SURVEY METHODOLOGY, ABUNDANCE, AND DEMOGRAPHY OF THE ENDANGERED HAWAIIAN HAWK: IS DELISTING WARRANTED?
by
John L. Klavitter
A thesis submitted in partial fulfillment of the requirements for the degree of
Master of Science
University of Washington
2000
Program Authorized to Offer Degree: College of Forest Resources
Master's Thesis
In presenting this thesis in partial fulfillment of the requirements for a Master's degree at the University of Washington, I agree that the library shall make its copies freely available for inspection. I further agree that extensive copying of this thesis is allowable only for scholarly purposes, consistent with "fair use" as prescribed in the U.S. Copyright Law. Any other reproduction for any purposes or by any means shall not be allowed without my written permission.
Signature: John Klavitter
Date: June 7, 2000
University of Washington Graduate School
This is to certify that I have examined this copy of a master's thesis by
John L. Klavitter
and have found that it is complete and satisfactory in all respects, and that any and all revisions by the final examining committee have been made.
Committee Members:
______Dr. John Marzluff
______Dr. Dave Manuwal
______Dr. John Skalski
Date: ______
University of Washington
Abstract
SURVEY METHODOLOGY, ABUNDANCE, AND DEMOGRAPHY OF THE ENDANGERED HAWAIIAN HAWK: IS DELISTING WARRANTED?
by John L. Klavitter
Chairperson of the Supervisory Committee: Associate Professor John M. Marzluff College of Forest Resources
To provide the U.S. Fish and Wildlife Service (USFWS) with updated information on the Hawaiian hawk (‘io, Buteo solitarius) for reconsideration of its current status
(endangered), I tested survey methodology, determined population size, distribution, habitat availability, survival, fecundity, and finite rate of increase (λ) of ‘io during
1998 and 1999 on the island of Hawai‘i. I estimated the total population at 1,457 (SE
= 176.3) hawks. Birds were distributed broadly around the island, but highest densities were found in mature native forest with a grass understory (0.0057 ‘io/ha). I calculated that 58.7% of the island (614,405 ha) is useable habitat for ‘io. Of the useable habitat, 31.8% (195,350 ha) is currently protected by State and Federal forests, parks, and refuges. Based on an average density of 0.0024 ± 0.0008 ‘io/ha in those areas, I calculated that protected areas currently support 469 ‘io (95% CI = 244-
901). I determined that the maximum number of ‘io found on the island prior to human occupation was 1,313 (95% CI = 857-2,013). In all habitats combined, first year and adult survival was 0.50 (SE = 0.0981) and 0.94 (SE = 0.0404), respectively.
In all habitats combined, fecundity was 0.23 (SE = 0.04) female young/breeding female. Overall finite rate of increase (λ) was 1.0324 (SE = 0.0428). Elasticity analyses showed adult survival as the most important parameter regulating finite
growth of this population. Based on current ‘io populations that are equal or larger in size to populations prior to human contact, high adult survival, the protection of substantial areas of habitat, a mean finite rate of increase ~ 1, resistance to avian diseases found on the island, no evidence of negative impacts of contaminants, and the birds ability to use human-altered landscapes and exotic prey, the population appears viable. However, because of the short duration of this study, the relatively low population size, the variance around my estimates, and environmental stochasticity, I feel delisting is not warranted. I feel downlisting would be appropriate for this species. Regardless of a change in listing, population size and especially adult survivorship should be routinely monitored.
TABLE OF CONTENTS
Page LIST OF FIGURES…………………………………………………………………..iii LIST OF TABLES……………………………………………………………………vi THESIS INTRODUCTION…………………………………………………………...1 CHAPTER 1: METHODS TO CORRECT FOR DENSITY INFLATION BIASES IN SURVEYS USING ATTRACTANT CALLS: A CASE STUDY OF HAWAIIAN HAWKS……………………………………………………………...4 Introduction………………………………………………………………………...4 Methods…………………………………………………………………………….5 Study Area……………………………………………………………………...5 Spot Map Estimates of Density…………………………………………………6 Point Count Estimates of Density………………………………………………7 Determining Hawk Response and Movement………………………………….9 Adjusting Point Count Estimates of Density………………………………….10 Results…………………………………………………………………………….13 Discussion………………………………………………………………………...14 Density of Hawaiian Hawks…………………………………………………..14 Adjusting Point Count Estimates of Density………………………………….15 CHAPTER 2: ABUNDANCE AND DEMOGRAPHY OF THE ENDANGERED HAWAIIAN HAWK: IS DELISTING WARRANTED?………………………...26 Introduction……………………………………………………………………….26 Methods…………………………………………………………………………...28 Study Area……………………...……………………………………………..28 Population Abundance and Distribution……………….………..…………….28 Estimating Survival……………………………………………………………33 Productivity……………………………………………………………………34 Estimating Finite Rate of Increase…………………………………………….35 Other Potentially Limiting Factors……………………………………………36 Results………………………….…………………………………………………37
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Population Abundance………..……………………………………………….37 Survival and Productivity……..………………………………………………39 Estimating Finite Rate of Increase…………………………………………….40 Other Potentially Limiting Factors……………………………………………41 Discussion………………………………………………………………………...41 Survey Approach……………...………………………………………………41 Abundance, Distribution, and Demography…………………………………..42 Other Potentially Limiting Factors……………………………………………45 MANAGEMENT IMPLICATIONS………………………………………………...46 LITERATURE CITED………………………………………………………………62 APPENDIX A: Survey Point Descriptions and Locations…………………………..76 APPENDIX B: ‘Io Survey Results…………………………………………………..90 APPENDIX C: Island Habitat Map………………………………………………….95 APPENDIX D: ‘Io Nest Locations…………………………………………………..97 APPENDIX E: Results From Environmental Contaminant Analyses……………...100
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LIST OF FIGURES
Number Page 1. Hawk pair locations (nest sites known and unknown), survey points, survey roads, and contour lines in the 4,085-ha Puu Waawaa study area. Estimated home ranges (dashed lines) are drawn around nest sites………………………...20 2. Hawk pair locations (nest sites known and unknown), an unpaired female location, survey points, survey roads, and contour lines in the 5,100-ha Kona Refuge study area. Estimated home ranges (dashed lines) are drawn around nest sites……………………………………………………………………….…21 3. Hawk movement (mean ± SE) in response to broadcasts of adult and fledgling Hawaiian hawk calls played various distances (min: 150 m, max: 2,008 m). Fifty tests were conducted on radio-tagged birds with 28 birds responding. No hawks responded beyond 1,000 m (n = 9). Numbers over points are number of tests performed in each distance category, and numbers under boxes are sample sizes of birds responding to calls. The letter "R" indicates that the distance was estimated by linear regression…………………………………..…22 4. Probability of hawk occurrence models. Labels above each ring are the distances from the survey point. Labels to the right of each ring are the probabilities associated with detecting a hawk within a distance category. (A) Model assumes equal probabilities of detecting birds within distance categories to 1,000 m. (B) Model assumes probability of detecting a hawk is a function of the area of each distance category. Distance category areas increase as you move away from the survey point……………………………....23 5. Probability density function for the secondary platform (upper curve) and primary platform (lower curve) (A). The Buckland and Turnock probability detection function resulting from integrating the primary and secondary platform probability density functions (B). The area under the curve is the corrected effective survey area, ν………………………………………………..24 6. Methods used to adjust point count densities (hawks/hectare) (mean ± SE) in Puu Waawaa study area (A) and the Kona Refuge study area (B). "Lack
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of response" - densities adjusted for lack of response. "No adjustment" - no adjustments to point count detection distances before analyzing with DISTANCE. "Attraction" - detection distances adjusted for movement. "Attraction & Lack of Response" - detection distances adjusted for movement and resultant density adjusted for lack of response. "View obstruction" - detection distances adjusted for movement stratifying by cover. "View obstruction and Lack of Response" - detection distances adjusted for movement stratified by cover and resultant density adjusted for lack of response. Horizontal reference lines represent "true" hawk densities determined by spot mapping (panel A: 0.0059, panel B: 0.0076)……………….25 7. Population estimates (mean ± 95% CI) obtained during four point count surveys as part of this study (Jan 98, June 98, Sept 98, and Jan 99), and an estimate by Hall et al. (1997) (Dec 93). Jan 98, June 98, and Dec 93 all followed the same survey routes and consisted of 399 points. June 98 and Sept 98 both followed the same survey route consisting of 677 points……………………………………………………………………………..57 8. Distribution and density of 'io on the island of Hawaii. The hatched area shows state sanctuaries/natural area reserves and national parks/wildlife refuges which overlap with areas with 'io density of 0.0007 or greater………....58 9. Island of Hawaii map showing the locations of 75 hawk pairs located during the 1998-99 field seasons (only the first nest found for each pair is shown). From the 75 total pairs, 50 active nests were located in 1998, and 62 in 1999…………………………………………………………………....59 10. Tree species and their frequency of use by hawks for nesting during 1998-99: ohia (Metrosideros polymorpha), kolea (Myrsine lanaiensis), koa (Acacia koa), lama (Diospyros sandwicensis), eucalyptus (Eucalyptus spp.), macadamia nut (Macadamia ternifolia), ironwood (Casuarina equisetifolia), mango (Mangifera indica), coconut (Cocos nucifera), Christmas berry (Schinus terebinthifolius)………..………….60 11. Hawk nesting success during the 1998-99 field seasons. Success is stratified into 5 habitats (native forest, native forest with grass, mixed
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native/exotic forest, exotic forest, and exurban) that correspond to habitat types in Fig. 1. "Native" combines native forest, native forest with grass, and mixed native/exotic forest when dominated by native components. "Exotic" include exotic forest, exurban, and mixed native/exotic forest that were dominated by exotic vegetation…………………………………………....61
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LIST OF TABLES
Number Page
1. Habitat scheme used to classify the surrounding area at each survey point.
Scheme was modified from Hall et al. (1997)……………………………………52
2. Current and historical habitat and their associated area (ha) on the island of
Hawaii. Current habitat types were estimated using Jacobi (1990) vegetation
map and satellite imagery (SPOT 1994)………………………………………….53
3. Summary of 'io density per habitat for January 1998 - January 1999 surveys…...54
4. June 1998 habitat specific density estimates ('io/ha) and the average rank of each
habitat (based on density) from our 4 surveys……………………………………55
5. Estimates of survival, fecundity, and finite rate of increase for birds in native,
mixed native/exotic, and all habitats between 1998 and 1999……………………56
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ACKNOWLEDGEMENTS
The majority of funding for this research project was provided by the U.S. Fish and Wildlife Service Pacific Islands Office with special thanks to Karen Rosa and
Robert Smith. Additional financial support was provided by the Geraldine R. Dodge
Foundation with special thanks to Mark Walters. Office space, logistical support, field accommodations, and encouragement were provided by The Hakalau National
Wildlife Refuge Kona Forest Unit (Dave Ledig, Donna Ball, Ken Clarkson, Glenn
Klingler, Dr. Jeff Burgett), the Hakalau National Wildlife Refuge (Dick Wass, Jack
Jeffrey), the U.S. Geological Survey Biological Research Division Kilauea Field
Station (Thane Pratt), and the State of Hawaii Department of Land and Natural
Resources Kamuela Office (Tod Lum).
I gratefully acknowledge my graduate committee for their contributions to my research and development as a wildlife biologist. I thank Dr. John Marzluff, committee chair, for his help setting up the project, his brilliant research ideas, advice on data analyses and writing, his encouragement, patience, motivation, friendship, great parties, and good humor. I thank Dr. John Skalski for a plethora of statistical assistance and writing advice, and Dr. Dave Manuwal for ideas and encouragement.
My fellow graduate students contributed to my research and enjoyment of the learning process. They provoked a lot of thought on conservation issues and provided a venue for much needed distraction. Thank you everyone!
Special thanks go out to several people for assistance with data analyses and computer software. Dr. Jeff Laake patiently provided advice and instruction on
vii
program DISTANCE and helped me with survey analyses. Rod Low and Phil
Hurvitz helped me with program ARCVIEW and assisted with GIS work. Kevin
Brink provided me with a substantial amount of statistical help. I thank Peter
Plimpton for writing computer code for a data simulation program.
I am particularly grateful to Mark Vekasy, a biologist who assisted me for the duration of the study. I greatly appreciated his creative ideas, work ethic, dedication, raptor expertise, ability to find nests, sharp eyes in the field, and friendship - many mahalos Bra!
I am appreciative of ‘Io Recovery Working Group for assistance and advice on my research proposal. Members and associates include Dr. Mike Kochert, Dr. Jim
Enderson, Dr. Beatrice Van Horne, Dr. Mike Morrison, Steve Martin, and Mick
Castillo.
Fieldwork occurred throughout the island of Hawaii. Without access to private,
State, and Federal lands to study ‘io, this research would not have been possible. I thank the individuals and staff associated with the Hakalau National Wildlife Refuge
Kona Forest Unit, the Hakalau National Wildlife Refuge, the State of Hawaii
Department of Land and Natural Resources Kamuela and Hilo Offices, University of
Hawaii at Hilo Agricultural Station, Hawaii Volcanoes National Park, Kamehameha
Schools Bishop Estate, Kau Agribusiness, MacFarms, Chalon International,
McCandless Ranch, Kealia Ranch, Kapapala Ranch, Panaewa Zoo, State of Hawaii
Kulani Correctional Facility, State of Hawaii Department of Water, and numerous private landowners that provided land access. Special thanks go out to Dave Ledig,
Dick Wass, Jack Jeffrey, Jon Giffin, Tod Lum, Darcy Hu, Tanya Rubenstein, Tonnie
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Casey, Perry Kealoha, Cynthia Salley, Keith Unger, Elizabeth Stack, Hillary Brown,
Dicky Short, Greg Nelson, Micheal Gomes, Tom and Maile Young, Joe Lowenhardt,
Sharon Vannatta, Tilton Sugi, Robby Hind, Gordon Cran, Albert Kawabata, and
Patrick at Kalopa State Park.
I am grateful for all the hard work and dedication from those who assisted me with fieldwork. This study would not have been possible without your help. I appreciated all the fun times in the field! Special thanks go out to Mark Vekasy, Matt Berry, Cam
Collins, Jay Osenkowski, Bart McDermond, Kenneth Jacobson, Nathaniel Carroll, and Greg Cunningham.
I am appreciative of all those individuals who assisted with ‘io surveys. I thank
Leona Laniawe, Donna Ball, Ken Clarkson, Michelle Reynolds, Lena Schnell, Buck
Pelkey, Kathleen Sherry, Kealii Bio, Jeremy Gooding, Jack Jeffrey, Jay Nelson, Eric
Tweed, Luanne Johnson, Reggie David, Peter Harrity, Tonnie Casey, Dr. Bethany
Woodworth, Lorna Young, Julie and Dan Lease, Pete Oboyski, Nick Shema, Tod
Lum, Bob Covington, Kirk at the Department of Fish and Wildlife, Miles Nakahara,
Wayne Taka, and Dan Goltz.
Others provided notable support and encouragement. I thank Dr. Carter Atkinson,
Dr. Thierry Work, and Dr. J.P. Dubey for analyzing ‘io plasma samples for malaria and Toxoplasma gondii. I thank Rick Warshauer, Linda Pratt, and Dr. Jim Jacobi for botanical assistance. Dr. Paul Banko, Dr. Thane Pratt, Gerald Lindsey, Ron Kerner, and Helene Love provided assistance, ideas, and encouragement. John Makaike,
Bonnie Nielson, and Loyd Yoshina provided information on the locations of several
‘io nests. Dr. Jim Jacobi, Dr. Jeff Fox, Mark Metevier, and Kealii Bio assisted with
ix
mapping. Dr. Dennis Lapointe and Dr. Lee Goff helped identify bird mites. I am particularly grateful to Peter Harrity for first turning me on to raptors, for help trapping birds and finding nests, and for his continual encouragement.
I would like to thank my family. I thank my parents, Nelson and Mona, and
David, Lisa, Li, Charles, Liann, John, and Sage for all their encouragement, love, and support. I am grateful.
Finally, and most of all, I thank my wife, Leona Laniawe, for all her love, support, patience, and encouragement. I could not have accomplished this undertaking without you!
x 1
THESIS INTRODUCTION
The ‘io or Hawaiian hawk (Buteo solitarius) is endemic to the island of Hawaii.
It one of only three raptors found in the Hawaiian Islands. The other two include the native pueo or short-eared owl (Asio flammeus) and the introduced barn owl (Tyto alba). Early ornithologists suggested this species was most closely related to the
Swainson’s hawk (Buteo swainsoni), colonizing from North America (Mayr 1943).
Recent genetic work postulates a different relation. DNA analyses indicate ‘io most likely diverged from the red-tailed hawk (Buteo jamaicencis) and are part of a clade that includes the short-tailed hawk (Buteo brachyurus), Swainson's hawk, and
Galapagos hawk (Buteo galapagoensis; R. Fleischer, P. Cordero, C. McIntosh, I.
Jones, A. Helbig unpublished data 1999).
‘Io exhibit many of the characteristics that are typical of other Buteos. ‘Io hunt prey most often from a perch. Their present day diet includes native and alien song birds, game birds, rats, mice, and insects, with the majority of their diet composed of rodents (Griffin 1985). Historically, ‘io foraged mainly on birds and insects, because rats and mice did not naturally occur on the islands (Griffin 1985). Two separate color phases are seen in this species, a light and dark morph. Birds of the same phase most often pair, but it is not unusual to see mixed pairs. When this occurs, their offspring are either light or dark, but not hybrids. Sexual dimorphism is more pronounced in ‘io compared to any other Buteo species with females weighing approximately 606 g and males 441 g (Griffin 1985).
2
The ‘io breeding season begins in mid March and extends through late September
(Griffin 1985). Pairs are typically monogamous and readily defend their nesting territory. ‘Io build large stick nests that are usually supported by one or more branches. Nests are placed near the trunks of large trees and ~ 11 m off the ground.
‘Io produce a single clutch per season, but will re-nest if the first nest fails early
(personal observation). They lay 1-2 eggs, although 2-egg clutches are rarely seen
(Griffin 1985). Incubation and the chick rearing period last 38 and 59-63 days, respectively, and parents will continue to feed fledged young almost until the next breeding season (Griffin 1985).
Although listed as an endangered species under the Endangered Species Act of
1973 (ESA, 16 U.S.C. 1531-1543, P.L. 93-205, as amended), ‘io are found island- wide and can be seen with regularity in many forested areas. This is in sharp contrast to most other endangered species in the Hawaiian Islands. Their persistence is most likely a result of their ability to use both native and exotic prey and habitat and their apparent resistance to avian diseases (Griffin 1985). As a result, their listing status is currently being reviewed by the U.S. Fish and Wildlife Service (USFWS).
In light of a potential change in listing status, the USFWS had a need for updated and additional information on the status of the population. Therefore, I initiated a study in January of 1998 to determine population abundance and viability in order to assess whether delisting was warranted. More specifically, I addressed the following questions:
(1) Do point count surveys using broadcasted adult and juvenile ‘io calls
reliable estimate density and abundance?
3
(2) What is the current size and distribution of the population?
(3) What are the survival rates for adults and first-year birds in native and
exotic dominated habitats?
(4) What are the fecundity rates (number of female young produced per
breeding female) in native, mixed native-exotic, and exotic habitats?
