I examined the distribution and abundance of bird species across an urban gradient, and concomitant changes in community structure, by censusing summer resident bird populations at six sites in Santa Clara County, California (all former oak woodlands). These sites represented a gradient of urban land use that ranged from relatively undisturbed to highly developed, and included a biological preserve, recreational area, golf course, residential neighborhood, office park, and business district. The composition of the bird community shifted from predominantly native species in the undisturbed area to invasive and exotic species in the business district. Species richness, Shannon diversity, and bird biomass peaked at moderately disturbed sites. One or more species reached maximal densities in each of the sites, and some species were restricted to a given site. The predevelopment bird species (assumed to be those found at the most undisturbed site) dropped out gradually as the sites became more urban. These patterns were significantly related to shifts in habitat structure that occurred along the gradient, as determined by canonical correspondence analysis (CCA) using the environmental variables of percent land covered by pavement, buildings, lawn, grasslands, and trees or shrubs. I compared each formal site to four additional sites with similar levels of development within a two-county area to verify that the bird communities at the formal study sites were rep- resentative of their land use category.

Land Use and Avian Species Diversity Along an Urban Gradient

Recognition and analysis of spatial autocorrelation has defined a new par- adigm in ecology. Attention to spatial pattern can lead to insights that would have been otherwise overlooked, while ignoring space may lead to false conclusions about ecological relationships. We used Gaussian spatial autoregressive models, fit with widely available software, to examine breeding habitat relationships for three common Neotropical migrant songbirds in the southern Appalachian Mountains of North Carolina and Tennessee, USA. In preliminary models that ignored space, the abundance of all three species was cor- related with both local- and landscape-scale habitat variables. These models were then modified to account for broadscale spatial trend (via trend surface analysis) and fine-scale autocorrelation (via an autoregressive spatial covariance matrix). Residuals from ordinary least squares regression models were autocorrelated, indicating that the assumption of independent errors was violated. In contrast, residuals from autoregressive models showed little spatial pattern, suggesting that these models were appropriate. The magnitude of habitat effects tended to decrease, and the relative importance of different habitat variables shifted when we incorporated broadscale and then fine-scale space into the analysis. The degree to which habitat effects changed when space was added to the models was roughly correlated with the amount of spatial structure in the habitat variables. Spatial pattern in the residuals from ordinary least squares models may result from failure to include or adequately measure autocorrelated habitat variables. In addition, con- tagious processes, such as conspecific attraction, may generate spatial patterns in species abundance that cannot be explained by habitat models. For our study species, spatial patterns in the ordinary least squares residuals suggest that a scale of 500-1000 m would be ap- propriate for investigating possible contagious processes.

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Spatial autocorrelation and autoregressive models in ecology

-We provide a detailed description of a fixed-radius point count method that carries fewer assumptions than most of the currently popular methods of estimating bird density and that can be used during both the nonbreeding and breeding seasons. The method results in three indices of bird abundance, any of which can be used to test for differences in community composition among sites, or for differences in the abundance of a given bird species among sites. These indices are (1) the mean number of detections within 25 m of the observer, (2) the frequency of detections within 25 m of the observer, and (3) the frequency of detections regardless of distance from the observer. The overall ranking of species abundances from a site is similar among the three indices, but discrepancies occur with either rare species that are highly detectable at great distances or common species that are repulsed by, or inconspicuous when near, the observer. We argue that differences in the behavior among species will preclude an accurate ranking of species by abundance through use of this or any other counting method in current use. Received 3 September 1985, accepted 2 February

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A Fixed-Radius Point Count Method for Nonbreeding and Breeding-Season Use

Although point counts are frequently used in ornithological studies, basic assumptions about detection probabilities often are untested. We apply a double-observer approach developed to estimate detection probabilities for aerial surveys (Cook and Jacobson 1979) to avian point counts. At each point count, a designated “primary” observer indicates to another (“secondary”) observer all birds detected. The secondary observer records all detections of the primary observer as well as any birds not detected by the primary observer. Observers alternate primary and secondary roles during the course of the survey. The approach permits estimation of observer-specific detection probabilities and bird abundance. We developed a set of models that incorporate different assumptions about sources of variation (e.g. observer, bird species) in detection probability. Seventeen field trials were conducted, and models were fit to the resulting data using program SURVIV. Single-observer point counts generally miss var...

