Dynamics of leaf litter and soil respiration in a complex multistrata agroforestry system,Pernambuco, Brazil

High litter inputs in agroforestry systems contribute to soil microbial activity, soil fertility and productivity. Considering that the cycling of organic matter is essential to the maintenance of physical–chemical and microbiological properties of the soil, the aims of this work were to estimate the production, accumulation and decomposition of litter, and assess soil microbial respiration in a complex multistrata agroforestry system located in the north-east of Brazil. This agroforestry system has three strata formed by forest and fruit trees and species of multiple uses. During 3 years (2011–2013), leaf litter was sampled monthly to account for litterfall and quarterly to account for litter accumulation. The rates of litter decomposition were estimated using the ratio produced-to-accumulated litter, and the correlation between litter fall and rainfall was calculated. Precipitation data were provided by the water and climate agency of Pernambuco (APAC). Soil samples (0–15 cm) were also taken quarterly, simultaneously with the litter accumulation samples, and soil microbial respiration was assessed using the capture, by a KOH solution, of the evolved CO₂. The annual production of leaf litter was stable in the 3 years of study in this agroforestry system, and the monthly input of litter to the soil was influenced by rainfall, being higher in the dry seasons. The accumulated litter on the ground was constant, as was microbial activity (respiration) through time. The estimated litter decomposition rates were 1.49 (first year), 1.33 (second year) and 1.42 (third year), being considered rapid rates of decomposition. This guarantees (to the farmer) that this system is capable of maintaining soil fertility and eliminates the need for chemical fertilizers.     

Composition and quantification of the anthropogenic and natural fractions of wastes collected from the stormwater drainage system for discussions about the waste management and people behavior

A study was made of the composition of wastes collected from the pipes of the stormwater drainage system of Sorocaba, SP, Brazil (600 thousand inhabitants). A total of 10 samples weighing at least 100 kg each were sorted into 19 items to determine the fraction that can be considered natural (earth/sand, stones, organic matter, and water, the latter determined after oven-drying the samples) and the anthropogenic fraction (the remaining 15 items, especially construction and demolition wastes and packaging). Soil/sand was found to be the main item collected (52.5 % dry weight), followed by the water soaked into the waste (24.3 %), which meant that all the other wastes were saturated in mud, whose contents varied from 6.4 % (glass) to 87.2 % (metalized plastics packaging). In general, 83 % of the collected wastes can be classified as “natural,” but the remaining 17 % represent 2,000 kg of the most varied types of wastes discarded improperly every day on the streets of the city. This is an alarming amount of wastes that may clog parts of the drainage systems, causing troubles for all the population (like flooding) and must be strongly considered in municipal solid wastes management and in environmental education programs.     

Pathways of rural change: an integrated assessment of metabolic patterns in emerging ruralities

While rural transformations are nothing new in human history, current processes of rural change occur under multiple forces at an unprecedented pace, involving profound and unexpected changes in land use and users, and rapid transformations in the metabolic patterns of rural systems. The present special section aims to shed light on current drivers and pathways of rural change by analyzing, under a common conceptual and theoretical framework, examples of new ruralities that are emerging as responses across different world regions. Within this context, this introduction presents: (1) common research questions of the six presented cases of rural change; (2) the general theoretical and methodological framework of integrated assessment of societal metabolism adopted to analyze rural systems and (3) the main contributions and conclusions that could be drawn from six context-specific case studies from Asia, Latin America and Europe.     

Beyond selectivity: Are behavioral avoidance and hormesis likely causes of pyrethroid-induced outbreaks of the southern red mite Oligonychus ilicis?

Secondary pest outbreak is a counterintuitive ecological backlash of pesticide use in agriculture that takes place with the increase in abundance of a non-targeted pest species after pesticide application against a targeted pest species. Although the phenomenon was well recognized, its alternative causes are seldom considered. Outbreaks of the southern red mite Oligonychus ilicis are frequently reported in Brazilian coffee farms after the application of pyrethroid insecticides against the coffee leaf miner Leucoptera coffeella. Selectivity favoring the red mite against its main predatory mites is generally assumed as the outbreak cause, but this theory has never been tested. Here, we assessed the toxicity (and thus the selectivity) of deltamethrin against both mite species: the southern red mite and its phytoseid predator Amblyseius herbicolus. Additionally, behavioral avoidance and deltamethrin-induced hormesis were also tested as potential causes of red mite outbreak using free-choice behavioral walking bioassays with the predatory mite and life-table experiments with both mite species, respectively. Lethal toxicity bioassays indicated that the predatory mite was slightly more susceptible than its prey (1.5×), but in more robust demographic bioassays, the predator was three times more tolerant to deltamethrin than its prey, indicating that predator susceptibility to deltamethrin is not a cause of the reported outbreaks. The predator did not exhibit behavioral avoidance to deltamethrin; however insecticide-induced hormesis in the red mite led to its high population increase under low doses, which was not observed for the predatory mite. Therefore, deltamethrin-induced hormesis is a likely cause of the reported red mite outbreaks.     

Organochlorine compounds in bovine milk from the state of Mato Grosso do Sul – Brazil

Organochlorines are highly hydrophobic, synthetic organic pollutants that accumulate in the environment and in food webs. The primary route of human exposure to organochlorines is through food-mainly fat-rich food of animal origin such as meat, fish, and dairy products. Here we determined the presence and concentration of organochlorine residues in pasteurized milk from Mato Grosso do Sul, Brazil, to monitor consumer exposure to these contaminants. Organochlorine pesticides in milk samples were analyzed using solid phase extraction in octadecyl silica-prepacked columns and identified by gas chromatography using an electron capture detector. Of the 100 composite samples analyzed, more than 90% contained residues of organochlorine pesticides: aldrin was present in 44% of the samples, followed by ∑DDT (36%), mirex (34%), endosulfan (32%), chlordane (17%), dicofol (14%), heptachlor (11%) and dieldrin (11%). Compared to the values established by law, the concentration of the compounds in some samples was above the reference values. Given the importance that milk and its products have in the human diet, it is essential to know whether the levels of pesticide residues are kept well below the recommended levels to minimize the risk to human health.     

