Assessing the impact of ecological and economic factors on land degradation vulnerability through multiway analysis

Land degradation (LD) is a global problem which involves climate, soil, vegetation, economic, and population conditions. In Mediterranean Europe climatic variability and human pressure combine to produce soil sealing, erosion, salinisation, fire risk, and landscape fragmentation, all regarded as important factors to start LD. The aim of this paper is to introduce a time-series evaluation of land vulnerability to degradation based on nine ecological and economic variables. The analysis was carried out over 1970–2000 at the municipality level in Latium (central Italy), a region which has shown increasing land vulnerability in the last years. A multiway data analysis (MDA) was applied in order to explore the relationship among indicators over the study period. Their importance in determining LD vulnerability was estimated through a weighting system based on MDA results. A composite index of land vulnerability (LVI) was obtained as the weighted average of the nine variables transformed into single indicators, according to their relationship with LD. Considerable increases in LVI were observed in dry coastal and lowland municipalities close to Rome, thus indicating that climate aridity, population growth, and land use changes are important determinants of land vulnerability in Latium. LVI was positively correlated to the environmental sensitive area index (ESAI) measured on the same spatial and time scales, thus suggesting that a sound evaluation of land vulnerability is possible through LVI score.     

Indirect validation of the Environmental Sensitive Area Index using soil degradation indicators: A country-scale approach

The Environmental Sensitivity Area Index (ESAI) is one of the most used frameworks to monitor land vulnerability to degradation in southern Europe, northern Africa and the Middle East. ESAI outputs were validated on the field at both local and regional scales, but a country or continental scale validation is still missing. Using non-parametric correlations and multivariate statistics, the present study contrasts the spatial distribution of the ESAI over 8100 local municipalities in Italy with 12 soil variables assessing individual soil attributes, soil degradation processes and the overall soil quality. Three supplementary variables assessing elevation, latitude and the urban–rural gradient have been also considered in the analysis. The ESAI correlated with both soil attributes (topsoil organic carbon) and degradation processes (soil contamination risk, landslide risk, grazing pressure and agricultural mechanization, considered a predisposing factor to soil compaction) varying in intensity along the elevation gradient. The approach illustrated provides an indirect evaluation of the reliability of the ESAI as a multi-domain indicator of land vulnerability to degradation in the Mediterranean region.     

Spatial indicators of fire risk in the arid and semi-arid zone of Australia

Fire plays a role in determining the shape of the earth's ecosystems, impacts socio-economic issues, and influences our climate. In arid and semi-arid Australia (70% of the continent), individual fires frequently exceed 1 million ha, and have collectively burnt up to 9% of the total area in a single year, associated with antecedent periods of above average rainfall which boost the fuel load. People affected by these fires – Federal and State governments, pastoralists, Aboriginal communities, larger towns, conservation park managers and tourist operators – all have different outlooks and priorities about these phenomena. Little objective information about the fire regime and its drivers has been available for this vast area with its very low population density. A predictive understanding of the spatial and temporal pattern of risk of large uncontrollable fires is needed to promote pro-active management.We present a conceptual framework which serves both to summarise existing knowledge and to reduce the complexity for a quantitative statistical analysis. This conceptual framework contains four main groups of independent variables; biomass, curing, ignition source, and fire weather. For these groups of variables we identified direct data sources or spatial surrogates. To quantify different aspects of the fire regime, interpretation of NOAA-AVHRR satellite imagery was employed, which identifies both fire hotspots (FHS) and fire affected area (FAA). For temporal variables, we present a surface displaying relationships for different combinations of lag/phase. This highlights different patterns for each region, and the most appropriate timeframes to use in modelling.Results of exploratory regression analysis in arid and semi-arid Australia show that the strongest influence is exerted by biomass or fuel load. As this is highly dependent on antecedent rainfall, we can anticipate a strong effect of climate change on the fire regime. The strongest combinations of relationships may be used as spatial indicators in the development of long-lead fire risk models for these areas. This can help improve the timing of pro-active strategies to manage fire, and in the allocation of sparse funds and resources. Our analysis has highlighted regional patterns of fire across different land tenures. Heightened awareness of these patterns may encourage a more cooperative and coordinated approach to fire management amongst stakeholders.     

