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Pain and psychopathology co-occur in adolescence, but the directionality and etiology of these associations are unclear. Using the pain questionnaire and the Child Behavior Checklist from the Adolescent Brain Cognitive Development study (n = 10,414 children [770 twin pairs] aged 12–13), we estimated longitudinal, co-twin control, and twin models to evaluate the nature of these associations. In two-wave cross-lag panel models, there were small cross-lag effects that suggested bidirectional associations. However, the co-twin control models suggested that most associations were familial. Pain at age 12 and 13 was mostly environmental (A = 0–12%, C = 15–30%, E = 70–73%) and the twin models suggested that associations with psychopathology were primarily due to shared environmental correlations. The exception was externalizing, which had a phenotypic prospective effect on pain, a significant within-family component, and a non-shared environmental correlation at age 12. Environmental risk factors may play a role in pain-psychopathology co-occurrence. Future studies can examine risk factors such as stressful life events. [ABSTRACT FROM AUTHOR]

Epiphytes on Posidonia oceanica play a crucial role for determination of the ecological status of marine environment in time and space besides the seagrasses alone. The study was aimed to estimate the spatiotemporal ecological status linked to variation in biometry of an epiphytic micro-calcareous red alga, Hydrolithon boreale, found on leaves of the meadow with the exclusive environmental parameters along the entire Turkish coast of the Mediterranean Sea. Collection of Posidonia oceanica samples was conducted at 64 stations in winter (December 2018–January 2019) and 112 stations in summer (June–July 2019) by SCUBA (0.4 × 0.4 m of a quadrate frame) in the infralittoral zone along the entire Turkish Mediterranean coast surrounded by the siliciclastic Taurus Mountain Range which favor growth of epiphytic micro-calcareous red algae. Percent occurrence of the epiphyte changed seasonally—lower in winter (25%) than in summer (44%). The epiphyte which is an indicator and sensitive to undisturbed marine area grew up well to 5 mm in diameter, 0.35 mm in thickness of the crust size, and was populated up to 1006 ind/m2 in summer owing to the increased utilization of the carbonate by the epiphyte with the increased water temperature. The size was contrasted to the density (abundance and biomass) in space. The biometry was significantly dependent on the siliciclastic-carbonate deposition as inferred from SiO4–Si of the water in relation to the leaf area index (LAI) of P. oceanica. Therefore, this deposition induced specimens to grow in size, followed by the reduced density concerning the N-based nutrient of the water. Further major environmental parameters which negatively affected the biometry were pH and total suspended matter of the water, analogous to turbidity. Of the trace elements, Ni was negatively correlated with the biometry, whereas the LAI was however positively correlated with all the anthropogenic-sourced trace elements (V, Cu, Zn, As, Cd, and Pb) in the leaves. Of the bottom types, the calcite rock had a higher density than the other soft bottoms in contrast to the size of the epiphyte. Future studies could be based on the present study for determination of the ecological status regarding two dominant epiphytes on leaves of two seagrasses (H. boreale on P. oceanica and partly Pneophyllum fragile on Cymodocea nodosa) found in the different environments and substrates in space and time. [ABSTRACT FROM AUTHOR]

Soil salinity is one of the major impact factors on agriculture in the South of Kazakhstan. Prediction and estimation of soil salinity before planting a season usually helps to plan for the leaching of the salt. In the paper, satellite data such as radar data and machine learning algorithms, were used to classify soil salinity. Numerical results were presented for the Turkestan region, which contains more than 102 points. The machine learning algorithms, including Gaussian Process, Decision Tree, and Random Forest, were compared. The evaluation of the model score was realized by using metrics, such as accuracy, Recall, and f1. In addition, the influence of the dataset features on the classification was investigated using machine learning algorithms. The research results showed that the Gaussian Process model has the best score among considered algorithms. In addition, the results are consistent with the outcome of the Shapley Additive exPlanations (SHAP) framework. [ABSTRACT FROM AUTHOR]

Macroalgae interact with planktonic microbes in seawater. It remains unclear how planktonic microbes interact with the environment and each other during the cultivation processes of commercially important algal species. Such an interaction is important for developing environment-friendly mariculture methods. In this study, the dynamics of the planktonic microbial community associated with Saccharina japonica were profiled during the seedling production stage, with its environmental correlation and co-occurrence pattern determined simultaneously. Microbial richness increased and positively correlated with light intensity and contents of NO3− and PO43−. A clear temporal succession of the community was observed, which coincided with changes in light intensity, dissolved oxygen, pH, and NO3− content. α-Proteobacteria, Bacteroidetes, γ-Proteobacteria, and the genera prevalent in these taxa dominated the planktonic microbial community, and their relative abundance temporally changed. A profile of keystone taxa that is different from prevalent genera was identified based on betweenness centrality scores. A modularized co-occurrence pattern was determined, in addition to intensified species-to-species interactions at the core of the co-occurrence network. These findings expanded our cognization of the planktonic microbial community in response to S. japonica cultivation. [ABSTRACT FROM AUTHOR]

This study evaluated the seasonal effects of two flavonoids on antioxidant activity and chromatographic profiles by thin layer chromatography and high-performance liquid chromatography (HPLC) in Erythroxylum suberosum A. St.-Hil, a species used by the Brazilian indigenous community. These variables were observed from August 2013 to May 2014 in correlation with climatic variables, such as temperature, rainfall index and global radiation. The chromatographic profiles were found to be similar in the aqueous and ethanol extracts, and flavonoid hyperoside and isoquercitrin were identified and quantified. In the inhibition of the DPPH• radical, the most active was the aqueous extract from the 2nd collection (IC50: 4.45 µg/mL). For the phosphomolybdenum complex reduction method, the ethanol extract from the 1st collection was the most active (206.39 µg/mL equivalent ascorbic acid). Regarding the environmental correlations, it was observed that a higher global radiation index had a strong influence on the concentrations of hyperoside and contributed to the antioxidant activity. On the other hand, higher temperatures contributed to a higher isoquercitrin content in the aqueous extracts. These results indicate that August is the best month for the collection of Erythroxylum suberosum A. St.-Hil. leaves which have the highest isoquercitrin and hyperoside content and, thus, a high antioxidant activity. [ABSTRACT FROM AUTHOR]

