How do context variables affect food insecurity in Mexico? Implications for policy and governance.

OBJECTIVE: To assess, from a systems perspective, how climate vulnerability and socio-economic and political differences at the municipal and state levels explain food insecurity in Mexico. DESIGN: Using a cross-sectional design with official secondary data, we estimated three-level multinomial hierarchical linear models. SETTING: The study setting is Mexico's states and municipalities in 2014. PARTICIPANTS: Heads of households in a representative sample of the general population. RESULTS: At the municipal level, vulnerability to climate disasters and a poverty index were significant predictors of food insecurity after adjusting for household-level variables. At the state level, gross domestic product and the number of nutrition programmes helped explain different levels of food insecurity but change in political party did not. Predictors varied in strength and significance according to the level of food insecurity. CONCLUSIONS: Findings evidence that, beyond food assistance programmes and household characteristics, multiple variables operating at different levels - like climate vulnerability and poverty - contribute to explain the degree of food insecurity. Food security governance is a well-suited multisectoral approach to address the complex challenge of hunger and access to a nutritious diet.

Assessing sustainability in North America's ecosystems using criticality and information theory.

Sustainability is a key concept in economic and policy debates. Nevertheless, it is usually treated only in a qualitative way and has eluded quantitative analysis. Here, we propose a sustainability index based on the premise that sustainable systems do not lose or gain Fisher Information over time. We test this approach using time series data from the AmeriFlux network that measures ecosystem respiration, water and energy fluxes in order to elucidate two key sustainability features: ecosystem health and stability. A novel definition of ecosystem health is developed based on the concept of criticality, which implies that if a system's fluctuations are scale invariant then the system is in a balance between robustness and adaptability. We define ecosystem stability by taking an information theory approach that measures its entropy and Fisher information. Analysis of the Ameriflux consortium big data set of ecosystem respiration time series is contrasted with land condition data. In general we find a good agreement between the sustainability index and land condition data. However, we acknowledge that the results are a preliminary test of the approach and further verification will require a multi-signal analysis. For example, high values of the sustainability index for some croplands are counter-intuitive and we interpret these results as ecosystems maintained in artificial health due to continuous human-induced inflows of matter and energy in the form of soil nutrients and control of competition, pests and disease.