top of page

Lindesay Scott-Hayward (Ph. D. Biostatistics)

Centre for Research into Ecological and Environmental Modelling, University of St Andrews

  • LinkedIn
  • GitHub


I work jointly on the conservation of several key species in Namibia and environmental impact assessment for offshore wind in the UK, Denmark and USA. I am a methods developer who is primarily involved in spatially explicit modelling and environmental impact assessment methods and is the main developer/maintainer of the MRSea R package for use in estimating distribution and abundance of animals. The R-package allows the fitting of spatially adaptive 1- and 2D splines in a GLM/GAM framework. Its main applications are in analysing data for environmental statements for the development of offshore wind (visual boat/aerial or digital aerial data) but it also finds use in home range estimation assisting in the conservation of several key Namibian species. She also had a significant contribution to developing guidance, methods and R software (MRSeaPower) for quantifying spatially explicit power to detect change.


I also have a keen interest in training workshops, teaching both in the UK and abroad.  Alongside teaching duties at the University of St Andrews I have delivered workshops in ‘Quantifying the power to detect change’ and ‘Statistical training for decision makers’ and developed materials for introductory statistics courses to up-skill PhD students and staff across the university.


Blend of statistics and biology

  • Methods for spatially adaptive smoothing in one and two dimensions in a GAM framework

  • Modelling species distributions in topographically complex regions

  • Spatially explicit power analysis

  • Multiple Namibian projects: tracking projects, home range analysis, annual wildlife surveys

  • Environmental impact and baseline analysis of offshore windfarms (UK, USA, Denmark)

  • Project Management

Using RCran

  • MRSea

    • GAMs

    • Functions to fit spatially adaptive smoothing splines using the exponential family of distributions and the Tweedie.​

  • MRSeaPower

    • spatially explicit power analysis.

    • Functions to simulate new data with the same characteristics of the original (from a fitted model) and estimate the power to detect change.​

University of St Andrews

  • Statistics upskilling programme (for PGR and Staff)

  • University statistics courses including introductory statistics, GLMs, GAMs and software

  • Field Methods for Conservation and Eco-Tourism

  • Workshops on software packages MRSea and MRSeaPower

  • Bespoke workshops for decision makers (environmental impact assessment)

University Statistician

Assistance for university planning

  • Analysis of university staff and student surveys

  • Module grade assessment

  • Review panel assessment

bottom of page