Global Land Project Presentation

GLPI will be presenting at the Global Land Project on Friday March 21 in the following session of the Global Land Project Open Science Meeting

Session No. 93: Land science contributions to improving modeling and mapping of ecosystem services (Chairs: Neville Crossman, Benjamin Burkhard, Brett Bryan – Theme 3) Friday 21 March 2014, 09:00 – 10:30, Room 0’101

http://www.ihdp.unu.edu/file/get/11599

Impacts of agricultural land management on human well-being and ecosystem services

D.T. Robinson1, D. Murray-Rust2, E. Karali3, M.D.A Rounsevell2, and E.E. Guillem4

1Department of Geography and Environmental Management, Faculty of Environment, University of Waterloo, Waterloo, ON, N2L3G1, Canada.

 2Institute of Geography and The Lived Environment, School of GeoSciences, The University of Edinburgh, Drummond Street, Edinburgh, EH8 9XP.

 3Euro-Mediterranean Centre on Climate Change (Centro Euro-Mediterraneo sui Cambiamenti Climatici (CMCC)), Viale Aldo Moro 44, I-40127 Bologna, Italy

 4SRUC, Land Economy and Environment Research Group, Kings Buildings, West Mains Road, Edinburgh EH9 3JG, UK

Due to the potential of agricultural land use to impact ecosystem services and simultaneously produce society’s food, the desire to quantify crop/livestock inputs and outputs and changes in ecosystem services is high. Traditional approaches used to assess the impacts of agriculture on ecosystem services apply benefits transfer or simple equation-based models to a single time-slice or compilation of data. We demonstrate how an ABM can be used to extend these approaches by incorporating a range of ecosystem service indicators that enable their estimation over time and farmer responses to their change over time. In addition to benefits transfer and equation-based indicators, we also demonstrate how conversion factors can be used in combination with benefit transfer methods to derive additional metrics (e.g., saleable meat yields from livestock), how rule-based indicators can be used to derive a qualitative representation of changes in location characteristics (e.g., soil quality) or processes (e.g., intensity of erosion), and how indices and metrics (e.g., diversity and aesthetic quality) can provide a single numerical representation of one or more factors. Furthermore, we set the stage for a tight coupling between the ABM and dynamic vegetation models that complement existing loose-coupling approaches.

To improve our understanding of how agricultural land-management decisions can lead to subsequent changes in ecosystem services we designed a suite of ecosystem indicators and incorporated them into an existing ABM, named Aporia. This presentation contributes to Theme 3.1 and the session on improving modeling and mapping ecosystem services by demonstrating how different ecosystem service indicators provide can be integrated with ABM and we provide those presented as an initial working set of computational libraries that are available for use and expansion by others. We use this extended version of Aporia to evaluate the effects of agricultural land-management decisions by empirically derived farm-household types from Aargau, Switzerland, on changes and the rate of change in ecosystem services. By representing the impact-response cycle of agricultural decisions in an ABM that harnesses a suite of ecosystem service indicators, we can better assess the cobenefits and tradeoffs among different services over time. Furthermore, the result of this work enables the use of the model to answer a variety of substantive questions; such as how do different socio-economic contexts alter the provision of ecosystem services in rural landscapes?