Impact of diversity of ownership scale on social, economic and environmental outcomes

Report on the impact of diversity of ownership on the socioeconomic outcomes for rural areas.


This project was designed to examine the social, economic and environmental outcomes that may have resulted in three case study localities from the fragmentation of large land holdings into smaller units since 1900 by comparing them against outcomes in three paired case study localities where scale of land ownership has been maintained. As there are many factors that have influenced local outcomes beyond scale of land ownership, a non-exhaustive list of 'other factors' was developed to help identify the key factors in the development process of each case study.

The initial case study selection method was to identify six proximal historic estates (three pairs) which were similar in character (one of each pair having been fragmented whilst the other had remained substantially intact) and collect information on both these areas and communities within their boundaries. However, after consideration of this approach to selecting case studies and the methods of assessing outcomes in more detail, the research team concluded that it would beneficial to move away from using estate areas to utilising parishes instead. The rationale for this methodological change surrounded the imperfect knowledge of (changing) estate boundaries and the fact that these do not align themselves to administrative boundaries and data. The parish approach had the benefit of being able to have greater confidence in using administrative information in detailing the timeline of change within each case study.

The project was designed around five key methodological stages to provide case study evidence on the impacts of diversity of ownership in Scotland.

Literature and Policy Review: provided the context for the project including a review of land ownership patterns, policy and other factors affecting the social, economic and environmental development of rural communities in Scotland.

Development of Assessment Frameworks: created three robust and transparent methodological frameworks to assess: (a) social, economic and environmental outcomes at the local level; (b) factors, other than land ownership scale that may have led to observed local community outcomes; and (c) the selection of comparable case studies. The Scottish Government and representatives of key stakeholder organisations were provided with the opportunity to comment on these frameworks.

Case Study Selection: analysed bio-physical Geographical Information System ( GIS) datasets to scientifically select three appropriately paired case studies that met the Scottish Government's criteria. At the direction of the Scottish Government this project excluded crofting areas and areas under community land ownership [19] as potential case studies.

Data Collection: created quantitative profiles of case studies and undertook qualitative fieldwork to ascertain how local outcomes have been achieved and what role, if any, scale of land ownership played.

The quantitative profiling of case studies utilised a wide range of datasets (e.g. population census, Integrated Administration and Control System, June Agricultural Census, environmental GIS datasets and Sasine Register) to provide a timeline of key land ownership changes, and statistical timelines for key outcomes (demography, housing, etc.) for each case study. For population census data [20] there was a need to match output areas to parish boundaries using National Records for Scotland lookup tables [21] due to boundary changes for official statistics.

Qualitative fieldwork was undertaken in case studies in order to elicit information regarding local "trigger events" and trends and their causes using both semi-structured interviews with key individuals (see Appendix 2 for interview schedule) and focus groups with wider interest groups (see Appendix 3 for topic guide) were conducted in each case study. The semi-structured interviews were conducted with land owners and/or managers, local heritage groups/historians and other community members in order to develop a more detailed understanding of parish history over the study period. These case study timelines were triangulated with the quantitative case study profiles and an adapted participatory multi-criteria analysis approach ( MCA) was used to evaluate the perceived main drivers of the social, economic and environmental change (following Davies et al, 2013; Sheppard and Meitner, 2005).

In each case study between 5 to 10 semi-structured interviews were conducted, with most carried out prior to the focus groups and some afterwards to allow for follow-up with some participants who were unable to make the dates/times of the focus groups. Three focus groups were targeted per case study with the local business community, land managers and the wider community. However, due to a low availability of business representatives, this focus group was combined with the wider community focus group in some case studies. Key contacts were identified initially through online research, including local historians, chairs/secretaries of community councils and the main local landowner(s)/estate manager.

With the aim of developing a diverse purposive sample of community members, business owners and land managers/farmers as potential participants, a database of contacts was developed through emailing and phoning key contacts, adopting a snowball sampling approach (where recruited participants help identify further possible participants from among their acquaintances and contacts). This approach generated a relatively comprehensive database of owner-occupier and tenant farmer contacts, local business listings and a range of community members. Interviews conducted with key contacts led to further identification of relevant land managers, farmers and community representatives. Following the development of specific lists for each focus group, potential participants were contacted individually by letter, email and phone to invite their participation in the process and made aware of the date, time and location of the most relevant focus group.

The sample for both interviews and focus groups was generally biased towards older community members due to the historical focus of the work. This sample of older, longer term residents undoubtedly introduced biases in the qualitative feedback, and it was notable that observed changes over time were often perceived negatively, with many aspects of community life, particularly relating to community cohesion, considered better in the past. Younger and newer community members would have offered different socio-economic perspectives but, due to the historic nature of the research in identifying changes, they were not specifically targeted as fieldwork participants.

