基于GIS的长江口海域生态系统脆弱性综合评价

气候变化、富营养化、生境破碎等是全球普遍面临的生态问题,科学评估生态系统外部压力及其弹性力,对生态系统管理和生态修复具有重要的指导意义。使用空间主成分分析(SPCA)和层次分析法(AHP)构建评价指标体系,结合地理信息系统软件,对长江口海域生态环境脆弱性进行综合评价,并根据生态环境脆弱性指数(EVI)值,将研究区生态环境脆弱性分为5级:微度脆弱(0.5)、轻度脆弱(0.5—0.8)、中度脆弱(0.8—1.0)、重度脆弱(1.0—1.2)、极度脆弱(1.2—1.5)。结果表明:空间尺度上,长江口口门内生态环境脆弱度最高,生态环境脆弱度从口门内向口门外呈显著的降低趋势,近五年,口门内极度脆弱区空间分布南移;评估区域内,约2000 km~2的极度脆弱区发生了转变,极度脆弱区、重度脆弱区面积占比分别下降了7%和5%,长江口海域生态环境脆弱性明显好转。总体上,近年来大量陆源污染物输入以及生态系统结构变化,是导致长江口生态环境脆弱度较高的重要因素。     

基于地形梯度的岩溶槽谷区土地利用空间格局分析

揭示当前多因素驱动机制下岩溶槽谷区典型地貌单元在地形梯度上土地利用分布的一般规律与差异性特征具有重要意义。以2017年landsat TM高清影像和30 m×30 m DEM（Digital Elevation Model）为数据源,并结合实地调查,通过地形位分布指数、土地利用多样性指数、土地利用程度指数及土地利用相对合理性指数指标计算,探讨岩溶槽谷区地形梯度的土地利用类型空间分布共同特征与差异。结果表明：（1）岩溶槽谷区土地利用类型呈现山坡（高地形位）-槽坝（低地形位）两种分布格局特色存在,且土地利用类型在地形梯度上主要以低、中、高3种地形位组合模式;（2）土地利用类型在地形梯度上呈现梯度效应,表现出各自分布特征与差异;（3）岩溶槽谷区土地利用多样性、土地利用程度和土地利用合理性在地形梯度上分布格局既存在一些共同性特征,又存在各自差异性;（4）地形梯度土地利用特征差异性是受自然因素、社会经济因素、政策因素共同作用的结果。     

Evaluation of groundwater quality using water quality index and its suitability for assessing water for drinking and irrigation purposes: Case study of Sistan and Baluchistan province (Iran)

The present study evaluates the groundwater quality for drinking and agricultural purposes and determines physicochemical characteristics of groundwater in the Sistan and Baluchistan province in Iran. In order to investigate the water quality, sampling was done in 654 open dug wells, the chemical parameters were analyzed, and water quality index was determined. In this regard, Langelier saturation index (LSI), Ryznar Stability index (RSI), Puckorius scaling index (PSI), Larson–Skold index (LS), and Aggressiveness index (AI) were considered to determine water suitability for industrial purposes. Finally, the analytical results were taken to generate the numerical spatial distribution of the parameters using the geographic information system (GIS) environment. According to the results, water sources were less corrosive based on AI and PSI, low and light corrosion according to RSI, and corrosion according to the Larsson–Sckold index. The results of the drinking water quality index showed that 1.2% shared extraction wells were classified as excellent, 52.1% as good, 39% as poor, 6% as very poor, and 1.7% as unsuitable for drinking purpose classes. In addition, irrigating water quality index illustrated that 19.9% and 80.1% wells were placed in the “excellent” and “Good” classes, respectively. Also, the quality of water in this study was categorized as brackish.     

