U.S. Department of the Interior

U.S. Geological Survey

Open-File Report 2020–1110

Prepared in cooperation with San Diego Association of Governments, U.S. Fish and Wildlife 

Service, Bureau of Land Management, and California Department of Fish and Wildlife

A Clarification on the Effects of Urbanization on Golden Eagle 

(Aquila chrysaetos) Habitat Selection
Cover Photo: Photograph of a golden eagle (Aquila chrysaetos) being released by U.S. Geological 

Survey biologist, Melanie Madden, after being captured and fitted with a telemetry unit, March 6, 

2018. Photograph by Peter H. Bloom, Bloom Biological, Inc. Used with permission.
A Clarification on the Effects of 

Urbanization on Golden Eagle 

(Aquila chrysaetos) Habitat Selection

By Jeff A. Tracey, Melanie C. Madden, Peter H. Bloom, and Robert N. Fisher

Prepared in cooperation with San Diego Association of Governments, U.S. Fish 

and Wildlife Service, Bureau of Land Management, and California Department of 

Fish and Wildlife

Open-File Report 2020–1110

U.S. Department of the Interior

U.S. Geological Survey
U.S. Department of the Interior

DAVID BERNHARDT, Secretary

U.S. Geological Survey

James F. Reilly II, Director

U.S. Geological Survey, Reston, Virginia: 2020

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Suggested citation:

Tracey, J.A., Madden, M.C., Bloom, P.H., and Fisher, R.N., 2020, A clarification on the effects of urbanization on 

Golden Eagle (Aquila chrysaetos) habitat selection: U.S. Geological Survey Open-File Report 2020–1110, 7 p., 

https://doi.org/10.3133/ofr20201110.

ISSN 2331-1258 (online)
iii

Contents

Introduction.....................................................................................................................................................1

Methods...........................................................................................................................................................1

Results and Discussion .................................................................................................................................3

References Cited............................................................................................................................................7

Figures

1. Histograms showing the distance to urban in meters at use locations and at 

availability locations used in the generalized additive mixed-effects model 

regression for a single sample ...................................................................................................2

2. Graph showing the mean generalized additive mixed-effects model 

population-level prediction for probability of use given availability as a function 

of distance to urban edge ...........................................................................................................4

3. Map showing the spatial effect of golden eagle avoidance of urban areas ......................6

Tables

1. The probability of use at 50-meter (m) intervals for distances of 0–2,000 m 

from the urban edge based on predictions from the generalized additive 

mixed-effects model .....................................................................................................................5
iv

Conversion Factors

International System of Units to U.S. customary units

Multiply By To obtain

Length

meter (m) 3.281 foot (ft)

meter (m) 1.094 yard (yd)

kilometer (km) 0.6214 mile (mi)

Area

hectare (ha) 2.471 acre

hectare (ha) 0.003861 square mile (mi2)

Abbreviations

GAMM generalized additive mixed-effects model

ID identification

TPI topographic position index

USGS U.S. Geological Survey

VRM vector ruggedness measure
A Clarification on the Effects of Urbanization on Golden 

Eagle (Aquila chrysaetos) Habitat Selection

By Jeff A. Tracey1, Melanie C. Madden1, Peter H. Bloom2, and Robert N. Fisher1

Introduction

In 2018, the U.S. Geological Survey (USGS) published 

an Open-File Report (Tracey and others, 2018) presenting 

a Bayesian habitat selection model for golden eagles 

(Aquila chrysaetos) in San Diego County, California. 

The model used telemetry data to examine the effects of 

urban development, exurban development, and topography 

(characterized by a topographic position index and a vector 

ruggedness measure, TPI and VRM respectively) on golden 

eagle habitat selection probability. Based on figures 3 and 

6 of Tracey and others (2018), we received inquiries from 

cooperators (U.S. Fish and Wildlife Service and California 

Department of Fish and Wildlife) about how the probability of 

eagle use declines with decreasing distance to the urban edge. 

Here, we clarify our results by addressing that question.

