (population growth, dietary preference, protected areas, forest policy) could have significant impacts in reducing competition for land. Technologies for increasing per-area productivity of agricultural land will also be necessary. Key uncertainties in our projections of competition for land in the future relate predominantly to uncertainties in the drivers and pressures within the scenarios, in the models and data used in the projections and in the policy interventions assumed to affect the drivers and pressures in the future.     

Pathogen spillover during land conversion

Pathogen spillover from wildlife to domestic animals and humans, and the reverse, has caused significant epidemics and pandemics worldwide. Although pathogen emergence has been linked to anthropogenic land conversion, a general framework to disentangle underlying processes is lacking. We develop a multi‐host model for pathogen transmission between species inhabiting intact and converted habitat. Interspecies contacts and host populations vary with the proportion of land converted; enabling us to quantify infection risk across a changing landscape. In a range of scenarios, the highest spillover risk occurs at intermediate levels of habitat loss, whereas the largest, but rarest, epidemics occur at extremes of land conversion. This framework provides insights into the mechanisms driving disease emergence and spillover during land conversion. The finding that the risk of spillover is highest at intermediate levels of habitat loss provides important guidance for conservation and public health policy.     

Challenges in using land use and land cover data for global change studies

Land use and land cover data play a central role in climate change assessments. These data originate from different sources and inventory techniques. Each source of land use/cover data has its own domain of applicability and quality standards. Often data are selected without explicitly considering the suitability of the data for the specific application, the bias originating from data inventory and aggregation, and the effects of the uncertainty in the data on the results of the assessment. Uncertainties due to data selection and handling can be in the same order of magnitude as uncertainties related to the representation of the processes under investigation. While acknowledging the differences in data sources and the causes of inconsistencies, several methods have been developed to optimally extract information from the data and document the uncertainties. These methods include data integration, improved validation techniques and harmonization of classification systems. Based on the data needs of global change studies and the data availability, recommendations are formulated aimed at optimal use of current data and focused efforts for additional data collection. These include: improved documentation using classification systems for land use/cover data; careful selection of data given the specific application and the use of appropriate scaling and aggregation methods. In addition, the data availability may be improved by the combination of different data sources to optimize information content while collection of additional data must focus on validation of available data sets and improved coverage of regions and land cover types with a high level of uncertainty. Specific attention in data collection should be given to the representation of land management (systems) and mosaic landscapes.     

A review of influences of land use and land cover change on ecosystems

随着人口的增长和人类社会的发展, 土地利用与土地覆盖变化已经是不可避免。土地利用与土地覆盖变化不仅对生态系统的要素、结构和功能产生深远的影响, 也会对全球变化产生反馈作用。针对土地利用与土地覆盖变化的过程、驱动机制以及在各个方面可能产生的生态环境效应的科学研究已经全面开展。该文综述了土地利用与土地覆盖变化对气候、土壤、生物地球化学循环、生物多样性以及区域生态环境等影响方面的研究进展, 并提出了相关研究的前沿方向展望。随着新技术的不断发展, 学者们将更多地侧重预测未来全球变化背景下的土地利用与土地覆盖变化趋势、合理性以及适应性, 为可持续发展提供基础资料和理论依据。     

土地利用与土地覆盖变化对生态系统的影响

随着人口的增长和人类社会的发展, 土地利用与土地覆盖变化已经是不可避免。土地利用与土地覆盖变化不仅对生态系统的要素、结构和功能产生深远的影响, 也会对全球变化产生反馈作用。针对土地利用与土地覆盖变化的过程、驱动机制以及在各个方面可能产生的生态环境效应的科学研究已经全面开展。该文综述了土地利用与土地覆盖变化对气候、土壤、生物地球化学循环、生物多样性以及区域生态环境等影响方面的研究进展, 并提出了相关研究的前沿方向展望。随着新技术的不断发展, 学者们将更多地侧重预测未来全球变化背景下的土地利用与土地覆盖变化趋势、合理性以及适应性, 为可持续发展提供基础资料和理论依据。     

