912 resultados para Soil environmental factors.
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Aim The aim of this study was to explore the environmental factors that determine the spatial distribution of oro-mediterranean and alti-mediterranean plant communities in Crete. Location The paper provides a quantitative analysis of vegetation-environment relationships for two study areas within the Lefka Ori massif Crete, a proposed Natura 2000 site. Methods Eleven environmental variables were recorded: altitude, slope, aspect, percentage of bare rock, percentage of unvegetated ground, soil depth, pH, organic matter content and percentages of sand, silt and clay content. Classification of the vegetation was based on twinspan, while detrended correspondence analysis (DCA) and canonical correspondence analysis (CCA) were used to identify environmental gradients linked to community distribution. Results One hundred and twenty-five species were recorded from 120 plots located within the two study areas. Forty-seven of the recorded species are endemic, belonging to 35 families. Hemicryptophytes and chamaephytes were the most frequent, suggesting a typical oro-mediterranean life form spectrum. The samples were classified into five main community types and one transitional. The main gradients, identified by CCA, were altitude and surface cover type in the North-west site, while in the Central site the gradients were soil formation-development and surface cover type. Main conclusions The use of classification in combination with ordination techniques resulted in a good discrimination between plant communities and a greater understanding of controlling environmental factors. The methodology adopted can be employed for improving baseline information on plant community ecology and distribution in Mediterranean mountain zones.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Root herbivores are important ecosystem drivers and agricultural pests, and, possibly as a consequence, plants protect their roots using a variety of defensive strategies. One aspect that distinguishes belowground from aboveground plant–insect interactions is that roots are constantly exposed to a set of soil-specific abiotic factors. These factors can profoundly influence root resistance, and, consequently, the outcome of the interaction with belowground feeders. In this review, we synthesize the current literature on the impact of soil moisture, nutrients, and texture on root–herbivore interactions. We show that soil abiotic factors influence the interaction by modulating herbivore abundance and behaviour, root growth and resistance, beneficial microorganisms, as well as natural enemies of the herbivores. We suggest that abiotic heterogeneity may explain the high variability that is often encountered in root–herbivore systems. We also propose that under abiotic stress, the relative fitness value of the roots and the potential negative impact of herbivory increases, which may lead to a higher defensive investment and an increased recruitment of beneficial microorganisms by the plant. At the same time, both root-feeding herbivores and natural enemies are likely to decrease in abundance under extreme environmental conditions, leading to a context- and species-specific impact on plant fitness. Only by using tightly controlled experiments that include soil abiotic heterogeneity will it be possible to understand the impact of root feeders on an ecosystem scale and to develop predictive models for pest occurrence and impact.
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Quercus robur L. (pedunculate oak) and Quercus petraea (Matt.) Liebl. (sessile oak) are two European oak species of great economic and ecological importance. Even though both oaks have wide ecological amplitudes of suitable growing conditions, forests dominated by oaks often fail to regenerate naturally. The regeneration performance of both oak species is assumed to be subject to a variety of variables that interact with one another in complex ways. The novel approach of this research was to study the effect of many ecological variables on the regeneration performance of both oak species together and identify key variables and interactions for different development stages of the oak regeneration on a large scale in the field. For this purpose, overstory and regeneration inventories were conducted in oak dominated forests throughout southern Germany and paired with data on browsing, soil, and light availability. The study was able to verify the assumption that the occurrence of oak regeneration depends on a set of variables and their interactions. Specifically, combinations of site and stand specific variables such as light availability, soil pH and iron content on the one hand, and basal area and species composition of the overstory on the other hand. Also browsing pressure was related to oak abundance. The results also show that the importance of variables and their combinations differs among the development stages of the regeneration. Light availability becomes more important during later development stages, whereas the number of oaks in the overstory is important during early development stages. We conclude that successful natural oak regeneration is more likely to be achieved on sites with lower fertility and requires constantly controlling overstory density. Initially sufficient mature oaks in the overstory should be ensured. In later stages, overstory density should be reduced continuously to meet the increasing light demand of oak seedlings and saplings.
