Gene flow of transgenes into non-target populations is an important biosafety concern. The case of genetically modified (GM) maize in Mexico has been of particular interest because of the country’s status as center of origin and landrace diversity. In contrast to maize in the U.S. and Europe, Mexican landraces form part of an evolving metapopulation in which new genes are subject to evolutionary processes of drift, gene flow and selection. Although these processes are affected by seed management and particularly seed flow, there has been little study into the population genetics of transgenes under traditional seed management. Here, we combine recently compiled data on seed management practices with a spatially explicit population genetic model to evaluate the importance of seed flow as a determinant of the long-term fate of transgenes in traditional seed systems. Seed flow between farmers leads to a much wider diffusion of transgenes than expected by pollen movement alone, but a predominance of seed replacement over seed mixing lowers the probability of detection due to a relative lack of homogenization in spatial frequencies. We find that in spite of the spatial complexities of the modeled system, persistence probabilities under positive selection are estimated quite well by existing theory. Our results have important implications concerning the feasibility of long term transgene monitoring and control in traditional seed systems.
Este artículo publicado en la revista Internacional, Molecular Ecology, confirma la presencia de transgenes en maíces nativos de Oaxaca y muestra modelos de simulación sobre la dinámica de dispersión de transgenes en poblaciones de maices nativos en México. Contribuye a la discusión sobre métodos de monitoreo,tanto en su componente molecular, como de muestreo.
El calentamiento global o "cambio climático" es el mayor reto ambiental que enfrentaremos en este siglo. Sus impactos ya se están verificando y, de no tomar medidas preventivas de inmediato, serán mucho más severos.
With the rapid growth of biofuel production and consumption, and the proliferation of policy decisions supporting this expansion, concerns about the biofuel sector’s environmental and social impacts are increasing. Consequently, a range of actors – among them governments, multilateral institutions, nongovernmental organisations and multistakeholder industry groups – have created sustainability frameworks, some mandatory, others voluntary. This report examines how the most developed sustainability frameworks for feedstock production (including biofuels) address key environmental issues. It identifies critical gaps in these frameworks and proposes areas for improvement. The frameworks analysed are the European Union Renewable Energy Directive (EU RED), Roundtable on Sustainable Biofuels (RSB), Roundtable on Sustainable Palm Oil (RSPO), Round Table on Responsible Soy Association (RTRS), Better Sugarcane Initiative (BSI) and the Forest Stewardship Council (FSC).
In this article, we attempt to find the spatial relations between deforestation and biofuel production at global level by analyzing available global deforestation and biofuels data, and find that, for a variety of reasons relating to data availability and its characteristics, and the way biofuels are produced, this task is extremely difficult if not virtually impossible. Then we bring down the scale of the analysis to the case study level and provide a detailed methodology for analyzing the spatial relation between deforestation and biofuel development. We argue that this multi-scale approach, based on systematic sampling at the case study level would help to better understand the relation between biofuels and deforestation. Given the fact that biofuels are a highly contested approach to reduction of global carbon emissions, and that different lobbies in this debate are making claims that deforestation is, or is not, occurring as a result of the expansion of biofuel production, clarity on the methodological difficulties of making statements of this kind, at least in a global spatial analysis, may help avoid false conclusions being promulgated in the future.