Termite mounds have been poorly studied in tropical rainforest in contrast to those of savannahs where they create fertility hotspots and influence the spatial pattern of vegetation. An inventory of termite mounds and of 15 tree species with a diameter at breast height ≥ 10 cm was carried out in two 800-ha blocks, in two rainforest sites located in northern Congo. We used inhomogeneous and intertype K functions to study the spatial pattern of termite mounds and of tree species around mounds, respectively. We found that mounds in Loundoungou were over-dispersed within a radius of less than 70 m, while those in Mokabi were randomly spaced. Tree species within a 20-m radius around a mound were aggregated towards the mound, e.g. Entandrophragma cylindricum, randomly distributed, or even repulsed by the mound. The specific responses also differed in the two sites. These results suggest that (i) the mounds in Loundoungou were created by savannah termite species 3,000-2,000 years BP during the Late Holocene Rainforest Crisis and (ii) the mounds in Mokabi are characteristic of forest mounds. The impact of termite mounds on the spatial pattern of tree species is thus site-dependent, and these differences might be due to species seed dispersal strategies and to soil calcium concentrations.

The diabetes epidemic is expanding rapidly in India, with 69.2 million people living with diabetes in 2015. This study assessed the spatial pattern and determinants of diagnosed diabetes prevalence in the districts of six states and one union territory (UT) in southern India – a region that has a high prevalence of diabetes. Using cross-sectional population-based survey data from the 2012–13 District Level Household and Facility Survey-4, the prevalence and magnitude of diagnosed diabetes at district level for the population aged 18 years and above were computed. Moran’s I was calculated to explore the spatial clustering of diagnosed diabetes prevalence. Ordinary Least Square (OLS) and Spatial Lag (SL) regression models were carried out to investigate the spatial determinants of diagnosed diabetes prevalence. The prevalence of diagnosed diabetes was found to be substantially higher than that of self-reported diabetes in southern India (7.64% vs 2.38%). Diagnosed diabetes prevalence in the study area varied from 10.52% in Goa to 4.89% in Telangana. The Moran’s I values signified positive moderate autocorrelation. Southern India had 14.15 million individuals with diagnosed diabetes in 2012–13. Bangalore had the highest number of persons with diagnosed diabetes, and Palakkad had the smallest number. In the OLS and SL models, the proportion of people with secondary education and above, wealthy and Christian populations were found to be significant determinants of diagnosed diabetes prevalence. In addition, in the OLS model, the proportion of Scheduled Tribe population showed a negative relationship with diagnosed diabetes prevalence. In order to prevent or postpone the onset age for diabetes, there is a need to raise awareness about diabetes in India.

In the post-pandemic period, influenza A(H1N1)pdm09 virus has been detected in swine populations in different parts of the world. This study was conducted to determine the presence and spatial patterns of this human pandemic virus among Nigerian pigs and identify associated risk factors. Using a two-stage stratified random sampling method, nasal swab specimens were obtained from pigs in Ibadan, Nigeria during the 2013–2014 and 2014–2015 influenza seasons, and the virus was detected by reverse transcriptase-polymerase chain reaction (RT-PCR). Purified RT-PCR products were sequenced in both directions, and sequences were aligned using MUSCLE. Phylogenetic analysis was conducted in MEGA6. Purely spatial scan statistics and a spatial lag regression model were used to identify spatial clusters and associated risk factors. The virus was detected in both seasons, with an overall prevalence of 8·7%. Phylogenetic analyses revealed that the M genes were similar to those of pandemic strains which circulated in humans prior to and during the study. Cluster analysis revealed a significant primary spatial cluster (RR = 4·71, LLR = 5·66, P = 0·0046), while ‘hours spent with pigs (R2 = 0·90, P = 0·0018)’ and ‘hours spent with pigs from different farms (R2 = 0·91, P = 0·0001)’ were identified as significant risk factors (P < 0·05). These findings reveal that there is considerable risk of transmission of the pandemic virus, either directly from pig handlers or through fomites, to swine herds in Ibadan, Nigeria. Active circulation of the virus among Nigerian pigs could enhance its reassortment with endemic swine influenza viruses. Campaigns for adoption of biosecurity measures in West African piggeries and abattoirs should be introduced and sustained in order to prevent the emergence of a new influenza epicentre in the sub-region.