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We used geographic information systems and a spatial analysis approach to explore the pattern of Ross River virus (RRV) incidence in Brisbane, Australia. Climate, vegetation and socioeconomic data in 2001 were obtained from the Australian Bureau of Meteorology, the Brisbane City Council and the Australian Bureau of Statistics, respectively. Information on the RRV cases was obtained from the Queensland Department of Health. Spatial and multiple negative binomial regression models were used to identify the socioeconomic and environmental determinants of RRV transmission. The results show that RRV activity was primarily concentrated in the northeastern, northwestern, and southeastern regions in Brisbane. Multiple negative binomial regression models showed that the spatial pattern of RRV disease in Brisbane seemed to be determined by a combination of local ecologic, socioeconomic, and environmental factors.
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Background: The seasonality of suicide has long been recognised. However, little is known about the relative importance of socio-environmental factors in the occurrence of suicide in different geographical areas. This study examined the association of climate, socioeconomic and demographic factors with suicide in Queensland, Australia, using a spatiotemporal approach. Methods: Seasonal data on suicide, demographic variables and socioeconomic indexes for areas in each Local Government Area (LGA) between 1999 and 2003 were acquired from the Australian Bureau of Statistics. Climate data were supplied by the Australian Bureau of Meteorology. A multivariable generalized estimating equation model was used to examine the impact of socio-environmental factors on suicide. Results: The preliminary data analyses show that far north Queensland had the highest suicide incidence (e.g., Cook and Mornington Shires), while the south-western areas had the lowest incidence (e.g., Barcoo and Bauhinia Shires) in all the seasons. Maximum temperature, unemployment rate, the proportion of Indigenous population and the proportion of population with low individual income were statistically significantly and positively associated with suicide. There were weaker but not significant associations for other variables. Conclusions: Maximum temperature, the proportion of Indigenous population and unemployment rate appeared to be major determinants of suicide at a LGA level in Queensland.
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Suicide has drawn much attention from both the scientific community and the public. Examining the impact of socio-environmental factors on suicide is essential in developing suicide prevention strategies and interventions, because it will provide health authorities with important information for their decision-making. However, previous studies did not examine the impact of socio-environmental factors on suicide using a spatial analysis approach. The purpose of this study was to identify the patterns of suicide and to examine how socio-environmental factors impact on suicide over time and space at the Local Governmental Area (LGA) level in Queensland. The suicide data between 1999 and 2003 were collected from the Australian Bureau of Statistics (ABS). Socio-environmental variables at the LGA level included climate (rainfall, maximum and minimum temperature), Socioeconomic Indexes for Areas (SEIFA) and demographic variables (proportion of Indigenous population, unemployment rate, proportion of population with low income and low education level). Climate data were obtained from Australian Bureau of Meteorology. SEIFA and demographic variables were acquired from ABS. A series of statistical and geographical information system (GIS) approaches were applied in the analysis. This study included two stages. The first stage used average annual data to view the spatial pattern of suicide and to examine the association between socio-environmental factors and suicide over space. The second stage examined the spatiotemporal pattern of suicide and assessed the socio-environmental determinants of suicide, using more detailed seasonal data. In this research, 2,445 suicide cases were included, with 1,957 males (80.0%) and 488 females (20.0%). In the first stage, we examined the spatial pattern and the determinants of suicide using 5-year aggregated data. Spearman correlations were used to assess associations between variables. Then a Poisson regression model was applied in the multivariable analysis, as the occurrence of suicide is a small probability event and this model fitted the data quite well. Suicide mortality varied across LGAs and was associated with a range of socio-environmental factors. The multivariable analysis showed that maximum temperature was significantly and positively associated with male suicide (relative risk [RR] = 1.03, 95% CI: 1.00 to 1.07). Higher proportion of Indigenous population was accompanied with more suicide in male population (male: RR = 1.02, 95% CI: 1.01 to 1.03). There was a positive association between unemployment rate and suicide in both genders (male: RR = 1.04, 95% CI: 1.02 to 1.06; female: RR = 1.07, 95% CI: 1.00 to 1.16). No significant association was observed for rainfall, minimum