Human Impacts on Land Cover and Water Balances in a Coastal Mediterranean County

We analyzed the effects of changes in land cover on the water balance in Spain’s Marina Baixa County, on the Mediterranean coast. To reveal how different land management strategies have affected the area’s environment, four municipalities within the same catchment were studied: Benidorm, Callosa d’en Sarrià, Beniardà, and Guadalest. In the municipalities of Callosa and Benidorm, the proportion of the area covered by woodland declined by 4.2% and 30.2%, respectively, and woodland was replaced by agriculture and urban development. The abandonment of farmland produced a 17% increase in the proportion of the area covered by vegetation in Guadalest and Beniardá, where frequent forest fires have exacerbated a decrease in the area of pine woodland. Tourism development in Benidorm has been accompanied by an increase in the transportation infrastructure and by an expansion of areas with an impermeable surface, with the lowest level of infiltration into the aquifer system. These changes have generated a net water deficit in Callosa and Benidorm of more than 6 Mm³/year, creating a high demand for water imported from other municipalities (Guadalest and Beniardá) or from outside of the county to maintain the sustainability of the current water management strategies. The Marina Baixa case study is representative of many of the world’s coastal areas that are undergoing rapid urban development based on an inappropriate understanding of human progress based mainly on economic development and thus provides insights into water management in other areas.     

Summer cover crops reduce atrazine leaching to shallow groundwater in southern Florida

At Florida's southeastern tip, sweet corn (Zea Mays) is grown commercially during winter months. Most fields are treated with atrazine (6-chloro-N-ethyl-N'-[1-methylethyl]-1,3,5-triazine-2,4-diamine). Hydrogeologic conditions indicate a potential for shallow groundwater contamination. This was investigated by measuring the parent compound and three degradates--DEA (6-chloro-N-[1-methylethyl]-1,3,5-triazine-2,4-diamine), DIA (6-chloro-N-ethyl)-1,3,5-triazine-2,4-diamine, and HA (6-hydroxy-N-[1-methylethyl]-1,3,5-triazine-2,4-diamine)--in water samples collected beneath sweet corn plots treated annually with the herbicide. During the study, a potential mitigation measure (i.e., the use of a cover crop, Sunn Hemp [Crotalaria juncea L.], during summer fallow periods followed by chopping and turning the crop into soil before planting the next crop) was evaluated. Over 3.5 yr and production of four corn crops, groundwater monitoring indicated leaching of atrazine, DIA, and DEA, with DEA accounting for more than half of all residues in most samples. Predominance of DEA, which increased after the second atrazine application, was interpreted as an indication of rapid and extensive atrazine degradation in soil and indicated that an adapted community of atrazine degrading organisms had developed. A companion laboratory study found a sixfold increase in atrazine degradation rate in soil after three applications. Groundwater data also revealed that atrazine and degradates concentrations were significantly lower in samples collected beneath cover crop plots when compared with concentrations below fallow plots. Together, these findings demonstrated a relatively small although potentially significant risk for leaching of atrazine and its dealkylated degradates to groundwater and that the use of a cover crop like Sunn Hemp during summer months may be an effective mitigation measure.     

Soil carbon storage in silvopasture and related land-use systems in the brazilian cerrado

Silvopastoral management of fast-growing tree plantations is becoming popular in the Brazilian Cerrado (savanna). To understand the influence of such systems on soil carbon (C) storage, we studied C content in three aggregate size classes in six land-use systems (LUS) on Oxisols in Minas Gerais, Brazil. The systems were a native forest, a treeless pasture, 24- and 4-yr-old eucalyptus ( sp.) plantations, and 15- and 4-yr-old silvopastures of fodder grass plus animals under eucalyptus. From each system, replicated soil samples were collected from four depths (0-10, 10-20, 20-50, and 50-100 cm), fractionated into 2000- to 250-, 250- to 53-, and <53-μm size classes representing macroaggregates, microaggregates, and silt + clay, respectively, and their C contents determined. Macroaggregate was the predominant size fraction under all LUS, especially in the surface soil layers of tree-based systems. In general, C concentrations (g kg soil) in the different aggregate size fractions did not vary within the same depth. The soil organic carbon (SOC) stock (Mg C ha) to 1-m depth was highest under pasture compared with other LUS owing to its higher soil bulk density. The soils under all LUS had higher C stock compared with other reported values for managed tropical ecosystems: down to 1 m, total SOC stock values ranged from 461 Mg ha under pasture to 393 Mg ha under old eucalyptus. Considering the possibility for formation and retention of microaggregates within macroggregates in low management-intensive systems such as silvopasture, the macroaggregate dynamics in the soil seem to be a good indicator of its C storage potential.     

