土地利用结构与生态过程

本文从土地利用与土壤水分、土地利用与土壤养分、土地利用与水土流失3个方面系统讨论了土地利用结构与生态过程研究的现状和特征,指出:1)土地利用结构对土壤水分的影响涉及生态系统、坡面、小流域和区域等系列尺度,土地利用的分布及景观特点影响土壤水分的时空变异;2)土地利用对土壤养分的影响表现在土地利用的镶嵌格局影响土壤养分的分布和迁移,土地利用的变化可以引起土壤养分的变化;3)土地利用与水土流失关系密切,土地利用的改变能够减少或增加径流和土壤侵蚀.尺度不同,土地利用与水土流失的机制也不尽相同.土地利用结构与生态过程的研究,还需要注重大尺度和多尺度上的综合研究.     

Geostatistical methods to identify and map spatial variations of soil salinity

The problem of estimating and predicting spatial distribution of a spatial stochastic process, observed at irregular locations in space, is considered in this paper. Environmental variables usually show spatial dependencies among observations, with lead one to use geostatistical methods to model the spatial distributions of those observations. This is particularly important in the study of soil properties and their spatial variability. In this study geostatistical techniques were used to describe the spatial dependence and to quantify the scale and intensity of spatial variations of soil properties, which provide the essential spatial information for local estimation. In this contribution, we propose a spatial Gaussian linear mixed model that involves (a) a non-parametric term for accounting deterministic trend due to exogenous variables and (b) a parametric component for defining the purely spatial random variation due possibly to latent spatial processes. We focus here on the analysis of the relationship between soil electrical conductivity and Na content to identify spatial variations of soil salinity. This analysis can be useful for agricultural and environmental land management.     

Using landscape indicators and Analytic Hierarchy Process (AHP) to determine the optimum spatial scale of urban land use patterns in Wuhan,China

Quantifying land use patterns and functions is critical for modeling urban ecological processes, and an emerging challenge is to apply models at multiple spatial scales. Methods of determining the optimum scale of land use patterns are commonly considered using landscape metrics. Landscape metrics are quantitative indicators for analyzing landscape heterogeneity at the landscape level. In this study, due to their widespread use in urban landscape analyses and well-documented effectiveness in quantifying landscape patterns, landscape metrics that represent dominance, shape, fragmentation and connectivity were selected. Five metrics include Patch Density, Contagion, Landscape Shape Index, Aggregation Index and Connectivity. Despite a wide application of landscape metrics for land use studies, the majority mainly focuses on the qualitative analysis of the characteristics of landscape metrics. The previous models are limited in exploring the optimum scale of land use patterns for their lack of quantitation. Therefore, taking the City of Wuhan as an example, the land use unit was treated as a patch, and the landscape pattern metrics at different spatial scales were calculated and compared so as to find the optimum one. Furthermore, a mathematical model of landscape metrics was proposed to quantify the scale effect of urban land use patterns, generating a complementary tool to select the optimum scale. In addition, Analytic Hierarchy Process (AHP) was introduced to determine the respective weights of the chosen landscape metrics in this model. Fractal dimension was ultimately applied to verify the chosen optimum scale of our study region. The results indicated that 60 m is confirmed to be the optimum scale for capturing the spatial variability of land use patterns in this study area.     

Threshold effects of coastal urbanization on<Emphasis Type="Italic">Phragmites australis</Emphasis> (common reed) abundance and foliar nitrogen in Chesapeake Bay

