Effects of agricultural management practices on earthworm populations and crop yield: validation and application of a mechanistic modelling approach

There is little consensus on how agriculture will meet future food demands sustainably. Soils and their biota play a crucial role by mediating ecosystem services that support agricultural productivity. However, a multitude of site-specific environmental factors and management practices interact to affect the ability of soil biota to perform vital functions, confounding the interpretation of results from experimental approaches. Insights can be gained through models, which integrate the physiological, biological and ecological mechanisms underpinning soil functions. We present a powerful modelling approach for predicting how agricultural management practices (pesticide applications and tillage) affect soil functioning through earthworm populations. By combining energy budgets and individual-based simulation models, and integrating key behavioural and ecological drivers, we accurately predict population responses to pesticide applications in different climatic conditions. We use the model to analyse the ecological consequences of different weed management practices. Our results demonstrate that an important link between agricultural management (herbicide applications and zero, reduced and conventional tillage) and earthworms is the maintenance of soil organic matter (SOM). We show how zero and reduced tillage practices can increase crop yields while preserving natural ecosystem functions. This demonstrates how management practices which aim to sustain agricultural productivity should account for their effects on earthworm populations, as their proliferation stimulates agricultural productivity. Synthesis and applications. Our results indicate that conventional tillage practices have longer term effects on soil biota than pesticide control, if the pesticide has a short dissipation time. The risk of earthworm populations becoming exposed to toxic pesticides will be reduced under dry soil conditions. Similarly, an increase in soil organic matter could increase the recovery rate of earthworm populations. However, effects are not necessarily additive and the impact of different management practices on earthworms depends on their timing and the prevailing environmental conditions. Our model can be used to determine which combinations of crop management practices and climatic conditions pose least overall risk to earthworm populations. Linking our model mechanistically to crop yield models would aid the optimization of crop management systems by exploring the trade-off between different ecosystem services.

Effects of superficial liming and silicate application on soil fertility and crop yield under rotation

Soil acidity and low natural fertility are the main problems for grain production in Brazilian 'cerrado'. Although lime has been the most applied source for soil correction, silicate may be an alternative material due to its lower solubility and Si supply, which is beneficial to several crops. This work aimed to evaluate the efficiency of superficial liming and calcium/magnesium silicate application on soil chemical attributes, plant nutrition, yield components and final yield of a soybean/white oat/maize/bean rotation under no-tillage system in a dry-winter region. The experiment was conducted under no tillage system in a deep acid clayey Rhodic Hapludox, Botucatu-SP, Brazil. The design was the completely randomized block with sixteen replications. Treatments consisted of two sources for soil acidity correction (dolomitic lime: ECC=90%, CaO=36% and MgO=12%; calcium/magnesium silicate: ECC=80%, CaO=34%, MgO=10% and SiO2=22%) applied in October 2006 to raise base saturation up to 70% and a control, with no soil correction. Soybean and white oat were sown in 2006/2007 as the main crop and off-season, respectively. Maize and bean were cropped in the next year (2007/2008). Products from silicate dissociation reach deeper soil layers after 18months from the application, compared to liming. Additionally, silicate is more efficient than lime to increasing phosphorus availability and reducing toxic aluminum. Such benefits in soil chemical attributes were only evidenced during bean cropping, when grain yield was higher after silicate application comparatively to liming. Both correction sources were improved mineral nutrition of all the other crops, mainly Ca and Mg levels and agronomical characteristics, reflecting in higher yield. © 2012 Elsevier B.V.

Crop Yield Responses to Temperature Fluctuations in 19th Century Finland: Provincial Variation in Relation to Climate and Tree Rings

Past agricultural responses to climate variability can helps us to better understand the current and future impacts of climate change on agricultural production. We studied rye (Secale cereale) and barley (Hordeum vulgare) yield responses to temperature fluctuations in Finland during the period 1861–1913. Our analyses demonstrate the high sensitivity of non-industrialised northern agriculture to temperature anomalies. We found evidence of a strong relationship between monthly and seasonal mean temperatures and crop yields. In particular, high spring temperatures were associated with higher yields. Additionally, we tested temperature-sensitive tree-ring series for their value in indicating previous agricultural outputs. The results imply that tree-ring proxies (in particular, maximum latewood density) can provide novel material for studies of historical periods and locations where instrumentally measured climate and harvest data are not available.

