EFFECTS OF SCALE AND HABITAT MANAGEMENT ON GRASSLAND BIRD RESPONSE IN CONSERVATION RESERVE PROGRAM FIELDS IN NORTHWEST ILLINOIS

North American populations of grassland birds have been declining consistently for the past several decades. Grassland birds respond to multiple scales which encompass a spectrum of habitat variables, and the habitat scale of importance may depend on the response of interest. For practitioners, having knowledge of the effect of scale is useful because conservation efforts can be focused at the most appropriate scale. However, previous multi-scale studies of grassland birds and other taxa have rarely incorporated on-the-ground habitat management while simultaneously investigating site-specific species turnover dynamics (Chapter 1) and daily nest survival (Chapter 2). Also, habitat management-related studies often suffer when not accounting for inherent variation between fields, field landscapes, and study year; thus, to disentangle specific effects of management, it is important to account for this variation by using these factors as random effects within mixed-effects models (Chapter 3). Understanding multi-scale habitat relationships affecting site turnover, also known as dynamic occupancy, and daily nest survival rate (nest survival or DSR), as well as how multiple avian responses vary with grassland management would further benefit conservation decision making for focal species. I investigated dynamic occupancy and nest survival of both obligate and facultative grassland species relative to multi-scale habitat factors on private lands (Conservation Reserve Program) in northwest Illinois during 2011-2014. I also conducted a separate analysis focusing on how multiple avian responses, ranging from species presence/absence (P/A) to species-specific nest survival, are influenced by non-fire grassland management treatments. For dynamic occupancy, a combination of ≥2 scales always outperformed single-scale models for all species. Three of 7 species responded to either cumulative habitat management (proportion of field managed over the study period) or yearly management (33% of field managed before a particular breeding season) regardless of dominant grass type. Of the 48 covariates appearing in top models across species for both dynamic and single-season occupancy, microhabitat covariates (42%) were represented most often, followed by patch-scale (33%) and landscape-scale (25%) factors. Covariates with the most consistent effects and the greatest frequencies appearing in competitive (∆AIC ≤ 4) dynamic and single-season occupancy models included landscape forest cover (n = 10), surrounding patch grassland cover (n = 7), and field size (n = 6). In general, increasing levels of forest cover adjoining fields had consistently negative effects on occupancy, colonization, and persistence across species, while grassland surrounding fields and field size had positive effects on these responses. Microhabitat covariates better explained colonization and extinction across the focal species. Of the 22 habitat covariates in top colonization and extinction models, microhabitat variables were represented 50% of the time, compared to 32% and 18% representation for patch-scale and landscape-scale covariates, respectively. I recommend that wildlife biologists utilize habitat management techniques to ensure grassland birds have different successional stages within their range of preferences. My results suggest that grassland disturbance, while influencing turnover dynamics of different species, may be less influential within smaller fields and landscapes dominated by forest cover. I analyzed the daily nest survival rate for 2 species (red-winged blackbirds and dickcissels) and 2 groups of nesting communities (ground and above-ground nesters). Temporal variables such as Julian date and stage of nest were significant predictors of nest survival for red-wings (50.58 ∆AICc = best temporal model) and dickcissels (2.28 ∆AICc = best temporal model) in addition to habitat covariates. In 3 of 4 analyses ≥2 habitat scales were better predictors of nest survival over one scale. For ground nesters the patch scale was be best predictor of nest survival. However, the best model for ground nesters did not have overwhelming support compared to the random model (1.43 ∆AICc). The ground-nesting community appeared to suffer decreased nest survival with increasing proportion of surrounding grassland. The blackbird top model included nest- and landscape-scale covariates, and top models for dickcissels and the above-ground nesting community included the nest- and patch-scale covariates. Blackbirds had a significant increase in nest survival when nests were placed in areas with higher vegetation density and height (greater visual obstruction). Comparatively, the predictive ability of habitat covariates was not as strong for the other 3 analyses; however, notable patterns include dickcissel nest survival decreasing with increasing nest distance to edge and above-ground nests had increased nest survival with increasing patch perimeter-area-ratio. My results suggest different species are responding to different scales, but finer-scale habitat covariates generally help predict nest survival over course-scale habitat features, such as landscape covariates. Songbird nest survival maybe more influenced by fine-scale habitat characteristics such as nesting cover and field vegetation complexity and density, which can deter nest predators and reduce their search efficiency. In a way, this is positive news for practitioners working in grasslands patches located in less than ideal patch or landscape configurations, suggesting more effort could be focused on improving conditions for colonization and persistence of focal species (Chapter 1). By focusing management on dynamic occupancy responses, increasing potential nesting habitat and territory quality for focal species will likely follow. When investigating multiple avian responses to management, within a consistent mixed-effect modeling framework, it appeared that avian survey related responses were best supported, having consistently larger ∆AICc values for top models, when compared to nesting-related data. One explanation of this relative difference could be attributed sample size difference between analyses. Focusing on the effects of management, this analysis accounted for inherent variation across fields, year, and potentially field landscape, as random effects within all models. As suggested from Chapter 2, and despite a large sample of nests, explanation of DSR across all species and focal species showed little improvement with management covariates. Brome fields cumulatively managed with spray or spray/seed treatments (Chapter 1) appeared to respond most and likely explained general positive effects for red-winged blackbird and dickcissel abundance; however, this was at a cost to species abundance for bobolink (Dolichonyx oryzivorus), Henslow’s sparrow (Ammodramus henslowii), eastern meadowlark (Sturnella magna), field sparrow (Spizella pusilla), and northern bobwhites (Colinus virginianus), due to the release of tall forbs within the seed bank after spraying brome dominated fields. Dramatic vegetation responses in sprayed brome fields likely led to an overall decrease in obligate-grassland bird richness and conservation value on brome field types that were cumulatively management over the course of the study. These results suggest the importance of non-native brome CRP fields for certain grassland-obligate bird species, while also revealing the apparent decoupling of nest survival and other avian responses measured commonly. I suggest managers and researchers pay closer attention to variables affecting nesting abundance/density in grassland systems when possible and recognize the potential importance of non-native grasses for grassland-obligate birds in some regions