A social–ecological analysis of ecosystem services in two different farming systems

In this exploratory study we use existing in situ qualitative and quantitative data on biophysical and social indicators to compare two contrasting Swedish farming systems (low intensity and high intensity) with regard to ecosystem service supply and demand of a broad suite of services. We show that the value (demand) placed on a service is not necessarily connected to the quantity (supply) of the service, most clearly shown for the services recreation, biodiversity, esthetic experience, identity, and cultural heritage. To better capture this complexity we argue for the need to develop portfolios of indicators for different ecosystem services and to further investigate the different aspects of supply and demand. The study indicates that available data are often ill-suited to answer questions about local delivery of services. If ecosystem services are to be included in policy, planning, and management, census data need to be formatted and scaled appropriately.     

Baselines for land-use change in the tropics: application to avoided deforestation projects

Although forest conservation activities, particularly in the tropics, offer significant potential for mitigating carbon (C) emissions, these types of activities have faced obstacles in the policy arena caused by the difficulty in determining key elements of the project cycle, particularly the baseline. A baseline for forest conservation has two main components: the projected land-use change and the corresponding carbon stocks in applicable pools in vegetation and soil, with land-use change being the most difficult to address analytically. In this paper we focus on developing and comparing three models, ranging from relatively simple extrapolations of past trends in land use based on simple drivers such as population growth to more complex extrapolations of past trends using spatially explicit models of land-use change driven by biophysical and socioeconomic factors. The three models used for making baseline projections of tropical deforestation at the regional scale are: the Forest Area Change (FAC) model, the Land Use and Carbon Sequestration (LUCS) model, and the Geographical Modeling (GEOMOD) model. The models were used to project deforestation in six tropical regions that featured different ecological and socioeconomic conditions, population dynamics, and uses of the land: (1) northern Belize; (2) Santa Cruz State, Bolivia; (3) Paraná State, Brazil; (4) Campeche, Mexico; (5) Chiapas, Mexico; and (6) Michoacán, Mexico. A comparison of all model outputs across all six regions shows that each model produced quite different deforestation baselines. In general, the simplest FAC model, applied at the national administrative-unit scale, projected the highest amount of forest loss (four out of six regions) and the LUCS model the least amount of loss (four out of five regions). Based on simulations of GEOMOD, we found that readily observable physical and biological factors as well as distance to areas of past disturbance were each about twice as important as either sociological/demographic or economic/infrastructure factors (less observable) in explaining empirical land-use patterns. We propose from the lessons learned, a methodology comprised of three main steps and six tasks can be used to begin developing credible baselines. We also propose that the baselines be projected over a 10-year period because, although projections beyond 10 years are feasible, they are likely to be unrealistic for policy purposes. In the first step, an historic land-use change and deforestation estimate is made by determining the analytic domain (size of the region relative to the size of proposed project), obtaining historic data, analyzing candidate baseline drivers, and identifying three to four major drivers. In the second step, a baseline of where deforestation is likely to occur–a potential land-use change (PLUC) map—is produced using a spatial model such as GEOMOD that uses the key drivers from step one. Then rates of deforestation are projected over a 10-year baseline period based on one of the three models. Using the PLUC maps, projected rates of deforestation, and carbon stock estimates, baseline projections are developed that can be used for project GHG accounting and crediting purposes: The final step proposes that, at agreed interval (e.g., about 10 years), the baseline assumptions about baseline drivers be re-assessed. This step reviews the viability of the 10-year baseline in light of changes in one or more key baseline drivers (e.g., new roads, new communities, new protected area, etc.). The potential land-use change map and estimates of rates of deforestation could be re-done at the agreed interval, allowing the deforestation rates and changes in spatial drivers to be incorporated into a defense of the existing baseline, or the derivation of a new baseline projection.     

Ozone exposure among Mexico City outdoor workers

In researching health effects of air pollution, pollutant levels from fixed-site monitors are commonly assigned to the subjects. However, these concentrations may not reflect the exposure these individuals actually experience. A previous study of ozone (O3) exposure and lung function among shoe-cleaners working in central Mexico City used fixed-site measurements from a monitoring station near the outdoor work sites as surrogates for personal exposure. The present study assesses the degree to which these estimates represented individual exposures. In 1996, personal O3 exposures of 39 shoe-cleaners working outdoors were measured using an active integrated personal sampler. Using mixed models, we assessed the relationship between measured personal O3 exposure and ambient O3 measurements from the fixed-site monitoring station. Ambient concentrations were approximately 50 parts per billion higher, on average, than personal exposures. The association between personal and ambient O3 was highly significant (mixed model slope p < 0.0001). The personal/ambient ratio was not constant, so use of the outdoor monitor would not be appropriate to rank O3 exposure and evaluate health effects between workers. However, the strong within-worker longitudinal association validates previous findings associating day-to-day changes in fixed-site O3 levels with adverse health effects among these shoe-cleaners and suggests fixed-site O3 monitors may adequately estimate exposure for other repeated-measure health studies of outdoor workers.     