Methods

We considered telemetry data for 44 golden eagles 

tracked between November 22, 2014, and December 2, 2019 

(Tracey and others 2016, 2017, 2020). Data from the telemetry 

devices were collected at a frequency of as little as 3 seconds 

between fixes. We identified move steps in these data that were 

separated by 15-minute time intervals (±1 minute). Each move 

step consisted of a starting point (a from-location) paired 

with an end point (a to-location). To ensure that each move 

step occurred between cells in our habitat predictor rasters, 

we removed any move steps that had a distance of less than 

100 meters (m) between the from-location and to-location 

of the move step. Hence, when an eagle was stationary (for 

example, when perching, nesting, or roosting) the associated 

move steps were removed, but the movements to and from the 

stationary location were included. In addition, any move steps 

with a from-location or to-location outside San Diego County 

were also excluded. The end points (to-locations) of each 

move step constituted the use data (distance to the urban edge 

at observed eagle locations) in the regression model.

Data were analyzed under a use-availability design 

(Design III, Manly and others, 2002) using a generalized 

additive mixed-effects model (GAMM; Wood, 2017) with 

distance to the nearest urban edge (distance to urban, for 

brevity) as the single fixed-effect predictor variable and 

the individual eagle identification (ID) as a random-effect 

variable. For each eagle with at least 2,000 observed 

use locations, we randomly sampled 2,000 availability 

(pseudo-absence) locations from a uniform distribution within 

San Diego County, excluding the desert climate zone. Any 

eagles that had less than 2,000 use locations were omitted 

from this analysis. Distance to urban was extracted at the use 

and availability locations for each eagle (using distance at the 

cell centroids using the land use raster described in Tracey 

and others, 2018). Finally, we omitted all data with locations 

more than 6,050 m from urban values, because 95 percent of 

our use data were within this distance (fig. 1). Distance to the 

urban edge was standardized (a common practice in regression 

modeling) by subtracting the mean distance to urban from 

each distance value and dividing by the standard deviation of 

the distances. In order to assess the effect of the resampling 

scheme on GAMM predictions, we repeated this process for 

10 trials, thereby generating 10 randomly sampled datasets, 

fitting the GAMM to each dataset, and calculating a mean 

prediction across all 10 trials. More extensive assessment 

using a larger number of trails will be performed prior to 

publication in a peer-reviewed journal.

Using these data, we used a generalized additive 

mixed-effects model (GAMM) to regress use (y=1) versus 

availability (y=0) on standardized distance to urban as a 

fixed-effect predictor with individual eagle as a random effect 

(Wood, 2017). Analysis was performed in R (R Core Team, 

2018) using the gamm4 package (Wood and Scheipl, 2020).

1U.S. Geological Survey, Western Ecological Research Center, San Diego, 

California

2Bloom Biological Inc., Santa Ana, California
2 A Clarification on the Effects of Urbanization on Golden Eagle Habitat Selection

A

B

0 1,000 2,000 3,000 4,000 5,000 6,000

0.0000 0.0010 0.0020

0 1,000 2,000 3,000 4,000 5,000 6,000

0.0000 0.0010 0.0020

Figure 1. Distance to urban in meters at A, use locations (lime green) and at B, availability locations 

(tan) used in the generalized additive mixed-effects model (GAMM) regression. These data are for a 

single trial.
Results and Discussion 3

Results and Discussion

The final datasets were generated based on data from 

13 female and 5 male golden eagles. We used a mean of 

66,667.3 observations per trial (range of 66,577–66,756). 