(5) What is the finite population growth rate, λ, in native, mixed native-exotic,
exotic, and all habitats combined?
(6) Are ‘io currently affected by avian malaria (Plasmodium relictum
capistranoae), avian pox (Poxivirus avium), Toxoplasma gondii, or
environmental contaminants?
My results are presented in 2 chapters. In chapter 1, I discuss point count survey methodology, density inflation that occurs when using broadcasted ‘io calls, and methods to correct for density inflation. In chapter 2, I estimate abundance, survival, and population growth, and discuss management implications from my results.
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CHAPTER 1: METHODS TO CORRECT FOR DENSITY INFLATION
BIASES IN SURVEYS USING ATTRACTANT CALLS: A CASE STUDY OF
HAWAIIAN HAWKS
INTRODUCTION
Surveying birds that are distributed in low densities across the landscape, are secretive, cryptic, and have low call rates is difficult (Fuller and Mosher 1981). Use of attractants such as playback recordings is sometimes necessary for game birds
(Marion et al. 1981, Spear et al. 1999), raptors (Mosher et al. 1990, Hall et al. 1997), and crows (Luginbuhl and Marzluff, submitted). Attractants can be used effectively and without bias when surveying birds for a relative index of abundance, however calculated densities are likely to be overestimated. Inflated densities result, because birds often move toward the observer, who then underestimates the detection distance. This violates one of the main assumptions of distance sampling, because it incorrectly suggests a smaller than actual area was surveyed (Buckland et al. 1993), and leads to inflated density estimates.
Researchers have long known that playbacks pose problems. They have responded by: (1) limiting the survey area (Luginbuhl and Marzluff, submitted), (2) multiplying density estimates by a constant to account for birds failing to respond to attractants (Marion et al. 1981), and (3) integrating probability density functions from two observers when one of the observers detects animals prior to movement
(Buckland and Turnock 1992). The latter approach is the most rigorous but requires two surveyors, one of which must be able to gather unbiased observations. Buckland
5 and Turnock (1992) accomplished this using a helicopter, which was appropriate for the Dall's porpoises (Ortalis vetula mccalli) that they studied, but difficult to apply to birds.
Routine use of radio-telemetry and powerful desktop computers increases the options available to detect and correct sampling bias. Here I use telemetry to determine density on two study areas and quantify movement of Hawaiian hawks to broadcasts during surveys. Standard database computer programs are then developed to correct surveys for a variety of biases and simulate repeated surveys to estimate variation in density. My objective is to compare adjusted densities to true densities to determine the most appropriate method to simply and conservatively estimate density.
Conservative and accurate estimates are needed in my case, because the Hawaiian hawk is endangered and currently proposed for delisting.
METHODS
Study Area
I studied hawks at the State of Hawai‘i Puu Waawaa Sanctuary (Puu Waawaa, Fig.
1) and the Kona Forest Unit of the Hakalau National Wildlife Refuge (Kona Refuge,
Fig. 2) on the island of Hawai‘i. Puu Waawaa, located on the west side of the island and on the northwest slopes of the dormant Hualalai volcano, ranges from 610-1,850 m in elevation and consists of a mixture of dry and mesic native forest dominated by an alien grass understory. The Kona Refuge, located on the southwest side of the island and the southwest slope of the dormant Mauna Loa volcano, ranges from 300-
1,800 m in elevation. Vegetation consists of a mixture of wet and mesic native forest
6 with some areas dominated by an alien grass understory and other areas dominated by native understory.
Spot Map Estimates of Density
I marked and identified all pairs and resident adults/subadults at Puu Waawaa
(Fig. 1) and the Kona Refuge (Fig. 2) between March 1998 and April 1999. I defined pairs and resident birds as those that nested in or defended a unique territory, or could be found consistently in the same general location in the study area during the study period. The U.S. Fish & Wildlife Service (USFWS) had identified the majority of the pairs at the Kona Refuge previously through ongoing monitoring studies since 1994
(U.S. Fish And Wildlife Service, unpublished data). I captured and banded birds with a unique combination of color bands. Backpack radio transmitters (Buehler et al.
1995, Vekasy et al. 1996) were also applied to at least one member of the pair (n =
14). I made a minimum of 20 separate visits and spent a minimum of 250 observer hours at each site to trap and identify birds. Broadcasts of Hawaiian hawk calls
(Radio Shack Musical Powerhorn (cat. no. 32-2037) rated for 90-dB ± 6-dB sound level at 3 m) were used extensively throughout the areas to help identify birds, and to ensure that no birds were missed (Falls 1981).
After all birds were marked or identified, I checked historical sites and used telemetry to find their nests (Puu Waawaa, n = 9; Kona Refuge, n = 9). When a nest was not found for a pair, I used the center of its home range to estimate its nest site
(Puu Waawaa, n = 2 pairs; Kona Refuge, n = 10 pairs, n = 1 unpaired female).
Griffin (1985) conducted Hawaiian hawk home range studies on the island during the
7 early 1980s. I used his estimate to assign a 1,193 m radius home range (447 ha) around each nest. I used the perimeter formed by the outer edge of the circular home ranges to define the Puu Waawaa (4,085 ha, Fig.1) and Kona Refuge (5,100 ha, Fig.
2) study areas. Density (hawks/ha) was calculated by dividing the total number of birds identified by the total amount of area. GPS coordinates were taken at each nest site and used to determine the nearest neighbor nest distance (mean ± SE, Sergio and
Boto 1999, Watson and Razafindramanana 1999). Distances where measured in program ARCVIEW (Environmental Systems Research Institute 1998). Nearest neighbor nest distances included pairs which built and repaired nests in 1998 and
1999. If a pair built more than one nest, the location of its initial nest was used.
When a nest was not found for a pair, I used the center of its home range to estimate its nest site.
Point Count Estimates of Density
I conducted point count surveys (Ramsey and Scott 1979, 1981; Buckland et al.
1993) using playbacks (Johnson et al. 1981, Fuller and Mosher 1987, Mosher et al.
1990, Hall et al. 1997) at Puu Waawaa (10 points, Fig. 1) and the Kona Refuge (12 points, Fig. 2) between January 1998 and January 1999 to estimate density. I chose the initial survey point by random draw. All subsequent survey points were spaced at
1.6 km intervals from this starting point (Anderson et al. 1976, Scott et al. 1981).
Points were located on dirt roads distributed throughout the study areas. Because of the difficult terrain and thick vegetation on the island, use of roads was necessary. I
8 felt the their use did not seriously violate assumptions of the point count method
(Andersen et al. 1985; Hall et al. 1997; Fuller and Mosher 1981, 1987).
Each point was surveyed for 10 min using playback recordings of adult and fledgling Hawaiian hawks for two, 1-min periods during the first and eighth minutes.
Prior to each day of surveying, all observers were calibrated for estimating distance using laser range finders, tape measures, and automobile odometers. Surveys were conducted between 0900–1700 H with winds ≤ Beaufort 3 (13-19 km/hr), on days without fog, steady drizzle, or prolonged rain. At each point, I recorded whether a detection was made, the distance at which the detection was first made, type of detection (audio or visual), and surveyor's percentage of view obstructed. View obstructed was any vegetation, landscape, or man-made structure that blocked a portion of the observer's survey field. Four separate surveys took place at Puu
Waawaa for a total of 40 points, while two separate surveys took place at the Kona
Refuge totaling 24 points. Point count data were analyzed by program DISTANCE to estimate density (version 3.5, 5; Thomas et al. 1998; Laake et al. 1993). Because habitats were similar, I pooled the detections from both sites and used a global detection function for a more precise estimate of effective area (Fancy 1997). I allowed DISTANCE to select the best density estimation model using minimum
Akaike Information Criterion values (AIC, Akaike 1973, Hall et al. 1997, Buckland et al. 1993). I right-truncated the largest 3 percent of the distances to facilitate model fitting (Buckland et al. 1993).
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Determining Hawk Response and Movement
I tested hawk response and movement to playbacks in a variety of habitats throughout the island between February and December 1999. I did this by locating a perched or soaring hawk (20 radio-tagged, 4 color-marked, 26 unmarked). One observer then watched the hawk from a concealed location and another observer moved away 150-2,008 m to perform a 10-min point count as described above (Hall et al. 1997). The surveyor recorded the percentage of their view obstructed by vegetation or other features, whether they detected the bird (audio or visual), distance at which the detection was first occurred (verified by laser range finder), and whether the bird had responded to the playback. The observer near the hawk ensured that bird stayed in relatively the same location until the test began and used GPS to measure the actual distance from the bird to the surveyor at the start and end of the point count. Most individuals were only tested once (45 of 50). When multiple testing occurred on an individual bird, I waited ≥ 3 mo. between tests.
Adjusting Point Count Estimates of Density
I adjusted uncorrected point count densities for lack of response following Marion et al. (1981). This method corrects for all birds not counted at the point, one of the assumptions of the point count method. Since it was not practical to test responses of a large number of birds at 0 m, I included all birds tested within 400 m. I determined that 19 of 26 birds (73%) responded to playbacks if they were within 400 m of the surveyor. Therefore I multiplied my density estimate(s) by
10
æ 26 ö p ç ÷ = 1.37 . è 19 ø
To adjust point counts only for hawk attraction to playbacks I grouped detection distances into the following categories: 0-200, 201-400, 401-600, 601-800, 801-
1,000, > 1,000 m. The mean distance moved prior to detection was calculated for each group (Fig. 3A). For each detection distance recorded during my point counts, I randomly added one of my 5 average movement distances (64, 85, 350, 337, 874 m) to it. I randomly added a movement distance to each detection distance, because I assumed that hawks were equally likely to be found in any distance category 0-1,000 m from the observer (Fig. 4A). Hawks only moved toward the surveyor if they were
< 1,000 m away, so distances were not added to any observation ≥ 1,000 m. I also investigated a model that assumed that hawks would be found in greater proportion as one moved away from the observer because of the increasing amount of area represented in each distance category (Fig. 4B). This model produced extreme underestimates of density and therefore was discarded from subsequent consideration.
I wrote computer code to instruct program ACCESS (Microsoft 1997) to perform the distance corrections (copy of code available from Klavitter). After all distances were corrected for a survey, I re-analyzed the point counts with DISTANCE and stored the outputs in a computer spreadsheet. I repeated the process of correcting the survey data and re-analyzing with DISTANCE 100 times. The adjusted density and variance was the average of the 100 simulations.
I adjusted for attraction and lack of response by multiplying the density estimate obtained from the attraction method by 1.37 following Marion et al. (1981) and the methods described above.
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By observation, I determined that as the proportion of the observer's view obstructed by vegetation, landscape, or other structure increased, the movement that occurred before hawks were detected also increased. I calculated the mean movement by hawks for each of the five distance groupings at points with < 40% of the view obstructed and ≥ 40% of the view obstructed (Fig. 3). As with the attraction method, the mean distance moved prior to detection was calculated for each of the 5 distance groupings (Fig. 3). I did not test any birds between 801-1,000 m with < 40% view obstructed, so I used linear regression to estimate a mean response distance for this distance category. When survey detections occurred with < 40% view obstructed, I randomly added 64, 60, 283, 313, or 422 m to the detection distance
(Fig. 3). When survey detections occurred with ≥ 40% view obstructed, I randomly added 82, 144, 397, 511, or 874 m to the detection distance (Fig. 3). As described above, I corrected distances using ACCESS, re-analyzed the point counts with
DISTANCE, and repeated the process of correcting the survey data and re-analyzing with DISTANCE 100 times. The adjusted density and variance were the average of the 100 simulations.
After adjusting my data for obstruction, I also multiplied my density estimate by
1.37 to account for unresponsive birds (Marion et al. 1981). This allowed us to correct density for the combination of obstruction, attraction, and lack of response.
Buckland and Turnock (1992) developed field and analysis methodology for estimates robust to departure from the assumptions that animals do not move in response to the observer before detection and that all animals 0 m from the point, g0,
12 are detected. I used my movement test data to correct using Buckland and Turnock methods as follows. Let
ns = all birds tested and their actual distances to the observer as measured without error using GPS. nps = the birds detected by the surveyor and their actual distance prior to movement.
I used DISTANCE to analyze nps and ns as unique surveys, resulting in the probability density functions, fps(r) and fs(r) (Fig. 5).
ˆ The Buckland and Turnock bias-corrected density estimate, Dc , (animals/ha) is calculated as follows.
gp(r) = probability that an animal detected by the observer at distance r from the surveyor is subsequently detected by the surveyor.
n fˆ (r) gˆ(r) = ps ps = detection function for the surveyor. ˆ ns f s (r)
ˆ ν ν π w f p (r) = gp(r)/ p, with p = 2 ò rg p (r)dr = effective area (Fig 4); 0
k = the number of points occurring in a survey.
ν EDR = = effective detection radius π
∧ n p D c = = animals/ha (kπEDR 2 ) /10,000
13
RESULTS
Hawk density varied slightly between Puu Waawaa and Kona. I identified 24 hawks (12 pairs) at Puu Waawaa for a density of 0.0059 hawks/ha (Fig. 1). The mean nearest neighbor nest distance was 1,013.8 ± 70.7 m (range 250-1,578 m, n = 12). At the Kona Refuge, I identified 39 hawks (19 pairs, 1 unpaired female) for a density of
0.0076 hawks/ha (Fig.2). The mean nearest neighbor nest distance was 1,009.0 ±
90.8 m (range 699-1,596 m, n = 19). Mean nearest neighbor nest distance did not differ between sites (F1,29 = 0.002, P = 0.97).
Uncorrected densities estimated from point counts were significantly greater than those obtained by spot mapping (Fig. 6). At Puu Waawaa I detected 29 birds for a density of 0.0197 ± 0.0056 hawks/ha. Detection distances ranged between 61-1,361 m. At the Kona Refuge I detected 21 birds for a density of 0.0238 ± 0.0068 hawks/ha. Detection distances ranged between 38-1,009 m.
Twenty-eight of 50 birds responded and were detected by the surveyor during movement response tests. Perched birds failed to respond beyond 600 m, while soaring birds failed to respond beyond 1,000 m. Birds that responded either: (1) called from their location and did not move (n = 3), (2) flew toward the observer and called (n = 17), or (3) flew toward the observer silently (n = 8). The distance a bird was from the surveyor affected the amount of movement in response to the playback
(Fig. 3). Hawks moved further before detection in heavily obstructed versus more open points (Z = 2.59, P = 0.01; Fig. 3).
14
All adjustments except simply correcting for lack of response estimated density more accurately than did unadjusted point counts (Fig. 6). Adjusting for lack of response inflated already overestimated densities. The Buckland and Turnock method was the most conservative adjustment as it gave the lowest density estimate in both areas. None of the adjustment methods except simple lack of response produced significantly different density estimates (95% CIs around each estimate overlap considerably).
DISCUSSION
Density of Hawaiian Hawks
Density of hawks at Puu Waawaa and the Kona Refuge was extremely high. In fact, this endangered species was as dense as the common mainland Buteo, the red- tailed hawk (Buteo jamaicensis). Preston and Beane (1993) reviewed 16 studies on red-tailed hawks that reported densities ranging from 0.0004 in Ohio (Shelton 1971) to 0.0154 hawks/ha in California (Fitch et al. 1946). The reason Hawaiian hawks are so dense is likely because my study plots were dominated by mature native forest with high amounts of human-created edge habitat and extensive areas with alien grass understory. ‘Io apparently have benefited by this habitat change just as several other raptors have benefited from habitat modification elsewhere (Donazar et al. 1993,
Preston and Beane 1993, Eakle 1994, Eakle et al. 1996). This type of habitat appears to contain the highest densities of hawks across the island (Klavitter 2000), probably because of an abundance of nest sites and prey, and lack of human persecution.
Actual densities on my plots are likely higher than I report. My density estimates
15 from spot mapping only identified paired or resident adult/subadults. Non-territory- holding birds (floaters) that are secretive or move in and out of territories with regularity were not counted.
Adjusting Point Count Estimates of Density
Comparing methods to adjust density, simply accounting for attraction is the most appropriate for obtaining reliable density estimates when conducting point counts with playbacks for Hawaiian hawks. I chose this method, because it conservatively estimated true density within 1 SE at both sites and required the least amount of post survey manipulation of data. I feel that a method that is precise, yet conservatively estimates density is the most appropriate for nearly all species, especially those that are rare, threatened, or endangered.
Correcting for lack of response worked well in studies by Marion et al. (1981), but performed poorly for us. This may reflect the fact that in my studies I did not have measures of response directly at the survey point. I based lack of response on all birds tested ≤ 400 m, which most likely overestimated those that failed to respond or that the observer failed to detect at the point. It is implicit in the underlying theory of point count sampling that as one moves farther from the survey point, fewer detections will be made (Buckland et al. 1993), so I should not have detected all hawks to a distance of 400 m. By correcting for lack of response based on this distance, my adjustment overestimated density. Estimates of variance also increase with this method leading to lower precision. Marion et al. (1981) did not use the correction factor after calculating densities for birds using the point count method. It
16 was only used after estimating density of birds using a technique that estimated their effective survey area based on the maximum distance birds responded to taped calls.
It appears that no correction is typically needed to adjust for lack of response when using the point count method, because the number of birds missed directly at the point is most likely negligible.
Adjustment for obstructed view gave conservative estimates, but in both cases, true densities did not fall within 1 SE of the adjusted densities. With more testing, this method may be valid. Others have also noted that the effective area sampled will vary with such things as the density of the surrounding vegetation or the topography
(Howell 1951, Svensson 1977, Weber and Theberge 1977, McCracken 1994).
Applying a second correction for lack of response gave reliable estimates that were conservative and contained true densities within 1 SE of adjusted densities. This may have been somewhat fortuitous in my study, because as mentioned previously, I feel my measure of lack of response up to 400 m is not appropriate and leads to increased estimates of variance.
The Buckland and Turnock method gave the lowest density estimates and true densities did not fall within 1 SE of the estimated density. Although the method did not perform well in this case, I feel it has potential to be useful in wildlife surveys and warrants additional experimentation. The method probably performed poorly in this case because of small sample sizes of survey tests, especially at distances beyond 600 m. Burnham et al. (1980) recommended a minimum of 60-80 observations during point counts to effectively model a detection function, while Buckland et al. (1993) recommended a minimum of 40. I had 28 observations with most occurring between
17
200-400 m due to the majority of the tests being conducted in this range. The method may have performed better if the highest number of tests were conducted at 0-200 m, the next highest in 201-401 m, and so on to 2,008 m or to a distance at which surveyors can no longer detect animals.
The Buckland and Turnock method is interesting to consider further, because it focuses on the movement of the animals and not the survey distance. Estimating distance is one of the most difficult aspects to point count surveys. Although laser range finders have made estimation more precise, large amounts of time are usually spent training and calibrating surveyors for distance estimation (Kepler and Scott
1981, Ramsey and Scott 1981). A technique such as proposed by Buckland and
Turnock that provides precise density and abundance estimates without having to train observers to estimate survey distances is valuable. More time could be spent on identification of birds by sound, another difficult component of point count sampling.
Additionally, the method could be used to calculate density and abundance for survey indices such as Christmas bird counts.
