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We investigated how a community of microbial decomposers adapted to a reference site responds to a sudden decrease in the water quality. For that, we assessed the activity and diversity of fungi and bacteria on decomposing leaves that were transplanted from a reference (E1) to a polluted site (E2), and results were compared to those from decomposing leaves either at E1 or E2. The two sites had contrasting concentrations of organic and inorganic nutrients and heavy metals in the stream water. At E2, leaf decomposition rates, fungal biomass, and sporulation were reduced, while bacterial biomass was stimulated. Fungal diversity was four times lower at the polluted site. The structure of fungal community on leaves decomposing at E2 significantly differed from that decomposing at E1, as indicated by the principal response curves analysis. Articulospora tetracladia, Anguillospora filiformis, and Lunulospora curvula were dominant species on leaves decomposing at E1 and were the most negatively affected by the transfer to the polluted site. The transfer of leaves colonized at the reference site to the polluted site reduced fungal diversity and sporulation but not fungal biomass and leaf decomposition. Overall, results suggest that the high diversity on leaves from the upstream site might have mitigated the impact of anthropogenic stress on microbial decomposition of leaves transplanted to the polluted site.

Rosana G. Moreira, Editor-in-Chief; Texas A&M University ; TECHNICAL ARTICLES: (1) P. Bruscoli, E. Bresci and F. Preti. Diagnostic Analysis of an Irrigation System in the Andes Region. Vol. III, February 2001. (2) T. Fischer, M. Gaderer, P. Lamp, W. Schoelkopf, and R. Ziegler. Processes and Economics for Energetic Use of Cotton Plant Residues. Vol. III, February 2001. (3) B. G. Kakou, H. Shimizu and S. Nishimura. Residual Strength of Colluvium and Stability Analysis of Farmland slope. Vol. III, March 2001. (4) P. N. Rodrigues, L. S. Pereira, A. Zairi, H. El Amami, H. A. Slatni, J. L. Teixeira, and T. Machado. Deficit Irrigation of Cereals and Horticultural Crops: Simulation of Strategies to Cope with Droughts. Vol. III, March 2001. (5) H. El Amami, A. Zairi, L. S. Pereira, T. Machado, A. Slatni, and P. Rodrigues. Deficit Irrigation of Cereals and Horticultural Crops: Economic Analysis. Vol. III, March 2001. (6) T. Tomson and A. Nova. Geographically Dispersed Wind Turbines on the West-Estonian Coast. Vol. III, April 2001. (7) L. Wiset, G. Srzednicki, R. Driscoll, C. Nimmuntavin, and P. Siwapornak. Effects of High Temperature Drying on Rice Quality. Vol. III, May 2001. (8) M. Horynski. The Effects of Field Intensity and Pneumatic Pressure on the Dielectric Constant of Rye Kernels. Vol. III, May 2001. (9) S. Lynikiene. Carrot Seed Preparation in a Corona Discharge Field. Vol. III, July 2001. (10) V. Anbumozhi, K. Matsumoto, and E. Yamaji. Sustaining Agriculture through Modernization of Irrigation Tanks: An Opportunity and a Challenge for Tamilnadu, India. Vol. III, August 2001. (11) A. Munack, O. Schroeder, J. Krahl, and J. Buenger. Comparison of Relevant Exhaust Gas Emissions from Biodiesel and Fossil Diesel Fuel. Vol. III, August 2001. (12) K. Maertens, M. Reyniers, and J. De Baerdemaeker. Design of a Dynamic Grain Flow Model for a Combine Harvester. Vol. III, September 2001. (13) D. Shitanda, Y. Nishiyama, and S. Koide. Performance Analysis of Impellor and Rubber Roll Husker Using Different Varieties of ...

