HOME RANGE AND HABITAT USE OF BREEDING COMMON RAVENS IN
REDWOOD NATIONAL AND STATE PARKS
by
Amy Leigh Scarpignato
A Thesis
Presented to
The Faculty of Humboldt State University
In Partial Fulfillment
Of the Requirements for the Degree
Masters of Science
In Natural Resources: Wildlife
August, 2011
ABSTRACT
Home range and habitat use of breeding Common Ravens in Redwood National and State
Parks
Amy Scarpignato
Very little is known about home range and habitat use of breeding Common
Ravens (Corvus corax) in Redwood National and State Parks (RNSP) despite their
identification as nest predators of the Marbled Murrelet (Brachyramphus marmoratus). I
used radio telemetry to examine home range, habitat use, and foraging behavior of
breeding Common Ravens in RNSP during 2009 (n = 3) and 2010 (n = 8). I estimated
home range and core-use area size, calculated home range overlap between adjacent
ravens, and quantified site fidelity by calculating overlap between years for the same
individuals. I used Resource Utilization Functions (RUFs) to examine raven resource use
within the home range. Average home range size of ravens in RNSP was 182.5 ha (range
82-381 ha) and average core-use area was 31.4 ha (range 5-71 ha). The most supported
habitat use models were the global and human models followed by the old-growth model.
All beta coefficients in models of individual birds differed from zero suggesting that the
variables in the models had a strong influence on home range use. Home range use of
individual ravens was generally higher near roads (n = 6), old-growth edge (n = 7), bare
ground (n = 6), and in mixed hardwood (n = 5) and prairie habitats (n = 5). Use generally decreased near human use areas (n = 5) and in old-growth habitat (n = 5). Radioed ravens were observed foraging in human use areas 85% of the time but only 35% of identified
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food items were anthropogenic. While I found little overlap between adjacent ravens, the areas of overlap were centered on anthropogenic food sources that occurred at adjacent territory boundaries. Removal of anthropogenic food sources along roads and in human use areas within and adjacent to Marbled Murrelet nesting areas may reduce raven use of these areas and thereby reduce potential encounters of ravens and murrelet nests.
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ACKNOWLEDGEMENTS
I would like to thank Dr. T. Luke George for his help throughout my experience at Humboldt State University. I would like to thank my committee members Dr. Mark
Colwell and Dr. Richard Golightly. I would like to thank David Haines for trapping expertise and an overall generous amount of support. I would like to thank CORA crew members; Micah Carnahan, Christina Varian, Bridget Roberts, Wendy Pearson, Skylar
Giordano, Lindy Keilson, Stephanie Nefas, Elizabeth Maldonado, and Caroline Allander for great tracking and data collection. I would also like to thank The Wright Family for providing funding for this research and the National Park Service, California State Parks,
Keith Benson, Jay Harris, and Rich Byrnes for access to study sites. Anthony Desch,
Kristin Sesser, and The Luke George Lab 2009-2011 provided both logistical and emotional support. I would also like to thank Brian Kertson, Chad Rittenhouse, and John
Marzluff for invaluable guidance and insight with statistical analysis. I would like to thank my family, especially Joe and Jackie Scarpignato, for providing me with a great support system and lots of love.
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TABLE OF CONTENTS
Page
ABSTRACT …………………………………………………………………………... iii
ACKNOWLEDGEMENTS …………………………………………………………… v
LIST OF TABLES ……………………………………………………………………. vii
LIST OF FIGURES ………………………………………………………………….. viii
LIST OF APPENDICES ………………………………………………………………. ix
INTRODUCTION ……………………………………………………………………. 1
METHODS ……………………………………………………………………………. 4
RESULTS …………………………………………………………………………….. 12
DISCUSSION ……………………………………………………………………….... 15
MANAGEMENT IMPLICATIONS …………………………………………………. 23
LITERATURE CITED ……………………………………………………………….. 24
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LIST OF TABLES
Table Page
1 Fixed-kernel density estimates with choice of the plug-in method for smoothing parameter of home range and core-use area of eight Common Ravens in Redwood National and State Parks, California, 2009 and 2010. Mean (±SE) of each variable for each year are also provided…………………. 31
2 Three-dimensional home range overlap for adjacent breeding Common Ravens in Redwood National and State Parks, California, 2010. Three- dimensional overlap measures the volume of overlap of the utilization Distributions. Mean (±SE) is also provided..…………………………………… 32
3 Site fidelity using 3-dimensional and 2-dimensional home range overlap of three breeding Common Ravens in Redwood National and State Parks, California between 2009 and 2010. Three-dimensional overlap measures the volume of overlap of utilization distributions and 2-dimensional overlap measures the area of overlap between years. Mean (±SE) of each variable are also provided………………………………………………………….……. 33
4 Number of times a model was the top model, average Akaike’s Information Criterion (AIC) weight, and range of model weights for Common Raven resource use in Redwood National and State Parks, California, 2010…………. 34
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LIST OF FIGURES
Figure Page
1 Location of the study area within the southern portion of Redwood National and State Parks, Humboldt County, California………………… 35
2 Routes surveyed during area searches to locate breeding Common Ravens. Despite extensive surveys in forest interior, ravens were only detected along roads and forest edges…………………………….. 36
3 Fixed-kernel density estimates of home range (95% kernel) with choice of the plug-in method for smoothing parameter of eight breeding Common Ravens in Redwood National and State Parks, California in 2010. Each individual raven is identified by a different pattern. Core-use areas (50% kernel) are indicated within each home range by darker lines…………………………………………………… 37
4 Overlap in home range use between breeding Common Ravens in 2009 and 2010 in Redwood National and State Parks, California. The shading represents the amount of 3-dimensional overlap based on utilization distributions from each year…………………………………. 38
viii
LIST OF APPENDICES
Appendix Page
A Common Raven banding information and morphometric measurements, Redwood National and State Parks, California, 2009 and 2010………………………………………………………… 39
B Fixed-kernel density estimates of home range (95% kernel) size (ha) for seven bandwidth selection techniques of eight Common Ravens in Redwood National and State Parks, 2010………………….. 40
C Fixed kernel density estimates of core-use area (50% kernel) size (ha) for seven bandwidth selection techniques of eight Common Ravens in Redwood National and State Parks, 2010…………………. 41
D Model selection results of standardized resource utilization functions (RUF) of eight Common Ravens in Redwood National and State Parks, California, 2010. Models are ranked according to the difference in Akaike’s Information Criterion (AIC) between the model and the best-fitting model (ΔAIC). Number of parameters (k)
and Akaike weight (wi) are presented for all models……………….….. 42
E Maximum likelihood estimates (MLE) of standardized resource utilization function (RUF) coefficients, standard errors (SE), and 95% lower and upper confidence intervals from the top model for eight Common Ravens in Redwood National and State Parks, California, 2010………………………………………………………… 43
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INTRODUCTION
Marbled Murrelet (Brachyramphus marmoratus) populations have declined substantially in the southern portion of their range, leading to their listing as a federally threatened species in Oregon, Washington, and California and a state-endangered species in California in 1992 (California Fish and Game Commission 1992, USFWS 1992). Loss of breeding habitat was identified as the greatest threat to the persistence of murrelet populations in the original listing decision, therefore, initial conservation efforts focused on protection and restoration of coastal old-growth forests. Despite the protection of remaining coastal old-growth forest in Oregon, Washington, and California, Marbled
Murrelet populations have continued to decline in the southern portion of their range
(McShane et al. 2004). More recent analyses suggest that the greatest threat to maintaining a viable Marbled Murrelet population in California is low productivity due to poor reproductive success (Nelson and Hamer 1995, Ralph et al. 1995, Peery et al. 2004).
