Negative Spatial Autocorrelation Research Articles

Spatial analysis of reported new cases and local risk of leprosy in hyper-endemic situation in Northeastern Brazil.

To analyse the spatial distribution of the incidence of leprosy and identify areas at risk for occurrences of hyper-endemic disease in Northeastern Brazil. Ecological study using municipalities as the analysis unit. Data on new cases of leprosy came from the Health Hazard Notification System (SINAN). This study focused on Pernambuco and covered the years 2005 to 2014. Indicators for monitoring were calculated per 100 000 inhabitants. The local empirical Bayes method was used to minimise rate variance, and spatial autocorrelation maps were used for spatial pattern analysis (box maps and Moran maps). A total of 28 895 new cases were registered in the study period. The average incidence was 21.88/100 000; the global Moran's I index was 0.36 (P < 0.01), thus indicating the existence of spatial dependence; and the Moran map identified 20 municipalities with high priority for attention. The average incidence rate among individuals under 15 years of age was 8.78/100 000; the global Moran's I index showed the presence of positive spatial autocorrelation (0.43; P < 0.01), and the Moran map showed a main cluster of 15 hyper-endemic municipalities. The average rate of grade 2 physical disability at the time of diagnosis was 1.12/100 000; the global Moran index presented a positive spatial association (0.17; P < 0.01); and the Moran map located clusters of municipalities (high-high) in three mesoregions. Application of different spatial analysis methods made it possible to locate areas that would not have been identified by epidemiological indicators alone.

Lateral heterogeneity of soil physicochemical properties in riparian zones after agricultural abandonment

The study aimed to identify the lateral heterogeneity of soil physicochemical properties in riparian zones, and its underlying drivers during natural restoration after agricultural abandonment. Abandoned farmlands, after 5-year natural restoration, within 500 m from the edges on both sides of Liaohe River were selected as the study area. Soil physicochemical properties of four lateral buffers (<10 m, 10~100 m, 100~300 m, and >300 m from river edge, respectively) along riparian zones were measured. The results showed that riparian soils were characterized by high sand content (78.88%~96.52%) and poor soil nutrients. Soil silt content, organic carbon (OC), cation exchange capacity (CEC), total nitrogen (TN), and available nitrogen (AN) increased laterally with increasing distance from river edge, while soil sand content decreased. Total phosphorus (TP) and available phosphorus (AP) are not spatially autocorrelated. Soil OC, TN, AN, and CEC along upstream and midstream reaches showed negative spatial autocorrelation along the lateral gradients, and positive along downstream reach. Altitude, distance from river edge and distance from nearest farmland were the pronounced factors affecting soil physicochemical properties in this study.

Some robustness assessments of Moran eigenvector spatial filtering

Moran eigenvector spatial filtering (MESF) is a novel methodology in the spatially varying coefficients tradition promoted in spatial statistics, quantitative geography, and statistical ecology that deals with spatial autocorrelation in georeferenced data. Its Moran Coefficient based estimators exhibit statistical properties of unbiasedness, efficiency, and consistency. Evidence is accumulating that it also exhibits robustness, or good performance with georeferenced data drawn from not only normal, but also at least Poisson and binomial, probability distributions. This paper further explores this performance. In doing so, it addresses the sensitivity of MESF results to changing: (1) the employed spatial weights matrix specification for constructing MESF synthetic variates, in space, space–time, and spatial flows network structures; (2) the design of Monte Carlo simulation experiments; (3) cross-validation type imputation estimators; (4) the nature of embedded geographical dependence to include negative spatial autocorrelation (SA) components; and, (5) the SA index (e.g., the Geary Ratio) basis of eigenvector spatial filter (ESF) estimators. Empirical illustrations involve 2010 county resolution population density across the state of Texas.

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.

Declines revisited: Long-term recovery and spatial population dynamics of tailed frog larvae after wildfire

Drought has fueled an increased frequency and severity of large wildfires in many ecosystems. Despite an increase in research on wildfire effects on vertebrates, the vast majority of it has focused on short-term (<5years) effects and there is still little information on the time scale of population recovery for species that decline in abundance after fire. In 2003, a large wildfire in Montana (USA) burned the watersheds of four of eight streams that we sampled for larval Rocky Mountain tailed frogs (Ascaphus montanus) in 2001. Surveys during 2004–2005 revealed reduced abundance of larvae in burned streams relative to unburned streams, with greater declines associated with increased fire extent. Rocky Mountain tailed frogs have low vagility and have several unusual life-history traits that could slow population recovery, including an extended larval period (4years), delayed sexual maturity (6–8years), and low fecundity (<50eggs/year). To determine if abundance remained depressed since the 2003 wildfire, we repeated surveys during 2014–2015 and found relative abundance of larvae in burned and unburned streams had nearly converged to pre-fire conditions within two generations. The negative effects of burn extent on larval abundance weakened >58% within 12years after the fire. We also found moderate synchrony among populations in unburned streams and negative spatial autocorrelation among populations in burned streams. We suspect negative spatial autocorrelation among spatially-clustered burned streams reflected increased post-fire patchiness in resources and different rates of local recovery. Our results add to a growing body of work that suggests populations in intact ecosystems tend to be resilient to habitat changes caused by wildfire. Our results also provide important insights into recovery times of populations that have been negatively affected by severe wildfire.

