Evidence Of Spatial Dependence Research Articles

The impact of agricultural credit on the cattle inventory and deforestation in Colombia: a spatial analysis

The relationship between agricultural credit and agricultural production as well as the impacts on sustainable development (i.e., poverty alleviation, reduction of inequalities, food and nutrition security, and stimulation of economic growth) have been widely documented. The objective of this study is to analyze the impact of credit on cattle production and deforestation in Colombia through spatial panel data models. For this purpose, a departmental data panel for the period 2011–2020 was built, based on available information from public entities. The results suggest that in Colombia, the relationship between access to credit and cattle production is significant and can be either negative or positive. In addition, there is evidence of spatial dependence, meaning that cattle production in one department is being affected by cattle production in a neighboring department or by all the departments that make up the national territory. Regarding deforestation, results show that, although the number of cattle present in a department does affect its annual deforestation rate due to a poor coverage of sustainably intensified cattle ranching systems, there is no relationship between deforestation and the access to credit nor any spatial correlations.

Spatial variability of soil secondary and micronutrients under smallholder maize production system in sub-humid condition of Zimbabwe

Achieving household and national food security is the core focus for policy makers in sub-Saharan Africa (SSA). However, land degradation and dearth of effective soil nutrient management strategies for spatially variable soils is significantly contributing to food insecurity in SSA. The aim of this study was to establish the spatial variability of soil secondary and micronutrients (SMN) under smallholder maize production system in sub-humid condition of Zimbabwe. Geo-referenced samples collected in all maize fields in seven of the eleven villages in ward 10 of Hurungwe district using purposive sampling were analyzed for Ca, Mg, Fe, Mn, Cu and Zn using standard methods. Pearson's correlation analysis was conducted to reveal the relationships among the nutrient status. The linear mixed model (LMM) was used to analyse spatial variation of the data with evidence for spatial dependence in the random component of the model assessed by calculating Akaike's information criterion (AIC). The results indicate that only Ca was significantly (p < 0.05) influenced by field type with larger concentrations in home fields compared to outfields. Soil texture had a significant (p < 0.05) effect on Ca, Mg and Zn with the largest values for Ca and Mg found in the sandy clay loams (with the largest clay content) compared to sand, loamy sand and sandy loam. Loamy sand had the largest Zn concentration with sandy clay loams having the least. There was evidence for spatial dependence in Ca and Mg with field type, latitude and longitude as fixed effects; hence these nutrients were mapped in the GIS environment. It can be concluded that SMN tend to be deficient in some areas and vary spatially as influenced by soil intrinsic conditions and management, even at ward level.

The socio-environmental production of malaria in three municipalities in the Carajás region, Pará, Brazil.

ABSTRACTOBJECTIVE To analyze the environmental production of malaria in the municipalities of Marabá, Parauapebas, and Canaã dos Carajás, in Pará, from 2014 to 2018.METHODS This ecological, cross-sectional study used epidemiological data in the Sistema de Informações de Vigilância Epidemiológica da Malária (Malaria Epidemiological Surveillance Information System) from the Secretaria de Saúde do Estado do Pará (State of Pará Health Department), cartographic data from the Brazilian Institute of Geography and Statistics (IBGE), and environmental data in the Projeto TerraClass (TerraClass Project) from the National Institute of Space Research (INPE). Statistical analyses used the chi-square test, while the spatial ones, the kernel and Moran’s (I) global bivariate techniques.RESULTS We analyzed a total of 437 confirmed cases of malaria in the selected area and period. The highest percentage of cases occurred among male miners and farmers, living in rural areas; Plasmodium vivax was the most frequent species; and the most used diagnosis, the thick drop/smear. We also observed a heterogeneous distribution of the disease — with evidence of spatial dependence between incidence areas and different forms of land use, and spatial autocorrelations related to the high variability of anthropic activities in the municipalities.CONCLUSION The environmental production of malaria relates mainly to cattle production and mining — anthropisms related to land use and occupation in the observed municipalities. Spatial data analysis technologies sufficed for the construction of the epidemiological scenario of the disease.

A spatio-temporal statistical model to analyze COVID-19 spread in the USA

Coronavirus pandemic has affected the whole world extensively and it is of immense importance to understand how the disease is spreading. In this work, we provide evidence of spatial dependence in the pandemic data and accordingly develop a new statistical technique that captures the spatio-temporal dependence pattern of the COVID-19 spread appropriately. The proposed model uses a separable Gaussian spatio-temporal process, in conjunction with an additive mean structure and a random error process. The model is implemented through a Bayesian framework, thereby providing a computational advantage over the classical way. We use state-level data from the United States of America in this study. We show that a quadratic trend pattern is most appropriate in this context. Interestingly, the population is found not to affect the numbers significantly, whereas the number of deaths in the previous week positively affects the spread of the disease. Residual diagnostics establish that the model is adequate enough to understand the spatio-temporal dependence pattern in the data. It is also shown to have superior predictive power than other spatial and temporal models. In fact, we show that the proposed approach can predict well for both short term (1 week) and long term (up to three months).