Mesh-structured films formed by the post-processing of microfibers improves their permeability and dexterity, such as disposable masks. However, the aging behavior and potential risks of mesh-structured microfibers (MS-MFs) in landfill leachate remain poorly understood. Herein, the aging behavior and mechanisms of MS-MFs and ordinary polypropylene-films (PP-films) microplastics, as well as their leaching concerning dissolved organic matter (DOM) in landfill leachate were investigated. Results revealed that MS-MFs underwent more significant physicochemical changes than PP-films during the aging process in landfill leachate, due to their rich porous habitats. An important factor in the photoaging of MS-MFs was related to reactive oxygen species produced by DOM, and this process was promoted by photoelectrons under UV irradiation. Compared with PP-films, MS-MFs released more DOM and nano-plastics fragments into landfill leachate, altering the composition and molecular weight of DOM. Aged MS-MFs-DOM generated new components, and humus-like substances produced by photochemistry showed the largest increase. Correlation analysis revealed that leached DOM was positively correlated with oxygen-containing groups accumulated in aged MS-MFs. Overall, MS-MFs will bring higher environmental risks and become a new long-term source of DOM contaminants in landfill leachate. This study provides new insights into the impact of novel microfibers on landfill leachate carbon dynamics. [Display omitted] • UV light promotes the aging of MS-MFs than that of PP-films in landfills. • MS-MFs release more photoinduced humic-like DOM than PP-films into leachate. • Leached DOM is positively related with O-containing groups in aged MS-MFs. • DOM promote ROS generation, thus accelerating the aging of MS-MFs. • Aged MS-MFs aggravate the complexity of DOM in landfill leachate. [ABSTRACT FROM AUTHOR]

Longline fishery surveys are major contributors to groundfish species abundance estimates. Catchability is often assumed constant, but bait is lost or consumed at inconsistent rates during and across gear sets. Accounting for hook availability and gear saturation can improve abundance estimates, but these data are challenging to collect. Our objectives were to determine whether video camera systems can be used to collect these data from the Northeast Fisheries Science Center's Gulf of Maine Bottom Longline Survey and to explore the associations between hook disposition percentages and environmental characteristics. Electronic monitoring camera systems were deployed on partner vessels during two fall and two spring seasons to capture video of gear retrieval. During post-survey review, individual hooks were recorded as one of the following hook dispositions: bait, empty hook, fish, and invertebrate. Percentages of these hook dispositions were characterized across categorical (season, day or night, and bottom substrata) and continuous (bottom temperature, bottom depth, and substrate rugosity) survey station variables. Nonmetric multidimensional scaling and logistic regression analyses revealed correlations between retained bait and low bottom temperatures, the spring season, shallow depths, rough bottom substrata, and high terrain rugosity. These characteristics were typical of shallow, inshore, and topographically variable survey strata, suggesting that catchability differs among habitat types. This information will be incorporated into catch rate models to develop standardized indices of abundance for groundfish stock assessments. This study is an example of the utility of electronic technologies to supplement on board data collection during cooperative fishery surveys. • We examined bait retention and hook disposition of retrieved longline survey gear. • Retained bait was correlated with springtime, rugged seafloor, and daytime hauls. • The effect of depth on bait retention was significant in the spring but not fall. • Catchability differs among habitat types and with seasonal ecological interactions. • Hook disposition data will be used to improve catch estimates of groundfish species. [ABSTRACT FROM AUTHOR]

To mitigate the accelerated corrosion of blast furnace gas pipelines induced by severe environmental conditions, this study has established an extensive high-throughput sensor system in the field. It leverages corrosion big data technology to investigate the corrosion factors affecting industrial gas pipelines and to precisely analyze the influence of related variables. The results indicated that temperature reduction is the driving factor that causes increased pipeline corrosion. On one hand, temperature fluctuations impact the evaporation and condensation of moisture in the tube. On the other hand, temperature fluctuations, in conjunction with corrosive gases, exhibit significant coupling effects, resulting in more severe corrosion. In addition, critical points for relative humidity and temperature are evident. When humidity exceeds 50%, corrosion in the pipe begins to increase, reaching its peak at 70%. The increase in temperature has a slowing effect on pipeline corrosion, reaching a peak value at 40°C. The response of corrosion rate to the concentration of corrosive gases follows a linear pattern. Based on these observations, we propose an effective corrosion control scheme. [Display omitted] • Established an extensive high-throughput sensor system to analyze corrosion factors. • Created data-driven corrosion control recommendations and optimization methods. • The relative humidity threshold for corrosion enhancement is only 49%. • A linear increasing relationship between harmful gases and corrosion rate under certain conditions. • Discover the corrosion driving effect of temperature. [ABSTRACT FROM AUTHOR]

Abstract Background Species richness and composition pattern of amphibians along elevation gradients in eastern Nepal Himalaya are rarely investigated. This is a first ever study in the Himalayan elevation gradient, the world’s highest mountain range and are highly sensitive to the effects of recent global changes. The aim of the present study was to assess amphibian community structure along elevation gradients and identify the potential drivers that regulate community structures. Amphibian assemblages were sampled within 3 months in both 2014 and 2015 (from May to July) using nocturnal time constrained and acoustic aids visual encounter surveys. In total, 79 transects between 78 and 4200 m asl were sampled within 2 years field work. A combination of polynomial regression, generalized linear models, hierarchical partitioning and canonical correspondence analysis were used to determine the effects of elevation and environmental variables on species richness, abundance, and composition of amphibian communities. Results Species richness and abundance declined linearly with increasing elevation, which did not support the Mid-Domain Model. Among all the environmental variables, elevation, surface area and humidity were the best predictors of species richness, abundance and composition of amphibians. The majority of amphibian species had narrow elevation ranges. There was no significant correlation between species range size and elevation gradients. However, body size significantly increased along elevation gradients, indicating that Bergmann’s rule is valid for amphibians in eastern Nepal Himalaya. Conclusions This study indicates that eastern Nepal Himalaya is a hotspot in amphibian diversity, and it should be served as a baseline for management and conservation activities.

Macroalgae interact with planktonic microbes in seawater. It remains unclear how planktonic microbes interact with the environment and each other during the cultivation processes of commercially important algal species. Such an interaction is important for developing environment-friendly mariculture methods. In this study, the dynamics of the planktonic microbial community associated with Saccharina japonica were profiled during the seedling production stage, with its environmental correlation and co-occurrence pattern determined simultaneously. Microbial richness increased and positively correlated with light intensity and contents of NO3− and PO43−. A clear temporal succession of the community was observed, which coincided with changes in light intensity, dissolved oxygen, pH, and NO3− content. α-Proteobacteria, Bacteroidetes, γ-Proteobacteria, and the genera prevalent in these taxa dominated the planktonic microbial community, and their relative abundance temporally changed. A profile of keystone taxa that is different from prevalent genera was identified based on betweenness centrality scores. A modularized co-occurrence pattern was determined, in addition to intensified species-to-species interactions at the core of the co-occurrence network. These findings expanded our cognization of the planktonic microbial community in response to S. japonica cultivation.