Predictions of weed seedling populations from seedbank data should characterize the spatial distribution as well as the composition and abundance of weeds. The spatial distribution of seedbank and seedling populations of common lambsquarters and annual grasses (giant foxtail, large crabgrass, and fall panicum) were described in moldboard plow and no-tillage soybean fields from 1990 to 1993. Spearman rank correlations between seedbank and seedling densities were significant for common lambsquarters in both tillages and all years, but for annual grasses correlations were significant only in no-tillage. Semivariograms showed spatial autocorrelation in seedbank and seedling populations of common lambsquarters in all years in no-till, but less often in the moldboard plow field. Annual grass seed and seedling populations were autocorrelated in the no-till field every year except 1993, and in the moldboard plow field in 1992 and 1993 only. Cross-semivariograms showed spatial continuity between seedbank and seedling population densities in 3 of 4 yr in no-till for common lambsquarters, and in all years of no-till and 1 yr of moldboard plow for annual grasses. Grey-scale field maps of common lambsquarters seedbanks corresponded visually to maps of seedling populations and could have been used to target control efforts, but visual correspondence between annual grass seedbank and seedling maps was poor. Seedbank and seedling mapping may be useful for site-specific management, but additional information is needed to understand the variation in the relationships between these two populations over time and space.

Seed dispersal, interacting with environmental disturbance and management across heterogeneous landscapes, results in irregular weed spatial distributions. Describing, predicting, and managing weed populations requires an understanding of how weeds are distributed spatially and the consequences of this distribution for population processes. Semivariograms and kriged maps of weed populations in several fields have helped describe spatial structure, but few generalizations can be drawn except that populations are aggregated at one or more scales. Limited information is available on the effect of weed arrangement, pattern, or field location on weed population processes. Because weeds are neither regular nor uniform in distribution, mean density alone is of limited value in estimating yield loss or describing population dynamics over a whole field. Sampling strategies that account for spatial distribution can increase sampling efficiency. Further research should focus on understanding processes that cause changes in spatial distributions over time to help predict rates of invasion and potential extent of colonization.

Weeds are often spatially aggregated in maize fields, and the level of aggregation varies across and within fields. Several annual weed species are present in maize fields before postemergence herbicide application, and herbicides applied will control several species at a time. The goal of this study was to assess the spatial distribution of multispecies weed infestation in maize fields. Ground-based imagery was used to map weed infestations in rain-fed maize fields. Image segmentation was used to extract weed cover information from geocoded images, and an expert-based threshold of 0.102% weed cover was used to generate maps of weed presence/absence. From 19 site-years, 13 (68%) demonstrated a random spatial distribution, whereas six site-years demonstrated an aggregated spatial pattern of either monocotyledons, dicotyledons, or both groups. The results of this study indicated that monocotyledonous and dicotyledonous weed groups were not spatially segregated, but discriminating these weed groups slightly increased the chances of detecting an aggregated pattern. It was concluded that weeds were not always spatially aggregated in maize fields. These findings emphasize the need for techniques allowing the assessment of weed aggregation prior to conducting site-specific weed management.

Recent studies have shown major advantages of increased crop density and spatial uniformity for competition of wheat with weeds. Field experiments were performed over 3 yr to determine whether the effects of crop density and sowing pattern on weed suppression are influenced by nitrogen fertilization. The independent variables were crop sowing pattern (normal rows and a highly uniform pattern), seeding density (204, 449, and 721 seed m−2) and nitrogen fertilization (0 and 80 kg nitrogen ha−1) of spring wheat, grown under high weed pressure. Increased crop density had strong and consistent negative effects on weed biomass and positive effects on crop biomass and yield. At the highest crop density, weed biomass was less than half that at the lowest density. Weed biomass was generally lower, and yield higher, in the uniform pattern, except in one case in which a combination of factors gave one weed species an early size advantage over the crop. When weeds were controlled with herbicide, no effects of crop density or spatial uniformity on crop biomass or yield were observed. Nitrogen fertilization increased weed biomass in 2 of 3 yr, and it also increased crop biomass in 2 of 3 yr, but there was little evidence that the relative effects of crop density and spatial pattern on weed suppression were influenced by nitrogen fertilization. In the presence of weeds, the highest yields were obtained with high crop density, high spatial uniformity and nitrogen fertilization. The results indicate that increased weed suppression through increased crop density and spatial uniformity will occur over a wide range of nitrogen levels.