Nonparametric functional data estimation applied to ozone data: prediction and extreme value analysis

The study of extreme values and prediction of ozone data is an important topic of research when dealing with environmental problems. Classical extreme value theory is usually used in air-pollution studies. It consists in fitting a parametric generalised extreme value (GEV) distribution to a data set of extreme values, and using the estimated distribution to compute return levels and other quantities of interest. Here, we propose to estimate these values using nonparametric functional data methods. Functional data analysis is a relatively new statistical methodology that generally deals with data consisting of curves or multi-dimensional variables. In this paper, we use this technique, jointly with nonparametric curve estimation, to provide alternatives to the usual parametric statistical tools. The nonparametric estimators are applied to real samples of maximum ozone values obtained from several monitoring stations belonging to the Automatic Urban and Rural Network (AURN) in the UK. The results show that nonparametric estimators work satisfactorily, outperforming the behaviour of classical parametric estimators. Functional data analysis is also used to predict stratospheric ozone concentrations. We show an application, using the data set of mean monthly ozone concentrations in Arosa, Switzerland, and the results are compared with those obtained by classical time series (ARIMA) analysis.     

Looking beyond the average agricultural impacts in defining adaptation needs in Europe

The effects of climate change on agriculture are often characterised by changes in the average productivity of crops; however, these indicators provide limited information regarding the risks associated with fluctuations in productivity resulting from future changes in climate variability that may also affect agriculture. In this context, this study evaluates the combined effects of the risks associated with anomalies reflected by changes in the mean crop yield and the variability of productivity in European agro-climatic regions under future climate change scenarios. The objective of this study is to evaluate adaptation needs and to identify regional effects that should be addressed with greater urgency in the light of the risks and opportunities that are identified. The results show differential effects on regional agriculture and highlight the importance of considering both regional average impacts and the variability in crop productivity in setting priorities for the adaptation and maintenance of rural incomes and agricultural insurance programmes.     

Agricultural adjustment,population dynamics and forests redistribution in a subtropical watershed of NW Argentina

Patterns of land-use and land-cover change are usually grouped into one of two categories defined by the dominant trend: (1) deforestation resulting from expanding agriculture and (2) forest expansion, usually related to the abandonment of marginal lands. At regional scale, however, both processes can occur simultaneously even in the absence of net change. Given the focus on net change, such redistribution of agricultural and natural and seminatural lands has been generally overlooked. The interaction between agriculture modernization, human demography and complex topographic gradients of northwestern Argentina has resulted in processes of both forest recovery and deforestation, thus providing the opportunity to analyze patterns and driving forces of land-cover redistribution. We analyzed 20 years (1986–2006) of land-cover change in a subtropical watershed in relation to topographic and demographic variables. Although net forest change represented <1 %, forests redistribution affected 7 % of forest lands. There was a consistent geographic segregation of deforestation and forest recovery, with forests expanding over steep highlands and agriculture expanding over lowland irrigated areas. Population trends were not associated to forest expansion in lowlands but they explained 32 % of forest recovery in highlands. Highland forest expansion and lowland deforestation, respectively, imply conservation opportunities for humid montane forests and the environmental services they provide (e.g., watershed conservation) and threats for the conservation of dry forests and its biodiversity. Our study exemplifies the importance of land-use redistribution (rather than net change) with relevant environmental consequences at regional scale.     

Integrated hydrologic–economic decision support system for groundwater use confronting climate change uncertainties in the Tunuyán River basin,Argentina

This study presents an integrated hydrologic–economic model as decision support system for groundwater use and incorporates uncertainties of climate change. The model was developed with the Vensim software (Ventana Systems) for system dynamic simulations. The software permitted the integration of economic variables along with hydrologic variables, in a unified format with the aim of evaluating the economic impacts of climate change on arid environments. To test the model, we applied it in one of the upper Tunuyán River sub-basin, located in the Mendoza Province (Argentina), where irrigation comes from groundwater. The model defines the best mix of crops and the total land use required to maximize the total river sub-basin monetary income, considering as a limit the amount of water that does not exceed the natural annual aquifer recharge. To estimate the impacts of climatic changes, four scenarios were compared: the business as usual (with the number of existing wells) in a dry year with a temperature increase of 4 °C; the business as usual in a wet year with an increase in temperature of 1.1 °C; an efficient use of wells in a dry year and a temperature increase of 4 °C and an efficient use of wells in a wet year with a temperature increase of 1.1 °C. Outputs calculated by the model were: land use per crop, total sub-basin net benefit, total sub-basin water extraction, water extraction limit depending on river discharge and total number of wells required to irrigate the entire area. Preliminary results showed that the number of existing wells exceeded the optimized number of wells required to sustainably irrigate the entire river sub-basin. Results indicated that in an average river discharge year, if wells were efficiently used, further rural development would be possible, until the limit of 350 million m³ of water extraction per year was reached (650 million m³ for a wet year and 180 million m³ for a dry year). The unified format and the low cost of the software license make the model a useful tool for Water Resources Management Institutions, particularly in developing countries.