Transgenic plants have the potential to produce recombinant proteins on an agricultural scale, with yields of several tons per year. The cost-effectiveness of transgenic plants increases if simple cultivation facilities such as greenhouses can be used for production. In such a setting, we expressed a novel affinity ligand based on the fluorescent protein DsRed, which we used as a carrier for the linear epitope ELDKWA from the HIV-neutralizing antibody 2F5. The DsRed-2F5-epitope (DFE) fusion protein was produced in 12 consecutive batches of transgenic tobacco (Nicotiana tabacum) plants over the course of 2 years and was purified using a combination of blanching and immobilized metal-ion affinity chromatography (IMAC). The average purity after IMAC was 57 ± 26% (n = 24) in terms of total soluble protein, but the average yield of pure DFE (12 mg kg−1) showed substantial variation (± 97 mg kg−1, n = 24) which correlated with seasonal changes. Specifically, we found that temperature peaks (>28°C) and intense illuminance (>45 klx h−1) were associated with lower DFE yields after purification, reflecting the loss of the epitope-containing C-terminus in up to 90% of the product. Whereas the weather factors were of limited use to predict product yields of individual harvests conducted for each batch (spaced by 1 week), the average batch yields were well approximated by simple linear regression models using two independent variables for prediction (illuminance and plant age). Interestingly, accumulation levels determined by fluorescence analysis were not affected by weather conditions but positively correlated with plant age, suggesting that the product was still expressed at high levels, but the extreme conditions affected its stability, albeit still preserving the fluorophore function. The efficient production of intact recombinant proteins in plants may therefore require adequate climate control and shading in greenhouses or even cultivation in fully controlled indoor farms.

Many species exhibit widespread spatial synchrony in population fluctuations. This pattern is of great ecological interest and can be a source of concern when the species is rare or endangered. Both dispersal and spatial correlations in the environment have been implicated as possible causes of this pattern, but these two factors have rarely been studied in combination. We develop a spatially structured population model, simple enough to obtain analytic solutions for the population correlation, that incorporates both dispersal and environmental correlation. We ask whether these two synchronizing factors contribute additively to the total spatial population covariance. We find that there is always an interaction between these two factors and that this interaction is small only when one or both of the environmental correlation and the dispersal rate are small. The interaction is opposite in sign to the environmental correlation; so, in the normal case of positive environmental correlation across sites, the population synchrony will be lower than predicted by simply adding the effects of dispersal and environmental correlation. We also find that population synchrony declines as the strength of population regulation increases. These results indicate that dispersal and environmental correlation need to be considered in combination as explanations for observed patterns of population synchrony.

Transgenic plants have the potential to produce recombinant proteins on an agricultural scale, with yields of several tons per year. The cost-effectiveness of transgenic plants increases if simple cultivation facilities such as greenhouses can be used for production. In such a setting, we expressed a novel affinity ligand based on the fluorescent protein DsRed, which we used as a carrier for the linear epitope ELDKWA from the HIV-neutralizing antibody 2F5. The D sRed-2 F 5- e pitope (DFE) fusion protein was produced in 12 consecutive batches of transgenic tobacco (Nicotiana tabacum) plants over the course of 2 years and was purified using a combination of blanching and immobilized metal-ion affinity chromatography (IMAC). The average purity after IMAC was 57 ± 26% (n = 24) in terms of total soluble protein, but the average yield of pure DFE (12 mg kg−1) showed substantial variation (± 97 mg kg−1, n = 24) which correlated with seasonal changes. Specifically, we found that temperature peaks (>28°C) and intense illuminance (>45 klx h−1) were associated with lower DFE yields after purification, reflecting the loss of the epitope-containing C-terminus in up to 90% of the product. Whereas the weather factors were of limited use to predict product yields of individual harvests conducted for each batch (spaced by 1 week), the average batch yields were well approximated by simple linear regression models using two independent variables for prediction (illuminance and plant age). Interestingly, accumulation levels determined by fluorescence analysis were not affected by weather conditions but positively correlated with plant age, suggesting that the product was still expressed at high levels, but the extreme conditions affected its stability, albeit still preserving the fluorophore function. The efficient production of intact recombinant proteins in plants may therefore require adequate climate control and shading in greenhouses or even cultivation in fully controlled indoor farms. [ABSTRACT FROM AUTHOR]

The current methodologies used to evaluate environmental similarities do not allow the simultaneous analysis and categorization of the environments. The objective of this study was to verify the possibility of using the Bayesian network (BN) to detect similarities between environments for plant height, lodging, and grain yield in maize. Thirteen experimental varieties were grown in six environments to measure the traits plant height, lodging, and grain yield. The BN was constructed for each trait, using the Hill-Climbing algorithm. Results were compared with the simple part of the genotypes x environments interaction, clustering by the Lin's method and by simple correlation between environments. The Lin's method clustered environments with predominance of complex interaction for all traits. The BN is efficient to analyze environmental similarity for plant height and grain yield since it detected the highest correlations. The BN revealed no connections among the environments that presented predominance of complex interaction. [ABSTRACT FROM AUTHOR]

Background: The longitudinal associations between serum uric acid (UA) levels and metabolic syndrome (MetS) and its components, as well as the shared genetic and environmental correlations between these traits, were evaluated. Participants and Methods: In a total of 1803 participants (675 men and 1128 women; 695 monozygotic twin individuals, 159 dizygotic twin individuals, and 949 non-twin family members; 44.3 ± 12.8 years old) and 321 monozygotic twin pairs with data on UA levels and MetS components at baseline and follow-up, mixed linear model, conditional logistic regression, and bivariate variance component analysis were conducted. Results: After 3.7 ± 1.4 years, the incident and persistent prevalence of MetS were 5.3% and 11.6%, respectively. UA was positively associated with the concurrent and future number of MetS criteria, blood pressure (BP), and triglyceride (TG) levels, whereas an inverse association was observed between UA and future high-density lipoprotein cholesterol (HDL-C) levels after adjusting for twin and household effects, demographics, health behaviors at baseline, and other confounders according to outcome variables. In the adjusted bivariate analysis, UA had genetic and environmental correlations with the concurrent and future number of MetS criteria, and had genetic correlations with concurrent BP and TG levels and future diastolic BP and HDL-C levels. In the adjusted co-twin control analysis, twins with a higher UA level were more likely to have concurrent MetS [odds ratio (95% confidence interval) 1.59 (1.00–2.53)], high blood glucose levels [1.84 (1.06–3.17)], future MetS [2.35 (1.19–4.64)], and high TG levels [1.52 (1.03–2.24)] than co-twins with a lower UA level. Conclusion: Genetic and environmental factors affect the concurrent and longitudinal associations between UA and MetS as well as some of its components. [ABSTRACT FROM AUTHOR]