Spatial variability and mapping of soil fertility status in a high-potential smallholder farming area under sub-humid conditions in Zimbabwe

A study was conducted to examine spatial variability of soil properties related to fertility in maize fields across varying soil types in ward 10 of Hurungwe district, Zimbabwe; a smallholder farming area with sub-humid conditions and high yield potential. Purposively collected and geo-referenced soil samples were analyzed for texture, pH, soil organic carbon (OC), mineral N, bicarbonate P, and exchangeable K. Linear mixed model was used to analyze spatial variation of the data. The model allowed prediction of soil properties at unsampled sites by the empirical best linear unbiased predictor (EBLUP). Evidence for spatial dependence in the random component of the model was evaluated by calculating Akaike’s information criterion. Soil pH ranged from 4.0 to 6.9 and showed a strong spatial trend increasing from north to south, strong evidence for a difference between the home and outfields with homefields significantly higher and between soil textural classes with the sand clay loam fraction generally higher. Soil OC ranged from 0.2 to 2.02% and showed no spatial trend, but there was strong evidence for a difference between home and outfields, with mean soil OC in homefields significantly larger, and between soil textural classes, with soil OC largest in the sandy clay loams. Both soil pH and OC showed evidence for spatial dependence in the random effect, providing a basis for spatial prediction by the EBLUP, which was presented as a map. There were significant spatial trends in mineral N, available P and exchangeable K, all increasing from north to south; significant differences between homefields and outfields (larger concentrations in homefields), and differences between the soil textural classes with larger concentrations in the sandy clay loams. However, there was no evidence for spatial dependence in the random component, so no attempt was made to map these variables. These results show how management (home fields vs outfields), basic soil properties (texture) and other factors emerging as spatial trends influence key soil properties that determine soil fertility in these conditions. This implies that the best management practices may vary spatially, and that site-specific management is a desirable goal in conditions such as those which apply in Ward 10 of Hurungwe district in Zimbabwe.

Environmental Drivers of Forage Fishes and Benthic Invertebrates at Multiple Spatial Scales in a Large Temperate Estuary

Vertebrate and invertebrate taxa that serve as forage for predators play a critical role in coastal ecosystems by linking lower trophic levels to ecologically and economically valuable predators in upper trophic levels. We analyzed long-term data from multiple monitoring surveys in Chesapeake Bay and its major tributaries to evaluate patterns and relative abundances of forage at two spatial scales and to identify drivers of forage availability. Time series of forage abundances showed positive spatial correlation, becoming increasingly similar with declining distance between tributaries and regions of Chesapeake Bay. Statistical models were fit to identify relationships among forage taxa and climatic, biological, and environmental variables. Annual abundance indices of many forage taxa were higher in years when spring water temperatures warmed slowly, as indicated by an annual 5 °C degree-day warming index that represented the rate of warming during late winter/early spring. Forage indices also were related (in taxon-specific ways) to winter–spring chlorophyll concentration and freshwater discharge, and to three summer water quality variables: dissolved oxygen, salinity, and water temperature, in addition to a broad-scale climate indicator (Atlantic Multidecadal Oscillation). Our findings broadly demonstrate that bottom–up climate forcing acts to control at least some taxa at lower trophic levels in Chesapeake Bay. Ongoing phenological changes in regional climate and evidence of spatial dependence in responses of forage to environmental conditions underscore the likelihood that spatiotemporal foraging conditions for predator species will change under projected climate conditions.

Social capital and regional development in Turkey

AbstractThis paper aims to improve the shortcomings of the empirical literature on regional social capital. The following three research questions are addressed: (i) do regional social capital and economic growth have an endoneous (circular) relationship as opposed to the exogenous one‐way relationship assumed in the literature; (ii) What are the socio‐economic and demographic determinants of cross‐regional variation in social capital? And (iii) Are spatial spillovers relevant in the analysis of these questions? Empirically, we pursue the analysis for 81 Turkish provinces in 2015. Indeed, regional social capital in Turkey is far less studied than country‐level social capital. The methodology adopted includes kernel density estimates, ordinary least squares, three stage least squares, and spatial error models. In terms of the obtained results, First, regional social capital is heterogenously distributed across regions. Second, social capital has no significant impact on economic growth but the growth induces the generation of social capital (in social norms). This represents a first result of reserve causality in the literature. Third, a typical province that has high social capital is the one with relatively high income, more even income distribution, low unemployment, big households and older age profile. Fourth, there is the evidence of spatial dependence that should be incorporated in empirical analyses.