The few direct observations that have been made suggest that corvids, in particular
Common Ravens (Corvus corax) and Steller’s Jays (Cyanocitta stelleri), are important predators of Marbled Murrelet nests (Singer et al. 1991, McShane et al. 2004, Peery et al.
2004, Hébert et al. 2006, Golightly and Gabriel 2009, Golightly and Schneider 2009,
USFWS 2009). Because space use by corvids has been found to predict nest predation
(Marzluff et al. 2004), a better understanding of the home range and habitat use of
Common Ravens in Redwood National and State Parks (RNSP) may provide insights into
1
2 management approaches to reduce Marbled Murrelet nest predation by Common Ravens in RNSP.
No long-term surveys have been conducted on corvids in RNSP but analyses of
Breeding Bird Surveys indicate that Common Ravens have increased 380% over the period 1966-2007 in the Southern Pacific Rainforest Ecoregion (George 2009). Common
Ravens are considered generalist omnivores, eating live prey, carrion, eggs, insects, grains, and anthropogenic foods. In addition, the ability for Common Ravens to use different environments, including human development (Boarman and Heinrich 1999,
Kristan and Boarman 2003, Marzluff and Neatherlin 2006, RNSP 2008a), has lead to a dramatic increase of their populations in western North America and Redwood National and State Parks (Liebezeit and George 2002, McShane et al. 2004). Marzluff and
Neatherlin (2006) found that Common Ravens exploited anthropogenic food sources when nesting within 1 km of settlements and campgrounds and that breeding ravens near human settlements and campgrounds exhibited reduced home range size, increased reproduction, and increased abundance. In addition, Common Ravens have been found to be more abundant along major roads and highways that provide an easy and dependable source of road-killed food (Austin 1971, Knight and Kawashima 1993, Knight et al.
1995, Boarman and Heinrich 1999).
An analysis of both real Marbled Murrelet nests with known fates and simulated nests indicated that the highest risk of predation was found near forest edges, especially in areas adjacent to human activity (Raphael et al. 2002, Malt and Lank 2009). Almost all of RNSP’s high-use visitor areas and major roadways are located within old-growth
3 forest (Bensen 2008). Thus, habitat fragmentation in combination with the availability of anthropogenic food sources may be attracting Common Ravens to high quality Marbled
Murrelet nesting habitat leading to higher predation rates of Marbled Murrelet nests and a decline in reproductive success (Raphael et al. 2002, Golightly and Gabriel 2009).
Despite their identification as an important nest predator of the Marbled Murrelet, very little is known about the Common Raven in Redwood National and State Parks
(Singer et al. 1991, Peery et al. 2004, Hébert and Golightly 2007). Understanding the relationship between nest predator ecology and behavior and predation risk can improve our ability to conserve sensitive species and make effective management decisions
(Liebezeit and George 2002, Marzluff and Neatherlin 2006). Common Raven home range use has been examined in other environments, but no home range studies have been conducted in coastal old-growth forests in California. Home range provides a direct measure of the area used by an animal during its normal activities (Burt 1943) while space use may determine the size of the home range, link the movement of animals to the distribution of resources within the home range (Borger 2006, Borger 2008), and be a good predictor of predation risk (Marzluff et al. 2004). I used radio-telemetry to examine factors that influence Common Raven space use within the home range. My objectives were to (1) estimate home range and core-use area size, (2) estimate the amount of home range overlap and site fidelity, and (3) examine resources influencing habitat use within the home range of breeding Common Ravens in Redwood National and State Parks.
METHODS
STUDY AREA
I studied Common Ravens in the southern portion of Redwood National and State
Parks (41°24′N, 124°01′W), Humboldt County, California, from the town of Orick, north, to the Klamath River (Fig. 1). The climate is characterized by cool, wet winters
and coastal fog that moderates summer temperatures. Annual precipitation of 175 cm
falls almost entirely as rain, occurring predominately between November and May.
Average summer temperatures range from 8-19° C and average winter temperatures
range from 4-13° C (RNPS 2008b). Old-growth forest comprises 30% of RNSP,
representing 45% of remaining old-growth redwood forests in California (RNPS 2008b).
Major habitats include old-growth and second-growth forests dominated by coast
redwood (Sequoia sempervirens) and Douglas-fir (Pseudotsuga menziesii), natural
prairies, and mixed hardwood forests dominated by red alder (Alnus rubra), willow (Salix
spp.), big-leaf maple (Acer macrophyllum), tanoak (Lithocarpus densiflorus), madrone
(Arbutus menziesii), and California bay (Umbellularia californica). Major river drainages
include the Klamath River, Redwood Creek, and Prairie Creek. There are four main
campgrounds and numerous backcountry campsites, picnic areas, visitor facilities, and
roads scattered throughout the park complex. Approximately 400 000 people visit the
park every year with highest visitation from May to September (RNSP 2008b). The park
is long and narrow, transected by California Highway 101, the Newton B. Drury
Parkway, and numerous smaller roads. The park boundaries are surrounded by human-
4
5 modified landscapes including towns, cattle pastures, managed timberland, and beaches
that provide many food sources for ravens.
