Development of a data-assimilation system to forecast agricultural systems: A case study of constraining soil water and soil nitrogen dynamics in the APSIM model

As we face today\u27s large-scale agricultural issues, the need for robust methods of agricultural forecasting has never been clearer. Yet, the accuracy and precision of our forecasts remains limited by current tools and methods. To overcome the limitations of process-based models and observed data, we iteratively designed and tested a generalizable and robust data-assimilation system that systematically constrains state variables in the APSIM model to improve forecast accuracy and precision. Our final novel system utilizes the Ensemble Kalman Filter to constrain model states and update model parameters at observed time steps and incorporates an algorithm that improves system performance through the joint estimation of system error matrices. We tested this system at the Energy Farm, a well-monitored research site in central Illinois, where we assimilated observed in situ soil moisture at daily time steps for two years and evaluated how assimilation impacted model forecasts of soil moisture, yield, leaf area index, tile flow, and nitrate leaching by comparing estimates with in situ observations. The system improved the accuracy and precision of soil moisture estimates for the assimilation layers by an average of 42% and 48%, respectively, when compared to the free model. Such improvements led to changes in the model\u27s soil water and nitrogen processes and, on average, increased accuracy in forecasts of annual tile flow by 43% and annual nitrate loads by 10%. Forecasts of aboveground measures did not dramatically change with assimilation, a fact which highlights the limited potential of soil moisture as a constraint for a site with no water stress. Extending the scope of previous work, our results demonstrate the power of data assimilation to constrain important model estimates beyond the assimilated state variable, such as nitrate leaching. Replication of this study is necessary to further define the limitations and opportunities of the developed system

Incorporation of crop phenology in Simple Biosphere Model (SiBcrop) to improve land-atmosphere carbon exchanges from croplands

Croplands are man-made ecosystems that have high net primary productivity during the growing season of crops, thus impacting carbon and other exchanges with the atmosphere. These exchanges play a major role in nutrient cycling and climate change related issues. An accurate representation of crop phenology and physiology is important in land-atmosphere carbon models being used to predict these exchanges. To better estimate time-varying exchanges of carbon, water, and energy of croplands using the Simple Biosphere (SiB) model, we developed crop-specific phenology models and coupled them to SiB. The coupled SiB-phenology model (SiBcrop) replaces remotely-sensed NDVI information, on which SiB originally relied for deriving Leaf Area Index (LAI) and the fraction of Photosynthetically Active Radiation (fPAR) for estimating carbon dynamics. The use of the new phenology scheme within SiB substantially improved the prediction of LAI and carbon fluxes for maize, soybean, and wheat crops, as compared with the observed data at several AmeriFlux eddy covariance flux tower sites in the US mid continent region. SiBcrop better predicted the onset and end of the growing season, harvest, interannual variability associated with crop rotation, day time carbon uptake (especially for maize) and day to day variability in carbon exchange. Biomass predicted by SiBcrop had good agreement with the observed biomass at field sites. In the future, we will predict fine resolution regional scale carbon and other exchanges by coupling SiBcrop with RAMS (the Regional Atmospheric Modeling System)

Can improved canopy light transmission ameliorate loss of photosynthetic efficiency in the shade An investigation of natural variation in Sorghum bicolor

Previous studies have found that maximum quantum yield of CO2 assimilation (φCO2,max,app) declines in lower canopies of maize and miscanthus, a maladaptive response to self-shading. These observations were limited to single genotypes, leaving it unclear whether the maladaptive shade response is a general property of this C4 grass tribe, the Andropogoneae. We explored the generality of this maladaptation by testing the hypothesis that erect leaf forms (erectophiles), which allow more light into the lower canopy, suffer less of a decline in photosynthetic efficiency than drooping leaf (planophile) forms. On average, φCO2,max,app declined 27% in lower canopy leaves across 35 accessions, but the decline was over twice as great in planophiles than in erectophiles. The loss of photosynthetic efficiency involved a decoupling between electron transport and assimilation. This was not associated with increased bundle sheath leakage, based on 13C measurements. In both planophiles and erectophiles, shaded leaves had greater leaf absorptivity and lower activities of key C4 enzymes than sun leaves. The erectophile form is considered more productive because it allows a more effective distribution of light through the canopy to support photosynthesis. We show that in sorghum, it provides a second benefit, maintenance of higher φCO2,max,app to support efficient use of that light resource

\u3ci\u3eCorrigendum to\u3c/i\u3e “Incorporation of crop phenology in Simple Biosphere Model (SiBcrop) to improve land-atmosphere carbon exchanges from croplands” published in Biogeosciences, 6, 969–986, 2009

In the above mentioned manuscript a mistake in Fig. 11 occured. The corrected version of the figure is as follows

HIV-1 replication and the cellular eukaryotic translation apparatus

Eukaryotic translation is a complex process composed of three main steps: initiation, elongation, and termination. During infections by RNA- and DNA-viruses, the eukaryotic translation machinery is used to assure optimal viral protein synthesis. Human immunodeficiency virus type I (HIV-1) uses several non-canonical pathways to translate its own proteins, such as leaky scanning, frameshifting, shunt, and cap-independent mechanisms. Moreover, HIV-1 modulates the host translation machinery by targeting key translation factors and overcomes different cellular obstacles that affect protein translation. In this review, we describe how HIV-1 proteins target several components of the eukaryotic translation machinery, which consequently improves viral translation and replication

