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Obtaining rigorous baseline density estimates of species of conservation interest is key when assisting landowners to achieve management goals on private lands. Northern bobwhite (Colinus virginianus) populations are declining throughout their range and despite being the focus of numerous private land conservation initiatives, baseline density estimates in privately owned pine forests are lacking. We sought to address this knowledge gap across the Southeastern United States by sampling 105 privately owned pine stands throughout 2018 to 2020 using observer point count and autonomous recording unit (ARU) sampling data. Using Bayesian hierarchical models, we investigated the influence of stand management (brush management or applied fire) on bobwhite density, as well as four landscape‐scale environmental variables. These included percentage cover of forest, herbaceous, agricultural or burnt land area across six different spatial scales ranging from 500‐m to 10‐km around each pine stand. Baseline density on sites with no management was estimated to be 2.24 coveys per 100 ha (1.00–5.03, 95% BCI), with little impact of applying brush management, but a trend for a positive effect of fire management (0.19, −0.01 to 0.38 95% BCI). This impact of fire was seen at both the stand‐scale, correlated with an increase in acreage of applied prescribed burn management, and across the greater landscape area, correlated with cover of burnt area within a 2‐km buffer around each site. There were also strong positive influences of herbaceous vegetation and a strong negative influence of forest cover on bobwhite density. Practical implication: our sampling efforts fill an important information gap regarding densities throughout private lands in the Southeastern United States. Our study also highlights the necessity of landscape scale planning for Northern Bobwhite conservation initiatives because the efficacy of conservation practices (i.e. prescribed fire and brush management) could be altered by the landscape surrounding the treated forest stand.
Obtaining rigorous baseline density estimates of species of conservation interest is key when assisting landowners to achieve management goals on private lands. Northern bobwhite (Colinus virginianus) populations are declining throughout their range and despite being the focus of numerous private land conservation initiatives, baseline density estimates in privately owned pine forests are lacking. We sought to address this knowledge gap across the Southeastern United States by sampling 105 privately owned pine stands throughout 2018 to 2020 using observer point count and autonomous recording unit (ARU) sampling data. Using Bayesian hierarchical models, we investigated the influence of stand management (brush management or applied fire) on bobwhite density, as well as four landscape‐scale environmental variables. These included percentage cover of forest, herbaceous, agricultural or burnt land area across six different spatial scales ranging from 500‐m to 10‐km around each pine stand. Baseline density on sites with no management was estimated to be 2.24 coveys per 100 ha (1.00–5.03, 95% BCI), with little impact of applying brush management, but a trend for a positive effect of fire management (0.19, −0.01 to 0.38 95% BCI). This impact of fire was seen at both the stand‐scale, correlated with an increase in acreage of applied prescribed burn management, and across the greater landscape area, correlated with cover of burnt area within a 2‐km buffer around each site. There were also strong positive influences of herbaceous vegetation and a strong negative influence of forest cover on bobwhite density. Practical implication: our sampling efforts fill an important information gap regarding densities throughout private lands in the Southeastern United States. Our study also highlights the necessity of landscape scale planning for Northern Bobwhite conservation initiatives because the efficacy of conservation practices (i.e. prescribed fire and brush management) could be altered by the landscape surrounding the treated forest stand.
Management of wildlife populations is most effective with a thorough understanding of the interplay among vital rates, population growth, and density-dependent feedback; however, measuring all relevant vital rates and assessing density-dependence can prove challenging. Integrated population models have been proposed as a method to address these issues, as they allow for direct modeling of density-dependent pathways and inference on parameters without direct data. We developed integrated population models from a 25-year demography dataset of Northern Bobwhites (Colinus virginianus) from southern Georgia, USA, to assess the demographic drivers of population growth rates and to estimate the strength of multiple density-dependent processes simultaneously. Furthermore, we utilize a novel approach combining breeding productivity and post-breeding abundance and age-and-sex ratio data to infer juvenile survival. Population abundance was relatively stable for the first 14 years of the study but began growing after 2012, showing that bobwhite populations may be stable or exhibit positive population growth in areas of intensive management. Variation in breeding and non-breeding survival drove changes in population growth in a few years; however, population growth rates were most affected by productivity across the entire study duration. A similar pattern was observed for density-dependence, with relatively stronger negative effects of density on productivity than on survival. Our novel modeling approach required an informative prior but was successful at updating the prior distribution for juvenile survival. Our results show that integrated population models provide an attractive and flexible method for directly modeling all relevant density-dependent processes and for combining breeding and post-breeding data to estimate juvenile survival in the absence of direct data.
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