Meta-analysis of strategies to control nitrate leaching in irrigated agricultural systems and their effects on crop yield.

Nitrate leaching (NL) is an important N loss process in irrigated agriculture that imposes a cost on the farmer and the environment. A meta-analysis of published experimental results from agricultural irrigated systems was conducted to identify those strategies that have proven effective at reducing NL and to quantify the scale of reduction that can be achieved. Forty-four scientific articles were identified which investigated four main strategies (water and fertilizer management, use of cover crops and fertilizer technology) creating a database with 279 observations on NL and 166 on crop yield. Management practices that adjust water application to crop needs reduced NL by a mean of 80% without a reduction in crop yield. Improved fertilizer management reduced NL by 40%, and the best relationship between yield and NL was obtained when applying the recommended fertilizer rate. Replacing a fallow with a non-legume cover crop reduced NL by 50% while using a legume did not have any effect on NL. Improved fertilizer technology also decreased NL but was the least effective of the selected strategies. The risk of nitrate leaching from irrigated systems is high, but optimum management practices may mitigate this risk and maintain crop yields while enhancing environmental sustainability.

Sulfuric acid rain effects on crop yield and foliar injury /

Mode of access: Internet.

Kenaf leaf development and stem height : index of crop yield in the United States /

Data collected 1961-69.

Root behavior and crop yield under irrigation,

Mode of access: Internet.

Adapting wheat sowing dates to projected climate change in the Australian subtropics: analysis of crop water use and yield

Projected increases in atmospheric carbon dioxide concentration ([CO2]) and air temperature associated with future climate change are expected to affect crop development, crop yield, and, consequently, global food supplies. They are also likely to change agricultural production practices, especially those related to agricultural water management and sowing date. The magnitude of these changes and their implications to local production systems are mostly unknown. The objectives of this study were to: (i) simulate the effect of projected climate change on spring wheat (Triticum aestivum L. cv. Lang) yield and water use for the subtropical environment of the Darling Downs, Queensland, Australia; and (ii) investigate the impact of changing sowing date, as an adaptation strategy to future climate change scenarios, on wheat yield and water use. The multimodel climate projections from the IPCC Coupled Model Intercomparison Project (CMIP3) for the period 2030–2070 were used in this study. Climate scenarios included combinations of four changes in air temperature (08C, 18C, 28C, and 38C), three [CO2] levels (380 ppm, 500 ppm, and 600 ppm), and three changes in rainfall (–30%, 0%, and +20%), which were superimposed on observed station data. Crop management scenarios included a combination of six sowing dates (1 May, 10 May, 20 May, 1 June, 10 June, and 20 June) and three irrigation regimes (no irrigation (NI), deficit irrigation (DI), and full irrigation (FI)). Simulations were performed with the model DSSAT4.5, using 50 years of daily weather data.Wefound that: (1) grain yield and water-use efficiency (yield/evapotranspiration) increased linearly with [CO2]; (2) increases in [CO2] had minimal impact on evapotranspiration; (3) yield increased with increasing temperature for the irrigated scenarios (DI and FI), but decreased for the NI scenario; (4) yield increased with earlier sowing dates; and (5) changes in rainfall had a small impact on yield for DI and FI, but a high impact for the NI scenario.

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.

Modified crop model estimation of depleted and potential soybean yield

Despite the great importance of soybeans in Brazil, there have been few applications of soybean crop modeling on Brazilian conditions. Thus, the objective of this study was to use modified crop models to estimate the depleted and potential soybean crop yield in Brazil. The climatic variable data used in the modified simulation of the soybean crop models were temperature, insolation and rainfall. The data set was taken from 33 counties (28 Sao Paulo state counties, and 5 counties from other states that neighbor São Paulo). Among the models, modifications in the estimation of the leaf area of the soybean crop, which includes corrections for the temperature, shading, senescence, CO2, and biomass partition were proposed; also, the methods of input for the model's simulation of the climatic variables were reconsidered. The depleted yields were estimated through a water balance, from which the depletion coefficient was estimated. It can be concluded that the adaptation soybean growth crop model might be used to predict the results of the depleted and potential yield of soybeans, and it can also be used to indicate better locations and periods of tillage.

