Spatial Autocorrelation Patterns Research Articles

Application of geographic weighted regression to establish flood-damage functions reflecting spatial variation

Flood damage functions are necessary to ensure comprehensive flood-risk management. This study attempts to establish a residential flood-damage function through interviewing the residents living in the region where flood disasters occur frequently. Keelung River basin, near Taipei Metropolitan in Taiwan was selected as study area. Flood damages are related to the flood depths, which are the most commonly considered factor in previously published work. Ordinary least squares (OLS) regression was used to construct the flood-damage function at the beginning. Analytical results indicate that flood depth is the significant variable, but the spatial pattern of the residuals shows that residuals exhibit spatial autocorrelation. The Geographically Weighted Regression (GWR) Model was then applied to modify the traditional regression model, which cannot capture spatial variations, and to reduce the problem of spatial autocorrelation. The R-square value was found to increase from 0.15 to 0.24, and the spatial autocorrelation in the residuals was no longer evident. A modified OLS model with a dummy variable to capture the spatial autocorrelation pattern was also proposed for future applications. In conclusion, the residential flood damage is determined by flood depth and zone, and the GWR model not only captures the spatial variations of the affecting factors, but also helps to discover the independent variable to modify the traditional regression model.

Harmonic Analysis of the Spatiotemporal Pattern of Thunderstorms in Iran (1961–2010)

The current study aimed at investigating cycles and the spatial autocorrelation pattern of anomalies of thunderstorms in Iran during different periods from 1961 to 2010. In this analysis, 50-year periods (1961–2010) of thunderstorm codes have been collected from 283 synoptic stations of Meteorological Organization of Iran. The study period has been divided into five different decades (1961–1970, 1971–1980, 1981–1990, 1991–2000, and 2001–2010). Spectral analysis and Moran’s I were used to analyze cycles and the spatial autocorrelation pattern, respectively. Furthermore, in order to conduct the calculations, programming facilities of MATLAB have been explored. Finally, Surfer and GIS were employed to come up with the graphical depiction of the maps. The results showed that the maximum of positive anomalies mainly occurred in the northwestern and western parts of Iran due to their special topography, during all the five studied periods. On the other hand, the minimum of negative anomalies took place in central regions of the country because of lack of appropriate conditions (e.g., enough humidity). Moran’s I spatial analysis further confirmed these findings as Moran’s I depicts the positive and negative spatial autocorrelation patterns in line with negative and positive anomalies, respectively. However, in recent decades, this pattern has experienced a declining trend, especially in southern areas of Iran. The results of harmonic analysis indicated that mainly short-term and midterm cycles dominated Iran’s thunderstorms.

Impact of Climate on Food Security in Mainland China: A New Perspective Based on Characteristics of Major Agricultural Natural Disasters and Grain Loss

Under the background of global warming, China has experienced frequent natural disasters that have seriously affected grain production in recent decades. Based on historical documents from 1978–2014, we explored the spatio-temporal variation of five major kinds of natural disasters and grain losses in China using statistical techniques: the Mann-Kendall (MK) test, social network analysis (SNA), and geographic information system (GIS) tools. The disaster intensity index (Q) clearly showed the variation of natural disasters; all of China experienced a significant increasing trend at an annual scale, reaching its peak (27.77%) in 2000. The step change points in floods, droughts, hail, and low-temperature events began to occur in 1983, 1988, 1988, 1992, respectively, while no obvious trend was detected for typhoon activity from 2001 to 2014. Drought and flood were the most serious types of disaster over the last four decades, accounting for more than 50% of total grain losses. Eight major provinces were identified with severe grain losses: Heilongjiang, Shandong, Henan, Hebei, Anhui, Sichuan, Jiangsu, Hunan, and Hubei. Five studied natural disaster types were identified throughout the seven physical geographical regions. Spatial distribution for the different disaster types showed significant geographical distribution characteristics. Natural disasters gradually became more diverse from north to south. Droughts, hail, and low-temperature disasters were randomly distributed throughout China; flood and typhoon disasters exhibited significant spatial auto-correlation and clustering patterns. Finally, in accordance with the intensity of natural disaster, the annual grain losses at the provincial scale initially increased (ranging from 0.14 million to 3.26 million tonnes in 1978–2000), and then decreased after 2000 (ranging from 3.26 million to 1.58 million tonnes in 2000–2014). The center of gravity of grain losses gradually moved northward. These results emphasize that developing different strategies for disaster prevention and mitigation programs in the major grain producing areas (e.g., Heilongjiang, Shandong, and Henan) are critical and important to China’s food security.