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A double-observer approach for estimating detection probability and abundance from point counts

During the past 5 years there have been a number of important developments in the estimation of animal abundance and related parameters such as survival rates. Many of the new techniques need to be more widely publicized as they supplant previous methods. The aim of this paper is to review this literature and suggest further avenues for research.

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A review of estimating animal abundance.

-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

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A Variable Circular-Plot Method for Estimating Bird Numbers

The prevalence of lead in Golden Eagles (Aquila chrysaetos) occurring within the recent historical range of the California Condor (Gymnogyps californianus) was deter- mined by analyzing blood samples from 162 Golden Eagles captured between June 1985 and December 1986 at three sites. We found no significant differences between sex and age classes in blood lead levels nor were there differences between residents and migrants. Significant differences were found between months with the highest blood lead levels oc- curring during the fall/winter period. Approximately one-third (35.8%) of the Golden Eagle population sampled had elevated blood lead levels, values similar to those reported for free- flying California Condors. Given this rate of exposure, if the proposed releases of California Condors back to the wild are to succeed, whether in their former range or elsewhere, any potential for lead poisoning must be reduced. It is essential that we identify the sources of the lead, the seasonal and geographic distribution of these sources, and develop management strategies to reduce or eliminate the hazard.

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Lead Hazards within the Range of the California Condor

Lead toxicosis has been identified as the cause of mortality in three California Condors ( Gymnogyps californianus) and it has been suggested as a reason for the species' recent decline (Wiemeyer etal., in press).Three of four Condors found dead or near death since 1983 had succumbed to lead poisoning (Janssen et al. 1986; Wiemeyer et al., in press).Lead bullet fragments were found in the gastrointestinal tract of 2 of the 3 birds that died of lead poisoning. A possible source of these toxic levels of lead is the carrion on which the birds feed, and which may contain bullets or bullet fragments. We initiated a study to examine the role of lead in the demise of the California Condor through the use of a locally common species, the Golden Eagle (Aquila chrysaetos). Since the Golden Eagle and California Condor exist sympatrically and feed on many of the same carrion resources, we selected this species for comparative research.The more similar Turkey Vulture ( Cathartes aura) was considered but not used, because it is less common, very localized within the Condor's range, and more migratory.

Lead contamination of golden eagles Aquila chrysaetos within the range of the California condor Gymnogyps californianus

We designed an experiment to identify factors contributing most to error in counts of Hawaiian Crow or Alala (Corvus hawaiiensis) groups that are detected aurally. Seven observers failed to detect calling Alala on 197 of 361 3-min point counts on four transects extending from cages with captive Alala. A detection curve describing the relation between frequency of flock detection and distance typified the distribution expected in transect or point counts. Failure to detect calling Alala was affected most by distance, observer, and Alala calling frequency. The number of individual Alala calling was not important in detection rate. Estimates of the number of Alala calling (flock size) were biased and imprecise: average difference between number of Alala calling and number heard was 3.24 (?0.277). Distance, observer, number of Alala calling, and Alala calling frequency all contributed to errors in estimates of group size (P < 0.0001). Multiple regression suggested that number of Alala calling contributed most to errors. These results suggest that welldesigned point counts may be used to estimate the number of Alala flocks but cast doubt on attempts to estimate flock size when individuals are counted aurally.

J. M. Scott

Papers

A Variable Circular-Plot Method for Estimating Bird Numbers

Lead Hazards within the Range of the California Condor

Lead contamination of golden eagles Aquila chrysaetos within the range of the California condor Gymnogyps californianus

Point counts from clustered populations : lessons from an experiment with Hawaiian crows