Tribute chromite mining and environmental management on the northern Great Dyke of Zimbabwe

A combination of poor mining methods, waste storage and disposal systems, as well as the day-to-day activities associated with tribute and contract chromite mining are primarily responsible for environmental problems on the Zimbabwe Great Dyke. For instance, the unsystematic dumping of waste rocks in rivers blocks channels and results in flooding, which further sterilizes agricultural land and mineral resources. Erosion of these haphazardly located dumps causes siltation of water bodies and results in the dispersion of heavy metals in soils and watercourses. Vegetation growth on waste dumps is limited and constrained by the high pH levels from phytotoxic metals in soils, the lack of nutrients, poor moisture retention qualities of the mining waste and critical cation imbalances within dumps. This article attributes poor environmental management on the Dyke to poverty, a direct result of the nature of tribute agreements and output prices. Prices based on output targets are exploitative and undervalue labour and thus perpetuate poverty. By absolving claim holders from environmental liability, tribute agreements contribute directly to environmental problems. Thus, the incorporation of enforceable dual environmental responsibility requirements in contract mining agreements is needed to overcome this problem. This article recommends that, to break the poverty cycle, the primary cause of environmental mismanagement in the sector, miners need to be empowered through claim ownership and the enhancement of their capacity to negotiate prices with buyers of chrome.     

Interlaboratory evaluation of endotoxin analyses in agricultural dusts--comparison of LAL assay and mass spectrometry

Endotoxin exposure is associated with wheeze and asthma morbidity, while early life exposure may reduce risk of allergy and asthma. Unfortunately, it is difficult to compare endotoxin results from different laboratories and environments. We undertook this study to determine if lipopolysaccharide (LPS) extraction efficiency could account for differences among laboratories. We generated and collected aerosols from chicken and swine barns, and corn processing. We randomly allocated side-by-side filter samples to five laboratories for Limulus assay of endotoxin. Lyophilized aliquots of filter extracts were analyzed for 3-hydroxy fatty acids (3-OHFAs) as a marker of LPS using gas chromatography-mass spectrometry. There were significant differences in endotoxin assay and GC-MS (LPS) results between laboratories for all dust types (p < 0.01). Patterns of differences between labs varied by dust type. Relationships between assay and GC/MS results also depended on dust type. The percentages of individual 3-OHFA chain lengths varied across labs (p < 0.0001) suggesting that each lab recovered a different fraction of the LPS available. The presence of large amounts of particle associated LPS and absence of a freezing thawing cycle were associated with lower correlations between LPS and bioactivity, consistent with an absence of Limulus response to cell-bound endotoxin. These data suggest that extraction methods affect endotoxin measurements. The LAL methods may be most suitable when comparing exposures within similar environments; GC-MS offers additional information helpful in optimizing sample treatment and extraction. GC-MS may be of use when comparing across heterogeneous environments and should be considered for inclusion in future studies of human health outcomes.     

A Watershed-based Cumulative Risk Impact Analysis: Environmental Vulnerability and Impact Criteria

Swine Concentrated Animal Feeding Operations (CAFOs) have received much attention in recent years. As a result, a watershed-based screening tool, the Cumulative Risk Index Analysis (CRIA), was developed to assess the cumulative impacts of multiple CAFO facilities in a watershedsubunit. The CRIA formula calculates an index number based on: 1) the area of one or more facilities compared to the area of the watershed subunit, 2) the average of the environmental vulnerability criteria, and 3) the average of the industry-specific impact criteria. Each vulnerability or impact criterion is ranked on a 1 to 5 scale, with a low rank indicating low environmental vulnerability or impact and a high rank indicating high environmental vulnerability or impact. The individual criterion ranks, as well as the total CRIA score, can be used to focus the environmental analysis and facilitate discussions with industry, public, and other stakeholders in the Agency decision-making process.     

Seven suggestive quantitative trait loci influence hygienic behavior of honey bees

In 1964, Walter Rothenbuhler proposed a two-gene model to explain phenotypic variance in the remarkable behavior in which honey bee workers remove dead brood from their colonies. Rothenbuhler's model proposed that one locus controls the uncapping of brood cells containing dead pupae, while a second controls the removal of the cell contents. We show here, through molecular techniques and quantitative trait loci (QTL) linkage mapping, that the genetic basis of hygienic behavior is more complex, and that many genes are likely to contribute to the behavior. In our cross, we detected seven suggestive QTLs associated with hygienic behavior. Each detected QTL controlled only 9-15% of the observed phenotypic variance in the character.     

Implications of Land Use Changes on Carbon Dynamics and Sequestration—Evaluation from Forestry Datasets, India