海南岛东北部土地利用与生态系统服务价值空间自相关格局分析

PDF HTML阅读 XML下载 导出引用 引用提醒 海南岛东北部土地利用与生态系统服务价值空间自相关格局分析 DOI: 10.5846/stxb201803090468 作者: 作者单位: 海南省林业科学研究所,海南省林业科学研究所,海南省林业科学研究所 作者简介: 通讯作者: 中图分类号: 基金项目: 海南省财政科技计划资助（SQ2017JSKF0035，KYYS-2018-32） Spatial autocorrelation pattern analysis of land use and the value of ecosystem services in northeast Hainan island Author: Affiliation: Hainan Forestry Institute,, Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:土地利用/覆被变化是全球环境变化的重要原因，对生态系统服务价值空间分布格局有直接影响。以海南岛东北部为研究对象，基于遥感影像数据，应用空间自相关理论定量探讨了土地利用与生态系统服务价值的空间自相关格局和分布特征，并运用双变量空间自相关分析两者之间的空间响应规律。结果表明：2016年海南岛东北部生态系统服务功能总价值为132.09亿元，其中林地构成生态系统服务功能价值的主体，而湿地的单位生态系统服务价值最高。土地利用类型具有显著的空间自相关性（P < 0.05），不同土地利用类型所表现的空间聚集或异常的区域及范围明显不同，以建设用地和林地的空间聚集性最强。研究区生态系统服务价值在空间上呈显著的正相关性（P < 0.05），高值区明显聚集于海岸带、东寨港和清澜港红树林一带，低值区集中在海口城区、文昌北部农耕区域；土地利用程度与生态系统服务价值呈空间负相关关系（P < 0.05），且具有明显的空间溢出效应。根据研究结论建议继续实施生态修复与保护政策，优化土地利用结构，提升生态核心的服务价值，实现区域可持续发展和维护生态安全。 Abstract:Land use and land cover change are important factors for global environmental change, and they also directly affect the spatial distribution patterns of the values on ecosystem services. This study used remote sensing image data and applied spatial autocorrelation theory to quantify the spatial autocorrelation patterns and distribution characteristics of land use and the value of ecosystem services in northeastern Hainan island. Additionally, we used a bivariate spatial autocorrelation to analyze the spatial response law. The results showed that the total value of the ecosystem services function in northeastern Hainan island was 13.209 billion yuan in 2016, in which forests had the largest contribution, while as for the unit ecosystem service value, the contribution of wetlands was the highest. Land use types had a significant spatial autocorrelation (P < 0.05). The area and scope of spatial aggregation and the anomaly represented by different land use types were significantly different. The ecosystem service value of the study area had a significant positive correlation in space (P < 0.05). The high value area was in the coastal zone and mangrove area in Dongzhaigang and Qinglangang. The low value area was in Haikou city and the farming area in northern Wenchang. The land use degree was negatively correlated with the value of ecosystem services (P < 0.05), and there was a clear spatial spillover effect. According to the study results, we suggest that ecological restoration and protection policies be implemented, and there should be optimization of land use structure, enhancement of the service value of the ecological core, and regional sustainable development to maintain ecological security. 参考文献 相似文献 引证文献

Spatial autocorrelation and data uncertainty in the American Community Survey: a critique

ABSTRACTWe argue that the use of American Community Survey (ACS) data in spatial autocorrelation statistics without considering error margins is critically problematic. Public health and geographical research has been slow to recognize high data uncertainty of ACS estimates, even though ACS data are widely accepted data sources in neighborhood health studies and health policies. Detecting spatial autocorrelation patterns of health indicators on ACS data can be distorted to the point that scholars may have difficulty in perceiving the true pattern. We examine the statistical properties of spatial autocorrelation statistics of areal incidence rates based on ACS data. In a case study of teen birth rates in Mecklenburg County, North Carolina, in 2010, Global and Local Moran’s I statistics estimated on 5-year ACS estimates (2006–2010) are compared to ground truth rate estimates on actual counts of births certificate records and decennial-census data (2010). Detected spatial autocorrelation patterns are found to be significantly different between the two data sources so that actual spatial structures are misrepresented. We warn of the possibility of misjudgment of the reality and of policy failure and argue for new spatially explicit methods that mitigate the biasedness of statistical estimations imposed by the uncertainty of ACS data.