The invasion of North American tidal marshes byPhragmites australis, or common reed, is a large-scale ecological problem that has been primarily studied at small spatial scales. Previous local-scale studies have provided evidence that the expansion ofPhragmites is facilitated by disturbance and increased nitrogen (N) associated with agricultural and urban-suburban (developed) land uses along wetland-upland borders. We tested the generality of previous findings across a larger spatial scale and wider range of environmental conditions in Chesapeake Bay, the largest estuarine ecosystem in the USA. We sampled 90 tidal wetlands nested within 30 distinct subestuarine watersheds and examined the relationship between land use andPhragmites abundance and foliar N, an indicator of nitrogen availability. We estimated land use adjacent to wetland borders and within subestuary watersheds and explored the importance of spatial proximity by weighting land use by its distance from the wetland border or subestuary shoreline, respectively. Regression tree and changepoint analyses revealed thatPhragmites abundance sharply increased in almost every wetland where development adjacent to borders exceeded 15%. Where development was <15% but natural land cover at the near the subestuary shoreline was low (<∼35%),Phragmites was abundant, suggesting that wetlands in highly modified watersheds also were susceptible to invasion, regardless of land use adjacent to wetlands.Phragmites foliar N was markedly elevated in watersheds with >14–22% shoreline development, the same level of development that corresponded to high levels of invasion. Our results suggest that development near wetlands is at least partially responsible for patterns of invasion across Chesapeake Bay. Larger-scale phenomena, such as nitrogen pollution at the watershed-subestuary scale, also may be facilitating invasion. Urbanization near coastlines appears to play an important role in the invasion success ofPhragmites in coastal wetlands of Chesapeake Bay and probably much of eastern North America.     

Opportunities and challenges of establishing coastal observing systems

Some of the challenges to establishing and sustaining environmental monitoring are potentially overcome under the framework of global observing systems. Observing systems go beyond monitoring by enabling links between user needs and observations and by providing valued information products to user groups at appropriate spatial and temporal scales. The United Nations established three global observing systems; for climate, oceans, and land and freshwater. Initiatives have also begun to address important issues within coastal ecosystems. Recent socio-political awareness and technical advances have imporoved the opportunities for establishing these observing systems and ensuring their sustainability. Awareness and current technology alone are not enough, and ongoing implementation of these systems is still stymied by a variety of factors. We make several recommendations to promote their success now and in the future.     

Responses of water quality to land use in riparian buffers: a case study of Huangpu River,China

Along with the continuous urbanization process, massive riparian buffers are developed to satisfy the increasing demands for flood protection and economic growth. Such changes of land use types and landscape patterns pose a significant challenge to the protection of the eco-system of urban rivers. This research concentrates on revealing the potential relation between the water quality of the urban river and land characteristics including land use types and landscape patterns of the riparian area and discusses if the relationship varies with spatial scales. The study area of this research are the 800 m riparian buffer of the six river water quality monitoring sections along Huangpu River. Based on the long-term monthly collection data of six monitoring points in Huangpu River, Shanghai, China, and the land use data of 100 m downstream of 1 km upstream of the monitoring point. Using landscape indicators, GIS spatial analysis, and statistical methods, the responses of land use and landscape patterns to water quality in different scales are obtained. Results show that: (1) Urban Land (UL) and Agricultural Land (AL) have an enormous negative contribution to each buffer, which is the primary non-point source pollution and influencing factor. (2) The active contribution of Wetland (WL) and Forestry Land (FL) is the most significant in the small range buffer of 0–200 m. (3) The negative effect of Industrial Land (IL) on water quality is only significant in the small buffer. (4) The effect of landscape pattern on water quality is more significant on the large spatial scale than the small scale. At the same time, this paper extends the conclusion to discuss the land use of the 800 m buffer zone of Huang River by using point to the area, proving that the research result is helpful for the political decision of urban management and provides suggestions for the land optimization of riparian buffers.

