Quantitative EIA support for windfarm developments
This is the title of the case study that should take up no more than a few lines.
The consenting process for windfarms requires extensive Environmental Impact Assessments (EIAs). An important component of this is the potential impact of developments on animal populations. This requires the design of monitoring programmes covering the pre-developement, development and operational phases. Data collected then requires modelling and simulation work to explore potential impacts and mitigations against these. DMP provide the quantitative support to all these phases, from design, power analysis, Density Surface Modelling (DSMs), Population Viability Analyses (PVAs) and simulation tools (e.g. sCRM).
This is the space for a nicely written and engaging synopsis that will entice people to read.
Clients: Marine Scotland, HiDef Aerial Surveying, SSE
Date: 2019
Client: The London Fire Brigade
Date: September 2018
Permission to build wind-farms is contingent on care for the natural environment. A large part of this is ensuring that the local animal populations are not significantly impacted - this requires a lot of population monitoring and modelling. We have provided modelling for most wind-farms about the UK.
WHAT WE'VE DONE
We've provided survey designs for aerial surveys to achieve particular monitoring objectives. Boat and plane-based survey data has been modelled to explore changes in animal distributions over different phases of wind-farm construction. Potential impacts have been modelled/simulated through to future population impacts to estimate practical consequences.
SOME TECHNICAL BITS
Observation data has to be adjusted for effort to generate local abundance estimates, and where needed, adjusted for imperfect detection (such as boat-based observers) and availability (diving animals) using distance analysis. Modelling consists of density surface models, with inferential adjustments for autocorrelation and bootstrapping. Speculative impacts can be simulated under similar models to explore mitigation or survey power. Estimated redistribution or changes in local abundances may be used in PVAs to determine medium-to-long term effects on populations.
REPRESENTATIVE CASE STUDIES
Quantifying the environment - EIAs#ENVIRONMENT
Measuring product efficacy#MARKETING
Predictive models from remote-sensed data#ENVIRONMENT
Modelling for sports betting#BETTING
