Placenames are seemingly universal, with the potential to reveal different systems of organizing information in everyday communication. We report on the relationship between placenames in Jahai, an indigenous language spoken by the Jahai people of the Malay Peninsula, and the environment. Our approach explores the tendency to organize names using a hierarchy of kinship associated with the cnεl, mythological entities in origin stories, which appears to map onto catchment areas. By associating linguistic data with these ethnographic inputs and geographical properties calculated in a Geographic Information System, we generate and make suggestions for productive ways of understanding placenames as systems.

The prevalence of vector-associated parasitic infections is high in central-southern Italy. The deltaic coastal plain of the Volturno River has been suspected, by veterinary practitioners, to have a high accidental incidence of Dirofilaria repens. Thus, the goal of this study was to evaluate the prevalence of dirofilariasis and other coinfections frequently described in dogs living in the Volturno area. Blood samples of 100 clinical asymptomatic dogs were examined using a Knott's technique and polymerase chain reaction in order to identify microfilariae. Other vector-borne coinfections were also investigated using ELISA kits. The results were analysed using statistical and Geographic Information System (GIS) software. Microfilariae of D. repens were detected in 10% of the dogs surveyed, with a presence of antibodies against Ehrlichia canis (4/10) and Dirofilaria immitis (1/10). Such high incidence should be considered in light of the zoonotic potential for D. repens and the support for more regular use of repellents to prevent the spread of this disease. The GIS analyses indicated that the study area provides suitable conditions to sustain populations of mosquito vectors and D. repens parasites throughout much of the year.

Cystic echinococcosis (CE) is caused by the larval form of Echinococcus granulosus that can cause serious health and economic problems in the endemic foci. CE is globally distributed in various climatic conditions from circumpolar to tropical latitudes. Iran is an important endemic area with a spectrum of weather conditions. The aim of this study was to determine the effects of geo-climatic factors on the distribution of livestock CE in south-western Iran (SWI) in 2016 to 2018. Data of livestock CE were retrieved from veterinary organizations of four provinces of SWI. The geo-climatic factors, including mean annual temperature (MAT), minimum MAT (MinMAT), maximum MAT (MaxMAT), mean annual rainfall (MAR), elevation, mean annual evaporation (MAE), sunny hours, wind speed, mean annual humidity (MAH), slope, frost days and land cover, were analysed using geographical information systems (GIS) approaches. The statistical analysis showed that MAR, frost days, elevation, slope and semi-condensed forest land cover were positively and MAE, MAT, MaxMAT, MinMAT and salt and salinity land cover were negatively correlated with CE occurrence. MAE was shown to be a predictive factor in the stepwise linear logistic regression model. In short, the current GIS-based study found that areas with lower evaporation were the main CE risk zones, though those with lower temperature and higher rainfall, altitude and slope, especially where covered with or in close proximity of semi-condensed forest, should be prioritized for consideration by health professionals and veterinarians for conducting control programmes in SWI.

Fasciola hepatica is a helminth parasite that causes huge economic losses to the livestock industry worldwide. Fasciolosis is an emerging foodborne zoonotic disease that affects both humans and grazing animals. This study investigated the associations between climatic/environmental factors (derived from satellite data) and management factors affecting the spatial distribution of this liver fluke in cattle herds across different climate zones in three Mexican states. A bulk-tank milk (BTM) IgG1 enzyme-linked immunosorbent assay (ELISA) test was used to detect F. hepatica infection levels of 717 cattle herds between January and April 2015. Management data were collected from the farms by questionnaire. The parasite's overall herd prevalence and mean optical density ratio (ODR) were 62.76% and 0.67, respectively. The presence of clustered F. hepatica infections was studied using the spatial scan statistic. Three marked clusters in the spatial distribution of the parasite were observed. Logistic regression was used to test three models of potential statistical association from the ELISA results using climatic, environmental and management variables. The final model based on climatic/environmental and management variables included the following factors: rainfall, elevation, proportion of grazed grass in the diet, contact with other herds, herd size, parasite control use and education level as significant predictors. Geostatistical kriging was applied to generate a risk map for the presence of parasites in dairy herds in Mexico. In conclusion, the spatial distribution of F. hepatica in Mexican cattle herds is influenced by multifactorial effects and should be considered in developing regionally adapted control measures.