     

祁连山黑河山区土地适宜性评价

以黑河山区为研究区域,利用Logic回归模型和空间分析技术对山区土地利用进行适宜性评价.以2011年土地利用现状数据作为背景值,构建气温、降水、海拔、坡度、人口密度、水系、交通网、村镇分布8种因子的评价指标体系.采用多尺度训练的方法确定适宜性评价最佳模拟尺度,对土地利用数据和评价因子进行Logic回归分析,得到评价因子对土地利用适宜性的影响程度.利用Spatial Analyst模块对对黑河山区土地适宜性进行评价,为区域土地资源合理利用提供科学参考.结果表明：（1）适宜性评价最佳尺度为210 m（ROC=0.79）.（2）Logic回归结果显示,坡度、气温（β_Temp=1.11）、降水对林地、草地的影响程度较高,同时距道路距离、人口密度（β_Pop=-0.555）对其分布也有重要影响.（3）山区土地利用适宜性排序为：Max_林地=Max_耕地 > Max_建设用地 > Max_裸地 > Max_草地 > Max_水域,林地与耕地最高,适宜性达到0.99.     

近20年来长江三角洲海岸带典型区土地利用变化与生态环境效应研究

【研究目的】近20年来,长江三角洲海岸带地区土地类型结构发生显著转化,海岸带开发与保护的矛盾凸显。本文旨在开展长江三角洲海岸带典型区土地利用变化与生态环境效应研究,为海岸带地区的土地资源可持续利用、海岸带环境保护提供科学依据。【研究方法】利用美国Landsat卫星系列遥感影像和中国资源卫星系列遥感影像,采用自动监督分类并结合目视解译,获取了研究区1995—2015年共5期土地利用分类数据,分析土地利用变化特征和趋势,探讨长江三角洲海岸带典型区城镇发展、围填海时空变化及生态环境效应。【研究结果】长江三角洲海岸带典型区（南通、上海、嘉兴、宁波和舟山）1995年至2015年,土地利用变化明显,耕地大幅度减少,比例从1995年的68.8%降为2015年的55.7%;城镇建设用地迅速扩张,年平均增加192.8 km²。【结论】在快速城市化过程中,人口、单位面积能源消耗等快速增加,环境问题凸显,大量的耕地转为建设用地,围填海使滨海湿地面积快速减小和消失,导致CO₂和污染物释放与吸收严重失衡,海洋环境受流域和沿海城镇化建设的影响明显,长江口及邻近海域近20年来赤潮频发,研究区陆域和海洋环境压力增加。创新点：选取长江三角洲海岸带典型区,首次以1995—2015年5期序列遥感影像数据为基础,采用空间叠加分析方法,着重分析了建设用地和围填海区域的时空演化特征;以人类活动为主线,综合多种海洋环境指标,分析快速城市化进程中,建设用地和围填海导致的生态环境效应。     

Enhancing the credibility of ecology: Is interdisciplinary research for land use planning useful?

Interdisciplinary approaches involving inputs from both the natural and social sciences represent one operational and social response to the complexity of today's environmental and land use problems. The resulting amalgam can be useful to both science and society, given the right mix of ingredients. Important steps in the planning and conduct of interdisciplinary research include problem indentification; definition of a precise scientific theme derived from the social demand; choice of relevant disciplines; selection of study area and spatial scale; ensuring that the project is adaptable to changing circumstances; obtaining the involvement of scientists, planners and local people; developing a continuum of actions from basic and applied research through to training and information diffusion; early and explicit definition of the criteria for evaluation. Though interdisciplinary approaches have shown their worth, they founder easily. Obstacles include the behavioural and psychological characteristics of individual scientists, differences in scientific method, and bottlenecks of a more administrative, institutional, political and financial nature.The views expressed are those of the authors and not necessarily those of the authors' employers.     

基于神经网络模型的中国表层土壤有机质空间分布模拟方法

基于全国第二次土壤普查得到的6 241个典型土壤剖面数据,采用主成分分析方法和径向基函数神经网络模型建立不同植被类型—土纲单元内土壤有机质与气候、地形和植被等环境因子间的非线性关系,模拟全国表层土壤有机质的空间分析格局。结果表明,该模型具有较准确的预测能力,性能指数达到1.94。与普通克里格法、反比距离法和多元回归模型相比,神经网络模型对621个验证点模拟结果与实测值的相关系数为0.799,分别提高了0.265、0.181和0.120,平均绝对误差分别降低了4.25、4.43和2.34 g/kg,平均相对误差分别降低了30.16%、32.66%和5.93%,均方根误差则分别降低了8.61、8.24和6.24 g/kg;从模拟结果图来看,神经网络模型能够提供更多的细节信息。该方法为大尺度土壤性质空间分布模拟提供了有益的参考。     

