Achieving Sustainable Agricultural Systems (ASSIST)

Transcription

1 Photo: Shutterstock Image copyright Shutterstock Achieving Sustainable Agricultural Systems (ASSIST)

2 Achieving Sustainable Agricultural Systems (ASSIST) Image copyright FreeImages Ensuring future food security without causing unacceptable environmental damage is one of the greatest threats facing humanity The science underpinning the concept of SI is incomplete and requires an immediate and bold investment Aim: to develop innovative farming systems that increase crop productivity & resilience to future perturbations, while reducing the environmental & ecological footprint of agriculture

3 Strategies for achieving SI Food production High input conventional farming A B C Low intensity Organic farming (e.g. farming organic) Natural capital & ecosystem services A: maintain yields while reducing environ. impact B: increase yields while reducing environ. impact C: increase yields without negative environ. impact

4 Image copyright Marek Nowakowski Wider science context Unites BBSRC and NERC-funded science essential for UK leadership in SI research Builds on current shorter-term and narrower-focus investments e.g. existing policies / practice (Defra), or single/few components of the agroecosystem (RCUK) Our focus is distinct in aiming to quantify effectiveness and robustness of novel far-horizon whole-systems agricultural and technologies Core to delivering SDGs

5 Opportunities for strategic partnerships Opportunities for new partnerships to address critical knowledge gaps (e.g. the socio-economic barriers to uptake) Community workshops to share plans in greater detail; consider how to build on ASSIST to deliver more excellent science A community platform providing opportunity for research, training & dissemination (including access to existing RRes & CEH Farms - North Wyke, Hillesden) Access to data via new technology (e.g. national sensor networks; Sentinel etc.) Hillesden Platform 1000ha

6 Model validation Image copyright Marek Nowakowski Structure WP1: Limitations on crop productivity WP2: Environmental impacts of agriculture WP3: Sustainable solutions (agri-tech + nature based) WP4: Synthesis modelling: Optimisation of future agriculture WP5: Agri-informatics & tools Implementation farm field landscape Refinement of management solutions External data: Agrimetrics, SIP, SARISA etc. Project co-ordination

7 WP1: Biophysical limitations on crop productivity Innovative remote sensing products mapping of crop type, health and productivity at national scale Attribution of spatial constraints on crop yield & resilience through time Quantification of limits on current and future crop yield 3D models of water connectivity at the farm and catchment scale: integrating surface and sub-surface processes in relation to farm productivity Pollinator habitat Crop yield values Water resource protection 250m

8 WP2: Environmental impacts of future agriculture Image copyright Shutterstock Predicting the effects of agricultural management on water quality and nutrient loss by adapting & extending the LTLS model P (Tonnes) By Trevor Rickard, CC BY-SA 2.0, d= Impacts of agricultural management on soil carbon and GHG fluxes Enhancing biological resilience of agro-ecosystems through parameterisation & analysis of response and effects traits of key species Predicted P fluxes from the LTLS model resulting from arable and improved grassland land use High FD Low FD National distribution of functional diversity of native crop pollinators. Note potential deficits in areas of important crop production

9 Image copyright Richard Pywell, CEH WP3: Sustainable solutions Core to ASSIST will be a statistically robust multi-site experiment infrastructure commercial arable and grassland farms Test field-scale combinations of innovative naturebased and agri-tech farming systems: Nature-based: enhance natural processes associated with crop production (so-called ecological intensification ), in particular soil function, and biodiversity-mediated pollination and pest-control services Agri-tech approaches: best-practice agronomy to improve resource-use efficiency and pest management to either maintain or increase yields while reducing the negative environmental impacts (e.g. precision farming, smart rotations etc.)

10 Eco-intensification of agriculture 6 year experiment on 1,000ha commercial farm Removed 3% to 8% of low-yielding land from cropping Created habitats for beneficial species (pollinators, pest predators) Yield of some crops increased by 35%, not net loss of yield for others First evidence of sustainable intensification Detailed arable crop yield mapping from the Hillesden Research Platform (red = high / green = low)

11 WP3: Farm experiment network a) Business as usual (Control) b) Agri-tech solutions (e.g. pesticide & fertiliser placement, crop varieties & N inhibitors) a) Control b) Agri-tech c) Nature-based solutions (e.g. 1yr fallow & in field strips) d) Agri-tech +Naturebased solutions c) Naturebased d) Agri-tech +Nature Design of a factorial experiment testing nature-based and agri-tech farming systems against a business as usual control Powerful factorial design Farms along the trade-off continuum of environmental services vs. productivity Will consider interaction with landscape Treatments defined at stakeholder workshops (building on existing best practice) community-led solutions Increase yield, reduce inputs & costs, lower environmental footprint, enhance natural processes

12 WP4: Synthesis: optimisation of future agriculture Using the InVEST model to synthesise the knowledge gained on: where to intensify/extensify production (WP1), the impacts of changed agricultural management on natural capital and biodiversity (WP2), and the application of intervention measures to mitigate/enhance these effects (WP3) build resilience future agroecosystems Targeting sites with potential for intensification / extensification (WP1) Risks to natural capital & biodiversity of future intensification (WP2) Conflicts Avoidance & Mitigation strategies (agri-tech + nature-based) (WP3) Scenarios of environ. change Building resilience of agro-ecosystem (WPs2/3) Trade-offs Optimisation Optimisation Planning future multi-functional agricultural landscapes Schematic showing how ASSIST will be used to identify and manage conflicts for planning future multi-functional agricultural landscapes Synergies SITE 1: A Elliot, North Farm Norton Barant Warminster BA12 0EP Phone: Mob: GridRef: ST9251 1km buffer Field Boundary Meters

13 WP5: Agri-informatics and tools Develop a new national Land Water Information System for Agro-ecology bringing together CEH/BGS/RRes data with that of Defra & the farming industry (via Agrimetrics) Create value added (modelled) products, and make data fully discoverable, interoperable and scalable Provide novel decision support tools to inform land management decisions and testing scenarios of intensification Intensification scenarios National: land cover transitions Land Cover Map Landscape: crop pattern & rotation Land Cover Map Plus Field: crop inputs Industry data Pesticide & Fertiliser Surveys Data infrastructure (integration, validation, discovery metadata, use of standards and vocabs etc. ) Biodiversity & natural capital National base data sets (examples): Rres/CEH Water quality BGS Soil carbon CEH GHG maps RRes Insect Trap BRC Biodiversity indicators CEH Pollination service CEH Pest control Defra Agri-environment Defra Farm Business Defra Crops Risks and conflicts identified Overlay & visualisation tool Fig. 7. Intensification Risk Mapping Tool

14 Getting involved This novel cross-council investment is an opportunity to coalesce and enable research ideas in this area for future funding (e.g. Newton, SPAG etc.) Kick-off meeting summer 2016 Community workshops Project Advisory Group Project web pages Data portal & tools Contacts: Prof. Richard Pywell (CEH) Prof. John Crawford (RRes)

15 Image copyright Lucy Balll, CEH Photo: Lucy Hulmes ASSIST will provide the long-term, large-scale strategic underpinning for a community-led transformation of agriculture New footer