Development of a population model tool to predict shooting levels of Greenland barnacle geese on Islay

Funded by NatureScot (Formerly Scottish Natural Heritage).

As part of the 10-year Islay Sustainable Goose Management Strategy (ISGMS), population management has been carried out on Islay based on a previous Population Viability Analysis (PVA) (Trinder 2005, 2014). However, Scottish Natural Heritage (SNH) now wishes to update its existing population model because intended Greenland barnacle geese (GBG) reductions during the first years of the ISGMS have proved difficult to achieve. Here, we present a new modelling approach combining data on population size, land-use, climate, and shooting effort that will enable shooting bags to be derived under quantified levels of uncertainty. Main findings  The Greenland barnacle goose (GBG) population on Islay has shown a logistic growth rate. After an initial rapid increase in population size, the population growth rate has declined.  The recent (e.g. 2003-2015) GBG Islay population fluctuates around 45,000 (± 4,082 standard deviation) individuals  The population model (PM) developed here accurately predicts the average winter population of GBG on Islay measured between November and March (inclusive) in the absence of culling on Islay.  Based on previous work, the PM assumes that both climate and the area of improved grassland (AIG) are strong predictors of the size of the GBG population on Islay. Similarly, the PM requires the inclusion of shooting bags implemented on Greenland and Iceland to estimate future population trends. Thus, all of the above (i.e. climate, AIG and shooting bags) need to be updated in the model to obtain future population predictions.  Integration of the PM into the Generalised Management Strategy Evaluation (GMSE) framework provides a tool for forecasting the dynamics of geese based on management targets and maximum allowed shooting bags.  The PM used here to inform shooting bags via the GMSE approach provides a good fit to available historic data and performs better than using the population count from the previous year alone, or using a simpler logistic growth model. RESEARCH REPORT Summary ii  For the PM-GMSE modelling approach to work, it is expected that the user updates the value for each predictor (climate, AIG and shooting bags) in the model so that it can be re-run each year. If such data are not available, a simpler (e.g. logistic growth approximation) population model should be used.  The PM-GMSE approach produces an estimate of the future GBG mean winter count on Islay, as well as a range of shooting bags given a population target.  For an initial run of 1,000 simulated managed populations with a management target of 29,000 and a maximum per year shooting bag of 2,500, most simulations came close to the management target within 10 years. But uncertainty and stochasticity could lead to the target being achieved in a shorter or longer time period, as well as higher or lower population sizes.  Future access to individual-based datasets will allow the implementation of more sophisticated models (e.g. integral population model, IPM) able to account for demographic rates, including processes of immigration and emigration.

Total award value £9,947.50

People (1)


Professor Nils Bunnefeld

Professor Nils Bunnefeld

Professor, BES

Outputs (1)


Research centres/groups