CAPTURE AND RADIO TELEMETRY
I conducted area searches from February to April 2009 and 2010 to locate
breeding pairs of Common Ravens (hereafter “raven”). Surveys were conducted along
roads and trails in the study area focusing on areas containing old-growth forest, known and potential Marbled Murrelet (hereafter “murrelet”) nest sites, and areas that were logistically feasible to capture ravens safely and conduct radio telemetry. When I located a breeding raven pair, I recorded the pair’s location (<10 m accuracy) in Universal
Transverse Mercator (UTM) coordinates with hand-held Global Positioning System
(GPS) units (Garmin GPSMAP 60Cx) and observed birds to identify habitual perches and food sources.
I captured ravens from May-July 2009 and March-June 2010 using a bow net
(Superior Bownet & Design, Clinton, MD) and remote control trigger design (Jackman et al. 1994). I baited trap sites with meat scraps or human food for approximately one week before trapping. I removed ravens from traps within a few minutes of capture and released ravens within 60-90 min after capture. Because breeding pairs occupy similar
home ranges and sex has not been found to influence home range size (Linz et al. 1992,
Roth et al. 2004, Marzluff and Neatherlin 2006), I captured one member of each of 10
target pairs. I banded ravens with a United States Geological Service stainless steel butt
end band and a unique engraved plastic band (Bedrosian and Craighead 2007). I attached
6 backpack mounted radio transmitters (model A1135, Advanced Telemetry Systems,
Isanti, MN) weighing 19 grams (< 3% body weight) with a 6.35mm-wide Teflon ribbon harness (Driscoll 2009, M. Lanzone 2009, pers. comm.). I measured wing chord, culmen length, tarsus length, and mass, determined age based on mouth color, iris color, and plumage (Kerttu 1973, Heinrich and Marzluff 1992), and sex based on the presence of a brood patch or cloacal protuberance and behavior (Appendix A). All capture and handling methods were approved by the Humboldt State University Institutional Animal
Care and Use Committee (# 08/09.W.64.A).
I relocated ravens with radios from May-September 2009 (n = 3) and March-
September 2010 (n = 8) using telemetry receivers (model RS 1000, Communication
Specialists Inc., Orange, CA or model TRX-1000S Wildlife Materials, Inc.,
Murphysboro, IL) and 3-element, collapsible Yagi antennas. I followed all birds captured in 2009 in both 2009 and 2010. Each bird was relocated in random order, 1-2 times per day, separated by at least 1 hr, during three randomly selected periods in the day: morning (06:00-11:00), midday (11:00-16:00) and evening (16:00-21:00). If the bird was visually located, a GPS location (<10 m accuracy), habitat type, and behavior were recorded. Habitat type was classified as second-growth, old-growth, prairie, bare ground, mixed hardwood, campground, picnic area, parking lot, paved road, roadside, or human habitation. I defined old-growth as areas that had never been logged and second-growth included any logged forests. Prairie included areas of natural prairies and dead or green grass, forbs, or shrubs. Bare ground included soil, pavement, rock, and gravel. Mixed hardwood included areas dominated by hardwoods such as alder and willow. Behavior
7 was categorized as foraging (searching for or carrying food), perching, courtship, nesting,
resting, preening, social interaction, or human interaction. If a bird was foraging, I recorded the food item it was manipulating. If a bird was perched, I recorded the perch type and estimated perch height (m) with a rangefinder (Opti-Logic Models 400 LH and
400 XLA; 0.9m accuracy). To find nest sites, I recorded the location of adults carrying food to fledglings, fledgling vocalizations, or any nesting behaviors. If a bird could not be seen, I triangulated its location with at least three bearings. I estimated locations and error polygons using LOAS™ 4.0.3.3 (Ecological Software Solutions LLC 2009). I eliminated
all points with error polygons larger than the smallest habitat patch size (1.3 ha) within
my study area based on vegetation maps provided by RNSP in ArcGIS® 9.3.1 (ESRI
2009).
STATISTICAL ANALYSIS
Home range and home range overlap
I calculated home range and core-use area size using fixed-kernel density
estimators. I determined smoothing parameters by calculating a pilot bandwidth to
estimate the density function. I plugged in the density function estimate to calculate the
ideal bandwidth (plug-in method; Wand and Jones 1995, Kernohan et al. 2001, Gitzen et
al. 2006). I calculated the smoothing parameter using the Hpi.diag function in the ks
package Version 1.7.1 (Duong 2010) in Program R 2.8.1 (R Development Core Team
2009). In addition, I compared home range and core-use area size estimates for seven bandwidth selection techniques (Appendix B, C). Kernel estimators are most robust with
8 at least 30 points, preferably more than 50, so I estimated all home ranges with at least 49
points in 2009 and 67 points in 2010 (Seaman et al. 1999, Kernohan et al. 2001). Home
range and core-use areas were defined as the extent of area with a 95% and 50%
probability of occurrence, respectively, during the study period. Home range estimates
provided a 95% utilization distribution, 95% home range, and 50% core-use area for each
bird at a 10 x 10 m cell size and were calculated in Home Range Tools Version 1.1
(Rodgers et al. 2005) in ArcGIS® 9.3.1. In addition, I calculated 99% utilization distributions, and 99% kernel home range estimates using Hawth’s Analysis Tools for
ArcGIS (Beyer 2004). I calculated autocorrelation among telemetry locations using the
Swihart and Slade index (Swihart and Slade 1985) in Home Range Tools in ArcGIS®
9.3.1. Significant autocorrelation was present among sampling points with a score less
than 1.6 or greater than 2.4.
I calculated the 3-dimensional home range overlap (Volume of Intersection Index;
Seidel 1992, Millspaugh et al. 2004, Kertson and Marzluff 2009) between adjacent
ravens within the same year. In addition, I calculated the 2-dimensional and 3-
dimensional home range overlap between years for the same individual to quantify site
fidelity. Home range overlap was calculated in ArcGIS® 9.3.1 using the 99% utilization
distribution (3-dimensional overlap) and the 99% kernel home range (2-dimensional
overlap) (Kertson and Marzluff 2009). Two-dimensional overlap assumes equal use of
the home range (Kertson and Marzluff 2009) while 3-dimensional overlap takes into
account spatial variation in home range use. Results are presented as means ± SE.
