Causes Of Spatial Heterogeneity Research Articles

The Impact of Rural Location on Farmers’ Livelihood in the Loess Plateau: Local, Urban–Rural, and Interconnected Multi-Spatial Perspective Research

With the strengthening of regional and urban–rural interactions, farmers’ livelihood activities are becoming increasingly complex, and environmental factors that influence farmers’ livelihoods have multi-spatial effects. Consequently, comprehending farmers’ livelihoods from a multi-spatial perspective is imperative. Based on surveys conducted in 65 villages and 451 households in Jia County on the Loess Plateau, China, rural locations were deconstructed into natural, traffic, and positional advantages to explore the relationships and mechanisms between the rural environment and farmers’ livelihood stability from local, urban–rural, and interconnected multi-spatial perspectives. We found that 77% of the villages achieved a moderate or high Rural Location Advantage Index (RLAI) rating; 45% still lack natural advantages and are mainly located in hilly and sandy areas because of the fragile ecological environment of the Loess Plateau. Additionally, the Livelihood Stability Index (LSI) was moderate overall, but with significant spatial heterogeneity, and 72% of farmers possess strong transition capacity and have shifted away from relying on monoculture as their primary livelihood strategy. While a certain coupling correspondence exists between the LSI and RLAI, the interaction is intricate rather than a simple linear agglomeration process. The spatial variation in the LSI results from the superposition or interaction of multi-spatial location factors. The rural–urban spatial location factors are the key control element of the LSI and the interaction between rural–urban and local spatial location factors has the greatest influence on the LSI. It is simple for interconnected spatial location factors to produce a scale correlation effect, and have non-negligible effects on farmers’ livelihoods when they interact with other spatial location factors. Understanding the impact of rural location on farmers’ livelihood from a multi-spatial perspective is of great practical significance for identifying the causes of spatial heterogeneity in livelihoods and enhancing multi-level policy coordination on rural revitalization and livelihood security.

Mapping the short-term exposure–response relationships between environmental factors and health outcomes and identifying the causes of heterogeneity: A multivariate-conditional-meta-autoregression-based two-stage strategy

Studying the spatial distribution of short-term exposure–response relationships (ERRs) between environmental factors and health-related outcomes and identifying the causes of spatial heterogeneity are of great importance on making region-specific environment-related public health policies. However, the widely used multivariate meta-regression (MMR)-based two-stage strategy does not consider the spatial dependence between regions, which may give unsatisfactory results, even a false policy implication. More importantly, possibly due to the limitation, the spatial distribution of short-term ERRs is less frequently focused on. In this work, we combined the conditional autoregression with MMR to construct an extended model called MCMAR. Then a MCMAR-based two-stage strategy is developed to map the ERRs and identify the causes of heterogeneity. A published motivating example and a simulation study were used to validate the efficiency of our strategy. Results show that the MCMAR-based strategy achieved considerably better fit performance in terms of the Akaike information criterion, obtained a more reasonable spatial distribution of ERRs, and identified more accurate causes of heterogeneity than the classic strategy. As numerous spatial ERR datasets have been and are being produced, we believed that MCMAR-based two-stagy strategy will have an important and wide application value.

Modelling the epidemiology of zoonotic parasites transmitted through a predator-prey system in urban landscapes: The Calgary Echinococcus multilocularis Coyote Agent-based model (CEmCA)

Traditional epidemiological models for managing disease risk face serious hurdles when applied to complex life-cycle parasites that involve several host species. Echinococcus multilocularis (Em) is such a parasite and the aetiological agent of a serious zoonosis, Alveolar Echinococcosis, affecting thousands of people every year worldwide. The parasite is transmitted through predation of infectious intermediate hosts (rodents) by definitive hosts (foxes, coyotes). Definitive hosts are usually territorial with individual home ranges in spatially heterogeneous urban landscapes, where they carry very diverse parasite load, thus creating a highly heterogeneous distribution of the parasite in the urban environment. To incorporate individual differences and spatial heterogeneity into an epidemiological model, we developed Calgary Echinococcus multilocularis Coyote Agent-based model (CEmCA).The CEmCA was developed to understand the processes and mechanisms that produces the heterogeneity in the transmission of Em. The model simulates behaviors of individual coyotes inhabiting the City of Calgary as agents, reproducing behavioral patterns such as their home ranges, where and which prey species they hunt, where they defecate, and how they transmit Em. The agents perform all its behaviors in a simulation landscape that represent an actual Calgary landscape that includes maps of natural habitats and small mammal assemblages.The CEmCA proved to be highly sensitive to unobservable epidemiological parameters, and although not fully matching the observed patterns it provided useful insights into the epidemiological processes of Em. Moreover, our experimental simulations supported the hypothesis that distribution of intermediate hosts and separation of habitats were the main causes of spatial heterogeneity in infection.By integrating individual differences and spatial heterogeneity this study contributed to the understanding of the epidemiology of trophically transmitted parasite with complex life-cycles. Notwithstanding requiring further work, this approach holds many promises for further applications in preventative management of infectious diseases in urban landscapes.

