Empirical test of an agricultural landscape model: The importance of farmer preference for risk aversion and crop complexity

Developing models to predict the effects of social and economic change on agricultural landscapes is an important challenge. Model development often involves making decisions about which aspects of the system require detailed description and which are reasonably insensitive to the assumptions. However, important components of the system are often left out because parameter estimates are unavailable. In particular, measurements of the relative influence of different objectives, such as risk, environmental management, on farmer decision making, have proven difficult to quantify. We describe a model that can make predictions of land use on the basis of profit alone or with the inclusion of explicit additional objectives. Importantly, our model is specifically designed to use parameter estimates for additional objectives obtained via farmer interviews. By statistically comparing the outputs of this model with a large farm-level land-use data set, we show that cropping patterns in the United Kingdom contain a significant contribution from farmer's preference for objectives other than profit. In particular, we found that risk aversion had an effect on the accuracy of model predictions, whereas preference for a particular number of crops grown was less important. While nonprofit objectives have frequently been identified as factors in farmers' decision making, our results take this analysis further by demonstrating the relationship between these preferences and actual cropping patterns

Indigenous and Scientific Knowledge of Soil Regulation Services, and Factors Effecting Decision-Making in Agricultural Landscapes in the Terai Plains of Nepal

Rapid degradation of soil regulation services is a growing concern for agricultural producers worldwide, with the potential for adverse impacts on agricultural productivity, food security, and livelihoods. Yet, data integrating observations of soil nutrient and physical status with farmers’ knowledge of soil fertility is lacking, while landscape-level empirical assessments remain limited. In this paper, it is argued that a deeper understanding of the benefits and trade-offs of management practices currently employed by farmers to secure soil nutrients could help to promote improvements in natural resource management, agricultural productivity and efficiency. Using the case of the Central and Western Terai Plains of Nepal in 2012–2014, rice-cultivated soil parameters were estimated, and 354 respondents were interviewed to determine the cropping systems, soil nutrient status and risks, indigenous soil classification systems, and key biophysical, institutional, economic and risk perception factors effecting decision-making. Findings reveal farmers are acutely aware of the main causes of soil degradation and until today, these issues continue to be of critical importance. To counter this degradation, farmers employ a diversity of landscape-level practices to secure optimal crop yields and soil nutrients. However, farmers have limited access to agricultural extension services and scientific monitoring and apply fewer mineral fertilisers than previously reported. Additional investments are required to optimize farmers’ practices and soil regulation services, such as cooperation for knowledge innovation systems, public/private extension, organisation for co-management, integrated nutrient management, and private forestry on farms. The case illustrates local knowledge and incremental efforts to adapt to emerging risks remain the foundation to implement spatially targeted conservation measures and design adaptive land use plans

Making ecological science policy-relevant: issues of scale and disciplinary integration

In this paper, we ask why so much ecological scientific research does not have a greater policy impact in the UK. We argue that there are two potentially important and related reasons for this failing. First, much current ecological science is not being conducted at a scale that is readily meaningful to policy-makers. Second, to make much of this research policy-relevant requires collaborative interdisciplinary research between ecologists and social scientists. However, the challenge of undertaking useful interdisciplinary research only re-emphasises the problems of scale: ecologists and social scientists traditionally frame their research questions at different scales and consider different facets of natural resource management, setting different objectives and using different language. We argue that if applied ecological research is to have greater impact in informing environmental policy, much greater attention needs to be given to the scale of the research efforts as well as to the interaction with social scientists. Such an approach requires an adjustment in existing research and funding infrastructures