• Functional Land Management for managing soil functions: A case-study of the trade-off between primary productivity and carbon storage in response to the intervention of drainage systems in Ireland

      O'Sullivan, Lilian; Creamer, Rachel E.; Fealy, Reamonn; Lanigan, Gary; Simo, Iolanda; Fenton, Owen; Carfrae, J.; Schulte, Rogier; Department of Agriculture, Food and the Marine (Elsevier, 2015-09-30)
      Globally, there is growing demand for increased agricultural outputs. At the same time, the agricultural industry is expected to meet increasingly stringent environmental targets. Thus, there is an urgent pressure on the soil resource to deliver multiple functions simultaneously. The Functional Land Management framework (Schulte et al., 2014) is a conceptual tool designed to support policy making to manage soil functions to meet these multiple demands. This paper provides a first example of a practical application of the Functional Land Management concept relevant to policy stakeholders. In this study we examine the trade-offs, between the soil functions ‘primary productivity’ and ‘carbon cycling and storage’, in response to the intervention of land drainage systems applied to ‘imperfectly’ and ‘poorly’ draining managed grasslands in Ireland. These trade-offs are explored as a function of the nominal price of ‘Certified Emission Reductions’ or ‘carbon credits’. Also, these trade-offs are characterised spatially using ArcGIS to account for spatial variability in the supply of soil functions.To manage soil functions, it is essential to understand how individual soil functions are prioritised by those that are responsible for the supply of soil functions – generally farmers and foresters, and those who frame demand for soil functions – policy makers. Here, in relation to these two soil functions, a gap exists in relation to this prioritisation between these two stakeholder groups. Currently, the prioritisation and incentivisation of these competing soil functions is primarily a function of CO2 price. At current CO2 prices, the agronomic benefits outweigh the monetised environmental costs. The value of CO2 loss would only exceed productivity gains at either higher CO2 prices or at a reduced discount period rate. Finally, this study shows large geographic variation in the environmental cost: agronomic benefit ratio. Therein, the Functional Land Management framework can support the development of policies that are more tailored to contrasting biophysical environments and are therefore more effective than ‘blanket approaches’ allowing more specific and effective prioritisation of contrasting soil functions.
    • Spatial evaluation and trade‐off analysis of soil functions through Bayesian networks

      Vrebos, Dirk; Jones, Arwyn; Lugato, Emanuele; O’Sullivan, Lillian; Schulte, Rogier; Staes, Jan; Meire, Patrick; European Union; 635201 (Wiley, 2020-08-23)
      There is increasing recognition that soils fulfil many functions for society. Each soil can deliver a range of functions, but some soils are more effective at some functions than others due to their intrinsic properties. In this study we mapped four different soil functions on agricultural lands across the European Union. For each soil function, indicators were developed to evaluate their performance. To calculate the indicators and assess the interdependencies between the soil functions, data from continental long‐term simulation with the DayCent model were used to build crop‐specific Bayesian networks. These Bayesian Networks were then used to calculate the soil functions' performance and trade‐offs between the soil functions under current conditions. For each soil function the maximum potential was estimated across the European Union and changes in trade‐offs were assessed. By deriving current and potential soil function delivery from Bayesian networks a better understanding is gained of how different soil functions and their interdependencies can differ depending on soil, climate and management. Highlights When increasing a soil function, how do trade‐offs affect the other functions under different conditions? Bayesian networks evaluate trade‐offs between soil functions and estimate their maximal delivery. Maximizing a soil function has varied effects on other functions depending on soil, climate and management. Differences in trade‐offs make some locations more suitable for increasing a soil function then others.