temperature, SEIFA, proportion of population with low individual income and low educational attainment. In the second stage of this study, we undertook a preliminary spatiotemporal analysis of suicide using seasonal data. Firstly, we assessed the interrelations between variables. Secondly, a generalised estimating equations (GEE) model was used to examine the socio-environmental impact on suicide over time and space, as this model is well suited to analyze repeated longitudinal data (e.g., seasonal suicide mortality in a certain LGA) and it fitted the data better than other models (e.g., Poisson model). The suicide pattern varied with season and LGA. The north of Queensland had the highest suicide mortality rate in all the seasons, while there was no suicide case occurred in the southwest. Northwest had consistently higher suicide mortality in spring, autumn and winter. In other areas, suicide mortality varied between seasons. This analysis showed that maximum temperature was positively associated with suicide among male population (RR = 1.24, 95% CI: 1.04 to 1.47) and total population (RR = 1.15, 95% CI: 1.00 to 1.32). Higher proportion of Indigenous population was accompanied with more suicide among total population (RR = 1.16, 95% CI: 1.13 to 1.19) and by gender (male: RR = 1.07, 95% CI: 1.01 to 1.13; female: RR = 1.23, 95% CI: 1.03 to 1.48). Unemployment rate was positively associated with total (RR = 1.40, 95% CI: 1.24 to 1.59) and female (RR=1.09, 95% CI: 1.01 to 1.18) suicide. There was also a positive association between proportion of population with low individual income and suicide in total (RR = 1.28, 95% CI: 1.10 to 1.48) and male (RR = 1.45, 95% CI: 1.23 to 1.72) population. Rainfall was only positively associated with suicide in total population (RR = 1.11, 95% CI: 1.04 to 1.19). There was no significant association for rainfall, minimum temperature, SEIFA, proportion of population with low educational attainment. The second stage is the extension of the first stage. Different spatial scales of dataset were used between the two stages (i.e., mean yearly data in the first stage, and seasonal data in the second stage), but the results are generally consistent with each other. Compared with other studies, this research explored the variety of the impact of a wide range of socio-environmental factors on suicide in different geographical units. Maximum temperature, proportion of Indigenous population, unemployment rate and proportion of population with low individual income were among the major determinants of suicide in Queensland. However, the influence from other factors (e.g. socio-culture background, alcohol and drug use) influencing suicide cannot be ignored. An in-depth understanding of these factors is vital in planning and implementing suicide prevention strategies. Five recommendations for future research are derived from this study: (1) It is vital to acquire detailed personal information on each suicide case and relevant information among the population in assessing the key socio-environmental determinants of suicide; (2) Bayesian model could be applied to compare mortality rates and their socio-environmental determinants across LGAs in future research; (3) In the LGAs with warm weather, high proportion of Indigenous population and/or unemployment rate, concerted efforts need to be made to control and prevent suicide and other mental health problems; (4) The current surveillance, forecasting and early warning system needs to be strengthened, to trace the climate and socioeconomic change over time and space and its impact on population health; (5) It is necessary to evaluate and improve the facilities of mental health care, psychological consultation, suicide prevention and control programs; especially in the areas with low socio-economic status, high unemployment rate, extreme weather events and natural disasters.
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Background: Initiatives to promote utility cycling in countries like Australia and the US, which have low rates of utility cycling, may be more effective if they first target recreational cyclists. This study aimed to describe patterns of utility cycling and examine its correlates, among cyclists in Queensland, Australia. Methods: An online survey was administered to adult members of a state-based cycling community and advocacy group (n=1813). The survey asked about demographic characteristics and cycling behavior, motivators and constraints. Utility cycling patterns were described, and logistic regression modeling was used to examine associations between utility cycling and other variables. Results: Forty-seven percent of respondents reported utility cycling: most did so to commute (86%). Most journeys (83%) were >5 km. Being male, younger, employed full-time, or university-educated increased the likelihood of utility cycling (p<0.05). Perceiving cycling to be a cheap or a convenient form of transport were associated with utility cycling (p<0.05). Conclusions: The moderate rate of utility cycling among recreational cyclists highlights a potential to promote utility cycling among this group. To increase utility cycling, strategies should target female and older recreational cyclists and focus on making cycling a cheap and convenient mode of transport.