Temperature and precipitation effects on wheat yield across a European transect: a crop model ensemble analysis using impact response surfaces

This study explored the utility of the impact response surface (IRS) approach for investigating model ensemble crop yield responses under a large range of changes in climate. IRSs of spring and winter wheat Triticum aestivum yields were constructed from a 26-member ensemble of process-based crop simulation models for sites in Finland, Germany and Spain across a latitudinal transect. The sensitivity of modelled yield to systematic increments of changes in temperature (-2 to +9°C) and precipitation (-50 to +50%) was tested by modifying values of baseline (1981 to 2010) daily weather, with CO2 concentration fixed at 360 ppm. The IRS approach offers an effective method of portraying model behaviour under changing climate as well as advantages for analysing, comparing and presenting results from multi-model ensemble simulations. Though individual model behaviour occasionally departed markedly from the average, ensemble median responses across sites and crop varieties indicated that yields decline with higher temperatures and decreased precipitation and increase with higher precipitation. Across the uncertainty ranges defined for the IRSs, yields were more sensitive to temperature than precipitation changes at the Finnish site while sensitivities were mixed at the German and Spanish sites. Precipitation effects diminished under higher temperature changes. While the bivariate and multi-model characteristics of the analysis impose some limits to interpretation, the IRS approach nonetheless provides additional insights into sensitivities to inter-model and inter-annual variability. Taken together, these sensitivities may help to pinpoint processes such as heat stress, vernalisation or drought effects requiring refinement in future model development.

Cultivar-specific effects of pathogen testing on storage root yield of sweet potato, Ipomoea batatas (L.) Lam.

The accumulation and perpetuation of viral pathogens over generations of clonal propagation in crop species such as sweet potato, Ipomoea batatas,inevitably result in a reduction in crop yield and quality. This study was conducted at Bundaberg, Australia to compare the productivity of field-derived and pathogen-tested (PT)clones of 14 sweet potato cultivars and the yield benefits of using healthy planting materials. The field-derived clonal materials were exposed to the endemic viruses, while the PT clones were subjected to thermotherapy and meristem-tip culture to eliminate viral pathogens. The plants were indexed for viruses using nitrocellulose membrane-enzyme-linked immunosorbent assay and graft-inoculations onto Ipomoea setosa. A net benefit of 38% in storage root yield was realised from using PT materials in this study.Conversely, in a similar study previously conducted at Kerevat, Papua New Guinea (PNG), a net deficit of 36% was realised. This reinforced our finding that the response to pathogen testing was cultivar dependent and that the PNG cultivars in these studies generally exhibited increased tolerance to the endemic viruses present at the respective trial sites as manifested in their lack of response from the use of PT clones. They may be useful sources for future resistance breeding efforts. Nonetheless, the potential economic gain from using PT stocks necessitates the use of pathogen testing on virus-susceptible commercial cultivars.

Analysis of high yielding maize production - A study based on a commercial crop

This paper reports on the use of APSIM - Maize for retrospective analysis of performance of a high input, high yielding maize crop and analysis of predicted performance of maize grown with high inputs over the long-term (>100 years) for specified scenarios of environmental conditions (temperature and radiation) and agronomic inputs (sowing date, plant population, nitrogen fertiliser and irrigation) at Boort, Victoria, Australia. It uses a high yielding (17 400 kg/ha dry grain, 20 500 kg/ha at 15% water) commercial crop grown in 2004-05 as the basis of the study. Yield for the agronomic and environmental conditions of 2004-05 was predicted accurately, giving confidence that the model could be used for the detailed analyses undertaken. The analysis showed that the yield achieved was close to that possible with the conditions and agronomic inputs of 2004-05. Sowing dates during 21 September to 26 October had little effect on predicted yield, except when combined with reduced temperature. Single year and long-term analyses concluded that a higher plant population (11 plants/m2) is needed to optimise yield, but that slightly lower N and irrigation inputs are appropriate for the plant population used commercially (8.4 plants/m2). Also, compared with changes in agronomic inputs increases in temperature and/or radiation had relatively minor effects, except that reduced temperature reduces predicted yield substantially. This study provides an approach for the use of models for both retrospective analysis of crop performance and assessment of long-term variability of crop yield under a wide range of agronomic and environmental conditions.