Manganese uptake and accumulation by the hyperaccumulator plant Phytolacca acinosa Roxb. (Phytolaccaceae)

The perennial herb Phytolacca acinosa Roxb. (Phytolaccaceae), which occurs in Southern China, has been found to be a new manganese hyperaccumulator by means of field surveys on Mn-rich soils and by glasshouse experiments. This species not only has remarkable tolerance to Mn but also has extraordinary uptake and accumulation capacity for this element. The maximum Mn concentration in the leaf dry matter was 19,300 microg/g on Xiangtan Mn tailings wastelands, with a mean of 14,480 microg/g. Under nutrient solution culture conditions, P. acinosa could grow normally with Mn supplied at a concentration of 8000 micromol/l, although with less biomass than in control samples supplied with Mn at 5 micromol/l. Manganese concentration in the shoots increased with increasing external Mn levels, but the total mass of Mn accumulated in the shoots first increased and then decreased. At an Mn concentration of 5000 micromol/l in the culture solution, the Mn accumulation in the shoot dry matter was highest (258 mg/plant). However, the Mn concentration in the leaves reached its highest value (36,380 microg/g) at an Mn supply level of 12,000 micromol/l. These results confirm that P. acinosa is an Mn hyperaccumulator which grows rapidly, has substantial biomass, wide distribution and a broad ecological amplitude. This species provides a new plant resource for exploring the mechanism of Mn hyperaccumulation, and has potential for use in the phytoremediation of Mn-contaminated soils.     

Using thermal units for estimating critical period of weed competition in off-season maize crop

Brazilian off-season maize production is characterized by low yield due to several factors, such as climate variability and inadequate management practices, specifically weed management. Thus, the goal of this study was to determinate the critical period of weed competition in off-season maize (Zea mays L.) crop using thermal units or growing degree days (GDD) approach to characterize crop growth and development. The study was carried out in experimental area of the University of S?o Paulo, Brazil, with weed control (C), as well as seven coexistence periods, 2, 4, 6, 8, and 12 leaves, flowering, and all crop cycle; fourteen treatments were done. Climate data were obtained from a weather station located close to the experimental area. To determine the critical period for weed control (CPWC) logistic models were fitted to yield data obtained in both W and C, as a function of GDD. For an arbitrary maximum yield loss fixed in 2.5%, the CPWC was found between 301 and 484 GDD (7-8 leaves). Also, when the arbitrary loss yield was fixed in 5 and 10%, the period before interference (PBI) was higher than the critical weed-free period (CWFP), suggesting that the weeds control can be done with only one application, between 144 and 410 GDD and 131 and 444 GDD (3-8 leaves), respectively. The GDD approach to characterize crop growth and development was successfully used to determine the critical period of weeds control in maize sown off-season. Further works will be necessary to better characterize the interaction and complexity of maize sown off-season with weeds. However, these results are encouraging because the possibility of the results to be extrapolated and because the potential of the method on providing important results to researchers, specifically crop modelers.     

Enhancing bioremediation of diesel oil and gasoline in soil amended with an agroindustry sludge

This paper presents a study of the bioremediation of diesel oil and gasoline by a series of controlled laboratory tests. Sludge from an agroindustry was used to enhance bioremediation of both gasoline and diesel oil mixed with a soil mass to compare its efficiency with that of a mineral fertilizer. Effects of soil microbiology and soil mixtures were investigated by means of evolution of CO2, microorganism populations at 90 days, pH at 65 and 95 days, mineral nitrogen, and gas chromatographic analysis of the benzene, toluene, methyl tertiary butyl ether, C8, and C9+total aromatics at the end of the experiments. Treatments containing sludge showed better soil conditions after 170 days of treatment (inorganic nitrogen and microbiota activity) compared with gasoline and diesel oil without amendments. Samples had no detectable traces of the measured hydrocarbons at 170 days of treatment.