An integrated population model to project viability of a northern bobwhite population in Ohio [DATA]

Increased variation in interannual weather due to climate change can exert
a powerful influence on the population dynamics of a species.
Understanding the influence of severe weather is important for managing
weather-sensitive species. While best management practices target vital
rates that are affected by weather, focusing on a single vital rate may
not be sufficient if other vital rates are secondarily limiting. A
comprehensive modeling framework to forecast future population dynamics
while incorporating weather scenarios and vital rate variation within
observed ranges that can be affected by management actions are necessary.
A potential approach is to combine an integrated population model (IPM)
with a population viability analysis (PVA) to generate novel insights
about population dynamics. We used the northern bobwhite (Colinus
virginianus), a rapidly declining gamebird sensitive to snowfall along the
northern extents of the species’ range, to demonstrate the utility of a
coupled IPM-PVA framework for projecting the response of a population to
weather, management, and changes in vital rates. We created an IPM using
two sources of count data spanning seven years, five years of winter
survival data, and two years of breeding season demographics for a
declining bobwhite population in southwestern Ohio during 2007–2015.
Quasi-extinction probability at the end of the decadal projection during
2019–2029 was 0.384–0.410 for mild, average, and severe winter weather
scenarios. Quasi-extinction probability declined to 0.326 with 20%
improvement in nest success and summer survival rates. A concurrent 20%
increase in winter survival further reduced quasi-extinction probability
to 0.263, which is a ~36% reduction in quasi-extinction probability
compared to the baseline scenario with no changes in vital rates. These
results suggest that long-term viability of this population may depend on
extensive management of winter habitat to improve survival but will also
require management actions to improve fecundity after severe winters. Our
modeling approach demonstrated how IPMs can be used to project population
responses to future weather conditions and overcome some of the pitfalls
of traditional PVA. The coupled framework presented here can serve as a
tool for managers to make climate informed management decisions.