Hemorrhagic fever with renal syndrome (HFRS) caused by hantaviruses is a serious public health problem in China, accounting for 90% of HFRS cases reported globally. In this study, we applied geographical information system (GIS), spatial autocorrelation analyses and a seasonal autoregressive-integrated moving average (SARIMA) model to describe and predict HFRS epidemic with the objective of monitoring and forecasting HFRS in mainland China. Chinese HFRS data from 2004 to 2016 were obtained from National Infectious Diseases Reporting System (NIDRS) database and Chinese Centre for Disease Control and Prevention (CDC). GIS maps were produced to detect the spatial distribution of HFRS cases. The Moran's I was adopted in spatial global autocorrelation analysis to identify the integral spatiotemporal pattern of HFRS outbreaks, while the local Moran's Ii was performed to identify ‘hotspot’ regions of HFRS at province level. A fittest SARIMA model was developed to forecast HFRS incidence in the year 2016, which was selected by Akaike information criterion and Ljung–Box test. During 2004–2015, a total of 165 710 HFRS cases were reported with the average annual incidence at province level ranged from 0 to 13.05 per 100 000 persons. Global Moran's I analysis showed that the HFRS outbreaks presented spatially clustered distribution, with the degree of cluster gradually decreasing from 2004 to 2009, then turned out to be randomly distributed and reached lowest point in 2012. Local Moran's Ii identified that four provinces in northeast China contributed to a ‘high–high’ cluster as a traditional epidemic centre, and Shaanxi became another HFRS ‘hotspot’ region since 2011. The monthly incidence of HFRS decreased sharply from 2004 to 2009 in mainland China, then increased markedly from 2010 to 2012, and decreased again since 2013, with obvious seasonal fluctuations. The SARIMA ((0,1,3) × (1,0,1)12) model was the most fittest forecasting model for the dataset of HFRS in mainland China. The spatiotemporal distribution of HFRS in mainland China varied in recent years; together with the SARIMA forecasting model, this study provided several potential decision supportive tools for the control and risk-management plan of HFRS in China.

The high near-infrared reflectance (0.76 to 0.90 μm) of Big Bend loco and Wooton loco contributed significantly to their orange-red and red image tonal responses, respectively, on color-infrared aerial photographs making them distinguishable from associated vegetation and soil. Big Bend loco could also be distinguished on color-infrared and near-infrared black-and-white video imagery where it had distinct red and whitish tonal responses, respectively. Computer analyses of photographic and videographic images showed that Big Bend loco and Wooton loco populations could be quantified from other landscape features. A global positioning system was integrated with the video imagery that permitted latitude-longitude coordinates to appear on each image. The latitude-longitude data were integrated with a geographical information system to map Big Bend loco populations.

In many regions primates are an important dietary resource for isolated human populations, and they are among the most hunted species by traditional and indigenous communities in the Neotropics. Little is known about the characteristics or the spatial and temporal patterns of hunting, which limits a more detailed evaluation of its impact. We describe, quantify and analyse the spatial dynamics of primate hunting in the várzea (seasonally flooded forest) and paleovárzea (characterized by a series of low-lying ridges interspersed with flooded depressions, which result from cyclical depositional processes) environments of Central Amazonia, based on the monitoring of riverine communities at the Amanã and Mamirauá Sustainable Development Reserves over an 11-year period. During this time 402 primate hunting events were recorded, involving the harvesting of 541 individuals of nine species: Alouatta juara, Aotus cf. vociferans, Ateles chamek, Cacajao ouakary, Callicebus lucifer, Cebus albifrons, Saguinus inustus, Saimiri cassiquiarensis and Sapajus macrocephalus. Two hundred and forty of these hunts occurred in the paleovárzea and 162 in the várzea. The distances travelled by the hunters from their communities to the kill sites were significantly different between the environments, with longer distances being covered in the paleovárzea. Hunters in the paleovárzea also hunted across significantly larger areas than those in the várzea. The continuous monitoring of hunting areas and the gathering of data on the exploitation of species are necessary to understand the effects of hunting, as well as to support decision making in the management of the local fauna by traditional communities, and the development of effective conservation strategies for the local game species.