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This study examined whether physical, social, cultural and economical environmental factors are associated with obesogenic dietary behaviours and overweight/obesity among adults. Literature searches of databases (i.e. PubMed, CSA Illumina, Web of Science, PsychInfo) identified studies examining environmental factors and the consumption of energy, fat, fibre, fruit, vegetables, sugar-sweetened drinks, meal patterns and weight status. Twenty-eight studies were in-scope, the majority (n= 16) were conducted in the USA. Weight status was consistently associated with the food environment; greater accessibility to supermarkets or less access to takeaway outlets were associated with a lower BMI or prevalence of overweight/obesity. However, obesogenic dietary behaviours did not mirror these associations; mixed associations were found between the environment and obesogenic dietary behaviours. Living in a socioeconomically-deprived area was the only environmental factor consistently associated with a number of obesogenic dietary behaviours. Associations between the environment and weight status are more consistent than that seen between the environment and dietary behaviours. The environment may play an important role in the development of overweight/obesity, however the dietary mechanisms that contribute to this remain unclear and the physical activity environment may also play an important role in weight gain, overweight and obesity.
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This exploratory enquiry employs qualitative methods to advance knowledge and understanding of physical environmental attributes related to active living among residents of Australian retirement villages. Six focus groups (n = 51 residents) were held and participants described how their current, and subsequently ideal, retirement village and neighborhood supported active lifestyles. Thematic analysis revealed three key environmental factors associated with active living: a positive social environment within the village; services and facilities provided in the village and wider neighborhood; and the presence of suitable pedestrian infrastructure. The unique discovery that environmental factors of both the retirement village and the surrounding neighborhood were associated with residents’ active living raises many questions for study. Findings informed the development of a survey instrument, and further understanding in this area has the potential to contribute to the design and siting practices of senior housing complexes within neighborhoods.
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The collection of basic environmental data by industry members was successful and offers a way of overcoming the problems associated with differences in scale between the environment and fisheries datasets. A simple method of collecting environmental data was developed that was only a small time burden on skippers, yet has the potential to provide very useful information on the same scale as the catch and effort data recorded in the logbooks. The success of this trial was aided by the natural interest of fishers to learn more about the environment in which they fish. The archival temperature-depth tags chosen proved robust, reliable and easy to use. While the use of large scale environmental data may not yield significant improvements in stock assessments for most SESSF species, fine-scale data collected from selected vessels using methods developed during this project may, in the longer term, be useful for incorporation into CPUE standardisations in the future...
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Japanese encephalitis (JE) is the most common cause of viral encephalitis and an important public health concern in the Asia-Pacific region, particularly in China where 50% of global cases are notified. To explore the association between environmental factors and human JE cases and identify the high risk areas for JE transmission in China, we used annual notified data on JE cases at the center of administrative township and environmental variables with a pixel resolution of 1 km×1 km from 2005 to 2011 to construct models using ecological niche modeling (ENM) approaches based on maximum entropy. These models were then validated by overlaying reported human JE case localities from 2006 to 2012 onto each prediction map. ENMs had good discriminatory ability with the area under the curve (AUC) of the receiver operating curve (ROC) of 0.82-0.91, and low extrinsic omission rate of 5.44-7.42%. Resulting maps showed JE being presented extensively throughout southwestern and central China, with local spatial variations in probability influenced by minimum temperatures, human population density, mean temperatures, and elevation, with contribution of 17.94%-38.37%, 15.47%-21.82%, 3.86%-21.22%, and 12.05%-16.02%, respectively. Approximately 60% of JE cases occurred in predicted high risk areas, which covered less than 6% of areas in mainland China. Our findings will help inform optimal geographical allocation of the limited resources available for JE prevention and control in China, find hidden high-risk areas, and increase the effectiveness of public health interventions against JE transmission.