Análise exploratória para a modelagem da frequência de acidentes de trânsito agregados ao nível de zonas de tráfego

Este trabalho apresenta uma análise exploratória das variáveis que contribuem na modelagem da segurança viária ao nível estratégico e tático de planejamento. A princípio, uma base de dados geográficos de 126 zonas de tráfego é compilada a partir de dados socioeconômicos disponíveis, características da rede e dos acidentes georreferenciados. Visando separar os efeitos parciais das variáveis sobre a ocorrência de acidentes, a análise compreende: i) uma análise fenomenológica e de correlação que resultou na redução de variáveis preditoras, e ii) uma análise de regressão binomial negativa, que identificou os preditores significativos. Dada a natureza espacial dos dados geográficos, a suposição de independência espacial entre erros modelados é analisada. Os resultados confirmaram que os acidentes estão relacionados com a renda e atividade econômica, no nível estratégico, e a atributos físicos e de operação da rede, no nível tático. A evidência da dependência espacial no nível estratégico aponta direções para trabalhos futuros.

State and Local Sales Taxes and Business Activity in the United States

There has been an increasing reliance on sales taxation in both the states and counties in the United States. In this paper, we are examining the relationship between state and local sales taxation and business activity in the U.S. by utilizing county-level data for the period 2002-2011. We have found significant negative association between the state and county combined sales tax rate and annual payroll of businesses particularly in the manufacturing sector. There is also evidence of spatial dependence particularly in the payroll response of businesses within the contiguous region. While we found no significant relationship with employment, there is also statistically significant negative association with retail establishments and small establishments with less than 10 employees. It is possible that businesses respond to a sales tax rate increase first, or more directly, by reducing payroll rather than employment. While the economic significance of these results, however, is not found to be overwhelmingly strong, policymakers should still pay attention particularly to how manufacturing businesses respond to sales tax rate tax changes in the form of changes in payroll, and the responses from the small retail establishments.

Spatial Dependence in Asylum Migration

Existing refugees in a destination country from the same source country reduce the uncertainty faced by subsequent asylum migrants since existing refugees can provide information and assistance. We argue that such network effects extend beyond the borders of specific source countries. Potential asylum migrants might also be able to draw on networks from geographically proximate as well as linguistically similar countries and from countries having previously been colonised by the same destination country, thus creating spatial dependence in asylum migration among source countries. Many destination countries meanwhile aspire to reduce the inflow of migrants by tightening their asylum policies. Target countries which restrict their policies relatively more than other destinations deflect some asylum migrants to geographically proximate destination countries, thus creating spatial dependence among target countries. We find evidence for both types of spatial dependence in our global analysis of asylum migration. However, while statistically significant, the degree of spatial dependence among target countries is modest. On the source side, there is evidence for modest spatial dependence among linguistically similar countries and no evidence for spatial dependence among countries which were previously colonised by the same destination country. By contrast, we find substantial spatial dependence among geographically proximate source countries.

Explaining the appearance and success of open space referenda

Many communities in the United States have begun enacting policies to preserve open space, often through local voter referenda. New Jersey sponsors such municipal action through the Green Acres Program by providing funding and low interest loans to towns that choose to increase property taxes and spend the money raised on open space preservation for the purposes of conservation and/or recreation. This paper endeavors to understand which factors contribute to the appearance and success of these measures. Although previous literature has examined this issue, this is the first study to account for spatial dependence/spatial autocorrelation and to explore dynamic issues through survival analysis. The traditional two stage model from the literature is extended by incorporating a Bayesian spatial probit for the first stage and a maximum-likelihood spatial error model in the second stage. A Cox-proportional hazard model is used to examine the timing of referenda appearance. Spatial dependence is found in the second stage of the analysis, indicating that future studies should account for its influence. There is no strong evidence for spatial dependence or correlation in the first stage. The survival model is found to be a useful complement to the traditional probit analysis of the first stage.