Spatial dynamics of soil salinity under arid and semi-arid conditions: geological and environmental implications

Salinity is a highly important problem in arid and semi-arid regions. Consequently, the analysis of soil salinity plays a crucial role in environmental sciences. Environmental variables show spatial variability and statistical tools able to analyze and describe the spatial dependence and quantify the scale and intensity of the spatial variation are needed. Moreover, the spatial prediction has special importance for agricultural transformation of the land or for environmental restoration (selection of the most appropriate species adapted to soil salinity). In this paper we propose a methodological framework based on geostatistics to model the spatial dynamics of soil salinity measurements to further analyze the case of a region in southeastern Spain.     

Application of Continuous Wavelet Transform in?Examining Soil Spatial Variation: A?Review

An adequate understanding of soil spatial variation as a function of space and scale is necessary in ecological modeling, environmental prediction, precision agriculture, soil quality assessment and natural resources management. Soil spatial variation can be partitioned into frequencies (scale) and positions (location) by the wavelet transform. This review focuses mainly on different applications of the continuous wavelet transform (CWT) for the identification of the scale and location dependence of soil attributes. We discussed both wavelet spectra and wavelet coherence in our analysis of soil spatial variation. Global wavelet spectra, being the sum of wavelet spectra over all spatial locations at a scale, can be used to examine the dominant scale of variation. Furthermore, some variations at a particular scale persist over all locations (termed global features), whereas others are present at only a few locations (localized features). Wavelet spectra can be used to identify both localized and global features. The combination of localized and global features provides a complete picture of the scale-location information of different processes in the field and may provide better guidance in designing efficient management practices. Wavelet coherency partitions the total correlation between two variables into correlations at different scales and locations, while also revealing the scale- and location-specific relationship between those two variables. This relationship may be helpful in developing predictive links between one property and another.     

Relationship between the variation of water quality in rivers and the characteristics of watershed at Miyun,Beijing, China

Based on the characteristics of land use and drainage network of the upper watershed of the Miyun Res-ervoir, Beijing, 26 monitoring and sampling sites were selected in different sub-catchments. Temporal and spatial variations in nutrient loss were dealt with in this paper in terms of the monitoring data on the water quality of the main tributaries flowing into the Miyun Reservoir. In combination with the monitoring data on water quality, the impacts of watershed characteristics including land-use type, landscape pattern, and drainage density were assessed, The concentrations of nutrients in the rainy season are higher than those in other seasons, and the concentrations of NO3--N are linearly related to those of total N which is the main form of nitrogen present in the fiver water. The concentrations of nitrogen become higher toward the reservoir along the main rivers. The seasonal variation of ni-trogen in the watershed affected by intensive human activities is very obvious; in the watershed with steady or low water flow, the seasonal variation of nitrogen is less obvious. Forest land and grassland can trap and filter nitrogen effectively. Land-use pattern also has important impacts on the loss of nitrogen. The concentrations of nitrogen and phosphorus in the water bodies show great temporal and spatial variations. On a temporal scale, the concentrations of TN and TP in the rainy reason are higher than those in other seasons. On a spatial scale, the concentrations of TN and NO3--N in the Qingshui River and Chaohe River are highest all the time. The spatial variation of TP is distinct, being obvious at sampling sites near villages. The form of nitrogen and phosphorus loss varies in different hydrological seasons. Dissolved nitrogen and phosphorus are the main forms in streams in non-rainy seasons, the dissolved nitro-gen and total nitrogen decrease in percentage in the rainy season. Particulate nitrogen and phosphorus are the main forms in some rivers. The concentrations of TN and NO3--N from orchards and villages are high whereas those from forest land are lowest. Land-use pattern has impacts on TN and NO3--N losses, at the sampling sites near the source landscape, the concentrations are higher than those at the sampling sites near the sink landscape. Water quality of the rivers which flow into the Miyuan Reservior is influenced by the composition of adjacent soils.     