Flow–ecology relationships are spatially structured and differ among flow regimes

Abstract In streams, hydrology is a predominant driver of ecological structure and function. Providing adequate flows to support aquatic life, or environmental flows, is therefore a top management priority in stream systems. Flow regime classification is a widely accepted approach for establishing environmental flow guidelines. However, it is surprisingly difficult to quantify relationships between hydrology and ecology (flow–ecology relationships) while describing how these relationships vary across classified flow regimes. Developing such relationships is complicated by several sources of spatial bias, such as autocorrelation due to spatial design, flow regime classification and other environmental or ecological sources of spatial bias. We used mixed moving‐average spatial stream network models to develop flow–ecology relationships across classified flow regimes and to assess spatial patterns of these relationships. We compared relationships between fish traits and life‐history strategies with hydrologic metrics across flow regimes and assessed whether spatial autocorrelation influenced these relationships. Trait–hydrology relationships varied between flow regimes and across all streams combined. Some relationships between traits and hydrologic metrics fit predictions based on life‐history theory, while others exhibited unexpected relationships with hydrology. Spatial factors described a large proportion of variability in fish traits and different patterns of spatial autocorrelation were observed in different flow regimes. Synthesis and applications. Further work is needed to understand why flow–ecology relationships vary across classified flow regimes and why these relationships may not fit predictions based on life‐history theories. Managers determining environmental flow standards need to be aware that different hydrologic metrics are often important drivers of fish trait diversity in different flow regimes. Flow–ecology relationships may therefore be confounded by spatial structure inherent in flow regime classification and much existing biological data. Complex patterns of spatial bias should be considered when managing stream systems within an environmental flows framework.

Shallow landslides predisposing and triggering factors in developing a regional early warning system

Landslides are the most dangerous and common natural phenomena causing higher number of victims and damages in Piemonte (north-western Italy). An integrated statistical approach to identify the main predisposing and triggering factor causing shallow landslides occurrence based on a large dataset of historical rainfall-induced shallow landslides and a long-time series of rainfall data is presented. Historical shallow landslide events were compared with territorial and rainfall characteristics. Exploratory Spatial Data Analysis (ESDA) has been performed in order to explore the spatial distributions of landslides with the environmental quantitative variables (morphometry and rainfall) to identify possible patterns of spatial autocorrelation. ESDA showed strong autocorrelation of landslide locations with rainfall variables, while resulting in low values for morphometric parameters at the investigated scale. Moreover, by intersecting landslides distribution with categorical land thematic parameters (land thematic maps) allowed to identify areas with different landslide density occurrence. Resulting susceptibility-related areas were used to improve the landslides regional Early Warning System of Piemonte based on refined empirical intensity vs duration (I-D) rainfall thresholds.

Arrangement of High-standard Basic Farmland Construction Based on Village-region Cultivated Land Quality Uniformity

As an important constitute of land consolidation, high-standard basic farmland construction is an important means to protect the quantity, quality and ecological environment of cultivated land. Its target not only lies in the increase of cultivated land quantity, but also the improvement of cultivated land quality, agricultural production conditions and ecosystem environments. In the present study, the quality evaluation method and construction arrangement of cultivated land were explored to facilitate the process of decision-making and implementation for high-standard basic farmland construction (HSBFC) with administrative village as the unit. Taking the land comprehensive improvement project area in Quzhou County, Handan City, Hebei Province as a case study, the whole process of the study comprised of three steps: 1) establishment of the evaluation model of cultivated land quality uniformity based on regional optimum cultivated land quality, and construction of the uniformity evaluation index system from the aspects of soil fertility quality, engineering quality, spatial quality and eco-environment quality, according to the new concept of cultivated land quality; 2) calculation of cultivated land quality uniformity by grading indicators, assigning scores and weighting sums, exploring the local homogenization characteristics of regional cultivated land quality through spatial autocorrelation analysis, and analyzing the constraints and transformative potential of barrier factors; 3) arrangement of HSBFC according to the principle of concentration, continuity and priority to the easy operation. The results revealed that the value of farmland quality uniformity for the administrative villages in the study area was between 7.76 and 21.96, and there was a difference between various administrative villages. The regional spatial autocorrelation patterns included High-High (HH), Low-Low (LL), High-Low (HL) and Low-High (LH). These indicate that regional cultivated land quality has local homogenization characteristics. The most restrictive factors in the study area were the medium and low transformation difficulty indexes, including soil organic matter content, farmland shelterbelt network density, field regularity and scale of the field. In addition, there were also high transformation difficulty indicators in some areas, such as sectional configuration. The project area was divided into four partitions: major construction area, secondary construction area, general construction area, and conditional construction area. The cultivated land area of each subarea was 1538.85 ha, 1224.27 ha, 555.93 ha, and 1666.63 ha, respectively. This comprised of 30.87%, 24.56%, 11.15% and 33.42% of the total project area, respectively. The evaluation model and index system could satisfy the evaluation of farmland quality and diagnosis of obstacle factors to facilitate the subsequent construction decision. The present study provides reference for the practice of regional HSBFC, and a new feasible idea and method for related studies.