乡村生态用地综合识别与分类

以川中丘陵区为例,从乡村生态用地的资源特征、形态特征、功能特征3个方面选取生态敏感性、生境质量等10个指标构建乡村生态用地辨识指标体系,开展乡村生态用地综合识别与分类研究。结果表明:辨识指标体系较全面反映了乡村生态用地特征,可以将生态功能强、生境质量高的生态用地和不适宜纳入生态用地范畴的非生态用地同时辨识出来,方法具有可行性;研究区核心、辅助和底线3种生态用地面积分别占土地总面积的20.48%、34.41%和41.16%,核心生态用地以林地、草地和水域为主,辅助和底线生态用地均以耕地为主;研究区生态用地空间分布均衡性表现为辅助生态用地>底线生态用地>核心生态用地>非生态用地,空间分布差异性则与地势(东北高、西南低)走向基本一致;土地利用/覆被类型与乡村生态用地类型之间呈现出一对多的相互关系,主要是由人类活动程度、地质灾害空间分布和地形地貌的差异等原因造成。本研究可以为构建区域生态安全格局、优化土地利用方式、协调区域生产发展和生态保护之间的矛盾提供参考和借鉴,丰富和发展空间规划学、乡村地理学的内容。     

基于探索性空间数据分析的海坛岛土地利用生态风险评价

生态风险评价作为一种新型环境管理工具,提供了定量化评估土地利用变化生态效应的新视角.本研究以福建海坛岛为案例区,基于1990年Landsat TM与2010年SPOT5遥感影像、2030年平潭综合试验区总体布局规划图和野外调查等数据,构建度量生态终点的生态风险表征指数,运用探索性空间数据分析中的空间自相关和半方差分析方法,对海坛岛过去 现在 未来不同土地利用情景下生态风险进行评价,分析其潜在的风险性及其变化趋势.结果表明： 海坛岛生态风险指数存在明显的尺度效应,在3000 m范围内表现出较强的正相关,生态风险指数空间分布以高 高聚集和低 低聚集类型为主;生态风险指数具有显著的各向同性特点,且其空间分布与对应时期局部空间自相关指数分布模式一致;各生态风险等级区年际变化较为剧烈,波动态势与波动幅度均有所不同;低生态风险区呈先增后降趋势,中、高生态风险区呈先降后升趋势.规划期的人为扰动强烈,高生态风险区在整个区域扩展蔓延.为减低土地利用生态风险、维护区域生态安全,可采取的生态风险控制策略包括：优化土地资源空间格局、保护关键生态区域、控制建设用地规模.
     

What limits fire? An examination of drivers of burnt area in Southern Africa

The factors controlling the extent of fire in Africa south of the equator were investigated using moderate resolution (500 m) satellite-derived burned area maps and spatial data on the environmental factors thought to affect burnt area. A random forest regression tree procedure was used to determine the relative importance of each factor in explaining the burned area fraction and to address hypotheses concerned with human and climatic influences on the drivers of burnt area. The model explained 68% of the variance in burnt area. Tree cover, rainfall in the previous 2 years, and rainfall seasonality were the most important predictors. Human activities – represented by grazing, roads per unit area, population density, and cultivation fraction – were also shown to affect burnt area, but only in parts of the continent with specific climatic conditions, and often in ways counter to the prevailing wisdom that more human activity leads to more fire. The analysis found no indication that ignitions were limiting total burnt area on the continent, and most of the spatial variation was due to variation in fuel load and moisture. Split conditions from the regression tree identified (i) low rainfall regions, where fire is rare; (ii) regions where fire is under human control; and (iii) higher rainfall regions where burnt area is determined by rainfall seasonality. This study provides insights into the physical, climatic, and human drivers of fire and their relative importance across southern Africa, and represents the beginnings of a predictive framework for burnt area.     

1980—2015年南四湖流域景观格局及其脆弱性

流域景观格局及脆弱性变化对流域生态环境具有重要影响.为保障南四湖流域生态环境安全,本研究以流域1980—2015年7期土地利用数据为基础,通过计算景观格局指数分析南四湖流域景观格局变化,利用景观适应度(LAI)和景观敏感度指数(LSI)构建景观格局脆弱度(LVI),并分析其空间分布与变化.结果表明: 1980—2015年,南四湖流域耕地面积比例下降4.6%,建设用地增加39.7%,其他土地利用类型呈波动变化,林地、草地、未利用地面积减少,水域面积增加.耕地一直是南四湖流域的优势景观类型.耕地和水域破碎度增加,其他地类破碎度降低.流域景观整体破碎度有所缓和,景观类型之间形成了较好的连接性,景观格局的不规则性和复杂性下降并朝着均匀化和多样化方向发展.各时期流域景观脆弱度大体上表现出东部高于西部、北部高于南部的趋势,其空间分布与流域地形,以及景观类型的分布、土地利用变化有关.研究期间,流域LVI整体下降,东部景观脆弱度严重地区的景观格局开始趋于分散,逐渐被低一级脆弱区所取代,西北部地区脆弱度的回升最明显,南部及西南部一直是低脆弱区.     