Prevalence of Inter-Tree Competition and Its Role in Shaping the Community Structure of a Natural Mongolian Scots Pine (Pinus sylvestris var. mongolica) Forest

Inter-tree competition is considered one of the most important ecological processes of forest development. However, its importance in structuring the spatial patterns of plant communities remains controversial. We collected observational data from two plots in a natural Mongolian Scots pine forest to study the contribution of competition to tree growth, mortality, and size inequality. We used the nearest neighbour method to determine the presence of competition, and unmarked and marked spatial point pattern analyses to test the density-dependent mortality effects and the spatial autocorrelation of tree size. We identified significant positive correlations between tree canopy diameter and nearest neighbour distance in both plots, which were more evident in the denser plot. The pair correlation functions of both plots indicated regular distribution patterns of living trees, and trees living in more crowded environments were more likely to die. However, the mark differentiation characteristics showed weak evidence of a negative spatial autocorrelation in tree size, particularly in the high-density plot. The high mortality rate of suppressed trees and weak asymmetric competition may have accounted for the lack of dissimilarity in tree size. This study showed that inter-tree competition is an important determinant of the development of Mongolian Scots pine forests.

Disturbance increases negative spatial autocorrelation in species diversity

Context Ecological processes that shape diversity and spatial pattern of ecological communities are often altered by disturbance. Spatial patterns (spatial autocorrelation) in species diversity are thus expected to change with disturbance.

A Novel Efficiency Measure Model for Industrial Land Use Based on Subvector Data Envelope Analysis and Spatial Analysis Method

With the rapid and unbalanced development of industry, a large amount of cultivated land is converted into industrial land with lower efficiency. The existing research is extensively concerned with industrial land use and industrial development in isolation, but little attention has been paid to the relationship between them. To help address this gap, the paper creates a new efficiency measure method for industrial land use combining Subvector Data Envelope Analysis (DEA) with spatial analysis approach. The proposed model has been verified by using the industrial land use data of 30 Chinese provinces from 2001 to 2013. The spatial autocorrelation relationship between industrial development and industrial land use efficiency is explored. Furthermore, this paper examines the effects of industrial development on industrial land use efficiency by spatial panel data model. The results indicate that the industrial land use efficiency and the industrial development level in the provinces of eastern region are higher than those of the western region. The spatial distribution of industrial land use efficiency shows remarkable positive spatial autocorrelation. However, the level of industrial development has obvious negative spatial autocorrelation since 2009. The improvement of industrial development has a significant positive impact on the industrial land use efficiency.

Urban ponds as an aquatic biodiversity resource in modified landscapes.

Urbanization is a global process contributing to the loss and fragmentation of natural habitats. Many studies have focused on the biological response of terrestrial taxa and habitats to urbanization. However, little is known regarding the consequences of urbanization on freshwater habitats, especially small lentic systems. In this study, we examined aquatic macro-invertebrate diversity (family and species level) and variation in community composition between 240 urban and 782 nonurban ponds distributed across the United Kingdom. Contrary to predictions, urban ponds supported similar numbers of invertebrate species and families compared to nonurban ponds. Similar gamma diversity was found between the two groups at both family and species taxonomic levels. The biological communities of urban ponds were markedly different to those of nonurban ponds, and the variability in urban pond community composition was greater than that in nonurban ponds, contrary to previous work showing homogenization of communities in urban areas. Positive spatial autocorrelation was recorded for urban and nonurban ponds at 0-50km (distance between pond study sites) and negative spatial autocorrelation was observed at 100-150km and was stronger in urban ponds in both cases. Ponds do not follow the same ecological patterns as terrestrial and lotic habitats (reduced taxonomic richness) in urban environments; in contrast, they support high taxonomic richness and contribute significantly to regional faunal diversity. Individual cities are complex structural mosaics which evolve over long periods of time and are managed in diverse ways. This facilitates the development of a wide range of environmental conditions and habitat niches in urban ponds which can promote greater heterogeneity between pond communities at larger scales. Ponds provide an opportunity for managers and environmental regulators to conserve and enhance freshwater biodiversity in urbanized landscapes whilst also facilitating key ecosystem services including storm water storage and water treatment.