A strong test of a maximum entropy model of trait-based community assembly

We evaluate the predictive power and generality of Shipley's maximum entropy (maxent) model of community assembly in the context of 96 quadrats over a 120-km2 area having a large (79) species pool and strong gradients. Quadrats were sampled in the herbaceous understory of ponderosa pine forests in the Coconino National Forest, Arizona, U.S.A. The maxent model accurately predicted species relative abundances when observed community-weighted mean trait values were used as model constraints. Although only 53% of the variation in observed relative abundances was associated with a combination of 12 environmental variables, the maxent model based only on the environmental variables provided highly significant predictive ability, accounting for 72% of the variation that was possible given these environmental variables. This predictive ability largely surpassed that of nonmetric multidimensional scaling (NMDS) or detrended correspondence analysis (DCA) ordinations. Using cross-validation with 1000 independent runs, the median correlation between observed and predicted relative abundances was 0.560 (the 2.5% and 97.5% quantiles were 0.045 and 0.825). The qualitative predictions of the model were also noteworthy: dominant species were correctly identified in 53% of the quadrats, 83% of rare species were correctly predicted to have a relative abundance of < 0.05, and the median predicted relative abundance of species actually absent from a quadrat was 5 x 10(-5).     

Modelling spatial and temporal variability in a zero-inflated variable: The case of stone pine (Pinus pinea L.) cone production

Modelling masting habit, i.e. the spatial synchronized annual variability in fruit production, is a huge task due to two main circumstances: (1) the identification of main ecological factors controlling fruiting processes, and (2) the common departure of fruit data series from the main basic statistical assumptions of normality and independence. Stone pine (Pinus pinea L.) is one of the main species in the Mediterranean basin that is able to grow under hard limiting conditions (sandy soils and extreme continental climate), and typically defined as a masting species. Considering the high economical value associated with edible nut production, the masting habit of stone pine has been a main concern for the forest management of the species. In the present work we have used annual fruit data series from 740 stone pine trees measured during a 13 years period (1996-2008) in order: (a) to verify our main hypothesis pointing out to the existence of a weather control of the fruiting process in limiting environments, rather than resource depletion or endogenous inherent cycles; (b) to identify those site factors, stand attributes and climate events affecting specific traits involved in fruiting process; and (c) to construct a model for predicting spatial and temporal patterns of variability in stone pine cone production at different spatial extents as region, stand and tree. Given the nature of the data, the model has been formulated as zero-inflated log-normal, incorporating random components to carry out with the observed lack of independence. This model attains efficiencies close to 70-80% in predicting temporal and spatial variability at regional scale. Though efficiencies are reduced according to the spatial extent of the model, it leads to unbiased estimates and efficiencies over 35-50% when predicting annual yields at tree or stand scale, respectively. In this sense, the proposed model is a main tool for facilitating decision making in some management aspects such as the quantification of total amount of cones annually supplied to nut industry, design of cone harvest programs or the optimal application of seedling felling.     

Influence of particle size on the physico-mechanical and energy properties of briquettes produced with coffee husks

Environmental Science and Pollution Research - Briquetting is a technology with the potential to convert agricultural wastes into solid biofuels with improved handling, transport, storage, and...     

Effects of lead exposure on salivary glands of rats: insights into the oxidative biochemistry and glandular morphology

Environmental Science and Pollution Research - This study aimed to investigate the effects of lead (Pb) exposure on parotid and submandibular glands through morphological aspects as well as the...     

Commercially available garden products as important sources of antibiotic resistance genes—a survey

Environmental Science and Pollution Research - The dissemination of antibiotic resistance genes (ARGs) in the environment contributes to the global rise in antibiotic resistant infections....     

Occupational safety and health in Spain

Occupational Health and Safety in Spain has improved considerably over the last decade, most likely due to a new concept where an overall concept of safety culture is defined. Important changes in industrial safety, hygiene, and psychosocial factors present an optimistic panorama for the future of Spain. Despite this general improvement, according to the European Convergence Program, Spanish statistics still offer far from good safety results. In fact, according to 1997 official statistics, Spain had the highest incidence rate for nonfatal occupational accidents of all European Union (EU) countries, and occupied third place for fatal accidents. This paper summarizes the organizational structure of the Spanish National System of Health & Safety at Work, its effective health and safety laws, and statistics on the Spanish work environment obtained from III Spanish National Survey on Work Conditions (1997). The researchers hope that the findings of this work will have an impact on Spanish industry that will subsequently bring about improvements in work conditions and develop assessment and intervention models in occupational health and safety, from a theoretical position integrating environmental, human, and organizational factors.