Privet has escaped from cultivation and is invading natural areas throughout eastern North America. Understanding the pattern of invasion over time could help us develop more efficient management strategies. We studied the invasion history and spatial distribution pattern of privet by mapping age and spatial data for established patches in a 132-ha (326 ac) forested natural area in northeast Ohio. We determined the age of 331 geo-referenced patches by counting annual rings, and mapped them with corresponding land habitat. Age distribution and cumulative number of privet patches over about 40 yr showed three phases of invasion. The initial 19-yr lag phase was characterized as a dispersed spatial pattern (based on nearest neighbor analysis), with patches located mostly at edges of different habitats and open places. In a second phase of about 15 yr, an average of 19 patches were initiated yearly, in a pattern that trended towards clustered. The final phase began around 2007, as the rate of new patch establishment declined, possibly because of saturation of the suitable habitat. Establishment of new patches was not associated with specific habitats. Aggregation of patches with similar ages increased after 1998 and became significantly clustered. Mapping of clusters of old and young patches identified invasion hot spots and barriers. Results affirmed that the best time for invasive control is during the lag phase. By monitoring edge habitats associated with early establishment, managers might detect and control early invaders and delay the onset of the expansion phase.

The goals of this article are: (i) to understand how individual characteristics affect the likelihood of patients defaulting their pulmonary tuberculosis (PTB) treatment regimens; (ii) to quantify the predictive capacity of these risk factors; and (iii) to quantify and map spatial variation in the risk of defaulting. We used logistic regression models and generalized additive models with a spatial component to determine the odds of default across continental Portugal. We focused on new PTB cases, diagnosed between 2000 and 2013, and included some individual information (sex, age, residence area, alcohol abuse, intravenous drug use, homelessness, HIV, imprisonment status). We found that the global default rate was 4·88%, higher in individuals with well-known risk profiles (males, immigrants, HIV positive, homeless, prisoners, alcohol and drug users). Of specific epidemiological interest was that our geographical analysis found that Portugal's main urban areas (the two biggest cities) and one tourist region have higher default rates compared to the rest of the country, after adjusting for the previously mentioneded risk factors. The challenge of treatment defaulting, either due to other individual non-measured characteristics, healthcare system failure or patient recalcitrance requires further analysis in the spatio-temporal domain. Our findings suggest the presence of significant within-country variation in the risk of defaulting that cannot be explained by these classical individual risk factors alone. The methods we advocate are simple to implement and could easily be applied to other diseases.

In this paper, we investigate which factors determine tree clustering in Southern African savannas. This was tested by measuring clustering of trees using the T-squared sampling method in plots of the Kruger National Park experimental burning programme in South Africa. Fire return interval is the main treatment in these plots, but also several auxiliary determining parameters like clay content in the soil, diameter of tree canopies, understorey composition, tree species diversity and average annual rainfall were measured while sampling. In the Kruger National Park 48 plots distributed over four different landscape types and with three different burning treatments (never, once every 3 y and annually) were sampled. First, we related the clustering of trees to these environmental variables. When looking at the most abundant species in each plot, the analysis revealed that clustering is mainly correlated with clay content in the soil. This analysis also showed that fire frequency had a positive effect on the clustering of tree species that are not very abundant. We suggest that less abundant species might be less resistant to fire and therefore adopt a mechanism of clustering to exclude grass fires under their canopy. Finally, we tested the effect of clustering on the impact of fire on trees by analysing the relationship between the distance of a tree to its nearest neighbour and its canopy diameter. We found that clustering reduces the damaging effect of fire on trees. Our study contributes to understanding of savanna functioning by showing which processes are relevant in the distribution of savanna trees.

Spodoptera frugiperda (J.E. Smith) is a major pest in maize fields in Argentina. However, a sampling method that accounts for spatial pattern and allows reliable pest density estimations is still lacking. This paper addresses the issue of how sampling unit size can influence the characterization of S. frugiperda spatial pattern and the performance of sampling plans. An intensive sampling programme for S. frugiperda larvae was carried out in maize fields from October until March in four growing seasons. On each sampling date, 12 to 20 sampling units were taken at random. Each unit consisted of 1, 2, 4, 6, 8, 10 or 12 consecutive plants along a row. The linearized version of the Taylor's power law (TPL) was fitted to mean and variance estimated for each sampling date and data set through least squares regression. In general, b values from TPL were significantly >1 (P<0.05), indicating an aggregated sampling distribution. Regression slopes (b) ranged from 1.28 to 1.48 in small larvae and from 1.06 to 1.24 in large larvae, indicating stronger clumping in the former. TPL parameters were used to develop constant precision sampling plans. The efficiency of these plans in terms of expected total cost (searching and handling sampling units) was very sensitive to the size of the sampling units with small larvae but not with large larvae. The influence of sampling unit size and spatial pattern on TPL parameters and sampling costs is discussed.