We aimed to assess shared genetic correlations of depressive and anxiety symptoms with concurrent and future estimated cardiovascular risk (CVR) score in Korean twins and family members. For the relationship with Adult Treatment Panel III CVR estimate in subjects aged 30–74 years (n = 1,059, baseline and follow-up after 3.2 ± 1.2 years), Center for Epidemiological Studies Depression Scale (CES-D) and state and trait anxiety inventory (SAI and TAI) were measured at baseline. A mixed linear model for CVR scores at baseline and follow-up was applied to include depressive and anxiety symptoms, twin and family effects, income, education, alcohol use, exercise, body mass index, and baseline CVR score for follow-up analysis. Higher CES-D scores were associated with higher CVR score at baseline in men, while higher TAI score was associated with higher CVR score at follow-up in women. Heritabilities were 0.245~0.326 for CVR score, 0.320 for CES-D score, 0.367 for TAI score, and 0.482 for SAI score. There were significant common genetic correlations in the relationships of CES-D, TAI, and SAI scores with CVR scores at baseline and follow-up (after adjusting for baseline CV risk score). Shared common environmental correlations were observed in the relationships of CES-D and SAI scores with CVR score at baseline; and SAI score with CVR score at follow-up. In the within-monozygotic twin analysis, there were no associations between CES-D, TAI, and SAI scores, and CVR score. In conclusion, shared genetic and environmental influences were observed in the relationship between depressive and anxiety symptoms with concurrent and future CVR estimates. [ABSTRACT FROM PUBLISHER]

Nosemosis is caused by Nosema spp microsporidium that parasites the midgut of adult worker bees, it is mortal in its acute form and causes very important economic losses for the beekeeper. The knowledge of the infection caused by N. spp in worker bees can help to prevent the spreading or control infection between colonies. The objective of the present work was to determine the presence and intensity of infection of N. spp in worker bees' colonies and its relation with temperature, pluvial precipitation and altitude in this region. Samples of Apis mellifera workers (n=352) were obtained from eight municipalities of south southwest of Jalisco. For the diagnosis, the abdomen tenderize method (Cantwell) was used and the Jaycox method to obtain the number of spores by bee. One hundred percent of the samples resulted positive, and 83.75% of them between 1 to 5 million spores of by bee was presented. Weak correlations were obtained between the intensity of infection with the altitude (r= -0.35), the temperature (r= 0.44) and the pluvial precipitation (r= -0.12), for what can be suggested that these parameters do not majorly influence the presence of the disease. The obtained results suggest that all workers bees' colonies of the sampled municipalities should be treated in a periodic way with antibiotics, or biologic control removing each year older honeycombs in the colonies and the annual change of queens. [ABSTRACT FROM AUTHOR]

Raising the degree of grain filling is an important issue for the genetic improvement of extra-heavy panicle type rice which does not always realize the high yield potential due to low degree of grain filling. The objective of this study was to analyze the variation and association of the traits related to grain filling in four cultivars, three extra-heavy panicle types and one non-extra-heavy panicle type as a control, under seven environments. The results showed wide variation among cultivars and among growing environments in most of the traits examined. In addition, significant interactions between cultivar and environment were detected. From the analyses of joint regression and genetic and environmental correlations, an extra-heavy panicle type cultivar, Milyang 23, showed a higher degree of grain filling and higher rate of grain filling (grain weight/ cumulative temperature), in response to several environments with a higher temperature and longer sunshine hours under which a large amount of photoassimilates would be available to grains. On the contrary, another extra-heavy panicle type cultivar, Akenohoshi, showed a lower rate of grain filling, even under the favorable environments mentioned above, resulting in a lower degree of grain filling. The difference in the rate of grain filling between Milyang 23 and Akenohoshi might be due to the difference in the growth of individual endosperm cells, not in the number of cells, because these two cultivars had similar grain sizes. This study obviously emphasized the importance of high grain sink activity in the genetic improvement of grain filling in extra-heavy panicle type rice.

The regolith is defined as weathered in situ and transported material overlying unweathered bedrock. As fresh bedrock exposures form a small proportion of the landscape, regolith is common in Australia and varies in depth from less than a metre in upland settings to many hundreds of metres (e.g. the Cenozoic Basins). Because of crucial fluxes in gases, water, nutrients, and dissolved salts and variation in permeability and connectivity, knowledge of the nature and depth of regolith is important to many land-based industries, including agriculture and forestry. The minerals industry sees regolith as a barrier to discovery of mineralised rock at depth or as a host of minerals in economic concentrations. There are clearly a range of important characteristics of regolith; depth (and therefore the quantity of regolith) is fundamental for resource inventory and biophysical modelling applications. A method is described that maps the depth of regolith (with estimates of mapping uncertainty) to the moderately weathered/saprock boundary for the whole of Australia. Our approach draws on an extensive legacy of publically available drillhole data (of variable attribute consistency), and applies an environmental correlation-style of digital mapping prediction that utilises relevant spatial covariates, e.g. terrain analysis, climate and gamma radiometric datasets. From the original database of > 350,000 records we filtered and harmonised a useable dataset of 128,000 records. Key predictive datasets used in the depth model included weathering intensity, lithology age, distance to out crop, elevation and relief. Shallowest cover corresponded to high relief erosional landscapes and deepest corresponded to Cenozoic basin sediments. The final map with a ground resolution of approximately 90 m (3 arcsec) was generated using 100 bootstrap model iterations. The reliability of the model was assessed using measures of r-square (0.38), Lin's concordance (0.51), mean error (− 5.73 m) and root mean squared error (24.56 m) calculated on a withheld test dataset. The regolith depth map is consistent with known areas of deep in-situ weathering and accumulation of recent sediment associated with the distribution of Cenozoic Basins and provides a testable estimate in areas with little drilling or survey history. The predictive modelling approach provides a framework to further build and improve regolith depth prediction across varying spatial scales where sufficient quality drillhole data and environmental predictors exist and set priorities for new data acquisition. [ABSTRACT FROM AUTHOR]

