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Fan, F., Henriksen, C. B., & Porter, J. (2018). Relationship between stoichiometry and ecosystem services: A case study of it organic farming systems. Ecological Indicators, 85, 400–408.
Abstract: Over the past five decades, the delivery of global Ecosystem Services (ES) has diminished and this has been driven partly by anthropogenic activities. Agro-ecosystems cover almost 40% of the terrestrial surface on Earth, and have been considered as one of the most significant ecological experiments with a potential to both contribute to and mitigate global ES loss. In the present study, six different ES (food and fodder production, carbon sequestration, biological pest control, soil water storage, nitrogen regulation and soil formation) were quantified in various organic farming systems and the hypothesis that there is a link between these ES and C:N, C:O and H:O stoichiometric ratios in farming systems was experimentally tested. The results show that different ES are correlated with the stoichiometric ratios to different extents. There are significant positive linear correlations between C:N stoichiometric ratios and all measured ES in the investigated organic farming systems, while not all the ES are correlated with the C:O and H:O ratios. This study has expanded the horizons of stoichiometry by linking a fundamental chemical property of molecules with an emergent property of organic farming systems, namely their ecosystem service provision.
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Abdelrahman, H. M., Olk, D. C., Dinnes, D., Ventrella, D., Miano, T., & Cocozza, C. (2016). Occurrence and abundance of carbohydrates and amino compounds in sequentially extracted labile soil organic matter fractions. Journal of Soils and Sediments, 16(10), 2375–2384.
Abstract: Purpose The study aimed to describe the carbohydrates and amino compounds content in soil, the light fraction (LF), the >53 μm particulate organic matter (POM), and the mobile humic acid (MHA) fraction and to find out whether the carbohydrates and amino compounds can be used to explain the origin of SOM fractions. Materials and methods Soil samples were collected from two agricultural fields managed under organic farming in southern Italy. The LF, the POM, and the MHA were sequentially extracted from each soil sample then characterized. Seven neutral sugars and 19 amino compounds (amino acids and amino sugars) were determined in each soil sample and its correspondent fractions. Results and discussion The MHA contained less carbohydrate than the LF or the POM but its carbohydrates, although dominated by arabinose, were relatively with larger microbial contribution as revealed by the mannose/xylose ratio. The amino compounds were generally less in the LF or the POM than in the MHA, while the fungal (aspartic and serine) and bacterial (alanine and glycine) amino acids were larger in the MHA than in the LF or the POM, underlining the microbial contribution to the MHA. Results from both sites indicated that total carbohydrates content decreased moving from the LF (younger fraction) to the MHA (older fraction), which seems to follow a decomposition continuum of organic matter in the soil-plant system. Conclusions The study showed that the MHA is a labile humified fraction of soil C due to its content of carbohydrates and concluded that the content of carbohydrates and amino compounds in the LF, the POM and the MHA can depict the nature of these fractions and their cycling pattern and response to land management.
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Minet, J., Laloy, E., Tychon, B., & François, L. (2015). Bayesian inversions of a dynamic vegetation model at four European grassland sites. Biogeosciences, 12(9), 2809–2829.
Abstract: Eddy covariance data from four European grassland sites are used to probabilistically invert the CARAIB (CARbon Assimilation In the Biosphere) dynamic vegetation model (DVM) with 10 unknown parameters, using the DREAM((ZS)) (DiffeRential Evolution Adaptive Metropolis) Markov chain Monte Carlo (MCMC) sampler. We focus on comparing model inversions, considering both homoscedastic and heteroscedastic eddy covariance residual errors, with variances either fixed a priori or jointly inferred together with the model parameters. Agreements between measured and simulated data during calibration are comparable with previous studies, with root mean square errors (RMSEs) of simulated daily gross primary productivity (GPP), ecosystem respiration (RECO) and evapotranspiration (ET) ranging from 1.73 to 2.19, 1.04 to 1.56 g C m(-2) day(-1) and 0.50 to 1.28 mm day(-1), respectively. For the calibration period, using a homoscedastic eddy covariance residual error model resulted in a better agreement between measured and modelled data than using a heteroscedastic residual error model. However, a model validation experiment showed that CARAIB models calibrated considering heteroscedastic residual errors perform better. Posterior parameter distributions derived from using a heteroscedastic model of the residuals thus appear to be more robust. This is the case even though the classical linear heteroscedastic error model assumed herein did not fully remove heteroscedasticity of the GPP residuals. Despite the fact that the calibrated model is generally capable of fitting the data within measurement errors, systematic bias in the model simulations are observed. These are likely due to model inadequacies such as shortcomings in the photosynthesis modelling. Besides the residual error treatment, differences between model parameter posterior distributions among the four grassland sites are also investigated. It is shown that the marginal distributions of the specific leaf area and characteristic mortality time parameters can be explained by site-specific ecophysiological characteristics.