Assessing uncertainties in land cover projections

Understanding uncertainties in land cover projections is critical to investigating land‐based climate mitigation policies, assessing the potential of climate adaptation strategies and quantifying the impacts of land cover change on the climate system. Here, we identify and quantify uncertainties in global and European land cover projections over a diverse range of model types and scenarios, extending the analysis beyond the agro‐economic models included in previous comparisons. The results from 75 simulations over 18 models are analysed and show a large range in land cover area projections, with the highest variability occurring in future cropland areas. We demonstrate systematic differences in land cover areas associated with the characteristics of the modelling approach, which is at least as great as the differences attributed to the scenario variations. The results lead us to conclude that a higher degree of uncertainty exists in land use projections than currently included in climate or earth system projections. To account for land use uncertainty, it is recommended to use a diverse set of models and approaches when assessing the potential impacts of land cover change on future climate. Additionally, further work is needed to better understand the assumptions driving land use model results and reveal the causes of uncertainty in more depth, to help reduce model uncertainty and improve the projections of land cover.     

北京市生态用地规划与管理对策

不合理土地开发加速了对自然生态系统的干扰和侵占,导致生态系统服务功能下降,危机区域生态安全,开展生态用地规划是构建区域生态安全格局的基础。合理规划和管理不同土地利用类型的数量和空间分布对区域可持续发展具有重要意义。目前我国广泛应用的土地利用分类体系主要以土地的社会经济属性为基础,忽视其生态属性,导致以提供生态系统服务为主、保障生态安全的土地缺乏保护机制,具有重要生态功能的土地得不到有效保护。以北京市为例,建立了北京市生态用地分类与规划的思路与程序,在明确北京市生态安全与生态系统服务功能的关系基础上分析了北京市生态系统服务功能重要性及其空间格局,并进行了北京市生态用地规划。研究规划了保障北京市生态安全的7类生态用地:地表水涵养与保护用地、地下水保护用地、生物多样性保护用地、水土保持用地、河流防护用地、公路防护用地和城市绿地,总面积5137.37km2,占北京市域面积的31.31%。最后从生态用地识别和划分、将生态用地融入土地利用分类体系、生态用地管理措施和对策3个方面探讨了生态用地规划和管理的方法与措施。研究结果为北京市土地利用规划和有效管理提供依据,也为其它地区的生态用地规划提供参考。     

城市生态用地分类及其规划的一般原则

城市生态用地的规划布局是城市规划的难点之一,也是急待解决的问题.本文根据城市生态系统的特点,给出了城市生态用地定义,指出城市生态用地同时具有自然属性和社会属性,依据这个特点,将城市生态用地划分为服务型生态用地和功能型生态用地两大类型,并结合具体的城市生态规划对各种类型的生态用地规划进行了定性分析.     

基于长时间序列landsat数据的科尔沁沙地土地利用演变分析

以科尔沁沙地沙丘-草甸过渡带区域主要土地覆被类型为研究对象，以1987-2017年多时相Landsat TM/OLI遥感影像解译分类为基础，参考生态学植被演替研究方法，系统分析研究区30年来的土地利用/覆被动态演变规律，研究结果表明：（1）决策树法在复杂下垫面不同覆被类型的同步识别效果较好，所有影像分类精度均达到88%以上，分类效果较好，其中2017年分类精度最高为95.24%，达到了分类研究的要求；（2）研究区存在着"半灌丛-草甸地-灌丛"的植被结构特征，且整体表现为"南进北退"的变化趋势。结合土地利用动态度分析结果表明人类活动干涉下，研究区整体上遵循了半干旱区植被条件改善的一般规律，侧面反映该研究区域生态环境的持续不稳定性和脆弱性；（3）研究区覆被类型发生变化的总面积达到2623.59 hm²，总变化强度为63.76%。其中正向演替的比例为52.61%，以半灌丛面积的持续减小与沙地草甸面积的持续扩张为主要变化特征。但同时，半灌丛转为沙地的面积为184.95 hm²，表明以放牧为主的研究区同时发生着局部的逆行演变；（4）质心迁移结果反映了1987-2017年间，除人为影响较大的林地、草地以及耕地向北迁移外，其他植被类型的质心都有很明显的南迁，主要植被类型重心迁移距离依次由大到小为耕地 > 半灌丛 > 灌丛 > 沙地草甸 > 湿地草甸 > 林地。研究通过记录科尔沁沙地连续扩展的时空模式，展示了遥感-生态和时间序列影像在30 m分辨率下跟踪土地利用/覆被变化的潜力，为提高干旱半干旱区土地利用情况的动态监测效率，开展土地利用/覆被动态演变研究提供参考。