Broomrapes (Orobanche and Phelipanche spp.) are obligate root parasites that spend most of their life cycle in the soil subsurface, making them hard to detect. In these underground developmental stages, broomrapes are highly sensitive to herbicides, and therefore knowledge of the dynamics of their parasitism is essential to precisely apply herbicide for their control. To address these complexities, two approaches have been proposed: (1) estimating the temporal variation in parasitism dynamics and predicting broomrape parasitism on its host by thermal time; (2) characterizing the spatial variation in infestation within and between fields by using a geographical information system and a global positioning system. In addition, the use of molecular markers to identify broomrape infestation (species and amount) in the field can contribute to determining its spatial distribution, which can then be used for site-specific weed management. In this paper, we discuss how technology can be optimized for control of the root-parasitic broomrapes. Special attention is given to the development of integrative approaches. An example of a decision support system for the rational management of Egyptian broomrape in processing tomato is given.

In-field surveys, which directly estimate weed population densities, typically utilize either random or nonrandom field selection methods. We used both methods to characterize the distribution and frequency of glyphosate-resistant (GR) horseweed populations and other late-season soybean weed escapes and to develop a database for tracking weed shifts, control failures, and the presence of other herbicide-resistant biotypes over time in Indiana. In-field surveys were conducted in a total of 978 Indiana soybean fields during September and October of 2003, 2004, and 2005. Information from fields with horseweed was obtained from 158 sites (19%) sampled through a systematic random site selection method and 128 fields through a nonrandom site selection method. When present, horseweed seed was collected and germinated in the greenhouse; rosettes 5 to 10 cm wide were sprayed with 1.72 kg ae/ha of glyphosate. Populations with less than 60% control at 28 d after treatment were determined to be glyphosate resistant. A selected subset of glyphosate-resistant populations was confirmed resistant by subsequent glyphosate dose response experiments. All populations in the subset with less than 60% control at the 1.72 kg ae/ha rate of glyphosate demonstrated 4- to 110-fold levels of resistance (R : S ratios). Glyphosate-resistant populations were found in all regions of Indiana; however, the highest frequencies were in the southeastern (SE) region with 38% of fields sampled and only 1, 2, and 2% of fields sampled in the northwestern (NW), northeastern (NE), and southwestern (SW) regions, respectively. Information gathered in this survey can assist in the development of applied research, as well as reactive glyphosate-resistant horseweed management education in the SE region of the state. Moreover, detecting resistance at low frequencies can direct proactive resistance education to farmers and practitioners in the other regions of the state as a means of providing an early warning system to address glyphosate resistance in weeds.

The objectives of this work were (i) geographical analysis of the 2012–2014 outbreak of rabies in Greece using GIS and (ii) comparative analysis of animal cases with data of potential human exposure to rabies together with environmental data, in order to provide information for risk assessment, effective monitoring and control. Most animal cases (40/48) involved red foxes, while domestic animals were also diagnosed with rabies. Overall, 80% of the cases were diagnosed in central northern Greece; 75% of the cases were diagnosed in low altitudes (<343·5 m), within a distance of 1 km from human settlements. Median distance from livestock farms was 201·25 m. Most people potentially exposed to rabies (889/1060) presented with dog bite injuries. Maximum entropy analysis revealed that distance from farms contributed the highest percentage in defining environmental niche profiles for rabid foxes. Oral vaccination programmes were implemented in 24 administrative units of the country during 2013 and 2014, covering a total surface area of ~60 000 km2. Rabies re-occurrence in Greece emphasizes the need for ongoing surveillance in cross-border areas and in areas with intense human activity.