Increased spatial and temporal autocorrelation of temperature under climate change

Understanding spatiotemporal variation in environmental conditions is important to determine how climate change will impact ecological communities. The spatial and temporal autocorrelation of temperature can have strong impacts on community structure and persistence by increasing the duration and the magnitude of unfavorable conditions in sink populations and disrupting spatial rescue effects by synchronizing spatially segregated populations. Although increases in spatial and temporal autocorrelation of temperature have been documented in historical data, little is known about how climate change will impact these trends. We examined daily air temperature data from 21 General Circulation Models under the business-as-usual carbon emission scenario to quantify patterns of spatial and temporal autocorrelation between 1871 and 2099. Although both spatial and temporal autocorrelation increased over time, there was significant regional variation in the temporal autocorrelation trends. Additionally, we found a consistent breakpoint in the relationship between spatial autocorrelation and time around the year 2030, indicating an acceleration in the rate of increase of the spatial autocorrelation over the second half of the 21st century. Overall, our results suggest that ecological populations might experience elevated extinction risk under climate change because increased spatial and temporal autocorrelation of temperature is expected to erode both spatial and temporal refugia.

Spatiotemporal distribution and predictors of tuberculosis incidence in Morocco

BackgroundTuberculosis (TB) is a major health problem in Morocco. This study aims at examining trends in TB in Morocco and identifying TB spatial clusters and TB-associated predictors.MethodCountry-level surveillance data was exploited. Kendall’s correlation test was used to examine trends and an exploratory spatial data analysis was conducted to assess the global and local patterns of spatial autocorrelation in TB rates (Moran’s I and local indicator of spatial association [LISA]) at the prefecture/province level. Covariates including living in a prefecture versus living in a province, annual rainfall, annual mean temperature, population density, and AIDS incidence were controlled. An ordinary least squares regression was thus performed and both spatial dependence and heteroscedasticity were assessed.ResultsA decrease in TB incidence rate was seen between 1995 and 2014 (Kendall’s tau b = − 0.72; P < 0.0001). However, while the period between 2005 and 2014 (10 last years) was considered, TB rate remained stable and as high as 84 per 100 000 population per year (95% CI: 83.7–84.3). The highest incidence rates were seen in Tanger-Assilah, Fez, Tetouen-M’diq Fnidaq, Inezgane Ait Melleoul, and Casablanca. From 2005 to 2014, while TB incidence rate was stable in Fez (P = 0.500), Tetouen-M’diq Fnidaq (P = 0.300), Casablanca (P = 0.500), Mohammadia (P = 0.146), Al Hoceima (P = 0.364), and Guelmim (P = 0.242), an increase in TB incidence rate was seen in Tanger-Assilah (Kendall’s tau = 0.49; P = 0.023) and a decrease in Salé (Kendall’s tau b = − 0,54; P = 0.014) and Inezgane-Ait Melloul (Kendall’s tau b = − 0,67; P = 0.0023). TB is strongly clustered in space (P-values of Moran’s I < 0.01). Two distinct spatial regimes that affect TB spatial clustering were identified (east and west). In the east, both annual rainfall (P = 0.003) and AIDS (P = 0.0002) exert a statistically significant effect on TB rate. In the west, only the living area (prefecture versus province) was associated with TB rate (P = 0.048).ConclusionsNew information on TB incidence and TB-related predictors was provided to decision-making and to further pertinent research. Association between annual rainfall and TB may be of interest to be explored elsewhere.

