The northern bobwhite (Colinus virginianus) population decline is a severe, rangewide phenomenon beginning >150 years ago and continuing today. In this investigation, I: 1. document the timeline of bobwhite population decline and unintended genetic consequences of attempted remedies, 2) develop a model useful for predicting possible locations of potentially sustainable bobwhite populations in semiarid rangeland in Texas and Oklahoma, and 3) examine the relationship between population monitoring data and meteorological factors. While breeding season call counts of male bobwhite have been used for >70 years to provide estimates of fall populations for hunting, most studies of call counts have focused on mathematics and statistical accuracy of the count, largely overlooking the influence of meteorological factors on call counts. Here, I present the results of >4,400 individual point counts and examine their relationship with meteorological variables recorded at each stop. Humidity was positively correlated with the number of birds recorded (ρ = 0.275, p < 0.001) and temperature was negatively correlated (ρ = -0.252, p < 0.001). The number of birds recorded was significantly higher in wet years than in drought years. There was no significant correlation between wind velocity and number of birds recorded. These results suggest that, while weather does influence call counts and efforts should be made to record meteorological conditions when collecting call count data, the influence of weather may not easily factor into the analysis. These results also provide another line of evidence for decreased breeding behavior during high temperatures. With the increased focus on bobwhite habitat management on a regional scale, there is a need for reliable methods to identify potential bobwhite habitat. To identify bobwhite habitat in semiarid rangeland, I performed classification of LANDSAT scenes of Clay County, Texas from July and December 2015. Stands of mature little bluestem provide excellent bobwhite nesting cover and could be identified using LANDSAT imagery. I scored habitat by type, compared these scores with the results of breeding season call counts from 2014 and 2015 and found significant correlation. When used in combination with other landscape data, this approach can provide a regional context to inform conservation and management decisions.