Identifying the spatial and temporal distribution characteristics of precipitation in Iran

Precipitation has been regarded as one of the most important meteorological parameters affecting human activities. The findings of research studies confirm that the variability and fluctuation in precipitation has direct impacts on climate of a given region. The purpose of the present study was to investigate long-term patterns in precipitation variation in Iran. To this end, the available data related to rainfall in Iran over the past half century (1957–2007) were retrieved from APHRODITE database in order to analyze the spatial-temporal variations of precipitation. The statistical test performed on the collected data included spatial auto-correlation, global Moran’s index, local Moran’s index, and hotspots. The results obtained showed that the precipitation variation in Iran followed a high clustering pattern. More specifically, the results of the local Moran’s index and hotspot analysis performed on the data revealed that the precipitation along the Caspian Sea coast and western and southwestern parts of the country had a positive spatial auto-correlation while the precipitation variation in some parts of the central Iran and along the coastline of the country showed a negative spatial auto-correlation. Moreover, the findings of the present study showed that the climate change continued during the decades under study, with clustering patterns of precipitation moving from the southern parts of the country upward towards the coastal regions of the Caspian Sea and the regions in the outskirt of Zagros Mountains.

Human leptospirosis distribution pattern analysis in Hulu Langat, Selangor

This paper discussed the distribution pattern of human leptospirosis in the Hulu Langat District, Selangor, Malaysia. The data used in this study is leptospirosis cases’ report, and spatial boundaries. Leptospirosis cases, data were collected from Health Office of Hulu Langat and spatial boundaries, including lot and district boundaries was collected from the Department of Mapping and Surveying Malaysia (JUPEM). A total of 599 leptospirosis cases were reported in 2013, and this data was mapped based on the addresses provided in the leptospirosis cases’ report. This study uses three statistical methods to analyze the distribution pattern; Moran's I, average nearest neighborhood (ANN) and kernel density estimation. The analysis was used to determine the spatial distribution and the average distance of leptospirosis cases and located the hotspot locations. Using Moran's I analysis, results indicated the cases were random, with a value of -0.202816 which show negative spatial autocorrelation exist among leptospirosis cases. The ANN analysis result, indicated the cases are in cluster pattern, with value of the average nearest neighbor ratio is -21.80. And results also show the hotspots are has been identified and mapped in the Hulu Langat District.

Analysis of spatial pattern of aerosol optical depth and affecting factors using spatial autocorrelation and spatial autoregressive model

Previous studies neglected the implicit information in the spatial pattern of the aerosol optical depth (AOD), such as spatial configuration characteristics, spatial heterogeneity and spatial dependence. The understanding of AOD is helpful in accurately estimating the environmental and climatic effects from aerosols. In this study, a method of spatial autocorrelation statistics from geostatistics was applied to investigate the spatial pattern of AOD in Hubei province in central China during the period 2003–2008. Spatial autoregressive models were used to quantize the correlations between AOD and affecting factors, such as elevation, forest coverage and population density. In addition, the difference between the standard linear regression model and the spatial models was discussed. The results were as follows: the spatial pattern of AOD in Hubei province shows significant spatial autocorrelation, indicating that AODs are clustered such that higher AODs tend to be surrounded by higher AOD neighbors, while lower AODs are surrounded by lower AOD neighbors, and the spatial autocorrelation scale of the AOD over Hubei is approximately 400 km. The high–high zone is mainly distributed in the Wuhan city circle and the Jianghan plain areas, while the low–low zones are mainly located in the middle and high mountain areas of northwest Hubei province. The overall degree and pattern of spatial autocorrelation do not change largely from 2003 to 2008, which indicates a stable spatial configuration of AOD. A significant negative spatial autocorrelation exists between AOD and elevation, which may suggest that AOD and elevation have an inverse spatial distribution, and the same applies for forest coverage. Population density and the AOD show a significant positive spatial autocorrelation, which may imply that they have similar spatial distribution, while industrial production and AOD do not show an obvious positive spatial autocorrelation. Spatial autoregressive models show better predictive ability and stability than the standard linear regression model because the spatial autocorrelation of the AOD is taken into consideration.