Tropical forests of the Amazon Basin are being rapidly converted to agricultural land uses and fallow land, resulting in accelerating rates of forest loss in one of the world's most biodiverse ecoregions. This process has been extensively described and modelled, but as yet there has been no formal test of how the spatial patterns of deforested and fragmented areas change with the spatial scale of forest clearings. It was hypothesised that different land-use practices are driving small and large clearings, with small-scale cultivators often creating small, irregularly shaped clearings and large-scale ranchers and soy farmers creating larger, more regular-shaped clearings. To quantitatively test this hypothesis, Mandelbrot's theory of fractals was applied to deforested areas in the Brazilian Amazon to test for scale-invariance in deforestation patterns. The spatial pattern of deforestation differed between small and large clearings, with the former creating more complex landscapes and with a threshold occurring at c. 1200 ha in area. As a consequence, the sizes and shapes of forest clearings, and hence the relative vulnerability of the remaining forest to edge, area and isolation effects, may differ systematically between landscapes with different deforestation drivers. Further tests of this hypothesis are needed to assess its efficacy in other tropical landscapes and geographical locations.

A fine-scale survey of the distribution of free-living terrestrial arthropods in the Stillwell Hills region of Kemp Land, East Antarctica, was carried out between 22 December 1996 and 27 January 1997. Three species, all Acari, were recorded: Protereunetes maudae Strandtmann, Nanorchestes triclivatus Booth and N. lalae Strandtmann. Population densities varied from 0 to 6802 ind. m−2 with a mean of 954 ind.m−2. The favoured microhabitat was found to be beneath stones in damp locations on north- and west-facing slopes. Sites with microalgal growth supported more microarthropods than sites with mosses, lichens and macroalgae. Arid and saline habitats, including such sites as wind-sweptridges and the seashore, were found to lack microarthropods. Thermal and humidity profiles above and below the ground surface were recorded to investigate the microenvironments of Acari. Special attention was focused upon the moderating role of snow thickness, vegetation cover, aspect and vertical depth in the soil profile. These microclimate data suggest that Acari are able to avoid the extremes of low temperature experienced at macroclimate level but that heat stress and desiccation may play important limiting roles.

The spatial pattern of lichen species richness was analyzed in a forest ecosystem impacted for 50 years by industrial emissions from a steelworks. Geostatistical tools were used to characterize the spatial pattern of the number of lichen species and multiple regression analysis was used to identify factors influencing it. Spatial analysis showed high variation of lichen species richness on a local scale, caused by patchiness of natural habitat factors (species composition of trees, their age, shade, etc.). On a large spatial scale, species richness differentiated the western from the eastern part of the forest. The western part, closer to the sources of pollution, had fewer species (average 6–10 per locality) than the eastern part (10–15 per locality). Multiple regression analysis was used to examine the relationships between the species richness of lichens and several environmental variables: input of ions with bulk precipitation (SO42−, NO−3, Cl−, Ca2+, Mg2+, Fe3+, Zn3+, Pb2+, Cd2+), distance to forest edge, tree stand age, and number of species per locality. Regression analysis was preceded by factor analysis for the input of ions to obtain uncorrelated variables. Regression explained 53% of the variation of lichen species richness. Highly significant predictor variables were the factor connected with the input of pollutants (Fe3+, Zn2+) emitted by the steelworks (negative effect) and the number of trees per locality (positive effect). Species richness was also affected by the age structure of the tree stand; more species were recorded in old forests.

Lake Titicaca is the largest freshwater lake in South America and one of the highest and oldest of the world's large lakes, but very little of its ecology is known. We report results from a study on the spatial variation of decomposition rate of Schoenoplectus tatora in Inner Puno Bay affected by direct wastewater discharges. The aims of the research were: (1) to evaluate the effect of benthos exclusion and the influence of other environmental factors on decomposition and (2) to map the decomposition rate in order to describe the spatial heterogeneity in the water body. We carried out the study at 21 sampling points using both fine-meshed and coarse-meshed litterbags to exclude and to allow detritivore action, respectively. Decomposition was on the average faster in the former than in the latter treatment. However, the difference decreased with increasing detritivore abundance, and reversed in the most densely populated waters of the bay. Coupled spatial dependence of the decomposition rate and temperature was observed. Both variables were related with the distance from the wastewater discharges, suggesting that thermal pollution constrains the decomposition rate within the inner bay. Detritivores did not change the general trend imposed by temperature, but their presence increased the spatial heterogeneity of the process.

