ABSTRACT
This paper addresses the highly relevant and timely issues of global trade and food security by developing an empirically grounded, relation-driven agent-based global trade model. Contrary to most price-driven trade models in the literature, the relation-driven agent-based global trade model focuses on the role of relational factors such as trust, familiarity, trade history and conflicts in countries' trade behaviour. Moreover, the global trade model is linked to a comprehensive nutrition formula to investigate the impact of trade on food and nutrition security, including macro and micronutrients. Preliminary results show that global trade improves the food and nutrition security of countries in Africa, Asia and Latin America. Trade also promotes a healthier and more balanced diet, as countries have access to an increased variety of food. The effect of trade in enhancing nutrition security, with an adequate supply of macro and micronutrients, is universal across nutrients and countries. As researchers call for a holistic and multifactorial approach to food security and climate change (Hammond and Dubé 2012 Proc. Natl Acad. Sci. USA 109, 12 356-12 363. (doi:10.1073/pnas.0913003109)), the paper is one of the first to develop an integrated framework that consists of socio-economic, geopolitical, nutrition, environmental and agri-food systems to tackle these global challenges. Given the ongoing events of Brexit, the US-China trade war and the global COVID-19 pandemic, the paper will provide valuable insights on the role of trade in improving the food and nutrition security across countries.
ABSTRACT
The 'Perfect Storm' metaphor describes a combination of events that causes a surprising or dramatic impact. It lends an evolutionary perspective to how social-ecological interactions change. Thus, we argue that an improved understanding of how social-ecological systems have evolved up to the present is necessary for the modelling, understanding and anticipation of current and future social-ecological systems. Here we consider the implications of an evolutionary perspective for designing research approaches. One desirable approach is the creation of multi-decadal records produced by integrating palaeoenvironmental, instrument and documentary sources at multiple spatial scales. We also consider the potential for improved analytical and modelling approaches by developing system dynamical, cellular and agent-based models, observing complex behaviour in social-ecological systems against which to test systems dynamical theory, and drawing better lessons from history. Alongside these is the need to find more appropriate ways to communicate complex systems, risk and uncertainty to the public and to policy-makers.
Subject(s)
Conservation of Natural Resources/methods , Ecosystem , Biological Evolution , Conservation of Natural Resources/trends , Data Collection/methods , Interpersonal Relations , Models, TheoreticalABSTRACT
A cholera epidemic that took place in KwaZulu-Natal, South Africa (2000-2001) was employed to investigate the impact of climatic and environmental drivers on cholera dynamics. Precipitation (PRE), sea surface temperature (SST) and chlorophyll-a (CHL-a) data acquired from publicly available satellite and ground measurements were analysed together with disease incidence in an effort to assess the environmental contribution to the outbreak. SST (r(2)=0.749, lag=0 months) and PRE (r(2)=0.744, lag=2 months) showed strong associations with incidence. CHL-a showed a moderately strong (r(2)=0.656, lag=6 months) association with incidence while sea surface height (SSH) demonstrated a weak relationship with incidence (r(2)=0.326, lag=5 months). Our analysis tentatively supports a coastal transmission hypothesis, heavily influenced by localized PRE extremes. The role of SSH is likely attenuated by local coastal topography. Future work should clarify the mechanism linking coastal cholera reservoirs and the regional climate system to outbreaks in this region. Finally, we discuss benefits of further research in this area using extended remotely sensed and epidemiological datasets towards the development of early-warning systems and enhanced epidemic preparedness.