ANALYSIS OF SPATIAL AUTOCORRELATION OF GRAIN PRODUCTION AND AGRICULTURAL STORAGE IN PARANÁ

ABSTRACT This work aimed to study the spatial autocorrelation of the total static capacity storage, the total number of warehouses in 2013/2014 (CONAB) and the average of the total grain production (soybean, corn 1st and 2nd crops and wheat) in the harvest years 2008/2009 to 2013/2014 (SEAB) in Parana State, Brazil. The study was based on Moran's global autocorrelation index, Moran's local and Moran's bivariate correlation. It was possible to identify regions with low and high total grain production. There was positive spatial autocorrelation for the Total Static Storage Capacity (TSSC) and Total Quantity of Warehouses (TQW). For the total grain production, significant spatial autocorrelation were found. The total static storage capacity showed similarity between the studied regions. When evaluating the bivariate spatial correlation between Total Production of Harvested Grains (TPHG) in relation to the total static storage capacity and total quantity of warehouses, the presence of positive spatial correlation was observed. The results indicated that Moran's global autocorrelation and local indexes showed significant patterns of spatial autocorrelation, as well as the bivariate spatial correlation indexes in the studied variables.

Spatial Analysis of Hospital Incidence and in Hospital Mortality of Abdominal Aortic Aneurysms in Germany: Secondary Data Analysis of Nationwide Hospital Episode (DRG) Data

This study aimed to analyze the spatial distribution and regional variation of the hospital incidence and in hospital mortality of abdominal aortic aneurysms (AAA) in Germany. German DRG statistics (2011-2014) were analysed. Patients with ruptured AAA (rAAA, I71.3, treated or not) and patients with non-ruptured AAA (nrAAA, I71.4, treated by open or endovascular aneurysm repair) were included. Age, sex, and risk standardisation was done using standard statistical procedures. Regional variation was quantified using systematic component of variation. To analyse spatial auto-correlation and spatial pattern, global Moran's I and Getis-Ord Gi* were calculated. A total of 50,702 cases were included. Raw hospital incidence of AAA was 15.7 per 100,000 inhabitants (nrAAA 13.1; all rAAA 2.7; treated rAAA 1.6). The standardised hospital incidence of AAA ranged from 6.3 to 30.3 per 100,000. Systematic component of variation proportion was 96% in nrAAA and 55% in treated rAAA. Incidence rates of all AAA were significantly clustered with above average values in the northwestern parts of Germany and below average values in the south and eastern regions. Standardised mortality of nrAAA ranged from 1.7% to 4.3%, with that of treated rAAA ranging from 28% to 52%. Regional variation and spatial distribution of standardised mortality was not different from random. There was significant regional variation and clustering of the hospital incidence of AAA in Germany, with higher rates in the northwest and lower rates in the southeast. There was no significant variation in standardised (age/sex/risk) mortality between counties.

Analysis of spatial autocorrelation patterns of heavy and super-heavy rainfall in Iran

Rainfall is a highly variable climatic element, and rainfall-related changes occur in spatial and temporal dimensions within a regional climate. The purpose of this study is to investigate the spatial autocorrelation changes of Iran’s heavy and super-heavy rainfall over the past 40 years. For this purpose, the daily rainfall data of 664 meteorological stations between 1971 and 2011 are used. To analyze the changes in rainfall within a decade, geostatistical techniques like spatial autocorrelation analysis of hot spots, based on the Getis-Ord G i statistic, are employed. Furthermore, programming features in MATLAB, Surfer, and GIS are used. The results indicate that the Caspian coast, the northwest and west of the western foothills of the Zagros Mountains of Iran, the inner regions of Iran, and southern parts of Southeast and Northeast Iran, have the highest likelihood of heavy and super-heavy rainfall. The spatial pattern of heavy rainfall shows that, despite its oscillation in different periods, the maximum positive spatial autocorrelation pattern of heavy rainfall includes areas of the west, northwest and west coast of the Caspian Sea. On the other hand, a negative spatial autocorrelation pattern of heavy rainfall is observed in central Iran and parts of the east, particularly in Zabul. Finally, it is found that patterns of super-heavy rainfall are similar to those of heavy rainfall.