山西高原草地景观的数量分类与排序

草地植被空间格局研究是草地景观研究中一项重要的基础工作。空间格局研究不仅限于描述景观的空间特征,而是要深入分析空间格局的分布规律及影响格局形成的原因及机制。以1∶50万《山西省草地类型图》、《山西省行政区域图》及《山西省地形图》为主要信息源,借助GIS技术,应用TWINSPAN和DCA对山西高原草地景观的1127个样方进行研究。结果表明:(1)在TWINSPAN分类结果中,31个群丛组从左到右的排列顺序很好地揭示了山西高原草地景观的纬向地带性分布规律。即从40°43'N向34°34'N依次分布着北部草原、中部灌草丛和草丛及南部的暖温带草丛。(2)1127个样方DCA排序图纵轴揭示了明显的海拔梯度,即由上至下海拔逐渐降低,相应地草地景观变化为亚高山草甸、灌草丛、草原及河漫滩草甸;DCA排序图的横轴揭示了明显的水分梯度,即从左到右水分逐渐增加。两大优势群丛组样方及44个优势群丛组物种DCA的排序图都很好地刻画了山西高原水热组合的变化,即从西北向东南由于地形地貌引起的水热组合由冷干向暖湿逐渐变化,水热组合的梯度变化进一步影响了草地景观整体的空间分布格局。(3)GIS技术与数量生态学方法相结合有助于丰富景观生态学研究的技术体系。     

Estimates of Lost Material Stock of Buildings and Roads Due to the Great East Japan Earthquake and Tsunami

This article describes research conducted for the Japanese government in the wake of the magnitude 9.0 earthquake and tsunami that struck eastern Japan on March 11, 2011. In this study, material stock analysis (MSA) is used to examine the losses of building and infrastructure materials after this disaster. Estimates of the magnitude of material stock that has lost its social function as a result of a disaster can indicate the quantities required for reconstruction, help garner a better understanding of the volumes of waste flows generated by that disaster, and also help in the course of policy deliberations in the recovery of disaster‐stricken areas. Calculations of the lost building and road materials in the five prefectures most affected were undertaken. Analysis in this study is based on the use of geographical information systems (GIS) databases and statistics; it aims to (1) describe in spatial terms what construction materials were lost, (2) estimate the amount of infrastructure material needed to rehabilitate disaster areas, and (3) indicate the amount of lost material stock that should be taken into consideration during government policy deliberations. Our analysis concludes that the material stock losses of buildings and road infrastructure are 31.8  and 2.1 million tonnes, respectively. This research approach and the use of spatial MSA can be useful for urban planners and may also convey more appropriate information about disposal based on the work of municipalities in disaster‐afflicted areas.     

Designing a “tailor-made” ecological network using geographical information systems

During the last few years, geographical information systems (GIS) have spread as powerful tools for landscape analysis. The main purpose of this work was to use GIS to display an ecological network made up of core areas, key areas and ecological corridors. As an example of the application of this method we refer to the population of deer (Cervus elaphus) and roe deer (Capreolus capreolus) in an alpine area in northwestern Italy. The method provided an overall view of the ecological network of the area, highlighting how linear infrastructures can affect animal populations and consequently, their survival probability.     

A framework for predicting and visualizing the East African wildebeest migration-route patterns in variable climatic conditions using geographic information system and remote sensing

In the Serengeti–Mara ecosystem of East Africa, the migrating wildebeests (Connochaetes taurinus) response to food resource distribution and terrain complexity impacts their movement characteristics. This manifests in varying ways such as movement speed, direction, turning frequency, and moving distance. To investigate these characteristics, indices derived from vegetation quantity (normalized difference vegetation index, NDVI) and relief (slope) were used in our previous work to quantify the relationships between migration route location versus vegetation, relief complexity, and their combination. Least cost pathways determined using these indices were representative of approximate migration routes. The simulated routes were shown to be strongly influenced by vegetation during the dry season. However the impact of climatic change (rainfall) on route location was not investigated though known to influence vegetation recovery patterns. This paper specifically addresses the impact of climatic change on route location. The mean monthly rainfall data were used to classify the rainy and dry seasons in the Serengeti, the Western, and the Mara areas as normal, drier, or wetter than normal, over the 1986–1997 period. The classification is based on the mean monthly rainfall variability about the 11-year seasonal mean. Regression analysis showed strong linear relationships between rainfall and mean NDVI for each one of the three areas. The subsequent seasonal classification based on the corresponding habitat vegetation characteristics (NDVI) revealed the relative variation of vegetation with rainfall. Using the derived general categories, migration routes are then predicted for the various categories using a route attractivity index. The seasonal migration routes were shown to change depending on the relative abundance of the rainfall during the dry season. Dry season migration routes tended toward areas with better vegetation activity, i.e., those characterized by higher NDVI gradients. Our results showed that during the western trek, wetter dry seasons have the effect of delaying the herds movement northwestward. During the northern trek, wetter dry seasons have the effect of delaying the tendency to move westward. However the variation in rainfall conditions during the rainy and dry season had no significant influence on the southern trek route location. We assume that predicted routes based on average general category conditions for different years are representative of main migration route patterns for similar seasons, therefore they are well suited for approximate route prediction, if the climatic characteristics of the year are known.     