Effects of land use on spatial patterns of soil properties in a rocky mountain area of Northern China

In the rocky mountain area of North China, soil fertility has decreased with severe soil and water losses under various land uses. Land use has been proven to affect soil fertility spatial distribution patterns at larger scales. However, less information is available about these effects in field scale plots. Soil samples were collected at 2-m intervals by grid sampling from an area (18?×?18 m) within three land use types (poplar woodland, rotation cropland with peanut and sweet potato, and peach orchard). Soil properties including soil particle composition, soil organic matter, total nitrogen (TN), nitrate nitrogen (NO₃ ^?-N), total phosphorus (TP), and available phosphorus (AP) were measured for each sample. The spatial variability and spatial pattern of the soil properties were assessed for the three contrasting land use types. NH₄ ⁺-N, NO₃ ^?-N, and AP in the peach orchard and NO₃ ^?-N in the poplar woodland exhibited strong variation (coefficient of variance >100 %). Other properties showed moderate variations. With annual plowing and fertilization, soil properties in the rotation cropland had less variability and greater spatial autocorrelated ranges. The spatial dependences of sand content, TN, NO₃ ^?-N, and SWC in both the peach orchard and the rotation cropland were weaker than those in the poplar woodland, but the spatial dependences of TP and AP in the peach orchard were stronger than those in either the rotation cropland or the poplar woodland. Human activities such as plowing, fertilization, and harvesting had obvious effects on the spatial variability and spatial pattern of soil properties.     

基于GWR和改进CLUE—S模型的区域土地利用格局模拟研究——以浙江省桐庐县为例

本文以浙江省桐庐县为研究区,在CLUE．S模型空间分析模块的回归建模中,考虑驱动因子对土地利用格局影响的空间不稳定性,用GWRLogistic模型取代全局最小二乘法（OLS）Logistic[D]lJ~模型来建立土地利用格局与其驱动因子之间的回归模型,实现了对CLUE—S模型的改进,并进行土地利用格局模拟的实证研究与模型比较。研究结果表明,运用GWRLogistic对CLUE—S模型进行改进,不但可以获得更高的模拟准确率,而且可以获得各驱动因子对土地利用格局影响的空间分异特征。同时,运用改进的模型定量地分析影响区域土地利用变化的内在机制,进行土地利用格局的动态模拟,预测土地利用未来变化的趋势,可以为桐庐县及其类似地区的土地利用规划决策提供科学依据。     

土地利用变化对全球气候影响的研究进展与方法初探

综合分析了土地利用与土地覆盖变化（LUCC）对全球气候影响研究的重要科学问题和国内外研究现状,在此基础上,考虑各学科的相互交叉、渗透和耦合等特点,提出并初步设计了土地利用变化对全球气候影响研究的星地一体化LUCC—气候—生态系统耦合研究技术方法体系,并就土地利用变化对全球气候影响的LUCC演变规律及动力学机制、LUCC...     