Data analysis and write up: qualitative, thematic analysis of notes from case study interviews and focus groups was integrated with the quantitative case study profiles and case study timelines, in order to complete the data requirements of the two assessment frameworks. Interpretation of these completed frameworks and the case study timelines provided an evidence-base for conclusions on/insights into the outcomes arising from diversity of land ownership, including a discussion of the limitations of the approach. An assessment of commonalities and differences in the quantitative indicators and the rich context provided by the qualitative results across case studies allowed conclusions to be drawn on the effect of land ownership scale on local outcomes.

Observations on qualitative approach to data gathering

The fieldwork team made a number of observations about the approach adopted that may act to guide future research:

  • The task of identifying appropriate people to interview and invite to the focus groups was not straightforward and therefore took considerably longer than anticipated, due to the practicalities of locating contact details and confirming willing participation, therefore recruitment costs were relatively high.
  • Most of the participants were long term residents as many newer residents felt they did not have the tacit knowledge of local changes that occurred over the study period, thereby limiting the recruitment pool available. This made recruitment more difficult (i.e. people not feeling they were able/suitable to take part, or not targeting certain groups) and also meant that the findings are biased towards the views of the more elderly, long-term, residents and those with an interest in local history. Local historical knowledge was dependent on the participants although some gaps in knowledge were filled through local books and media.
  • The participatory timeline process, in which participants completed a timeline of important change factors, worked very well by animating people and ensuring their engagement in the focus group discussion.
  • Participants often focused attention to perceived negative factors in each of the case studies rather than discussion of positive factors, even when guided to discuss more positive elements.
  • Other than land based businesses it was challenging to get a number of other businesses to engage in the project especially where they felt they had no real connection to landownership. Many businesses that were influential to case study communities within were actually located outwith case study parish boundaries and therefore were not invited to participate.
  • Identification of community "gatekeepers" is important for recruitment but it is also acknowledged that these people can bias who is recruited.
  • The multi-criteria analysis ( MCA) approach worked well when there was a common issue that people could debate. However, the approach was considered too difficult for some to make an assessment of the key factors for all nine identified sustainable rural development "ingredients" as participants often found close interdependencies in factors or outcomes meaning that they could become confused by the task. A reduced, more targeted MCA is recommended for future community research.
  • Tenant farmers sometimes needed reassurance that the land owner or their representatives would not attend the focus group in order to encourage participation of the tenant farming community (i.e. many were reticent to engage when their landlords may be present). Main landowners (or their representatives) were interviewed separately.

Case Study Selection

Option estates / parishes

The intention, from the outset of this work, was to ensure that the parishes (and hence estates) used in the study were not identifiable. This was perceived as important to ensure that sentiments and opinions were non attributable, thereby improving the likelihood of local participation during the fieldwork stage. As such the case study locations and estates have been anonymised throughout this report.

Following agreement with the Scottish Government to use parish boundaries instead of estate boundaries as a means of selecting case studies, the team set out to identify unfragmented and fragmented estates that were in similar geographic locations and are (or were) the dominant land holding in a parish. These estates were identified from a range of sources, including: the teams' collective knowledge of unfragmented and fragmented estates; land ownership literature; historic valuation office records; and current land ownership databases (including Who Owns Scotland [22] , Deer Management Groups, etc.). This process allowed us to identify a range of 'option' parishes (as proxies for estates) in similar locations (grouped into 'sets') to geospatially analyse where the parish either: (a) largely remains under the influence of a small number of large estates, or; (b) was historically under the control of a small number of large estates but has become more fragmented.

The option estates/parishes within local 'sets' were picked to be of similar characteristics whereas the different local 'sets' of parishes were selected to ensure a range of different: land qualities, farming systems, degrees of peripherality, etc. were available for the selection of case study pairs. An initial set of 28 option parishes, grouped into 6 local sets, was identified, and following consultation with RESAS and stakeholder groups this was expanded to 31 parishes, grouped into 7 local sets that included both fragmented and unfragmented estates.

Following the selection of the option parishes a number of Geographic Information System ( GIS) datasets were used to analyse the option parishes to allow an objective scientific assessment of similarities and differences to be made between option parishes within each geographic cluster. The purpose of this exercise was to assess the similarities of parishes within each set thereby ensure that each of the final three paired case study parishes were as similar as possible yet reflected different types of estate and differing degrees of peripherality.

The GIS datasets analysed included:

  • Altitude / topography
  • The Macaulay Land Capability for Agriculture ( LCA) classification
  • Land Cover of Scotland ( LCS88)
  • Peripherality (8 fold rural urban classification)
  • Less Favoured Area ( LFA)

A summary of the GIS analysis are presented in Appendix 4. As an example of the scientific selection process amongst the option estates Figure 1 reveals the proportion of land within each LCA class within each of the option parishes [23] . For example in Set 1 each of the parishes has a high proportion of LCA 3.2 land (land capable of producing a moderate range of crops with a tendency to grass within rotations) whilst parishes in Set 6 have a high proportion of LCA 6.1- 6.3 (land capable of only rough grazing due to intractable physical limitations). This helped identify within the geographic sets which parishes are closely similar in terms of land capability proportions allowing for further comparisons between unfragmented and fragmented land ownership parishes within each set.

