Monitoring abundance of black bears (Ursus americanus) is critical, as this information is required to inform sustainable management of a harvested black bear population. In Ontario, black bears have been monitored using a combination of direct and indirect measures, including determining if harvest is sustainable by examining annual harvest statistics; estimating survival, mortality, and abundance through telemetry studies; modelling population viability using the RISKMAN program; and estimating abundance and density through genetic capture-recapture methods.
Many jurisdictions in the United States reconstruct the hunted population of black bears using harvest and age-at-harvest data to estimate population size and trend. Our objectives were to: 1) Determine whether population reconstruction models could be used as an alternative to direct measures of population size, such as capture-recapture methods 2) Summarize the main data requirements and assumptions common to many population reconstruction models 3) Determine the extent to which those requirements can be met by data available in Ontario
We also provide recommendations to improve the reliability of black bear harvest and age-at-harvest data, which would be required to implement population reconstruction as a viable management tool in Ontario.
Population reconstruction is based on an estimate of the number and age distribution of harvested animals, as well as other auxiliary data, such as hunter effort, to determine the original size, age distribution, and recruitment rate of the harvested population of a wildlife species. To calculate total population size, annual mortality due to other causes must also be known or estimated. We present and discuss six methods of population reconstruction, and describe the data and assumptions required to run the models. We conclude that no population reconstruction model can replace direct estimates of abundance, but such models can provide managers with accurate, important population trend information between years of other surveys.
For accurate and precise population estimates via population reconstruction, harvest and effort data must be complete, accurate, and unbiased. Age-at-harvest data from annual tooth submissions must be accurate and representative of the harvested population. Independently collected auxiliary data, such as mortality or abundance, should be available at regular intervals and be representative of the bear population. Finally, immigration and emigration should be negligible, and harvest mortality should be the main cause of death. If other causes of death are common, the rate of that mortality should either be constant and known, or measured annually for each region.
Ontario harvest and age-at-harvest data for 1985 to 2014 violated the main assumptions of population reconstruction.
* Harvest and effort surveys for non-residents were completed by most non-resident hunters; therefore, they can be considered to be accurate. However, corresponding data for resident hunters were likely more biased through time and across space. Resident hunters may hunt in any wildlife management unit (WMU) with an open season, so if spatial biases in the data exist, we could not account for them because we did not know where non-replying hunters hunted. Harvest and effort data were biased to hunters who replied voluntarily and likely to those who were successful.
* Survey methods changed through time, making reported success rates and projected annual bear harvests inconsistent through time.
*Total bear harvest was estimated using a provincial correction factor instead of a local factor, potentially biasing WMU-specific harvest estimates.
* Non-resident hunters submitted an adequate sample of bear teeth for ageing, but resident hunters did not. As a result, it is unlikely that the sample of age-at-harvest data from residents was representative of the harvested population.
* In some WMUs, especially those surrounding protected areas, seasonal immigration may significantly outweigh seasonal emigration during the hunting season in Ontario (Obbard et al. 2017), which introduces differential biases in the population estimate.
* Harvest mortality is the main cause of death for black bears in Ontario, but many bears die from other natural and human-induced causes. We have poor estimates of these mortalities. Therefore, estimated population size can be viewed only as an indicator of total population size. Trends in the proportion of mortality due to factors other than hunting, which may occur over time, could bias population estimates.
* Independent bear abundance estimates from regularly conducted telemetry or capture-recapture studies (every 5 to 10 years) are necessary to calibrate estimates from population reconstruction. Currently, vital rate information for bears in Ontario is dated and may not be available at appropriate spatial scales.
If population reconstruction is to be considered a viable method for estimating population size and population trends in Ontario in the future, consistent survey methods, greater compliance with mandatory reporting, and higher rates of tooth submission are needed. Population reconstruction should not be used in isolation to obtain accurate abundance estimates. Other jurisdictions conduct independent abundance estimates using alternate methods every 5 to 10 years to confirm and correct population reconstruction trends and estimates. Therefore, Ontario requires upto-date vital rate information from capture-recapture programs, such as collaring (physical capture-recapture) or barbed-wire hair-trap (genetic capture-recapture). Without these auxiliary data, population reconstruction models may produce trends or estimates that are unrealistic or incorrect. Ontario manages bear populations at the WMU scale; therefore, accurate and precise data are required at that scale to provide meaningful estimates. We present specific recommendations to improve data collection and meet the assumptions of the model. When assumptions and data requirements are met, population reconstruction could be a valuable tool for local bear managers, especially as population estimates are available each year, allowing managers to respond immediately to local problems or socioeconomic opportunities.