Efficient use of harvest data: An integrated population model for exploited animal populations

Abstract

1 9 2 0 3 1 marine and terrestrial populations of vertebrates. As individual measures of body mass at both 3 2 capture and death are often collected in fish and terrestrial game species, our model integrates 3 3 capture-mark-recapture-recovery data and data collected at death into a body mass-structured 3 4 population model. It allows the observed number of individuals harvested to be compared 3 5with the expected number and provides accurate estimates of demographic parameters. 3 63. We illustrate the usefulness of this IPM using an emblematic game species distributed 3 7 worldwide, the wild boar Sus scrofa, as a case study. For this species that has increased in 3 8 distribution and abundance over the last decades, the model provides accurate and precise 3 9 annual estimates of key demographic parameters (survival, reproduction, growth) and of 4 0 population size while accounting for imperfect detection and observation error.4 1 3 4. To avoid an overexploitation of declining populations or an under-exploitation of 4 2 increasing populations, it is crucial to gain a good understanding of the dynamics of exploited 4 3 populations. When managers or conservationists have limited demographic data, the IPM 4 4 offers a powerful framework to assess population dynamics. Being highly flexible, the 4 5 approach is broadly applicable to both terrestrial and marine exploited populations for which 4 6 measures of body mass are commonly recorded and more generally, to all populations 4 7 suffering from anthropogenic mortality causes. 4 8 4 9

Modelling harvest of Greenland barnacle geese and its implications in mitigating human–wildlife conflict

“…This would reduce uncertainty and improve reliability of parameter estimation including differential vulnerability, natural survival and metapopulation dynamics. This IPM provides an example of a sound framework to assess harvest management, which can be adapted and developed should more flyway‐specific data become available (Gamelon et al, 2019; Saunders et al, 2018).…”

“…IPMs also offer improved precision in estimating demographic rates and population size and can estimate latent (unobserved) variables (Kéry & Schaub, 2012; Schaub & Abadi, 2011). The adaptability of IPMs provides an ideal framework to inform and develop management programmes, as parameters can be updated as new data become available (Gamelon et al, 2019; Johnson et al, 2020; Saunders et al, 2018).…”