This project involves development of a flyway-wide decision model for use in investigating population-management strategies for Greylag Geese. This decision model will consist of three primary elements: (a) a flyway model of population dynamics; (b) a set of decision alternatives (i.e., varying levels of offtake in each management unit); and (c) a value model:

• (a) The development of population models for the NW/SW population of Greylag Geese has been hindered due to evidence of potentially severe bias in extant estimates of abundance and/or offtake (Johnson and Koffijberg 2021). We propose to develop a matrix population model that characterizes the dynamics of both breeding segments (MU1 and MU2) and, critically, that accounts for the mixing of the two segments during autumn and winter. We will parameterize this model using demographic information from published literature and, where necessary, we will rely on basic life history characteristics and allometric relationships (Johnson et al. 2012, 2018). Density-dependent effects in survival and/or reproduction can be accommodated as appropriate. The demographic parameters of the model can be updated when reliable monitoring data become available. As a placeholder, we will use the abundance of breeding pairs in each management unit that was reported in the ISSMP. 
• (b) Decision alternatives consist of varying levels of offtake, including hunting during autumn/winter and derogations during the breeding and wintering seasons. In addition to investigating the effects of the seasonality of offtake, we also will explore how the age structure of the offtake might affect the ability to meet management objectives.
• (c) The development of a value model is critical for identifying preferred population-management strategies. A value model expresses the value associated with different offtake strategies. Value is defined by both the ability of management to meet the population targets in the two management units and by the costs of offtake (e.g., the costs of government-funded derogations). We will use the concept of Pareto efficiency (Kennedy et al. 2007) to assess viable tradeoffs among these two basic management objectives, as well as suggest a possible structure for a multi-attribute value function that could be used to optimize population management.