Modelling Visitor Rates for Special Protected Areas

Special Protected Areas (SPAs) are protected sites within the EU to safeguard the habitats of rare and vulnerable birds, and for regularly occurring migratory species. Within the UK there are 270 SPAs that cover over 2.5 million hectares. SPAs are often made up of estuaries, marshland, heathlands and/or wooded habitats and are open to visitors, who commonly come from the surrounding areas. Whilst there are clear benefits to SPA visitor access (such as health benefits and increased voluntary and conservation work), it is well known that recreational access (such as horse riding, dog walking and mountain biking) can have detrimental effects both in terms of the disturbance of birds and the erosion of habitats.

The Challenge

When local planning authorities are planning a new development, they must consider whether it will affect a SPA and, in particular, how it could impact visitor numbers to a site. As the Government’s advisor on nature conservation, Natural England encourage all planning authorities whose strategies could increase the number of recreational visitors to SPAs to undertake visitor surveys. These surveys collect a wealth of information on SPA visitor numbers and visitor behaviour, but only sample a subset of the SPA access points. To fully understand the impact of new developments, we need to identify what the key drivers of visitor numbers are (for example, distance from the SPA access point) in order to accurately estimate current visitor numbers for the entire SPA and how they might change in the future.

The Approach

Visitor surveys typically provide information on the counts of visitors that arrived at and left a SPA during the survey period and also include a more detailed questionnaire given to a subset of these visitors. These questionnaires collect information such as home postcode, visit frequency, mode of transport and the activity planned during the SPA visit.

Additional information from other sources is also usually required for a detailed analysis. Examples include:

  • GIS data on the distance travelled from the home to the SPA,
  • Access to Suitable Alternative Natural Greenspace (SANG),
  • Population sizes for visitors’ home areas.

Since the underlying data are visitor counts, we fit a Poisson generalized linear model to the data from the access points sampled, which allows us to account for differing lengths of time over which visitor numbers were recorded. Of course, the appropriate model needs to account for the nature of the data and different analyses may require other model structures. For example, if we were analysing multiple SPAs, a mixed-effects model could be used to account for the variation between SPAs.

Using the statistical model, we can:

  1. Estimate the total visitor rate across all access points,
  2. Identify the key drivers of visitor rates (for example, local population size or distance to site),
  3. Predict visitor rates for future scenarios such as an increased population size due to potential new developments in the local area.

The Value

Using a statistical model, we can help local planning authorities, developers and statutory bodies, such as Natural England, to better understand the current visitor rates of a SPA, what the key drivers are and the potential impacts of new developments on visitor numbers. This information is critical when planning for the future and can be used to develop potential mitigation strategies for reducing the impact of new developments on SPAs. For example, by including information on Suitable Alternative Natural Greenspace (SANGs) in the model, we can investigate whether the provision of further SANGs might counteract the increase in the number of visitors to an SPA driven by a new development.