京津冀城市群土地利用生态风险的时空变化分析

以京津冀城市群为研究区,基于1984、1990、2000、2005、2010和2015年土地利用数据,利用斑块密度、蔓延度和土地利用类型的主观权重构建土地利用生态风险指数,从而揭示京津冀城市群地区6个时间节点的土地利用生态风险空间分布特征。土地利用生态风险划分为5个等级:低风险区、较低风险区、中等风险区、较高风险区和高风险区,将较高风险区和高风险区定义为综合高风险区,然后计算其重心转移轨迹,从而探究土地利用生态综合高风险区的空间转移动态变化规律。结果表明在研究时段内:(1)研究区土地利用生态风险的总体分布规律为城市中心城区周边的土地利用生态风险逐渐加剧,非城市地区低于城市地区,且高风险区、较高风险区的面积呈增加趋势。(2)京津冀城市群13个地级市综合高风险区变化各不相同:北京市、天津市、唐山市和廊坊市的综合高风险区呈现出增加的趋势;承德市、张家口市、保定市、石家庄市、秦皇岛市、邯郸市和邢台市的综合高风险呈现出降低的趋势;而沧州市和衡水市几乎不变。(3)综合高风险区的重心转移方向基本分为三类:朝首都方向、朝东部海洋方向和自身发展方向,且重心转移方向与城市的规划、治理及发展方向联系密切。     

基于土地利用变化的江苏沿海地区生态风险格局

为探讨经济快速发展地区土地利用变化对生态系统造成的风险,以江苏沿海地区1990、2000、2010和2015年的遥感解译土地利用数据为基础,基于景观格局指数和生态环境脆弱度构建了区域生态风险指数,在Arc GIS和Fragstats软件支持下,借助地统计分析和空间自相关分析方法,定量评价江苏沿海地区1990—2015年区域生态风险的时空分异特征。结果表明:1990—2015年,江苏沿海地区整体生态安全状况有所好转,研究区生态风险平均值从0.1563减少至0.1529,该区主要处于中等级生态风险。生态风险等级降低区在较高风险区、中风险区和较低风险区均有分布,而等级升高区域主要集中在较低风险区与中风险区,即东部草地和水域地区以及西南部耕地地区,其原因主要是临海产业和临海城镇的快速发展造成土地利用变化加剧,导致生态系统平衡遭到破坏,生态风险加强。区域生态风险整体空间分异性增加,局部呈现高-高聚集和低-低聚集,其中高值聚集区主要由研究区西部外围边界处向南聚集,低值聚集区主要分布在研究区东北部和东部沿海地区。耕地、水域和建设用地是整个研究区生态风险的主要来源。研究结果为该区实现土地可持续利用、促进土地利用与生态环境的协调发展以及制定生态风险管理政策提供科学依据与技术支持。     

矿区土地利用生态风险的时空异质性

以微山县煤矿较集中、地面塌陷较严重的11个乡镇作为研究区,以遥感影像和土地利用现状数据为数据源,获取4期土地利用类型分布图,根据景观生态学理论构建景观意义上的土地利用生态风险指数,结合空间统计学及地统计学理论,探究2000—2016年研究区适宜尺度下土地利用生态风险的时空变化情况及空间异质性。结果表明:1 km×1 km规则网格是最佳研究尺度,在该尺度下研究区土地利用生态风险的空间分布呈集聚模式,且具有很强的空间正相关性;2000—2005年土地利用生态风险指数在小尺度上的随机变异逐渐被较大尺度上的空间结构性变异所取代,2005年生态风险总的空间变异程度较高,2005—2016年随机因素引起的空间变异程度增强;2000—2016年土地利用生态风险呈现由中高、高生态风险向中、中低生态风险转变的特征;生态风险恶化区和明显恶化区主要分布在东部矿区周边、道路沿线、地面塌陷较严重的区域,研究区西南部微山湖沿岸东西两侧,耕地的生态风险恶化程度2010—2016年较高;17年间微山湖湖区的生态风险稳定区和改善区大幅增加,生态风险明显下降。     

Contemporary landscape burning patterns in the far North Kimberley region of north-west Australia: human influences and environmental determinants