An integrated approach for spatial analysis of the coupling relationship between tourism footprint and environment in the Beijing–Tianjin–Hebei region of China

ABSTRACTThis study aims at examining the spatial relationship between tourism footprint network and comprehensive environment which contains economic, social and ecological environment. The integrated approach combining network analysis and the coupling coordination degree model with spatial autocorrelation analysis was developed to analyze the network structure of regional tourism footprint, to evaluate the coupling coordination degree of tourism footprint network and comprehensive environment, and to explore the spatial pattern of the coupling coordination development. Data were collected from the Beijing–Tianjin–Hebei region of China. The results revealed that tourism footprints were concentrated in a few cities, and the regional coupling coordination degree showed a weak negative spatial autocorrelation. Beijing, Tianjin and Baoding had high agglomeration, while their spillover effect is not significant. Shijiazhuang and Qinhuangdao located in the High–Low area are potential growth poles. Findings indicate the integrated approach established is objective and effective, and contributes to macro policy-making of regional tourism development.

Spatial lag dependence in the presence of missing observations

We explore the estimation effectiveness of spatial lag models in the presence of missing observations. Spatial lag models are used to measure interdependency between dependent variables. If there are no missing data, it is easy to interpret this spatial autocorrelation process. Very sparsely sampled data are sometimes used in empirical studies. For such data, we observe only a small part of a population containing possible mutual dependencies. Simulation studies based on artificial data confirm the relation between the sampling rate and selection ratio of spatial and non-spatial models. Our findings include the following: (1) Negative spatial autocorrelation of the data-generating process (DGP) may not be observed. (2) Positive spatial autocorrelation of the DGP may be observed, but it is downward-biased. (3) We obtain less-biased estimates if we use a non-row-standardized weight matrix. (4) Non-spatial models tend to be selected in preference to the correct model, the spatial lag model. (5) Estimates of regression coefficients remain almost unbiased.

A new permutation technique to explore and control for spatial autocorrelation

Summary Permutation tests are important in ecology and evolution as they enable robust analysis of small sample sizes and control for various forms of dependencies among observations. A common source of dependence is spatial autocorrelation. Accounting for spatial autocorrelation is often crucial, because many ecological and evolutionary processes are spatially restricted, such as gene flow, dispersal, mate choice, inter‐ and intraspecific competition, mutualism and predation. Here we discuss various ways of controlling for spatial autocorrelation in permutation tests; we highlight their particular properties and assumptions and introduce a new permutation technique which explores and controls for spatial autocorrelation: the floating grid permutation technique (FGPT). The FGPT is a method to randomize observations with known geographical locations. Within the randomization process, the probability an observation is assigned to any of the spatial locations is a negative function of the distance between its original and assigned location. The slope of this function depends on a preset parameter, and by exploring its parameter space, non‐random ecological and evolutionary processes can be both assessed and controlled at multiple spatial scales. We show that the FGPT has acceptable type‐I‐error rates. We applied the FGPT to simulated univariate and bivariate data sets in which both negative and positive spatial autocorrelation were present. In comparison with a method that uses eigenvector decomposition to separate negative from positive spatial autocorrelation, the FGPT performed better for negative spatial autocorrelation alone, equal for positive spatial autocorrelation alone and equal or slightly worse for simultaneous negative and positive spatial autocorrelation. For the bivariate data, it performed equally to a bootstrapping technique in which sampling probabilities were weighted by distance. The FGPT benefits from a large flexibility for application to bivariate (e.g. dyadic interactions) and multivariate observations (e.g. genetic marker‐based relatedness measures) and has a large freedom in the choice of test statistic. It also has the potential to identify two spatial autocorrelation patterns, even if both result in positive spatial autocorrelation, given that they operate at different spatial scales. The Floating Grid Permutation Technique is available as the R‐package fgpt in CRAN.

Avian metapopulation dynamics in a fragmented urbanizing landscape

As urbanization transforms landscapes around the globe, we are challenged to find ways for urban habitats to contribute to ongoing wildlife conservation efforts. Yet aside from basic distributions and relative abundance, we know little about the population dynamics of most species occupying urban habitats and almost nothing about the extent to which local populations serve as source or sink habitats. We analyzed the spatial synchrony and persistence of local populations of 16 avian species breeding in 14 mature riparian forests in central Ohio, USA during 2005–2011. In addition, we examined demographic growth rates (λ) for 2 focal species (northern cardinal, Cardinalis cardinalis, and Acadian flycatcher, Empidonax virescens) to understand source-sink structure. Our results showed high rates of population turnover for the majority of species and negative growth rates for both focal species, indicating that most populations functioned as sinks. Local populations showed little evidence of population synchrony, as we found consistently low or negative spatial autocorrelation and relatively high rates of population turnover for both migratory and resident species. Collectively our results suggest that long-term persistence of regional populations of birds breeding in Midwestern riparian forest fragments may be facilitated by metapopulation dynamics.