Playbacks work well to increase detections during counts (Marion et al. 1981,
Mosher et al. 1990), but could act as another source of variation during surveys
(Fuller and Mosher 1981). They can also cause unnecessary disturbance to birds, especially during nesting (Glinski 1976). Playbacks should therefore be used if the variation they cause during surveys can be adjusted for with methods that I described or with other similar ones. Care should be taken with the timing and frequency in which playbacks are used. Birds may become habituated to calls with overuse and cease to respond during surveys, biasing results. Use of playbacks should be
18 minimized during incubation to avoid pulling birds off their nests and exposing eggs to weather extremes and predators (Grier and Richard 1987). Finally, responding to taped calls causes birds to expend extra energy, may distract them from foraging, and may expose birds to predators (Stalmaster 1983).
Because I had previously radio-tagged birds around the island to find nests and to determine survival as part of another study, the effort required to obtain the movement data was not substantial. It required relatively little effort to locate birds with telemetry and conduct a playback test. I suggest limiting birds to one test per 3- month interval to avoid excessive disturbance and possible habituation to the taped calls. Movement tests can also be performed on unmarked birds, saving capture time and effort, but more search time will be required time to locate them compared to radio-tagged birds.
My findings suggest movement during surveys can be corrected post hoc with several methods to give reliable, yet conservative estimates of density that can be used to calculate abundance. Future Hawaiian hawk surveys should continue to use playbacks during surveys to increase hawk detections. However, they should be corrected for attraction, so reliable and conservative density estimates are made. The method of correction can be improved by re-sampling detection distances prior to correction for each successive simulation and by increasing the number of correction simulations from 100 to 1,000 so that more robust variance estimates are produced.
Researchers interested in applying this technique to their study should customize the correction to their unique setting and attempt to validate their correction by
19 comparing calculated densities to areas of known density or by comparing results produced by several techniques (Fancy 1997).
20
#
#
# # # # # # # # # # # # # # #
Puu Waawaa # # % #
Study Area # #
# # # b # # # # # # #
# # # # # # # # # # b# # # # # #
# # 914 # % #
# # # #
#
# #
# # # b# # # # # # # # # b # # # # # # b # # # # # # 1219 # # # # # # # b# # # b b # # ##### # b % # # b# # # # # ###
1524 #
1828 b Survey point N # Dirt road # Pair - nest known 0 1 2 3 4 5 Kilometers % Pair - nest unknown Contour line (m)
Figure 1. Hawk pair locations (nest sites known and unknown), survey points, survey roads, and contour lines in the 4,085-ha Puu Waawaa study area. Estimated home ranges (dashed lines) are drawn around nest sites.
21
305 610 914 1219 1524 1828
Kona Refuge Study Area % # # #
#
# % # % # % # b # # # # # # # % # #
# # # # # # % # # # # # # # # # # # # # ## # # # # # % # # # ## # # # # # # # # # # # # # b # b # # # b# # # b # # # # # ## # ## # # # # # # # # b # # # # b # # # # # % # b # # # # b # #
# $ % # b # # # # ### # # # % # #
# b # # # b # # # #
b Survey point N # Di rt road # Pair - nest known % Pair - nest unknown 012345Kilometers $ Unpaired hawk Contour line (m)
Figure 2. Hawk pair locations (nest sites known and unknown), an unpaired female location, survey points, survey roads, and contour lines in the 5,100-ha Kona Refuge study area. Estimated home ranges (dashed lines) are drawn around nest sites.
1000 A. All B. < 40% View Obstructed C. > 40% View Obstructed 3 3
800 2 2
600 2 6 6 4 2 1 400 4 R 1
11 4 200 20 2 9 6 5 1 3 3 Distance moved prior to detection (m) 1 0 4 5 14 7 7
0 0 0 00 00 00 0 00 00 00 -4 -600 -4 -6 -20 -800 0 -2 1 1 -8 -10 0-20 1 0 -1 0 1 1 01 20 40 0 20 4 601-800 201-400 401-600 601 01 6 80 801-1000 8
Original distance (m)
Figure 3. Hawk movement (mean ± SE) in response to broadcasts of adult and fledgling Hawaiian hawk calls played various distances (min: 150 m, max: 2,008 m). Fifty tests were conducted on radio-tagged birds with 28 birds responding. No hawks responded beyond 1,000 m (n = 9). Numbers over points are number of tests performed in each distance category, and numbers under boxes are sample sizes of birds responding to calls. The letter "R" indicates that the distance was estimated by linear regression.
A. B. 1,000 m 1,000 m 800 m 800 m
600 m 600 m
400 m 400 m
200 m 200 m
0 #m 0# m 0.20 0.20 0.20 0.200.20 0.04 0.12 0.20 0.280.36 Survey point Survey point
Figure 4. Probability of hawk occurrence models. Labels above each ring are the distances from the survey point. Labels to the right of each ring are the probabilities associated with detecting a hawk within a distance category. (A) Model assumes equal probabilities of detecting birds within distance categories to 1,000 m. (B) Model assumes probability of detecting a hawk is a function of the area of each distance category. Distance category areas increase as you move away from the survey point.
1.0 A. Probability Density Functions B. Detection Function 0.0025
0.8 0.0020
0.6 0.0015
0.4 0.0010 Probability of of Detection Probability
Probability density function density Probability 0.2 0.0005
0.0000 0.0 0 200 400 600 800 1000 0 500 1000 1500 Detection Distance r (m) Detection Distance r (m)
Figure 5. Probability density function for the secondary platform (upper curve) and primary platform (lower curve) (A.). The Buckland and Turnock probability detection function resulting from integrating the primary and secondary platform probability density functions (B). The area under the curve is the corrected effective survey area, v.
25
0.045 A. Puu Waawaa B. Kona Refuge Area 0.040
0.035
0.030
0.025
0.020
0.015 Density (Hawks/ha) Density
0.010
0.005
0.000 n e k t e e se s n s n s n io tio nse o act p r sponse spon trac spon s e Turnoc e e Att f r d At of respo o n adjustme k w obstruction a k of r w obstruction No adjustment ie ck of responnd No c ck of r ie ack lac V a a la V L d L Lack of re n kla d a and ckland and Turnock and L u n Buc B tion ction ctio c a u ttr ttra A A w obstruction an ie View obstr V Method
Figure 6. Methods used to adjust point count densities (hawks/hectare) (mean ± SE) in Puu Waawaa study area (A) and the Kona Refuge study area (B). "Lack of response" - densities adjusted for lack of response. "No adjustment" - no adjustments to point count detection distances before analyzing with DISTANCE. "Attraction" - detection distances adjusted for movement. "Attraction & Lack of Response" - detection distances adjusted for movement and resultant density adjusted for lack of response. "View obstruction" - detection distances adjusted for movement stratifying by cover. "View obstruction and Lack of Response" - detection distances adjusted for movement stratified by cover and resultant density adjusted for lack of response. Horizontal reference lines represent "true" hawk densities determined by spot mapping (panel A: 0.0059, panel B: 0.0076).
26
CHAPTER 2: ABUNDANCE AND DEMOGRAPHY OF THE ENDANGERED
HAWAIIAN HAWK: IS DELISTING WARRANTED?
INTRODUCTION
Hawai‘i is the home to 349 endangered species and 14 threatened species, 282 of which are plants (U.S. Fish & Wildlife Service 2000). It has been called the endangered species capital of the world representing nearly one third of the 1,197 species listed in the U.S. (U.S. Fish & Wildlife Service 1999). Although many threatened and endangered species have been helped by the conservation activities of
Federal, State, and private organizations in the islands, the future seems uncertain for the majority of them. To date, there have been no delisting or downlisting of species in Hawai‘i, although 4 bird species in other Pacific islands have been removed from the Endangered Species List. They include the Tinian monarch (Monarcha takatsukasae), Palau ground-dove (Gallicolumba canifrons), Palau owl (Pyrrhoglaux podargina), and Palau fantail (Rhipidura lepida) whose populations declined dramatically during wartime activity in the early part of the 20th century, and have slowly recovered during peacetime (Noecker 1998, U.S. Fish and Wildlife Service
1999).
The Hawaiian hawk or ‘io (Buteo solitarius) is currently being considered for delisting (K. Rosa, U.S. Fish and Wildlife Service, personal communication). The ‘io was federally listed as an endangered species in 1967 (37 FR 4001, 11 March 1967) based on a distribution limited to the island of Hawai‘i, a low population size
27
(Oreinstein 1968, Berger 1981), perceived threats to its native forest habitat from agriculture, logging, and commercial development (U.S. Fish and Wildlife Service
1984), and the lack of information on the species (Griffin 1985). Additionally, raptors had been declining worldwide from contaminants such as DDT (Newton
1979), and it was not known what effects contaminants were having on the ‘io.
A recovery plan was written for the ‘io in 1984 (U.S. Fish and Wildlife Service
1984). The plan's prime objective is to "ensure a self-sustaining ‘io population in the range of 1,500-2,500 adult birds in the wild, as distributed in 1983, and maintained in stable, secure habitat". For the purposes of tracking the progress of recovery, it suggested using 2,000 ‘io as a target to reclassify to threatened status. No criteria were given for delisting.
Griffin (1985, 1989) estimated the population at 2,700 individuals in 1983. He based his estimate on distribution data collected between 1976 and 1983 (Scott et al.
1986) and by extrapolating his findings from a detailed breeding biology and home range study occurring on < 1% of the island's area (Griffin 1985, 1989; Hall et al.
1997). Based on Griffin's population estimate, the USFWS proposed downlisting the
‘io from endangered to threatened status (58 FR 41684, 4 August 1993). Because of public response of basing downlisting on 10-year-old data, USFWS funded an island- wide ‘io survey in December of 1993 (Morrison et al. 1994, Hall et al. 1997). Hall et al. (1997) found ‘io distributed throughout the island and calculated a total population estimate of 1,600 birds. They agreed with the recommendation to downlist, but suggested researchers collect long-term demographic data to better understand the status of the species. In 1994 the USFWS withdrew the proposal to downlist because
28 of lack of public support, the 1993 survey could not ascertain the population status with confidence, and several important factors remained unresolved such as total population size, breeding pair productivity, and fledgling survival (50 CFR Part 17,
U.S. Fish and Wildlife Service 1994).
I initiated this study to provide the USFWS with demographic information to assist in their assessment of status of the Hawaiian hawk. My objectives were to: 1)
Estimate population abundance by point count surveys and determine if the results were repeatable over several surveys. 2) Determine the amount of habitat on the island. 3) Determine survival of first year birds in native and exotic-dominated habitats. 4) Determine adult survival in native and exotic-dominated habitats. 5)
Determine fecundity in native, mixed native-exotic, and exotic habitats. 6) Determine finite rate of increase, λ, in native, mixed native-exotic, and exotic dominated habitats.
METHODS
Study Area
Studies took place on State, Federal, and private lands distributed widely throughout the island of Hawai‘i. Point counts and nest monitoring occurred between
10-2,150 m in elevation. Detailed descriptions of the study area can be found in
(Scott et al. 1986, Cuddihy and Stone 1990, Jacobi 1990, Klavitter and Marzluff submitted).
Population Abundance and Distribution
29
I conducted four, island-wide, road surveys using methods developed by (Hall et al. 1997) to estimate population density and abundance. Two pre-breeding surveys were done in January 1998 and 1999, a breeding survey in June 1998, and a post- breeding survey in September 1998. For the pre-breeding surveys, I followed exact survey routes and methods used by (Hall et al. 1997), with 399 survey points located a minimum of 0.8 km apart (App. A.1, A.2). For the breeding and post-breeding surveys, I expanded the survey routes, increased the number of survey points to 677, and increased the minimum distance between points to 1.6 km for greater coverage on the island and increased independence between sampling points.
I surveyed the population multiple times during the study to aid in refining survey techniques for this species and to see if repeated surveys could produce consistent results. I were interested in finding a survey period that avoided disturbance to incubating birds, had birds responding well to playbacks, and had good weather conditions.
The ‘io breeding season begins in late March and continues through early October.
Chicks begin hatching in May and begin fledging in July (Griffin et al. 1998).
Surveys occurring in January or June would measure the population after it experienced over-winter mortality and prior to young of the year entering the population, therefore conservatively estimating total population size. A September or
October survey would measure the population after young of the year entered the population and prior to significant mortality, producing a liberal population estimate.
I found hawks responded well to playbacks during pre-breeding and breeding
30 surveys, but dropped off during the post-breeding survey (Klavitter and Marzluff submitted).
Each point was surveyed for 10 min using playback recordings of adult and fledgling Hawaiian hawks for two, 1-min periods during the first and eighth minutes.
Prior to each day of surveying, all observers were calibrated for estimating distance using a Bushnell 400 laser range finder, tape measures, and automobile odometers.
Surveys were conducted between 0900–1700 H, with winds ≤ 24 km/hr, and with no precipitation or light rain. At each point, I recorded whether: a detection was made, the distance at which the detection was first made, type of detection (audio or visual), surveyors percentage of view obstructed, and the habitat surrounding each detection according to a modified habitat scheme (Table 1). This scheme modified Hall et al.'s
(1997) habitat classes by combining vegetation types 5 and 10, and adding two new classes: urban and lava.
Because the species was distributed in relatively low densities across the landscape, was secretive, and did not call frequently, use of playbacks during surveys was important for detection (Fuller and Mosher 1981, Johnson et al. 1981, Joy et al.
1994, Hall et al. 1997, Bosakowski and Smith 1998, McLeod and Andersen 1998).
Playbacks were effective in increasing detection, but they caused a positive movement bias, which resulted in inflated density estimates. I conducted playback tests on ‘io to understand their movement and adjusted survey movements to correct the bias (Klavitter and Marzluff submitted).
I analyzed point count data with program DISTANCE (Laake et al. 1993, Thomas et al. 1998). I used a global detection function and allowed the program to select the
31 best model using minimum Akaike Information Criterion values (AIC) (Akaike 1973,
Buckland et al. 1993, Hall et al. 1997). I right-truncated the largest 3 percent of the distances to facilitate model fitting (Buckland et al. 1993).
Densities were estimated for each habitat and combined for an island-wide population estimate. This necessitated a determination of the amount of area in each habitat on the island (Table 1, App. C.1). Jacobi (1990) mapped 495,453 ha of the
1,047,087 ha that compose the island of Hawai‘i. Most of the habitat mapped occurred between 500-2,500 m and was comprised of native vegetative communities.
Plant community boundaries were mapped on stereo-pairs of black-and-white aerial photographs taken by the U.S. Geological Survey (USGS) between 1976 and 1978
(GS-VEEC series) at the approximate scale of 1:40,000. The boundaries drawn on the aerial photographs were compiled onto scale-stable overlays on the 1: 24,000- scale orthophoto quadrangle sheets. All mapped areas were field-checked along transects located throughout the island of Hawai‘i (Scott et al. 1981) with a total of
7,863 sampling points. I converted the level 1 classes from Jacobi's map to the 13 habitat types in Table 1. I used satellite imagery (SPOT 1994) to visually map the remaining 551,634 ha of habitat on the island to complete my habitat map (App C.1).
I used 1,076 ‘io survey points, 75 ‘io nest sites, and my two years of intensive field experience to ground truth classifications.
Habitat specific density estimates from the June 1998 survey and my habitat map
(as described above) were used to map ‘io abundance and distribution on the island. I chose to use results from the June 1998 survey, because I felt it provided the most accurate, yet conservative estimates. The survey occurred before young of the year
32 were added to the population, had a greater number and increased independence between points compared to the January surveys, and occurred at a time when ‘io responded well to playbacks. Because surveys points in each habitat were distributed broadly around the island, I felt it was appropriate to map ‘io abundance and distribution based on the occurrence of that particular habitat.
Because of the difficulty in predicting future land use changes for property currently supporting ‘io which are zoned residential, commercial, and agricultural, I determined the amount of ‘io habitat protected by State forest and natural area reserves and Federal parks and refuges (protected lands). I assumed that protected lands that currently support ‘io would be unlikely to change greatly in the foreseeable future and would continue to support hawks. I used program ARCVIEW
(Environmental Systems Research Institute 1998) to calculate the area of all protected lands (324,071 ha). I then determined the overlap of the protected lands and the areas supporting a minimum density of 0.0007 ‘io/ha to calculate the amount 'io habitat currently protected on the island. I considered habitat with densities < 0.0007 ‘io/ha as poor habitat and did not include them in my measurement.
In addition to estimating the current population size, I wanted to estimate historical abundance prior to human contact. Early Polynesians were thought to have arrived on the Hawaiian Islands between 300-800 A.D. (Green 1971; Handy and Handy
1972; Kirch 1982, 1985). A historical abundance estimate would provide a baseline to evaluate current and future population estimates. I did this by assuming the island would have been composed of the following native habitat types: mature native forest, pioneer native forest, high elevation pioneer native forest, mamane-naio forest,
33 native grass, native shrub, high elevation native grass and shrubs, and lava. I assumed that areas on the island presently classified as native, would have been the same type of native habitat in the past. Next, I converted areas that currently contain human altered habitat to native habitats (Table 2). I multiplied my current habitat density estimates by the amount of area of each habitat (as I assumed it to occur to the past) to calculate historical abundance.
Estimating Survival
From January-April 1998, I trapped, banded, and radio-tagged adult male and female ‘io. I used bal-chatri traps (Berger 1959) with live black rats (Rattus rattus) in native- and exotic-dominated habitats. Birds were weighed, measured, and banded with a unique combination of color bands and a USFWS band. A backpack radio transmitter was attached using a break-away harness design modified from Buehler et al. (1995) and Vekasy et al. (1996). I added a medium-weight cotton thread "weak link" to the harness on the ventral surface of the bird that connected all four straps. I placed a small leather patch under the weak link that prevented ‘io from using their bill to sever the cotton thread. Radio transmitters (9 g for males, 13 g for females) were manufactured by Advanced Telemetry Systems (ATS) and weighed ≤ 3% of the birds body weight. Transmitters were rated to last ≥ 10 and 24 mo. for males and females, respectively, and included a mortality switch that slowed the pulse rate when no movement occurred for 14 hr. Birds were located with telemetry a minimum of once per month from the ground, except for a 3-mo period in the fall of 1998
34
(October-December). Helicopters were used on several occasions to track missing birds. I determined survival for a 1-yr period from April 1998-April 1999.
From June-September 1998 I banded and attached radio transmitters to nestling and recently fledged birds to determine survival for a 1-yr period. I determined survival from April 1998-April 1999 using simple binomial proportions (Zar 1996) and assuming 100 percent detection rates for radio tagged birds. Variance was calculated as
æ ˆ ö æ ˆ ö ç S ÷ ç M ÷ ç ÷ ⋅ ç ÷ è X ø è X ø Vaˆr()Sˆ = X where Sˆ = number birds surviving after 1 yr, where Mˆ = number of mortalities after
1 yr, and X = total number of birds (Sˆ + Mˆ ). I chose the April time period for the beginning of the survival period based on my 1998 egg laying date (mean ± SD) of 23
April ± 26.2 days. I attached radio transmitters between June and September to birds in the nest at 38-45 days of age or to birds 7-28 days after fledging. Griffin (1985) and Griffin et al. (1998) determined fledging to occur at 59-63 days. Birds were located with telemetry a minimum of once per month, except for a 3-mo period in the fall of 1998 (October-December).
Productivity
I monitored nests to determine success from March through September during
1998 and 1999. I checked historical nesting territories and followed radio-tagged birds to find active nests. I considered a nest active if it was constructed that year or
35 if new material (sticks and green foliage) was added to an old nest from a previous year. Once an active nest was found, it was checked a minimum of once every two weeks to determine when the female began incubating. To avoid disturbance and possible abandonment, nest trees were not climbed during the incubation period or the first 5 weeks of chick rearing. Minimum observations were made at nests during this time.