Aim This study of contemporary landscape burning patterns in the North Kimberley aims to determine the relative influences of environmental factors and compare the management regimes occurring on Aboriginal lands, pastoral leases, national park and crown land. Location The study area is defined at the largest scale by Landsat Scene 108–70 that covers a total land area of 23,134 km² in the North Kimberley Bioregion of north‐west Australia, including the settlement of Kalumburu, coastline between Vansittart Bay in the west and the mouth of the Berkeley River in the east, and stretching approximately 200 km inland. Methods Two approaches are applied. First, a 10‐year fire history (1990–1999) derived from previous study of satellite (Landsat‐MSS) remote sensing imagery is analysed for broad regional patterns. And secondly, a 2‐year ground‐based survey of burning along major access roads leading to an Aboriginal community is used to show fine‐scale burning patterns. anova and multiple regression analyses are used to determine the influence of year, season, geology, tenure, distance from road and distance from settlement on fire patterns. Results Satellite data indicated that an average of 30.8% (±4.4% SEM) of the study area was burnt each year with considerable variability between years. Approximately 56% of the study area was burnt on three or more occasions over the 10‐year period. A slightly higher proportion of burning occurred on average in the late dry season (17.2 ± 3.6%), compared with the early dry season (13.6 ± 3.3%). The highest fire frequency occurred on basalt substrates, on pastoral tenures, and at distances 5–25 km from roads. Three‐way anova demonstrated that geological substrate and land use were the most significant factors influencing fire history, however a range of smaller interactions were also significant. Analysis of road transects, originating from an Aboriginal settlement, showed that the timing of fire and geology type were the most significant factors affecting the pattern of area burnt. Of the total transect area, 28.3 ± 2.9% was burnt annually with peaks in burning occurring into the dry season months of June, August and September. Basalt uplands (81.2%) and lowlands (30.1%) had greater areas burnt than sandstone (12.3%) and sands (17.7%). Main conclusions Anthropogenic firing is constrained by two major environmental determinants; climate and substrate. Seasonal peaks in burning activity in both the early and late dry season relate to periods of optimal fire‐weather conditions. Substrate factors (geology, soils and physiognomy) influence vegetation‐fuel characteristics and the movement of fire in the landscape. Basalt hills overwhelmingly supported the most frequent wildfire regime in the study region because of their undulating topography and relatively fertile soils that support perennial grasslands. Within these spatial and temporal constraints people significantly influenced the frequency and extent of fire in the North Kimberley thus tenure type and associated land uses had a significant influence on fire patterning. Burning activity is high on pastoral lands and along roads and tracks on some tenure types. While the state government uses aerial control burning and legislation to try to restrict burning to the early dry season across all geology types, in practice burning is being conducted across the full duration of the dry season with early dry season burning focused on sandstone and sand substrates and late dry season burning focused on basalt substrates. There is greater seasonal and spatial variation in burning patterns on landscapes managed by Aboriginal people.     

Analyzing spatial variations in land use/cover distributions: A case study of Nanchang area,China

Quantification of spatial variation is important for analyzing and predicting the environmental and social impacts of land development. This paper presents a density-based framework to analyze spatial variations within land use/cover classes through a case study of the Nanchang area, China. By means of grid sampling, the categorical patches were represented by grid densities, and spatial indicators of class abundance, scale-area curve and neighborhood density were constructed to measure the spatial variables of area, distance and scale. The scale variations within each class were demonstrated by abundance indicators and were divided into three types with different similarity degrees, which were measured by coefficients of congruence. These variations roughly corresponded to the distribution patterns revealed by the scale-area indicators. The scaling behaviors of these patterns exhibited discontinuity and coherence, which were possibly affected by the change rates of some patch characteristics in the classes. The neighborhood density indicators showed that every class was more aggregated at short distances, while multimodal patterns fluctuating in nearly random distributions occurred at considerable distances. The degree of clumping correlated positively with the abundance of each class. The characteristics of distribution sizes, ranges and patch isolation in these classes left some imprints on the variations in aggregation intensity. These findings have implications for data integration, mechanism exploration and methodological framework, which are also needed for management practices.     

