Prediction of reproductive success and failure in lesser snow geese based on early season climatic variables

• Published in: Global Change Biology
• Main Authors: Skinner, W. R., Jefferies, R. L., Carleton, T. J., Abraham, R. F. Rockwell&dagger K. F.
• Format: Article in Journal/Newspaper
• Language: English
• Published: Wiley 1998
• Subjects: Hudson Bay
• Online Access: http://dx.doi.org/10.1046/j.1365-2486.1998.00097.x; https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1046%2Fj.1365-2486.1998.00097.x; https://onlinelibrary.wiley.com/doi/pdf/10.1046/j.1365-2486.1998.00097.x; https://onlinelibrary.wiley.com/doi/full-xml/10.1046/j.1365-2486.1998.00097.x

Abstract The North American mid‐continent population of lesser snow geese ( Anser caerulescens caerulescens ) breeds in coastal areas of the Hudson Bay region. Breeding success is highly variable, particularly during recent decades. The availability of long‐term data sets of weather and the breeding success of geese allowed us to determine whether climatic variables in spring and early summer (May–June) are reliable predictors of different attributes of the reproductive biology of snow geese. A large region of strong anomalous cooling in north‐eastern North America has been the dominant anomalous climatic feature since the mid‐1970s. The cooling which becomes established during winter persists into spring and early summer when migration, nesting and hatching of geese are occurring. Redundancy analysis (RDA) of the data sets was made to identify dominant correlations and regression relationships between climatic and goose variables. Individual goose response variables were further explored with stepwise multiple regression and bipartial regression. 96.7% of year‐to‐year variance in the goose data was explained by the selected climatic data. The first four orthogonal axes out of seven possible axes explained 92.2% of the total variance. Date of last snow on the ground and mean daily temperature from 6 to 20 May formed the lowest and highest predictor scores, respectively. Initiation date and hatching date at the low end and total clutch size and clutch size at hatch at the high end were associated with these extremes, particularly in certain years. Days of freezing rain in May and total rainfall were correlated with nest failure. Bivariate correlation/regression showed that the most parsimonious model for nest initiation day was based on four climatic predictors, for hatching day four predictors, and for clutch size at hatch, nine predictors. Both the multiple regression analyses and the redundancy analyses confirm the high degree of predictability of goose reproductive variables from selected climatic variables. ...