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Wu, L., Whitmore, A. P., & Bellocchi, G. (2015). Modelling the impact of environmental changes on grassland systems with SPACSYS. Advances in Animal Biosciences, 6(01), 37–39.
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Rolinski, S., Weindl, I., Heinke, J., Bodirsky, B. L., Biewald, A., & Lotze-Campen, H. (2015). Pasture harvest, carbon sequestration and feeding potentials under different grazing intensities. Advances in Animal Biosciences, 6(01), 43–45.
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Bannink, A., van Lingen, H. J., Ellis, J. L., France, J., & Dijkstra, J. (2016). The contribution of mathematical modeling to understanding dynamic aspects of rumen metabolism. Frontiers in Microbiology, 7, 1820.
Abstract: All mechanistic rumen models cover the main drivers of variation in rumen function, which are feed intake, the differences between feedstuffs and feeds in their intrinsic rumen degradation characteristics, and fractional outflow rate of fluid and particulate matter. Dynamic modeling approaches are best suited to the prediction of more nuanced responses in rumen metabolism, and represent the dynamics of the interactions between substrates and micro-organisms and inter-microbial interactions. The concepts of dynamics are discussed for the case of rumen starch digestion as influenced by starch intake rate and frequency of feed intake, and for the case of fermentation of fiber in the large intestine. Adding representations of new functional classes of micro-organisms (i.e., with new characteristics from the perspective of whole rumen function) in rumen models only delivers new insights if complemented by the dynamics of their interactions with other functional classes. Rumen fermentation conditions have to be represented due to their profound impact on the dynamics of substrate degradation and microbial metabolism. Although the importance of rumen pH is generally acknowledged, more emphasis is needed on predicting its variation as well as variation in the processes that underlie rumen fluid dynamics. The rumen wall has an important role in adapting to rapid changes in the rumen environment, clearing of volatile fatty acids (VFA), and maintaining rumen pH within limits. Dynamics of rumen wall epithelia and their role in VFA absorption needs to be better represented in models that aim to predict rumen responses across nutritional or physiological states. For a detailed prediction of rumen N balance there is merit in a dynamic modeling approach compared to the static approaches adopted in current protein evaluation systems. Improvement is needed on previous attempts to predict rumen VFA profiles, and this should be pursued by introducing factors that relate more to microbial metabolism. For rumen model construction, data on rumen microbiomes are preferably coupled with knowledge consolidated in rumen models instead of relying on correlations with rather general aspects of treatment or animal. This helps to prevent the disregard of basic principles and underlying mechanisms of whole rumen function.
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Ruiu, L. M., Maurizi, S., Sassu, S., Seddaiu, G., Zuin, O., Blackmore, C., et al. (2017). Re-Staging La Rasgioni: lessons learned from transforming a traditional form of conflict resolution to engage stakeholders in agricultural water governance. Water, 9(4), 297.
Abstract: This paper presents an informal process inspired by a public practice of conflict mediation used until a few decades ago in Gallura (NE Sardinia, Italy), named La Rasgioni (The Reason). The aim is twofold: (i) to introduce an innovative method that translates the complexity of water-related conflicts into a “dialogical tool”, aimed at enhancing social learning by adopting theatrical techniques; and (ii) to report the outcomes that emerged from the application of this method in Arborea, the main dairy cattle district and the only nitrate-vulnerable zone in Sardinia, to mediate contrasting positions between local entrepreneurs and representatives of the relevant institutions. We discuss our results in the light of four pillars, adopted as research lenses in the International research Project CADWAGO (Climate Change Adaptation and Water Governance), which consider the specific “social–ecological” components of the Arborea system, climate change adaptability in water governance institutions and organizations, systemic governance (relational) practices, and governance learning. The combination of the four CADWAGO pillars and La Rasgioni created an innovative dialogical space that enabled stakeholders and researchers to collectively identify barriers and opportunities for effective governance practices. Potential wider implications and applications of La Rasgioni process are also discussed in the paper.
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Webber, H., Ewert, F., Olesen, J. E., Müller, C., Fronzek, S., Ruane, A. C., et al. (2018). Diverging importance of drought stress for maize and winter wheat in Europe. Nat. Comm., 9, 4249.
Abstract: Understanding the drivers of yield levels under climate change is required to support adaptation planning and respond to changing production risks. This study uses an ensemble of crop models applied on a spatial grid to quantify the contributions of various climatic drivers to past yield variability in grain maize and winter wheat of European cropping systems (1984-2009) and drivers of climate change impacts to 2050. Results reveal that for the current genotypes and mix of irrigated and rainfed production, climate change would lead to yield losses for grain maize and gains for winter wheat. Across Europe, on average heat stress does not increase for either crop in rainfed systems, while drought stress intensifies for maize only. In low-yielding years, drought stress persists as the main driver of losses for both crops, with elevated CO2 offering no yield benefit in these years.
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