Perceptions about switchgrass and land allocation decisions: Evidence from a farmer survey in Missouri
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Optimizing hydropower operations to balance economic profitability and support functioning ecosystem services is integral to river management policy. In this article, we propose a dynamic, constrained optimization framework for small hydropower plants (SHPs) to evaluate trade-offs between economic profitability and socio-ecological requirements. Specifically, we examine the balance between short-term losses in hydropower generation and the potential for compensatory benefits in the form of revenue from recreational ecosystem services, irrespective of the direct beneficiary. Our framework integrates a fish habitat model, a hydropower optimization model, and a recreational ecosystem service estimate to evaluate different environmental flow scenarios. The optimization process gives three outflow release scenarios, informed by previous streamflow realisations (dam inflow), and designed environmental flow constraints. The framework is applied and tested for the river Kuusinkijoki in North-eastern Finland, which is a habitat for migratory brown trout and grayling populations. We show that the revenue loss due to the environmental flow constraints arises through a reduction in revenue per generated energy unit and through a reduction in turbine efficiency. Additionally, the simulation results reveal that all the designed environmental flow constraints cannot be met simultaneously. Under the environmental flow scenario with both minimum flow and flow ramping rate constraints, the annual hydropower revenue decreases by 16.5 %. An annual increase of 8 % in recreational fishing visits offsets the revenue loss. In conclusion, the developed framework provides knowledge of the costs and benefits of hydropower environmental flow constraints and guides the prioritizing process of environmental measures.
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Plant roots and the organisms that surround them are a primary source for stabilized soil organic carbon (SOC). While grassland soils have a large capacity to store organic carbon (C), few field-based studies have quantified the amount of plant-fixed C that moves into soil and persists belowground over multiple years. Yet this characteristic of the soil C cycle is critical to C storage, soil water holding capacity, nutrient provisions, and the management of soil health. Here, we tracked the fate of plant-fixed C following a five-day 13 CO 2 labeling of a Northern California annual grassland, measuring C pools starting at the end of the labeling period, at three days, four weeks, six months, one year, and two years. Soil organic carbon was fractionated using a density-based approach to separate the free-light fraction (FLF), occluded-light fraction (OLF), and heavy fraction (HF). Using isotope ratio mass spectrometry, we measured 13 C enrichment and total C content for plant shoots, roots, soil, soil dissolved organic carbon (DOC), and the FLF, OLF, and HF. The chemical nature of C in the HF was further analyzed by solid state 13 C nuclear magnetic resonance (NMR) spectroscopy.
Series flexible AC transmission systems devices, such as the variable series reactor, have the ability to continuously regulate the transmission line reactance so as to control power flow. This study presents a new approach to optimally locating such devices in the transmission network considering multiple operating states and contingencies. To investigate optimal investment, a single target year planning with three different load patterns is considered. The transmission contingencies may occur under any of the three load conditions and the coupling constraints between base case and contingencies are included. A reformulation technique transforms the original mixed integer non‐linear programming model into mixed integer linear programming model. To further relieve the computational burden and enable the planning model to be directly applied to practical large‐scale systems, a two‐phase decomposition algorithm is introduced. Detailed numerical simulation results on IEEE 118‐bus system and the Polish 2383‐bus system illustrate the efficient performance of the proposed algorithm.
The behavior of below-gap luminescence of undoped GaN grown by MOCVD has been studied by the scheme of two-wavelength-excited photoluminescence. The emission intensity of shallow donor to valence band transition (I{sub OX}) increased while intensities of donor-acceptor pair transition and the Yellow Luminescence band (YLB) decreased after the irradiation of a below-gap excitation source of 1.17 eV. The conventional energy schemes and recombination models have been considered to explain our experimental result but only one model in which YLB is the transition of a shallow donor to a deep state placed at ∼1 eV above the valence band maximum satisfies our result. The defect related parameters that give a qualitative insight in the samples have been evaluated by systematically solving the rate equations and fitting the result with the experiment.
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In the large LHC experiments the majority of computing resources are provided by the participating countries. These resource pledges account for more than three quarters of the total available computing. The experiments are asked to give indications of their requests three years in advance and to evolve these as the details and constraints become clearer. In this paper we will discuss the resource planning techniques used in CMS to predict the computing resources several years in advance. We will discuss how we attempt to implement the activities of the computing model in spread-sheets and formulas to calculate the needs. We will talk about how those needs are reflected in the 2012 running and how the planned long shutdown of the LHC in 2013 and 2014 impacts the planning process and the outcome. In the end we will speculate on the computing needs in the second major run of LHC.
Here, High Energy Physics (HEP) is a very data intensive and trivially parallelizable science discipline. HEP is probing nature at increasingly finer details requiring ever increasing computational resources to process and analyze experimental data. In this paper, we discuss how HEP provisioned resources so far using Grid technologies, how HEP is starting to include new resource providers like commercial Clouds and HPC installations, and how HEP is transparently provisioning resources at these diverse providers.
The higher energy and luminosity from the LHC in Run2 has put increased pressure on CMS computing resources. Extrapolating to even higher luminosities (and thus higher event complexities and trigger rates) in Run3 and beyond, it becomes clear the current model of CMS computing alone will not scale accordingly. High Performance Computing (HPC) facilities, widely used in scientific computing outside of HEP, present a (at least so far) largely untapped computing resource for CMS. Even just being able use a small fraction of HPC facilities computing resources could significantly increase the overall computing available to CMS. Here we describe the CMS strategy for integrating HPC resources into CMS computing, the unique challenges these facilities present, and how we plan on overcoming these challenges. We also present the current status of ongoing CMS efforts at HPC sites such as NERSC (Cori cluster), SDSC (Comet cluster) and TACC (Stampede cluster).
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The ability of terrestrial vegetation to both take up and release carbon and water makes understanding climate change effects on plant function critical. These effects could alter the impacts and feedbacks of vegetation on climate and either slow down or accelerate climatic warming (Bonan 2008). In conclusion, studies on plant responses to increased atmospheric CO 2 concentration and elevated temperatures have become abundant in the last 20 years (for reviews, see Way and Oren 2010, Franks et al. 2013).
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