This map provides our best guess of population change for the species over its range. Areas of increase are blue, and areas of decline are red. Areas where there is no apparent trend, or where we do not have enough information to say that a trend exists, are also indicated. Note that these maps are designed to provide a general view of population change for the long-term. Because they are based on averages of trend estimate for each route, they do not provide much insight into short-term changes within the BBS period. To get trend estimates for a specific region or time, please use the trend estimation parts of the Home Page.
Also, remember that the BBS did not begin in the Western United States and most of southern Canada until 1968, and in the Central United States in 1967, so trends do not always provide information from the first years of the survey.
Details: Maps of Geographic Patterns in Population Trends
The design of the BBS allows us to conduct an analysis that
directly uses geographic information to illustrate geographic
patterns in population change. Route locations can be incorporated
into a geographic information system (GIS), and population change
can be displayed directly for each route. Geographic patterns can
be summarized by 2-dimensional smoothing procedures such as Kriging
or inverse distancing (Cressie 1991) to display regions of
increasing and declining
populations. Temporal patterns can be displayed using population
change estimates on individual routes for periods of interest.
We used the geographic location of the starting points of
survey routes summarized in latitude and longitude as the index to
route locations. The route locations were projected as a series
of point locations (a point coverage) in an ARC/Info GIS
(Environmental Systems Research Institute 1993). Using the GIS,
data for individual species can be associated with the point
locations for analysis and display.
Because most BBS routes have some missing data and >1 observer
during the survey period, simple use of yearly counts or average
counts would lead to spurious geographic patterns. Therefore, we
summarized the data before entering it into the GIS. In
particular, we estimated the population trend (b) for individual
routes using the estimating equations estimator of Link and Sauer
(1994). On our maps, we transform this proportional change to a
%/year for ease in interpretation.
To accommodate the obvious differences in quality of
information among routes, we weighted the trend estimates by an
estimate of the variance of trends from individual routes. This
variance is estimated using a model-based variance from the
estimating equations, corrected for a common overdispersion (W. A.
Link, Personal Communication). We note that this variance estimate
is proportional to the precision weights used in the estimation of
the regional mean trends (Geissler and Sauer 1990).
Although simply displaying the trend estimates for individual
routes provides insight into regional patterns, some kind of
summary of the data is needed to assist in evaluating regional
consistency in trends. We contoured the route trend estimates
using a procedure called inverse distancing. See the discussion
related to the abundance maps for a description of how inverse
distancing was applied to the route data, and a rationale for the
use of inverse distancing relative to other procedures such as
Kriging. As noted in the discussion regarding relative abundance
maps, there are many technical details for the smoothing, and many
features that can create bias and imprecision in the smoothed maps
Because of the complexity of the modeling, different investigators
tend to choose slightly different methods, all of which lead to
slightly different smooths (e.g., Englund 1990, Weber and Englund
Because no information exists for areas outside the range of
the species, we truncated these maps at the edge of the species'
range, as estimated from BBS data. Also, the "range," as indicated
by the trend maps is somewhat smaller than the range from the
relative abundance maps, because many of the marginal routes for
species do not provide sufficient data for estimation of population
Cressie, N. 1992. Statistics for spatial data. Wiley, New York. 900pp.
Englund, E. J. 1990. A variance of geostatisticians. Math. Geol. 22:417-456.
Environmental Systems Research Institute. 1991. Surface Modeling
with TIN. Environmental Systems Research
Institute, Inc., Redlands, CA.
Environmental Systems Research Institute. 1993. Understanding
GIS-The Arc/Info Method. Environmental Systems Research
Institute, Inc., Redlands, CA.
Geissler, P.H., and J.R. Sauer. 1990. Topics in route-
regression analysis. Pp. 54-57 in J.R. Sauer and S.
Droege (eds.) Survey designs and statistical methods
for the estimation of avian population trends. U.S.
Fish Wildl. Serv., Biol. Rep. 90(1).
Isaaks, E. H., and R. M. Srivastava. 1989. An introduction to
applied geostatistics. Oxford University Press, New York.
Link, W. A., and J. R. Sauer. 1994. Estimating equations
estimates of trend. Bird Populations 2:23-32.
Weber, D., and E. Englund. 1992. Evaluation and comparison of
spatial interpolators. Math. Geol. 24:381-391.