About the Analyses
Annual estimates of population size were estimated for each species in spring and/or fall by fitting a generalized additive model (GAM) with Poisson distribution or, in cases where a Poisson model provided a poor fit, a negative binomial distribution. All models were fit using the GAM function in the R statistical language version (R-2.13.0). All analyses were restricted to data within the migratory season of each species (see 'Seasonal Graphs' below). All models included a fixed categorical year effect and a smoothed date effect to model variation in daily counts through a migration season. Total observation counts each year was used as a weight variable. Using parameters from the fitted models, annual indices were calculated as the mean of the predicted daily counts for each species and year.
Options for LOESS smoothed and Best Polynomial Model trend lines are offered in this application. A trend estimate is not available using the LOESS smoothed option. For the Best Polynomial Model option, trends were calculated in the following way:
Trends in annual abundance indices were calculated by fitting a generalized additive model (GAM) with Poisson distribution or, in cases where a Poisson model provided a poor fit, a negative binomial distribution. All models were fit using the GAM function in the R statistical language version (R-2.13.0). All models included a fixed continuous year effect and a smoothed date effect to model variation in daily counts through a migration season. Total observation counts each year was used as a weight variable. A log-linear estimate of population change was calculated by back-transforming the year coefficient: 100*(exp(year coefficient)-1). Because the full dataset was used to estimate population change, as opposed to annual indices of population size, the precision of the year effect using GAM was overly precise (more likely to be significant than in reality). As a result, a bootstrapping procedure was used to estimate the precision of the trend.
Annual Indices Tool
Long Point Bird Observatory (fall)
Cape May Warbler
The following are displayed only with the "Best Polynomial Order" option:
Order: Polynomial order of best fit model (model with minimum AIC value)
R2: R square based on best fit model
P: P-value of trend estimate; trends with p-value < 0.05 are considered statistically significant.
Trend maps show the estimated population trend over a comparable period (eg, the most recent ten-year period 1997-2006) at sites or regions with sufficient data. For details on annual index and trend estimation procedures,
see the Annual Indices section above.
Seasonal graphs are plots of the daily mean log(count) across years sampled at a location (e.g., Canadian Migration Monitoring Network station).
Options are available to display a LOESS smoothed line of the percent of years the selected species was present each day of year, and the raw percent of years the station was in operation during each day of year (i.e., station coverage).
Migration windows show the boundaries of the spring and fall migration window, and are shown only if the species was analyzed during a particular season. The bounds of spring and fall migration windows were restricted to those days of the year when the station operated during at least 50% of total years in operation.
Delta Marsh Bird Observatory - Northern Waterthrush
˜ daily mean log(species count)
____ Percent of years species present each day
____ Percent of years station in operation each day
| Spring and/or fall migration window boundaries