More management, less damage? With increasing population size, economic costs of managing geese to minimize yield losses may outweigh benefits

Conflicts between farmers and geese are intensifying; yet, it remains unclear how interactions between goose population size and management regimes affect yield loss and economic costs. We investigate the cost-effectiveness of accommodation and scaring areas in relation to barnacle goose (Branta leucopsis) population size. We use an existing individual-based model of barnacle geese foraging in nature, accommodation, and scaring areas in Friesland, the Netherlands, to study the most cost-effective management under varying population sizes (i.e., between 20 and 200% of the current size). Our study shows that population size non-linearly affects yield loss costs and total costs per goose. The most cost-effective management scenario for intermediate to large populations is to avoid scaring of geese. For small populations, intensive scaring resulted in minimized yield loss costs and total costs, but also substantially lower goose body mass. Our results strongly suggest that scaring becomes a less effective management measure as goose populations increase

Integrated population modeling identifies low duckling survival as a key driver of decline in a European population of the Mallard

Europe’s highest densities of breeding Mallards (Anas platyrhynchos) are found in the Netherlands, but the breeding population there has declined by ~30% since the 1990s. The exact cause of this decline has remained unclear. Here, we used an integrated population model to jointly analyze Mallard population survey, nest survey, duckling survival, and band-recovery data. We used this approach to holistically estimate all relevant vital rates, including duckling survival rates for years for which no explicit data were available. Mean vital rate estimates were high for nest success (0.38 ± 0.01) and egg hatch rate (0.96 ± 0.001), but relatively low for clutch size (8.2 ± 0.05) compared to populations in other regions. Estimates for duckling survival rate for the three years for which explicit data were available were low (0.16–0.27) compared to historical observations, but were comparable to rates reported for other regions with declining populations. Finally, the mean survival rate was low for ducklings (0.18 ± 0.02), but high and stable for adults (0.71 ± 0.03). Population growth rate was only affected by variation in duckling survival, but since this is a predominantly latent state variable, this result should be interpreted with caution. However, it does strongly indicate that none of the other vital rates, all of which were supported by data, was able to sufficiently explain the population decline. Together with a comparison with historic vital rates, these findings point to a reduced duckling survival rate as the likely cause of the decline. Candidate drivers of reduced duckling survival are increased predation pressure and reduced food availability, but this requires future study. Integrated population modeling can provide valuable insights into population dynamics even when empirical data for a key parameter are partly missing

Integrated population modeling identifies low duckling survival as a key driver of decline in a European population of the Mallard

Europe’s highest densities of breeding Mallards (Anas platyrhynchos) are found in the Netherlands, but the breeding population there has declined by ~30% since the 1990s. The exact cause of this decline has remained unclear. Here, we used an integrated population model to jointly analyze Mallard population survey, nest survey, duckling survival, and band-recovery data. We used this approach to holistically estimate all relevant vital rates, including duckling survival rates for years for which no explicit data were available. Mean vital rate estimates were high for nest success (0.38 ± 0.01) and egg hatch rate (0.96 ± 0.001), but relatively low for clutch size (8.2 ± 0.05) compared to populations in other regions. Estimates for duckling survival rate for the three years for which explicit data were available were low (0.16–0.27) compared to historical observations, but were comparable to rates reported for other regions with declining populations. Finally, the mean survival rate was low for ducklings (0.18 ± 0.02), but high and stable for adults (0.71 ± 0.03). Population growth rate was only affected by variation in duckling survival, but since this is a predominantly latent state variable, this result should be interpreted with caution. However, it does strongly indicate that none of the other vital rates, all of which were supported by data, was able to sufficiently explain the population decline. Together with a comparison with historic vital rates, these findings point to a reduced duckling survival rate as the likely cause of the decline. Candidate drivers of reduced duckling survival are increased predation pressure and reduced food availability, but this requires future study. Integrated population modeling can provide valuable insights into population dynamics even when empirical data for a key parameter are partly missing