The CSC Platform offers the following resources to support and add value to collaborative research projects. In return, the platform benefits from the additional data gathered and more detailed information on specific aspects of the arable ecosystem. In return for free access to these resources all we ask is for joint authorship on initial publication and that any data gathered are stored alongside core datasets in our long-term data archive.
Data on the key indicators of arable ecosystems can be used for new analyses or as context to add value for shorter-term research projects. Data from all core datasets are double punched, QA checked and stored in a fully relational SQL database. Each entry is referenced to a specific date and point in the field allowing easy extraction of subsets and combinations of variates for any given analysis. The database also contains genstat output from REML analysis of variety/treatment/yeareffects on each of the main variates.
Surveys of each of the key are collected from 360 permanent GPS sample locations across all fields and treatments. Samples are collected each growing season following standardised sampling protocols. Once processed for analysis, subsample from each strip/treatment/field from each growing season are archived and available for future research.
Oven dried, milled samples:
- soil (bulk soil to 20 cm depth)
- weeds (separated into monocots and dicots)
- crop material (separated into stems and grain)
- 2mm sieved bulk soil from all GPS locations every year stored at -80 deg C
- pitfall trap and vortis samples from the cropped area and field margins are separated into groups and stored in 70% alcohol at 5 deg C.
The paired comparison of sustainable and conventional cropping systems is set up to monitor long-term trends in system response. This provides an ideal platform for shorter term research that aim to gain a more mechanistic understanding of system processes.
The Scottish Government RESAS Underpinning Capacity programme funds the matinenance of the platform but does not have the resources for more intensive studies. Our platform provides an ideal base to support additional research projects which benefit from the historical build-up of differences between cropping systems and background data on systems indicators that may not be affordable to collect from scratch.