Field-scale modeling of tree–crop interactions: Challenges and development needs

Luedeling, Eike; Smethurst, P. J.; Baudron, Frédéric; Bayala, Jules; Huth, Neil; Noordwijk, Meine van; Ong, C. K.; Mulia, Rachmat; Lusiana, Betha; Muthuri, Catherine; Sinclair, F.L.

doi:10.1016/j.agsy.2015.11.005

Cited by 130 publications

(113 citation statements)

References 163 publications

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“…In this context, research on agroforestry systems aims at quantifying and analyzing the spatiotemporal patterns of resource capture between species. However, papers covering temperate agroforestry systems reveal contrasting results (Luedeling et al, 2016;Smith et al, 2013;Tsonkova et al, 2012). This is probably due to the fact that the interactions between two different species may depend on multiple factors such as the design of the mixture (e.g.…”

Section: Introductionmentioning

confidence: 87%

Impact of spatio-temporal shade dynamics on wheat growth and yield, perspectives for temperate agroforestry

Artru

Garré

Dupraz

et al. 2017

European Journal of Agronomy

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a b s t r a c tA stumbling block to the adoption of silvoarable agroforestry systems is the lack of quantitative knowledge on the performance of different crops when competing for resources with trees. In North-Western Europe, light is likely to be the principal limiting resource for understorey crops, and most agronomic studies show a systematic reduction of final yield as shade increases. However the intensity of the crop response depends on both the environmental conditions and the shade characteristics. This study addressed the issue by monitoring winter wheat (Triticum aestivum L.) growth, productivity and quality under artificial shade provided by military camouflage shade-netting, and using the Hi-sAFe model to relate the artificial shade conditions to those applying in agroforestry systems.The field experiment was carried out over two consecutive years (2013-14 and 2014-15) on the experimental farm of Gembloux Agro-Bio Tech, Belgium. The shade structures recreated two shade conditions: periodic shade (PS) and continuous shade (CS), with the former using overlapping military camouflage netting to provide discontinuous light through the day, and the latter using conventional shade cloth. The experiment simulated shading from a canopy of late-flushing hybrid walnut leaves above winter wheat. Shading was imposed 16 (2013-14) and 10 (2014-15) days before flowering and retained until harvest. The crop experienced full light conditions until the maximum leaf area index stage (LAI max ) had been reached. In both years, LAI followed the same dynamics between the different treatments, but in 2013-2014 an attack of the take-all disease (Gaeumannomyces graminis var. tritici) reduced yields overall and prevented significant treatment effects. In season 2014-15 the decrease in global radiation reaching the crop during a period of 66 days (CS: -61% and PS: -43%) significantly affected final yield (CS: -45% and PS: -25%), mainly through a reduction of the average grain weight and the number of grain per m 2 . Grain protein content increased by up to 45% under the CS treatment in 2015. Nevertheless, at the plot scale, protein yield (t/ha) did not compensate for the final grain yield decrease.The Hi-sAFe model was used to simulate an agroforestry plot with two lines of walnut trees running either north-south or east-west. The levels of artificial shade levels applied in this experiment were compared to those predicted beneath trees growing with similar climatic conditions in Belgium. The levels used in the CS treatment are only likely to occur real agroforestry conditions on 10% of the cropped area until the trees are 30 years old and only with east-west tree row orientation.

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Section: Introductionmentioning

confidence: 87%

Impact of spatio-temporal shade dynamics on wheat growth and yield, perspectives for temperate agroforestry

Artru

Garré

Dupraz

et al. 2017

European Journal of Agronomy

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“…Further, the APSIM-maize model uses the air temperature -sensors protected from direct sunlightand not crop temperature to simulate crop yields while the latter may be more appropriate (Luedeling et al, 2016), potentially over-estimating impacts of trees on crop yields.…”

