Examining the interaction of growing crops with local climate using a coupled crop-climate model

This paper examines to what extent crops and their environment should be viewed as a coupled system. Crop impact assessments currently use climate model output offline to drive process-based crop models. However, in regions where local climate is sensitive to land surface conditions more consistent assessments may be produced with the crop model embedded within the land surface scheme of the climate model. Using a recently developed coupled crop–climate model, the sensitivity of local climate, in particular climate variability, to climatically forced variations in crop growth throughout the tropics is examined by comparing climates simulated with dynamic and prescribed seasonal growth of croplands. Interannual variations in land surface properties associated with variations in crop growth and development were found to have significant impacts on near-surface fluxes and climate; for example, growing season temperature variability was increased by up to 40% by the inclusion of dynamic crops. The impact was greatest in dry years where the response of crop growth to soil moisture deficits enhanced the associated warming via a reduction in evaporation. Parts of the Sahel, India, Brazil, and southern Africa were identified where local climate variability is sensitive to variations in crop growth, and where crop yield is sensitive to variations in surface temperature. Therefore, offline seasonal forecasting methodologies in these regions may underestimate crop yield variability. The inclusion of dynamic crops also altered the mean climate of the humid tropics, highlighting the importance of including dynamical vegetation within climate models.

Soil factors associated with zinc deficiency in crops and humans

Zinc deficiency is the most ubiquitous micronutrient deficiency problem in world crops. Zinc is essential for both plants and animals because it is a structural constituent and regulatory co-factor in enzymes and proteins involved in many biochemical pathways. Millions of hectares of cropland are affected by Zn deficiency and approximately one-third of the human population suffers from an inadequate intake of Zn. The main soil factors affecting the availability of Zn to plants are low total Zn contents, high pH, high calcite and organic matter contents and high concentrations of Na, Ca, Mg, bicarbonate and phosphate in the soil solution or in labile forms. Maize is the most susceptible cereal crop, but wheat grown on calcareous soils and lowland rice on flooded soils are also highly prone to Zn deficiency. Zinc fertilizers are used in the prevention of Zn deficiency and in the biofortification of cereal grains.

Midden cultivation in prehistoric Britain: arable crops in gardens

This paper summarizes some of the geoarchaeological evidence for early arable agriculture in Britain and Europe, and introduces new evidence for small-scale but very intensive cultivation in the Neolithic, Bronze Age and Iron Age in Scotland. The Scottish examples demonstrate that, from the Neolithic to the Iron Age, midden heaps were sometimes ploughed in situ; this means that, rather than spreading midden material onto the fields, the early farmers simply ran an ard over their compost heaps and sowed the resulting plots. The practice appears to have been common in Scotland, and may also have occurred in England. Neolithic cultivation of a Mesolithic midden is suggested, based on thin-section analysis of the middens at Northton, Harris. The fertility of the Mesolithic middens may partly explain why Neolithic farmers re-settled Mesolithic sites in the Northern and Western Isles.

Factors affecting the adoption of leguminous cover crops in Nigeria and a comparison with the adoption of new crop varieties

This paper presents the results of (a) On-farm trials (eight) over a two-year period designed to test the effectiveness of leguminous cover crops in terms of increasing maize yields in Igalaland, Nigeria. (b) A survey designed to monitor the extent of, and reasons behind, adoption of the leguminous cover crop technology in subsequent years by farmers involved, to varying degrees, in the trial programme. particular emphasis was placed on comparing adoption of leguminous cover crops with that of new crop varieties released by a non-governmental organization in the same area since the mid 1980s. While the leguminous cover crop technology boosted maize grain yields by 127 to 136% above an untreated control yield of between 141 and 171 kg ha(-1), the adoption rate (number of farmers adopting) was only 18%. By way of contrast, new crop varieties had a highly variable benefit in terms of yield advantage over local varieties, with the best average increase of around 20%. Adoption rates for new crop varieties, assessed as both the number of farmers growing the varieties and the number of plots planted to the varieties, were 40% on average. The paper discusses some key factors influencing adoption of the leguminous cover crop technology, including seed availability. Implications of these results for a local non-governmental organization, the Diocesan Development Services, concerned with promoting the leguminous cover crop technology are also discussed.

Phenolic contents of lettuce, strawberry, raspberry, and blueberry crops cultivated under plastic films varying in ultraviolet transparency

The levels of health-related phytochemicals were determined in lettuce leaf and in strawberry, raspberry and blueberry fruits grown in near-commercial conditions under plastic films of three different UV transparencies. In the red lettuce Lollo Rosso, total phenolics, anthocyanin, luteolin and quercetin levels were all raised by changing from a UV blocking film to a film of low UV transparency, and to a film of high UV transparency. The related green lettuce, Lollo Biondo, cultivated under the same conditions, showed virtually no phytochemical responses to the same variation in UV levels. Overall, the phenolic levels of strawberries, raspberries, and blueberries were unresponsive to the UV transparency of the plastic film under which the crops were grown. The significance of these findings is discussed in relation to the nutritional quality of soft fruit and salad crops which are increasingly being grown commercially under plastic tunnels.

