The rural evidence base: what do rural social scientists have available and what do they need? Bill Slee Macaulay Institute

What do we mean by the evidence base? A pool of appropriate data at suitable spatial scale to: –Monitor change –Address contemporary and likely future research questions –Respond to policy needs (not just evaluation) –(from our institute point of view) to link land use and socio-economic data

Our focus The use in a rural context of SIMD and SNS The blending of these with other statistics of relevance and interest

Some recent experience Exploring socio-economic change in Perth and Kinross Scoping impacts of land reform Understanding trends in land use in crofting counties Examining the commercial recreation informal recreation interface for FCS Examining the new entrant problem in Scottish agriculture

Example 1: Perth and Kinross: big spatial units may harbour considerable diversity

…and different stats use different spatial entities

Upper Glen Lyon and Aberfeldy are one spatial unit with land use data

SIMD - an urban indicator? “Eilean Siar, Moray, Orkney Islands and Shetland Islands do not have any data zones in the SIMD per cent most deprived. This does not mean there is no deprivation in these areas rather that it is not concentrated in small areas” Rural deprivation is not geographically concentrated but it does exist

Example 2: Some observations on land reform and rural datasets Community-based land reform is about community decisions- but it is not possible to baseline from existing stats E.g. Gigha is a small part of one SNS data zone, yet Gigha is the relevant unit of change that we need to explore

Data are often not available at the right spatial scale

Example 3: Some observations on crofting Land use and socio-economic datasets are collected on the basis of completely different spatial entities Different admin bodies use different spatial units for data presentation Ag holdings data (JAHC) and wider land use data are incompatible A lack of key socio-economic info on crofts as socio-economic entities

Example 4: Some observations on forestry and informal recreation Good data on forest visits Very poor data on state forest recreation- related expenditures at forest unit level (c. 600 in Scotland) Quite impossible to ascertain where the forest recreation enterprise is breaking even with any accuracy

Example 5: New entrants Not clear how much land is under different tenurial categories which are neither under tenancies or owner occupancy Therefore it is unclear who is working the land (grass lets, cropping licences, contract farming etc) Thus the basic evidence lacking

Some issues of social science How ‘objective’ are the SIMD and SNS indicators- are they socially constructed around predominantly urban values? (the Mackay and Laing example) Are some big dimensions of wellbeing and livelihoods missing? –A sense of greater control over resources and development –Tradeoffs between environmental quality and wealth –Non-market/ecosystem goods and services

SIMD

Conclusions We now have quite good socio-economic ‘wallpaper’ as context Often (in my experience) it does not help greatly to answer specific research questions The land resource does matter and may become even more important with respect to climate change and sustainability agendas –its inter-relationships with socio-economic well-being are weakly documented Trade-offs between different Ecosystem Goods and Services (EGSs) are complex and weakly understood

The workshop format to hrs Break into small groups around tables Address the six questions listed (and add your own if you feel a need to) to hrs All groups together

Stage 1 discussion Can we find/cite examples of successful use of SIMD and SNS in the rural arena in policy relevant academic investigations? Do SIMD and SNS capture the complexity of factors that underpin rural livelihoods? What gaps exist with regard to socio-economic data and how important are they? How could the academic community engage with the policy community in improving rural socio-economic data? Are the policy and academic communities sufficiently engaged with the practice community? What scope is there for innovation in dataset development?

Bringing it together (i) What are the main data gaps? (ii) How can the different communities keep the conversation going? (and do they want to/need to?) (iii) Are academic and policy communities sufficiently engaged with the practice community