Competition in Research Activity among Economic Departments: Evidence by Negative Spatial Autocorrelation

Despite the prevalence of both competitive forces and patterns of collaboration within academic communities, studies on research productivity generally treat universities as independent entities. By exploring the research productivity of all academic economists employed at 81 universities and 17 economic research institutes in Austria, Germany, and German‐speaking Switzerland, this study finds that a research unit's productivity negatively depends on that of neighboring research units weighted by inverse distances. This significant and exemplary robust negative relationship is compatible with the notion of competition for priority of discovery among individual researchers and the universities that employ them, and with the notion that the willingness to relocate decreases with distance. In addition, the empirical results support the hypotheses that collaboration and that the existence of economies of scale increase research productivity.A pesar de la existencia de tanto fuerzas de competencia como de patrones de colaboración dentro de la comunidad académica, los estudios sobre la productividad de investigación tratan por lo general a las universidades como entidades independientes. El presente estudio explora la productividad de investigación de todos los economistas académicos empleados en 81 universidades y 17 institutos de investigación económica en Austria, Alemania y Suiza germano‐parlante, y concluye que la productividad de una unidad de investigación depende negativamente de la productividad de las unidades vecinas ponderada por las distancias inversas que las separan. Esta relación negativa es robusta, significativa y emblemática, lo cual concuerda con el concepto de competencia por prioridad de descubrimiento (priority of discovery) entre investigadores individuales y entre las universidades que los emplean. Así mismo concuerda con la idea de que la voluntad de desplazarse disminuye con la distancia. Adicionalmente, los resultados empíricos de este estudio apoyan la hipótesis de que la colaboración y la presencia de economías de escala tienen un efecto positivo sobre (incrementan) la productividad de investigación.尽管对学术团体的研究主要针对竞争力和合作模式，但在研究科研生产率时，大学仍被视为独立的实体。本文通过调查奥地利、德国和瑞士德语区的81所高校和17个经济研究单位经济学家的研究产出率，研究发现一个研究单位的产出效率高低负依赖于反距离加权相邻研究单位的研究产出率。这种重要且典型稳健的负相关关系与个人研究者及其所在大学关于发现优先权的竞争观念相符，同时也与研究者的调动意愿因距离增加而减少的情况相一致。此外，经验结果也支持了合作和规模经济的存在能提高研究产出率的假设。

Do foreign subsidiaries innovate and perform better in a cluster? A spatial analysis of Japanese subsidiaries in the US

The interrelationship between clustering, innovation, and performance of Japanese subsidiaries in the US is examined in this paper. First, we apply Kulldorff's spatial scan statistic to identify process innovation clustering among Japanese subsidiaries. The scale at which clustering occurs is regional rather than local, and cluster location captures the geographical environment of home-transplants from Japan. Second, we apply spatial autoregressive models to test the relationship between cluster location and innovation among Japanese subsidiaries. The results indicate that cluster location strengthens the relationship between subsidiary innovation and firm performance. Negative spatial autocorrelation shows that clustering contributes to innovation by facilitating proximate learning between less innovative laggards, and, leading innovative Japanese subsidiaries.

Population genetic patterns among social groups of the endangered Central American spider monkey (Ateles geoffroyi) in a human-dominated landscape.

Spider monkeys (Genus: Ateles) are a widespread Neotropical primate with a highly plastic socioecological strategy. However, the Central American species, Ateles geoffroyi, was recently re-listed as endangered due to the accelerated loss of forest across the subcontinent. There is inconsistent evidence that spider monkey populations could persist when actively protected, but their long-term viability in unprotected, human-dominated landscapes is not known. We analyzed noninvasive genetic samples from 185 individuals in 14 putative social groups on the Rivas Isthmus in southwestern Nicaragua. We found evidence of weak but significant genetic structure in the mitochondrial control region and in eight nuclear microsatellite loci plus negative spatial autocorrelation in Fst and kinship. The overall pattern suggests strong localized mating and at least historical female-biased dispersal, as is expected for this species. Heterozygosity was significantly lower than expected under random mating and lower than that found in other spider monkey populations, possibly reflecting a recent decline in genetic diversity and a threat from inbreeding. We conclude that despite a long history of human disturbance on this landscape, spider monkeys were until recently successful at maintaining gene flow. We consider the recent decline to be further indication of accelerated anthropogenic disturbance, but also of an opportunity to conserve native biodiversity. Spider monkeys are one of many wildlife species in Central America that is threatened by land cover change, and an apt example of how landscape-scale conservation planning could be used to ensure long-term persistence.