9
Resource Utilization Function Analysis
I used the Resource Utilization Function approach (RUF; Marzluff et al. 2004) to examine the relationship between raven home range use and habitat variables because it
allowed the individual animal to be the sampling unit, used a continuous measure of
space use, and considered the entire home range in the analysis. Because this approach
examined space use within the home range, it corresponded to third-order habitat
selection (Johnson 1980). Within each raven’s 99% utilization distribution (30 x 30 m
cell size to match the spatial resolution of the landscape data), I used the height of the
utilization distribution at each pixel as the dependent variable and the landscape attributes
within the same pixel as the independent variables. I conducted multiple regression
analyses between home range use and habitat variables with the ruf package in Program
R 2.8.1(Handcock 2004), which adjusts for spatial autocorrelation using the Matern
correlation function. The magnitude of the standardized coefficients indicated the relative
importance of the resource. A positive sign indicated resource use increased with an
increase in quantity and a negative sign indicated resource use decreased with an increase
in quantity.
Model development and selection
I developed four a priori models based on previous research and park management concerns using eight habitat variables to describe raven habitat use. The
eight variables included: distance to road, distance to human use areas, distance to old-
growth edge, and five habitat types. I measured the Euclidean distance within each pixel
10 in the utilization distribution to the nearest human use area (m), road (m), and old-growth edge (m) in ArcGIS® 9.3.1 from GIS layers provided by RNSP (D. Best 2009, pers.
comm.) . Human use areas included: campgrounds, parking lots, private homes, park
facilities, picnic areas, farms, a lumber mill, and the town of Orick. Distance to road
quantified the distance to Highway 101, Newton B. Drury Parkway, and Bald Hills Road, which were paved roads with high traffic that may provide road kill for ravens. Distance to old-growth edge was the distance to the nearest edge between old-growth forest and
any other habitat type. I identified five habitat categories: second-growth forest, bare
ground, mixed hardwood forest, old-growth forest, and prairie (refer to p. 6 for habitat
descriptions). Habitat types were assigned based on vegetation maps from RNSP in
ArcGIS® 9.3.1 (D. Best 2009, personal communication). All of the distance variables were log-transformed prior to analysis. I ran correlation matrices in Program R 2.8.1 to test for correlations among model covariates. I only included variables with a correlation coefficient less than 0.7 in the models. If a variable did not occur within the utilization distribution of the individual raven, it was left out of the model for that individual.
I developed candidate models based on insights from previous studies on raven habitat use and concerns about the potential impact of ravens on nesting murrelets. The human model included distance to roads and distance to human use areas. The old-growth
model included a dummy variable for old-growth forest and distance to old-growth edges. The habitat model included all of the five habitat types. The global model included distance to human use areas, distance to roads, distance to old-growth edges, and all of the habitat variables. I used Akaike’s Information Criterion (AIC) to identify the best
11 model for individual ravens from the set of candidate models. Models were ranked using
∆AIC and relative likelihood was determined using Akaike weights (Burnham and
Anderson 2002). Models within 2.0 ∆AIC points were averaged, using model averaging to obtain unconditional estimates of coefficients, standard errors, and 95% confidence intervals.
RESULTS
I surveyed large portions of the study area, including interior forest trails and
areas away from roads, but found all ravens near roads or along edges (Fig. 2). Surveys
totaled 105 hrs. I captured ten ravens, three in 2009 and seven in 2010. Trapping totaled
184 hrs, with a range of 0.5-106.5 trap hrs per individual bird. Average time for a raven
to be captured from initial trap set-up was 1.5 hrs. In 2009, I collected an average of 51 locations (range 49-53 points) for each bird (n = 3). In 2010, I relocated the three ravens
captured in 2009 and five of the seven ravens captured in 2010. I could not relocate two ravens after capture in 2010 either due to transmitter failure, departure from the study area, or residing in a location with too much interference to receive a signal. I collected an average of 95 locations (range 67-117 points) for each bird (n = 8)
I observed ravens perched on human structures (29%) and trees or snags (71%) with an average perch height of 22 ± 3 m (n = 127). Average perch height for human structures was 5 ± 1 m (n = 30) and included light posts (55%), fences (38%), and road signs (7%). Average perch height for natural perches was 29 ± 3 m (n = 97) and included redwood (49%), hardwood (37%), and Douglas-fir (14%) trees. When perched in redwoods, average perch height was 55 ± 5 m (n = 48). I observed ravens foraging (n =
39) in human use areas 85% of the time, including campgrounds (18%), parking lots
(36%), and roads and roadsides (46%). Ravens foraging outside of human use areas were observed in prairies or grassy areas along roads. When I observed birds foraging (n = 39),
I could identify food items 30% of the time. Of those observations, 35% were
12
13 anthropogenic (trash, scrambled eggs, chips, and human vomit) and 65% were natural
food items (Gray Fox (Urocyon cinereoargenteus), snake, and chipmunk (Tamias sp.) roadkill, worms, mushrooms, and a fish carcass). I could not locate exact nest trees but all nesting areas were located within core-use areas (n = 8) and in old-growth forest except one for which the habitat type could not be determined.
HOME RANGE AND HOME RANGE OVERLAP
In 2010, raven home range size averaged 182.5 ± 41.5 ha (range 82-381 ha) and
core-use area size averaged 31.4 ± 7.4 ha (range 5-71 ha; n = 8; Table 1, Fig. 3). Home range size for the three ravens captured in 2009 averaged 121.3 ± 5.0 ha (range 114-131 ha) and core-use area size averaged 24.0 ± 4.0 ha (range 16-29 ha; n = 3; Table 1). Raven core-use areas contained human use areas, such as campgrounds, housing, and parking lots (75%) and high traffic road interchanges (25%; n = 8). I detected autocorrelation among locations for two birds. However, I did not adjust the estimates for autocorrelation because all raven locations were collected at least an hour apart.