Figure 1 Area of each LCA (as % of Parish) for option parishes - anonymised


Selected Paired Case Studies

Having considered all the GIS evidence generated the merits of the different sets and option parishes were considered. It was concluded that there could be four useful case study pairs to study; however, with budget and time constraints in conducting fieldwork and in order to meet the Scottish Government's requirements to assess a range of land capabilities and range of distances from major urban centres the most appropriate three were selected. These include pairs that are (a) very accessible to major urban area with mixed farmland; (b) relatively accessible with good quality grazing land; and, (c) hill and upland land in remoter areas. The case study pairings chosen were:

A1 (fragmented) and A3 (unfragmented)
E2 (fragmented) and E4 (unfragmented)
F1 (fragmented) and F3 (unfragmented).

The initial numbering system used for parishes considered as potential case studies is potentially confusing if used for the actual case studies (i.e. the reference numbers become non-sequential). Hence the selected case studies have been renumbered to facilitate interpretation of the results throughout this report. The new reference number for the anonymised case studies area are:

Case study A1 = 1a
Case Study E2 = 2a
Case Study F1 = 3a

Case Study A3 = 1b
Case Study E4 = 2b
Case Study F3 = 3b

An anonymised summary description of each of the chosen case study parishes is provided in Table 2

Table 2 Anonymised description of case study pairs

Paired Case Studies
Landholding Scale Maintained
Landholding Scale not Maintained
Parish 1a: is an accessible rural area with the main village being about half an hour from a major urban centre. It contains six villages and two smaller hamlets with the two largest villages being located on main roads connecting the urban area to its hinterlands. Both main villages contain typical services: shop, restaurant, primary school, village hall and playing fields etc. The population of both villages has increased in the last two decades due to phases of housing development on land sold directly from the main private estate. The parish is largely owned by a single private estate with a handful of other private landowners. Primary industry includes mixed farming (largely tenanted), quarrying, and forestry, with significant local employment influenced by urban employment. Parish 1b: is an accessible rural area with the main village being about 25 minutes from the centre of a major urban centre. It contains two towns, one of which has been growing rapidly in the last 20 years. The area is well serviced with the main town lying adjacent to the main trunk between two large urban areas. It is situated 5 miles from a main railway station with an airport close by, meaning that it is slightly more accessible than its paired case study, 1a. The main estate in the parish was sold in the decade after the First World War, particular as a result of financial difficulties around the financial crash of the 1920s. The main town is surrounded by new housing developments and industrial estates and has several shops, public hall, caravan park, golf course, etc. but is quite reliant on neighbouring larger town for many facilities (e.g. shops and restaurants) .
Parish 2a: is classified as relatively accessible, with the main estate office being within 20 minutes of an urban centre with a population of just over 10,000. The hillier section of the parish is more remote and has poorer accessibility than the coastal, low lying areas that are well connected through trunk roads. The parish boundary cuts through a large urban area and includes another village that plays an important role as a regional transport hub. A number of other small villages make up the remainder of the parish. The majority of the parish is under the ownership of a private estate although a number of smaller landowners and farmers also own land. Agriculture in the area consists primarily of tenanted farms engaged in livestock farming. Parish 2b: is a coastal parish that is just classified as being remote, situated about 40 minutes from an urban centre with population of just over 10,000. The parish is not directly connected to the main trunk roads servicing the urban centre. There are 4 villages and the main settlement is now a popular tourist destination but facilities are relatively limited in these villages. One of the main estates in the parish was split up in the 1920s and 1940s, although the main house remains within the family associated with historic ownership. Agriculture remains important to the area and is dominated by livestock farming.
Parish 3a The parish has 2 main villages and a cluster of several hamlets, all in relatively close proximity. In a remote rural area, the main village is just under an hour from an urban centre. Situated within the highland area, there are extensive montane and upland habitat and major rivers and lochs. Large parts of the parish area have very low populations. Sporting is a major land use in the parish with livestock farming and forestry also significant activities. The area has been popular with tourists since the 1930s and this has become increasingly so over the years due to its scenic value, range of recreational activities available and relative accessibility. The parish has good access through rail and trunk road networks. Parish 3b In a remote rural area, the parish is over an hour drive from the nearest urban area and consists of one main village and thirteen other small villages and hamlets. There is a rich cultural and archaeological history associated with the area and tourism has been the dominant industry in the parish since the 1960s, due to the high scenic value of the area and its relative accessibility with many related developments (including housing) in the last 30 years. There is extensive woodland cover (associated with commercial forestry and woodland regeneration activities) and livestock farming. The parish contains the summits of several hills, including Munros. The parish has more restricted transport access than its paired case study 3a. The principal estate was largely sold off following the death of the incumbent laird in the 1920s following mounting debts.


Email: Graeme Beale,

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