Urbanization patterns in Iran visualized through spatial auto-correlation analysis

In recent decades urbanization in the world and Iran has changed and evolved based on a variety of patterns. Many factors influence these patterns, including climate conditions, national policies, international developments, and the economic situation. The aim of this study was to investigate changes in spatial autocorrelation pattern of urbanization in Iran. Hence, data has been extracted from the Statistical Center of Iran. At first, patterns of urbanization were calculated and then global Moran index has been used in the analysis of spatial pattern changes. The results showed that central and northern regions of the country, particularly Isfahan and Tehran, in all courses have a positive spatial autocorrelation pattern and its intensity has increased in recent times. This is while the south-eastern half of the country, due to climatic determinism, has a negative spatial autocorrelation pattern.

Decadal Spatial-Temporal Variations in the Spatial Pattern of Anomalies of Extreme Precipitation Thresholds (Case Study: Northwest Iran)

This study focused on decadalvariations of extreme precipitation thresholds within a 50-year period (1961–2010) for 250 stations of Iran’s northwest. The 99th percentile was used as the threshold of extreme precipitation. In order to analyze threshold cycles and spatial autocorrelation pattern dominating extreme precipitation thresholds, spectral analysis and Gi (known as HOTSPOT) were used respectively. The results revealed that the highest threshold of extreme precipitation occurred along the Ghoosheh Dagh mountain range. Additionally, in all the five studied decades, the highest positive anomalies were observed in the same region (i.e., the Ghoosheh Dagh). The findings also showed that the intensity of positive spatial autocorrelation pattern of extreme precipitation thresholds experienced a declining trend in recent decades. At the same time, extreme precipitation weighted mean center indicated that they followed an ordered pattern during the studied period. The results of harmonic analysis demonstrated that, in all decades, short-term (2–4 years) and mid-term (4–8 years) cycles of extreme precipitation thresholds were dominated. However, especially the southwest of the studied area, the return period of extreme precipitation thresholds was as long as the studied period, a phenomenon that indicates the existence of a trend in extreme precipitation thresholds of these regions.

Application of modified Spatial K’luster Analysis by Tree Edge Removal Method (SKATER) on the level of Crime data in Way Kanan district, Lampung

Modification of method Spatial K'luster Analysis by Tree Edge Removal (SKATER) is one of the regionalization method for clustering based on the location by spatial autocorrelation and spatial patterns. This method uses graph theory approach to identify the homogeneous location is the minimum spanning tree. In addition to clustering objects based on similarity characteristics, in everyday life, often found that there are significant spatial clustering that affect specific object. This study was conducted to determine the relationship of the crime rate between districts in Way Kanan, Lampung. Based on these results, the characteristics of the crime rate in terms of spoliation, robbery and gambling have spatial autocorrelation and spatial patterns. Further applied modifications of SKATER. Generate 4 cluster (k) graded of the 14 districts. on average k1 (17.67% ) k2 (10.09%) k3 (7.80%) k4 (4.28%).

Small‐scale and regional spatial dynamics of an annual plant with contrasting sexual systems

Summary Plant demography is known to depend on both spatial dynamics and life history, but how these two factors interact is poorly understood. We conducted a longitudinal study of the wind‐pollinated annual plant Mercurialis annua that varies geographically in its sexual system to investigate this interaction. Metapopulation demographic models predict that regular population turnover should be a more common feature of monomorphic than dimorphic populations because males and females cannot found new populations by selfing but hermaphrodites can. We tested the prediction that rates of population turnover would be higher in monomorphic compared to dimorphic regions. We surveyed 356 populations of M. annua along five regional transects in Morocco and the Iberian Peninsula over a 3‐year period to examine their demography and persistence. Each transect crossed a transition in the sexual system, from a monomorphic region where almost all populations were hermaphroditic to a dimorphic one in which most populations had separate sexes (males with females or hermaphrodites). As predicted, rates of local apparent extinctions (i.e., the disappearance of adult plants) were nearly 50% higher in monomorphic compared to dimorphic regions. Local extinctions appeared to be driven by changes in vegetation cover, with extinctions tending to occur in sites in which perennial cover also declined. This suggests that disturbance is a primary agent of local extinctions. We further examined the influence of regional dynamics on local demographic properties by investigating patterns of spatial autocorrelation in population density across years. We found positive spatial autocorrelations in plant densities within regions for both sexual systems. However, these positive autocorrelations extended over shorter distances in monomorphic regions, perhaps as a result of greater population flux in these regions. Synthesis. Our study shows that population dynamics may be influenced by processes acting at a range of spatial scales: within patches, across patches within sites, and across sites within regions, as well as by life‐history variation. In Mercurialis annua, regional variation in apparent extinction rates is affected by life history and implicated in regulating the geographical distribution of populations with different sexual systems.