Large carnivores are recolonizing parts of North America and Europe as a result of modern management and conservation policy. In the midwestern USA, black bears Ursus americanus, cougars Puma concolor and grey wolves Canis lupus have the potential to recolonize provided there is suitable habitat. Understanding where large carnivores may become re-established will prepare resource professionals for the inevitable ecosystem effects and potential human–carnivore conflicts associated with these species. We developed individual and combined models of suitable habitat for black bears, cougars and wolves in 18 midwestern states, using geospatial data, expert-opinion surveys, and multi-criteria evaluation. Large, contiguous areas of suitable habitat comprised 35, 21 and 13% of the study region for wolves, bears and cougars, respectively. Approximately 12% of the region was considered suitable for all three species. Arkansas, Minnesota, Texas and Wisconsin had the highest proportions (> 40%) of suitable habitat for black bears; Arkansas, Michigan, Missouri, Texas and Wisconsin had the highest proportions (≥ 20%) of suitable habitat for cougars; and only in four states in the study region was < 29% of land suitable wolf habitat. Models performed well when validated by comparing suitability values of independent sets of known carnivore locations to those of random locations. Contiguous areas of suitable habitat typically spanned multiple states, thus coordination across boundaries and among agencies will be vital to successful conservation of these species. Our models highlight differences in habitat requirements and geographical distribution of potential habitat among these carnivores, as well as areas vital to their persistence in the Midwest.

We studied the spatial trend of norovirus (NoV) epidemics using sentinel gastroenteritis surveillance data for patients aged <15 years (n = 140) in the Tokyo area for the 2006–2007 to 2008–2009 seasons utilizing the kriging method of geographical information system (GIS). This is the first study of the spreading pattern of NoV epidemics using sentinel surveillance data. Correlations of sentinel cases between the seasons and with demographic data were examined to identify the trend and related factors. A similar pattern of diffusion was observed over the seasons, and its mean correlation between seasons was significantly high. A higher number of cases were found in the peripheral area, which surrounds the most populated central area, and showed a correlation with the ratio of the children population (r = 0·321, P < 0·01) and the ratio of residents in larger families (r = 0·263, P < 0·01). While NoV susceptibility remained, the results suggest a transmission route in the local community as a possible epidemic factor. Prevention with focus on the peripheral area is desirable.

To identify forests of high priority for conservation in tropical dry forests of New Caledonia, Fiji, the Marquesas and Hawaii, we examined patterns of woody plant species richness (total, native and endemic) and threatened species (IUCN categorization and density) at the stand level, using Gentry's transect method. There were associations between total, native and endemic plant species richness in all four Pacific dry forest regions but we found no significant association with the presence or density of species listed on the IUCN Red List. Dry forests in New Caledonia and Hawaii merit the highest conservation priority in the Pacific, based on level of endemism and number of threatened species. The study sites that merit high conservation priority are Metzdorf, Nekoro and Pindai, in New Caledonia, Kokee and Kaupulehu, in Hawaii, and Vatia, in Fiji. New Caledonia and Fiji have a small dry forest extent and protected area extent compared with other dry forests in biodiversity hotspots. Although we identified priority areas for dry forest conservation, more comparative plot data, presence/absence data in fragments and regional geographical data are needed to adequately manage and protect dry forests in the Pacific.

Site selection for Antarctic research stations is of great importance and is necessary to support Antarctic expeditions. Site selection is affected by both the scientific investigations planned and the expected life of stations following construction. In the site allocation process, an efficient spatial data management system is required to manage various criteria and a robust allocation method is important to handle decision uncertainties. The aim of this study was to build a criteria system and to conduct a site selection process with aid from geographical information systems (GIS) and the fuzzy analytical hierarchy process (FAHP). In considering the natural environment and building conditions, fifteen factors were used as multiple evaluation sub-criteria and grouped into four main criteria: scientific research, environment, logistical support and topography. Comparisons were made between potentially suitable areas and the locations of existing stations and camps to demonstrate fitness-for-use of the allocation results. Finally, the suitability map was applied to identify candidate sites for a new Chinese research station by considering the position of current stations and areas of scientific interest. This model offers a comprehensive methodology for decision-makers in the assessment of potential Antarctic research station sites.

