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

Postglacial soil formation in the loess of pegwell bay, kent (england)

Seven samples, representative of all zones of the Upper Chalk in the Arundel area of Sussex, were treated with acetic acid and the residues analysed to determine their mechanical and mineralogical compositions. The sand and silt fractions of the residues consist mainly of flint and opaline silica, collo- phane, limonite, and quartz, and the' clay fractions consist of montmorillonite, mica, quartz, and apatite. Authigenic apatite and quartz occur in the clay and silt and authigenic alkali feldspar in the silt. The montmorillonite may also be authigenic. A necessary preliminary to any investigation of drift deposits or soils on the English Chalk is a knowledge of the composition of the insoluble residue of the Chalk left after dissolution under atmospheric conditions. The early work of Hume (1893) and Double (1927) on the Chalk of the south coast of England and East Anglia respec- tively, showed that HCl-insoluble residues were composed almost entirely of clay, and that the small amounts of sand contained limonite, pyrite, glauconite, and a range of detrital minerals including quartz, feldspar, zircon, tourmaline, mica, garnet, hornblende, rutile, chlorite, augite, chalcedony, magnetite, jasper, epidote, andalu- site, staurolite, sphene, and kyanite. In addition to these minerals Cayeux (1890, 1891a, b, 1897) recorded anatase, brookite, apatite, and corundum in the Chalk of northern France. The use of hydrochloric acid, even in very dilute solution, is liable to remove minerals that might be expected in natural chalk residues; for this reason, Perrin (1956, 1957, 1964) and Avery et al. (1959) used buffered acetic acid. Both made accurate mechanical analyses of the residues and showed that montmorillonite and mica are the dominant constituents of the insoluble clay fraction. Brown & Oilier (1956) used the same treatment for samples of Middle and Upper Chalk from the Chilterns and found abundant collophane in the sand fraction and an apatite-like mineral in the silt and clay. Young (1965) identified mont- morillonite, illite, kaolinite, chlorite (or vermiculite), and apatite in the clay fractions of acetic acid-insoluble residues from the Lower Chalk of the Leatherhead (Fetcham Mill) borehole, but found only montmoriUonite, illite, and apatite in the Middle and Upper Chalk.

The mineralogy of some upper chalk samples from the arundel area, sussex

Summary
Clay-with-flints rests on remnants of the exhumed sub-Eocene surface, which is shown to be an important geomorphological feature of the West Sussex Downs. Mineralogical and other soil profile studies indicate that the deposit has developed by the action of cryoturbation and soil-forming processes on a thin cover of Reading Beds clay left on the sub-Eocene surface during the southward recession of a small Eocene escarpment. Two horizons corresponding to Clay-with-flints sensu stricto of Loveday (1962) are recognized. The basal horizon is composed partly of insoluble Chalk residue, but mainly of clay moved down from overlying horizons into the spaces left on dissolution of the Chalk at the junction of the Chalk with the base of the Clay-with-flints. The upper horizon is composed of material from weathered remnants of Reading Beds clay, thoroughly mixed by cryoturbation with flints, other insoluble Chalk residue and clay from former basal horizons. The surface horizons of the soils often include additions of loess.

The origin and development of clay-with-flints and associated soil horizons on the south downs

Summary

Thin silty deposits cover large areas of north-east Norfolk, occurring mainly on gently sloping and flat plateau sites and on the floors of valleys cut in the glacial deposits. Particle size and geographic distribution of the deposits suggest that the silt is windblown. The mineralogical composition of the silt fraction resembles that of the silt of Hunstanton Till, suggesting that most of the deposit was derived as loess from outwash of the Weichselian glacier. However, at some localities the sand and clay components of the deposits were derived, at least partly, from subjacent glacial sediments of pre-Weichselian age. The distribution of the silty deposits strongly affects the pattern of soil types and sometimes the growth of crops.

A. H. Weir

Papers

A winter wheat crop simulation model without water or nutrient limitations

Postglacial soil formation in the loess of pegwell bay, kent (england)

The mineralogy of some upper chalk samples from the arundel area, sussex

The origin and development of clay-with-flints and associated soil horizons on the south downs

Loess in the soils of north norfolk