Ecological and genetic variation in reef-building corals on four Society Islands

We quantified benthic community structure on shallow (10 m isobath) reefs separated by 3–130 km on four islands in the south Pacific, and evaluated the roles of disturbances vs. coral recruitment as causes of spatial heterogeneity. Reefs were surveyed in 2013 on Moorea, Tahiti, Tetiaroa, and Maiao, with community structure sampled at two sites on each island using photoquadrats. The effects of coral recruitment on population structure were evaluated through genetic analyses of Pocillopora on three of the islands. Benthic community structure with functional group resolution differed among islands and generally among sites, but coral community structure (generic resolution) differed among islands, but generally not among sites. Genetic analyses of Pocillopora using the open reading frame of host mtDNA revealed varying relative abundances of Pocillopora meandrina/Pocillopora eydouxi, Pocillopora verrucosa, Pocillopora effuses, and two unnamed haplotypes on each island. These results suggest that corals on each island represent unique samplings of genetically discrete larval assemblages rather than random samplings of a single larval assemblage. Together, our findings emphasize the extent to which coral community structure varies over a scale of <200 km, and suggests that recruitment from spatially discrete pools of coral larvae plays an important role in creating spatial variation in community structure, even where reefs are connected by prevailing currents.

Geospatial observations on tropical forest surface soil chemistry

At plot scales (&lt;1 km2) used to study tropical forest plant communities the causes of spatial heterogeneity of soils are disputed. We collected, georeferenced, and chemically analyzed a large spatial sample of soil cores (n = 625 sites, 6.25 cm diameter × 10 cm depth cores) on an approximately 28 m regular grid from the Barro Colorado Island (BCI) 50‐ha (0.5 km2) forest dynamics plot (FDP), Republic of Panama (9.15° N, 79.8° W). Here we present these data for general use. We also present differential GPS measurements of the plot corners for the BCI 50‐ha FDP, which aid in geospatial research in one of the most studied tropical forests. Further, we present a free open source command line software program written in Python that allows point data referenced to the plot coordinate system to be converted to a projected coordinate reference system for geospatial research. Together, the data sets allow for testing the drivers of soil heterogeneity in a tropical tree community using a wide variety of geospatial data sources.

Regional Heterogeneity and Interregional Research Spillovers in European Innovation: Modelling and Policy Implications

Guastella G. and van Oort F. G. Regional heterogeneity and interregional research spillovers in European innovation: modelling and policy implications, Regional Studies. In agglomeration studies the effects of various regional externalities related to knowledge spillovers remain largely unclear. To explain innovation clustering, scholars emphasize the contribution of localized knowledge spillovers (LKS) and, specifically when estimating the knowledge production function (KPF), of (interregional) research spillovers. However, less attention is paid to other causes of spatial heterogeneity. In applied works, spatial association in data is econometrically related to evidence of research spillovers. This paper argues that, in a KPF setting, omitting spatial heterogeneity might lead to biased estimates of the effect of research spillovers. As an empirical test, a spatial KPF is estimated using EU-25 regional data, including a spatial trend to control for unexplained spatial variation in innovation. Accounting for geographical characteristics substantially weakens evidence of interregional research spillovers.

