Crop models are essential tools for assessing the threat of climate change to local and global food production(1). Present models used to predict wheat grain yield are highly uncertain when simulating how crops respond to temperature(2). Here we systematically tested 30 different wheat crop models of the Agricultural Model Intercomparison and Improvement Project against field experiments in which growing season mean temperatures ranged from 15 degrees C to 32 degrees C, including experiments with artificial heating. Many models simulated yields well, but were less accurate at higher temperatures. The model ensemble median was consistently more accurate in simulating the crop temperature response than any single model, regardless of the input information used. Extrapolating the model ensemble temperature response indicates that warming is already slowing yield gains at a majority of wheat-growing locations. Global wheat production is estimated to fall by 6% for each degrees C of further temperature increase and become more variable over space and time.

Rising Temperatures Reduce Global Wheat Production

https://digitalcommons.unl.edu/cgi/viewcontent.cgi?article=1086&context=usdaarsfacpub

Growing degree-days: one equation, two interpretations

In order to better assess the role of agriculture within the global climate-vegetation system, we present a model of the managed planetary land surface, Lund-Potsdam-Jena managed Land (LPJmL), which simulates biophysical and biogeochemical processes as well as productivity and yield of the most important crops worldwide, using a concept of crop functional types (CFTs). Based on the LPJ-Dynamic Global Vegetation Model, LPJmL simulates the transient changes in carbon and water cycles due to land use, the specific phenology and seasonal CO2 fluxes of agricultural-dominated areas, and the production of crops and grazing land. It uses 13 CFTs (11 arable crops and two managed grass types), with specific parameterizations of phenology connected to leaf area development. Carbon is allocated daily towards four carbon pools, one being the yield-bearing storage organs. Management (irrigation, treatment of residues, intercropping) can be considered in order to capture their effect on productivity, on soil organic carbon and on carbon extracted from the ecosystem. For transient simulations for the 20th century, a global historical land use data set was developed, providing the annual cover fraction of the 13 CFTs, rain-fed and/or irrigated, within 0.5 degrees grid cells for the period 1901-2000, using published data on land use, crop distributions and irrigated areas. Several key results are compared with observations. The simulated spatial distribution of sowing dates for temperate cereals is comparable with the reported crop calendars. The simulated seasonal canopy development agrees better with satellite observations when actual cropland distribution is taken into account. Simulated yields for temperate cereals and maize compare well with FAO statistics. Monthly carbon fluxes measured at three agricultural sites also compare well with simulations. Global simulations indicate a similar to 24% (respectively similar to 10%) reduction in global vegetation (respectively soil) carbon due to agriculture, and 6-9 Pg C of yearly harvested biomass in the 1990s. In contrast to simulations of the potential natural vegetation showing the land biosphere to be an increasing carbon sink during the 20th century, LPJmL simulates a net carbon source until the 1970s (due to land use), and a small sink (mostly due to changing climate and CO2) after 1970. This is comparable with earlier LPJ simulations using a more simple land use scheme, and within the uncertainty range of estimates in the 1980s and 1990s. The fluxes attributed to land use change compare well with Houghton's estimates on the land use related fluxes until the 1970s, but then they begin to diverge, probably due to the different rates of deforestation considered. The simulated impacts of agriculture on the global water cycle for the 1990s are similar to 5% (respectively similar to 20%) reduction in transpiration (respectively interception), and similar to 44% increase in evaporation. Global runoff, which includes a simple irrigation scheme, is practically not affected. (Less)

Modelling the role of agriculture for the 20th century global terrestrial carbon balance

An overview of the crop model STICS

Temperatures and the growth and development of wheat: a review

A whole crop computer simulation model of winter wheat has been written in FORTRAN and used to simulate the growth of September- and October-sown crops of Hustler wheat at Rothamsted for the years 1978–9, 1979–80 and 1980–1. Results of the simulations, which are for crops with adequate water and nutrients, are compared with observations from experiments at Rothamsted. The model uses daily maximum and minimum temperatures and daylength to calculate the dates of emergence, double ridge, anthesis and maturity of the crops and the growth and senescence of tillers and leaves. In the simulations, the canopy intercepts daily radiation and produces dry matter that is partitioned between roots, shoots, leaves, ears and grain. Partial simulations, using observed LAI values, produced dry matter in close agreement with observations of late-sown crops, but consistently overestimated the total dry-matter production of the early-sown crops. Full simulation described satisfactorily the average difference in dry-matter production to be expected with changes in time of sowing, but did not give as close correspondence for individual crops. A grain growth submodel, that linked maximum grain weight to average temperatures during the grain growth period, correctly simulated the observed growth of individual grains in the 1981 crop. The benefits to be obtained by combining whole crop modelling with detailed crop observations are discussed.

https://www.cambridge.org/core/services/aop-cambridge-core/content/view/S0021859600042702

A winter wheat crop simulation model without water or nutrient limitations

Four methods of measuring root distribution in a spring oat crop were compared: minirhizotrons installed vertically, minirhizotrons installed at an angle of 45°, core-break root counts and direct measurement of lengths of root washed from soil cores.

A comparison of methods, including angled and vertical minirhizotrons, for studying root growth and distribution in a spring oat crop

SUMMARY In a field experiment where winter wheat and winter barley were sown on the same date, the patterns of root growth of the two species were similar, with a few roots reaching a depth of at least 120 cm. Roots senesced sooner in barley, in association with earlier maturity of the shoots and grain. The number of shoots and leaf area index of the barley were greater than for the wheat, but rates of dry-matter production until anthesis of the barley were similar in both species. The grain yield of wheat was about 10% heavier than for barley. Where chlormequat had been applied in early December at the 3- to 4-leaf stage, when shoot apices of both species were still vegetative, root density of the winter wheat in the following March and April was slightly greater than for untreated plants, but the difference disappeared later. For winter barley there was no effect of chlormequat on root growth until July when root length tended to be greater at depth after the chlormequat treatment. The chlormequat treatment significantly shortened stem length, but did not significantly affect the number of shoots, crop dry weight or grain yield of either species.

A comparison of the root and shoot growth of winter barley and winter wheat, and the effect of an early application of chlormequat

Opportunities for manipulation of cereal productivity

Grain yield of winter barley in the year preceding the experiment (1978) was relatively uniform over the site. In 1978–9 after the drainage treatments had been introduced, growth and yield of winter wheat were not affected by drainage, probably due to a compact layer at 20 cm that prevented the mole drains from controlling the water table (Harris et al. 1984).In 1979–80 after disrupting this layer, root growth in undrained plots during the winter and spring was severely restricted by the presence of a water table 20 cm from the soil surface, although some root axes were able to grow down to 75–100 cm below the soil surface. The differences in root distribution patterns between drained and undrained plots disappeared after the water table declined in April. Uptake of nitrogen, phosphorus and potassium were less on undrained plots. Dry-matter production, leaf area index and peak number of tillers was also depressed, so that the yield of winter wheat was 0·74 t/ha greater on the drained treatment; the grain from the drained plots contained fewer impurities and weed seeds.

P. L. Bragg

Papers

A winter wheat crop simulation model without water or nutrient limitations

A comparison of methods, including angled and vertical minirhizotrons, for studying root growth and distribution in a spring oat crop

A comparison of the root and shoot growth of winter barley and winter wheat, and the effect of an early application of chlormequat

Opportunities for manipulation of cereal productivity

A study of mole drainage with simplified cultivation for autumn-sown crops on a clay soil: 3. Agronomy, root and shoot growth of winter wheat, 1978–80