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Scottish Marine and Freshwater Science Reports

Formal report series, containing results of research and monitoring carried out by Marine Scotland Science


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Scoping Study - Regional Population Viability Analysis for Key Bird Species CR/2016/16

Scottish Marine and Freshwater Science Vol 11 No 10

The Scottish Government has set a target of 100% of Scottish demand for electricity to be met by renewable sources by 2020. Offshore renewables have the potential to make a significant contribution to achieving this target. However, the Scottish Government has a duty to ensure that offshore renewable developments (ORDs) are achieved in a sustainable manner, by protecting habitats and species from adverse impacts.

ORDs may negatively affect seabirds, in particular due to collisions with turbine blades, displacement to less favourable habitats and barrier effects to movement. Population Viability Analysis (PVA) is a common approach in Environmental Impact Assessments to forecast potential impacts of marine renewables on protected populations such as seabird species. There are several methods of PVA available to use that vary in their complexity, data requirements and biological reality.

This project provides a comparative investigation of these methods for seabirds, describing model performance, providing a set of recommendations for practitioners and highlighting research gaps.

The project recommends the use of the Leslie-matrix model as the most broadly applicable and biologically realistic method with the additional recommendation of adjusting demographic rates relative to abundance data, in those populations where adequate abundance data are available, to reduce uncertainty in forecasting.

The report recommendations provides a roadmap for improving how PVA is used in environmental assessment providing practical approaches for practitioners of PVA. Specifically, these recommendations help work towards improved common approaches to predicting impacts and reducing uncertainty in assessments.

This research is part of the Scottish Marine Energy Research Programme (ScotMER).

Searle, K., Butler, A., Bogdanova, M. and Daunt, F. 2020. Scoping Study - Regional Population Viability Analysis for Key Bird Species CR/2016/16. Scottish Marine and Freshwater Science Vol 11 No 10, 118pp. DOI: 10.7489/12327-1
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Temporal Coverage
1998-01-01 to 2017-12-31
UK Open Government Licence (OGL)
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At the national scale, we compared deterministic and stochastic Leslie matrix models (which are usually used in practice for PVAs) against each other, and against a range of simple time series growth models. We applied these methods to data on abundance, breeding success and survival for 15 seabird species, for breeding colonies throughout the British Isles. We evaluated performance by applying the methods to abundance and demographic data, with these split in to a training period and a subsequent “test” period, assessing whether the predictions that the methods generated for the “test” period were consistent with the observed counts of abundance for that period. We considered four possible definitions of the test period – 1998-2017, 2003-2017, 2008-2017 and 2013-2017 – and in each case considered the training period to be all years (with suitable available population data) prior to this.

In one region (Forth/Tay), for five species, we also used a five year test period (2013-2017) to compared this suite of approaches against the Semi-Integrated Population Models (SIPMs) produced by Freeman et al. (2014) and Jitlal et al. (2017) (termed Bayesian State Space Models in those reports).

We assessed performance of methods by looking at: a) whether the method was possible to apply; b) how frequently it yielded “highly implausible” results (i.e., results that are more than 100 times larger or smaller than the actual abundance); c) whether it produced systematically biased results (i.e. over-estimated or under-estimated actual abundance); d) how much error the methods had, on average, in predicting the observed count; e) whether the method provided an accurate quantification of uncertainty; f) the level of uncertainty associated with each method and g) the computational time required to implement the method.

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Marine Scotland
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