Estimating crop area using seasonal time series of enhanced vegetation index from MODIS satellite imagery

Cereal grain is one of the main export commodities of Australian agriculture. Over the past decade, crop yield forecasts for wheat and sorghum have shown appreciable utility for industry planning at shire, state, and national scales. There is now an increasing drive from industry for more accurate and cost-effective crop production forecasts. In order to generate production estimates, accurate crop area estimates are needed by the end of the cropping season. Multivariate methods for analysing remotely sensed Enhanced Vegetation Index (EVI) from 16-day Moderate Resolution Imaging Spectroradiometer (MODIS) satellite imagery within the cropping period (i.e. April-November) were investigated to estimate crop area for wheat, barley, chickpea, and total winter cropped area for a case study region in NE Australia. Each pixel classification method was trained on ground truth data collected from the study region. Three approaches to pixel classification were examined: (i) cluster analysis of trajectories of EVI values from consecutive multi-date imagery during the crop growth period; (ii) harmonic analysis of the time series (HANTS) of the EVI values; and (iii) principal component analysis (PCA) of the time series of EVI values. Images classified using these three approaches were compared with each other, and with a classification based on the single MODIS image taken at peak EVI. Imagery for the 2003 and 2004 seasons was used to assess the ability of the methods to determine wheat, barley, chickpea, and total cropped area estimates. The accuracy at pixel scale was determined by the percent correct classification metric by contrasting all pixel scale samples with independent pixel observations. At a shire level, aggregated total crop area estimates were compared with surveyed estimates. All multi-temporal methods showed significant overall capability to estimate total winter crop area. There was high accuracy at pixel scale (>98% correct classification) for identifying overall winter cropping. However, discrimination among crops was less accurate. Although the use of single-date EVI data produced high accuracy for estimates of wheat area at shire scale, the result contradicted the poor pixel-scale accuracy associated with this approach, due to fortuitous compensating errors. Further studies are needed to extrapolate the multi-temporal approaches to other geographical areas and to improve the lead time for deriving cropped-area estimates before harvest.

Cultivar-specific effects of pathogen testing on storage root yield of sweetpotato, Ipomoea batatas.

The accumulation and perpetuation of viral pathogens over generations of clonal propagation in crop species such as sweetpotato, Ipomoea batatas, inevitably result in a reduction in crop yield and quality. This study was conducted at Bundaberg, Australia to compare the productivity of field-derived and pathogen-tested (PT) clones of 14 sweetpotato cultivars and the yield benefits of using healthy planting materials. The field-derived clonal materials were exposed to the endemic viruses, while the PT clones were subjected to thermotherapy and meristem-tip culture to eliminate viral pathogens. The plants were indexed for viruses using nitrocellulose membrane-enzyme-linked immunosorbent assay and graft-inoculations onto Ipomoea setosa. A net benefit of 38% in storage root yield was realised from using PT materials in this study. Conversely, in a similar study previously conducted at Kerevat, Papua New Guinea (PNG), a net deficit of 36% was realised. This reinforced our finding that the response to pathogen testing was cultivar dependent and that the PNG cultivars in these studies generally exhibited increased tolerance to the endemic viruses present at the respective trial sites as manifested in their lack of response from the use of PT clones. They may be useful sources for future resistance breeding efforts. Nonetheless, the potential economic gain from using PT stocks necessitates the use of pathogen testing on virus-susceptible commercial cultivars. .