Terrestrial ecosystems from space: a review of earth observation products for macroecology applications

Aim Earth observation (EO) products are a valuable alternative to spectral vegetation indices. We discuss the availability of EO products for analysing patterns in macroecology, particularly related to vegetation, on a range of spatial and temporal scales. Location Global. Methods We discuss four groups of EO products: land cover/cover change, vegetation structure and ecosystem productivity, fire detection, and digital elevation models. We address important practical issues arising from their use, such as assumptions underlying product generation, product accuracy and product transferability between spatial scales. We investigate the potential of EO products for analysing terrestrial ecosystems. Results Land cover, productivity and fire products are generated from long‐term data using standardized algorithms to improve reliability in detecting change of land surfaces. Their global coverage renders them useful for macroecology. Their spatial resolution (e.g. GLOBCOVER vegetation, 300 m; MODIS vegetation and fire, ≥ 500 m; ASTER digital elevation, 30 m) can be a limiting factor. Canopy structure and productivity products are based on physical approaches and thus are independent of biome‐specific calibrations. Active fire locations are provided in near‐real time, while burnt area products show actual area burnt by fire. EO products can be assimilated into ecosystem models, and their validation information can be employed to calculate uncertainties during subsequent modelling. Main conclusions Owing to their global coverage and long‐term continuity, EO end products can significantly advance the field of macroecology. EO products allow analyses of spatial biodiversity, seasonal dynamics of biomass and productivity, and consequences of disturbances on regional to global scales. Remaining drawbacks include inter‐operability between products from different sensors and accuracy issues due to differences between assumptions and models underlying the generation of different EO products. Our review explains the nature of EO products and how they relate to particular ecological variables across scales to encourage their wider use in ecological applications.     

Changes and interactions between forest landscape connectivity and burnt area in Spain

The spatial structure, functionality and dynamics of forest landscapes in peninsular Spain and the Balearic Islands were compared over the last five decades. Two particular features were studied in the sample sites: forest connectivity for wildlife and areas burnt by wildfires. 191 Squares, each 4 km × 4 km, were selected from the SISPARES (the monitoring framework designed to evaluate the trends in the structure of Spanish rural landscapes) environmental strata. Aerial photographs from 1956, 1984, 1998 and 2008 were interpreted and 11 land cover categories mapped and checked in the field, using a minimum mapping area of one hectare. The Equivalent Connected Area Index was used to assess forest connectivity over the sampling period. Social and economical factors were assessed using indicators of farm intensiveness. The Spanish forest connectivity has improved in the last five decades although two different trends can be identified: the first 40 years are characterized by positive rates of growth whereas the 10 last years are characterized by their stability. Nevertheless the area of burnt land was higher along the first 25 studied years and decreased significantly over the last decade.Our results show the climate is the main driver in the evolution of forest connectivity and burnt area in the forest landscapes, playing a direct role on forest biomass production and wildfire ignition and propagation, as well as an indirect role by keeping vertical and horizontal forest continuity through the landscape spatial pattern. Social and economic factors are very important drivers as well: Rural population density and farm size average have been tested as good indicators of landscape artificiality, highly correlated to wildfire hazard and forest connectivity.Finally, we have pointed out the evolutionary path followed by SISPARES framework as a tool for monitoring rural landscapes. It emphasises on the requirement of a 30 years time window for building-up reliable dynamic multifunctional model.     

Potential role of ignition management in reducing unplanned burning in Arnhem Land,Australia

Fire management attempts to coerce fire into a desired regime using three primary strategies: prescribed burning, fire suppression and ignition management. The West Arnhem Land Fire Abatement project (WALFA), where prescribed Early Dry Season burning is used to reduce unplanned Late Dry Season burning, is heralded as model for prescribed burning. However, a previous analysis found that Late Dry Season area burnt in WALFA had been reduced further than would be expected based purely on the Early Dry Season treatment area. This study investigated whether treatment has reduced the number and size of unplanned fires. Daily burnt area mapping from MODIS satellite sensors was used to identify individual fires to compare fire activity before and after management was introduced in WALFA (2005) and in a control region in East Arnhem Land. Late Dry Season area burnt reduced after treatment in WALFA but also in the control region. The number of fires in August–October increased after treatment. There is a period from early August until late September when human ignitions can cause huge fires. Late Dry Season area burnt was strongly influenced by the size of the largest single fire and only weakly by the number of ignitions. Early Dry Season area burnt had modest effects on both the number and maximum size of Late Dry Season fires. Eliminating the largest fire in each 1600 km² sample block would have halved the total Late Dry Season area burnt. A similar reduction could be obtained from a 14% annual treatment with Early Dry Season fire, but this may not reduce the overall area burnt. If overall fire frequency is the main threat to biodiversity in the savannas, then the best solution will be to prevent the small subset of fires that have the potential to become very large.     