We review historical soil maps from a geographical perspective, in contrast to the more traditional temporal–historical perspective. Our geographical approach examines and compares soil maps based on their scale and classification system. To analyze the connection between scale in historical soil maps and their associated classification systems, we place soil maps into three categories of cartographic scale. We then examine how categories of cartographic scale correspond to the selection of environmental soil predictors used to initially create the maps, as reflected by the maps' legend. Previous analyses of soil mapping from the temporal perspective have concluded that soil classification systems have co-evolved with gains in soil knowledge. We conclude that paradigm shifts in soil mapping and classification can be better explained by not only their correlation to historical improvements in scientific understanding, but also by differences in purpose for mapping, and due to advancements in geographic technology. We observe that, throughout history, small cartographic scale maps have tended to emphasize climate–vegetation zonation. Medium cartographic scale maps have put more emphasis on parent material as a variable to explain soil distributions. And finally, soil maps at large cartographic scales have relied more on topography as a predictive factor. Importantly, a key characteristic of modern soil classification systems is their multi-scale approach, which incorporates these phenomena scales within their classification hierarchies. Although most modern soil classification systems are based on soil properties, the soil map remains a model, the purpose of which is to predict the spatial distributions of those properties. Hence, multi-scale classification systems still tend to be organized, at least in part, by this observed spatial hierarchy. Although the hierarchy observed in this study is generally known in pedology today, it also represents a new view on the evolution of soil science. Increased recognition of this hierarchy may also help to more holistically combine soil formation factors with soil geography and pattern, particularly in the context of digital soil mapping. [ABSTRACT FROM AUTHOR]

• Loneliness is a strong risk factor for various health problems. • Personality is useful in understanding why people differ in loneliness. • It is largely unclear why certain personality traits are associated with loneliness. • We found evidence of genetic and environmental influences in the associations. • This may suggest several traits being involved in the development of loneliness. As a strong risk factor for mortality, individual differences in loneliness are of clear public health significance. Four of the Big Five traits have emerged as cross-sectional correlates, but the etiology of these links is unclear, as are relations with more specific personality facets. Thus, we estimated phenotypic, genetic, and environmental associations between loneliness and both broader and narrower personality dimensions. Traits that indexed Negative Emotionality (e.g., Neuroticism, Stress Reactivity, Alienation) and low Positive Emotionality (e.g., low Extraversion, low Well-Being) had the strongest associations with loneliness, though low Conscientiousness, low Agreeableness, and high Aggression were also implicated. These associations were explained by both genetic (0.30 < |r g | < 0.80) and unique environmental (0.10 < |r e | < 0.35) influences, consistent with an etiology of loneliness involving several personality domains. [ABSTRACT FROM AUTHOR]

The Vibrionaceae, which encompasses several potential pathogens, including V. cholerae, the causative agent of cholera, and V. vulnificus, the deadliest seafood-borne pathogen, are a well-studied family of marine bacteria that thrive in a diverse habitats. To elucidate the environmental conditions under which vibrios proliferate, numerous studies have examined correlations with bulk environmental variables – e.g., temperature, salinity, nitrogen and phosphate – and association with potential host organisms. However, how meaningful these environmental associations are remains unclear because data are fragmented across studies with variable sampling and analysis methods. Here, we synthesize findings about Vibrio correlations and physical associations using a framework of increasingly fine environmental and taxonomic scales, to better understand their dynamics in the wild. We first conduct a meta-analysis to determine trends with respect to bulk water environmental variables, and find that while temperature and salinity are generally strongly predictive correlates, other parameters are inconsistent and overall patterns depend on taxonomic resolution. Based on the hypothesis that dynamics may better correlate with more narrowly defined niches, we review evidence for specific association with plants, algae, zooplankton, and animals. We find that Vibrio are attached to many organisms, though evidence for enrichment compared to the water column is often lacking. Additionally, contrary to the notion that they flourish predominantly while attached, Vibrio can have, at least temporarily, a free-living lifestyle and even engage in massive blooms. Fine-scale sampling from the water column has enabled identification of such lifestyle preferences for ecologically cohesive populations, and future efforts will benefit from similar analysis at fine genetic and environmental sampling scales to describe the conditions, habitats, and resources shaping Vibrio dynamics.

Inland excess water hazard was regionalized and digitally mapped using auxiliary spatial environmental information for a county in Eastern Hungary. Quantified parameters representing the effect of soil, geology, groundwater, land use and hydrometeorology on the formulation of inland excess water were defined and spatially explicitly derived. The complex role of relief was characterized using multiple derivatives computed from a DEM. Legacy maps displaying inland excess water events were used as a reference dataset. Regression kriging was applied for spatial inference with the correlation between environmental factors and inundation determined using multiple linear regressions. A stochastic factor derived through kriging the residual was added to the regression results, thus producing the final inundation hazard map. This may be of use for numerous land-related activities. [ABSTRACT FROM AUTHOR]

Tropical Northern Australia is a vast region dominated by extensive cattle grazing. Australia is seeking opportunities to intensify land use in this region through irrigation. We describe a digital soil mapping (DSM) approach for the Flinders and Gilbert catchments (combined area, 155,000 km 2 ) in north Queensland to supply soil property (i.e. target variable) maps for an eventual crop-specific irrigation suitability assessment. We applied a statistically-based survey design to identify new soil sampling sites. This data was merged with legacy soil data to produce a combined dataset of 1951 soil sites used in our DSM approach to map 16 soil target variables. Our mapping relied on the RuleFit3 analytical toolset and environmental correlation employing 13 predictors from terrain analysis, mapping and remote sensing. We present prediction and evaluation for three categories of target variables, namely: numeric, binary and categorical using the examples of surface pH (H 2 O) (numeric), rocky/non-rocky (binary) and permeability (categorical). Prediction quality was evaluated using internal cross-validation, independent validation, and non-parametric bootstrapping. Under internal cross-validation the models achieved R-squared of 0.49 for surface pH (H 2 O) (numerical), 76% classification accuracy for rocky/non-rocky (binary) and 56% classification accuracy for soil permeability (categorical). Under independent validation the target variables achieved a R-squared of 0.67 for surface pH (H 2 O), and accuracy of 93% for rocky/non-rocky accuracy of 63% for soil permeability. Non-parametric bootstrapping conducted on the surface pH (H 2 O) estimation showed the most reliable predictions to be in the pH range of 6–7. Despite the practical pressures imposed on the project (i.e. short project duration, and study area remoteness, size and difficult access), our DSM approach delivered the soil data within required specifications for the crop-specific irrigation suitability assessment. The approach gives a working framework of other soil mapping exercises sharing similar practical (i.e. environmental, logistical, data) constraints. [ABSTRACT FROM AUTHOR]