吉林蛟河针阔混交林树木生长的空间关联格局

PDF HTML阅读 XML下载 导出引用 引用提醒 吉林蛟河针阔混交林树木生长的空间关联格局 DOI: 10.5846/stxb201510272172 作者: 作者单位: 北京林业大学森林资源与生态系统过程北京市重点实验室,吉林省林业科学研究院,吉林省林业科学研究院,北京林业大学森林资源与生态系统过程北京市重点实验室,北京林业大学森林资源与生态系统过程北京市重点实验室 作者简介: 通讯作者: 中图分类号: 基金项目: 国家林业公益性行业科研专项项目（201204309）；教育部新世纪优秀人才支持计划项目（NCET-12-0781）；国家自然科学基金项目（31200315） Spatial autocorrelation patterns of tree growth in a coniferous and broad-leaved mixed forest in Jiaohe of Jilin province Author: Affiliation: The Key Laboratory for Forest Resources & Ecosystem Processes of Beijing, Beijing Forestry University,,,The Key Laboratory for Forest Resources DdDd Ecosystem Processes of Beijing, Beijing Forestry University, Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:以吉林蛟河21.12hm2（660m×320m）针阔混交林样地为对象，利用2009年和2014年森林生长观测数据，研究树木生长的空间自相关格局及其生境影响机制。在样地生境型划分结果的基础上，采用Ripley's L（r）函数分析不同生境型中树木种群空间分布特征；利用标记相关函数分析不同生境型中树木生长特征的空间关联格局。研究结果表明：（1）红松（生境型3：1-5m）、蒙古栎（生境型3：1-3m）、胡桃楸（生境型2：1-2m；生境型3：1-7m）、黄檗（生境型2：1-3m；生境型4：1-5m）、水曲柳（生境型3：1-2m；生境型4：1-2m）、瘤枝卫矛（生境型2：1-15m）在特定生境和空间尺度上呈随机分布，但空间格局仍以聚集性分布为主；其余10个物种则在全部0-30m尺度上呈聚集分布。（2）标记相关函数分析显示春榆、毛榛、色木槭、瘤枝卫矛和千金榆的径向生长至少在一个生境中表现出正相关格局；暴马丁香、胡桃楸、裂叶榆、瘤枝卫矛、水曲柳、紫椴、糠椴、毛榛、色木槭和白牛槭的径向生长至少在一个生境中表现出负相关格局；红松、黄檗、蒙古栎和簇毛槭的径向生长在全部尺度上均未检测到显著的空间关联格局。因此，不同树种径向生长的空间自相关特征不同，树种生长特征的空间关联格局具有明显的生境依赖性。 Abstract:This study aimed to determine the spatial autocorrelation patterns of tree growth and the mechanisms influencing habitat heterogeneity. A dataset of observed forest growth was used, with data between 2009 and 2014 from a 21.12 hm2 stem-mapped mixed forest plot (temperate coniferous and broadleaved forest) in Jiaohe, Jilin Province. Based on habitat type classifications, Ripley's L(r) function was adopted to evaluate the spatial distribution characteristics of tree locations. A mark correlation function (MCF) was used to evaluate the spatial autocorrelation characteristics of tree growth. Our results showed that (1) Pinus koraiensis (habitat type 3: 1-5 m), Quercus mongolica (habitat type 3: 1-3 m), Juglans mandshurica (habitat type 2: 1-2 m; habitat type 3: 1-7 m), Phellodendron amurense (habitat type 2: 1-3 m; habitat type 4: 1-5 m), Fraxinus mandshurica (habitat type 3: 1-2 m; habitat type 4: 1-2 m), and Euonymus verrucosus (habitat type 2: 1-15 m) were randomly distributed at particular scales and for certain habitat types. Nonetheless, they mainly showed clumped distribution patterns. For ten other species, the spatial distribution of tree positions showed an aggregated pattern at a scale of 0-30 m. (2) The mark correlation function analysis indicated that the radial growth of Ulmus davidiana var. japonica, Corylus mandshurica, Acer mono, E. verrucosus, and Carpinus cordata were positively autocorrelated for at least one of the habitat types. In contrast, the radial growth of Syringa reticulata var. amurensis, J. mandshurica, Ulmus laciniata, E. verrucosus, F. mandshurica, Tilia amurensis, Tilia mandshurica, C. mandshurica, A. mono, and Acer mandshuricum were negatively autocorrelated at least in one of habitat types. Other species did not show any significant autocorrelations at any of the studied scales. Our results indicate that different species had different spatial autocorrelation characteristics of radial growth, as well as significantly different habitat dependencies. 参考文献 相似文献 引证文献

