Special Issue Scaling Methods In Integrated Assessment Of Agricultural Systems

Agriculture increasingly faces the challenge of balancing its multiple functions in a sustainable way. Integrated assessment and modelling (IAM) can provide insight into the potential impacts of policy changes. However, concepts to address the wide range of issues and functions typical for agriculture are still scarce. Environmental and Agricultural Modelling reviews and presents our current understanding of integrated and working tools to assess and compute, ex-ante, alternative agricultural and environmental policy options, allowing: 1. Analysis at the full range of scales (farm to European Union and global) whilst focusing on the most important issues emerging at each scale; 2. Analysis of the environmental, economic and social contributions of agricultural systems towards sustainable rural development and rural viability; 3. Analysis of a broad range of issues and agents of change, such as climate change, environmental policies, rural development options, effects of an enlarging EU, international competition, and effects on developing countries.

Linking People, Place, and Policy: A GIScience Approach describes a breadth of research associated with the study of human-environment interactions, with particular emphasis on land use and land cover dynamics. This book examines the social, biophysical, and geographical drivers of land use and land cover patterns and their dynamics, which are interpreted within a policy-relevant context. Concepts, tools, and techniques within Geographic Information Science serve as the unifying methodological framework in which landscapes in Thailand, Ecuador, Kenya, Cambodia, China, Brazil, Nepal, and the United States are examined through analyses conducted using quantitative, qualitative, and image-based techniques. Linking People, Place, and Policy: A GIScience Approach addresses a need for a comprehensive and rigorous treatment of GIScience for research and study within the context of human-environment interactions. The human dimensions research community, land use and land cover change programs, and human and landscape ecology communities, among others, are collectively viewing the landscape within a spatially-explicit perspective, where people are viewed as agents of landscape change that shape and are shaped by the landscape, and where landscape form and function are assessed within a space-time context. This book articulates some of these challenges and opportunities.

Agriculture is the product of a complex mixture of behavioural, biophysical and market drivers. Understanding how these factors interact to produce crops and livestock for food has been the focus of economic investigation for many years. The advent of optimisation algorithms and the exponential growth in computing technology has allowed significant growth in mathematical modelling of the dynamics of agricultural systems. The complexity of approaches has grown in parallel with the availability of data at increasingly finer resolutions. Farm-level models have been widely used in agricultural economic studies to understand how farmers and land owners respond to market and policy levers. This book provides an in-depth description of different methodologies and techniques currently used in farm-level modelling. While giving an overview of the theoretical grounding behind the models, an applied approach is also used. Case studies range from the application of modelling to policy reforms and the subsequent impacts on rural communities and food supply. This book also provides descriptions of the use of farm-level models in much wider fields such as aggregation and linking with sectoral models. Its purpose is to show the reader the methods that have been employed to inform decision-makers about how to improve the economic, social and environmental goals required to achieve the aims of multidimensional policy.

Ecologists, agronomists, and others who may question the validity of current models for determining sustainable growth of agroecosystems, need a new set of analytical tools that more effectively address the complex nature of related processes. Those who challenge traditional assumptions of optimization and static factors in agricultural modeling de