(173ah) Assessing Global Warming Impacts on Food and Macronutrient Supply By Compartmental Modeling Approach

In recent decades, population growth, anthropogenic activity, and inefficient resource management have led to an excess of Greenhouse Gas (GHG) emissions and concentration in the atmosphere, intensifying the greenhouse effect and giving rise to phenomena such as Global Warming and subsequent Climate Change.In this context, the livestock sector, despite not being considered a direct emitter, significantly contributes GHG emissions with high global warming. Additionally, the agricultural sector is strongly influenced by livestock demand, as 80% of global agricultural production is destined for animal consumption. The increase in agricultural demand has exceeded sustainable production capacities, leading to practices such as deforestation and the exploitation of wild ecosystems to meet this growing livestock demand.

In addition to its environmental impacts, the intensive focus on meeting livestock demand has significant repercussions for macronutrient supply and distribution. The emphasis on animal consumption within the agricultural sector not only diverts resources away from direct human consumption but also affects the availability and diversity of macronutrients in the global food supply. This skewed allocation of resources towards animal feed production limits the accessibility of essential macronutrients such as carbohydrates, proteins, and fats for human consumption, particularly in regions where food insecurity is prevalent. Moreover, the reliance on monoculture practices to sustain this demand further exacerbates the issue by compromising the nutritional diversity of crops grown for both human and animal consumption. Thus, while addressing the environmental implications of livestock production is crucial, it is equally imperative to consider the broader implications for macronutrient availability and nutritional equity on a global scale.

Considering these complex interrelations between anthropogenic activities, environmental impacts, and macronutrient supply, the utilization of mathematical models, particularly compartmental models, emerges as a valuable tool for analysis and prediction. Compartmental models allow researchers to represent the intricate dynamics of various sectors and their interactions within a unified framework, enabling a comprehensive assessment of the repercussions of livestock demand on macronutrient availability and environmental sustainability. Furthermore, compartmental models facilitate the exploration of feedback loops and nonlinear relationships inherent in complex systems, offering insights into the long-term consequences of current trends and identifying critical leverage points for intervention. The objective of this work is to provide a tool that facilitates the analysis of strategies based on evidence-based decision-making and guides efforts toward achieving a more sustainable and equitable food system amid the challenges of climate change and growing global demand for food.

A mathematical global food model is proposed consisting of 9 compartments depicting the flow of matter between the primary economic sectors and adjacent sectors that contribute in some way to the human food chain. The agricultural sector is divided into two compartments: Grains, which are edible for humans, and Forage, or residues that are not edible for humans. On the other hand, the Livestock sector is divided into Ruminant animals that generate a greater amount of GHG emissions and monogastric animals with a lower environmental impact. The interactions between compartments are modeled by Lotka-Volterra type differential equations and parameterized using the Food and Agriculture Database (FAOSTAT).

Additionally, the CO2eq concentration in the atmosphere is determined by summing the contributions of various greenhouse gases emitted or absorbed within the system. This calculation involves multiplying the compartment size by its respective Emission Factor to quantify the greenhouse gases emitted by each compartment. This GHG concentration feeds back into the model by influencing temperature changes and altering plant growth rates in the Lotka-Volterra equations. Finally, to calculate the food demand of the human sector, an average nutritional contribution is estimated for each unit of agricultural and livestock food. This estimation is obtained from FAOSTAT, utilizing the values of annual worldwide production and per capita consumption for each category in the year 2022.

The model is implemented in Matlab software, where parameters and differential equations are inputted and integrated using the Euler method with a unit step size over a span of 80 years. The results compares the per capita availability of macronutrients within the context of food availability. This comparison contrasts the requirements established by the WHO with the current macronutrient. The analysis reveals that presently, we are meeting the required parameters. However, projections indicate a shortfall by the year 2078, which would limit the availability of carbohydrates and minimum calories per capita.

In conclusion, the utilization of mathematical models, such as the one implemented in this work, offers invaluable insights into the dynamics of macronutrient supply, greenhouse gas emissions, and their implications for global food security and environmental sustainability. However, the projections highlight the urgency of proactive intervention to address future shortages in macronutrient availability. Sustainable resource management practices, coupled with efforts to reduce greenhouse gas emissions and enhance agricultural productivity, are imperative to ensure a resilient and equitable food system for future generations.