Nesting success was defined for pairs found during the early incubation phase
(Steenhof and Kochert 1982, Steenhof 1987). "Successful" pairs raised at least one offspring. "Failed" pairs were unsuccessful in fledgling at least one offspring.
Because this species typically lays one egg, I used simple binomial proportions (Zar
1996) to calculate success. Radio-tagged and known breeding-aged females that did not attempt to breed were recorded to determine the portion of the population not breeding in a given year. I determined fecundity as the number of female offspring produced per breeding-aged female per year. Variance was calculated as
fˆ ⋅ (1− fˆ ) Vaˆr()fˆ = n
where fˆ is an estimate of the average number of female offspring per breeding-aged female per year, and n = total number of females used to calculate fecundity.
Estimating Finite Rate of Increase
I used program RAMAS GIS (Akcakaya 1999) and Leslie matrices (Leslie 1945,
1948) to estimate the finite rate of increase, λ, the long-term stable age distribution
(SAD), and the average age class residence. I set up my stage matrix using 4 age
36 classes: 0-1, 2, 3, and 4+ yr birds. I assumed age of first reproduction was 3 yr based on plumage and banding records (n = 2, U.S. Fish and Wildlife Service unpublished data). I used my estimate of first year survival for 0-1 age class, and my adult survival for 2, 3, and 4+ aged birds. I did not model demographic or environmental stochasticity. I used elasticity analyses (Caswell 1989, 2000; de Kroon et al. 2000;
Heppell et al. 2000) to determine the relative contribution of each demographic parameter to λ. Elasticity values range between 0-1, with 1 being the most influential. Parameters with highest elasticity values were used to identify potential management targets (de Kroon et al. 2000, Saether and Bakke 2000, Wisdom et al.
2000). I used program MATHEMATICA (Wolfram Research 1999) and the Delta method (Seber 1973) to find the variance of λ given the variances of the survival and fecundity rates. I used one-tailed Z-tests and α = 0.05 to test: Ho: λ ≤ 1.
Other Potentially Limiting Factors
I collected ‘io eggs from nests 2-6 wk after nest failure to determine levels of environmental contaminants such as organochlorines and heavy metals. Eggs were weighed and measured, and contents were then extracted, stored in sterile glass containers, and frozen. Samples were shipped to the U.S. Geological Survey (USGS)
Patuxent Analytical Control Facility in Laurel, Maryland for analyses. Samples were scanned (detection limits: 0.01-0.758 ppm) for the following contaminants: alpha chlordane, cis-nonachlor, gamma chlordane, heptachlor epoxide, oxychlordane, trans-nonachlor, o,p'-DDD, o,p'-DDE, o,p'-DDT, p,p'-DDD, p,p'-DDE, p,p'-DDT, p,p' DDE, PCB-Total, Endrin, Dieldrin, Mirex, HCB, Alpha BHC, Beta BHC,
37
Toxaphene, Aluminum (Al), Arsenic (As), Boron (B), Barium (Ba), Berylium (Be),
Cadmium (Cd), Chromium (Cr), Copper (Cu), Iron (Fe), Mercury (Hg), Magnesium
(Mg), Manganese (Mn), Molybdenum (Mo), Nickel (Ni), Selenium (Se), Strontium
(Sr), Vanadium (V), and Zinc (Zn).
I obtained ‘io plasma samples from the USFWS to test for avian malaria
(Plasmodium relictum capistranoae) and Toxoplasma gondii, both known to cause mortality in other native Hawaiian forest birds (van Riper III et al. 1986; Atkinson et al. 1995a,b; Kuehler et al. 1996; Zahn and Rothstein 1999). Samples were sent to the
USGS Biological Research Division in Volcano, Hawaii to check for avian malaria, and samples were sent to the U.S. Department of Agriculture in Beltsville, Maryland to check for Toxoplasma gondii.
I conducted health screenings of all hawks that were captured to check for avian pox (Poxivirus avium) infections, since avian pox is known to cause mortality in other native Hawaiian forest birds (van Riper III et al. 1986; Atkinson et al. 1995a,b). I also checked birds and nests for ectoparasites. Nests were checked after nest failure or during the late chick phase.
RESULTS
Population Abundance
During the January 1998, June 1998, September 1998, and January 1999 surveys, I counted 78, 178, 144, and 72 ‘io respectively (App. B.1, B.2, B.3, B.4). Population estimates were similar among all surveys (Fig.7). Densities differed among habitats and between surveys (Table 3). I chose to statistically assess the June 1998 survey,
38 because it produced the most accurate population estimate. During the June 1998 survey densities differed significantly among habitats (Table 4). For all surveys combined, native forest with grass and orchards had the highest average density rank
(Table 4). Mamane-naio, urban, and lava had the lowest densities.
I found ‘io distributed widely throughout the island with densities ranging from
0.0001-0.0057 ‘io/ha (Fig. 8). Areas below 300 m on the west and southwest portions of the island were found to support few or no hawks. ‘Io were absent from areas above 2100 m. I calculated that 58.7% of the island (614,405 ha) is useable habitat
(supporting densities ≥ 0.0007 ‘io/ha) for hawks. The total amount of useable habitat that is protected amounted to 195,350 ha (32%, Fig. 8), with an average density of
0.0024 ± 0.0008 ‘io/ha. I calculated that protected lands support a total of 469 hawks
(95% CI = 244-901). Very few high density areas (0.0040-0.0057 ‘io/ha) are protected, while some of the moderate density (0.0015-0.0039 ‘io/ha) are. The high density areas consist of native forest with grass understory and fallow sugarcane habitats.
Combining all habitats, I calculated historical island abundance as 1,313 ‘io (95%
CI = 857-2,013). For mature native forest, pioneer native forest, native grass, and native shrub, I calculated 923 ± 256.3, 273 ± 119.1, 50 ± 14.9, and 68 ± 41.9 ‘io, respectively. I assumed all other habitats had zero birds based on the June 1998 density estimates. Historical (1,313 ± 286.1) and current ‘io abundance (1,457 ±
176.3) were similar.
39
Survival and Productivity
Survival rates for both first year birds and adults were high (Table 5). First year
2 survival was significantly greater in exotic forest than native forest (χ 1 = 7.72, P =
0.005; Table 5). Adult survival was slightly higher in exotic forest than native forest,
2 although the difference was not significant (χ 1 = 2.90, P = 0.09; Table 4).
Nest sites over the 2-yr study were distributed widely throughout the island (Fig.
9; App. D.1, D.2). I found 50 nests in 1998, 39 of which were found during early incubation and used to calculate success. I found 63 nests in 1999, 49 of which were found during early incubation and used to calculate success. The majority of nest sites were found in native ‘ohi‘a trees, but some exotic trees were also used (Fig. 10).
In all habitats combined, nesting success in 1998 and 1999 was 59% and 49%, respectively (Fig. 11). In 1998, success in native habitat (71%) was slightly higher
2 than success in exotic habitat (44%; χ 1 = 2.94, P = 0.09). In 1999, less difference in
2 nesting success occurred between native (56%) and exotic habitat (35%; χ 1 = 1.97, P
= 0.16).
In all successful nests, only 1 young fledged. Of the 113 nests monitored during the study, females laid 2 eggs on only two occasions. Combining all habitats, overall fecundity was 0.23 female young per adult female ± 0.04 (Table 5). I found no difference in fecundity between native (0.28) and mixed (0.17), native and exotic
(0.10), or mixed and exotic habitats (Table 4; Z = 1.27, P = 0.20; Z = 1.35, P = 0.18,
Z = 0.69, P = 0.49).
40
Estimating Finite Rate of Increase
I used survival and fecundity results to set up the following Leslie matrices:
æ ö æ ö ç 0 0 0 0.23÷ ç 0 0 0 0.28÷ ç0.50 0 0 0 ÷ ç0.27 0 0 0 ÷ (1) Overall ç ÷ (2) Native ç ÷ ç 0 0.94 0 0 ÷ ç 0 0.88 0 0 ÷ ç ÷ ç ÷ è 0 0 0.94 0.94ø è 0 0 0.88 0.88ø
æ ö æ ö ç 0 0 0 0.17÷ ç 0 0 0 0.10÷ ç0.82 0 0 0 ÷ ç0.82 0 0 0 ÷ (3) Mixed ç ÷ (4) Exotic ç ÷ . ç 0 0.94 0 0 ÷ ç 0 0.94 0 0 ÷ ç ÷ ç ÷ è 0 0 0.94 0.94ø è 0 0 0.94 0.94ø
Overall finite rate of increase is 1.0324 ± 0.0428 (Table 5). I failed to reject Ho: λ
≤ 1 (Z = 0.76, P = 0.22, 1 - β = 0.20). I found no difference in λ between native
(0.9486) and mixed (1.0448), native and exotic (1.0073), and mixed and exotic habitats (Table 4; Z = 1.02, P = 0.31, Z = 0.24, P = 0.81, Z = 0.15, P = 0.88). The long-term stable age distribution of the population is expected to be 15.6% in 0-1 yr class, 7.5% in 2 yr, 6.9% in 3 yr, and 70.0% of the population in the 4 yr and older class. The average time of residence in the 4+ age class is expected to be 16.7 yr.
Adult survival was the most important parameter regulating the population
(elasticity = 0.7179). First year survival and fecundity had elasticity values of only
0.0706. With fecundity and first year survival held constant, adult survival needs to exceed 0.91% for the finite rate of increase to remain stable (λ = 1) or to increase (λ >
ˆ 1). My estimated adult survival was not statistically different from 0.91 (Ho: S ≤
0.91, 1-tailed, α = 0.05, Z = 0.74, P = 0.23, 1- β = 0.19).
41
Other Potentially Limiting Factors
I found no evidence that environmental contaminants, avian pox, avian malaria, or Toxoplasma gondii are limiting this population. Eggs (n = 5) contained none or trace amounts of organochlorines, PCBs, or heavy metals (App. E.1, E.2). Plasma samples (n = 7) tested negative for malaria, and only 1 sample showed a positive result for Toxoplasma gondii (titer = 25). I found 1 bird with avian pox (n = 155). It had healed lesions on 2 digits of both the left and right tarsometatarsus, causing slight deformities in each. They did not appear to affect the birds perching ability.
I found low incidence of ectoparasites. I found 5 hawks (n = 155) with minor
Hippoboscidae infestations, but they did not appear to be adversely affecting the birds. I observed 4 nests and 1 chick infested with tropical fowl mites (Ornithonyssus bursa). When the chick was first observed in the nest (~ 28 days), its eyes were nearly swollen shut and it was extremely lethargic. Over the next 2 wk, the swelling decreased dramatically, and it was more energetic. It successfully fledged, although it was ~ 1 wk early. Fate after fledgling was unknown.
DISCUSSION
Survey Approach
Four lines of evidence suggest that the June 1998 survey best estimates ‘io densities per habitat and produced the most accurate population estimate. (1) The survey had more total survey points and distance between points compared to the
January surveys. (2) The survey occurred at a time when the weather was consistently reliable. (3) Response to playbacks was high in June, because most pairs
42 had young chicks in the nest. (4) Population estimates are conservative, because young of the year have not yet been added to the population. My results were similar to several other studies. Fuller and Mosher (1981) performed playblack tests on
Cooper's hawks (Accipiter cooperii) and red-shouldered hawks (Buteo lineatus) and found birds most responsive during the period from arrival to their nest area until egg laying, less responsive during incubation, and moderately responsive during the fledgling period. Joy et al. (1994) found northern goshawk (Accipiter gentilis) response twice as high during the nestling period as compared to the fledgling period.
Despite the merits of the June survey and the resources required to complete it (16 people, 16 days), it was rather imprecise. Confidence intervals were large (95% CI =
1149-1847) but similar to previous efforts (Hall et al. 1997). I suggest that precision could be increased in future surveys by reallocating survey effort from areas where hawks are not known to occur (lava, urban, and mamane-naio forest) to areas of high abundance (native forest with grass, orchards, fallow cane, mature native forest).
Abundance, Distribution, and Demography
‘Io are abundant throughout their entire range and their population appears stable
(Figs. 7 and 8). My current population estimates are similar to those obtained in 1993
(Banko 1980, Scott et al. 1986, Hall et al. 1997), in 1983 (Griffin 1985), and similar to my historical estimate. I feel that the methods used by Griffin to estimate the population were positively biased, because he assumed hawks were distributed island-wide at the same high density as in his small study area (< 1% of the island's land area; Griffin 1985, 1989; Hall et al. 1997). My different density estimates
43 among habitat types show that his assumption of constant density was biased (Table
4).
‘Io are found in nearly all vegetative habitats (with some large tree component) on the island (Banko 1980, Scott et al. 1986, Hall et al. 1997). High elevation mamane- naio is rarely used, but lower elevation forests, grasslands, and plantations are used readily. Densities are highest in mature native forest with grass understory. This habitat has high amounts of edge which seems beneficial to ‘io, just as it has benefited other buteos (Santana and Temple 1988, Preston and Beane 1993, Zelenak and Rotella 1997). It most likely contains an abundance of game birds, rats, and other prey, numerous perch sites, and a surplus of nest sites. Logging, land clearing, and grazing in mature native forests have created this type of habitat. Thus ‘io can coexist with anthropogenic resource extraction, but careful management needs to occur to ensure that native tree recruitment occurs in these areas, or they may eventually change into grassland areas that support much lower densities of hawks. I found high densities of hawks in some orchard areas. Small orchards with a forest edge were most used. Large expanses of orchards without windrows or forest edge appear incompatible with ‘io. Extensive urban development could negatively impact the population.
‘Io are typical island/tropical birds, having low mortality and low reproduction
(Murray 1985, Faaborg 1986). ‘Io typically lay only 1 egg per season, lay a single clutch, and live approximately 20 yr. They are also similar to several forest birds studied in Hawai‘i such as the ‘akepa (Loxops coccineus), Hawai‘i creeper
(Oreomystis mana), ‘oma‘o (Myadestes obscurus), apapane (Himatione sanguinea),
44
‘i‘iwi (Vestiaria coccinea), ‘akiapola‘au (Hemignathus munroi), and palila (Loxioides bailleui) that show high survival ranging between 0.60-0.73 (Ralph and Fancy
1994a,b, 1995, 1996; Lindsey et al. 1995). The Galapagos hawk (Buteo galapagoensis) has similar rates of survival as ‘io (territorial: 0.90, non-territorial: ≤
0.50) and fecundity (0.34-0.45, Faaborg 1986). ‘Io adult survival and reproduction do not appear to have changed since Griffin's (1985) study. He reported a minimum of 91% survival for adults (n = 12) and 0.31-0.50 fledglings/breeding pair. My adult survival estimate of 0.94 in all habitats combined was > 0.91 (survival rate needed to sustain the population), indicating the population is most likely stable and possibly slightly increasing. Although not significant in adults, I was surprised at finding lower rates of survival in native forest compared to exotic. For adults, this finding was probably due to low sample sizes.
Elasticity analyses showed that adult survivorship was the most important demographic parameter contributing to population growth rate. This is consistent with published data on 49 bird species where the mean elasticity of adult survival rate was significantly larger than the mean elasticity of the fecundity rate, especially with long-lived species that matured late and laid few eggs (Saether and Bakke 2000).
Native and exotic forests have different effects on adults versus young. For adults, reproduction is high in native, and survival is high in both native and exotic. For juveniles, survival is low in native and high in exotic. The differences in fecundity and survival between native and exotic habitats seem to balance each other out, allowing stable populations in both native and exotic habitat (Table 4).
45
Most native forests occur at high elevation (> 1,200 m) while exotic forests generally occur below this elevation (Jacobi 1990). Juveniles may have difficulty finding enough easily caught prey in native forests. Easily caught prey, such as large insects, are generally more available at low elevations in the exotic forest. USFWS
(unpublished data) radio-tagged ‘io fledglings (n = 3) in high elevation native forest and monitored their movements for 1 yr. All birds moved out of the native forest and into low elevation (< 1,460 m) exotic forest, agricultural, and exurban areas. This movement could be in response to greater food availability at lower elevations that tend to be dominated by nonnative habitats. Black et al. (1997) assessed the
Hawaiian goose (Branta sandvicensis) reintroduction program and found a portion of the high elevation release sites unsuitable, indicating low elevation areas may be important for young of several species of Hawaiian birds.
Other Potentially Limiting Factors
Environmental contaminants, avian pox, avian malaria, and Toxoplasma gondii do not appear limiting to this population. My findings are consistent with those of
Griffin (1985). He found no evidence of malaria in 75 blood samples from 32 ‘io, and observed only 2 pox-like lesions on birds (n = 44). Griffin found none or trace amounts of contaminants in 3 eggs and 1 chick between 1980 and 1981.
Contaminants were also absent from 1 egg analyzed in 1969 (Berger 1981). Effects due to secondary rodenticide poisoning are believed to be low (Lindsey and Mosher
1994), but may warrant additional investigation (K. Clarkson, U.S. Fish and Wildlife
Service, personal communication).
46
MANAGEMENT IMPLICATIONS
When a species is listed as endangered or threatened under the ESA, the ultimate goal is to recover the species and remove it from the list, but determining when a species is deemed recovered can be difficult. This may be one of the reasons why so few species have been downlisted or delisted. The determination needs to be based on sound scientific criteria. Basing recovery solely on population levels is not sufficient (Kennedy 1997). In general, for recovery or delisting, evidence of population stability and projected ability to remain viable in the face of expected land use change is needed (Kennedy 1997). Evidence of population stability may include
(1) a population distributed throughout all or most of its historic range and (2) a stable finite population growth rate (λ = 1). Evidence of the projected ability to remain viable in the face of expected land use change may include (1) a species ability to adapt to alien habitat and prey, (2) a large population size, and (3) the protection of substantial portion of the species natural habitat. In the case of the recent delisting of the American peregrine falcon (Falco peregrinus anatum), Pagel et al. (1998) suggested using effective population size (Ne), finite rate of population change, and population viability as the important measures necessary to support a scientifically based decision. As mentioned previously, no delisting criteria were specified in the
Hawaiian hawk recovery plan, and limited criteria were given for downlisting. The plan stated that, "A target of 2,000 birds distributed as they were in 1983 will be used to reclassify the species from endangered to threatened".
47
Is downlisting or delisting warranted for the Hawaiian hawk? Results from my study are encouraging for this island endemic. ‘Io continue to be distributed widely around the island and are as abundant now as ever before. My current estimate of
1,457 hawks is equal to or higher than in pre-human times indicating the bird's ability to adapt and persist with habitat change and food resource changes. Adult survival is high and the population appears stable in all habitats combined (λ ~ 1). ‘Io have shown the ability to adapt to modified habitat and use exotic prey (Griffin 1985).
Contaminants and avian disease do not appear to be negatively affecting ‘io. Despite my estimate falling below the downlisting target of 2,000 birds (U.S. Fish and
Wildlife Service 1984), my data support downlisting this species, but not delisting because of the relatively small ‘io population size making it vulnerable to future environmental stochasticity (Spiller et al. 1998) and changes to the island. The recovery target was based on Griffins (1985) estimate of 1,500-2,500 ‘io. My estimate of hawks on the island prior to human contact (1,313) gives evidence that a recovery goal of 2,000 birds to downlist to threaten is unreasonable or potentially unobtainable on the island of Hawai‘i. Although Griffin used the best available information at the time, his estimate was based on limited data and unproven assumptions. He assumed ‘io saturated all forested areas and had similar home ranges (densities) to pairs he studied in low elevation forest. This assumption is untrue, because I have shown that densities vary among habitats on the island (Table
4).