Nucleic Acids Res

The HIV-1 viral infectivity factor (Vif) is required for productive infection of non-permissive cells, including most natural HIV-1 targets, where it counteracts the antiviral activities of the cellular cytosine deaminases APOBEC-3G (A3G) and A3F. Vif is a multimeric protein and the conserved proline-rich domain (161)PPLP(164) regulating Vif oligomerization is crucial for its function and viral infectivity. Here, we expressed and purified wild-type Vif and a mutant protein in which alanines were substituted for the proline residues of the (161)PPLP(164) domain. Using dynamic light scattering, circular dichroism and fluorescence spectroscopy, we established the impact of these mutations on Vif oligomerization, secondary structure content and nucleic acids binding properties. In vitro, wild-type Vif formed oligomers of five to nine proteins, while Vif AALA formed dimers and/or trimers. Up to 40% of the unbound wild-type Vif protein appeared to be unfolded, but binding to the HIV-1 TAR apical loop promoted formation of beta-sheets. Interestingly, alanine substitutions did not significantly affect the secondary structure of Vif, but they diminished its binding affinity and specificity for nucleic acids. Dynamic light scattering showed that Vif oligomerization, and interaction with folding-promoting nucleic acids, favor formation of high molecular mass complexes. These properties could be important for Vif functions involving RNAs

Leaf photosynthesis and respiration of three bioenergy crops in relation to temperature and leaf nitrogen: how conserved are biochemical model parameters among crop species?

Given the need for parallel increases in food and energy production from crops in the context of global change, crop simulation models and data sets to feed these models with photosynthesis and respiration parameters are increasingly important. This study provides information on photosynthesis and respiration for three energy crops (sunflower, kenaf, and cynara), reviews relevant information for five other crops (wheat, barley, cotton, tobacco, and grape), and assesses how conserved photosynthesis parameters are among crops. Using large data sets and optimization techniques, the C3 leaf photosynthesis model of Farquhar, von Caemmerer, and Berry (FvCB) and an empirical night respiration model for tested energy crops accounting for effects of temperature and leaf nitrogen were parameterized. Instead of the common approach of using information on net photosynthesis response to CO2 at the stomatal cavity (An–Ci), the model was parameterized by analysing the photosynthesis response to incident light intensity (An–Iinc). Convincing evidence is provided that the maximum Rubisco carboxylation rate or the maximum electron transport rate was very similar whether derived from An–Ci or from An–Iinc data sets. Parameters characterizing Rubisco limitation, electron transport limitation, the degree to which light inhibits leaf respiration, night respiration, and the minimum leaf nitrogen required for photosynthesis were then determined. Model predictions were validated against independent sets. Only a few FvCB parameters were conserved among crop species, thus species-specific FvCB model parameters are needed for crop modelling. Therefore, information from readily available but underexplored An–Iinc data should be re-analysed, thereby expanding the potential of combining classical photosynthetic data and the biochemical model

Contrasting effects of long term versus short-term nitrogen addition on photosynthesis and respiration in the Arctic

We examined the effects of short (<1–4 years) and long-term (22 years) nitrogen (N) and/or phosphorus (P) addition on the foliar CO2 exchange parameters of the Arctic species Betula nana and Eriophorum vaginatum in northern Alaska. Measured variables included: the carboxylation efficiency of Rubisco (Vcmax), electron transport capacity (Jmax), dark respiration (Rd), chlorophyll a and b content (Chl), and total foliar N (N). For both B. nana and E. vaginatum, foliar N increased by 20–50 % as a consequence of 1–22 years of fertilisation, respectively, and for B. nana foliar N increase was consistent throughout the whole canopy. However, despite this large increase in foliar N, no significant changes in Vcmax and Jmax were observed. In contrast, Rd was significantly higher (>25 %) in both species after 22 years of N addition, but not in the shorter-term treatments. Surprisingly, Chl only increased in both species the first year of fertilisation (i.e. the first season of nutrients applied), but not in the longer-term treatments. These results imply that: (1) under current (low) N availability, these Arctic species either already optimize their photosynthetic capacity per leaf area, or are limited by other nutrients; (2) observed increases in Arctic NEE and GPP with increased nutrient availability are caused by structural changes like increased leaf area index, rather than increased foliar photosynthetic capacity and (3) short-term effects (1–4 years) of nutrient addition cannot always be extrapolated to a larger time scale, which emphasizes the importance of long-term ecological experiments

The Costs of Photorespiration to Food Production Now and in the Future

Photorespiration is essential for C3 plants but operates at the massive expense of fixed carbon dioxide and energy. Photorespiration is initiated when the initial enzyme of photosynthesis, ribulose-1,5-bisphosphate carboxylase/ oxygenase (Rubisco), reacts with oxygen instead of carbon dioxide and produces a toxic compound that is then recycled by photorespiration. Photorespiration can be modeled at the canopy and regional scales to determine its cost under current and future atmospheres. A regional-scale model reveals that photorespiration currently decreases US soybean and wheat yields by 36% and 20%, respectively, and a 5% decrease in the losses due to photorespiration would be worth approximately $500 million annually in the United States. Furthermore, photorespiration will continue to impact yield under future climates despite increases in carbon dioxide, with models suggesting a 12–55% improvement in gross photosynthesis in the absence of photorespiration, even under climate change scenarios predicting the largest increases in atmospheric carbon dioxide concentration. Although photorespiration is tied to other important metabolic functions, the benefit of improving its efficiency appears to outweigh any potential secondary disadvantages.This article is from Annual Review of Plant Biology 67 (2016): 107, doi: 10.1146/annurev-arplant-043015-111709. Posted with permission.</p

Simulated responses of soil organic carbon stock to tillage management scenarios in the Northwest Great Plains

© 2007 Tan et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution Licens