Diagnostic model construction and example analysis of habitat degradation in enclosed bay: III. Sansha Bay habitat restoration strategy

Unbalanced inputs and outputs of material are the root cause of habitat degradation in Sansha Bay, Fujian Province, China. However, the cumulative pollution varies in different geographic locations and natural conditions in the enclosed bay. In this study, hydrodynamic conditions, sediment characteristics, and aquaculture methods were recognized as the underlying causes of spatial heterogeneity in the distribution of nitrogen and phosphorous pollutants, the two major controlling factors of habitat degradation in the bay area. In order to achieve the goal of balancing nutrient inputs and outputs in Sansha Bay, we developed a feasible and practical zone restoration strategy for reasonable adjustment and arrangement of aquaculture species and production scale in accordance with varying hydrodynamic conditions and sediment characteristics in six sub-bay areas (sub-systems). The proposed zone restoration strategy lays a solid foundation for habitat restoration and management in Sansha Bay.

Shear Wave Elasticity Imaging of Cervical Lymph Nodes

A pilot study of real-time shear wave ultrasound elastography (SWE) for cervical lymphadenopathy in routine clinical practice was conducted on 55 nodes undergoing conventional ultrasound (US) with US-guided needle aspiration for cytology. Elastic moduli of stiffest regions in nodes were measured on colour-coded elastograms, which were correlated with cytology. Malignant nodes (n = 31, 56.4%) were stiffer (median 25.0 kPa, range 6.9–278.9 kPa) than benign nodes (median 21.4 kPa, range 8.9–30.2 kPa) (p = 0.008, Mann Whitney U test). A cut-off of 30.2 kPa attained highest accuracy of 61.8%, corresponding to 41.9% sensitivity, 100% specificity and 0.77 area under the receiver operating characteristic curve. Qualitatively, elastograms of benign nodes were homogeneously soft; malignant nodes were homogeneously soft or markedly heterogeneous with some including regions lacking elasticity signal. SWE is feasible for neck nodes. It appears unsuitable for cancer screening but may detect a subset of malignant nodes. The cause of spatial heterogeneity of malignant nodes on SWE is yet to be established.

Tree mortality in drought-stressed mixed-conifer and ponderosa pine forests, Arizona, USA

We monitored tree mortality in northern Arizona (USA) mixed-conifer and ponderosa pine ( Pinus ponderosa Dougl. ex Laws) forests from 1997 to 2007, a period of severe drought in this area. Mortality was pervasive, occurring on 100 and 98% of 53 mixed-conifer and 60 ponderosa pine plots (1-ha each), respectively. Most mortality was attributable to a suite of forest insects, mediated by drought stress. The number of trees dying from 2002 to 2007 was more than 200% greater than the number dying from 1997 to 2002 in mixed-conifer forest and 74% greater in ponderosa pine forest. Extent of mortality was spatially variable in both forest types. Median cumulative mortality (the ratio of dead to live trees) increased by approximately 53 and 65% in mixed-conifer and ponderosa pine forests, respectively, from 2002 to 2007. Median mortality rates from 2002 to 2007 were approximately 2.0% year −1 in mixed-conifer forest (range = 0–28.5%) and 0.4% year −1 in ponderosa pine forest (range = 0–13.6%). Mortality rates generally were not strongly related to either elevation or stand density. Mortality was nonrandom with respect to tree size classes and species. Proportions of trees dying were greatest in the largest size classes, particularly in mixed-conifer forest, where mortality in the largest size class exceeded 22% from 2002 to 2007. Mortality in mixed-conifer forest was particularly pronounced for quaking aspen (85%) and white fir (28%), the least drought tolerant species present. These results provide an early glimpse of how these forest types are likely to respond to predicted climate changes in the southwestern USA. They suggest that these forests are not resilient to climate change, and that treatments to increase resilience to climate change may be appropriate. Research on causes of spatial heterogeneity in extent of mortality might suggest valuable approaches to aid in increasing resilience.

Spatial modelling and landscape‐level approaches for visualizing intra‐specific variation

Spatial analytical methods have been used by biologists for decades, but with new modelling approaches and data availability their application is accelerating. While early approaches were purely spatial in nature, it is now possible to explore the underlying causes of spatial heterogeneity of biological variation using a wealth of environmental data, especially from satellite remote sensing. Recent methods can not only make inferences regarding spatial relationships and the causes of spatial heterogeneity, but also create predictive maps of patterns of biological variation under changing environmental conditions. Here, we review the methods involved in making continuous spatial predictions from biological variation using spatial and environmental predictor variables, provide examples of their use and critically evaluate the advantages and limitations. In the final section, we discuss some of the key challenges and opportunities for future work.

