Yield-SAFE: A parameter-sparse, process-based dynamic model for predicting resource capture, growth, and production in agroforestry systems.
Date
2007-04-01T00:00:00Z
Supervisor/s
Journal Title
Journal ISSN
Volume Title
Publisher
Elsevier Science B.V., Amsterdam.
Department
Type
Article
ISSN
0925-8574
Format
Free to read from
Citation
Wopke van der Werf, Karel Keesman, Paul Burgess, Anil Graves, David Pilbeam, L.D. Incoll, Klaas Metselaar, Martina Mayus, Roel Stappers, Herman van Keulen, João Palma, Christian Dupraz, Yield-SAFE: A parameter-sparse, process-based dynamic model for predicting resource capture, growth, and production in agroforestry systems, Ecological Engineering, Volume 29, Issue 4, Carbon sequestration and landscape ecology in Western Europe, 1 April 2007, Pages 419-433.
Abstract
- Silvoarable agroforestry (SAF) is the cultivation of trees and arable crops on the same parcel of land. SAF may contribute to modern diversified land use objectives in Europe, such as enhanced biodiversity and productivity, reduced leaching of nitrogen, protection against flooding and erosion, and attractiveness of the landscape. Long-term yield predictions are needed to assess long-term economic profitability of SAF. 2. A model for growth, resource sharing and productivity in agroforestry systems was developed to act as a tool in forecasts of yield, economic optimization of farming enterprises and exploration of policy options for land use in Europe. The model is called Yield- SAFE; from “YIeld Estimator for Long term Design of Silvoarable AgroForestry in Europe”. The model was developed with as few equations and parameters as possible to allow model parameterization under constrained availability of data from long-term experiments. 3. The model consists of seven state equations expressing the temporal dynamics of: (1) tree biomass; (2) tree leaf area; (3) number of shoots per tree; (4) crop biomass; (5) crop leaf area index; (6) heat sum; and (7) soil water content. The main outputs of the model are the growth dynamics and final yields of trees and crops. Daily inputs are temperature, radiation and precipitation. Planting densities, initial biomasses of tree and crop species, and soil parameters must be specified. 4. A parameterization of Yield-SAFE is generated, using published yield tables for tree growth and output from the comprehensive crop simulation model STICS. Analysis of tree and crop growth data from two poplar agroforestry stands in the United Kingdom demonstrates the validity of the modelling concept and calibration philosophy of Yield-SAFE. A sensitivity analysis is presented to elucidate which biological parameters most influence short and long-term productivity and land equivalent ratio. 5. The conceptual model, elaborated in Yield-SAFE, in combination with the outlined procedure for model calibration, offers a valid tool for exploratory land use stud
Description
Software Description
Software Language
Github
Keywords
Agroforestry model, Competition, Parameter estimation, Resource use, Land use, Land equivalent ratio, Long-term yield prediction