Perhaps management activities (i.e. habitat modification - altering mature native forest to native forest with grass understory) could be initiated to increase the
48 population above 2,000. If such actions were taken, I feel serious consequences to other native communities and birds, especially endangered, could result. Over the last 4 yr, ‘io have been found to prey upon endangered Hawaiian Crows (Corvus
Hawaiiensis) (U.S. Fish and Wildlife Service unpublished data). Depredation may have occurred historically, but altered native forest (mature native forest with grass understory) has allowed ‘io densities to double (Table 4), likely leading to increased pressure on crows and other native passerines. ‘Io were not known to occur on the other Hawaiian Islands in recent times, but researchers have suggested the possibility of re-introducing ‘io to other islands where they were known based on sub-fossil records (Olson and James 1982, 1991, 1996). This action would create a second population and increase overall abundance. The idea is not well supported because of the potential negative effects that might be incurred by the other native forest birds on those islands (Molokai, Kauai).
Despite the apparently positive outlook for the ‘io having a stable population with current abundance similar to historical abundance, I have some concerns with basing a reclassification on only 2 yr of data. Others have expressed similar concerns.
Brook and Kikkawa (1998) suggested being cautious when using relatively short (5- year) periods of data collection to predict population stability, especially of endangered species on islands. Beissinger and Westphal (1998) recommended a conservative approach when using deterministic models (finite population growth models) to appraise the status of endangered species because of the variability of demographic estimates. Continued monitoring of ‘io through time is important to confirm the stability of the population.
49
Since ‘io are found only on the island of Hawaii, I am concerned about the possible future changes to the island. Future human population growth and commercial development will increase over time on the island. As I have shown, some human altered habitat can increase ‘io densities higher than those supported by native habitats, but strictly urban and large scale agriculture without forest edge and/or windrow are incompatible with ‘io. As of 1998, 143,135 people resided on the island, an estimate expected to increase by approximately 2,850 per year (U.S.
Bureau of the Census 1998). In 1998, 773 new family homes were built on the island
(Hawaii State Department of Business 1998). These figures show modest growth, but it is difficult to predict future growth. If growth and development continued to a point where all lands (except those protected by reserves, parks, and refuges) were converted to urban, I calculated 469 ‘io would still remain. Such a projection gives evidence that the population can persist into the foreseeable future, but may always be threatened with extinction.
Most islands are relatively small in terms of land area, resulting in species with naturally small population sizes. My calculation of ‘io abundance prior to human occupation serves as an example. Based on small population sizes and limited distributions, by definition nearly every island species could be considered as threatened under the ESA. One possible alternative for island species is for Federal agencies to adopt IUCN categories. IUCN designations have more, well-defined categories to classify species. Recovered and/or stable island species could be listed as vulnerable - not critically endangered or endangered but is facing a high risk of
50 extinction in the wild in the medium-term future, or listed as near threatened - close to qualifying for vulnerable (International Union for Conservation of Nature 1994).
Regardless of a change in listing status, I recommend continued monitoring of this species. I recommend focusing monitoring efforts on adult survival and island-wide surveys, since adult survival is the main component regulating this population and surveys allow monitoring abundance, distribution, and habitat. I recommend monitoring survival with a radio-tagging study at 5 yr intervals, tagging a minimum of 30 birds (probably 100 for sufficient statistical power) from various habitats around the island. To minimize the costs involved, continuous tracking is not needed.
Birds only need to be tracked at the end of the 1-yr period to confirm survival or mortality. Using color bands in place of radio-tags will not be adequate, because survival may be underestimated. I observed one adult female change territories and would have assumed the bird dead had it not been radio-tagged.
The current survey methods represent the best possible way to monitor abundance in the future. Because of the vast amount of effort and resources needed to perform these surveys in their current state, it would be difficult to improve upon them.
However, the survey technique produces rather wide confidence intervals around its estimate and currently only has the power to detect major changes in the population.
Assuming the same amount of variance around the June 1998 density estimate, the population would need to drop 48% to 700 ‘io (95% CI = 427-1147) to be able to detect a significant decrease in the population with 95% confidence. I recommend excluding poor habitats and sampling higher density areas to decrease variance.
Excluded habitats could be surveyed periodically (i.e. survey every third survey
51 period). Future surveys should be performed every 5 yr and vegetation changes tracked at survey points and on a landscape level using satellite imagery and GIS.
Although not the primary regulating parameter for this population, reproduction should be monitored. I recommend monitoring a minimum of 30 nests in a mixture of habitats dispersed around the island every 10 yr. If reproduction studies occurred simultaneously with survival studies, adult females could be tracked directly to their nests. Since fecundity is currently low, it may be one of the few parameters that can be enhanced by management.
Monitoring alone is not sufficient to ensure continued stability of the population. I recommend managing for ‘ohi‘a trees, public education programs, and protection of additional habitat. Land managers need to ensure long-term persistence of native
‘ohi‘a trees and their continued recruitment, because they are the principle tree species used for nesting. Invasive exotic vegetation and intensive grazing currently seem to limit ‘ohi‘a recruitment (Cuddihy and Stone 1990). Public education programs need to be continued and improved upon to protect habitat and nest trees, prevent harassment at nest sites purposeful shooting of birds. A large portion of ‘io habitat is currently protected, but few of the highest density areas fall within reserve, refuge, or park boundaries (Fig. 8). Incentives need to be implemented that encourage landowners to manage these lands for ‘io.
52
Table 1. Habitat scheme used to classify the surrounding area at each survey point. Scheme was modified from Hall et al. (1997).
Habitat Types Areaa Codeb Descriptionc Fallow sugarcane 17,413 1 Sugar cane fields (fallow or active) with exotic and/or native trees or shrubs at edges as forest stands, gultches, or windrows. Exotic trees, shrubs, 73,307 2 Short or tall exotic trees with exotic shrubs, and sometimes grasses exotic grasses. Orchards 7,628 3 Macadamia nut, papaya, or other orchard with native and/or exotic trees or shrubs at edges. Grass dominated 77,444 4 Areas dominated by grass with few or none native and/or exotic trees; scattered homes. Shrub dominated 114,155 5,10 Native and/or exotic shrubs dominated landscape; lava often times present. Mature native forest 150,785 6 Native trees and native shrubs dominating the area. Native-exotic forest 58,301 7 Mixed exotic and native trees, sometimes with mixed exotic and native shrubs or grass. Exurban 29,288 8 Residential areas with scattered exotic and native vegetation. Pioneer native forest 166,152 9 Native tree and mixed exotic and native shrub vegetation on lava; a pioneer community. Mature native forest 63,337 11 Mature native forest with a grass dominated understory. with grass understory Mamane-naio forest 53,411 12 Mamane-naio vegetation, with grass and/or exotic shrub understory, or sometimes with scattered exotic trees. Urban 34,547 13 Highly concentrated residential areas with few or no trees. Lava 156,921 14 Areas dominated by lava with no trees and few or no shrubs or grasses. a Total area of each habitat on the island (ha). High elevation pioneer native forest (23,650 ha) and high elevation shrubs-grasses (20,709) are not shown, because habitats are outside the birds normal range. b Vegetation codes used by Hall et al. (1997). Corresponding codes are listed adjacent to our habitat types. Codes 5 and 10 were combined, and 13 and 14 were added. c Scientific names of plants listed: sugar cane (Saccharum officinarum), macadamia nut (Macadamia ternifolia), papaya (Carica papaya), Mamane (Sophora chrysophylla), and naio (Myoporum sandwicensis).
53
Table 2. Current and historical habitat and their associated area (ha) on the island of Hawaii. Current habitat types were estimated using Jacobi (1990) vegetation map and satellite imagery (SPOT 1994).
Current Historical Current Habitat Types Area (ha) Historical Habitat Types Area (ha) Fallow sugarcane 17,413 - - Exotic trees, shrubs, 73,307 - - grasses Orchards 7,628 - - Grass dominated 77,444 Native grassa 38,722 Shrub dominated 114,155 Native shrubb 114,155 Mature native forest 150,785 Mature native forestc 343,764 Native-exotic forest 58,301 - - Exurban 29,288 - - Pioneer native forest 166,152 Pioneer native forestd 295,755 Mature native forest 63,337 - - with grass understory Mamane-naio forest 53,411 Mamane-naio forest* 53,411 Urban 34,547 - - Lava 156,921 Lava* 156,921 High elevation pioneer 23,650 High elevation pioneer 23,650 native forest native forest* High elevation shrubs 20,709 High elevation pioneer 20,709 and grasses native forest* a We assumed half of current grass areas would have been native grass historically. b We assumed that native shrubs covered the same amount of area historically as native and exotic shrubs currently cover. c We assumed historical areas of mature native forest were the same as current estimates. We increased the amount of this habitat by assuming the following current habitat would have been mature native forest: 100% of mature native forest with grass understory, 50% of orchards, 50% of urban, 50% of sugarcane, 50% of mixed native-exotic, and 25% of grass dominated areas. d We assumed historical areas of pioneer native forest were the same as current estimates. We increased the amount of this habitat by assuming the following current habitat would have been mature native forest: 50% of orchards, 50% of urban, 50% of sugarcane, 50% of mixed native-exotics, and 25% of grass dominated. * Historical habitat areas assumed to be similar to current estimates of habitat areas.
54
Table 3. Summary of 'io density per habitat for January 1998 - January 1999 surveys.
Janurary 1998 June 1998 September 1998 January 1999 ______Habitat Estimatea SE Estimatea SE Estimatea SE Estimatea SE Fallow 0.0024 0.0011 0.0040 0.0011 0.0038 0.0010 0.0010 0.0006 Sugarcane Exotic Trees, 0.0024 0.0011 0.0024 0.0010 0.0019 0.0008 0.0029 0.0010 Shrubs, Grasses Orchards 0.0035 0.0012 0.0028 0.0009 0.0038 0.0012 0.0022 0.0010
Grass 0.0029 0.0009 0.0013 0.0004 0.0017 0.0006 0.0022 0.0010 Dominated Shrub 0.0019 0.0009 0.0006 0.0004 0.0003 0.0003 0.0007 0.0007 Dominated Mature Native 0.0033 0.0011 0.0027 0.0007 0.0012 0.0006 0.0022 0.0009 Forest Native-Exotic 0.0015 0.0011 0.0015 0.0005 0.0025 0.0008 0.0015 0.0006 Forest Exurban 0.0004 0.0003 0.0006 0.0003 0.0017 0.0006 0.0005 0.0005
Pioneer Native 0.0008 0.0008 0.0009 0.0004 0.0014 0.0007 0.0004 0.0003 Forest Native Forest 0.0092 0.0040 0.0057 0.0012 0.0045 0.0012 0.0010 0.0010 With Grass Mamane-Naio ------Forest Urban ------
Lava ------a Density estimate is the number of hawks/ha.
55
Table 4. June 1998 habitat specific density estimates ('io/ha) and the average rank of each habitat (based on density) from our 4 surveys.
No Avg.
Habitat Estimate Differencea Rank
Native forest with grass 0.0057 1 2.25
Fallow sugarcane 0.0040 1,2 3.75
Orchards 0.0028 2,3 2.25
Mature native forest 0.0027 2,3 4.50
Exotic trees, shrubs, 0.0024 2,3,4 4.00 grasses
Native-exotic forest 0.0015 3,4,5 5.75
Grass dominated 0.0013 3,4,5 4.75
Pioneer native forest 0.0009 4,5 8.75
Shrub dominated 0.0006 5 8.50
Exurban 0.0006 5 8.50
Mamane-naio Forest - - 11.00
Urban - - 11.00
Lava - - 11.00 a Habitats with the same numbers indicate no difference in density estimates (Z-test, α=0.10).
56
Table 5. Estimates of survival, fecundity, and finite rate of increase for birds in native, mixed native/exotic, and all habitats between 1998 and 1999.
0-1 yr 1+ yr 4+ yr
Surv- Surv- Fecu-
Habitata ivalb nc SE ivald ne SE ndityf ng SE λh SE
Overall 0.50 26 0.0981 0.94 34 0.0404 0.23 102 (73) 0.0417 1.0324 0.0428
Native 0.27 15 0.1146 0.88 17 0.0781 0.28 59 (44) 0.0585 0.9486 0.0788
Mixed 0.82 11 0.1163 0.94 17 0.0404 0.17 43 (28) 0.0566 1.0448 0.0483
Exotic 0.82 11 0.1163 0.94 17 0.0404 0.10 16 (10) 0.0733 1.0073 0.0584 a Overall habitat is a combination of native and mixed. Native refers to habits dominated by native vegetation; mixed: those habitats having a mix of native and exotic vegetation with the majority of nests found in native trees; exotic: those habitats dominated by exotic vegetation and nest were placed in nonnative trees. b Survival estimate for 0 - 1 yr. where 0 is avg. laying date (April) and 1 is April of the next year. Data from mixed native/exotic was used for exotic estimate. c The number of individuals used to estimate survival for 0 - 1 yr. birds in each habitat. d1+ survival is the survival for all birds > 1 yr. age. We used our estimate of adult survivorship (birds ≥ 4 yr.) for all birds in this category. No deaths occurred for birds in mixed habitat, so we used the estimate for overall survival. e The number of individuals used to estimate survival for 1+ birds in each habitat. f Fecundity is the avg. number of female offspring produced per individual breeding aged female per year. We considered all breeding aged females regardless of whether or not they attempted to breed in a given year. g The total number of birds used to estimate fecundity in each habitat. Numbers in parentheses represent the number of unique pairs. h λ is the finite rate of increase from one year to the next. Age at for first reproduction was estimated as age 4.
57
2600 2400 2200
2000 1800 1600 1400 1200 1000
Number of Hawks of Number 800 600 400 200
0 8 9 93 ec Jan 99 Jan 98 June 98 Sept D Survey
Figure 7. Population estimates (mean ± 95% CI) obtained during four point count surveys as part of this study (Jan 98, June 98, Sept 98, and Jan 99), and an estimate by Hall et al. (1997) (Dec 93). Jan 98, June 98, and Dec 93 all followed the same survey routes and consisted of 399 points. June 98 and Sept 98 both followed the same survey route consisting of 677 points.
58
Reserves/refuges N Densities (hawks/ha) 0.0000 0.0001-0.0006 0.0007-0.0014 0.0015-0.0039 0 9 18 27 36 Kilometers 0.0040-0.0057
Figure 8. Distribution and density of ‘io on the island of Hawaii. The hatched area shows state sanctuaries/natural area reserves and national parks/wildlife refuges which overlap with areas with ‘io density of 0.0007 or greater.
59
% % %% % % % % % % % % % % %
% % % %% %
% %% % % %%%% % % % % % %%
% %
%
% % % %
% % % % % % % % % % % %% %% % % % % %%% %% %
% % % %
%
N ( Hawk nest Coastline Major roads 0 1020304050Kilometers 305 m Contour lines
Figure 9. Island of Hawaii map showing the locations of 75 hawk pairs located during the 1998-99 field seasons (only the first nest found for each pair is shown). From the 75 total pairs, 50 active nests were located in 1998, and 62 in 1999.
60
1.0
1998 42 1999 0.8 50
0.6
0.4 Nest tree use (%) use tree Nest
0.2
5 3 2 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0.0 0 t t u ry lea tus er Ohia o Koa ama K L s b alyp onwood Mango amia nu Ir Cocon Euc d ristma Maca Ch
Tree species
Figure 10. Tree species and their frequency of use by hawks for nesting during 1998-99: ohia (Metrosideros polymorpha), kolea (Myrsine lanaiensis), koa (Acacia koa), lama (Diospyros sandwicensis), eucalyptus (Eucalyptus spp.), macadamia nut (Macadamia ternifolia), ironwood (Casuarina equisetifolia), mango (Mangifera indica), coconut (Cocos nucifera), Christmas berry (Schinus terebinthifolius).
61
1.0 1998 0.9 1999 5 0.8 7 21 0.7 11 16 19 39 0.6 32
0.5 49 18 5 0.4 16 17 Nesting Success 3 0.3 4 0.2
0.1 2 0.0 n st d ss st a e a re b ine orest r b Gr u For h Fo F " Forest ic Ex om ot otic C tive Forest x s a E Ex t N ita ll "Exotic" ive/ a at ive Forest wit N d Over at e Overall "Native All Hab N ix M Habitat Type
Figure 11. Hawk nesting success during the 1998-99 field seasons. Success is stratified into 5 habitats (native forest, native forest with grass, mixed native/exotic forest, exotic forest, and exurban) that correspond to habitat types in Fig. 1. "Native" combines native forest, native forest with grass, and mixed native/exotic forest when dominated by native components. "Exotic" include exotic forest, exurban, and mixed native/exotic forest that were dominated by exotic vegetation.
62
LITERATURE CITED
Akaike, H. 1973. Information theory and extension of the maximum likelihood
principle. In Second international symposium on information theory. B. N.
Petram and F. Csaaki, editors, Akadeemia Kiaki, Budapest, Hungary. 267-
281.
Akcakaya, H. R. 1999. RAMAS GIS: Linking landscape data with population
viability analysis. Applied Biomathematics, Setauket, NY.
Andersen, D. E., O. J. Rongstad, and W. R. Mytton. 1985. Line transect analysis of
raptor abundance along roads. Wildlife Society Bulletin. 13:533-539.
Anderson, D. R., J. L. Laake, B. R. Crain, and K. P. Burnham. 1976. Guidline for line
transect sampling of biological populations. Utah Cooperative Wildlife
Research Unit. Utah State University, Logan, Utah.
Atkinson, C. T., K. L. Woods, R. J. Dusek, L. S. Sileo, and W. M. Iko. 1995a.
Wildlife disease and conservation in Hawaii: Pathogenicity of avian malaria
(Plasmodium relictum) in experimentally infected Iiwi (Vestiaria coccinea).
Parasitology. 111:559-569.
Atkinson, C. T., N. Yorinks, K. L. Woods, R. J. Dusek, and W. M. Iko. 1995b.
Pathogenicity of malaria (Plasmodium relictum) in experimentally-infected
Hawaiian forest birds. In Proceedings of a Joint Conference American
Association of Zoo Veterinarians, Wildlife Disease Association, and
American Association of Wildlife Veterinarians, East Lansing, Michigan,
USA, August 12-17, 1995.
63
Banko, W. E. 1980. Avian History Report 6A. History of endemic Hawaiian birds.
Part 1. Population histories - species accounts. Coop. Natl. Park Res. Stud.
Unit, Univ. of Hawaii, Honolulu.
Beissinger, S. R., and M. I. Westphal. 1998. On the use of demographic models of
population viability in endangered species management. Journal of Wildlife
Management. 62:821-841.
Berger, A. J. 1981. Hawaiian birdlife. Univ. of Hawaii Press, Honolulu, HI.
Berger, D. D. H. C. M. 1959. The bal-chatri: a trap for birds of prey. Bird Banding.
30:18-26.
Black, J. M., A. P. Marshall, A. Gilburn, N. Santos, H. Hoshide, J. Medeiros, J.