Abstract The growth and development of maize (Zea mays L.) largely depends on its nutrient uptake through the root. Hence, studying its growth, response, and associated metabolic reprogramming to stress conditions is becoming an important research direction. A genome-scale metabolic model (GSM) for the maize root was developed to study its metabolic reprogramming under nitrogen stress conditions. The model was reconstructed based on the available information from KEGG, UniProt, and MaizeCyc. Transcriptomics data derived from the roots of hydroponically grown maize plants were used to incorporate regulatory constraints in the model and simulate nitrogen-non-limiting (N+) and nitrogen-deficient (N−) condition. Model-predicted flux-sum variability analysis achieved 70% accuracy compared with the experimental change of metabolite levels. In addition to predicting important metabolic reprogramming in central carbon, fatty acid, amino acid, and other secondary metabolism, maize root GSM predicted several metabolites (l-methionine, l-asparagine, l-lysine, cholesterol, and l-pipecolate) playing a regulatory role in the root biomass growth. Furthermore, this study revealed eight phosphatidylcholine and phosphatidylglycerol metabolites which, even though not coupled with biomass production, played a key role in the increased biomass production under N-deficient conditions. Overall, the omics-integrated GSM provides a promising tool to facilitate stress condition analysis for maize root and engineer better stress-tolerant maize genotypes.

AbstractIn Laurentian Great Lakes coastal wetlands (GLCWs), dominant emergent invasive plants are expanding their ranges and compromising the unique habitat and ecosystem service values that these ecosystems provide. Herbiciding and burning to control invasive plants have not been effective in part because neither strategy addresses the most common root cause of invasion, nutrient enrichment. Mechanical harvesting is an alternative approach that removes tissue‐bound phosphorus and nitrogen and can increase wetland plant diversity and aquatic connectivity between wetland and lacustrine systems. In this study, we used data from three years of Great Lakes‐wide wetland plant surveys, published literature, and bioenergy analyses to quantify the overall areal extent of GLCWs, the extent and biomass of the three most dominant invasive plants, the pools of nitrogen and phosphorus contained within their biomass, and the potential for harvesting this biomass to remediate nutrient runoff and produce renewable energy. Of the approximately 212,000 ha of GLCWs, three invasive plants (invasive cattail, common reed, and reed canary grass) dominated 76,825 ha (36%). The coastal wetlands of Lake Ontario exhibited the highest proportion of invasive dominance (57%) of any of the Great Lakes, primarily from cattail. A single growing season's biomass of these invasive plants across all GLCWs was estimated at 659,545 metric tons: 163,228 metric tons of reed canary grass, 270,474 metric tons of common reed, and 225,843 metric tons of invasive cattail, and estimated to contain 10,805 and 1144 metric tons of nitrogen and phosphorus, respectively. A one‐time harvest and utilization for energy of this biomass would provide the gross equivalent of 1.8 million barrels of oil if combusted, or 0.9 million barrels of oil if converted to biogas in an anaerobic digester. We discuss the potential for mitigating non‐point source nutrient pollution with invasive wetland plant removal, and other potential uses for the harvested biomass, including compost and direct application to agricultural soils. Finally, we describe the research and adaptive management program we have built around this concept, and point to current limitations to the implementation of large‐scale invasive plant harvesting.

Natural ecosystems benefit human communities by providing ecosystem services such as water purification and crop pollination. Mapping ecosystem service values has become popular, but most are static snapshots of average value. Estimating instead the economic impacts of specific ecosystem changes can better inform typical resource decisions. Here we develop an approach to mapping marginal values, those resulting from the next unit of ecosystem change, across landscapes. We demonstrate the approach with a recent model of crop pollination services in Costa Rica, simulating deforestation events to predict resulting marginal changes in pollination services to coffee farms. We find that marginal losses from deforestation vary from zero to US$700/ha across the landscape. Financial risks for farmers from these losses and marginal benefits of forest restoration show similar spatial variation. Marginal values are concentrated in relatively few forest parcels not identified using average value. These parcels lack substitutes: nearby forest parcels that can supply services in the event of loss. Indeed, the marginal value of forest parcels declines exponentially with the density of surrounding forest cover. The approach we develop is applicable to any ecosystem service. Combined with information on costs, it can help target conservation or restoration efforts to optimize benefits to people and biodiversity.