Section: Maize Phenologymentioning

confidence: 99%

“…In addition to competition and complementarity in the capture of light (which figure in crop models), water and nutrients must often be considered in attempts to predict the yield of tree-crop mixtures (Luedeling et al 2016). Many models have been developed for agroforestry: (i) the WaNuLCAS model, developed as a generic model for water, nutrient and light capture in agroforestry systems (Noordwijk et al 2011) , (ii) the Agricultural Production Systems Simulator Modelling framework (APSIM), which includes tree sub-models (Luedeling et al 2016), (iii) the Yield-SAFE model for Europe (van der Werf et al 2007), (iv) the Simile model (Muetzelfeldt and Massheder 2003) and (v) the Soil Changes Under Agriculture, Agroforestry and Forestry model (SCUAF) (Young et al 1998).…”

Section: Quantification Of Tree Effects On Cropsmentioning

confidence: 99%

“…Many models have been developed for agroforestry: (i) the WaNuLCAS model, developed as a generic model for water, nutrient and light capture in agroforestry systems (Noordwijk et al 2011) , (ii) the Agricultural Production Systems Simulator Modelling framework (APSIM), which includes tree sub-models (Luedeling et al 2016), (iii) the Yield-SAFE model for Europe (van der Werf et al 2007), (iv) the Simile model (Muetzelfeldt and Massheder 2003) and (v) the Soil Changes Under Agriculture, Agroforestry and Forestry model (SCUAF) (Young et al 1998). However, the usefulness of these models has remained limited for reasons including insufficient flexibility, a restricted ability to simulate interactions, extensive parameterization needs or a lack of model maintenance.…”

Section: Quantification Of Tree Effects On Cropsmentioning

confidence: 99%

“…However, the usefulness of these models has remained limited for reasons including insufficient flexibility, a restricted ability to simulate interactions, extensive parameterization needs or a lack of model maintenance. Rapid progress in the reliable modelling of tree and crop performance of agroforestry systems is needed to ensure that agroforestry fulfils its potential to contribute to reducing poverty, improving food security and fostering sustainability (Luedeling et al 2016). …”

Section: Quantification Of Tree Effects On Cropsmentioning

confidence: 99%

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Farming with trees: a balancing act in the shade

Ndoli¹

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The smallholder agriculture sector in East Africa is the dominant economic and social activity for millions of farm households who are often resource-poor, food-insecure and most vulnerable to climate change. In this region, population pressure has led to shorter fallow periods or continuous cropping even on hillslopes causing erosion and leading to reduced soil organic matter content and nutrient mining without replenishment. Consequently, poor agricultural productivity has led to food shortages and these problems are likely to intensify in the region, as the human population is growing faster than in other parts of the world. Agroforestry, a low-input technology, was shown to contribute to the enhancement of food production while ensuring sustainability in sub-Saharan Africa.Agroforestry may improve food security by increasing soil fertility and providing additional income from tree products. Thus, agroforestry is now receiving increasing attention as a sustainable landmanagement option and some countries in East Africa (e.g. Rwanda) have pledged to restore up to 100% of their agricultural land mainly through agroforestry by the year 2020. Nevertheless, crop yields reduction in agroforestry are frequent due to competition for resources among trees and crops.In recent studies, tree canopy and root pruning were tested to improve light availability and resource use efficiency but studies that tackle crop management and tillage options to optimize crop productivity in the agroforestry systems are scarce.This thesis aims to assess the importance of agroforestry across Rwanda and its implication on crop productivity and food security of farm households, explore and recommend the maize varieties and tillage options that could minimize tree-crop competition in the equatorial savannah of Rwanda and Ethiopia. The approach combined household survey on the contribution of trees on household income and food security in six agroecologies of Rwanda, experiments on the microclimate and fertility effects of trees on crops in sub-humid region of Rwanda, maize variety testing in agroforestry systems and trials on conservation agriculture with trees in the equatorial savannah of two East African countries: Rwanda (Bugesera site) and Ethiopia (Meki site). The survey in Rwanda found that food security increases with increasing farm size and farmers with more trees tended to be wealthier (e.g. with larger land and more often higher crop and livestock income) and therefore tended to be more food secure in half of the agroecologies. The proportion of household income that came from tree products was the least among sources of income suggesting that most tree products are not sold but kept by farmers for their own use. Yet tree vi income was important for about 12% of the farmers, contributing more than 20% of their overall income. Households having low food security relied more on income from tree products than those with higher food security status. Therefore, income from tree products can be seen as a 'safety net' for the po...

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