Bonatti, M., Schlindwein, S. L., De Vasconcelos, A. C. F., Sieber, S., Agostini, L. R. D., Lana, M. A., et al. (2013). Social organization and agricultural strategies to face climate variability: a case study in Guaraciaba, southern Brazil. Sustainable Agriculture Research, 2(3), 118.
Abstract: Climate scenarios and projections have suggested that the impacts of climate change on land use will be noticed particularly by the communities that depend on natural resources for their subsistence. The climate vulnerability of poor communities varies greatly, but in general, climate change combines with other threats and becomes superimposed on existing vulnerabilities. This paper presents a case study that strives to understand the social organization in a vulnerable community of Guaraciaba, in southern Brazil, to investigate aspects of an adaptation strategy to climate change based on the local development and conservation of landraces of a set of crop species. Landraces are varieties better adapted to adversities, especially drought, which is an important threat to the famers in the region. Every farmer receives annually a “kit of biodiversity”, a set of local varieties with the amount of seeds necessary to be cultivated in order to produce enough food for the family. The study had a qualitative approach and was carried out through semi-structured interviews with technicians and 30% of the rural families who farm with landraces. The study concludes that the factors that make this adaptation strategy sustainable are: the ability to undertake actions strongly based on local socio-cultural needs (a social support network), biodiversity management practices designed to reduce external economic dependence, self management of genetic resources, the establishment of priorities based on locally available resources, a work plan for community participation (field days, a community based festival), the establishment of the roles of community in the planning and implementation of programs for biodiversity management.
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de Visser, C., Schoorlemmer, H., Golaszewski, J., Olba-Ziety, E., Stolarski, M., Brodzinski, Z., et al. (2013). Agenda for Transnational Co-operation on energy efficiency in agriculture. Wageningen.
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Dumont, B., Basso, B., Leemans, V., Bodson, B., Destain, J. - P., & Destain, M. - F. (2015). Systematic analysis of site-specific yield distributions resulting from nitrogen management and climatic variability interactions. Precision Agric., 16(4), 361–384.
Abstract: At the plot level, crop simulation models such as STICS have the potential to evaluate risk associated with management practices. In nitrogen (N) management, however, the decision-making process is complex because the decision has to be taken without any knowledge of future weather conditions. The objective of this paper is to present a general methodology for assessing yield variability linked to climatic uncertainty and variable N rate strategies. The STICS model was coupled with the LARS-Weather Generator. The Pearson system and coefficients were used to characterise the shape of yield distribution. Alternatives to classical statistical tests were proposed for assessing the normality of distributions and conducting comparisons (namely, the Jarque-Bera and Wilcoxon tests, respectively). Finally, the focus was put on the probability risk assessment, which remains a key point within the decision process. The simulation results showed that, based on current N application practice among Belgian farmers (60-60-60 kgN ha(-1)), yield distribution was very highly significantly non-normal, with the highest degree of asymmetry characterised by a skewness value of -1.02. They showed that this strategy gave the greatest probability (60 %) of achieving yields that were superior to the mean (10.5 t ha(-1)) of the distribution.
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Dumont, B., Leemans, V., Ferrandis, S., Bodson, B., Destain, J. - P., & Destain, M. - F. (2014). Assessing the potential of an algorithm based on mean climatic data to predict wheat yield. Precision Agric., 15(3), 255–272.
Abstract: The real-time non-invasive determination of crop biomass and yield prediction is one of the major challenges in agriculture. An interesting approach lies in using process-based crop yield models in combination with real-time monitoring of the input climatic data of these models, but unknown future weather remains the main obstacle to reliable yield prediction. Since accurate weather forecasts can be made only a short time in advance, much information can be derived from analyzing past weather data. This paper presents a methodology that addresses the problem of unknown future weather by using a daily mean climatic database, based exclusively on available past measurements. It involves building climate matrix ensembles, combining different time ranges of projected mean climate data and real measured weather data originating from the historical database or from real-time measurements performed in the field. Used as an input for the STICS crop model, the datasets thus computed were used to perform statistical within-season biomass and yield prediction. This work demonstrated that a reliable predictive delay of 3-4 weeks could be obtained. In combination with a local micrometeorological station that monitors climate data in real-time, the approach also enabled us to (i) predict potential yield at the local level, (ii) detect stress occurrence and (iii) quantify yield loss (or gain) drawing on real monitored climatic conditions of the previous few days.
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Francioni, M., D’Ottavio, P., Lai, R., Trozzo, L., Budimir, K., Foresi, L., et al. (2019). Seasonal Soil Respiration Dynamics and Carbon-Stock Variations in Mountain Permanent Grasslands Compared to Arable Lands. Agriculture-Basel, 9(8), 165.
Abstract: Permanent grasslands provide a wide array of ecosystem services. Despite this, few studies have investigated grassland carbon (C) dynamics, and especially those related to the effects of land-use changes. This study aimed to determine whether the land-use change from permanent grassland to arable lands resulted in variations in the soil C stock, and whether such variations were due to increased soil respiration or to management practices. To address this, seasonal variations of soil respiration, sensitivity of soil respiration to soil temperature (Q(10)), and soil C stock variations generated by land-use changes were analyzed in a temperate mountain area of central Italy. The comparisons were performed for a permanent grassland and two adjacent fields, one cultivated with lentil and the other with emmer, during the 2015 crop year. Soil respiration and its heterotrophic component showed different spatial and temporal dynamics. Annual cumulative soil respiration rates were 6.05, 5.05 and 3.99 t C ha(-1) year(-1) for grassland, lentil and emmer, respectively. Both soil respiration and heterotrophic soil respiration were positively correlated with soil temperature at 10 cm depth. Derived Q(10) values were from 2.23 to 6.05 for soil respiration, and from 1.82 to 4.06 for heterotrophic respiration. Soil C stock at over 0.2 m in depth was 93.56, 48.74 and 46.80 t C ha(-1) for grassland, lentil and emmer, respectively. The land-use changes from permanent grassland to arable land lead to depletion in terms of the soil C stock due to water soil erosion. A more general evaluation appears necessary to determine the multiple effects of this land-use change at the landscape scale.
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