Mello, C. N. Hodges, and L. Katahira. 1997. Survival, movements, and
breeding of released Hawaiian geese: An assessment of the reintroduction
program. Journal of Wildlife Management. 61:1161-1173.
Bosakowski, T., and D. G. Smith. 1998. Response of a forest raptor community to
broadcasts of heterospecific and conspecific calls during the breeding season.
Canadian Field Naturalist. 112:198-203.
Brook, B. W., and J. Kikkawa. 1998. Examining threats faced by island birds: a
population viability analysis on the Capricorn silvereye using long-term data.
Journal Of Applied Ecology. Aug. 35:491-503.
Buckland, S. T., D. R. Anderson, K. P. Anderson, K. P. Burnham, and J. L. Laake.
1993. Distance sampling: estimating abundance of biological populations.
Chapman and Hall, London, U.K.
64
Buckland, S. T., and B. J. Turnock. 1992. A robust line transect method. Biometrics.
48:901-909.
Buehler, D. A., J. D. Fraser, M. R. Fuller, L. S. McAllister, and J. K. D. Seegar. 1995.
Captive and field tested radio attachment techniques for Bald Eagles. Journal
of Field Ornithology. 66:173-180.
Burnham, K. P., D. R. Anderson, and J. L. Laake. 1980. Estimation of density from
line transect sampling of biological populations. Wildlife Monographs. 72:1-
202.
Caswell, H. 1989. Matrix population models: construction, analysis, and
interpretation. Sinauer Associates, Sunderland, Massachusetts.
Caswell, H. 2000. Prospective and retrospective perturbation analyses: their roles in
conservation biology. Ecology. 81:619-627.
Cuddihy, L. W., and C. P. Stone. 1990. Alteration of native Hawaiian vegetation:
Effects of humans, their activities and introductions. Univ. Hawaii Press,
Honolulu. de Kroon, H., J. van Groenendael, and J. Ehrlen. 2000. Elasticities: a review of
methods and model limitations. Ecology. 81:607-618.
Donazar, J. A., O. Ceballos, A. Travaini, and F. Hiraldo. 1993. Roadside raptor
surveys in the Argentinian Patagonia. Journal of Raptor Research. 27:106-
110.
Eakle, W. L. 1994. A raptor roadside survey in western Turkey and eastern Greece.
Journal of Raptor Research. 28:186-191.
65
Eakle, W. L., E. L. Smith, S. W. Hoffman, D. W. Stahlecker, and R. B. Duncan.
1996. Results of a raptor survey in southwestern New Mexico. Journal Of
Raptor Research. Dec. 30:183-188.
Environmental Systems Research Institute. 1992-1998. Arcview 3.1, Redlands, CA.
Faaborg, J. 1986. Reproductive success and survivorship of the Galapagos hawk
Buteo galapagoensis; potential costs and benefits of cooperative polyandry.
Ibis. 128:337-347.
Falls, J. B. 1981. Mapping territories with playback: an accurate census method for
songbirds. Pp. 86-91 in C.J. Ralph and J.M Scott (eds.). Estimating the
numbers of terrestrial birds. .
Fancy, S. G. 1997. A new approach for analyzing bird densities from variable
circular-plot counts. Pacific Science. 51:107-114.
Fitch, H. S., F. Swenson, and D. F. Tillotson. 1946. Behavior and food habits of the
Red-tailed Hawk. Condor. 48:205-257.
Fuller, M. R., and J. A. Mosher. 1981. Methods of detecting and counting raptors: a
review. Pp. 235-246 in C.J. Ralph and J.M Scott (eds.). Estimating the
numbers of terrestrial birds. Studies in Avian Biology No. 6.
Fuller, M. R., and J. A. Mosher. 1987. Raptor survey techniques. In Raptor
management techniques manual. B. A. Giron Pendleton, B. A. Millsap, K. W.
Cline, and D. M. Bird, editors. National Wildlife Federation, Washington,
D.C. 37-66.
Glinski, R. L. 1976. Birdwatching etiquette: the need for a developing philosophy.
Am. Birds. 30:655-657.
66
Green, R. C. 1971. The chronology and age of sites at South Point, Hawaii.
Archeological and Physical Anthropology in Oceania. 6:170-176.
Grier, J. W., and F. W. Richard. 1987. Preventing research and management
disturbance. In Raptor management techniques manual. B. A. Giron
Pendleton, B. A. Millsap, K. W. Cline, and D. M. Bird, editors. National
Wildlife Federation, Washington, D.C. 173-182.
Griffin, C. 1989. Raptors in the Hawaiian islands. In Western Raptor Management
Symposium and Workshop. K. Steenhof, M. N. Kochert, and M. N. LeFranc
Jr., editors. Natl. Wildl. Fed, Sci. Tech. Ser. No. 12, Washington, DC.
Griffin, C. R. 1985. Biology of the Hawaiian hawk (Buteo solitarius). Dissertation.
Univ. Missouri, Columbia, MO.
Griffin, C. R., P. W. C. Paton, and T. S. Baskett. 1998. Breeding ecology and
behavior of the Hawaiian Hawk. Condor. 100:654-662.
Hall, L. S., M. L. Morrison, and P. H. Bloom. 1997. Population status of the
endangered Hawaiian hawk. Journal of Raptor Research. 31:11-15.
Handy, E. S. C., and E. G. Handy. 1972. Native planters in old Hawaii: their life, lore,
and environment. B.P. Bishop Museum Bull. 233., Honolulu, HI.
Hawaii State Department of Business, E. D. a. T. 1998. Web document at:
http://www.hawaii.gov/dbedt/db98/index.html. Private residential
construction and demolition authorized by permits, by counties: 1993 to 1998.
Heppell, S. S., H. Caswell, and L. B. Crowder. 2000. Life histories and elasticity
patterns: pertubation analysis for species with minimal demographic data.
Ecology. 81:654-665.
67
Howell, J. C. 1951. The roadside census as a method of measuring birds populations.
Auk. 68:334-357.
International Union for Conservation of Nature. 1994. Red list categories. Species
Survival Commission, Gland, Switzerland.
Jacobi, J. D. 1990. Distribution maps, ecological relationships, and status of native
plant communities on the island of Hawaii. Dissertation. University of Hawaii
at Manoa.
Johnson, R. R., B. T. Brown, L. T. Haight, and J. M. Simpson. 1981. Playback
recordings as a special avian censusing tool. Pp. 68-75 in C.J. Ralph and J.M
Scott (eds.). Estimating the numbers of terrestrial birds. Studies in Avian
Biology No. 6.
Joy, S. M., R. T. Reynolds, and D. G. Leslie. 1994. Northern goshawk broadcast
surveys: hawk response variables and survey cost. Pp. 24-30 in W.M. Block,
M.L. Morrison, and M.H. Reiser (eds.). The Northern Goshawk: ecology and
management. Studies in Avian Biology No. 16.
Kennedy, P. L. 1997. The Northern Goshawk (Accipiter gentilis): is there evidence of
a population decline? Journal of Raptor Research. 31:95-106.
Kepler, C. B., and J. M. Scott. 1981. Reducing bird count variability by training
observers. Pp. 366-371 in C.J. Ralph and J.M Scott (eds.). Estimating the
numbers of terrestrial birds. Studies in Avian Biology No. 6.
Kirch, P. V. 1982. The impact of prehistoric Polynesians on the Hawaiian ecosystem.
Pacific Science. 36:1-14.
68
Kirch, P. V. 1985. Feathered gods and fishhooks. An introduction to Hawaiian
archaeology and prehistory. Univ. Hawaii Press, Honolulu, HI.
Klavitter, J. L., and J. M. Marzluff. (submitted). Methods to correct for density
inflation biases in surveys using attractant calls: a case study of Hawaiian
Hawks. .
Kuehler, C., M. Kuhn, J. E. Kuhn, A. Lieberman, N. Harvey, and B. Rideout. 1996.
Artificial incubation, hand-rearing, behavior, and release of common 'Amakihi
(Hemignathus virens virens): Surrogate research for restoration of endangered
Hawaiian forest birds. Zoo Biology. 15:541-553.
Laake, J. L., S. T. Buckland, D. R. Anderson, and K. P. Burnham. 1993. Distance
user's guide, version 2.0. Colorado Cooperative Fish and Wildlife Research
Unit, Colorado St. Univ., Fort Collins, CO.
Leslie, P. H. 1945. On the use of matrices in certain population mathematics.
Biometrika. 33:183-212.
Leslie, P. H. 1948. Some further notes on the use of matrices in certain population
mathematics. Biometrika. 35:213-245.
Lindsey, G. D., S. G. Fancy, M. H. Reynolds, T. K. Pratt, K. A. Wilson, P. C. Banko,
and J. D. Jacobi. 1995. Population structure and survival of the Palila. Condor.
97:528-535.
Lindsey, G. D., and S. M. Mosher. 1994. Tests indicate minimal hazard to 'Io from
diphacinone baiting. Hawaii's Forests and Wildlife. 9:4.
69
Luginbuhl, J., and J. M. Marzluff. (submitted). Does stand size, surrounding forest
composition, and distance from stand edge influence predation on Marbled
Murrelet nests in coastal Oregon? .
Marion, W. R., T. E. O'Meara, and D. S. Maehr. 1981. Use of playbacks in sampling
elusive or secretive birds. Pp. 81-85 in C.J. Ralph and J.M Scott (eds.).
Estimating the numbers of terrestrial birds. Studies in Avian Biology No. 6.
Mayr, E. 1943. The zoogeographic position of the Hawaiian Islands. Condor. 45:45-
48.
McCracken, M. L. 1994. Factors affecting bird counts and their influence on density
estimates. Dissertation. Oregon State University, Corvallis.
McLeod, M. A., and D. E. Andersen. 1998. Red-shouldered hawk broadcast surveys:
Factors affecting detection of responses and population trends. Journal of
Wildlife Management. 62:1385-1397.
Microsoft Corp. 1997. Access 97, Seattle, WA.
Morrison, M. L., L. S. Hall, and P. H. Bloom. 1994. Hawaiian Hawk (Buteo
solitarius) population survey. U.S. Fish & Wildlife Service, Pacific Islands
Office, Honolulu, HI U.S.A.
Mosher, J. A., M. R. Fuller, and M. Kopeny. 1990. Surveying woodland raptors by
broadcast of conspecific vocalizations. Journal of Field Ornithology. 61:453-
461.
Murray, B. G. J. 1985. Evolution of clutch size in tropical species of birds.
Ornithological Monographs. 36:505-519.
Newton, I. 1979. Population ecology of raptors. Buteo Books, Vermillion, S.D.
70
Noecker, R. J. 1998. Endangered species list revisions: a summary of delisting and
downlisting. Congressional Research Service. Library of Congress,
Washington, D.C.
Olson, S. L., and H. F. James. 1982. Fossil birds from the Hawaiian Islands: evidence
for wholesale extinction by man before western contact. Science. 217:633-
635.
Olson, S. L., and H. F. James. 1991. Ornithological monograph No. 45: descriptions
of thirty-two new species of birds from the Hawaiian islands: part 1. Non-
passeriformes. Allen Press, Lawrence, KS.
Olson, S. L., and H. F. James. 1996. Prehistoric status and distribution of the
Hawaiian hawk (Buteo solitarius), with the first fossil record from Kauai.
Bishop Museum Occasional Papers. 49:65-69.
Oreinstein, R. 1968. Birds of the Crowder "birds of Hawaii" Tour, December 23,
1967 to January 5, 1968. Elepaio. 29:21-27.
Pagel, J. E., D. A. Bell, and M. L. Johnson. 1998. When is an endangered species
recovery complete: Is delisting the American Peregrine falcon appropriate?
Trans. No. Am. Wildl. and Natur. Resour. Conf. 63:463-474.
Preston, C. R., and R. D. Beane. 1993. Red-tailed hawk: Buteo jamaicensis. Birds of
North America:1-24.
Ralph, C. J., and S. G. Fancy. 1994a. Demography and movement of the endangered
Akepa and Hawaii Creeper. Wilson Bulletin. 106:615-628.
Ralph, C. J., and S. G. Fancy. 1994b. Demography and movement of the Omao
(Myadestes obscurus). Condor. 96:503-511.
71
Ralph, C. J., and S. G. Fancy. 1995. Demography and movement of the Apapane and
Iiwi in Hawaii. Condor. 97:729-742.
Ralph, C. J., and S. G. Fancy. 1996. Aspects of the life history and the foraging
ecology of the endangered Akiapolaau. Condor. 98:312-321.
Ramsey, F. L., and J. M. Scott. 1979. Estimating population densities from variable
circular plot surveys. In Sampling biological populations. R. M. Cormack, G.
P. Patil, and D. S. Robson, editors. International Cooperative Publishing
House, Fairland, Maryland. 155-181.
Ramsey, F. L., and J. M. Scott. 1981. Analysis of bird survey data using a
modification of Emlen's methods. Pp. 483-487 in C.J. Ralph and J.M Scott
(eds.). Estimating the numbers of terrestrial birds. Studies in Avian Biology
No. 6.
Saether, B.-E., and O. Bakke. 2000. Avian life history variation and contribution of
demographic traits to the population growth rate. Ecology. 81:642-653.
Santana, C. E., and S. A. Temple. 1988. Breeding biology and diet of red-tailed
hawks in Puerto Rico. Biotropica. 20:151-160.
Scott, J., S. Mountainspring, F. Ramsey, and C. Kepler. 1986. Forest bird
communities of the Hawaiian islands: Their dynamics, ecology, and
conservation. Studies in Avian Biology No. 9.
Scott, J. M., J. D. Jacobi, and F. L. Ramsey. 1981. Avian surveys of large
geographical areas: a systematic approach. Wildlife Society Bulletin. 9:190-
200.
Seber, G. A. F. 1973. The estimation of animal abundance. Griffin, London.
72
Sergio, F., and A. Boto. 1999. Nest dispersion, diet, and breeding success of Black
Kites (Milvus migrans) in the Italian pre-Alps. Journal of Raptor Research.
Sept. 33:207-217.
Shelton, A. D. 1971. A population study of breeding hawks genus Buteo in Marion
County, Ohio. M.S. Ohio State University, Columbus.
Spear, L. B., S. B. Terrill, C. Lenihan, and P. Delevoryas. 1999. Effects of temporal
and environmental factors on the probability of detecting California Black
Rails. Journal Of Field Ornithology. Fal. 70:465-480.
Spiller, D. A., J. B. Losos, and T. W. Schoener. 1998. Impact of a catastrophic
hurricane on island populations. Science. 281:695-697.
SPOT. 1994. Systeme pour l'observation de la terre (SPOT). Hawaii statewide XS
coverage. CD-ROM, order 3467006003. SPOT Image Corporation, Reston.
Stalmaster, M. V. 1983. An energetics simulation model for managing wintering bald
eagles. Journal of Wildlife Management. 47:349-359.
Steenhof, K. 1987. Assessing raptor reproductive success and productivity. In Raptor
management techniques manual. B. A. Giron Pendleton, B. A. Millsap, K. W.
Cline, and D. M. Bird, editors. National Wildlife Federation, Washington,
D.C. 151-170.
Steenhof, K., and M. N. Kochert. 1982. An evaluation of methods used to estimate
raptor nesting success. Journal of Wildlife Management. 46:85-93.
Svensson, S. E. 1977. Land use planning and bird census work with particular
reference to the application of the point sampling method. Pol. Ecol. Stud.
3:207-213.
73
Thomas, L., J. Laake, S. Buckland, D. Borchers, K. Burnham, and D. Anderson.
1998. Distance version 3.5, release 5. Research Unit for Wildlife, University
of St. Andrews, U.K.
U.S. Bureau of the Census. 1998. Web document found at:
http://www.hawaii.gov/abedt/db98/01/014798.pdf. County population
estimates and demographic components of population change: annual time
series, July 1, 1990 to July 1, 1998.
U.S. Fish & Wildlife Service. 1999. Web document at
http://endangered.fws.gov/boxscore.html. Listings and recovery plans.
U.S. Fish & Wildlife Service. 2000. Web document at
http://www.r1.fws.gov/pacific/wesa/endspindex.html. U.S. Fish and Wildlife
Service, Pacific Islands ecoregion homepage: Endangered species.
U.S. Fish and Wildlife Service. 1984. Hawaiian hawk recovery plan. U.S. Fish and
Wildlife Service, Portland, OR.
U.S. Fish and Wildlife Service. 1994. Endangered and threatened wildlife and plants;
withdrawal of proposed rule to reclassify the Hawaiian hawk (Buteo
solitarius) from endangered to threatened. U.S. Fish and Wildlife Service,
Honolulu.
U.S. Fish and Wildlife Service. 1999. U.S. Fish and Wildlife Service proposes to
remove Tinian Monarch from Endangered Species Act protection. U.S. Fish
and Wildlife Service, Honolulu.
74 van Riper III, C., S. G. van Ripper, M. L. Goff, and M. Laird. 1986. The
epizootiology and ecological significance of malaria in Hawaiian land birds.
Zoological Monographs. 56:327-344.
Vekasy, M. S., J. M. Marzluff, M. N. Kochert, R. N. Lehman, and K. Steenhof. 1996.
Influence of radio transmitters on Prairie Falcons. Journal of Field
Ornithology. 67:680-690.
Watson, J. W., D. W. Hays, and D. J. Pierce. 1999. Efficacy of Northern Goshawk
broadcast surveys in Washington state. Journal of Wildlife Management.
63:98-106.
Watson, R. T., and S. Razafindramanana. 1999. Nearest neighbor nest distances,
home range, and territory area of the Madagascar Fish-eagle (Haliaeetus
vociferoides). Journal of Raptor Research. 33:335-338.
Weber, W. C., and J. B. Theberge. 1977. Breeding bird survey counts as related to
habitat and date. Wilson Bulletin. 89:543-561.
Wisdom, M. J., L. S. Mills, and D. F. Doak. 2000. Life stage simulation analysis:
estimating vital-rate effects on population growth for conservation. Ecology.
81:628-641.
Wolfram Research, I. 1999. Mathematica. Wolfram Research, Inc., Champaign.
Zahn, S. N., and S. I. Rothstein. 1999. Recent increase in male house finch plumage
variation and its possible relationship to avian pox disease. Auk. 116:35-44.
Zar, J. H. 1996. Biostatistical analysis. Prentice Hall, Upper Saddle River, NJ.
75
Zelenak, J. R., and J. J. Rotella. 1997. Nest success and productivity of Ferruginous
Hawks in northern Montana. Canadian Journal of Zoology Jul. 75:1035-
1041.
76
APPENDIX A
Survey Point Descriptions and Locations
Table A.1. Survey point locations (339 pt) for the January 1998 and 1999 ‘io surveys.
