A Variable Circular-Plot Method for Estimating Bird Numbers

-A bird census method is presented that is designed for tall, structurally complex vegetation types, and rugged terrain. With this method the observer counts all birds seen or heard around a station, and estimates the horizontal distance from the station to each bird. Count periods at stations vary according to the avian community and structural complexity of the vegetation. The density of each species is determined by inspecting a histogram of the number of individuals per unit area in concentric bands of predetermined widths about the stations, choosing the band (with outside radius x) where the density begins to decline, and summing the number of individuals counted within the circle of radius x and dividing by the area (m2). Although all observations beyond radius x are rejected with this procedure, coefficients of detectability may be determined for each species using a standard fixed maximum distance. A bird census technique that estimates the number of birds per area rather than relative abundance is desirable when the objective is to estimate the number and species of birds in a community for energetic considerations (Wiens and Nussbaum 1975), for calculating species diversity (MacArthur 1960, MacArthur and MacArthur 1961), or for elucidating the effects of habitat disturbances on bird populations (Bock and Lynch 1970). Since existing methods require different amounts of effort and give results of differing accuracy (Kendeigh 1944, Emlen 1971, Robinette et al. 1974, Best 1975, Franzreb 1976), the choice of a suitable technique should be based on the species of interest, the season of the year, time and personnel available, number and types of habitats to be censused, and accuracy of the density estimate that is required. Territorial or spot-mapping methods (Williams 1936, Kendeigh 1944) require that the census be conducted during the breeding season and involve considerable time and effort. Both factors severely restrict the number of habitats that can be sampled (Franzreb 1976). Plots of fixed size (e.g., Fowler and McGinnes 1973, Anderson and Shugart 1974), whether traversed by transect or censused from a fixed point, are more easily censused since only bird occurrence needs to be noted. However, density estimates from a number of fixed plots in habitats that differ structurally may not be comparable because of differences in the detectability of birds. For this reason data from fixed plots are frequently reported as relative numbers rather than densities. One way of adjusting for varying detectability among species is to use small plots in dense ,vegetation and large plots in open habitats. Problems arise when an "optimal" plot size, in which the detectability effects are averaged across all species in the community of interest, is required. Another problem is the variance in effectiveness in which two or more observers census plots of fixed sizes (Emlen 1971). Emlen's (1971) variable strip transect count, in which right angle distances from the transect to each observation are estimated, eliminates problems of matching plot size to habitat complexity. This is so because the area used to calculate density is determined by the distance on both sides of the transect within which all individuals of a species are seen or heard. Consequently, the area surveyed is determined by the detectability of each species and observer acuity in each habitat. Additionally, the variable strip method is rapid and relatively accurate and one person can census a variety of communities during any season. For a discussion of these points and a comparison of the variable strip count with the spotmap method see Franzreb (1976). In our work we have found that a stationary observer spends more time searching for birds and less time watching the path of travel. This is particularly true in tall, dense 310 R. T. REYNOLDS, J. M. SCOTT AND R. A. NUSSBAUM vegetation and in uneven terrain. Thus. as " a result of being stationarv. estimates of density and of siecies compbsition should improve. We found, for example, that stationary observers have a greater probability of seeing and hearing birds high in the canopy than even slowly moving observers; standing observers have less effect on bird acGvity; and, because rates of travel along a transect vary with terrain, complexity of vegetation, and number of birds seen, a further advantage of being stationary is that the census periods at each station can be fixed. This aids in standardizing the time spent counting birds in each habitat. Finally, the use of stations allows more definite statements to be made concerning the relationships between the habitat variables and the abundance and occurrence of bird species. This DaDer describes a variable circularplot census technique that gives estimates of birds per unit area during all seasons. This method originated in the need for an effective techniiue for counting birds in mature conifer forests. As such, it represents an a t t em~t to combine what we feel are the best attr;butes of existing methods for habitats of this type. Following its development and use in conifer forests, we have applied it to shrub-steppe, riparian, and semi-tropical rain forests. DESCRIPTION OF THE METHOD In the variable circular-plot method, stations (points) are established within a plant community either at equal intervals along a transect or scattered (avoiding edges) in such a manner as to minimize the probability of observing the same bird from several stations. Thus, the distance between stations depends (in part) on how far away the birds can be detected and how fast they move; it will vary with vegetation and the behavior of the birds (see below). Each bird seen or heard during a fixed time period around a station is counted and the horizontal distance to its location when first observed is estimated. We adjust the time counting at stations to match the structural characteristics of the vegetation and the number of bird species in the plant community being censused. Our strategy is to select the time required to count all birds within an effective detection distance (see below) but to keep the time short enough so that the probability of counting the same bird more than once or of counting birds that move into the area being sampled is minimized. For conifer forests, 10 min at each station following a 1-min "rest period" for equilibration of bird activity after arrival at each station, appears to be sufficient. For the closed canopy rain forests of Hawaii, 8 min is sufficient (J. M. Scott and J. L. Sincock, unpubl, data). For more open habitats (e.g., shrub-steppe) less time is required. With the variable circular-plot method no maximum distance restrictions are placed on any observation. We count only those birds actively using the census area. For example, gulls flying over a stand of cottonwoods are not counted. Peregrine Falcons (Falco peregrinus) soaring over the same area are included because they may capture prey therein. Birds that are flushed while approaching a station are recorded using the distance from the station to where they were first observed as the detection distance. Species that commonly do this are quail, grouse, hawks and owls. In the analysis, we determine the distance from the stations where the number of birds observed begins to decline (the point of inflection) by plotting for each species the number of individuals seen in concentric bands around all stations in each type of habitat. Since the area in each consecutively larger band around the stations is greater (see below) the number of birds observed in each band cannot be plotted directly. Thus, we plot the number of birds per area per band and convert the density in each to a standard of birds/km2. The number of birds in the habitat is then determined by summing the number of individuals counted within the circle of radius x (the inflection point), dividing by the area (,rr2) and converting the resultant density to a standard area (birds/km). With this procedure, we reject all observations outside of the circle of radius x. However, coefficients of detectability (CDs) may be calculated from these data using a standard fixed maximum distance for all species as described by Emlen (1971). For example, we plot the density (birds/ km) of Apapane (Himatione s. sanguinea) in each band with 5-m widths from 0 to 100m, and 10-m widths from 100-m to 200-m from the stations (Fig. 1). Since the density of birds recorded in the bands may vary, we established the following criteria to provide consistency in estimating the point of inflection: choose the distance to the outermost edge of the band where the density of individuals per km2 in the next outermost band is less than 50% of the previous band, with the specified condition that the number of individuals per km in any one of the CIRCULAR-PLOT CENSUS METHOD 311 lnf lect ion Point L