Our findings show that eagles used locations near the 

urban edge less than their availability within the study 

area based on histograms of distances to urban for the use 

and availability locations (fig. 1); this result is reinforced 

by the mean GAMM regression curve that shows a lower 

probability of use by eagles with decreasing distance to 

urban less than 2,089 m (fig. 2; table 1 numerical results at 

50-m-distance intervals). Results were consistent across all 

10 trials (fig. 2). At a distance of less than 1,285 m to the 

urban edge, predicted probability of eagle use falls below 

any probability predicted at greater distances and continually 

declines (to 0.0799) as distance to the urban edge goes to 

zero m. Hence, a deduction in predicted use by golden eagles 

occurs not only in urban areas, but also extends beyond the 

urban edge into non-developed areas. The mean predicted 

probability of eagle use continues to increase with increasing 

distance from 1,285 to 2,089 m from the urban edge (reaching 

0.6895); however, these probabilities fall within the range of 

predicted probability of use beyond 2,089 m (0.5540–0.7307). 

At distances greater than 1,285 m, predicted probability of 

eagle use levels off as distance to the urban edge increases, 

fluctuating between 0.5540 and 0.7307. These fluctuations 

in predicted use over this range are due to the adaptability of 

the GAMM function and variation in eagle habitat quality 

and use due to factors other than response to the urban edge. 

The spatial effect of the avoidance of urban areas is shown on 

figure 3. The mechanism behind this reduced use may be due 

to behavioral avoidance of urban areas by golden eagles or 

habitat impacts near the urban edge. The results in figures 2

and 3 and table 1 suggest that golden eagle use is reduced in 

non-urban areas within a kilometer or more of the urban edge.
4 A Clarification on the Effects of Urbanization on Golden Eagle Habitat Selection

0 1,000 2,000 3,000 4,000 5,000 6,000

0.0 0.2 0.4 0.6 0.8 1.0

Figure 2. The mean generalized additive mixed-effects model (GAMM) population-level prediction for 

probability of use given availability as a function of distance to urban edge (in meters, m). The mean regression 

curve over 10 trials is shown in dark blue. Individual GAMM regression curves are shown in dark gray, and 

the range of predictions are shaded in light gray. The red-dashed lines show the distance at which predicted 

use declines below any level predicted at larger distances to urban (1,285 m) and the distance to the first local 

maximum of the predicted probability of the use regression curve (2,089 m).
Results and Discussion 5

Table 1. The probability of use at 50-meter (m) intervals for distances of 

0–2,000 m from the urban edge based on predictions from the generalized 

additive mixed-effects model.

[For each distance, the mean predicted probability (Prediction) and the 95 percent 

confidence interval (95% CI) are given based on the 10 trials. Abbreviation: m, meter]

Distance (m) Prediction 95% CI

0 0.0799 0.0735–0.0821

50 0.0889 0.0827–0.0911

100 0.0988 0.0928–0.1011

150 0.1096 0.104–0.1119

200 0.1214 0.1163–0.1237

250 0.1343 0.1298–0.1365

300 0.1481 0.1445–0.1504

350 0.1631 0.1604–0.1652

400 0.1791 0.1775–0.1811

450 0.1961 0.1946–0.1979

500 0.2141 0.2124–0.216

550 0.2331 0.2311–0.2365

600 0.2529 0.2506–0.258

650 0.2735 0.2709–0.2802

700 0.2947 0.2918–0.3031

750 0.3164 0.3132–0.3266

800 0.3386 0.335–0.3503

850 0.3609 0.357–0.3742

900 0.3834 0.3791–0.3981

950 0.4057 0.4012–0.4217

1,000 0.4279 0.4231–0.4448

1,050 0.4496 0.4447–0.4674

1,100 0.4709 0.4658–0.4892

1,150 0.4915 0.4864–0.5101

1,200 0.5114 0.5062–0.5299

1,250 0.5305 0.5253–0.5487

1,300 0.5486 0.5436–0.5662

1,350 0.5657 0.5608–0.5825

1,400 0.5818 0.5771–0.5975

1,450 0.5968 0.5924–0.6112

1,500 0.6108 0.6067–0.6235

1,550 0.6236 0.6198–0.6345

1,600 0.6352 0.6319–0.6441

1,650 0.6458 0.6428–0.6524

1,700 0.6552 0.6527–0.6593

1,750 0.6634 0.6613–0.6668

1,800 0.6705 0.6676–0.6741

1,850 0.6765 0.6704–0.6804

1,900 0.6813 0.6718–0.6855

1,950 0.685 0.6718–0.6895

2,000 0.6876 0.6706–0.6924
6 A Clarification on the Effects of Urbanization on Golden Eagle Habitat Selection 3,600,000 3,650,000 3,700,000

