About

The Agricultural Impacts Research Group (AIRG) is composed of faculty and graduate students at Clark University in Worcester, Massachusetts. As agriculture is the dominant driver of terrestrial ecological change and its impacts will continue to grow along with demand for fuel, food, and fiber, AIRG research focuses on improving understanding of how this continued agricultural development can be achieved for substantially lower environmental and social costs. Our work investigates this in three ways: 

 

1. Reducing Agriculture’s Ecological Impacts

By 2050, global food needs are expected to nearly double. Meanwhile, our current agricultural practices are the chief cause of terrestrial biodiversity loss, and one of the major drivers of climate change. If we want to feed ourselves and avoid causing large-scale environmental, and thus socioeconomic, disruptions, it is critical to examine how to dramatically lower agriculture’s environmental impacts. Thus, a key part of our research is to identify successful trade-offs that allow agricultural development objectives to be met for substantially lower ecological cost. It also entails gaining a better understanding of how land use impacts ecosystems, including individual species (such as the mountain bongo antelope, the subject of Lyndon Estes’ PhD research). The AIRG’s work currently focuses on sub-Saharan Africa, which will likely experience the greatest agricultural expansion in the coming decades, given its rapid growth and large areas of potential agricultural land.

 

2. Understanding the Drivers of Agricultural Change

Any solution we find to make agriculture more sustainable must itself be sustainable. If we can identify and encourage land uses that maximize agricultural benefits for the lowest possible ecological cost, we need to make sure that they will last. However, such trade-offs can be easily upset when changes in biophysical and socioeconomic conditions alter the costs and benefits of agriculture, thereby precipitating a change in land use. Climate change is one of the most important biophysical factors that can disrupt agriculture. On the socioeconomic side, there are many variables that can drive agricultural land use change, ranging from new technologies to consumer demand to government policies. An important focus of our research is thus to understand how such variables can impact agricultural land uses and farmers’ decisions, so that this information can ultimately be factored into the design of agriculture-environment trade-offs. Our current research in this area examines how the interactions of climate (both short-term variability and long-term change) and food security policies (ranging from subsidies to trade) impact agriculture and associated livelihoods in sub-Saharan Africa.

 

3. Developing the necessary data

In order to find valid trade-offs between agriculture and conservation, and to gain a proper understanding of how agriculture responds to global change, we need agricultural (e.g. productivity, crop choice, field boundaries) and environmental (e.g. daily weather, carbon stocks, species range maps) data that are regional to continental in extent, span the last two to three decades, and are accurate at fine field-to-landscape-scales. We need data that have such exacting standards for two reasons: 1) To make agricultural development more sustainable, we try to find and direct development to those areas that are both a) agriculturally productive and b) will result in unusually low environmental damage when developed. This means that we are looking to delineate specific areas, based on the values of two or more variables, which makes this type of investigation unusually sensitive to data error, 2) To understand how agriculture responds to socioeconomic and environmental changes, it is ultimately necessary to study how farmers change their agricultural practices and land use over time and in space. That cannot be done with provincial or national-level statistics. Unfortunately, the agricultural and environmental data sets that we need to conduct such analyses do not yet exist (with some rare exceptions) for the regions that will change most rapidly this century, particularly sub-Saharan Africa. Furthermore, the characteristics of agricultural systems in this region (small fields that often look indistinguishable from savanna vegetation in satellite image analyses) complicate the task of developing the necessary data. We therefore devote a substantial amount of research effort to developing the tools and methods needed to create these data sets, utilizing some of the latest advances in Earth Observing technology and data analytics.