Breeding Biology of Grassland Birds in Western New York: Conservation and Management Implications

Declining grassland breeding bird populations have led to increased efforts to assess habitat quality, typically by estimating density or relative abundance. Because some grassland habitats may function as ecological traps, a more appropriate metric for determining quality may be breeding success. Between 1994 and 2003 we gathered data on the nest fates of Eastern Meadowlarks (Sturnella magna), Bobolinks (Dolichonyx oryzivorous), and Savannah Sparrows (Passerculus sandwichensis) in a series of fallow fields and pastures/hayfields in western New York State. We calculated daily survival probabilities using the Mayfield method, and used the logistic-exposure method to model effects of predictor variables on nest success. Nest survival probabilities were 0.464 for Eastern Meadowlarks (n = 26), 0.483 for Bobolinks (n = 91), and 0.585 for Savannah Sparrows (n = 152). Fledge dates for first clutches ranged between 14 June and 23 July. Only one obligate grassland bird nest was parasitized by Brown-headed Cowbirds (Molothrus ater), for an overall brood parasitism rate of 0.004. Logistic-exposure models indicated that daily nest survival probabilities were higher in pastures/hayfields than in fallow fields. Our results, and those from other studies in the Northeast, suggest that properly managed cool season grassland habitats in the region may not act as ecological traps, and that obligate grassland birds in the region may have greater nest survival probabilities, and lower rates of Brown-headed Cowbird parasitism, than in many parts of the Midwest.

Models to predict the distribution and abundance of breeding ducks in Canada

Detailed knowledge of waterfowl abundance and distribution across Canada is lacking, which limits our ability to effectively conserve and manage their populations. We used 15 years of data from an aerial transect survey to model the abundance of 17 species or species groups of ducks within southern and boreal Canada. We included 78 climatic, hydrological, and landscape variables in Boosted Regression Tree models, allowing flexible response curves and multiway interactions among variables. We assessed predictive performance of the models using four metrics and calculated uncertainty as the coefficient of variation of predictions across 20 replicate models. Maps of predicted relative abundance were generated from resulting models, and they largely match spatial patterns evident in the transect data. We observed two main distribution patterns: a concentrated prairie-parkland distribution and a more dispersed pan-Canadian distribution. These patterns were congruent with the relative importance of predictor variables and model evaluation statistics among the two groups of distributions. Most species had a hydrological variable as the most important predictor, although the specific hydrological variable differed somewhat among species. In some cases, important variables had clear ecological interpretations, but in some instances, e.g., topographic roughness, they may simply reflect chance correlations between species distributions and environmental variables identified by the model-building process. Given the performance of our models, we suggest that the resulting prediction maps can be used in future research and to guide conservation activities, particularly within the bounds of the survey area.