Point Trans- Stat- Location description Utm Utm_x Utm_y Elev- ect ation Zone ation WGS84 (ft)
1 A 1 Begin transect around mile 6 on Kaumana Drive (Saddle Road). Drive 0.5 mi. 5 273753 2176844 1490 down Country Club Rd. Park at the end on gravel where turn around is. 2 A 2 Junction of Country Club Rd. and Kaumana Dr. (Saddle Rd). 5 273838 2177579 1400 3 A 3 0.3 miles down Wilder Rd. from Wilder/Kaumana junction. 5 275479 2177506 1130 4 A 4 At end of Wilder Rd., 0.8 mi. off of Kaumana Dr. 5 275507 2176620 1180 5 A 5 0.2 miles north of Akolea Rd./Kaumana Dr. junction. 5 276057 2178531 1030 6 A 6 0.5 miles north of A5 and 0.7 north of Akolea/Saddle junction. 5 276045 2179360 7 A 7 1.2 miles north from Akolea /Kaumana Dr. junction. 0.5 miles north of A6. 5 276238 2180422 780 8 A 8 Turn left on Waianuenue from Akolea. Drive 0.3 miles. Point is at the bridge. 5 275904 2181354 890 9 A 9 0.5 miles mauka A8 on Waianuenue. (0.8 miles mauka Akolea/Waianuenue junction.) 5 275100 2181731 1030 10 A 10 0.5 miles mauka of A9. At end of Waianuenue. Gate with Hawaiian Homelands sign. 5 274337 2181891 1220 11 A 11 At Kaumana Caves on Kaumana Dr. 5 276632 2178189 1080 12 A 12 Turn south on Edita rd. off of Kaumana. Drive to the end of rd. 5 277629 2178361 740 (Junction with Mele/Manu St.). 13 AA 1 ~0.1m N of Kalopa/Kalopa Mauka intersection 5 245682 2220415 14 AA 2 1.0 miles from AA1, up Kalopa Mauka Rd. 5 245669 2219201 15 AA 3 1 Mile from AA2, at end of Kalopa Mauka 5 244628 2218006 16 AA 4 Intersection of Kaapahu Rd. & Hookahua Rd. 5 246826 2218922 17 AA 5 1.0 Mile from AA4 up Kula Kahika Rd. 5 246974 2217505 18 AA 6 1.4 mile from AA5 up Kuikui Papa Rd. 5 246072 2215580 19 B 1 Start just north of Hilo At intersection of Kaiwiki rd. and Wainaku. 5 280670 2183809 110 20 B 2 0.5 miles mauka of B1. Up Kaiwiki rd. 5 279872 2184205 300 21 B 3 0.5 miles mauka of B2. (1.0 mile mauka of start. Corner of Kaiwiki rd./Anuenue). 5 279211 2184733 440 22 B 4 0.5 miles mauka B3. (1.5 miles mauka of start. Nice waterfall to the right). 5 278399 2185044 610 23 B 5 0.5 miles mauka B4 (2.0 miles mauka from start). Just after bridge. 5 277428 2185052 740 24 B 6 2.5 miles mauka B1 (0.5 miles mauka B5) At a private drive on the left as you go mauka. 5 276760 2185350 990 25 B 7 3.5 miles mauka from B1. Telephone pole 53x. Mail box 262655. 5 275328 2185750 1320 26 B 8 4.5 miles mauka from B1. Just before small bridge. Grey house. 5 273979 2186317 1680 27 B 9 5.5 miles mauka from B1. At turn around with sign, "End County Road". 5 272454 2186419 1980
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28 B 10 Drive back down Kaiwiki to Wainaku. Find Amauulu rd. Drive mauka to 5 276370 2183531 910 "T" where macnuts end and cane starts. 29 B 11 0.5 miles makai B10. At "T" junction in macnut orchard. Orange marker 49. 5 277121 2183352 780 30 B 12 0.5 miles makai B11. (In macnut orchard). 5 277962 2183120 650 31 B 13 0.5 miles makai of B12. In macnuts on road. 5 278714 2182785 510 32 B 14 0.5 miles makai of B13. Cross paved road. In fallow cane. 0.8 miles mauka from 5 279625 2182763 390 Waihau/ Amauulu intersection. 33 BB 1 0.1 mile from start of Chin Chuck Rd 5 277304 2201080 34 BB 2 1mile from start or BB1 5 275963 2200163 35 BB 3 2 miles from start at pole 65 5 274735 2199228 36 BB 4 3 miles from start end of chin chuck rd 5 273404 2198295 37 C 1 Begin on 40th Street outside of Kurtistown, at junction with Napua St., 5 286214 2165952 work back towards town; point every .5 mile 38 C 2 .5 miles from c1. 5 285682 2166791 39 C 3 .5 miles from c2. 5 285275 2167521 40 C 4 0.5 miles from C3. Just past Fuka Bonsai cultural center toward Hwy. 5 284757 2167789 41 CC 1 Begin at junction of Crater Rim Drive and Chain of Craters Rd. 5 263401 2147223 42 CC 2 Mile 1.35, dirt road on right just before cattle guard. 5 264044 2145248 43 CC 3 Mile 2.65, at turnout for Hiaka Crater. 5 265290 2143667 44 CC 4 Mile 3.3, just past turnout for Pauahi Crater. 5 266248 2143233 45 CC 5 Mile 4.35, small dead end Rd. To right. 5 266314 2141899 46 D 1 Akaka falls state park parking lot 5 274661 2196678 47 D 2 1mile mauka of state park at 1st fork go right at 2nd fork go right 5 273749 2196194 48 D 3 1.1mile makai of Akaka falls park entrance 5 276027 2196501 49 D 4 2 miles makai of Akaka fall park entrance at pole 39 5 277482 2197210 50 D 5 3 miles makai of Akaka falls park or 1 mile from D1 5 278603 2198180 51 D 6 .1 mile from start of homestead Rd intersection with route 19 mauka across from Hilo 5 279432 2195141 Power Company sign 52 D 7 1 miles from D6 or 1.1 mile from start of Homestead Rd mauka surrounded by banana fields 5 278158 2195483 53 D 8 1.2 miles form D7 past Eucalyptus biomass plantation 5 276358 2194942 54 D 9 end of road 1mile from D8 5 274960 2194306 55 D 10 1mile form D6 at intersection with Kaakepa and kumula 5 279572 2194540 56 D 11 end of Kulaimano Rd or .4 from intersection with Kulaimano and route 19 5 279085 2193944 57 D 12 at Assembly of God Parking Lot .5makai intersection with Kulaimani Rd and route 19 5 270399 2194166 58 D 13 1mile mauka Kaielie Rd at water tank 5 279060 2189895 59 D 14 start of Kaapoko Hmstd Rd at intersection with the Immaculate Mary Catholic 5 280533 2189577 Church and the school
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60 D 15 1.1 miles after D14 on Old Mamalahoa right after Gulch heading east 5 280705 2188584 61 D 16 .3 miles west on Kulana St just past Kingdom Hall Jehovah's Witnesses if heading west 5 280687 2186987 62 DD 1 Begin at KMC baseball diamond, continue counter-clockwise around Crater Rim Dr. 5 260917 2150150 63 DD 2 1.2 mi. From DD1 5 259259 2148759 64 DD 3 0.9 mi. From DD2. 5 258866 2147497 65 DD 4 East side of Keanakakoi Crater. 5 262358 2147016 66 DD 5 0.25 mi. From Thurston Lava Tube, toward park Headquarters. 5 264698 2148376 67 DD 6 0.2 mi. Down closed road near USFWS office. 5 263293 2148850 68 E 1 Begin 0.2 mi. before milepost 15 on Saddle Rd. Survey toward Hilo. 5 261620 2178687 3800 69 E 2 ~ mile 14. 0.85 mi. from E1. At left hand turn. 5 263117 2178877 3610 70 E 3 0.85 mi. from E 2. At turnout with small sign about DLNR Forest Reserve. ~ mile 13.1. 5 263897 2173138 3400 71 E 4 0.8 mi. from E3 at approx. mile 12.3 on left-hand downhill curve. 5 265115 2179578 3080 72 E 5 0.80 mi. from E 4 on slight left hand curve. ~ mile 11.5. 5 266322 2179687 2950 73 E 6 0.8 mi. from E 5. Road is downhill and straight after right hand curve. ~ mile 10.7. 5 267635 2179202 2640 74 E 7 0.8 mi. from E 6 at approx. Mile 9.75.. 5 268733 2179027 2450 75 EE 1 Begin route at Vanda Street and Ainaloa Dr off of Ainaloa Blvd off Hwy 130 5 292590 2161430 76 EE 2 .9 mile from EE1 5 291864 2160224 77 EE 3 .6 mile from EE2 5 291238 2159322 78 EE 4 1 mile from EE3 5 289808 2158532 79 EE 5 .7mile from EE4 go up Stardust .1 then take left on unmarked washed out Road 5 288963 2158288 80 EE 6 1mile from EE5 5 287590 2157568 81 EE 7 .9mile from EE6 5 286365 2156822 82 EE 8 1 mile from EE7 at intersection with Road G and Road 1 5 284846 2155985 83 EE 9 .9 to Hibiscus St and Anthurium St intersection. Makai of Mt. View 5 283440 2155255 84 F 1 Puu Waawaa. 1 mile mauka hwy.190. (Stay right). A-frame house ~140m away. 5 202143 2190883 2380 85 F 2 2 miles from highway. At Puu Waawaa Ranch HQ. At yellow gate in rear. 5 202025 2189453 2420 86 F 3 3 miles from highway. At edge of large clearing. 5 200860 2188729 2680 87 F 4 4 miles from highway. Go through and mauka gate marked Henahena. Point at 5 199796 2187806 2750 large clearing. 88 F 5 5 miles mauka of hwy. Drove past large cement cattle trough. 5 199519 2186339 3380 89 F 6 6 miles mauka hwy. Heading toward new state cabin. Cabin ~ 300m away. 5 198910 2185319 3750 90 F 7 stay at base of sanctuary - 7miles go by New cabin and through rock coral follow 5 199906 2185076 3860 fence line fence corner 91 F 8 7.5 miles .5miles from F7 at Henaheua gate Sanct fence on right 5 200579 2184969 4010 92 F 9 8miles .5from F8 Sanct fence on right 5 201332 2185322 3950 93 F 10 8.5 miles .5from F9 5 202065 2185439 3910 94 F 11 9 miles .5 from F10 go past cedar water tank Through fence and turn left point at gate 5 202703 2185817 3800
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in fence line? 95 F 12 9.5miles .5 from F11 ~.3miles past double pipe gate 5 203415 2185952 3810 96 FF 1 0.1 miles from main headquarters of Mauna Kea Ranch (ranch at Umikoa Village) 5 251057 2210695 97 FF 2 0.6 miles from HQ 5 251723 2211012 98 FF 3 1.1 miles from HQ (At bridge) 5 252401 2211306 99 FF 4 1.6 miles from HQ 5 253073 2211546 100 FF 5 2.1 miles from HQ 5 253437 2212238 101 FF 6 2.6 miles from HQ (Ranch gate) 5 253610 2212985 102 FF 7 3.1 miles from HQ 5 254032 2213498 103 FF 8 3.6 miles from HQ 5 254019 2214061 104 FF 9 4.1 miles from HQ 5 254298 2214566 105 FF 10 4.6 miles from HQ 5 254172 2215173 106 FF 11 5.1 miles from HQ 5 254978 2215559 107 G 1 1 mile north of Manuka St. Park. 5 201667 2116597 108 G 2 .5 mile north of Manuka State Park. 5 202001 2115902 109 G 3 Manuka State Park. At Water Tank. 5 202725 2115395 110 G 4 Follow hiking trail mauka. Station 5 on trail. 5 203328 2115878 111 G 5 station 10 on trail 5 203316 2116432 112 G 6 station 15 on trail. 5 203001 2116500 113 G 7 .5 mile south of Manuka Park. 5 203451 2114655 114 G 8 1 mile south of Manuka Park. 5 204267 2114236 115 GG 1 At junction of Hwy. 130 and Hwy. 137. 5 293431 2142690 116 GG 2 1.1 miles from GG1 on Hwy. 130, toward Pahoa. 5 294272 2144421 117 GG 3 At mile marker 18 on Hwy. 13 5 294623 2146118 118 GG 4 At One Ele Rd. across from large water tank. 5 295009 2147785 119 GG 5 200 m. South of Kamaili St. 5 295613 2149773 120 GG 6 At Ala Ili Rd. , near entrance to cinder pit. 5 296231 2151951 121 GG 7 Mile marker 13. 5 296241 2153975 122 H 1 .5 miles makai H2 on Milolii Rd (2.1 miles makai hwy11) 5 195986 2125772 700 123 H 2 .5 miles makai H3 on Milolii Rd at driveway on Left 5 196450 2125948 1100 124 H 3 .5miles Makai H4 on Milolii Rd 5 197002 2126043 1200 125 H 4 .6 miles makai of Hwy 11 down Milolii Rd at blacktop pullout. Shannon Farm sign 5 197734 2126133 1510 126 H 5 80m makai from Milolii Rd Hwy11 junction 5 198328 2126547 1700 127 HH 1 0.5 miles off 130; 0.1 miles up Hoopili St. 5 296850 2155767 128 HH 2 1.0 miles off 130; 0.1 miles up Kaululaau St. 5 298048 2155609 129 HH 3 1.5 miles off 130; 0.1 miles South of 132 5 300467 2155002 130 HH 4 Lava Tree Park, along trail past parking lot 5 300142 2155297
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131 HH 5 3.0 miles off 130; on 132 5 301065 2155374 132 HH 6 3.5 miles off 130; on 132 (at water tank pull off) 5 301834 2155938 133 HH 7 4.0 miles off 130; on 132 5 302596 2156235 134 HH 8 4.5 miles off 130; on 132 (150 meters before milepost 5) 5 303589 2156147 135 HH 9 5.0 miles off 130; on 132 (dirt road on left ~ mile 5.5) 5 304593 2156395 136 I 1 Pullout on highway on Makai side of rd just south of mile marker18 entrance 5 205641 2195273 2250 to Puu Anahulu 137 I 2 Mile marker 20 on highway just north of Puu Waawaa entrance 5 202850 2194064 2216 138 I 3 .5miles makai I4 .3miles mauka and to left of Puu Waawaa entrance 5 202510 2192078 2160 139 I 4 .5 miles makai I5 5 202820 2191372 2490 140 I 5 .5miles makai I6 5 203118 2190551 2640 141 I 6 .5 miles makai I7 where the pavement begins mauka just below tile factory 5 203300 2189713 2790 142 I 7 .5miles makai I8 5 203820 2189384 3080 143 I 8 .5 miles makai green cabin .1 miles makai of 2gates with cattle guard 5 203941 2188658 3360 144 I 9 .5miles from "y" turn to go around back side of Puu Waawaa stay to right and 5 202764 2188013 3450 follow cow path till reach .5 miles 145 I 10 .5 miles makai I11 1.5 miles makai Kileo gate @ green cabin 5 203642 2187806 3510 146 I 11 .5 miles makai I12 1mile makai Kileo gate 5 204047 2187442 3600 147 I 12 .5miles makai I13 and Kileo gate go Kileo gate? 5 204266 2186731 3670 148 I 13 at aluminum gate "Kileo" 5 204157 2186204 3720 149 I 14 go left 0.5 miles from point I15 and 0.5 mile mauka through gut of Kileo gate 5 204730 2186615 3730 150 I 15 1mile from Kileo gate to the left point at small turn around just before small puu 5 205386 2186276 3870 151 II 1 0.5 mi. From junction with Hwy. 130, 500 ft. NW. or at sign for Runaway truck ramp 5 296563 2149844 152 II 2 0.75 mi. 5 297622 2149534 153 II 3 0.75 mi. from II 2 at crossroads with a small plantation road and gate. 5 298323 2150492 154 II 4 0.65 mi. from II 3 at left hand turn next to several large conifers 5 299087 2150977 155 II 5 0.65 mi. from II 4 where 2 driveways lead to the right. One driveway has gate. 5 300056 2150893 156 II 6 0.7 mi. from II 5. Next to gate that leads to grassy field on right 5 301080 2150456 157 II 7 Intersection of Kalapana-Kapoho Rd. and Kamaili Rd. 5 302491 2149125 158 J 1 point at intersection of Wittington beach park rd and hwy 11 (Honuapo) 5 231789 2112730 120 159 J 2 mile marker 59 on hwy 11 5 233212 2114789 50 160 J 3 mile marker 57 on hwy 11 5 234866 2117547 50 161 J 4 40m east of mile 55 on hwy 11 small mauka pull off 5 236576 2120309 280 162 J 5 .6 miles SW of J6 50m mauka from intersection hwy11 and Old Gov Rd 5 237179 2121323 405 163 J 6 1mile SW of J7 5 237703 2122097 500 164 J 7 .5 miles southwest of J8 at small Blue Water Pipe on makai side of road 5 238078 2123456 600 165 J 8 .5 miles southwest of J9 on Old Gov Rd? heading out of Pahala and toward 5 238788 2123966 680
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hwy 11 @ blue water pipe. 166 J 9 at y junction heading out of Pahala. Pahala Rd old Gov Rd Old theatre 120m away 5 239291 2124450 760 167 J 10 1mile toward Pahala from J11 at Macnut gravel road junction going makai 5 239542 2127165 1350 (.9miles from y junction with stop sign heading out of Pahala just after Pikaka Rd 168 J 11 1mile southwest (toward Pahala) from J12 at beginning of Rd going Mauka 5 239384 2128752 1670 169 J 12 1mile southwest (toward Pahala) from wood valley Rd junction Telephone pole 16 5 240009 2130362 1860 170 J 13 1mile mauka (take right at "y" from pt 14, heading mauka and east toward 5 241495 2133656 2420 Kapapala mauka middle of cane 171 J 14 .6miles northeast (toward mauka Kapapala) from wood valley junction will 5 241024 2132613 1980 encounter 1"y" stay left. Pt at Y intersection 172 J 15 .5 miles makai J16 ~.15miles makai of Budest Temple (.15 mauka of t intersection 5 240669 2132030 1900 of wood valley Rd and Cane Rd) 173 J 16 .5 miles makai J17 at driveway with turtle sign "Hale Hunu" 5 240042 2132578 2090 174 J 17 .5 miles makai J18 Across pasture from io nest 5 239812 2133169 2220 175 J 18 Towards the back of wood valley at T intersection with a paved road Telephone 5 239190 2133180 2320 pole 157x ~175m before narrow bridge. 176 JJ 1 0.2 miles from 132 5 300552 2154935 177 JJ 2 0.8 miles from 132; 0.1 miles up Leilani 5 301268 2154001 177a JJ 2 0.8 miles from 132; 0.1 miles up Leilani 5 301268 2154001 178 JJ 3 1.4 miles from 132 5 302084 2153896 179 JJ 4 2.0 miles from 132; 0.1 miles hike in on N side at no outlet signs 5 303027 2154195 180 JJ 5 2.6 miles from 132; 0.1 miles hike in on S side. .6 from JJ4 intersection 5 303776 2154015 of 2 unmarked unpaved roads 181 JJ 6 3.2 miles from 132; 0.1 miles hike in on N side 5 304953 2153578 182 JJ 7 3.8 miles from 132; 0.1 miles hike in on S side 5 305873 2153079 183 K 1 Start at the end of Hue Hue St 5 193592 2182856 184 K 2 intersection of Hue Hue St and Kaloko Dr .6 miles from k1 5 193381 2181895 185 K 3 Intersection of Kaphe St(no sign) and koloko Dr. .5 from K2 5 192561 2182387 186 K 4 .5 from k3. Right before bend in road 5 192267 2181914 187 K 5 .2 miles after Maleamau on Kaloko Dr heading upslope 5 191763 2181783 188 K 6 End of Haleamanu rd .8 miles from K5 5 191608 2182989 189 K 7 Start of Makahi Rd 5 191035 2182689 190 K 8 upper intersection of Hao and Kaloko Dr. 5 190689 2181764 191 K 9 End of Hau St (mauka) 5 191468 2181130 192 K 10 .5 from intersection with Hao and Kaloko Dr. heading downslope at telephone pole 11 5 190049 2182152 193 K 11 .5 from lower intersection Hao St. and Kaloko Dr. or ,5 from k8 at Mahi Nala Kaloko pole 42 5 190498 2180824 194 K 12 .5 from k11 makai or at lower intersection b/t Hao St. and Kaloko Dr 5 189811 2181358