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Carabano, M. J., Logar, B., Bormann, J., Minet, J., Vanrobays, M. L., Diaz, C., et al. (2016). Modeling heat stress under different environmental conditions. J. Dairy Sci., 99(5), 3798–3814.
Abstract: Renewed interest in heat stress effects on livestock productivity derives from climate change, which is expected to increase temperatures and the frequency of extreme weather events. This study aimed at evaluating the effect of temperature and humidity on milk production in highly selected dairy cattle populations across 3 European regions differing in climate and production systems to detect differences and similarities that can be used to optimize heat stress (HS) effect modeling. Milk, fat, and protein test day data from official milk recording for 1999 to 2010 in 4 Holstein populations located in the Walloon Region of Belgium (BEL), Luxembourg (LUX), Slovenia (SLO), and southern Spain (SPA) were merged with temperature and humidity data provided by the state meteorological agencies. After merging, the number of test day records/cows per trait ranged from 686,726/49,655 in SLO to 1,982,047/136,746 in BEL. Values for the daily average and maximum temperature-humidity index (THIavg and THImax) ranges for THIavg/THImax were largest in SLO (22-74/28-84) and shortest in SPA (39-76/46-83). Change point techniques were used to determine comfort thresholds, which differed across traits and climatic regions. Milk yield showed an inverted U-shaped pattern of response across the THI scale with a HS threshold around 73 THImax units. For fat and protein, thresholds were lower than for milk yield and were shifted around 6 THI units toward larger values in SPA compared with the other countries. Fat showed lower HS thresholds than protein traits in all countries. The traditional broken line model was compared with quadratic and cubic fits of the pattern of response in production to increasing heat loads. A cubic polynomial model allowing for individual variation in patterns of response and THIavg as heat load measure showed the best statistical features. Higher/lower producing animals showed less/more persistent production (quantity and quality) across the THI scale. The estimated correlations between comfort and THIavg values of 70 (which represents the upper end of the THIavg scale in BEL-LUX) were lower for BEL-LUX (0.70-0.80) than for SPA (0.83-0.85). Overall, animals producing in the more temperate climates and semi-extensive grazing systems of BEL and LUX showed HS at lower heat loads and more re-ranking across the THI scale than animals producing in the warmer climate and intensive indoor system of SPA.
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Yang, H., Dobbie, S., Ramirez-Villegas, J., Feng, K., Challinor, A. J., Chen, B., et al. (2016). Potential negative consequences of geoengineering on crop production: A study of Indian groundnut. Geophys. Res. Let., 43(22), 11786–11795.
Abstract: Geoengineering has been proposed to stabilize global temperature, but its impacts on crop production and stability are not fully understood. A few case studies suggest that certain crops are likely to benefit from solar dimming geoengineering, yet we show that geoengineering is projected to have detrimental effects for groundnut. Using an ensemble of crop-climate model simulations, we illustrate that groundnut yields in India undergo a statistically significant decrease of up to 20% as a result of solar dimming geoengineering relative to RCP4.5. It is somewhat reassuring, however, to find that after a sustained period of 50 years of geoengineering crop yields return to the nongeoengineered values within a few years once the intervention is ceased.
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