460,000 500,000 540,000 580,000

Figure 3. The spatial effect of golden eagle avoidance of urban areas. Urban areas (based on Tracey and 

others, 2018) shown in brown (estimated to be 82,548 hectares, ha); distance to urban less than 1–1,285 meters 

(m) shown in tan (estimated to be 273,574 ha); distance to the urban edge 1,285–2,089 m in light blue (estimated 

to be 109,011 ha); and distance to urban edge greater than or equal to 2,089–6,000 m in teal (estimated to 

be 324,307 ha). Note the modeled usage shown here does not consider the additional effects of exurban or 

other forms of development, small habitat patch size, or patch isolation. The map projection used is Universal 

Transverse Mercator (UTM) Zone 11, World Geodetic System (WGS) 84.
References Cited 7

References Cited

Manly, B.F., McDonald, L., Thomas, D.L., McDonald, T.L., 

and Erickson, W.P., 2002, Resource selection by 

animals—statistical design and analysis for field 

studies, second edition: Dordrecht, Netherlands, 

Springer Science & Business Media, 222 p., 

https://www.springer.com/gp/book/9781402006777.

R Core Team, 2018, R—A language and environment for 

statistical computing: Vienna, Austria, R Foundation for 

Statistical Computing, https://www.R-project.org/.

Tracey, J.A., Madden, M.C., Sebes, J.B., Bloom, P.H., 

Katzner, T.E., and Fisher, R.N., 2016, Biotelemetry data 

for golden eagles (Aquila chrysaetos) captured in coastal 

southern California, November 2014–February 2016: 

U.S. Geological Survey Data Series 994, 32 p., 

https://doi.org/10.3133/ds994.

Tracey, J.A., Madden, M.C., Sebes, J.B., Bloom, P.H., 

Katzner, T.E., and Fisher, R.N., 2017, Biotelemetry data 

for golden eagles (Aquila chrysaetos) captured in coastal 

southern California, February 2016–February 2017: 

U.S. Geological Survey Data Series 1051, 35 p., 

https://10.3133/ds1051.

Tracey, J.A., Madden, M.C., Bloom, P.H., Katzner, T.E., 

and Fisher, R.N., 2018, Golden eagle (Aquila chrysaetos) 

habitat selection as a function of land use and terrain, 

San Diego County, California: U.S. Geological 

Survey Open-File Report 2018–1067, 13 p., 

https://doi.org/10.3133/ofr20181067.

Tracey, J.A., Madden, M.C., Molden, J.C., Sebes, J.B., 

Bloom, P.H., and Fisher, R.N., 2020, Biotelemetry data 

for golden eagles (Aquila chrysaetos) captured in coastal 

southern California, February 2017–December 2019: 

U.S. Geological Survey Data Series 1128, 34 p., 

https://doi.org/10.3133/ds1128.

Wood, S., 2017, Generalized additive models—An 

introduction with R, second edition: New York, N.Y., CRC 

press, 496 p., https://doi.org/10.1201/9781315370279.

Wood, S., and Scheipl, F., 2020, gamm4:—

Generalized additive mixed models using 'mgcv' 

and 'lme4', R package version 0.2-6 software: 

https://CRAN.R-project.org/package=gamm4.

For more information concerning the research in this report, 

contact the

Director, Western Ecological Research Center

U.S. Geological Survey

3020 State University Drive East

Sacramento, California 95819

https://www.usgs.gov/centers/werc

Publishing support provided by the U.S. Geological Survey

Science Publishing Network, Sacramento Publishing Service Center
Tracey and others—A Clarification on the Effects of Urbanization on Golden Eagle Habitat Selection—OFR 2020–1110

ISSN 2331-1258 (online)

https://doi.org/10.3133/ofr20201110