Quantitative palaeobiogeography: GIS, phylogenetic biogeographical analysis, and conservation insights

Aim  The utility of GIS-based and phylogenetic biogeographical analysis in palaeobiogeography is reviewed with reference to its ability to elucidate patterns of interest for modern conservation biology, specifically the long-term effects of invasive species.
Location  Emphasis is on biogeographical patterns in the Appalachian basin and mid-continent of North America during the Devonian. Global palaeobiogeographical patterns of the Cambrian are also considered.
Methods  Palaeobiogeographical patterns are assessed within a GIS framework, including both direct range reconstruction and niche modelling methods, and within phylogenetic biogeographical analysis. Biogeographical patterns are considered within multiple clades of fossil invertebrates, including trilobites, crustaceans, brachiopods, and bivalves.
Results  GIS-based analysis (including niche modelling methods) of Devonian invertebrates demonstrates a tightly correlated relationship between sea-level rises and range expansion, dispersal events, and species invasions. The predominance of range expansion and species invasions during the Late Devonian reduced opportunities for vicariant speciation during this interval. Comparison of phylogenetic biogeographical patterns between Cambrian and Devonian trilobites allows discernment of the relative roles of tectonics and eustacy in driving biogeographical patterns.
Main conclusions  GIS analysis and phylogenetic biogeography are powerful tools for analysing the coevolution of the Earth and its biota. Analyses can identify episodes of vicariance and geo-dispersal and produce testable hypotheses for further analysis within the fossil record.     

Non‐destructive dry matter estimation of Alhagi sparsifolia vegetation in a desert oasis of Northwest China

Question: Can above‐ground biomass of naturally growing Alhagi sparsifolia shrubs be estimated non‐destructively? Location: Qira oasis (37° 01′N, 80° 48′E, 1365 ma.s.l.) at the southern fringe of the Taklamakan desert, Xinjiang, NW China. Methods: Two methods were compared to estimate above‐ground biomass (AGB) of Alhagi. At first shrub AGB was estimated by manual ground measurements (called ‘allometric approach’) of length, width and height of 50 individuals. Subsequently regression equations were established between calculated shrub canopy volume and shrub AGB (r²= 0.96). These equations were used to calculate AGB from manual ground measurements in 20 sample plots within the Alhagi field. Secondly, kite‐based colour aerial photography coupled with the use of a Geographic Information System (called ‘GIS approach’) was tested. First and second order polynomial regressions between AGB data of the 50 individual shrubs and their respective canopy area allowed to automatically calculate the AGB of all remaining shrubs covered by the photograph (r²= 0.92 to 0.96). The use of non‐linear AGB regression equations required an automatised separation of shrubs growing solitary or in clumps. Separation criteria were the size and shape of shrub canopies. Results: The allometric approach was more reliable but also more time‐consuming than the GIS‐based approach. The latter led to an overestimation of Alhagi dry matter in densely vegetated areas. However, this systematic error decreased with increasing size of the surveyed area. Future research in this field should focus on improvements of AGB estimates in areas of high shrub density.