We examined the involvement of genetic and environmental factors in the variations and associations of the rate and duration of grain filling and the final grain weight in rice cultivars, instead of the simple phenotypic correlation and variance. The estimations were conducted by analyses of variance and covariance in a two-way classification, using ten rice cultivars cultivated under three environments at different locations and years. Also examined were the differences in these parameters for various grain positions on a panicle ; the grains on primary rachis-branches and the grains on secondary rachis-branches. In both grain positions in a panicle, the rate and duration of grain filling differed widely with the environment and cultivar, and showed a very high negative environmental correlation between these two traits. The final grain weight (=filling rate×filling duration) showed a much smaller variation due to environmental fluctuations compared with the rate and duration of filling, which reflects the negatively associated environmental changes in the rate and duration of grain filling. The duration of filling, especially that in the grains on secondary rachis-branches, was more influenced by non-genetic factors than the rate of filling. The genetic correlation between the rate and duration of grain filling was not so high. The final grain weight, on the other hand, was strongly and genetically correlated only with the filling rate, not with the filling duration. This may have resulted from some constraints which do not allow longer filling durations to attain higher final grain weights.

Lodgepole pine ( Pinus contorta var. latifolia) and jack pine ( Pinus banksiana) hybridize in western Canada, an area of recent mountain pine beetle range expansion. Given the heterogeneity of the environment, and indications of local adaptation, there are many unknowns regarding the response of these forests to future outbreaks. To better understand this we aim to identify genetic regions that have adaptive potential., We used data collected on 472 single nucleotide polymorphism ( SNP) loci from 576 tree samples collected across 13 lodgepole pine-dominated sites and four jack pine-dominated sites. We looked at the relationship of genetic diversity with the environment, and we identified candidate loci using both frequency-based ( arlequin and bayescan) and correlation-based ( matsam and bayenv) methods., We found contrasting relationships between environmental variation and genetic diversity for the species. While we identified a number of candidate outliers (34 in lodgepole pine, 25 in jack pine, and 43 interspecific loci), we did not find any loci in common between lodgepole and jack pine. Many of the outlier loci identified were correlated with environmental variation., Using rigorous criteria we have been able to identify potential outlier SNPs. We have also found evidence of contrasting environmental adaptations between lodgepole and jack pine which could have implications for beetle spread risk. [ABSTRACT FROM AUTHOR]

Abstract: Soil mapping is a major goal of soil science. Soil maps rely upon accurate base maps, both for positional reference and to provide environmental data that can assist in the prediction of soil properties. This paper reviews the historical development of base maps used for soil mapping, and evaluates the dependence of soil mapping on base maps. The availability of geographic technology for producing base maps has both constrained and directed the geographic study of soil. The lack of accurate methods for determining location limited early geographic descriptions of soils to narratives, or to listings of attributes for property-based map units. The first real base maps available for soil mapping were outline maps produced in the late 18th century, fueled by governments' interests in documenting national boundaries and popular interest in world atlases. These early soil maps primarily used outline maps as a positional reference onto which soil-related thematic detail was added. Eventually, additional spatial information, in the form of topographic maps and later aerial photographs, increased the predictive role of base maps in soil mapping. In the current digital, geospatial revolution, global positioning systems and geographic information systems have nearly replaced the positional reference function of base maps. Today, base maps are more likely to be used as parameters in soil-landscape models for predicting the spatial distribution of soil properties and classes. Formerly, as a reference for spatial position, paper base maps controlled the cartographic scale of soil maps. However, this relationship is no longer true in geographic information systems. Today, as parameters for digital soil maps, base maps constitute the library of predictive variables and constrain the supported resolution of the soil map. [Copyright &y& Elsevier]

Abstract: In this study, we evaluate the application of a Random Forest (RF) classifier as a tool for understanding and predicting the complex hierarchical relationships between soil parent material and topography using a digital elevation model (DEM) and conventional soil survey maps. Single-component soil polygons from conventional soil survey maps of the Langley–Vancouver Map Area, British Columbia (Canada), were used to generate randomized training points for 9 parent material classes. Each point was intersected with values from 27 topographic indices derived from a 100m DEM. RF's m try parameter was optimized using multiple replicates of 5-fold cross validation and parent material predictions were made for the region. Predictive parent material maps were validated through comparisons with legacy soil survey maps and 307 field points. Results show that predictions made by a non-optimized RF resulted in a kappa index of 89.6% when validated with legacy soil survey data from single-component polygons and a kappa index of 79.5% when validated with field data. Variable reduction and m try optimization resulted in minimal improvements in RF predictions. Our results demonstrate the effectiveness of RF as a machine learning and data mining approach; however, the need for reliable training data was highlighted by less reliable results for polygon disaggregation in portions of the map where fewer training data points could be established. [Copyright &y& Elsevier]

Shallow population structure is generally reported for most marine fish and explained as a consequence of high dispersal, connectivity and large population size. Targeted gene analyses and more recently genome-wide studies have challenged such view, suggesting that adaptive divergence might occur even when neutral markers provide genetic homogeneity across populations. Here, 381 SNPs located in transcribed regions were used to assess large- and fine-scale population structure in the European hake ( Merluccius merluccius), a widely distributed demersal species of high priority for the European fishery. Analysis of 850 individuals from 19 locations across the entire distribution range showed evidence for several outlier loci, with significantly higher resolving power. While 299 putatively neutral SNPs confirmed the genetic break between basins ( FCT = 0.016) and weak differentiation within basins, outlier loci revealed a dramatic divergence between Atlantic and Mediterranean populations ( FCT range 0.275-0.705) and fine-scale significant population structure. Outlier loci separated North Sea and Northern Portugal populations from all other Atlantic samples and revealed a strong differentiation among Western, Central and Eastern Mediterranean geographical samples. Significant correlation of allele frequencies at outlier loci with seawater surface temperature and salinity supported the hypothesis that populations might be adapted to local conditions. Such evidence highlights the importance of integrating information from neutral and adaptive evolutionary patterns towards a better assessment of genetic diversity. Accordingly, the generated outlier SNP data could be used for tackling illegal practices in hake fishing and commercialization as well as to develop explicit spatial models for defining management units and stock boundaries. [ABSTRACT FROM AUTHOR]