There were few areas where raven home ranges overlapped but in all six cases, home range overlap between adjacent pairs was not more than 6% (xˉ = 3.4 ± 0.8 %; range 1-6%; n = 6; Table 2) and the area of overlap included human use areas, such as a lumber mill, highway interchange, campground, visitor’s center, and housing area. Site fidelity among individual ravens was high between 2009 and 2010 with an average 3- dimensional overlap of 65 ± 0.1% (range 54-74%; n = 3; Table 3, Fig. 4) and an average
2-dimensional overlap of 81 ± 0.03% (range 77-86%; n = 3; Table 3, Fig. 4).
14
RESOURCE UTILIZATION FUNCTION ANALYSIS AND MODEL SELECTION
The global and human models received the most support (3 of 8 individuals,
37.5% each; Table 4, Appendix D) followed by the old-growth model (2 of 8 individuals,
25%; Table 4, Appendix D). The habitat model was not ranked as a top model for any raven (0 of 8; Table 4, Appendix D). The global model received the highest average
Akaike weight (0.39; Table 4, Appendix D) followed by the old-growth (0.30; Table 4,
Appendix D), human (0.26; Table 4, Appendix D) and habitat models (0.05; Table 4,
Appendix D). Individual use patterns were variable but all of the 95% confidence intervals of the coefficients in the top models differed from zero indicating that variables were good predictors of home range use. After model averaging, old-growth and distance to old-growth edge were important covariates in all eight top models, distance to road in seven top models, distance to human use in six top models, and bare ground, mixed hardwood, and prairie habitats in three top models (Appendix E). Within top models of individual ravens, raven use increased closer to roads and old-growth edge (6 of 7 ravens and 7 of 8 ravens, respectively; Appendix E). Raven use in proximity to human use areas was variable with four ravens showing decreased use closer to human use areas and two ravens showing increased use closer to human use areas (Appendix E). Use decreased in old-growth forest (5 of 8 ravens; Appendix E) while use increased in bare ground, mixed hardwood, and prairie habitats (3 of 3 ravens; Appendix E).
DISCUSSION
RESOURCE UTILIZATION FUNCTION ANALYSIS AND MODEL SELECTION
Individual ravens exhibited preferences for resources within their respective home
ranges. The global and human models were ranked as the top model most often but no
single model consistently explained raven use. However, the top model for raven use
within the home range of each individual was well supported with beta coefficients that
did not overlap zero. In general, individual ravens showed greater use of roads, old-
growth edges, bare ground, prairies, mixed hardwood and decreased use of old-growth
and human use areas.
Space use by ravens has been attributed to locations of food sources and nest site
placement (Roth et al. 2004, Marzluff and Neatherlin 2006), which is consistent with my
results. I was only able to quantify use of human influenced resources because exact nest
locations could not be confirmed. Models built using only foraging locations may provide
more consistent and repeatable measures of foraging habitat use yet a complete
description of raven habitat use, including nest site location, breeding stage, and seasonal
variation may be necessary to identify potential conflicts with sensitive species, such as
the Marbled Murrelet (Roth et al. 2004).
Due to the large variability in diet and food sources within each raven’s home
range, I found no relationship between distance to human use areas and raven use of human use areas within the home range. This pattern may also be due to small sample size (Powell and Backensto 2009) but was not due to collinearity among the independent
15
16 variables. There was no correlation between distance to human use sites and any of the
other independent variables. These conclusions did not change when distance to road and
distance to human use models were analyzed separately.
The lack of an association between raven use and distance to human use areas was
unexpected based on my observations and the results of other studies (Engel and Young
1992, Roth et al. 2004, Marzluff and Neatherlin 2006). There are three reasons why a
relationship between home-range use and distance to human use areas may not have been
found. First, I examined third order habitat selection (use within the home range) and
ravens may be responding to human use areas at a larger (second order) scale. Ravens
may place their territories near anthropogenic resources but within their home range (the
scale I examined) nest placement, old-growth edge, and roads may be more important.
All raven core-use areas contained roads or human use areas and my surveys indicated
little or no raven use away from these areas. Although detection may have been difficult
in interior forests, most often ravens would be attracted to a human presence or vocalize,
making detection probable. Because raven core-use areas contained human use areas,
variation in use relative to human use areas may have been difficult to detect. Second,
human activity may cause ravens to leave human use areas quickly after obtaining food
items. RNSP’s greatest visitation occurs from May to September, when 96% of radio-
telemetry locations (n = 758) were collected. Thus, the temporal use of the areas (as measured by radio locations) may not reflect the amount of resources ravens derive from human use areas. Ravens were observed foraging in human use areas but most often after visitors had vacated the area or ravens would obtain a food item and quickly leave to
17 consume it elsewhere. One raven was observed pulling trash from a parking lot trash
receptacle and many ravens were observed foraging in campsites, parking lots, or picnic
tables, but all were unoccupied. When campground visitation was high or when parking and picnic areas were full, ravens were observed perched in nearby trees. Third, resident pairs of ravens have been observed exploiting anthropogenic resources during most of the year and switching to natural prey during the breeding season when feeding nestlings and fledglings (Boarman and Heinrich 1999, Kristan and Boarman 2003). Because I collected
most of the locations during the period when ravens had nestlings or fledglings, ravens
may have switched to forage in locations where they could obtain natural prey, which
would reduce the association with human use areas and may increase the likelihood of
nest predation.
Ravens exhibited increased use closer to roads. Roads provide a dependable food
resource for ravens and in areas with limited resources may provide a significant portion
of the food available to ravens (Kristan et al. 2004, Marzluff and Neatherlin 2006).
Radio-marked ravens were observed foraging on snake, chipmunk and Gray Fox killed on roads. In addition, ravens were observed patrolling roadways, flying along road corridors, or perched on light posts, road signs, fences, and trees near highway interchanges during every visit to the study site. My findings and observations are consistent with other studies that have found high use of roads by ravens (Sherman 1993,
Marzluff and Neatherlin 2006, Kristan and Boarman 2007, Bui et al. 2010). In the
Mojave Desert, ravens spent 49% of their time foraging directly on linear-right-of-ways
(Sherman 1993). In addition, breeding ravens in the Mojave Desert placed their nests
18 closer to roads than to human use areas and distance to road was associated with high fledgling success (Kristan and Boarman 2007). Roads and road-killed carrion may be contributors to raven reproductive success (Kristan et al. 2004, Kristan and Boarman
2007) therefore, further studies are necessary, but management of food resources provided by roads may also decrease raven populations (Kristan et al. 2004, Kristan and
Boarman 2007, Bui et al. 2010).
