| Home | << 1 2 3 4 5 6 7 8 9 10 >> [11–14] |
|
Jing, Q., Bélanger, G., Baron, V., Bonesmo, H., Virkajärvi, P., & Young, D. (2012). Regrowth simulation of the perennial grass timothy. Ecol. Model., 232, 64–77.
Abstract: Several process-based models for simulating the growth of perennial grasses have been developed but few include the simulation of regrowth. The model CATIMO simulates the primary growth of timothy (Phleum pratense L), an important perennial forage grass species in northern regions of Europe and North America. Our objective was to further develop the model CATIMO to simulate timothy regrowth using the concept of reserve-dependent growth. The performance of this modified CATIMO model in simulating leaf area index (LAI), biomass dry matter (DM) yield, and N uptake of regrowth was assessed with data from four independent field experiments in Norway, Finland, and western and eastern Canada using an approach that combines graphical comparison and statistical analysis. Biomass DM yield and N uptake of regrowth were predicted at the same accuracy as primary growth with linear regression coefficients of determination between measured and simulated values greater than 0.79, model simulation efficiencies greater than 0.78, and normalized root mean square errors (14-30% for biomass and 24-34% for N uptake) comparable with the coefficients of variation of measured data (1-21% for biomass and 1-25% for N uptake). The model satisfactorily simulated the regrowth LAI but only up to a value of about 4.0. The modified CATIMO model with its capacity to simulate regrowth provides a framework to simulate perennial grasses with multiple harvests, and to explore management options for sustainable grass production under different environmental conditions. Crown Copyright (C) 2012 Published by Elsevier B.V. All rights reserved.
|
|
Bennetzen, E. H., Smith, P., Soussana, J. - F., & Porter, J. R. (2012). Identity-based estimation of greenhouse gas emissions from crop production: case study from Denmark. European Journal of Agronomy, 41, 66–72.
Abstract: In order to feed the world we need innovative thinking on how to increase agricultural production whilst also mitigating climate change. Agriculture and land-use change are responsible for approximately one-third of total anthropogenic greenhouse gas (GHG) emissions but hold potential for climate change mitigation but are only tangentially included in UNFCCC mitigation policies. To get a full estimate of GHG emissions from agricultural crop production both energy-based emissions and land-based emissions need to be accounted for. Furthermore, the major mitigation potential is likely to be indirect reduction of emissions i.e. reducing emissions per unit of agricultural product rather than the absolute emissions per se. Hence the system productivity must be included in the same analysis. This paper presents the Kaya-Porter identity, derived from the Maya identity, as a new way to calculate GHG emissions from agricultural crop production by deconstructing emissions into five elements; the GHG intensity of the energy used for production (kg CO2-eq./MJ), energy intensity of the production (MJ/kg dry matter), areal productivity (kg dry matter/ha), areal land-based GHG emissions (CO2-eq./ha) and area (ha). These separate elements in the identity can be targeted in emissions reduction and mitigation policies and are useful to analyse past and current trends in emissions and to explore future scenarios. Using the Kaya-Porter identity we have performed a case study on Danish crop production and find emissions to have been reduced by 12% from 1992 to 2008, whilst yields per unit area have remained constant. Both land-based emissions and energy-based emissions have decreased, mainly due to a 41% reduction in nitrogen fertilizer use. The initial identity based analysis for crop production presented here needs to be extended to include livestock to reflect the entire agricultural production and food demand sectors, thereby permitting analysis of the trade-offs between animal and plant food production, human dietary preferences and population and resulting GHG emissions. (C) 2012 Elsevier B.V. All rights reserved.
|
|
Mueller, L., Schindler, U., Shepherd, T. G., Ball, B. C., Smolentseva, E., Hu, C., et al. (2012). A framework for assessing agricultural soil quality on a global scale. Archives of Agronomy and Soil Science, 58(sup1), S76–S82.
Abstract: This paper provides information about a novel approach of rating agricultural soil quality (SQ) and crop yield potentials consistently over a range of spatial scales. The Muencheberg Soil Quality Rating is an indicator-based straightforward overall assessment method of agricultural SQ. It is a framework covering aspects of soil texture, structure, topography and climate which is based on 8 basic indicators and more than 12 hazard indicators. Ratings are performed by visual methods of soil evaluation. A field manual is then used to provide ratings from tables based on indicator thresholds. Finally, overall rating scores are given, ranging from 0 (worst) to 100 (best) to characterise crop yield potentials. The current approach is valid for grassland and cropland. Field tests in several countries confirmed the practicability and reliability of the method. At field scale, soil structure is a crucial, management induced criterion of agricultural SQ. At the global scale, climate controlled hazard indicators of drought risk and soil thermal regime are crucial for SQ and crop yield potentials. Final rating scores are well correlated with crop yields. We conclude that this system could be evolved for ranking and controlling agricultural SQ on a global scale.
Keywords: soil quality; indicators; muencheberg soil quality rating
|
|
Kowalczyk, A., & Twardy, S. (2012). Comparison of the water erosion magnitude estimated by the modified USLE methods (Vol. 121).
|
|
Francone, C., Katul, G. G., Cassardo, C., & Richiardone, R. (2012). Turbulent transport efficiency and the ejection-sweep motion for momentum and heat on sloping terrain covered with vineyards. Agricultural and Forest Meteorology, 162-163, 98–107.
Abstract: In boundary layer flows, it is now recognized that the net momentum and mass exchange rates are dominated by the statistical properties of ejecting and sweeping motion often linked to the presence of coherent turbulent structures. Over vineyards, three main factors impact the transport properties of such coherent motion: presence of sloping terrain, variations in leaf area index (LAI) during the growing season, and thermal stratification. The effect of these factors on momentum and heat transport is explored for three vineyard sites situated on different slopes. All three sites experience similar seasonal variation in LAI and mean wind conditions. The analysis is carried out using a conventional quadrant analysis technique and is tested against two models approximating the joint probability density function (JPDF) of the flow variables. It is demonstrated that a Gaussian JPDF explains much of the updraft and downdraft statistical contributions to heat and momentum transport efficiencies for all three sites. An incomplete or truncated third-order cumulant expansion method (ICEM) of the JPDF that retains only the mixed moments and ignores the skewness contributions describes well all the key properties of ejections and sweeps for all slopes, LAI, and stability classes. The implication of these findings for diagnosing potential failures of gradient-diffusion theory over complex terrain is discussed. Because only lower order moments are needed to describe the main characteristics of the JPDF, the use of the Moving Equilibrium Hypothesis (MEH) to predict these moments from the locally measured sensible heat flux and friction velocity is explored. Provided the planar fit coordinate transformation is applied to the data, the MEH can describe these statistical moments at all three sites regardless of terrain slopes and LAI values. (C) 2012 Elsevier B.V. All rights reserved.
|