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。     

Wildfire–vegetation dynamics affect predictions of climate change impact on bird communities

Community‐level climate change indicators have been proposed to appraise the impact of global warming on community composition. However, non‐climate factors may also critically influence species distribution and biological community assembly. The aim of this paper was to study how fire–vegetation dynamics can modify our ability to predict the impact of climate change on bird communities, as described through a widely‐used climate change indicator: the community thermal index (CTI). Potential changes in bird species assemblage were predicted using the spatially‐explicit species assemblage modelling framework – SESAM – that applies successive filters to constrained predictions of richness and composition obtained by stacking species distribution models that hierarchically integrate climate change and wildfire–vegetation dynamics. We forecasted future values of CTI between current conditions and 2050, across a wide range of fire–vegetation and climate change scenarios. Fire–vegetation dynamics were simulated for Catalonia (Mediterranean basin) using a process‐based model that reproduces the spatial interaction between wildfire, vegetation dynamics and wildfire management under two IPCC climate scenarios. Net increases in CTI caused by the concomitant impact of climate warming and an increasingly severe wildfire regime were predicted. However, the overall increase in the CTI could be partially counterbalanced by forest expansion via land abandonment and efficient wildfire suppression policies. CTI is thus strongly dependent on complex interactions between climate change and fire–vegetation dynamics. The potential impacts on bird communities may be underestimated if an overestimation of richness is predicted but not constrained. Our findings highlight the need to explicitly incorporate these interactions when using indicators to interpret and forecast climate change impact in dynamic ecosystems. In fire‐prone systems, wildfire management and land‐use policies can potentially offset or heighten the effects of climate change on biological communities, offering an opportunity to address the impact of global climate change proactively.     

Historic distribution and driving factors of human-caused fires in the Chinese boreal forest between 1972 and 2005

Aims The pattern and driving factors of forest fires are of interest for fire occurrence prediction and forest fire management. The aims of the study were: (i) to describe the history of human-caused fires by season and size of burned area over time; (ii) to identify the spatial patterns of human-caused fires and test for the existence of 'hotspots' to determine their exact locations in the Daxing'an Mountains; (iii) to determine the driving factors that determine the spatial distribution and the possibility of human-caused fire occurrence.Methods In this study, K -function and Kernel density estimation were used to analyze the spatial pattern of human-caused fires. The analysis was conducted in S-plus and ArcGIS environments, respectively. The analysis of driving factors was performed in SPSS 19.0 based on a logistic regression model. The variables used to identify factors that influence fire occurrence included vegetation types, meteorological conditions, socioeconomic factors, topography and infrastructure factors, which were extracted and collected through the spatial analysis mode of ArcGIS and from official statistics, respectively.Important findings The annual number of human-caused fires and the area burnt have declined since 1987 due to the implementation of a forest fire protection act. There were significant spatial heterogeneity and seasonal variations in the distribution of human-caused fires in the Daxing'an Mountains. The heterogeneity was caused by elevation, distance to the nearest railway, forest type and temperature. A logistic regression model was developed to predict the likelihood of human-caused fire occurrence in the Daxing'an Mountains; its global accuracy attained 64.8%. The model was thus comparable to other relevant studies.     

密云水库流域多尺度景观生态风险时空演变趋势

密云水库作为北京重要的地表饮用水水源地、水资源战略储备基地受到广泛关注，相关研究多基于流域尺度，缺乏多尺度针对水源保护区的生态风险评价，开展多尺度生态风险评价有利于指导密云水库流域高质量和可持续发展。以1990、2000、2010和2018年4期土地利用数据为基础，基于景观指数，采用地统计学方法，分析流域土地利用类型及变化，从流域尺度、水源保护区尺度构建生态风险评价模型，揭示生态风险时空变化。结果表明：(1)流域内主要土地利用类型为林地和草地，随着城市扩张和“退耕还林”等政策实施，耕地和未利用地面积减少，建设用地面积增加，流域景观趋于复杂和分散，破碎化程度加剧；(2)生态风险区域在流域尺度呈“边缘高、中间低”的空间分布规律，高风险区域面积逐渐向低风险区域转移，高风险区域集中分布在流域边缘的南部密云区、兴隆县、赤城县和流域北部丰宁县，生态安全逐渐提高。(3)水源保护区尺度呈“中间高、边缘低”的空间分布规律，高风险面积逐渐减少且空间分布集中，生态风险趋于减弱。(4)流域景观生态风险呈正相关关系，Moran’s I指数均大于0,分别为0.322、0.305、0.298和0.317,1990年...