Ravens also showed greater use of bare ground and prairie habitats, which is consistent with other studies of raven habitat use (Engel and Young 1992, Boarman and
Heinrich 1999, Marzluff and Neatherlin 2006, Mueller et al. 2009). Ravens are primarily ground foragers in open habitats and feed most often while walking on the ground
(Boarman and Heinrich 1999, Mueller et al. 2009). Diet studies found that arthropods were one of the most frequent food items in raven pellets (Engel and Young 1989, Camp et al. 1993, Kristan et al. 2004). Radioed ravens were regularly observed foraging for arthropods in the short grasses along roads and in natural prairies or eating worms and other food items in grassy roadsides. Thus, the high use of prairie and bare ground habitat that I found is consistent with raven foraging ecology and findings from other studies.
Models indicated greater use of mixed hardwood habitats by ravens. Mixed hardwood may be important foraging habitat for ravens during other times of the year but during my study, I did not observe ravens foraging in hardwood, only perched. I observed radioed ravens perched in hardwood trees adjacent to prairies, pastures, roads, parking lots and highway interchanges. High use of trees in riparian areas has previously been documented because of the importance of its perch sites (Engel and Young 1992). Mixed
19 hardwood trees in RNSP may provide perch sites for ravens and are often in close proximity to important food sources. Perch locations adjacent to food sources allow ravens to avoid human interaction while still being able to take advantage of anthropogenic food. It appears that ravens used mixed hardwood possibly because hardwoods provide important perch sites rather than food resources.
The only habitat where raven use decreased was old-growth forest. The low use of
old-growth forest interior by radioed ravens was consistent with my initial surveys and
point count surveys conducted in RNSP (Bensen 2008). During the 2007 and 2008
murrelet nesting season, 10 point stations in interior old-growth forest were surveyed 10
times and no ravens were detected within 50 m of the point count (Bensen 2008). Low
use of old-growth was most likely due to limited food resources and lack of suitable
foraging habitat in coniferous forests (Mueller et al. 2009).
Despite low use of old-growth, models indicated high use of old-growth edge.
Ravens were observed daily perched in tall redwood trees and snags along old-growth
edges. Although greater use of old-growth edge may be a reflection of the edges created
by roads or human use areas, ravens may take advantage of the good viewing along old-
growth edges to search for potential food items, especially along roads and near human
use areas. The combination of the attraction of anthropogenic resources with a preference
for perching along old-growth edges may draw ravens closer to murrelet nesting habitat,
especially near human use areas (Raphael et al. 2002, Marzluff et al. 2004, Malt and
Lank 2009).
20 HOME RANGE AND HOME RANGE OVERLAP
I examined general patterns in home range size estimates of ravens in northern California
and western coniferous forests. Raven home range size in RNSP was substantially
smaller (xˉ = 265 ha (99% kernel)) than ravens in coniferous forests in Washington (xˉ =
1211 ha (99% kernel); Marzluff and Neatherlin 2006). Raven home ranges in RNSP were larger (xˉ = 183 ha (95% kernel)) than ravens inhabiting open areas in northern
California (xˉ = 121 ha (95% kernel); Roth et al. 2004). Small home range size is likely related to the presence of reliable food sources (Roth et al. 2004). Core-use areas of
radioed ravens in RNSP contained reliable food sources, such as campgrounds, housing,
parking lots or high traffic road interchanges.
Within smaller home ranges in RNSP, foraging effort may be greater; therefore a
raven may be more likely to encounter a murrelet nest if one is present in the home range.
Based on the home range size of the birds I captured and the amount of area surveyed, it
is clear that I sampled a large proportion of the breeding ravens in my study area.
Therefore, at the landscape scale, smaller home ranges of ravens in RNSP may mean that
less of the old-growth habitat is occupied by territorial ravens, especially in areas away
from roads and human use areas. Because home range placement of ravens in RNSP may
be associated with roads and human use areas and home range size is smaller than other
areas with similar habitat, raven use of RNSP is rather limited and could be greatly
reduced if anthropogenic food sources are removed.
The three ravens radioed in both years exhibited high site fidelity with an average
of 81% range overlap and 65% use overlap between years. This is higher than ravens in
21 coniferous forests in Washington where home range overlap between years averaged
66% for nine ravens. High site fidelity has also been documented for ravens in California,
Alaska and elsewhere (Boarman and Heinrich 1999, Roth et al. 2004, Powell and
Backensto 2009). I found little 3-dimensional home range overlap between adjacent ravens (xˉ = 5.5%) in RNSP but the few areas where ravens did overlap were human use areas. Marzluff and Neatherlin (2006) also detected a low amount of home range overlap among adjacent territories (xˉ = 7.7%) in Washington.
Raven pairs in RNSP actively defended territories throughout the study period.
Throughout this study, I did not observe non-breeding ravens in any breeding territories. I observed ten territorial displays between adjacent raven pairs. Five times, I observed radioed ravens chasing Red-tailed Hawks (Buteo jamaicensis) out of their territories and twice I observed Turkey Vultures (Cathartes aura) being chased away from food sources. In addition, I once observed a radio-marked raven preying on a Steller’s Jay nest. Active territoriality and predation of other murrelet nest predators might effect murrelet predation risk because raven territoriality and site fidelity may decrease overall raven and predator abundance within the park.
Although raven territoriality and site fidelity may decrease overall predator abundance, breeding ravens whose territories include nesting habitat of sensitive species may pose a predation risk to those individuals within the territory (Kristan and Boarman
2007, Bui et al. 2010). Nests of radioed ravens were located in old-growth forest; therefore despite overall low use of old-growth, nest placement within old-growth forest draws ravens through murrelet nesting habitat and may pose a predation risk in the area
22 around the raven nest. In addition, breeding ravens may effect murrelets because ravens have been observed to switch from anthropogenic food to natural prey when they start feeding young (Kristan and Boarman 2007). In RNSP, young ravens hatch as early as late
April and I observed adult ravens feeding fledglings into August. Thus, ravens in RNSP may be switching to forage on natural food items from April to August. Raven nest placement in old-growth along with the switch to natural prey items during the murrelet breeding season may increase the potential for ravens to encounter a murrelet nest.