Space-time income distribution dynamics in Mexico

The uneven income distribution in Mexico has frequently being subject to both scrutiny and concern. This phenomenon seems to have a spatial counterpart much less explored and increasingly complex. This paper introduces a novel approach to analyse space–time integration of income distribution dynamics in Mexico. We draw on recent extensions in Exploratory Space-Time Data Analysis (ESTDA) and directional statistics, to investigate spatial dynamics and income movement patterns between Mexican states over 70 years. We use spatial randomization to test directional co-movements in spatially contiguous units as evidence of spatial dependence in income distribution dynamics. Strong evidence of spatial integration of income distribution dynamics is found along the study period. Our results suggest that, in many instances, states do not act independently and we identify a range of integrated movements. The lack of independence itself has important implications for income distributional outcomes as higher mobility will not necessarily imply mixing in the distribution, which is more likely to occur among neighbouring states within a similar income strata. This can be illustrated by the findings of two spatial, yet, contrasting effects: spatial integration in (low) top-down mobility, on the one hand, and negative spatial dependence on the other. While the latter is mostly explained by losses in states and distributional gains of the neighbours with income mixing (rank shifts among neighbouring states) within a group of states, the former phenomena obey a different spatial process where a state and neighbours move in the same direction in the distributional space. Altogether, our findings suggest the presence of slow spatial change in Mexico, mainly due to the presence of heterogeneous, spatially integrated dynamics influencing net change in income distributional outcomes.

Spatial Dependence in Asylum Migration

Existing refugees in a destination country from the same source country reduce the uncertainty faced by subsequent asylum migrants since existing refugees can provide information and assistance. We argue that such network effects extend beyond the borders of specific source countries. Potential asylum migrants might also be able to draw on networks from geographically proximate as well as linguistically similar countries and from countries having previously been colonized by the same destination country, thus creating spatial dependence in asylum migration among source countries. Many destination countries meanwhile aspire to reduce the inflow of migrants by tightening their asylum policies. Target countries which restrict their policies relatively more than other destinations deflect some asylum migrants to geographically proximate destination countries, thus creating spatial dependence among target countries. We find evidence for both types of spatial dependence in our global analysis of asylum migration. However, while statistically significant, the degree of spatial dependence among target countries is modest. On the source side, there is evidence for modest spatial dependence among linguistically similar countries and no evidence for spatial dependence among countries which were previously colonized by the same destination country. By contrast, we find substantial spatial dependence among geographically proximate source countries.

Spatial dependence in constitutional constraints: the case of US states

Several theories suggest that states’ choices of constitutional rules are at least partially a function of neighboring constitutions. This paper provides the first analysis of spatial dependence of specific provisions within state constitutions in the United States. The analysis effectively makes constitutional rules endogenous, contributing to a relatively underdeveloped branch of constitutional economics. By employing a series of probit estimations of nineteen specific constitutional rules, I find evidence of spatial dependence in state constitutions. Specifically, the presence of specific constitutional constraints pertaining to term limits, supreme court justice selection, recall, home rule, direct democracy, constitutional amendment by convention, balanced budget requirements, tax and expenditure limits, line item veto, victims’ bill of rights, health and welfare, right to privacy, environmental protection, sex discrimination, abortion, and official language all exhibit some evidence spatial dependence.

The use of nest boxes by arboreal marsupials in the forests of the Central Highlands of Victoria

The results are reported of a nest-box study conducted in two locations in the mountain ash (Eucalyptus regnans) forests of the Central Highlands of Victoria (south-eastern Australia) to compare usage of different nest-box designs located at different heights in trees. A total of 96 nest boxes was established using a rigorous experimental design – two regions (Powelltown and Toolangi State Forests), two forest age classes (20-year post-logging regrowth and 60-year fire- and salvage-logging regrowth), two nest-box designs (large boxes with large entrance holes and small boxes with small entrance holes), and two heights at which nest boxes were attached to trees (3 m and 8 m above the ground). The study entailed setting out four nest boxes at each of 24 sites to meet the design criteria. Evidence of occupancy by vertebrates was recorded in a total of 19 of 96 boxes on 11 of 24 sites site during regular inspections over more than three years. Thirteen boxes were used by Leadbeater's possum (Gymnobelideus leadbeateri), six by the mountain brushtail possum (Trichosurus cunninghami) and seven by the common ringtail possum (Pseudocheirus peregrinus). The common ringtail possum and mountain brushtail possum were seen only in high–large boxes but Leadbeater's possum used all but the low–large boxes. There was evidence of spatial dependence in usage patterns, with all four boxes at a given site showing signs of eventually being occupied. Only two nest boxes located in mountain ash forest regenerating after the 1939 wildfires were occupied. Relatively limited use of nest boxes supports concerns about the use of a nest box over large scales and long timeframes as an effective recovery tool for species threatened by the loss and subsequent shortage in the numbers of naturally occurring hollows.