中国历史耕地变化及其对自然环境的影响*

农业开发已经直接或间接地影响并正在影响自然环境的许多方面,中国农业开发历史悠久,对自然环境造成的影响广泛而强烈,对认识人类活动导致的全球与区域环境变化具有代表性。文中总结了近年来基于考古和历史文献记录的中国历史耕地变化定量重建和耕地开发环境影响的研究成果。主要结论包括: (1)中国在历史耕地变化重建方面具有独特的优势,主要数据源包括田亩、税赋、人口等与耕地数量相关的数值记录,考古遗址点、聚落、路网、行政建制等与农业活动相关的信息,有关土地开发和农业生产的描述性记录等三大类。 (2)对全国尺度的耕地面积推断始于春秋战国时期,过去1000年以来已重建了省(路)域的垦殖率,过去300年基于历史记录重建的东北、华北等区域垦殖率的分辨率已到县,在重建基础上利用分配模型获得的过去300年格网化垦殖率的分辨率可达10 km×10 km甚至1 km×1 km。相比于当前广泛使用的国际数据集,这些区域定量重建结果更为准确。(3)历史时期中国耕地的3次大规模扩张分别主要出现在西汉、两宋和清中叶,与此相对应,植被破坏和水土流失从北方地区扩展到南方地区,从平原低地扩展到低山丘陵、深山地区;过去300年耕地变化导致了碳排放的增加和可辨识的区域气候变化。未来中国的历史耕地变化重建及其对环境影响研究,应与国际过去土地利用/覆盖研究衔接,研究重点为延长历史耕地重建时限、提高重建单元的空间分辨率和改进耕地格网化分配模型。     

应用MapGIS空间分析模块进行土地质量地球化学评估的探讨

利用农业地质调查资料,探讨了如何应用MapGIS空间分析模块进行土地质量地球化学评估。以内江市沱江乡土地整理区为例,选取土壤养份指标、土壤环境指标、水、大气环境指标以及大宗农作物安全性指标为主要评价指标,通过MapGIS数字地面模型,绘制出单因素单指标分级图,并应用区对区的空间分析模块进行多指标、多因素的叠加分析,最终绘制成土地质量地球化学分等定级图。采用MapGIS空间分析模块进行土地质量地球化学评估,可以提高土地质量地球化学评估后期成图的效率,其方法简单实用,评估结果与工作区实际情况相符。     

Extraction and Analysis of Land Cover Heterogeneity over China

Spatial heterogeneity exists in land surface at every scale, and it is one of key factors to bring uncertainty to land parameter retrieval from remote-sensed data. This paper proposed a methodology to use the boundary length among different land cover types to characterize and quantify land surface heterogeneity based on high-resolution land cover images. Then the heterogeneity feature at 1 kilometer scale in China was extracted from “GlobalLand30” land cover datasets with the spatial resolution of 30 m. The mixed structure, degree of fragmentation and intra-heterogeneity of eight main vegetation biomes from MODIS land cover product over heterogeneous surface in china were analyzed. Mountain area and ecotone are more heterogeneous than other regions. Savanna biome (average boundary length is 7 426 meters) is the most heterogeneous zone followed by forest, grass/crop and shrub biome with average boundary length of 4 323, 3 160, 1 779 meters, respectively.     

Evaluation on the change characteristics of ecosystem service in Dhanbad district of Jharkhand,India based on land use change

Ecosystem services (ESs) simply refer to those services conferred by Mother Nature for the survival of her offspring living within. But the provision of ESs is continuously affected by human activity and related changes like transformations in land use and land cover. The present study has been initiated to evaluate the pattern of landscape transformation and its impact on ecosystem service, along with estimating the per capita availability of ESs based on remotely sensed data in the Dhanbad district, Jharkhand, India. The result shows that the total ecosystem service value (ESV) loss of the district was $2251959.76 during 1990–2020. The highest loss of ESV was recorded due to the conservation of agricultural land to built-up area ($15884988.50) and vegetation cover on agricultural land ($14451545.01), while the increased vegetation cover on other types of land helped the district to gain back some balance over the loss. But in a smaller scale study, 5 out of the 8 spatial units are facing negative change in ESV, and unfortunately, they are altogether inhabited by more than 85% of the district's total population. That means the loss of ESV is greater where it needs to be more as per population. Moreover, the per capita ESs in the district decreased by 68.48%, while among the spatial units in Dhanbad it decreased the most (89.60%), which is a serious cause for worry in the future. Therefore, this study can contribute to the process of decision-making, proposing ecological conservation and sustainable development plans for the region.