| Records |
| Author |
Jing, Q.; Bélanger, G.; Baron, V.; Bonesmo, H.; Virkajärvi, P. |
| Title |
Simulating the Nutritive Value of Timothy Summer Regrowth |
Type |
Journal Article |
| Year |
2013 |
Publication |
Agronomy Journal |
Abbreviated Journal |
Agronomy Journal |
| Volume |
105 |
Issue |
3 |
Pages |
563 |
| Keywords |
varying n nutrition; cation-anion difference; spring growth; swine manure; leaf-area; nitrogen; yield; model; digestibility; dynamics |
| Abstract |
The process-based grass model, CATIMO, simulates the spring growth and nutritive value of timothy (Phleum pratense L.), a forage species widely grown in Scandinavia and Canada, but the nutritive value of the summer regrowth has never been simulated. Our objective was to improve CATIMO for simulating the N concentration, neutral detergent fiber (NDF), in vitro digestibility of NDF (dNDF), and in vitro true digestibility of dry matter (IVTD) of summer regrowth. Daily changes in summer regrowth nutritive value were simulated by modifying key crop parameters that differed from spring growth. More specifically, the partitioning fraction to leaf blades was increased to increase the leaf-to-weight ratio, and daily changes in NDF and dNDF of leaf blades and stems were reduced. The modified CATIMO model was evaluated with data from four independent experiments in eastern and western Canada and Finland. The model performed better for eastern Canada than for the other locations, but the nutritive value attributes of the summer regrowth across locations (range of normalized RMSE = 8-25%, slope < 0.17, R-2 < 0.10) were not simulated as well as those of the spring growth (range of normalized RMSE = 4-16%, 0.85 < slope < 1.07, R-2 > 0.61). These modeling results highlight knowledge gaps in timothy summer regrowth and prospective research directions: improved knowledge of factors controlling the nutritive value of the timothy summer regrowth and experimental measurements of leaf-to-weight ratio and of the nutritive value of leaves and stems. |
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English |
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0002-1962 |
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CropM, LiveM |
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no |
| Call Number |
MA @ admin @ |
Serial |
4493 |
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| Author |
Irz, X.; Kuosmanen, N. |
| Title |
Explaining growth in demand for dairy products in Finland: an econometric analysis |
Type |
Journal Article |
| Year |
2013 |
Publication |
Food Economics |
Abbreviated Journal |
Food Economics |
| Volume |
9 |
Issue |
sup5 |
Pages |
47-56 |
| Keywords |
Consumption; food; almost ideal demand system; decomposition; elasticities; milk; demand analysis; farm |
| Abstract |
The dairy sector represents the cornerstone of Finnish agriculture but faces new challenges linked to the decoupling of farm subsidies and abolition of milk production quotas. Because of its increasing exposure to market forces, the sector must anticipate future changes in demand and deliver precisely what Finnish consumers want. This paper contributes to that goal by analyzing retroactively the drivers of demand for dairy products over the period 1975–2010 using National Accounts Data. After presenting the evolution of consumption for dairy products, we estimate a complete system of demand for food and dairy products and use it to decompose demand growth into a substitution effect, income effect, and trend effect. The analysis points to the severity of the challenges that the sector is facing. Stagnant consumption is at least partially the result of continuous but adverse taste changes, and as Finnish consumers grow more prosperous, they allocate an increasingly smaller share of their food budget to the dairy group. The low own-price elasticity of demand for dairy products also limits the benefits to the sector of growth in milk production. Hence, business-as-usual will result in the dwindling importance of the dairy sector in the Finnish food chain. Innovation and product differentiation, perhaps emphasizing the attributes of livestock production processes, are clearly required to counter this evolution. |
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2164-828x |
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Article |
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| Notes |
TradeM, ftnotmacsur |
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no |
| Call Number |
MA @ admin @ |
Serial |
4491 |
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| Author |
Höglind, M.; Thorsen, S.M.; Semenov, M.A. |
| Title |
Assessing uncertainties in impact of climate change on grass production in Northern Europe using ensembles of global climate models |
Type |
Journal Article |
| Year |
2013 |
Publication |
Agricultural and Forest Meteorology |
Abbreviated Journal |
Agricultural and Forest Meteorology |
| Volume |
170 |
Issue |
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Pages |
103-113 |
| Keywords |
climatic variability; frost damage; grass modelling; ice damage; multi-model ensemble; elevated co2 concentration; phleum-pratense l; timothy regrowth; change scenarios; winter survival; meadow fescue; crop yields; growth; frost; temperature |
| Abstract |
Forage-based dairy and livestock production is the backbone of agriculture in Northern Europe in economic terms. Changes in growing conditions that affect forage grass yield may have great economic consequences. This study assessed the impact of climate change on two grass species, timothy and ryegrass, at 14 locations in Northern Europe (Iceland, Scandinavia, Baltic countries) in a near-future scenario (2040-2065) compared with the baseline period 1960-1990. Local-scale climate scenarios were based on the CMIP3 multi-model ensembles of 15 global climate models in order to quantify the uncertainty in the impacts relating to highly uncertain projections of future climate. Potential yield of timothy, the most important perennial forage grass in Northern Europe, was simulated under the assumption of optimal overwintering conditions and current CO2 level, in order to obtain an estimate of the effect of changes in summer climate per se. The risk of frost and ice damage during winter was also assessed. The simulation results demonstrated that potential grass yield will increase