Scale-dependant control of motile epifaunal community structure along a coral reef fishing gradient

Large-scale fishing is mostly conducted using towed gears that reduce the biomass and diversity of benthic invertebrates. However, it is impossible to differentiate between the physical disturbance effect of towed gears from the effect of fish predator removal upon benthic invertebrate communities. Here we explore the impact of fish removal alone on the community structure of small motile coral reef invertebrates (epifauna) along a subsistence fishing intensity gradient in the Lau group, Fiji. We deployed settlement plates at three areas in each of six fishing grounds and examined the density and class richness of the motile epifaunal communities and the associated algal communities in relation to the structure of fish and benthic communities. Motile epifaunal density was unrelated to fishing intensity. However, at smaller inter-area scale (0.5–10 km) motile epifaunal density was negatively related to plate algal biomass, whereas at the larger inter-fishing-ground scale (4–180 km) motile epifaunal density was positively related to the rugosity (substrate complexity) of the surrounding benthos. The class richness and diversity (Margalef's d) of motile epifaunal communities were negatively related to fishing intensity, but unrelated to grazing intensity, rugosity or algal biomass at either scale. Benthic community structure varied significantly with fishing intensity; hard-coral cover was lower and turf-algal cover was higher at high fishing pressure. The variation in benthic community structure was associated with variation in fish community structure, which in turn varied with fishing intensity. Motile epifaunal community structure upon plates was linked to the structure of the surrounding benthic community, but was not directly linked to the plate algal community. We suggest the decline in richness of the motile epifauna community along the fishing gradient is attributable to either to exploiter-mediated coexistence or the reduction in ‘habitat quality’ of the surrounding benthos. At the large spatial scale substrate complexity is the key determinant of motile epifaunal density, suggesting predation by fishes plays an important structuring role at this scale. Assuming that rugosity is inversely related to predation risk then this study represents the first evidence for spatial-dependence on the top-down (predation) vs. bottom-up (algal biomass) control of community structure. We argue fisheries exploitation, in the absence of a physical disturbance can negatively influence motile epifaunal community structure at large spatial scales.

Spatial and Probability Distribution of Mexican Bean Beetle (Coleoptera: Coccinellidae) Egg Mass Populations in Dry Bean

The spatial pattern and probability distribution of Mexican bean beetle, Epilachna varivestis Mulsant, egg masses were studied in four dry bean, Phaseolus vulgaris L., fields near Scottsbluff, NE, during the 1994 and 1995 growing seasons. Sampling was conducted in a regular and uniform grid to guarantee coverage of the field. The experimental unit in all fields was 0.30 row-m, and five measurements were made at 0.76-m intervals. A total of 12,290 locations was sampled. Geostatistics and discrete statistics were used to describe the egg mass distribution. Regression was used to detect and separate macroscale trends from the microscale variation. The presence of macroscale variation indicated a significant edge effect with ovipositing females moving into dry bean fields from their overwintering sites. The microscale variation estimated from the estimated residuals from regressions to estimate trends was studied using semivariograms for all fields. Semivariograms strongly indicate that Mexican bean beetle eggs are randomly distributed across the field and that this random distribution holds across 10-fold differences in population densities. As a result of the significant macroscale trends observed, we conclude that egg mass densities may be greater in areas of the field near edges adjacent to beetle overwintering sites. The probability distribution that best fit the data was the negative binomial. Our results illustrate the importance of scale in discussing and characterizing distribution. Although there is evidence of edge effect at the field level, there is no evidence of spatial dependence between egg samples at the sampling region level. At an even lower level, the egg mass itself, eggs are aggregated.

Spatial dependence and block designs in spaced plant herbage trials

Data from three ryegrass spaced plant variety trials conducted at Crossnacreevy, Co. Down in each of 1989, 1990 and 1991 were investigated for evidence of spatial dependence. Spatial dependence was most evident in variates measuring the overall dimensions of the plants, especially late season variates. However, the ‘date of ear emergence’ variate, which identifies most of the variety distinctnesses that the trials are intended to detect, was not spatially dependent. On average, 45% of the residual variation in the plot means of the spatially dependent variates was estimated to be of a spatial nature. Consequently, it is likely that the efficiency of analysis of these variates would be improved by using spatial analysis instead of non-spatial analysis or by using alpha (incomplete block) designs instead of complete block designs. The spatial information was used to determine the optimal incomplete block sizes and the likely increase in efficiency due to using alpha designs instead of complete block designs. The optimal incomplete block size for a trial with 10 plants per plot was compared with the optimal incomplete block size for the same trial with single plant plots at the same spacing and was found to be smaller. The gains in efficiency were larger in the trial with 10 plants per plot than in the trial with single plant plots.