A total of 20 749 bulk tank milk (BTM) samples was collected in November 2008 from all over Germany, corresponding to 20·9% of all German dairy herds. The BTM samples were analysed for antibodies against Fasciola hepatica using the excretory–secretory (ES) ELISA. A geospatial map was drawn to show herd prevalences per postal code area. Various spatial risk factors were tested for potential statistical associations with the ELISA results in logistic regression supported by a geographical information system (GIS). The mean seroprevalence was 23·6% and prevalences in different German federal states varied between 2·6% and 38·4%. GIS analysis revealed statistically significant positive associations between the proportion of grassed area and water bodies per postal code area and positive BTM ELISA results. This can be explained by the biology of the intermediate host, the amphibious snail Galba (Lymnea) truncatula and the pasture-borne nature of fasciolosis. The full logistic regression model had a Pseudo-R2 of 22%, while the final model obtained by controlled stepwise model building revealed a Pseudo-R2 of 14%, indicating that additional, unrecorded factors and random effects contributed substantially to the occurrence of positive ELISA results. Considering the high seroprevalences in some areas and the economic impact of fasciolosis, farmers and veterinarians should be strongly advised to implement effective liver fluke control programmes.

The epidemiology of schistosomiasis japonicum over small areas remains poorly understood, and this is particularly true in China. We aimed to identify high-risk areas for schistosomiasis and associated risk factors in the Poyang Lake region, China. A cross-sectional study was conducted and 60 of 920 persons (6·5%) were found to be infected with Schistosoma japonicum. Locations of households and snail habitats were determined using a hand-held global positioning system. We mapped the data in a geographical information system and used spatial scan statistics to explore clustering of infection, logistic regression and Bayesian geostatistical models to identify risk factors for each individual's infection status and multinomial logistic regression to identify risk factors for living in a cluster area. The risk of schistosomiasis was spatially clustered and higher in fishermen and males, not in persons who lived in close proximity to snail habitats and infected water sources. This study has demonstrated significant spatial variation in the prevalence of schistosomiasis at a small spatial scale. The results suggest that demographic factors (gender, occupation) rather than the distance to infected water are driving human transmission at small-scale spatial levels. Such information can be used to plan locally targeted interventions based on anthelminthic drug administration, snail control and sanitation improvement.

Beginning in 1970, the potential of remote sensing (RS) techniques, coupled with geographical information systems (GIS), to improve our understanding of the epidemiology and control of schistosomiasis in Africa, has steadily grown. In our current review, working definitions of RS, GIS and spatial analysis are given, and applications made to date with RS and GIS for the epidemiology and ecology of schistosomiasis in Africa are summarised. Progress has been made in mapping the prevalence of infection in humans and the distribution of intermediate host snails. More recently, Bayesian geostatistical modelling approaches have been utilized for predicting the prevalence and intensity of infection at different scales. However, a number of challenges remain; hence new research is needed to overcome these limitations. First, greater spatial and temporal resolution seems important to improve risk mapping and understanding of transmission dynamics at the local scale. Second, more realistic risk profiling can be achieved by taking into account information on people's socio-economic status; furthermore, future efforts should incorporate data on domestic access to clean water and adequate sanitation, as well as behavioural and educational issues. Third, high-quality data on intermediate host snail distribution should facilitate validation of infection risk maps and modelling transmission dynamics. Finally, more emphasis should be placed on risk mapping and prediction of multiple species parasitic infections in an effort to integrate disease risk mapping and to enhance the cost-effectiveness of their control.

There is growing interest and commitment to the control of schistosomiasis and other so-called neglected tropical diseases (NTDs). Resources for control are inevitably limited, necessitating assessment methods that can rapidly and accurately identify and map high-risk communities so that interventions can be targeted in a spatially-explicit and cost-effective manner. Here, we review progress made with (1) mapping schistosomiasis across Africa using available epidemiological data and, more recently, climate-based risk prediction; (2) the development and use of morbidity questionnaires for rapid identification of high-risk communities of urinary schistosomiasis; and (3) innovative sampling-based approaches for intestinal schistosomiasis, using the lot quality assurance sampling technique. Experiences are also presented for the rapid mapping of other NTDs, including onchocerciasis, loiasis and lymphatic filariasis. Future directions for an integrated rapid mapping approach targeting multiple NTDs simultaneously are outlined, including potential challenges in developing an integrated survey tool. The lessons from the mapping of human helminth infections may also be relevant for the rapid mapping of malaria as its control efforts are intensified.