WaNuLCAS, a model of water, nutrient and light capture in agroforestry systems

Noordwijk, Meine van; Lusiana, Betha

doi:10.1007/978-94-017-0679-7_14

Cited by 87 publications

(113 citation statements)

References 21 publications

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“…The WaNuLCAS model was used in this study (van Noordwijk and Lusiana 1999;van Noordwijk et al 2004). In view of initial poor simulation of water dynamics, the Wösten et al (1998) pedotransfer functions (PTF) functions used to derive the van Genuchten (1980) constants for volumetric soil water content in the WaNuLCAS model were substituted by those from Hodnett and Tomasella (2002) during this investigation.…”

Section: Wanulcas Modelmentioning

confidence: 99%

“…Nutrient demand is based on target biomass nutrient concentrations and actual biomass nutrient concentrations. These demands are used to calculate uptake based on root length densities, water/nutrient amounts in soil and effective diffusion constants within a zero sink uptake model (van Noordwijk and Lusiana 1999). Crop yield is allocated a variable proportion of this actual crop growth depending on the crops growth stage.…”

Section: Wanulcas Modelmentioning

confidence: 99%

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Modelling of planted legume fallows in Western Kenya using WaNuLCAS. (I) Model calibration and validation

Walker

Mutuo²,

Noordwijk³

et al. 2007

Agroforest Syst

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Poor soil fertility is the biggest obstacle to agricultural productivity in Sub-Saharan Africa. Improved fallows can help to raise agricultural productivity in these systems of low financial capital, however, experimental testing of their potential application domain and design is costly and time consuming. Models can evaluate alternative systems relatively quickly and at relatively low cost, but must first be validated to assess satisfactory simulation of the target systems. Specific climatic, edaphic, crop and fallow growth data was used from five sites in Western Kenya to calibrate and validate simulations of maize and improved fallow growth using the Water, Nutrient and Light Capture in Agroforestry Systems (WaNuLCAS) model. The model predicted continuous maize yields across the sites with an R 2 of 0.72, an EF (model efficiency) of 0.66 and a CD (coefficient of determination) of 2.73, although the default pedotransfer functions (PTF) for volumetric soil water content used in the model had to be substituted for a tropical soils specific PTF before this was achieved. Predicted maize yield was consistently related to fallow biomass (i.e. higher fallow biomass correlated with higher subsequent maize yields) at two sites and the model predicted maize yields following fallow growth from this subset of the data with an R 2 of 0.42. This relationship of fallow biomass to subsequent maize yield was not observed across the whole data set due to incomplete fallow litterfall data, factors not included in the model and associated poor model prediction of recycled tree biomass. After site and tree calibration, the model can thus be applied to assess fallow management strategies for sites limited by water and nitrogen.

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Section: Wanulcas Modelmentioning

confidence: 99%

Section: Wanulcas Modelmentioning

confidence: 99%

Modelling of planted legume fallows in Western Kenya using WaNuLCAS. (I) Model calibration and validation

Walker

Mutuo²,

Noordwijk³

et al. 2007

Agroforest Syst

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“…WaNuLCAS is a process-based model of the water, nutrient, and light capture in agroforestry systems developed by van Noordwijk et al ( 2004 ). It enables evaluation of the choice of tree species, their spacing and pattern, and possible intercrop.…”

Section: Bioeconomic Modeling Using Wanulcasmentioning

confidence: 99%

Agroforestry Models for Promoting Effective Risk Management and Building Sustainable Communities