MANAGEMENT IMPLICATIONS
Due to individual variation of raven home range use within RNSP, a number of different
management approaches are necessary to reduce impacts of ravens on murrelets. More
studies are necessary to identify important food sources for ravens but I observed ravens foraging in human use areas and exploiting anthropogenic food. In addition, ravens exhibited more use closer to roads, bare ground, and prairies possibly because these features provide food resources for ravens. More effort is needed to reduce the food availability within human use areas and along roads, especially in areas adjacent to old- growth forest. Reducing food sources may reduce raven presence in old-growth forest, thus reducing the potential for a raven to encounter a murrelet nest. Testing closures of human use areas or roads may be helpful in assessing the impacts of these features on raven populations. Caution should be used with future development of roads, campgrounds, or activities that create unnatural edges. Because of high site fidelity and territoriality, conditioned taste aversion in raven territories within high-risk areas may be an effective method of reducing nest predation by ravens (Avery et al. 1995, Golightly and Gabriel 2009).
23
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TABLES
Table 1. Fixed-kernel density estimates with choice of the plug-in method for smoothing parameter of home range and core-use area of eight Common Ravens in Redwood National and State Parks, California, 2009 and 2010. Mean (±SE) of each variable for each year are also provided.
Birda 95% Home Range (ha) 50% Core-use Area (ha) C 118 25 E 353 46 G 152 36 H 163 37 H(2009) 131 29 K 98 17 K(2009) 119 27 P 113 14 W 381 71 Y 82 5 Y(2009) 114 16 2009 121.3 ± 5.0 24.0 ± 4.0 2010 182.5 ± 41.5 31.4 ± 7.4 a Home range and core-use area size were estimated for 2009 and 2010 for the three ravens captured in 2009.
31
32 Table 2. Three-dimensional home range overlap for adjacent breeding Common Ravens in Redwood National and State Parks, California, 2010. Three-dimensional overlap measures the volume of overlap of the utilization distributions. Mean (±SE) is also provided.
Volume of Intersection Pair 3-dimensional overlap (%) Y_K 2 K_C 4 C_W 2 W_H 3 G_P 6 2010 Average 3.4 ± 0.8
33 Table 3. Site fidelity using 3-dimensional and 2-dimensional home range overlap of three breeding Common Ravens in Redwood National and State Parks, California between 2009 and 2010. Three-dimensional overlap measures the volume of overlap of the utilization distributions and 2-dimensional overlap measures the area of overlap between years. Mean (±SE) of each variable are also provided.
Site Fidelity Bird 3-dimensional overlap (%) 2-dimensional overlap (%) Y 54 80 K 67 77 H 74 86 Average 65 ± 0.06 81 ± 0.03
34 Table 4. Number of times a model was the top model, average Akaike’s Information Criterion (AIC) weight, and range of model weights for Common Raven resource use in Redwood National and State Parks, California, 2010.
AIC weight Model No. times Avg. Range Humana 3 0.26 0.00 - 0.61 Old-growthb 2 0.30 0.00 - 0.91 Habitatc 0 0.05 0.00 - 0.10 Globald 3 0.39 0.01 - 1.00 a Human model included distance to road and distance to human use area. b Old-growth model included a dummy variable for old-growth forest and distance to old-growth edge. c Habitat model included old-growth, bare ground, mixed hardwood, prairie, and a dummy variable for second-growth. d Global model included distance to human use area, distance to road, distance to old- growth edge, and all of the habitat variables.
FIGURES
Figure 1. Location of the study area within the southern portion of Redwood National and State Parks, Humboldt County, California.
35
36
Figure 2. Routes surveyed during area searches to locate breeding Common Ravens. Despite surveys in forest interior, ravens were only detected along roads and forest edges.
37
Figure 3. Fixed-kernel density estimates of home range (95% kernel) with choice of the plug-in method for smoothing parameter of eight breeding Common Ravens in Redwood National and State Parks, California in 2010. Each individual raven is identified by a different pattern. Core-use areas (50% kernel) are indicated within each home range by darker lines.
38 Bird K Bird H
Bird Y
Figure 4. Overlap in home range use between breeding Common Ravens in 2009 and 2010 in Redwood National and State Parks, California. The shading represents the amount of 3-dimensional overlap based on utilization distributions from each year.
Appendix A. Common Raven banding information and morphometric measurements, Redwood National and State Parks, California, 2009 and 2010.
Wing Culmen Tarsus Color Weight Date Band no. Trap Bait Ageb How agedc Sexd Howe sexed chord length length banda (g) (cm) (mm) (mm) 5/20/09 Y 1987-01001 Bow net Raw meat & Cheetos ASY I, P, MC, CP M CP, B - 43.5 47.2 66.4 6/1/09 H 1987-01002 Bow net Raw meat ASY I, P, MC, BP F BP, B 935 41 45 65 6/6/09 K 1987-01003 Bow net Raw meat ASY I, P, MC, BP F BP 891 40 48 64 3/10/10 W 1987-01004 Bow net Beef fat ASY I, P, MC F B 1055 - 56 73 3/17/10 J 1987-01005 Bow net Beef fat ASY I, P, MC F S 840 42 50 66 4/10/10 E 1987-01006 Bow net Beef fat ASY I, P, MC M S, B, V 1035 44 45 67 4/16/10 P 1987-01007 Bow net Beef fat & Cheetos ASY I, P, MC F S, V 970 - 47 - 4/30/10 S 1106-12051 Bow net Bread ASY I, P, MC F S, V 925 42 42 65 5/12/10 C 1987-01008 Bow net Carrion ASY I, P, MC F S, V 950 45 50 68 5/23/10 G 1987-01009 Bow net Cheeseburger & fries ASY I, P, MC F S, V 890 43 45 67 aColor bands were white with dark green lettering etched into each band. b After second year. c I = iris color, P = plumage, MC = mouth color. d M = male, F = female. e CP = cloacal protuberance, BP = brood patch, B = behavior, S = size, V = vocalization.
