| Records |
| Author |
Crout, N.M.J.; Craigon, J.; Cox, G.M.; Jao, Y.; Tarsitano, D.; Wood, A.T.A.; Semenov, M. |
| Title |
An objective approach to model reduction: Application to the Sirius wheat model |
Type |
Journal Article |
| Year |
2014 |
Publication |
Agricultural and Forest Meteorology |
Abbreviated Journal |
Agricultural and Forest Meteorology |
| Volume |
189-190 |
Issue |
100 |
Pages |
211-219 |
| Keywords |
Complexity; Crop model; Evaluation; Model reduction; Parsimony; Wheat |
| Abstract |
An existing simulation model of wheat growth and development, Sirius, was evaluated through a systematic model reduction procedure. The model was automatically manipulated under software control to replace variables within the model structure with constants, individually and in combination. Predictions of the resultant models were compared to growth analysis observations of total biomass, grain yield, and canopy leaf area derived from 9 trials conducted in the UK and New Zealand under optimal, nitrogen limiting and drought conditions. Model performance in predicting these observations was compared in order to evaluate whether individual model variables contributed positively to the overall prediction. Of the 1 1 1 model variables considered 16 were identified as potentially redundant. Areas of the model where there was evidence of redundancy were: (a) translocation of biomass carbon to grain; (b) nitrogen physiology; (c) adjustment of air temperature for various modelled processes; (d) allowance for diurnal variation in temperature; (e) vernalisation (f) soil nitrogen mineralisation (g) soil surface evaporation. It is not suggested that these are not important processes in real crops, rather, that their representation in the model cannot be justified in the context of the analysis. The approach described is analogous to a detailed model inter-comparison although it would be better described as a model intra-comparison as it is based on the comparison of many simplified forms of the same model. The approach provides automation to increase the efficiency of the evaluation and a systematic means of increasing the rigour of the evaluation. |
| Address |
2016-10-31 |
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| Language |
English |
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Edition |
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| ISSN |
0168-1923 |
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Article |
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| Notes |
CropM |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4788 |
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| Author |
Olesen, J.E. |
| Title |
Rainfed intensive crop systems |
Type |
Book Chapter |
| Year |
2014 |
Publication |
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Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
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| Keywords |
CropM |
| Abstract |
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| Publisher |
Cabi |
Place of Publication |
Wallingford |
Editor |
Fuhrer, J.; Gregory, P.J. |
| Language |
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Summary Language |
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Original Title |
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Series Title |
Climate Change Impact and Adaptation in Agricultural Systems |
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| Notes |
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Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
2686 |
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| Author |
Dietrich, J.P.; Schmitz, C.; Lotze-Campen, H.; Popp, A.; Muller, C. |
| Title |
Forecasting technological change in agriculture-An endogenous implementation in a global, and use model |
Type |
Journal Article |
| Year |
2014 |
Publication |
Technological Forecasting and Social Change |
Abbreviated Journal |
Technological Forecasting and Social Change |
| Volume |
81 |
Issue |
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Pages |
236-249 |
| Keywords |
Technological change; Land use; Agricultural productivity; Land use; intensity; Research and development; land-use; research expenditures; productivity growth; impact; deforestation; forest; yield; Business & Economics; Public Administration |
| Abstract |
Technological change in agriculture plays a decisive role for meeting future demands for agricultural goods. However, up to now, agricultural sector models and models on land use change have used technological change as an exogenous input due to various information and data deficiencies. This paper provides a first attempt towards an endogenous implementation based on a measure of agricultural land use intensity. We relate this measure to empirical data on investments in technological change. Our estimated yield elasticity with respect to research investments is 029 and production costs per area increase linearly with an increasing yield level. Implemented in the global land use model MAgPIE (”Model of Agricultural Production and its Impact on the Environment”) this approach provides estimates of future yield growth. Highest future yield increases are required in Sub-Saharan Africa, the Middle East and South Asia. Our validation with FAO data for the period 1995-2005 indicates that the model behavior is in line with observations. By comparing two scenarios on forest conservation we show that protecting sensitive forest areas in the future is possible but requires substantial investments into technological change. (C) 2013 Elsevier Inc. All rights reserved. |
| Address |
2016-10-31 |
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English |
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| ISSN |
0040-1625 |
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Article |
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| Notes |
CropM |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4789 |
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| Author |
Banse, M.; Brouwer, F.; Palatnik, R.R.; Sinabell, F. |
| Title |
The Economics of European Agriculture under Conditions of Climate Change (Editorial) |
Type |
Journal Article |
| Year |
2014 |
Publication |
German Journal of Agricultural Economics |
Abbreviated Journal |
German Journal of Agricultural Economics |
| Volume |
63 |
Issue |
3 |
Pages |
131-132 |
| Keywords |
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| Abstract |
This Special Issue on “The Economics of European Agriculture under Conditions of Climate Change” brings together a selection of papers that contribute to the understanding of recent developments related to agriculture and climate change in four European coun- tries. The focus of the Special Issue is on quantitative modeling and empirical analyses. The papers presented here not only cover the heterogeneity of agriculture in Europe with case studies from the Mediterranean (Italy), central (Austria) and north-western Europe (Ireland and Scotland) but also give insights into the diversity of quantitative modeling approaches in agriculture. |
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English |
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Editorial material |
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| Notes |
TradeM, ft_macsur |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4763 |
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| Author |
Klatt, S.; Kraus, D.; Rahn, K.-H.; Werner, C.; Kiese, R.; Butterbach-Bahl, K.; Haas, E. |
| Title |
Parameter-induced uncertainty quantification of a regional N2O and NO3 inventory using the biogeochemical model LandscapeDNDC |
Type |
Manuscript |
| Year |
2014 |
Publication |
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CropM |
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Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
2542 |
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