Effect of Pre‐Harvest Mortality on Harvest Rates and Derived Population Estimates

Multistage time-to-event models improve survival inference by partitioning mortality processes of tracked organisms

Advances in tagging technologies are expanding opportunities to estimate survival of fish and wildlife populations. Yet, capture and handling effects could impact survival outcomes and bias inference about natural mortality processes. We developed a multistage time-to-event model that can partition the survival process into sequential phases that reflect the tagged animal experience, including handling and release mortality, post-release recovery mortality, and subsequently, natural mortality. We demonstrate performance of multistage survival models through simulation testing and through fish and bird telemetry case studies. Models are implemented in a Bayesian framework and can accommodate left, right, and interval censorship events. Our results indicate that accurate survival estimates can be achieved with reasonable sample sizes ( n ≈ 100 + ) and that multimodel inference can inform hypotheses about the configuration and length of survival stages needed to adequately describe mortality processes for tracked specimens. While we focus on survival estimation for tagged fish and wildlife populations, multistage time-to-event models could be used to understand other phenomena of interest such as migration, reproduction, or disease events across a range of taxa including plants and insects.

BAITING AND BANDING: EXPERT OPINION ON HOW BAIT TRAPPING MAY INFLUENCE THE OCCURRENCE OF HIGHLY PATHOGENIC AVIAN INFLUENZA (HPAI) AMONG DABBLING DUCKS

A Eurasian lineage highly pathogenic avian influenza virus (HPAIV) of the clade 2.3.4.4b (Goose/Guangdong lineage) was detected in migratory bird populations in North America in December 2021, and it, along with its reassortants, have since caused wild and domestic bird outbreaks across the continent. Relative to previous outbreaks, HPAIV cases among wild birds in 2022 exhibited wider geographic extent within North America and higher levels of mortality, suggesting the potential for population-level impacts. Given the possible conservation implications of HPAIV in wild birds, natural resource managers have sought guidance on actions that may mitigate negative effects of disease among North American bird populations, including modification of existing management practices. Banding of waterfowl is a critical tool for population management for several harvested species in North America, but some banding techniques, such as bait trapping, can lead to increased congregation of waterfowl, potentially altering HPAIV transmission. We used an expert opinion exercise to assess how bait trapping of dabbling ducks in Canada may influence HPAIV transmission and wild bird health. The expert group found that it is moderately likely that bait trapping of dabbling ducks in wetlands will significantly increase the transmission of HPAIV among individual ducks, but there is a low probability that this will result in significant population-level effects on North American dabbling ducks. Considering the lack of empirical work studying how capture and handling methods may change transmission of HPAIV among waterfowl, as well as the importance of bait trapping for waterfowl management in North America, future work should focus on filling knowledge gaps pertaining to the influence of baiting on HPAIV occurrence to better inform banding procedures and management decision making.

Including a spatial predictive process in band recovery models improves inference for Lincoln estimates of animal abundance

Abundance estimation is a critical component of conservation planning, particularly for exploited species where managers set regulations to restrict harvest based on current population size. An increasingly common approach for abundance estimation is through integrated population modeling (IPM), which uses multiple data sources in a joint likelihood to estimate abundance and additional demographic parameters. Lincoln estimators are one commonly used IPM component for harvested species, which combine information on the rate and total number of individuals harvested within an integrated band‐recovery framework to estimate abundance at large scales. A major assumption of the Lincoln estimator is that banding and recoveries are representative of the whole population, which may be violated if major sources of spatial heterogeneity in survival or harvest rates are not incorporated into the model. We developed an approach to account for spatial variation in harvest rates using a spatial predictive process, which we incorporated into a Lincoln estimator IPM. We simulated data under different configurations of sample sizes, harvest rates, and sources of spatial heterogeneity in harvest rate to assess potential model bias in parameter estimates. We then applied the model to data collected from a field study of wild turkeys (Meleagris gallapavo) to estimate local and statewide abundance in Maine, USA. We found that the band recovery model that incorporated a spatial predictive process consistently provided estimates of adult and juvenile abundance with low bias across a variety of spatial configurations of harvest rate and sampling intensities. When applied to data collected on wild turkeys, a model that did not incorporate spatial heterogeneity underestimated the harvest rate in some subregions. Consistent with simulation results, this led to overestimation of both local and statewide abundance. Our work demonstrates that a spatial predictive process is a viable mechanism to account for spatial variation in harvest rates and limit bias in abundance estimates. This approach could be extended to large‐scale band recovery data sets and has applicability for the estimation of population parameters in other ecological models as well.