Globalization and land-use transitions in Latin America

Current socioeconomic drivers of land-use change associated with globalization are producing two contrasting land-use trends in Latin America. Increasing global food demand (particularly in Southeast Asia) accelerates deforestation in areas suitable for modern agriculture (e.g., soybean), severely threatening ecosystems, such as Amazonian rain forests, dry forests, and subtropical grasslands. Additionally, in the coming decades, demand for biofuels may become an emerging threat. In contrast, high yields in modern agricultural systems and rural–urban migration coupled with remittances promote the abandonment of marginal agricultural lands, thus favoring ecosystem recovery on mountains, deserts, and areas of poor soils, while improving human well-being. The potential switch from production in traditional extensive grazing areas to intensive modern agriculture provides opportunities to significantly increase food production while sparing land for nature conservation. This combination of emerging threats and opportunities requires changes in the way the conservation of Latin American ecosystems is approached. Land-use efficiency should be analyzed beyond the local-based paradigm that drives most conservation programs, and focus on large geographic scales involving long-distance fluxes of products, information, and people in order to maximize both agricultural production and the conservation of environmental services.Fil: Grau, Hector Ricardo. Universidad Nacional de Tucumán. Facultad de Ciencias Naturales e Instituto Miguel Lillo; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán; ArgentinaFil: Mitchell, Aide. Universidad de Puerto Rico; Puerto Ric

Validation Report: outcome stories for CIAT-CCAFS projects in Colombia during 2014

In November 2014, I engaged with five Colombian government staff to validate two Outcome Stories prepared by CIAT staff describing governmental changes that CIAT science had influenced. The first Story described how the Ministry of Agriculture and Rural Development (MADR)1 and the Ministry of Environment and Sustainable Development (MADS) prioritized mitigation actions for the agriculture and livestock sector. CIAT’s contribution was its scientific collaboration in 2013 and 2014 with the Colombian government to identify appropriate mitigation measures for the agricultural sector and establish the evidence base for the Colombian Low Emission Development Strategy (LEDS). The second Story described how the Colombian National Planning Department (DNP) developed detailed sector level adaptation plans in part as a result of CIAT researchers’ measurement of the economic impacts of climate change in the water, biodiversity and livestock sector. The purpose of the validation was to both verify and enrich the understanding of the influence of CIAT research in decision-making at the policy level

Validation Report: outcome stories for CIAT-CCAFS projects in Colombia during 2014

In November 2014, I engaged with five Colombian government staff to validate two Outcome Stories prepared by CIAT staff describing governmental changes that CIAT science had influenced. The first Story described how the Ministry of Agriculture and Rural Development (MADR)1 and the Ministry of Environment and Sustainable Development (MADS) prioritized mitigation actions for the agriculture and livestock sector. CIAT’s contribution was its scientific collaboration in 2013 and 2014 with the Colombian government to identify appropriate mitigation measures for the agricultural sector and establish the evidence base for the Colombian Low Emission Development Strategy (LEDS). The second Story described how the Colombian National Planning Department (DNP) developed detailed sector level adaptation plans in part as a result of CIAT researchers’ measurement of the economic impacts of climate change in the water, biodiversity and livestock sector. The purpose of the validation was to both verify and enrich the understanding of the influence of CIAT research in decision-making at the policy level

Two cases of type 2 diabetes mellitus successfully treated with probiotics

The gut microbiota, and particularly probiotic bacteria, has emerged as a promising and novel intervention to fight the looming worldwide diabetes epidemic when combined with the appropriate medication. Herein, we report two cases of patient with type 2 diabetes refractory to conventional therapy that showed notable improvement after probiotic intervention.Fil: Grau, Roberto Ricardo. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas. Departamento de Microbiología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario; ArgentinaFil: Bauman, Carlos. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas. Departamento de Microbiología; ArgentinaFil: Rodriguez Ayala, Facundo. Comisión Nacional de Energía Atómica; ArgentinaFil: Grau, Roberto Ricardo. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas. Departamento de Microbiología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario; Argentin

Iterative design of dynamic experiments in modeling for optimization of innovative bioprocesses

Finding optimal operating conditions fast with a scarce budget of experimental runs is a key problem to speed up the development and scaling up of innovative bioprocesses. In this paper, a novel iterative methodology for the model-based design of dynamic experiments in modeling for optimization is developed and successfully applied to the optimization of a fed-batch bioreactor related to the production of r-interleukin-11 (rIL-11) whose DNA sequence has been cloned in an Escherichia coli strain. At each iteration, the proposed methodology resorts to a library of tendency models to increasingly bias bioreactor operating conditions towards an optimum. By selecting the ‘most informative’ tendency model in the sequel, the next dynamic experiment is defined by re-optimizing the input policy and calculating optimal sampling times. Model selection is based on minimizing an error measure which distinguishes between parametric and structural uncertainty to selectively bias data gathering towards improved operating conditions. The parametric uncertainty of tendency models is iteratively reduced using Global Sensitivity Analysis (GSA) to pinpoint which parameters are keys for estimating the objective function. Results obtained after just a few iterations are very promising.Fil: Cristaldi, Mariano Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; ArgentinaFil: Grau, Ricardo José Antonio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico para la Industria Química; ArgentinaFil: Martínez, Ernesto Carlos. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo y Diseño. Universidad Tecnológica Nacional. Facultad Regional Santa Fe. Instituto de Desarrollo y Diseño; Argentin