Transgenic crops: the current and next generations.

This chapter describes the present status and future prospects for transgenic (genetically modified) crops. It concentrates on the most recent data obtained from patent databases and field trial applications, as well as the usual scientific literature. By these means, it is possible to obtain a useful perspective into future commercial products and international trends. The various research areas are subdivided on the basis of those associated with input (agronomic) traits and those concerned with output (e.g., food quality) characteristics. Among the former group are new methods of improving stress resistance, and among the latter are many examples of producing pharmaceutical compounds in plants.

Landscape context and habitat type as drivers of bee diversity in European annual crops

To better understand the dynamics of bee populations in crops, we assessed the effect of landscape context and habitat type on bee communities in annual entomophilous crops in Europe. We quantified bee communities in five pairs of crop-country: buckwheat in Poland, cantaloupe in France, field beans in the UK, spring oilseed rape in Sweden, and strawberries in Germany. For each country, 7-10 study fields were sampled over a gradient of increasing proportion of semi-natural habitats in the surrounding landscape. The CORINE land cover classification was used to characterize the landscape over a 3 km radius around each study field and we used multivariate and regression analyses to quantify the impact of landscape features on bee abundance and diversity at the sub-generic taxonomic level. Neither overall wild bee abundance nor diversity, taken as the number of sub-genera. was significantly affected by the proportion of semi-natural habitat. Therefore, we used the most precise level of the CORINE classification to examine the possible links between specific landscape features and wild bee communities. Bee community composition fell into three distinct groups across Europe: group I included Poland, Germany, and Sweden, group 2 the UK, and group 3 France. Among all three groups, wild bee abundance and sub-generic diversity were affected by 17 landscape elements including some semi-natural habitats (e.g., transitional wood land-shrub), some urban habitats (e.g., sport and leisure facilities) and some crop habitats (e.g., non-irrigated arable land). Some bee taxa were positively affected by urban habitats only, others by semi-natural habitats only, and others by a combination of semi-natural, urban and crop habitats. Bee sub-genera favoured by urban and crop habitats were more resistant to landscape change than those favoured only by semi-natural habitats. In agroecosystems, the agricultural intensification defined as the loss of semi-natural habitats does not necessarily cause a decline in evenness at the local level, but can change community composition towards a bee fauna dominated by common taxa. (C) 2009 Elsevier B.V. All rights reserved.

Landscape gene flow, coexistence and threshold effect: The case of genetically modified herbicide tolerant oilseed rape (Brassica napus)

Globally there have been a number of concerns about the development of genetically modified crops many of which relate to the implications of gene flow at various levels. In Europe these concerns have led the European Union (EU) to promote the concept of 'coexistence' to allow the freedom to plant conventional and genetically modified (GM) varieties but to minimise the presence of transgenic material within conventional crops. Should a premium for non-GM varieties emerge on the market, the presence of transgenes would generate a 'negative externality' to conventional growers. The establishment of maximum tolerance level for the adventitious presence of GM material in conventional crops produces a threshold effect in the external costs. The existing literature suggests that apart from the biological characteristics of the plant under consideration (e.g. self-pollination rates, entomophilous species, anemophilous species, etc.), gene flow at the landscape level is affected by the relative size of the source and sink populations and the spatial arrangement of the fields in the landscape. In this paper, we take genetically modified herbicide tolerant oilseed rape (GM HT OSR) as a model crop. Starting from an individual pollen dispersal function, we develop a spatially explicit numerical model in order to assess the effect of the size of the source/sink populations and the degree of spatial aggregation on the extent of gene flow into conventional OSR varieties under two alternative settings. We find that when the transgene presence in conventional produce is detected at the field level, the external cost will increase with the size of the source area and with the level of spatial disaggregation. on the other hand when the transgene presence is averaged among all conventional fields in the landscape (e.g. because of grain mixing before detection), the external cost will only depend on the relative size of the source area. The model could readily be incorporated into an economic evaluation of policies to regulate adoption of GM HT OSR. (c) 2007 Elsevier B.V. All rights reserved.