Vesicomyid bivalves have a substantial biomass in deep-sea chemosynthetic biological communities in the Pacific. Using a novel multiplex-PCR (mPCR) method to identify the co-occurring vesicomyids in Sagami Bay, we analyzed the distribution of Calyptogena okutanii and Calyptogena soyoae along environmental gradients. All the known distributions of C. okutanii indicated the different preferences in salinity and temperature to those of C. soyoae, and in Sagami Bay, depth seemed to be an important environmental factor, too. Although the concentration of hydrogen sulfide in sediment was not examined, our results showed that the distributions of these two Calyptogena clams were affected by salinity and temperature. [ABSTRACT FROM AUTHOR]

Question Many broad-scale surveys are made, and local communities described, with time spent recording some measure of the abundance of each species. The results are always somewhat different from those obtained with presence/absence records, but which best represents the underlying structure of the community? Two partial answers to this question are suggested and tested here: which analysis correlates best with the habitat, and which gives more stable ordination scores under subsampling? Methods Tests were made on ten field data sets, ranging widely in habitat type, spatial extent, spatial grain and measure of abundance. Correlation with the habitat was examined for the four larger-extent data sets with reasonably complete environmental information, using multiple regression of detrended correspondence analysis ( DCA) ordination scores on environmental factors. Stability was tested for each data set using random subsets of the quadrats, and measuring stability as correlation between quadrat ordination scores in the subset and those using all quadrats. Results Correlation with the habitat for the four data sets, where possible, was closer with presence/absence in most comparisons. Stability was greater with presence/absence in some cases and with abundance in others. Where abundance analyses were more stable, reduction to abundance categories, which are often used in field sampling, resulted in a loss of stability, although in two out of three data sets some advantage of abundance information over presence/absence was retained. Jittering to simulate subjective recording gave no further degradation. Conclusions The data sets in which stability was higher in abundance analyses suggest that abundance is of value only in the rather homogeneous vegetation types that tend to occur over short distances, and with high-quality abundance data. From this, and environmental correlations being on the whole better with presence/absence analyses, I conclude that in broader-scale survey work, abundance information is unnecessary and may even be misleading. It seems that the primary assembly rule control on communities is on the presence of species, not their abundance. [ABSTRACT FROM AUTHOR]

Abstract: The life-history parameters of most living organisms are modified by fluctuations in environmental conditions. The impact of environmental autocorrelation on population persistence is well understood in single species systems. However, in multi-species communities the impact of stochasticity is complicated by the possibility of different species having differing intrinsic responses to the environment (environmental correlation). Previous work has shown that whether increasing between-species environmental correlation stabilises population fluctuations or not, depends on an interaction between density-dependence and environmental autocorrelation. Here we derive analytical conditions for how this interaction in turn depends on the strength of interspecific competition. Under relatively weak between-species interactions, increasing environmental autocorrelation always dampens population fluctuations, while increasing autocorrelation destabilises strongly interacting populations. In contrast, under intermediate interaction strengths, increasing autocorrelation destabilises (stabilises) population dynamics when populations respond independently (similarly) to environmental fluctuations. These results apply to a wide range of competitive communities and also have some relevance to consumer-resource systems. The results presented here help us better understand population responses to environmental fluctuations under different conditions. [Copyright &y& Elsevier]

Abstract: Soil texture is an important soil characteristic that drives crop production and field management, and is the basis for environmental monitoring (including soil quality and sustainability, hydrological and ecological processes, and climate change simulations). The combination of coarse sand, fine sand, silt, and clay in soil determines its textural classification. This study used Geographic Information Systems (GIS) and regression-tree modeling to precisely quantify the relationships between the soil texture fractions and different environmental parameters on a national scale, and to detect the most important parameters that can be used as weighted input data in soil environmental prediction models. Seven primary terrain parameters (elevation, slope gradient, slope aspect, plan curvature, profile curvature, flow direction, flow accumulation) and one compound topographic index (CTI) were generated from a Digital Elevation Model (DEM) acquired using airborne LIDAR (Light Detection and Ranging) systems. They were used along with digital data collected from other sources (existing maps and available pluviometric stations), i.e. parent materials, landscape types, geographic regions, yearly precipitation, seasonal precipitation to statistically explain soil texture fractions field/laboratory measurements (45,224 sampling sites) in the area of interest (Denmark). The developed strongest relationships were associated with clay and silt, variance being equal to 60%, followed by coarse sand (54.5%) and fine sand (52%) as the weakest relationship. This study also showed that parent materials (with a relative importance varying between 47% and 100%), geographic regions (31–100%) and landscape types (68–100%) considerably influenced all soil texture fractions, which is not the case for climate and DEM parameters. Yearly and seasonal precipitation had a significant impact on clay and silt; elevation had higher influence on coarse sand (13%), fine sand (12%) and clay (10%) where; slope gradient influenced silt (11.5%); slope aspect (14%) and CTI (9%) influenced fine sand; and profile/plan curvatures and flow direction/accumulation did not interfere in the building of the soil texture regression trees and associated relationships. The latter can be extrapolated to other areas sharing similar geo-environmental conditions. [Copyright &y& Elsevier]

Soil salinity in the Aral Sea Basin is one of the major limiting factors of sustainable crop production. Leaching of the salts before planting season is usually a prerequisite for crop establishment and predetermined water amounts are applied uniformly to fields often without discerning salinity levels. The use of predetermined water amounts for leaching perhaps partly emanate from the inability of conventional soil salinity surveys (based on collection of soil samples, laboratory analyses) to generate timely and high-resolution salinity maps. This paper has an objective to estimate the spatial distribution of soil salinity based on readily or cheaply obtainable environmental parameters (terrain indices, remote sensing data, distance to drains, and long-term groundwater observation data) using a neural network model. The farm-scale (∼15 km) results were used to upscale soil salinity to a district area (∼300 km). The use of environmental attributes and soil salinity relationships to upscale the spatial distribution of soil salinity from farm to district scale resulted in the estimation of essentially similar average soil salinity values (estimated 0.94 vs. 1.04 dS m). Visual comparison of the maps suggests that the estimated map had soil salinity that was uniform in distribution. The upscaling proved to be satisfactory; depending on critical salinity threshold values, around 70-90% of locations were correctly estimated. [ABSTRACT FROM AUTHOR]

