Simulation of crop yields using ERA-40: Limits to skill and nonstationarity in weather-yield relationships

Reanalysis data provide an excellent test bed for impacts prediction systems. because they represent an upper limit on the skill of climate models. Indian groundnut (Arachis hypogaea L.) yields have been simulated using the General Large-Area Model (GLAM) for annual crops and the European Centre for Medium-Range Weather Forecasts (ECMWF) 40-yr reanalysis (ERA-40). The ability of ERA-40 to represent the Indian summer monsoon has been examined. The ability of GLAM. when driven with daily ERA-40 data, to model both observed yields and observed relationships between subseasonal weather and yield has been assessed. Mean yields "were simulated well across much of India. Correlations between observed and modeled yields, where these are significant. are comparable to correlations between observed yields and ERA-40 rainfall. Uncertainties due to the input planting window, crop duration, and weather data have been examined. A reduction in the root-mean-square error of simulated yields was achieved by applying bias correction techniques to the precipitation. The stability of the relationship between weather and yield over time has been examined. Weather-yield correlations vary on decadal time scales. and this has direct implications for the accuracy of yield simulations. Analysis of the skewness of both detrended yields and precipitation suggest that nonclimatic factors are partly responsible for this nonstationarity. Evidence from other studies, including data on cereal and pulse yields, indicates that this result is not particular to groundnut yield. The detection and modeling of nonstationary weather-yield relationships emerges from this study as an important part of the process of understanding and predicting the impacts of climate variability and change on crop yields.

Quantification of physical and biological uncertainty in the simulation of the yield of a tropical crop using present-day and doubled CO2 climates

The impacts of climate change on crop productivity are often assessed using simulations from a numerical climate model as an input to a crop simulation model. The precision of these predictions reflects the uncertainty in both models. We examined how uncertainty in a climate (HadAM3) and crop General Large-Area Model (GLAM) for annual crops model affects the mean and standard deviation of crop yield simulations in present and doubled carbon dioxide (CO2) climates by perturbation of parameters in each model. The climate sensitivity parameter (lambda, the equilibrium response of global mean surface temperature to doubled CO2) was used to define the control climate. Observed 1966-1989 mean yields of groundnut (Arachis hypogaea L.) in India were simulated well by the crop model using the control climate and climates with values of lambda near the control value. The simulations were used to measure the contribution to uncertainty of key crop and climate model parameters. The standard deviation of yield was more affected by perturbation of climate parameters than crop model parameters in both the present-day and doubled CO2 climates. Climate uncertainty was higher in the doubled CO2 climate than in the present-day climate. Crop transpiration efficiency was key to crop model uncertainty in both present-day and doubled CO2 climates. The response of crop development to mean temperature contributed little uncertainty in the present-day simulations but was among the largest contributors under doubled CO2. The ensemble methods used here to quantify physical and biological uncertainty offer a method to improve model estimates of the impacts of climate change.

Bias from farmer self-selection in genetically modified crop productivity estimates: Evidence from Indian data

In the continuing debate over the impact of genetically modified (GM) crops on farmers of developing countries, it is important to accurately measure magnitudes such as farm-level yield gains from GM crop adoption. Yet most farm-level studies in the literature do not control for farmer self-selection, a potentially important source of bias in such estimates. We use farm-level panel data from Indian cotton farmers to investigate the yield effect of GM insect-resistant cotton. We explicitly take into account the fact that the choice of crop variety is an endogenous variable which might lead to bias from self-selection. A production function is estimated using a fixed-effects model to control for selection bias. Our results show that efficient farmers adopt Bacillus thuringiensis (Bt) cotton at a higher rate than their less efficient peers. This suggests that cross-sectional estimates of the yield effect of Bt cotton, which do not control for self-selection effects, are likely to be biased upwards. However, after controlling for selection bias, we still find that there is a significant positive yield effect from adoption of Bt cotton that more than offsets the additional cost of Bt seed.

Whole crop cereals 2. Prediction of apparent digestibility and energy value from in vitro digestion techniques and near infrared reflectance spectroscopy and of chemical composition by near infrared reflectance spectroscopy

Samples of whole crop wheat (WCW, n = 134) and whole crop barley (WCB, n = 16) were collected from commercial farms in the UK over a 2-year period (2003/2004 and 2004/2005). Near infrared reflectance spectroscopy (NIRS) was compared with laboratory and in vitro digestibility measures to predict digestible organic matter in the dry matter (DOMD) and metabolisable energy (ME) contents measured in vivo using sheep. Spectral models using the mean spectra of two scans were compared with those using individual spectra (duplicate spectra). Overall NIRS accurately predicted the concentration of chemical components in whole crop cereals apart from crude protein. ammonia-nitrogen, water-soluble carbohydrates, fermentation acids and solubility values. In addition. the spectral models had higher prediction power for in vivo DOMD and ME than chemical components or in vitro digestion methods. Overall there Was a benefit from the use of duplicate spectra rather than mean spectra and this was especially so for predicting in vivo DOMD and ME where the sample population size was smaller. The spectral models derived deal equally well with WCW and WCB and Would he of considerable practical value allowing rapid determination of nutritive value of these forages before their use in diets of productive animals. (C) 2008 Elsevier B.V. All rights reserved.

