Developing Composite Indicators for Agricultural Sustainability Assessment: Effect of Normalization and Aggregation Techniques

The assessment of the sustainability of agricultural systems is multidimensional in nature and requires holistic measures using indicators with different measurements and units reflecting social, economic, and environmental aspects. To simplify the assessment process, various indicators have different units, and measurements are grouped under broad indicator heads, and normalization and/or transformation processes are carried out in order to aggregate them. In this study, a total of 50 indicators from agricultural sustainability categories of productivity, stability, efficiency, durability, compatibility, and equity are employed to investigate which normalization technique is the most suitable for further mathematical analysis for developing a final composite indicator. To understand the consistency and quality of normalization measurement techniques and compare the benefits and drawbacks of the various selected normalization processes, the indicators of agricultural sustainability are considered. Each of the different techniques for normalization has advantages and drawbacks. This study shows that the proportionate normalization and hybrid aggregation rules of the arithmetic mean and the geometric mean are appropriate for the selected data set, and that this technique has a wider applicability for developing composite indicators for agricultural sustainability assessment.Social Sciences and Humanities Research Council (SSHRC), Canad

COVID-19's implications on agri-food systems and human health in Bangladesh

The COVID-19 pandemic in Bangladesh has put agri-food systems and resultant human health under serious pressure and this has thus become a priority concern for the country and its development partners. To understand, describe and analyse the impacts of COVID-19 on agri-food systems, human health issues and related SDGs, this study used systematic rapid literature review, analysis of blogs and news and engagement with key informants. The analysis reveals impacts that can be addressed through a set of recommendations for a coordinated effort to minimize the effects of the COVID-19 pandemic on agri-food systems and related health issues in Bangladesh

Elimination Method of Multi-Criteria Decision Analysis (MCDA): A Simple Methodological Approach for Assessing Agricultural Sustainability

In the present world context, there is a need to assess the sustainability of agricultural systems. Various methods have been proposed to assess agricultural sustainability. Like in many other fields, Multi-Criteria Decision Analysis (MCDA) has recently been used as a methodological approach for the assessment of agricultural sustainability. In this paper, an attempt is made to apply Elimination, a MCDA method, to an agricultural sustainability assessment, and to investigate its benefits and drawbacks. This article starts by explaining the importance of agricultural sustainability. Common MCDA types are discussed, with a description of the state-of-the-art method for incorporating multi-criteria and reference values for agricultural sustainability assessment. Then, a generic description of the Elimination Method is provided, and its modeling approach is applied to a case study in coastal Bangladesh. An assessment of the results is provided, and the issues that need consideration before applying Elimination to agricultural sustainability, are examined. Whilst having some limitations, the case study shows that it is applicable for agricultural sustainability assessments and for ranking the sustainability of agricultural systems. The assessment is quick compared to other assessment methods and is shown to be helpful for agricultural sustainability assessment. It is a relatively simple and straightforward analytical tool that could be widely and easily applied. However, it is suggested that appropriate care must be taken to ensure the successful use of the Elimination Method during the assessment process.Social Sciences and Humanities Research Council (SSHRC), Canad

Climate Change-Accelerated Ocean Biodiversity Loss & Associated Planetary Health Impacts

A planetary health perspective views human health as a function of the interdependent relationship between human systems and the natural systems in which we live. The planetary health impacts of climate change induced ocean biodiversity loss are little understood. Based on a systematic literature review, we summarize how climate change-induced ocean warming, acidification, and deoxygenation affect ocean biodiversity and their resulting planetary health impacts. These impacts on the planets’ natural and human systems include biospheric and human consequences for ecosystem services, food and nutrition security, human livelihoods, biomedical and pharmaceutical research, disaster risk management, and for organisms pathogenic to humans. Understanding the causes and effects of climate change impacts on the ocean and its biodiversity and planetary health is crucial for taking preventive, restorative and sustainable actions to ensure ocean biodiversity and its services. Future courses of action to mitigate climate change-related ocean biodiversity loss to support sound planetary health are discussed

Complex adaptive systems-based framework for modeling the health impacts of climate change

Introduction: Climate change is a global phenomenon with far-reaching consequences, and its impact on human health is a growing concern. The intricate interplay of various factors makes it challenging to accurately predict and understand the implications of climate change on human well-being. Conventional methodologies have limitations in comprehensively addressing the complexity and nonlinearity inherent in the relationships between climate change and health outcomes. Objectives: The primary objective of this paper is to develop a robust theoretical framework that can effectively analyze and interpret the intricate web of variables influencing the human health impacts of climate change. By doing so, we aim to overcome the limitations of conventional approaches and provide a more nuanced understanding of the complex relationships involved. Furthermore, we seek to explore practical applications of this theoretical framework to enhance our ability to predict, mitigate, and adapt to the diverse health challenges posed by a changing climate. Methods: Addressing the challenges outlined in the objectives, this study introduces the Complex Adaptive Systems (CAS) framework, acknowledging its significance in capturing the nuanced dynamics of health effects linked to climate change. The research utilizes a blend of field observations, expert interviews, key informant interviews, and an extensive literature review to shape the development of the CAS framework. Results and discussion: The proposed CAS framework categorizes findings into six key sub-systems: ecological services, extreme weather, infectious diseases, food security, disaster risk management, and clinical public health. The study employs agent-based modeling, using causal loop diagrams (CLDs) tailored for each CAS sub-system. A set of identified variables is incorporated into predictive modeling to enhance the understanding of health outcomes within the CAS framework. Through a combination of theoretical development and practical application, this paper aspires to contribute valuable insights to the interdisciplinary field of climate change and health. Integrating agent-based modeling and CLDs enhances the predictive capabilities required for effective health outcome analysis in the context of climate change. Conclusion: This paper serves as a valuable resource for policymakers, researchers, and public health professionals by employing a CAS framework to understand and assess the complex network of health impacts associated with climate change. It offers insights into effective strategies for safeguarding human health amidst current and future climate challenges