Seed distribution of four co-occurring grasses around Artemisia halodendron shrubs in a sandy habitat

In a natural population of the perennial semi-shrub Artemisia halodendron in a shifting sandy habitat in the Horqin Desert of eastern Inner Mongolia, six isolated adult A. halodendron individuals of similar canopy size were chosen as target plants. The density of seeds in the top 5 cm soil depth around shrubs was measured using transects aligned to the four main wind directions and at different distances from the shrub base on both the windward and leeward sides. The effects of shrub presence on seed distribution of four co-occurring grasses were examined by linking seed distribution to seed traits. Of the four species, Setaris viridis and Eragrostis pilosa had small but similar seed mass, while Chloris virgata and Aristida adscensionis had large but similar seed mass. The species were grouped into two cohorts: small-seeded vs. large-seeded cohorts, and shrub presence effects on seed distribution of both cohorts were examined. We found marked difference in the seed distribution pattern among species, especially between the small-seeded and large-seeded cohorts. The small-seeded cohort had significantly higher seed accumulation on the windward than the leeward sides in the most and least prevailing wind directions and much higher seed accumulation on the leeward than the windward sides in the second and third most prevailing wind directions, while opposite patterns occurred in the large-seeded cohort. Four species also showed marked variation in the seed distribution pattern among transects and between windward and leeward sides of each transect. This study provided further evidence that shrubs embedded in a matrix of herbaceous plants is a key cause of spatial heterogeneity in seed availability of herbaceous species. However, seed distribution responses to the presence of shrubs will vary with species as well as with wind direction, sampling position (windward vs. leeward sides of the shrub) and distance from the shrub.

Patterns of Influenza-associated Mortality among US Elderly by Geographic Region and Virus Subtype, 1968–1998

The regular seasonality of influenza in temperate countries is recognized, but regional differences in patterns of influenza-related mortality are poorly understood. Identifying patterns could improve epidemic prediction and prevention. The authors analyzed the monthly percentage of deaths attributable to pneumonia and influenza among people aged 65 or more years in the contiguous United States, 1968-1998. The local Moran's I test for spatial autocorrelation and correlograms assessing space-time synchrony within each influenza season were applied to detect and to characterize mortality patterns. Western US regions experienced epidemics of greater magnitude than did eastern regions. Positive spatial autocorrelation (two-sided p = 0.001) revealed the similarity in influenza mortality of neighboring states, with several western states forming a focus of high mortality. In transmission seasons dominated by virus subtype A(H3N2), mortality was correlated at a high and consistent level across the United States (mean correlation = 0.56, standard deviation = 0.134). However, when subtype A(H1N1) or type B dominated, the average synchrony was lower (mean correlation = 0.23, standard deviation = 0.058). These novel analyses suggest that causes of spatial heterogeneity (e.g., large-scale environmental drivers and population movement) have impacted influenza-associated mortality.

Temporal and Spatial Genetic Variability in White-tailed Deer (Odocoileus virginianus)

Starch-gel electrophoresis was used to assess temporal and spatial genetic variation in populations of white-tailed deer (Odocoileus virginianus) in western Tennessee. Samples of liver and kidney obtained from animals at five localities during 1985-1992 were analyzed at 11 loci known to be polymorphic in white-tailed deer. There were minimal significant differences in allelic frequencies between sexes and among age groups for each year at each locality and among years at each locality with ages and sexes combined. No significant difference occurred among mean values of heterozygosity. A heterozygote deficiency was detected in white-tailed deer populations from western Tennessee and could reflect limited inbreeding but was more likely due to Wahlund effects. Limited temporal variation occurred among years within a locality and indicated a stasis in terms of minimal genetic drift and harvest effects on genetic structure of the populations. Herd origin, stocking history of populations, and gene flow were probable causes of spatial heterogeneity in deer populations in western Tennessee.