Whole crop cereals 1. Effect of method of harvest and preservation on chemical composition, apparent digestibility and energy value

A total of 133 samples (53 fermented unprocessed, 19 fermented processed. 62 urea-treated processed) of whole crop wheat (WCW) and 16 samples (five fermented unprocessed, six fermented processed, five urea-treated processed) of whole crop barley (WCB) were collected from commercial farms over two consecutive years (2003/2004 and 2004/2005). Disruption of the maize grains to increase starch availability was achieved at the point of harvest by processors fitted to the forage harvesters. All samples were subjected to laboratory analysis whilst 50 of the samples (24 front Year 1, 26 front Year 2 all WCW except four WCB in Year 2) were subjected to in vivo digestibility and energy value measurements using mature wether sheep. Urea-treated WCW had higher (P<0.05) pH, and dry matter (DM) and crude protein contents and lower concentrations of fermentation products than fermented WCW. Starch was generally lower in fermented, unprocessed WCW and no effect of crop maturity at harvest (as indicated by DM content) on starch concentrations was seen. Urea-treated WCW had higher (P<0.05) in vivo digestible organic matter contents in the DM (DOMD) in Year 1 although this was not recorded in Year 2. There was a close relationship between the digestibility values of organic matter and gross energy thus aiding the use of DOMD to predict metabolisable energy (ME) content. A wide range of ME values was observed (WCW. 8.7-11.8 MJ/kg DM; WCB 7.9-11.2 MJ/kg DM) with the overall ME/DOMD ratio (ME = 0.0156 DOMD) in line With Studies in other forages. There was no evidence that a separate ME/DOMD relationship was needed for WCB which is helpful for practical application. This ratio and other parameters were affected by year of harvest (P<0.05) highlighting the influence of environmental and Other undefined factors. The variability in the composition and nutritive value of WCW and WCB highlights the need for reliable and accurate evaluation methods to be available to assess the Value of these forages before they are included in diets for dairy cows. (C) 2008 Elsevier B.V. All rights reserved.

Pea-barley intercropping and short-term subsequent crop effects across European organic cropping conditions

Grain legumes are known to increase the soil mineral nitrogen (N) content, reduce the infection pressure of soil borne pathogens, and hence enhance subsequent cereals yields. Replicated field experiments were performed throughout W. Europe (Denmark, United Kingdom, France, Germany and Italy) to asses the effect of intercropping pea and barley on the N supply to subsequent wheat in organic cropping systems. Pea and barley were grown either as sole crops at the recommended plant density (P100 and B100, respectively) or in replacement (P50B50) or additive (P100B50) intercropping designs. In the replacement design the total relative plant density is kept constant, while the additive design uses the optimal sole crop density for pea supplementing with 'extra' barley plants. The pea and barley crops were followed by winter wheat with and without N application. Additional experiments in Denmark and the United Kingdom included subsequent spring wheat with grass-clover as catch crops. The experiment was repeated over the three cropping seasons of 2003, 2004 and 2005. Irrespective of sites and intercrop design pea-barley intercropping improved the plant resource utilization (water, light, nutrients) to grain N yield with 25-30% using the Land Equivalent ratio. In terms of absolute quantities, sole cropped pea accumulated more N in the grains as compared to the additive design followed by the replacement design and then sole cropped barley. The post harvest soil mineral N content was unaffected by the preceding crops. Under the following winter wheat, the lowest mineral N content was generally found in early spring. Variation in soil mineral N content under the winter wheat between sites and seasons indicated a greater influence of regional climatic conditions and long-term cropping history than annual preceding crop and residue quality. Just as with the soil mineral N, the subsequent crop response to preceding crop was negligible. Soil N balances showed general negative values in the 2-year period, indicating depletion of N independent of preceding crop and cropping strategy. It is recommended to develop more rotational approaches to determine subsequent crop effects in organic cropping systems, since preceding crop effects, especially when including legumes, can occur over several years of cropping.

The interrelationships of winter wheat cultivars, crop density and competition of naturally occurring weed flora

The effects of intraspecific and interspecific competition on a wide range of winter wheat cultivars were investigated in two consecutive split plot field experiments. Significant reductions of grain yield at greatly reduced seed rates were observed in the first experiment, whereas increasing crop density up to 380 plants m(-2) in the second experiment failed to produce a significant yield response due to compensation through increased ears and grains per plant at lower crop densities. Appreciable weed suppression and acceptable grain yield can be achieved at crop densities between 150 and 270 plants m(-2). Reductions in final yield due to weed competition occurred in both experiments; 11.7 and 13.6% for the first and second experiment, respectively, with the onset of weed competition occurring from tittering in the first experiment and from stem elongation in the second. The possibility of enhancing crop competitiveness for weed suppression and improved grain yield is discussed.

The role of weeds in supporting biological diversity within crop fields

Weeds are major constraints on crop production, yet as part of the primary producers within farming systems, they may be important components of the agroecosystem. Using published literature, the role of weeds in arable systems for other above-ground trophic levels are examined. In the UK, there is evidence that weed flora have changed over the past century, with some species declining in abundance, whereas others have increased. There is also some evidence for a decline in the size of arable weed seedbanks. Some of these changes reflect improved agricultural efficiency, changes to more winter-sown crops in arable rotations and the use of more broad-spectrum herbicide combinations. Interrogation of a database of records of phytophagous insects associated with plant species in the UK reveals that many arable weed species support a high diversity of insect species. Reductions in abundances of host plants may affect associated insects and other taxa. A number of insect groups and farmland birds have shown marked population declines over the past 30 years. Correlational studies indicate that many of these declines are associated with changes in agricultural practices. Certainly reductions in food availability in winter and for nestling birds in spring are implicated in the declines of several bird species, notably the grey partridge, Perdix perdix . Thus weeds have a role within agroecosystems in supporting biodiversity more generally. An understanding of weed competitivity and the importance of weeds for insects and birds may allow the identification of the most important weed species. This may form the first step in balancing the needs for weed control with the requirements for biodiversity and more sustainable production methods.