39
40 Appendix B. Fixed-kernel density estimates of home range (95% kernel) size (ha) for seven bandwidth selection techniques of eight Common Ravens in Redwood National and State Parks, 2010.
Bird LSCVa 0.4refb 0.6refb 0.8refb REFc HPId Hpi.diagd Y 13 97 146 188 222 75 82 H 80 127 156 183 208 152 163 K 66 71 90 110 128 87 98 W 217 282 388 485 586 142 381 E 80 293 414 506 589 322 353 P 16 92 131 162 188 101 113 C 64 97 121 146 170 107 118 G 155 105 131 161 191 141 152 Average 86.4 145.5 197.1 242.6 285.3 140.9 182.5 a Least squares cross validation. b Proportion of reference bandwidth. c Reference bandwidth. d Plug-in method.
41 Appendix C. Fixed-kernel density estimates core-use area (50% kernel) size (ha) Estimates for seven bandwidth selection techniques of eight Common Ravens in Redwood National and State Parks, 2010.
Bird LSCVa 0.4refb 0.6refb 0.8refb REFc HPId Hpi.diagd Y 1 6 11 17 23 5 5 H 17 27 36 42 47 38 37 K 12 13 16 19 22 16 17 W 45 55 73 92 114 70 72 E 14 37 56 76 99 43 46 P 2 11 15 19 24 13 14 C 12 20 27 32 38 24 25 G 37 28 33 37 42 35 36 Average 17.5 24.6 33.4 41.8 51.1 30.5 31.5 a Least squares cross validation. b Proportion of reference bandwidth. c Reference bandwidth. d Plug-in method.
42 Appendix D. Model selection results of standardized resource utilization functions (RUF) of eight Common Ravens in Redwood National and State Parks, California, 2010. Models are ranked according to the difference in Akaike’s Information Criterion (AIC) between the model and the best-fitting
model (ΔAIC). Number of parameters (k) and Akaike weight (wi) are presented for all models.
Bird Model k ΔAIC wi C Global 8 0.00 1.00 Old-growth 3 33.28 0.00 Human 3 181.19 0.00 Habitat 5 192.82 0.00 G Global 8 0.00 1.00 Habitat 5 108.57 0.00 Old-growth 3 175.88 0.00 Human 3 207.05 0.00 P Human 3 0.00 0.50 Old-growth 3 0.32 0.42 Habitat 5 3.79 0.07 Global 8 8.95 0.01 Y Old-growth 3 0.00 0.49 Human 3 0.38 0.41 Habitat 5 3.64 0.08 Global 8 6.34 0.02 H Human 3 0.00 0.56 Old-growth 3 1.14 0.32 Habitat 5 3.56 0.10 Global 8 6.28 0.02 K Human 3 0.00 0.61 Old-growth 3 1.52 0.29 Habitat 5 3.73 0.09 Global 8 7.90 0.01 E Global 7 0.00 1.00 Habitat 5 109.40 0.00 Old-growth 3 133.41 0.00 Human 2 138.33 0.00 W Old-growth 3 0.00 0.91 Global 8 3.50 0.06 Habitat 5 7.62 0.02 Human 3 8.09 0.01
43 Appendix E. Maximum likelihood estimates (MLE) of standardized resource utilization function (RUF) coefficients, standard errors (SE), and 95% lower and upper confidence intervals from the top model for eight Common Ravens in Redwood National and State Parks, California, 2010.
Bird Covariate MLE SE Lower CI Upper CI C Intercept 9.574 0.023 9.529 9.618 Dist. to road -0.331 0.008 -0.348 -0.315 Dist. to human use 0.040 0.013 0.014 0.066 Dist. to old gr. edge -1.934 0.017 -1.967 -1.900 Bare ground 0.257 0.008 0.242 0.272 Mixed hardwood 0.034 0.007 0.021 0.047 Old-growth 0.159 0.008 0.143 0.176 Prairie 0.054 0.012 0.032 0.077 G Intercept 14.741 0.028 14.687 4.796 Dist. to road -0.529 0.009 -0.546 -0.512 Dist. to human use 0.115 0.012 0.092 0.138 Dist. to old gr. edge -1.589 0.018 -1.623 -1.554 Bare ground 1.687 0.016 1.656 1.719 Mixed hardwood 0.254 0.013 0.228 0.280 Old-growth -0.053 0.012 -0.077 -0.029 Prairie 0.835 0.017 0.803 0.868 Y Intercept -0.252 0.033 -0.316 -0.188 Dist. to road -0.034 0.003 -0.040 -0.029 Dist. to human use -0.035 0.006 -0.048 -0.022 Old-growth -0.032 0.003 -0.039 -0.025 Dist. to old gr. edge -0.066 0.005 -0.076 -0.057 K Intercept 0.724 0.012 0.701 0.746 Dist. to road 0.021 0.002 0.018 0.024 Dist. to human use -0.009 0.002 -0.013 -0.005 Old-growth 0.002 0.001 0.001 0.004 Dist. to old gr. edge -0.002 0.001 -0.003 0.000 H Intercept 0.219 0.012 0.195 0.243 Dist. to road -0.021 0.001 -0.023 -0.019 Dist. to human use 0.008 0.001 0.005 0.010 Old-growth 0.008 0.000 0.007 0.009 Dist. to old gr. edge -0.006 0.001 -0.009 -0.003 E Intercept 17.547 0.025 17.499 17.596 Dist. to road -1.017 0.013 -1.043 -0.991 Dist. to old gr. edge 0.589 0.010 0.570 0.608 Bare ground 0.728 0.011 0.706 0.750 Mixed hardwood 0.727 0.012 0.704 0.750 Old-growth -0.431 0.012 -0.455 -0.407 Prairie 0.457 0.009 0.440 0.474 W Intercept 0.804 0.009 0.786 0.822 Old-growth -0.005 0.001 -0.007 -0.003 Dist. to old gr. edge -0.029 0.001 -0.031 -0.027 P Intercept 0.69 0.017 0.657 0.722 Dist. to road -0.021 0.003 -0.027 -0.016 Dist. to human use 0.008 0.002 0.005 0.012 Old-growth -0.009 0.001 -0.012 -0.006 Dist. to old gr. edge -0.006 0.002 -0.01 -0.002