Aims and objectives:
Evidence suggests that any future agricultural intensification could be detrimental to natural capital and associated ecosystem services, while extensification of management may provide environmental benefits, but with lower productivity. Scenarios of agricultural intensification will also interact strongly with climate. Accurate prediction of the environmental impacts of future agricultural scenarios and the scales at which these will operate is central to the formulation of effective mitigation strategies and sustainable farming systems.
The aims of this work package are to:
- To predict the effects of changes to agricultural management on water quality and nutrient losses;
- To predict the impacts of changes to agricultural management on soil carbon pools and greenhouse gas fluxes from soils and waters;
- To develop our understanding of the biological underpinning of ecosystem resilience to the impacts of future stressors resulting from agricultural and climate change;
- To develop an ecosystem services assessment tool for grassland and arable systems.
Key outcomes:
- Robust predictions of the impacts of future agricultural management on soil carbon, GHG emissions, nutrient fluxes and water quality
- A database compiling all known response and effects traits for crop pollinators and pest predators
- Models describing the resilience of biodiversity-mediated ecosystem services to agricultural change
- Strategies to increase the resilience of agro-ecosystems to future environmental stressors to ensure continuity of food supply
- A GIS-based ecosystem services assessment tool for grassland and arable systems that operates at a hydrogeomorphic unit scale
Key products and datasets:
The Climate, Hydrology and Ecology research Support System (CHESS).
Analysis and simulation of the Long-Term / Large-Scale interactions of C, N and P in UK land, freshwater and atmosphere (LTLS)
Relevant publications:
A.P. Whitmore (2007) Describing the transformation of organic carbon and nitrogen in soil using the MOTOR system Computers and Electronics in Agriculture, Volume 55, Issue 2, Pages 71–88.
L. Wu, M.B. McGechan, N. McRoberts, J.A. Baddeley, C.A. Watson (2007) SPACSYS: Integration of a 3D root architecture component to carbon, nitrogen and water cycling—Model description Ecological Modelling. Volume 200, Issue 3-4, Pages 343–359.
E. Tipping et al. (2012) N14C: A plant–soil nitrogen and carbon cycling model to simulate terrestrial ecosystem responses to atmospheric nitrogen deposition. Ecological Modelling. Volume 247, Pages 11–26.
D. S. Jenkinson, and K. Coleman (2008) The turnover of organic carbon in subsoils. Part 2. Modelling carbon turnover. European Journal of Soil Science, Volume 59, Issue 2, Pages 400–413.
ZM Harris, et al. (2014) Research Spotlight: The ELUM project: Ecosystem Land-Use Modeling and Soil Carbon GHG Flux Trial. Biofuels, Volume 5, Issue 2, Pages 111-116.
B.A. Woodcock, et al. (2013) Crop flower visitation by honeybees, bumblebees and solitary bees: Behavioural differences and diversity responses to landscape. Agriculture, Ecosystems & Environment. Volume 171, Pages 1-8.
T, H. Oliver et al. (2015) Declining resilience of ecosystem functions under biodiversity loss. Nature Communications, In press.
E,Tipping, et al. (2015) LTLS: Analysing and simulating long-term and large-scale interactions of carbon nitrogen and phosphorus in UK land, freshwater and atmosphere. Website.
E,Tipping, et al. (2016) LTLS: Royal Society Meeting June 2016. Website.
P Nadena, et al. (2016) Nutrient fluxes from domestic wastewater: A national-scale historical perspective for the UK 1800–2010. Science of The Total Environment, Volume 572, Pages 1471–1484.
Eigenbrod, F et al. (2011) The impact of projected increases in urbanization on ecosystem services. Proceedings of The Royal Society B Biological Sciences. Volume 278, Issue 1722, Pages 3201-3208.
Lead scientists:
Dr Vicky Bell (Centre for Ecology & Hydrology)
Dr Ed Rowe (Centre for Ecology & Hydrology)
Dr Nick Isaac (Centre for Ecology & Hydrology)
Dr Martin Blackwell (Rothamsted Research)
Professor Adrian Collins (Rothamsted Research)
Professor Andy Whitmore (Rothamsted Research)