Use of a crop model ensemble to quantify CO2 stimulation of water-stressed and well-watered crops

Increased atmospheric concentrations of carbon dioxide (CO2) will benefit the yield of most crops. Two free air CO2 enrichment (FACE) meta-analyses have shown increases in yield of between 0 and 73% for C3 crops. Despite this large range, few crop modelling studies quantify the uncertainty inherent in the parameterisation of crop growth and development. We present a novel perturbed-parameter method of crop model simulation, which uses some constraints from observations, that does this. The model used is the groundnut (i.e. peanut; Arachis hypogaea L.) version of the general large-area model for annual crops (GLAM). The conclusions are of relevance to C3 crops in general. The increases in yield simulated by GLAM for doubled CO2 were between 16 and 62%. The difference in mean percentage increase between well-watered and water-stressed simulations was 6.8. These results were compared to FACE and controlled environment studies, and to sensitivity tests on two other crop models of differing levels of complexity: CROPGRO, and the groundnut model of Hammer et al. [Hammer, G.L., Sinclair, T.R., Boote, K.J., Wright, G.C., Meinke, H., Bell, M.J., 1995. A peanut simulation model. I. Model development and testing. Agron. J. 87, 1085-1093]. The relationship between CO2 and water stress in the experiments and in the models was examined. From a physiological perspective, water-stressed crops are expected to show greater CO2 stimulation than well-watered crops. This expectation has been cited in literature. However, this result is not seen consistently in either the FACE studies or in the crop models. In contrast, leaf-level models of assimilation do consistently show this result. An analysis of the evidence from these models and from the data suggests that scale (canopy versus leaf), model calibration, and model complexity are factors in determining the sign and magnitude of the interaction between CO2 and water stress. We conclude from our study that the statement that 'water-stressed crops show greater CO2 stimulation than well-watered crops' cannot be held to be universally true. We also conclude, preliminarily, that the relationship between water stress and assimilation varies with scale. Accordingly, we provide some suggestions on how studies of a similar nature, using crop models of a range of complexity, could contribute further to understanding the roles of model calibration, model complexity and scale. (C) 2008 Elsevier B.V. All rights reserved.

Adaptation of crops to climate change through genotypic responses to mean and extreme temperatures

The importance of temperature in the determination of the yield of an annual crop (groundnut; Arachis hypogaea L. in India) was assessed. Simulations from a regional climate model (PRECIS) were used with a crop model (GLAM) to examine crop growth under simulated current (1961-1990) and future (2071-2100) climates. Two processes were examined: the response of crop duration to mean temperature and the response of seed-set to extremes of temperature. The relative importance of, and interaction between, these two processes was examined for a number of genotypic characteristics, which were represented by using different values of crop model parameters derived from experiments. The impact of mean and extreme temperatures varied geographically, and depended upon the simulated genotypic properties. High temperature stress was not a major determinant of simulated yields in the current climate, but affected the mean and variability of yield under climate change in two regions which had contrasting statistics of daily maximum temperature. Changes in mean temperature had a similar impact on mean yield to that of high temperature stress in some locations and its effects were more widespread. Where the optimal temperature for development was exceeded, the resulting increase in duration in some simulations fully mitigated the negative impacts of extreme temperatures when sufficient water was available for the extended growing period. For some simulations the reduction in mean yield between the current and future climates was as large as 70%, indicating the importance of genotypic adaptation to changes in both means and extremes of temperature under climate change. (c) 2006 Elsevier B.V. All rights reserved.

Design and optimisation of a large-area process-based model for annual crops

The formulation of a new process-based crop model, the general large-area model (GLAM) for annual crops is presented. The model has been designed to operate on spatial scales commensurate with those of global and regional climate models. It aims to simulate the impact of climate on crop yield. Procedures for model parameter determination and optimisation are described, and demonstrated for the prediction of groundnut (i.e. peanut; Arachis hypogaea L.) yields across India for the period 1966-1989. Optimal parameters (e.g. extinction coefficient, transpiration efficiency, rate of change of harvest index) were stable over space and time, provided the estimate of the yield technology trend was based on the full 24-year period. The model has two location-specific parameters, the planting date, and the yield gap parameter. The latter varies spatially and is determined by calibration. The optimal value varies slightly when different input data are used. The model was tested using a historical data set on a 2.5degrees x 2.5degrees grid to simulate yields. Three sites are examined in detail-grid cells from Gujarat in the west, Andhra Pradesh towards the south, and Uttar Pradesh in the north. Agreement between observed and modelled yield was variable, with correlation coefficients of 0.74, 0.42 and 0, respectively. Skill was highest where the climate signal was greatest, and correlations were comparable to or greater than correlations with seasonal mean rainfall. Yields from all 35 cells were aggregated to simulate all-India yield. The correlation coefficient between observed and simulated yields was 0.76, and the root mean square error was 8.4% of the mean yield. The model can be easily extended to any annual crop for the investigation of the impacts of climate variability (or change) on crop yield over large areas. (C) 2004 Elsevier B.V. All rights reserved.