Forests and soils are a major sink of carbon, and land use changes can affect the magnitude of above ground and below ground carbon stores and the net flux of carbon between the land and the atmosphere. Studies on methods for examining the future consequences of changes in patterns of land use change and carbon flux gains importance, as they provide different options for CO₂ mitigation strategies. In this study, a simulation approach combining Markov chain processes and carbon pools for forests and soils has been implemented to study the carbon flows over a period of time. Markov chains have been computed by converting the land use change and forestry data of India from 1997 to 1999 into a matrix of conditional probabilities reflecting the changes from one class at time t to another class time t+1. Results from Markov modeling suggested Indian forests as a potential sink for 0.94 Gt carbon, with an increase in dense forest area of about 75.93 Mha and decrease of about 3.4 Mha and 5.0 Mha in open and scrub forests, if similar land use changes that occurred during 1997–1999 would continue. The limiting probabilities suggested 34.27 percent as dense forest, 6.90 as open forest, 0.4 percent mangrove forest, 0.1 percent scrub and 58 percent as non-forest area. Although Indian forests are found to be a potential carbon sink, analysis of results from transition probabilities for different years till 2050 suggests that, the forests will continue to be a source of about 20.59 MtC to the atmosphere. The implications of these results in the context of increasing anthropogenic pressure on open and scrub forests and their contribution to carbon source from land use change and forestry sector are discussed. Some of the mitigation aspects to reduce greenhouse gas emissions from land use change and forestry sector in India are also reviewed in the study.     

REGION,LANDSCAPE, AND SCALE EFFECTS ON LAKE SUPERIOR TRIBUTARY WATER QUALITY1

ABSTRACT: In 1998 and 1999, third‐order watersheds in high mature forest (HMF) and low mature forest (LMF) classes were selected along gradients of watershed storage within each of two hydrogeomorphic regions in the Lake Superior Basin to evaluate threshold effects of storage on hydrologic regimes and watershed exports. Differences were detected between regions (North and South Shore) for particulates, nutrients, and pH, with all but silica values higher for South Shore streams (p < 0.05). Mature forest effects were detected for turbidity, nutrients, color, and alkalinity, with higher values in the LMF watersheds, that is, watersheds with less that 50 percent mature forest cover. Dissolved N, ammonium, N:P, organic carbon, and color increased, while suspended solids, turbidity, and dissolved P decreased as a function of storage. Few two‐way interactions were detected between region and mature forest or watershed storage, thus threshold based classification schemes could be used to extrapolate effects across regions. Both regional differences in water quality and those associated with watershed attributes were more common for third‐order streams in the western Lake Superior drainage basin as compared with second‐order streams examined in an earlier study. Use of ecoregions alone as a basis for setting regional water quality criteria would have led to misinterpretation of reference condition and assessment of impacts in the Northern Lakes and Forest Ecoregion.     

The acetochlor registration partnership surface water monitoring program for four corn herbicides

A surface drinking water monitoring program for four corn (Zea mays L.) herbicides was conducted during 1995-2001. Stratified random sampling was used to select 175 community water systems (CWSs) within a 12-state area, with an emphasis on the most vulnerable sites, based on corn intensity and watershed size. Finished drinking water was monitored at all sites, and raw water was monitored at many sites using activated carbon, which was shown capable of removing herbicides and their degradates from drinking water. Samples were collected biweekly from mid-March through the end of August, and twice during the off-season. The analytical method had a detection limit of 0.05 microg L(-1) for alachlor [2-chloro-N-(2,6-diethylphenyl)-N-(methoxymethyl)-acetamide] and 0.03 microg L(-1) for acetochlor [2-chloro-N-(ethoxymethyl)-N-(2-ethyl-6-methylphenyl)-acetamide], atrazine [6-chloro-N-ethyl-N'-(1-methylethyl)-1,3,5-triazine-2,4-diamine], and metolachlor [2-chloro-N-(2-ethyl-6-methylphenyl)-N-(2-methoxy-1-methylethyl)-acetamide]. Of the 16528 drinking water samples analyzed, acetochlor, alachlor, atrazine, and metolachlor were detected in 19, 7, 87, and 53% of the samples, respectively. During 1999-2001, samples were also analyzed for the presence of six major degradates of the chloroacetanilide herbicides, which were detected more frequently than their parent compounds, despite having higher detection limits of 0.1 to 0.2 microg L(-1). Overall detection frequencies were correlated with product use and environmental fate characteristics. Reservoirs were particularly vulnerable to atrazine, which exceeded its 3 microg L(-1) maximum contaminant level at 25 such sites during 1995-1999. Acetochlor annualized mean concentrations (AMCs) did not exceed its mitigation trigger (2 microg L(-1)) at any site, and comparisons of observed levels with standard measures of human and ecological hazards indicate that it poses no significant risk to human health or the environment.     

Soil C and N models that integrate microbial diversity

Industrial agriculture is yearly responsible for the loss of 55–100 Pg of historical soil carbon and 9.9 Tg of reactive nitrogen worldwide. Therefore, management practices should be adapted to preserve ecological processes and reduce inputs and environmental impacts. In particular, the management of soil organic matter (SOM) is a key factor influencing C and N cycles. Soil microorganisms play a central role in SOM dynamics. For instance, microbial diversity may explain up to 77 % of carbon mineralisation activities. However, soil microbial diversity is actually rarely taken into account in models of C and N dynamics. Here, we review the influence of microbial diversity on C and N dynamics, and the integration of microbial diversity in soil C and N models. We found that a gain of microbial richness and evenness enhances soil C and N dynamics on the average, though the improvement of C and N dynamics depends on the composition of microbial community. We reviewed 50 models integrating soil microbial diversity. More than 90 % of models integrate microbial diversity with discrete compartments representing conceptual functional groups (64 %) or identified taxonomic groups interacting in a food web (28 %). Half of the models have not been tested against an empirical dataset while the other half mainly consider fixed parameters. This is due to the difficulty to link taxonomic and functional diversity.