Abstract: Relationships between World Reference Base (WRB) soil groups and the soil forming factors of climate, parent material and topography are examined using the ISRIC WISE Global database (2002 and 2008 versions). For each of 70 different environmental regimes, being combinations of the above three variables, the dominant WRB soil groups were determined and presented with the aid of pie charts. Soil qualifiers associated with the 1988 FAO soil classification scheme are also presented for each regime. Results are brought together into two summary “star charts” that give an overview of the broad distribution patterns of these soil groups relative to the three variables. The charts may provide a useful first approximation of WRB soil groups likely to occur under different environmental conditions and form a basis for regional modelling of WRB soil distribution. They have a potential for widespread application in conventional and possibly also quantitative soil mapping programs as they are based on a global soil database and do not require sophisticated data sources or technologies. Testing with 100 independent samples revealed a moderate predictive success rate, with 58% of test samples matching one of the top three predictions, and 74% matching one of the top five predictions. The charts appear to be effective in suggesting a range of likely WRB soil groups in a given environment, but could not be relied upon to predict a single specific soil group. The World Reference Base for Soil Resources classification scheme is shown to be at least moderately guided by the soil forming factors of climate, parent material and topography. This suggests that genetic factors are an important guiding principle behind the classification scheme. It may represent a scheme with an appropriate balance between soil management and soil genesis factors in its underlying principles. [ABSTRACT FROM AUTHOR]

Abstract: The data quality of soil properties, such as the soil organic matter (SOM) content, can be improved and the spatial sampling intensities may be reduced by incorporating secondary information, such as those derived from topographic (TOPO) and remote sensing (RS) data to enhance their spatial estimates. This study adopted a generic framework for spatial interpolation using regression kriging (RK) developed by Hengl et al. (2004) to evaluate RK''s capability in improving SOM spatial interpolation using internal secondary variables (sampling coordinates) and external auxiliary information, such as soil map (SOIL), vegetation indices (VIs) derived from a Landsat 5 TM image, and several terrain attributes (elevation, slope, convergence and wetness indices, and plan and profile curvatures). Meanwhile, the SOM spatial distribution was also interpolated by using ordinary kriging (OK) and universal kriging (UK) methods for comparison purposes. The results of this study showed that the prediction accuracy of SOM by using RK was unimproved with the inclusion of more auxiliary information in the regression models, but in contrast it significantly declined when TOPO, VI and SOIL information were combined, particularly the last one. It was also observed that with the increase of the minimum sampling distances from 25 to 500m or with the decrease of the sampling densities from 0.42 to 0.26 # km− 2, the RK techniques did not outperform OK and UK in improving the SOM prediction accuracy at coarse sampling resolutions. Interestingly, the highest accuracy of the SOM prediction by all these interpolation methods was achieved at the minimum sampling distance of 250m. The suitability of RK implementation in the spatial interpolation was therefore discussed by considering the minimum sampling distance, the sampling density and the compatibility of spatial resolutions of target variables and auxiliary information or the spatial scales. [Copyright &y& Elsevier]

Abstract: Evolutionary branching has been suggested as a mechanism to explain ecological speciation processes. Recent studies indicate however that demographic stochasticity and environmental fluctuations may prevent branching through stochastic competitive exclusion. Here we extend previous theory in several ways; we use a more mechanistic ecological model, we incorporate environmental fluctuations in a more realistic way and we include environmental autocorrelation in the analysis. We present a single, comprehensible analytical result which summarizes most effects of environmental fluctuations on evolutionary branching driven by resource competition. Corroborating earlier findings, we show that branching may be delayed or impeded if the underlying resources have uncorrelated or negatively correlated responses to environmental fluctuations. There is also a strong impeding effect of positive environmental autocorrelation, which can be related to results from recent experiments on adaptive radiation in bacterial microcosms. In addition, we find that environmental fluctuations can lead to cycles of repeated branching and extinction. [Copyright &y& Elsevier]

Abstract: Leaves are organs sensitive to environmental changes in the process of evolution and may exhibit phenotypic plasticity as a response to abiotic stress. However, affirmation of leaf morphological plasticity and its regulations in different environments are still unclear. We performed a simulated experiment to study the variations of leaf morphology in different gradients of water and light availability. Considering different types of leaves and venation, we chose pinnate-veined simple leaves of Quercus acutissima and compound leaves of Robinia pseudoacacia as the study objects. The morphological parameters we investigated include leaf size, shape and venation pattern which can be easily measured in the field. Significant variations occurred in many parameters due to the effects of the environment and/or allometry. There were broadly consistent trends for leaf morphological variations along the gradients. The leaf size became smaller with a short supply of resources. Leaf elongation and fractions of the lamina area altered to enhance resources acquisition and conservation. Trade-offs between investments in support and functional structures optimized the venation pattern of major and minor veins. Leaflets partially played a role such as leaf teeth, for they are not only individual units, but also a part of the compound leaf. We suggest that more or less the same trends in morphological variations may be an important explanation for coexisting species to adapt to similar habitats and form the niche differentiation. [Copyright &y& Elsevier]

Abstract: The ISRIC WISE Global soil database was used to develop broad quantitative relationships between the environmental factors of climate, parent material and topography and a range of important soil properties (pH, sum of bases, organic carbon, clay content and others). Three different analytical approaches were used in the analysis, involving (i) multiple linear regressions, (ii) fitted decision trees and (iii) categorical analysis with median values. The strengths of the predictive relationships are generally only moderate at best, with R 2 values in the regression relationships typically in the range 0.2 to 0.4 and a wide spread in inter-quartile values in categorical median results. Testing with 100 random samples revealed only broadly moderate accuracy for the soil property predictions, with root mean square error down to 0.84 for pH predictions and down to 2.6 cmolc/kg for sum of bases. Despite their low strengths, the predictive relationships can provide useful first approximations of soil character under different environmental conditions and could be applied in broad quantitative soil modelling and mapping programs. They have the potential for widespread application as they should be universally applicable, are based on readily available data and do not require sophisticated quantitative modelling techniques. The relationships revealed in the study can assist in our understanding of soil formation and soil distribution. Most relationships are in accord with accepted pedological thinking and support the state factor model of soil formation, but some anomalies are observed and deserve further examination. The results reveal the dominant influence of climate and parent material in controlling the distribution of many soil properties, with the influence of topography being less evident, at least at the global scale. [Copyright &y& Elsevier]