A 272-ha grove of dominant Microberlinia bisulcata (Caesalpinioideae) adult trees ≥50 cm stem diameter was mapped in its entirety in the southern part of Korup National Park, Cameroon. The approach used an earlier-established 82.5-ha permanent plot with a new surrounding 50-m grid of transect lines. Tree diameters were available from the plot but trees on the grid were recorded as being ≥50 cm. The grove consisted of 1028 trees in 2000. Other species occurred within the grove, including the associated subdominants Tetraberlinia bifoliolata and T. korupensis. Microberlinia bisulcata becomes adult at a stem diameter of c. 50 cm and at an estimated age of 50 y. Three oval-shaped subgroves with dimensions c. 850 m×1350 m (90 ha) were defined. For two of them (within the plot) tree diameters were available. Subgroves differed in their scales and intensities of spatial tree patterns, and in their size frequency distributions, these suggesting differing past dynamics. The modal scale of clumping was 40–50 m. Seed dispersal by pod ejection (to c. 50 m) was evident from the semi-circles of trees at the grove's edge and from the many internal circles (100–200 m diameter). The grove has the capacity, therefore, to increase at c. 100 m per century. To form its present extent and structure, it is inferred that it expanded and infilled from a possibly smaller area of lower adult-tree density. This possibly happened in three waves of recruitment, each one determined by a period of several intense disturbances. Climate records for Africa show that 1740–50 and 1820–30 were periods of drought, and that 1870–1895 was also regionally very dry. Canopy openings allow the light-demanding and fast-growing ectomycorrhizal M. bisulcata to establish, but successive releases are thought to be required to achieve effective recruitment. Nevertheless, in the last 50 y there were no major events and recruitment in the grove was very poor. This present study leads to a new hypothesis of the role of periods of multiple extreme events being the driving factor for the population dynamics of many large African tree species such as M. bisulcata.

Biological crusts are a common feature of the soil surface in arid and semi-arid ecosystems, where they play a major role in ecosystem functioning. In recent years, there has been an increasing interest in the ecophysiology, floristics, and dynamics of crust-forming lichens but little is known about the effect of vascular plants on their small-scale spatial distribution. To increase our understanding about the interactions between crust-forming lichens and vegetation in semi-arid areas, the spatial pattern and interaction of two soil lichens, Cladonia convoluta and Squamarina cartilaginea, at two microsites in semi-arid Stipa tenacissima steppe of south-eastern Spain are evaluated. The aim of this study was to determine if the microsite provided by Stipa tussocks promoted changes in the individual patterns and in the spatial covariation of these soil lichens. Spatial analysis by distance index (SADIE) coupled with correlation analysis was used to explore the individual patterns and the spatial relationships between the two species. SADIE detected a significant clumped pattern in the spatial distribution of both species, but Stipa tussocks promoted changes only in the spatial pattern of Cladonia. Correlation analysis revealed the presence of significant relationships between the two species, particularly close to Stipa tussocks. The results show that the microenvironment provided by Stipa is able to modify the small-scale spatial pattern of soil lichens in semi-arid steppe, and suggest the presence of facilitation between Stipa and Cladonia.

The island of Minorca, Spain, has become a patchy mosaic landscape as a result of centuries of human-induced fragmentation. The dynamics of the landscape elements and the spatial pattern of Minorca were analysed to test whether this human-modelled landscape was at a stationary state, and, if it was the case, to see whether the system could be characterized by a particular spatial pattern. Landsat TM satellite images were processed to derive land cover classification and vegetation index maps corresponding to the years 1984 and 1992, the best compromise between null cloudiness and maximum time span. The classification was used to test the stationary state by estimating the transition matrix of land cover. The Normalized Difference Vegetation Index (NDVI) was used to analyse the spatial pattern of change at the patch level. The spatial analysis of NDVI was based on four indices: fractal dimension, number and size distribution of patches, and spatial Kappa index. Those pattern descriptors were compared with values obtained from stochastic landscape simulations. Temporal analysis showed that land cover proportions remained approximately constant over the 8-year period, although interchange amongst patches existed. This suggested that the landscape of Minorca was close to a stationary state. The study of NDVI changes revealed that the spatial structure was different from that of neutral models and presented scale invariance properties. Results from land cover transitions and from NDVI patterning suggest that the landscape of Minorca is a critical system, in the framework of the self-organized criticality hypothesis, i.e. the mosaic of patches would self-organize at the frontier of a dynamic equilibrium constituted by the balance between disturbances and successional processes.