Salt marsh vegetation density varies considerably on short spatial scales, complicating attempts to evaluate plant characteristics using airborne remote sensing approaches. In this study, we used a mast-mounted hyperspectral imaging system to obtain cm-scale imagery of a salt marsh chronosequence on Hog Island, VA, where the morphology and biomass of the dominant plant species, Spartina alterniflora, varies widely. The high-resolution hyperspectral imagery allowed the detailed delineation of variations in above-ground biomass, which we retrieved from the imagery using the PROSAIL radiative transfer model. The retrieved biomass estimates correlated well with contemporaneously collected in situ biomass ground truth data ( R 2 = 0.73 ). In this study, we also rescaled our hyperspectral imagery and retrieved PROSAIL salt marsh biomass to determine the applicability of the method across spatial scales. Histograms of retrieved biomass changed considerably in characteristic marsh regions as the spatial scale of the imagery was progressively degraded. This rescaling revealed a loss of spatial detail and a shift in the mean retrieved biomass. This shift is indicative of the loss of accuracy that may occur when scaling up through a simple averaging approach that does not account for the detail found in the landscape at the natural scale of variation of the salt marsh system. This illustrated the importance of developing methodologies to appropriately scale results from very fine scale resolution up to the more coarse-scale resolutions commonly obtained in airborne and satellite remote sensing.

Darfur farming and pastoralist livelihoods are both adaptations to the environmental variability that characterises the region. This article describes this adaptation and the longer‐term transformation of these specialised livelihoods from the perspective of local communities. Over several decades farmers and herders have experienced a continuous stream of climate, conflict and other shocks, which, combined with wider processes of change, have transformed livelihoods and undermined livelihood institutions. Their well‐rehearsed specialist strategies are now combined with new strategies to cope. These responses help people get by in the short term but risk antagonising not only their specialist strategies but also those of others. A combination of factors has undermined the former integration between farming and pastoralism and their livelihood institutions. Efforts to build resilience in similar contexts must take a long‐term view of livelihood adaptation as a specialisation, and consider the implications of new strategies for the continuity and integration of livelihood specialisations.

Catalytic conversion of biomass-derived oxygenates to fuels and value-added chemicals is a promising strategy in the search for renewable and sustainable energy sources. Most relevant catalytic processes are carried out in an aqueous environment using supported transition metal catalysts. The reaction network consists of multiple series and parallel pathways leading to formation of hydrogen, alkanes, and lighter oxygenates. The final product distribution ultimately depends on the sequence and competition of C−C, C−O, C−H, and O−H bonds scissions. Ethylene glycol (EG) is the simplest model molecule of various biomass-derived polyols that has a C:O stoichiometry of 1:1 and contains all relevant C−C, C−O, C−H, and O−H bonds. While the reaction mechanism of EG reforming is to some degree understood at the metal–gas interface, lack of a well-established methodology for describing the influence of a complex liquid phase on a reaction across a solid–liquid interface has hindered similar theoretical studies in an aqueous environment. In this dissertation, we show how first-principles calculations can be used for a systematic investigation of complex reaction pathways at a metal–water interface. We proposed a multistep strategy where the description of the influence of an aqueous environment on reaction kinetics and equilibria is successively refined. First, we developed a new computational approach for implicit solvation of periodic metal slabs by integrating planewave density functional theory (DFT) calculations with an implicit solvation model. Rapid convergence with size of the metal cluster and basis set was demonstrated for C−C cleavage in dehydrogenated EG at a Pt (111)/H2O interface. The method was then successfully applied for predicting experimentally reported CO frequency shifts in water at Pt (111)/H2O and Pd (111)/H2O interfaces. Next, we developed a hybrid quantum mechanics/molecular mechanics (QM/MM) method to allow an explicit description of water molecules at the metal–water interface, and applied it to ...