Magcale-Macandog

2014

Sustainable Living With Environmental Risks

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Soil erosion and environmental degradation due to the cultivation of marginal upland areas are now considered major environmental risks in the Philippines. Agroforestry may help address the situation. In agroforestry systems, the positive interactions of tree-crop combinations not only improve biophysical conditions in farms, but also enhance food security in farming households.A combination of Participatory Rural Appraisal (PRA), a household survey, focus group discussions, fi eld experiments, and simulation modeling was undertaken in Claveria, Misamis Oriental, Philippines. The agroforestry system adopted depended on the farmers' motivations. The adoption of agroforestry signifi cantly increased the households' level of income by around 42-137 %, compared with that from continuous annual mono-cropping. Another benefi cial feature of an agroforestry system was the enhanced nutrient infl ow to the system through leaf litterfall, stemfl ow, and throughfall. A modeling study using the WaNuLCAS model showed that the Eucalyptus -maize hedgerow system provided signifi cant improvements to a range of biophysical and economic measures of productivity and sustainability.It is recommended that both national and local government units mainstream their policies and efforts toward promoting agroforestry adoption in the Philippine uplands. Keywords IntroductionThe uplands in the Philippines are of great importance and interest because they comprise about 59 % of the country's total land area. They are dynamic and highly interactive landscape components of the rural system, and also serve as the life support for the lowlands and coastal areas. In addition, they are home to the increasing population of the "poorest of the poor," and are expected to absorb more of the expanding population (Sajise and Ganapin 1991 ).The Philippine uplands are a very heterogeneous and fragile resource base (Sajise and Ganapin 1991 ). Most of these areas are either open grassland, degraded, or occupied by settlers (Villancio et al. 2003 ). More than 20 million people are estimated to have settled in the uplands, and the number is increasing at a rate of about 2.8 % annually, which is above the national average of 2.32 %.Its geographical location has made the Philippines highly vulnerable to natural hazards, the most common of which is the occurrence of turbulent typhoons. During the decade from 2001 to 2012, the country was hit by a total of 184 typhoons, or an average of 18 typhoons per year (Israel and Briones 2012 ). Climate change is perceived to have increased the frequency and intensity of heavy rainfall associated with typhoons and other weather systems, resulting in fl ooding. From 2000 to 2010, damage to agricultural crops caused by typhoons, fl oods, and droughts amounted to nearly PHP 106.88 million. Rice, corn, and other high value cash crops sustained the most damage. Typhoons Ondoy (Ketsana) and Pepeng (Parma) in September and October 2009 wrought havoc in both urban and rural areas in the country, with total damage reachin...

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Section: Agroforestry Modelsmentioning

confidence: 99%

“…WaNuLCAS incorporates a plant-plant interaction model focusing on above-and below-ground resource capture in a competitive situation (van Noordwijk and Lusiana 1999). The model links mulch production, its effect on soil fertility and shading effects of trees on crop yields (van Noordwijk and Lusiana 2000). The model allows different management options such as plot size, tree spacing and choice of tree species, cropping cycles, pruning, organic and inorganic fertilizer inputs and crop residue removal (van Noordwijk and Lusiana 2000).…”

Section: Agroforestry Modelsmentioning

confidence: 99%

Computer-based tools for decision support in agroforestry: Current state and future needs

Ellis

Bentrup

Schoeneberger

2004

Agroforestry Systems

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Successful design of agroforestry practices hinges on the ability to pull together very diverse and sometimes large sets of information (i.e., biophysical, economic and social factors), and then implementing the synthesis of this information across several spatial scales from site to landscape. Agroforestry, by its very nature, creates complex systems with impacts ranging from the site or practice level up to the landscape and beyond. Computer-based Decision Support Tools (DST) help to integrate information to facilitate the decision-making process that directs development, acceptance, adoption, and management aspects in agroforestry. Computer-based DSTs include databases, geographical information systems, models, knowledge-base or expert systems, and 'hybrid' decision support systems. These different DSTs and their applications in agroforestry research and development are described in this paper. Although agroforestry lacks the large research foundation of its agriculture and forestry counterparts, the development and use of computer-based tools in agroforestry have been substantial and are projected to increase as the recognition of the productive and protective (service) roles of these tree-based practices expands. The utility of these and future tools for decision-support in agroforestry must take into account the limits of our current scientific information, the diversity of aspects (i.e. economic, social, and biophysical) that must be incorporated into the planning and design process, and, most importantly, who the end-user of the tools will be. Incorporating these tools into the design and planning process will enhance the capability of agroforestry to simultaneously achieve environmental protection and agricultural production goals.

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WaNuLCAS, a model of water, nutrient and light capture in agroforestry systems

Cited by 87 publications

References 21 publications

Modelling of planted legume fallows in Western Kenya using WaNuLCAS. (I) Model calibration and validation

Modelling of planted legume fallows in Western Kenya using WaNuLCAS. (I) Model calibration and validation

Agroforestry Models for Promoting Effective Risk Management and Building Sustainable Communities

Computer-based tools for decision support in agroforestry: Current state and future needs

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