throughout the study area, mainly as a result of increased growing temperatures. The yield response to climate change was slightly larger in irrigated than non-irrigated conditions (14% and 11%, respectively), due to larger water deficit for the 2050 scenario. However, a geo-climatic gradient was evident, with the largest predicted yield response at western locations. A geo-climatic gradient was also revealed with respect to potential frost damage, which was predicted to increase during winter in some areas east of the Baltic Sea for timothy, and for a larger number of locations both east and west of the Baltic Sea for perennial ryegrass. The risk of frost damage in spring was predicted to increase mainly in western parts of the study area. If frost damage to perennial ryegrass increases during winter, the expected increase in winter temperature due to global warming may not necessarily improve overwintering conditions, so the growing zone may not necessarily expand to the north and east of the study area by 2050. The uncertainty in impacts was frequently, but not consistently, greater in western than eastern locations. (C) 2012 Elsevier B.V. All rights reserved. |
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Edition |
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| ISSN |
0168-1923 |
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Article |
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| Notes |
CropM, LiveM, ftnotmacsur |
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no |
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MA @ admin @ |
Serial |
4492 |
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| Author |
Heinke, J.; Ostberg, S.; Schaphoff, S.; Frieler, K.; Müller, C.; Gerten, D.; Meinshausen, M.; Lucht, W. |
| Title |
A new climate dataset for systematic assessments of climate change impacts as a function of global warming |
Type |
Journal Article |
| Year |
2013 |
Publication |
Geoscientific Model Development |
Abbreviated Journal |
Geosci. Model Dev. |
| Volume |
6 |
Issue |
5 |
Pages |
1689-1703 |
| Keywords |
dangerous anthropogenic interference; vegetation model; carbon-cycle; emissions; targets |
| Abstract |
In the ongoing political debate on climate change, global mean temperature change (Delta T-glob) has become the yardstick by which mitigation costs, impacts from unavoided climate change, and adaptation requirements are discussed. For a scientifically informed discourse along these lines, systematic assessments of climate change impacts as a function of Delta T-glob are required. The current availability of climate change scenarios constrains this type of assessment to a narrow range of temperature change and/or a reduced ensemble of climate models. Here, a newly composed dataset of climate change scenarios is presented that addresses the specific requirements for global assessments of climate change impacts as a function of Delta T-glob. A pattern-scaling approach is applied to extract generalised patterns of spatially explicit change in temperature, precipitation and cloudiness from 19 Atmosphere-Ocean General Circulation Models (AOGCMs). The patterns are combined with scenarios of global mean temperature increase obtained from the reduced-complexity climate model MAGICC6 to create climate scenarios covering warming levels from 1.5 to 5 degrees above pre-industrial levels around the year 2100. The patterns are shown to sufficiently maintain the original AOGCMs’ climate change properties, even though they, necessarily, utilise a simplified relationships between Delta T-glob and changes in local climate properties. The dataset (made available online upon final publication of this paper) facilitates systematic analyses of climate change impacts as it covers a wider and finer-spaced range of climate change scenarios than the original AOGCM simulations. |
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| ISSN |
1991-9603 |
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CropM |
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no |
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MA @ admin @ |
Serial |
4490 |
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| Author |
Dietrich, J.P.; Popp, A.; Lotze-Campen, H. |
| Title |
Reducing the loss of information and gaining accuracy with clustering methods in a global land-use model |
Type |
Journal Article |
| Year |
2013 |
Publication |
Ecological Modelling |
Abbreviated Journal |
Ecol. Model. |
| Volume |
263 |
Issue |
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Pages |
233-243 |
| Keywords |
aggregation; downscaling; clustering; information conservation; land use model; scale; scales; agriculture; simulation; dynamics; pattern |
| Abstract |
Global land-use models have to deal with processes on several spatial scales, ranging from the global scale down to the farm level. The increasing complexity of modern land-use models combined with the problem of limited computational resources represents a challenge to modelers. One solution of this problem is to perform spatial aggregation based on a regular grid or administrative units such as countries. Unfortunately this type of aggregation flattens many regional differences and produces a homogenized map of the world. In this paper we present an alternative aggregation approach using clustering methods. Clustering reduces the loss of information due to aggregation by choosing an appropriate aggregation pattern. We investigate different clustering methods, examining their quality in terms of information conservation. Our results indicate that clustering is always a good choice and preferable compared to grid-based aggregation. Although all the clustering methods we tested delivered a higher degree of information conservation than grid-based aggregation, the choice of clustering method is not arbitrary. Comparing outputs of a model fed with original data and a model fed with aggregated data, bottom-up clustering delivered the best results for the whole range of numbers of clusters tested. (C) 2013 Elsevier B.V. All rights reserved. |
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0304-3800 |
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TradeM |
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no |
| Call Number |
MA @ admin @ |
Serial |
4488 |
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