Patterns of spatial autocorrelation in the distribution and diversity of carabid beetles and spiders along Alpine glacier forelands

Spatial autocorrelation is a common feature of ecological data and can be found in the distribution pattern of many species or in the diversity of many species assemblages. The presence of spatial autocorrelation in species distribution along primary successions on recently deglaciated terrains has been largely overlooked until now, despite its potential consequences for comparisons between glacier forelands. Here, we investigated the occurrence of spatial autocorrelation at different spatial scales in the distribution and diversity of ground beetles and spiders along glacier forelands. We found positive spatial autocorrelation in patterns of occurrence of most species and in patterns of species assemblages diversity at spatial scales representing single (< 3 km) or adjacent valleys (< 7 km), whereas at a larger spatial scales (0–30 km) such positive spatial autocorrelation disappeared. We concluded that spatial autocorrelation could be a key issue for studies investigating distribution of arthropods, including in glacier forelands, in order to perform more robust analysis and to avoid misinterpretation of species distribution in relation to the glacier retreat and other environmental characteristics.

Spatial-temporal pattern differentiation and influencing mechanism of land reclamation in China

A large quantity of land resources have been damaged due to intense human activities and natural disasters, such as mining operation, infrastructure construction, and landslide. The expectation to restore the function of the degraded land is increasingly drawing much attention from both publics and governments. After decades' efforts, there is still a heavy task of land reclamation that needs to be finished in China. Due to the strong regional differentiation, the situation of land reclamation in each province is different from others. In order to reduce the regional differences with a purpose of promoting the land reclamation in China, it is essential to explore the spatial-temporal pattern differentiation and influence mechanism of land reclamation. This paper took 31 provinces, municipalities and autonomous districts in China as research area to reveal the spatial pattern of the quantity of land reclamation and its influence factors. The considered factors included the economic, social, technical, institutional and natural conditions. Data were collected from related statistical yearbook, published paper and China national knowledge internet (CNKI). We employed exploratory spatial data analysis to detect the spatial pattern of land reclamation in China. Besides, factor analysis was used to discover the public driving force of land reclamation. Panel data model was used to quantify the influence of different factors on the quantity of land reclamation in different regions. It could be found that: 1) The quantity of land reclamation in China was featured by a weak spatial autocorrelation and three-grade distribution pattern, and it showed a spatial nonstationary process with inter-annual instability from 1999 to 2013. This pattern was partly in accordance with the economic development and affected by some factors such as the distribution of mineral resource and differentiated land reclamation policies; 2) Due to the weak spatial aggregation, only one area with H-H (high-high) clustered reclamation was detected in eastern China (the center was Jiangsu Province), and not any other significant hot area was been found; 3) The 3 public factors mainly affecting land reclamation were mission, drive and support respectively. It can be inferred that the most significant motive force of land reclamation in China is economic driving force, and the second force is mission of land reclamation. This indicates that, to some degree, the insufficient quantity of land reclamation cannot only attribute to the technical problem. Obviously, it is a synthesis problem related to other factors, especially the economy. For eastern China, land reclamation is mainly driven by the pressure of land resource shortage and economic attraction. Central China is also suffering from the pressure of land resource shortage, but its land reclamation is negatively affected by the ongoing mining activity. In western China, there is more mission of land reclamation, but the natural condition acts as a significant limiting factor. Based on the results above, some policy suggestions, such as improving the mission-driving mechanism, reforming the guidance of policy, enhancing the transfer of technology and coordinating land reclamation project, have been proposed. The results and conclusions above are expected to provide reference for the planning and management of land reclamation.