Using tree recruitment patterns and fire history to guide restoration of an unlogged ponderosa pine/Douglas-fir landscape in the southern Rocky Mountains after a century of fire suppression

Summary Tree age and fire history were studied in an unlogged ponderosa pine/Douglas-fir (Pinus ponderosa/Pseudotsuga menziesii) landscape in the Colorado Front Range mountains. These data were analysed to understand tree survival during fire and post-fire recruitment patterns after fire, as a basis for understanding the characteristics of, and restoration needs for, an ecologically sustainable landscape. Comparisons of two independent tree age data sets indicated that sampling what subjectively appear to be the five oldest trees in a forest polygon could identify the oldest tree. Comparisons of the ages of the oldest trees in each data set with maps of fire history suggested that delays in establishment of trees, after stand-replacing fire, ranged from a few years to more than a century. These data indicate that variable fire severity, including patches of stand replacement, and variable temporal patterns of tree recruitment into openings after fire were major causes of spatial heterogeneity of patch structure in the landscape. These effects suggest that restoring current dense and homogeneous ponderosa pine forests to an ecologically sustainable and dynamic condition should reflect the roles of fires and variable patterns of tree recruitment in regulating landscape structure.

Variable Predation: Effects of Whelks on a Mid‐Intertidal Successional Community

In most habitats and ecosystems, predation varies significantly over space and over time. While several studies have demonstrated the effects of varying predation intensities, the effects of varying frequencies of predation have not been addressed explicitly. Here, I studied the impact of variable predation by whelks on a mid—intertidal successional community at a wave—exposed environment on the coast of Oregon. Densities of whelks were monitored in fixed—position quadrats for 34 mo, permitting an estimation of the natural spatial and temporal variation in predation by whelks. Two simultaneous cage experiments were then conducted for a period of 25 mo. One experiment evaluated the effect of prolonged exclusion of invertebrate predators on the sessile community. The other experiment evaluated the effects of the intensity and the temporal frequency of predation by whelks by manipulating both the density and presence of whelks inside cages. Three density levels were combined with three temporal patterns of predation (constant predation, medium and low frequency) in an orthogonal design to create nine different predation regimes. The replicated design allowed me to separate the effects of these two components of predation. The densities of the two whelk species present in the study site, Nucella canaliculata and N. emarginata, were highly correlated over time and varied greatly within and among years. Some areas of the site had whelks present most of the time (high frequency), while other areas were rarely visited. The frequency at which whelks were observed in a given area was uncorrelated with the yearly mean density, which contributed to the within—habitat variability in predation regimes by whelks. A suite of direct and indirect effects were observed following the permanent exclusion of invertebrate predators, notably, a rapid increase in the cover of the bay mussel Mytilus trossulus and a slow and small increase in the cover of gooseneck barnacles and the California mussel Mytilus californianus. Temporally variable predation (medium and low frequencies) produced community compositions different from those observed under a constant predation regime or predator exclusions. In general, individual species responses to variable predation could not be predicted from knowledge of the overall effect of predators obtained in the permanent exclusion experiment, nor from the results observed under different intensities and constant predation. Similarly, the actual number of predation days, estimated from the density and number of days whelks were in the cages, was not correlated with the mean cover of species. These results support the hypothesis that temporal frequency is an important component of predation with distinctive effects on intertidal prey communities. Both the ability of some prey to escape predators by reaching a large size and the temporal pattern of prey recruitment seemed important in determining the effect of variable predation on individual prey, but mechanistic understanding of the responses was complicated by the existence of many indirect effects. While temporally variable predation did not significantly increase spatial variability in prey abundance, constant predation regimes tended to reduce this variability over the course of succession. Temporal variability in predation by whelks can have distinctive effects on prey, create distinctive community compositions, and affect successional paths in this intertidal community. Temporal variability in predation is probably an important, yet poorly understood cause of spatial heterogeneity in most ecosystems.

Plant Dominance Along an Experimental Nutrient Gradient

Fertilization experiments in an 8—yr—old field demonstrated that N was the major limiting nutrient of N, P, K, Ca, and Mg, and suggested that Mg became limiting when N was added. After the fertilization experiments, this field was disturbed via thorough disking and divided into 36 plots for a Latin square design experiment on the effect of N:Mg fertilization ratios on vegetation patterns. By the second year, the major species had separated along the imposed N:Mg gradient, with Agrostis scabra dominant at the low Mg but high N end, followed by Agropyron repens, Berteroa incana, Oenothera biennis, and Aristida basiramea, which was dominant at the high Mg but low N end of the gradient. An unmanipulated resource, light availability at the soil surface, was significantly affected by the treatments. The results demonstrate that spatial heterogeneity in the relative availability of soil nutrient may be one cause of spatial heterogeneity in early successional vegetation.