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195 K 13 .5 makai from k12 on Kaloko Dr. at start of Mahi St. 5 189130 2181546 196 K 14 .6 from k13 pole 13x perpendicular to Private Rd 5 188820 2180683 197 KK 1 End of Hwy 148 end of Mahie Rd 5 262902 2153251 198 KK 2 End of Amaumau Rd., at hunter check station for Makaala Reserve. 5 261782 2156063 199 KK 3 0.5 mi. From KK 2, SSE on Amaumau Rd. 5 262182 2155278 200 KK 4 0.6 mi. From KK3 on Amaumau Rd. 5 262683 2154410 201 KK 5 At 90 degree bend in Hwy 148 (Wright Rd.), 0.4 mile from junction with Amaumau Rd. 5 263812 2153798 202 KK 6 0.6 mi. From KK5 toward Hwy.11. 5 264342 2152901 203 KK 7 0.6 mi. From KK6, toward Hwy. 11 5 264789 2152089 204 KK 8 0.5 mi. From KK 7, toward Hwy. 11. 5 265214 2151413 205 KK 10 Wright Rd. At Cooper Center. 5 265947 2150299 206 KK 9 .4 miles down Laukapu Rd NW of Hwy 148 to intersection with Haunani RD 5 264758 2150864 207 KK 11 2.9 miles off Hwy 11, on Glenwood Rd. 5 271088 2159251 208 KK 12 2.2 miles off hwy 11, on Glenwood Rd. 5 271710 2158918 209 KK 13 1.7 miles off hwy 11, on Glenwood Rd. 5 271314 2158005 210 KK 14 1.0 mile off Hwy 11, in Glenwood Rd. 5 271814 2157583 211 KK 15 1mile mauka Hwy 11 on Glenwood Rd North 5 272759 2156970 212 L 1 Start on Holuaoa Road (180), .2 mile from junction with Route 190. 5 188316 2179344 213 L 2 Point 2- .5 mile Makai pull off at edge of field 5 188680 2178616 214 L 3 Point 3- ~ .5 mile, pull off mauka on side road. (Makai pull off just past side rd.) 5 189024 2177684 215 L 4 Point 4- Back on 180, .5 mile form last turn-off. Makai pull off at small banana field 5 189450 2176932 216 L 5 Point 5- .5 mile At intersection of Keopu Mauka Rd & Mamalohoa Hwy. 5 190008 2176124 217 L 6 Point 6- Mauka turn to Keopu Pl. 5 190182 2176143 218 L 7 At Keopu cemetery before Kama Lani St 5 190130 2175324 219 L 8 Point 8- Back on 180, .5 mile from last point. 5 190396 2174436 220 L 9 Point 9- .8 mile form last. 5 190732 2173164 221 L 10 Point 10- Elementary school parking lot. 5 190644 2171708 222 L 11 Point 11- Pull out just off 180, just past Doris' Place 5 190657 2170501 223 L 12 .4 from Holaloua Kona Coffee Co. 5 190933 2168746 224 LL 1 .2 miles from hwy 19 on Stainback hwy and corner of Halemanu. 5 283720 2175260 230 225 LL 2 .7 miles from hwy 19, .5 from LL1. 5 283164 2174621 310 226 LL 3 .5 mile mauka LL2 1.2 miles mauka Hwy19 5 282561 2174040 430 227 LL 4 1.7 miles mauka hwy 19 .5miles mauka LL3 @sign for Waiakea experimental station 5 282033 2173333 540 228 LL 5 2.2 miles mauka hwy 19 .5miles mauka LL4 5 281512 2172697 630 229 LL 6 .3 miles mauka from LL5 Turn Left on gravel rd @ Waiakea forest reserve sign 5 281846 2171751 680 Drive .5 miles on Road S @ turn around 230 LL 7 return to Stainback/Waiakea forest Reserve junction drive .2 miles mauka 5 280896 2172179 720
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(2,7 miles Mauka Hwy) 231 LL 8 .5 miles mauka LL7 3.2 miles mauka hwy19 5 280126 2171606 810 232 LL 9 .4 miles mauka of LL8 Turn Right on gravel Rd (3.6 mile s mauka Hwy) Drive 5 279239 2172060 890 down gravel road .5 miles 233 LL 10 Return to Stainback Rd Drive .1 miles mauka (3.7 mauka hwy19) 5 279558 2171183 920 234 LL 11 .4 miles mauka LL10 (4.1 miles mauka of hwy Turn left on gravel road and drive .5 miles) 5 279529 2170158 980 235 LL 12 Return to Stainback Rd . Drive .1 mile mauka ( 4.2 miles mauka of Hwy 19) 5 278816 2170682 1040 236 LL 13 .5 miles mauka LL12 (4.7 miles mauka of hwy 19) 5 278207 2170242 1160 237 LL 14 .5 MILES MAUKA LL13 ( 5.2 miles mauka of hwy19) 5 277505 2169765 1280 238 LL 15 .5 miles mauka LL14 (5.7 miles mauka from hwy19) 5 276745 2169206 1420 239 LL 16 .5 miles mauka LL15 (6.2 miles Mauka from hwy19) 5 276042 2168716 1540 240 LL 17 .6 miles mauka LL16 (6.8 miles mauka of hwy 19) 5 275359 2168215 1690 241 LL 18 .65 miles mauka LL17 5 274439 2167670 2000 242 M 1 Macfarms @hwy where south Mauka Rd begins Just N of Manuka State Park 5 201063 2117936 1670 243 M 2 .5 miles mauka M1 on S Boundary of Macfarms 5 201710 2118432 1920 244 M 3 1mile Mauka hwy and M1 .5 miles mauka M2 5 202351 2118891 2140 245 M 4 1.5miles mauka hwy and M1 .5 miles mauka M3 At mauka south corner of farm 5 202975 2119304 2490 246 M 5 Now Drive north along upper boundary of Macfarm @ 2450'elevation. .5 miles north of M4 5 202631 2120090 2440 247 M 6 .5 miles north of M5 5 202326 2120765 2460 248 M 7 .5 miles north of M6 5 201928 2121493 2430 249 M 8 .5 miles north of M7 @ North mauka corner of Macfarm 5 201605 2122263 2460 250 M 9 .5 miles makai of M8 (heading down north mauka boundary of Macfarms 5 200888 2122061 2250 251 M 10 .5 miles makai M9 1mile makai from mauka North corner 5 200078 2121863 2020 252 M 11 .5 miles makai M10 1.5 miles makai from mauka north corner of Macfarms 5 199344 2121543 1740 253 M 12 Drive .3 makai M11-@hwy Turn left drive until 1st right. Turn in @makai Macfarms 5 198803 2121364 1530 &drive gravel rd north to North bound( now directly makai of M11 yellow cattle guard 254 M 13 .5miles makai of M12 5 198120 2120903 1320 255 M 14 Drive makai of M13 ~.3miles (locked gate turn left (south) and drive .2 miles) 5 197797 2120428 1160 256 M 15 Drive south .5 miles from M14 5 198158 2119712 1250 257 M 16 Drive south .5miles form M15 5 198508 2118910 1220 258 M 17 Drive south .5 miles from M16 at Makai south corner of Macfarm 5 198321 2118112 1170 259 M 18 Drive mauka ~.2 miles turn south and drive ~.3 miles (drive~.1mile turn left 5 199327 2117603 1140 and go mauka a to reach hwy) 260 MM 1 Begin at gate to Kulani Prison on Stainback Road. Large orange gate, no guard. 5 263900 2164713 3980 261 MM 2 1mile makai MM1 5 265417 2164572 3750 262 MM 3 1mile makai MM2 5 266690 2165338 3450 263 MM 4 1mile makai MM3 5 268372 2165431 3200
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264 MM 5 .9miles makai MM4 @intersection of tree planting Rd and Stainback 5 269681 2165755 2970 265 N 1 Intersection of Hwy 111 and Mamalahoa Hwy. Just north of mile marker 86 5 198844 2122028 1640 266 N 2 1mile north of N1 on Mamalahoa Hwy Hoomau Ranch. Telephone pole 22 5 199196 2123501 1790 267 N 3 1mile north of N2 on Mamalahoa hwy ~.15 miles from north junction with hwy 11 5 198647 2124957 268 NN 1 .4 mile south from Stainback/N. Kulani Rd intersection 5 276369 2168142 1620 269 NN 2 .9miles south of Stainback/N. Kulani at Ihope/N.Kulani intersection 5 276881 2167374 1580 270 NN 3 .5 miles mauka Ihope/N Kulani Intersection Pole 10 5 276217 2166746 1640 271 NN 4 .5 miles mauka of NN3 at pole 20 5 275664 2166285 1830 272 NN 5 .5miles mauka of NN4 @pole 30 on Ihope Rd 5 274970 2165662 2280 273 NN 6 .5 miles past NN5 pole 39 5 274375 2165185 2200 274 NN 7 .5 miles past NN6 pole 49-covered by veg 5 273661 2164573 2360 275 NN 8 .5 miles past Rd turns into 4x4(go past dead end sign) pt. @large clearing 5 273018 2164013 2380 276 NN 9 Turn around on Ihope Rd and drive back to Peck Rd Go down N. Peck Rd 5 274633 2164367 2220 .5 miles to "y" in Rd 277 O 1 Start outside of Pahala, off 150,intersection of 150 and 180 points every mile. 5 238826 2125084 1040 Point 2 only .6 mile from first. Last point near big ball tower. 278 O 2 .6 miles mauka and west of O1 just after small yellow bridge 5 237953 2125088 1250 279 O 3 1 mile west of O2 on cane rd ~80m before "y" in rd 5 236706 2124117 1260 280 O 4 1mile west of O2 5 235564 2123178 1320 281 O 5 1mile west of O2-east side of Large Puu ~250m east of base 5 234513 2122088 1220 282 O 6 1mile west of O2-west side of large Puu 5 233390 2121157 1230 283 O 7 1 mile west O6 5 232790 2119779 1160 284 O 8 1.2 miles west of O7. Pull off on right. Green Gate 5 231563 2118373 1270 285 O 9 1mile west O8. At gravel rd. going mauka 5 230624 2117261 1340 286 O 10 1 mile west O9 @ double pipe gate on makai side of Rd 5 230371 2115922 1360 287 O 11 1.6 miles west of O10 @ pull off going mauka. 177m before Ballantenna tower 5 229745 2113508 1390 288 P 1 Mile marker 51 on Hwy 11 ~.3 miles from Pahala 5 240418 2125375 1040 289 P 2 Mile Marker 50 ~.1 miles mauka @ pull off just before small bridge 5 241091 2126952 1290 290 P 3 Hwy 11, mile 46.9 on Pull on mauka side of Rd 5 243521 2131130 1980 291 P 4 Hwy 11, mile 46.1. Kapapala Ranch sign 5 243521 2132279 292 Q 1 Hwy 11. West of Waiohinu. Mile 68.7. 5 221208 2109754 1760 293 Q 2 Hwy 11 west of Waiohinu. Mile 67.2, mauka of hwy. Near large water tank. 5 223311 2109782 1410 just as road curves to the right. ~125m Mauka 294 Q 3 A4WD ONLY Road, ~0.2 mile west of Waiohinu, mauka of hwy. Point is 0.2 mi. 5 224476 2110616 1110 Up road at large water tank Whalings Hideaway sign 295 Q 4 Kaalaiki Rd. Leading mauka .25 out of Naalehu. Point is at backside of Naalehu Cemetery. 5 227650 2109984 670 296 Q 5 Turn makai Naalehu town on NIU pt @ corner NIU/Poha 5 228384 2109327 520
85
297 Q 6 ~0.6 mi. east of Naalehu fruit stand 5 229174 2109933 859 298 R 1 Begin at Pololu Lookout. Head toward Hawi. 5 214304 2236424 299 R 2 0.55 mi. From R1 at sharp right hand turn with creek 5 213760 2236980 300 R 3 0.5 mi. From R2 at gated dirt road on left. 5 213288 2237637 301 R 4 0.7 mi. From R3. Just past AAll Saints @ Church. 5 212555 2238366 302 R 5 0.75 Mi. From R4 at junction of 2 dirt roads. Left dirt road is gated. 5 211803 2238442 303 R 6 Kalahikiola Rd. Off Hwy. 270 0.6 mi. At Kalahikiola church 5 208085 2238543 304 R 7 At junction of Kalahikiola Rd. And Hwy. 270. 5 208351 2239173 305 R 8 Junction of Hwy. 250 and road to Honomakau (Kapa'au) 5 204123 2237289 306 R 9 0.6 mi. From R8 . Small dirt road on right with gate. 5 204856 2237783 307 R 10 0.5 mi. From R9 continuing NE. 5 205411 2238235 308 R 11 Dirt Rd. To right off Hwy. 250. Across from Episcopal church, west of 5 206736 2239495 Kapaau. Approx. mile 22.9. 309 S 1 Hwy. 270, Mahukona lighthouse Rd. 5 197096 2234869 310 S 2 Hwy. 250, mile 12.2. 5 208317 2227053 311 S 3 Hwy. 250, mile 8.7. 5 211026 2222709 312 S 4 Hwy. 250, mile 3.2. 5 216955 2217210 313 T 1 0.7 mi. Down Hapuna Beach Park Rd. makai Hwy. 19. 5 204446 2212622 314 T 2 Hwy. 19, mile 82.5, 0.1 mi. Down road makai of hwy. 5 193212 2196319 315 T 3 Kaiminani Rd., 0.2 mi. mauka of Hwy. 19. at intersection with Pukiawe St 5 811343 2183750 316 T 4 Hwy. 19, mile 95, 0.1 mi. Down dirt rd. Makai of hwy. 5 811134 2181387 317 T 5 Kaloko Park Rd., 0.1 mi. Makai of Hwy. 19. 5 812075 2179453 318 U 1 Ocean View Subdivision. Corner of Donola Dr. and Bamboo Ln 5 210853 2112576 319 U 2 corner of Reef Pkwy and Princess Kaulani Rd 5 211852 2113828 320 U 3 Corner of Luau Dr and Plumeria Rd 5 211852 2114580 321 U 4 Corner of Kona and Iwalani 5 212359 2115543 322 U 5 Corner of Orchid and Mahimahi 5 207251 2117251 323 U 6 Corner of Palm Parkway and Lotus Blossom Ln 5 206763 2116244 324 U 7 at dead end of Ocean View Pkwy past intersection with Leilani 5 205950 2115560 325 U 8 at dead end of Hukilaa Dr past intersection with Tree Fern 5 205421 2114942 326 U 9 Corner of Aloha and Hula ln 5 204950 2114020 327 U 10 Corner of Ginger Blossom and Aloha Blvd 5 206098 2114380 328 U 11 intersection of Sea Breeze and Kona Dr 5 206033 2113505 329 U 12 intersection of Lotus Blossom and Kona Dr 5 207508 2114045 330 U 13 intersection of Lotus Blossom and Coconut 5 207128 2115175 331 U 14 Orchid circle Makai 5 207719 2115885 332 U 15 King Kamehemeha Blvd and Palm Pkwy 5 208289 2116773
86
333 U 16 Corner of Catamaran Ln and Mahimahi Dr 5 208739 2117720 334 U 17 Corner of Hukilau & Catamaran 5 209265 2116278 335 U 18 Intersection of Aloha Blvd and King Kamehameha 5 208740 2115242 336 U 19 Corner of Kona and Paradise Pkwy. 5 208566 2114325 337 U 20 Corner of Luau Dr and Orchid Pkwy. 5 208510 2113470 338 U 21 Corner of Luau Dr and Hawaii Blvd. 5 207380 2113066 339 U 22 Corner of Keaka Pkwy and Lehau Pkwy. 5 208368 2112601 340 U 23 corner of Donola Dr and Paradise Pkwy. 5 209326 2112089 341 U 24 Tiki Ln and Keaka Pkwy. 5 209891 2113112 342 U 25 Coral Pkwy and Catamaran Ln. 5 209870 2114380 343 U 26 Sea Breeze and Reef Pkwy. 5 210368 2115326 344 U 27 Koa and Coconut 5 210912 2116335 345 U 28 Tradewind Blvd and Palm Pkwy. 5 210150 2117355 346 U 29 Ohia dr. and Tradewind Blvd 5 209753 2118453 347 U 30 Catamaran Ln and Outrigger Dr. 5 208368 2118896 348 U 31 Catamaran Ln and Poinciana Dr 5 208031 2120001 349 U 32 Seaview and Tradewind Blvd 5 209289 2120014 350 U 33 Pineapple Circle Mauka 5 210721 2119459 351 V 1 Ocean View subdivision. Makai of hwy. .1 miles down Prince 5 207739 2112208 Kuhio Rd. toward Pohue Bay. 352 V 2 .6 miles ... 5 207409 2111520 353 V 3 1.1 miles... 5 207020 2110789 354 V 4 1.6 miles... 5 206635 2109899 355 V 5 Turn left on Lauhala and drive .5 miles. 5 207330 2109561 356 V 6 1 mile down Lauhala. 5 208028 2109201 357 V 7 turn left on Kohala. Drive .5 miles. 5 208778 2109844 358 V 8 1 mile mauka on Kohala. 5 209129 2110584 359 V 9 1.5 miles mauka on Kohala. 5 209461 2111174 360 V 10 turn left on maile .5 miles. 5 208734 2111944 361 V 11 left on Prince Kuhio then left on bougainvillea .5 miles. 5 208404 2111642 362 V 12 down Bougainvillea then left Kamaaina Blvd .1 miles mauka 5 209893 2111110 363 W 1 Road to the Sea. 0.1 miles Makai from Highway. 5 205031 2113672 364 W 2 .6 miles makai 5 204684 2112945 365 W 3 1.1 miles makai. 5 204362 2112268 366 X 1 Macfarms south boundary makai .5 miles makai of hwy 19 and M1 5 200422 2117444 1420 367 X 2 .5 miles makai X1 (1 mile makai of Hwy11) 5 199725 2116901 1210 368 Y 1 mile marker 12 5 265362 2179629
87
369 Y 2 mile marker 13 5 264180 2179241 370 Y 3 mile marker 14 5 262593 2178707 371 Y 4 mile marker 15 5 261025 2178417 372 Y 5 mile marker 16 5 259493 2178203 373 Y 6 mile marker 17 5 258090 2177442 374 Y 7 mile 17.5 on Saddle rd. 5 257485 2177431 375 Y 8 mile marker 18 on Saddle Rd. 5 256768 2177417 376 Y 9 mile 18.5 5 255917 2177323 377 Y 10 mile marker 19 on Saddle Rd. 5 255175 2177351 378 Y 11 mile 19.5 5 254385 2177063 379 Y 12 mile 20... 5 253613 2176797 380 Y 13 mile 20.5... 5 252949 2176774 381 Y 14 mile 21... 5 252105 2176646 382 Y 15 mile 22 5 250937 2177303 383 Y 16 mile 23 5 249278 2177917 384 Y 17 mile 24 5 247621 2178090 385 Y 18 mile 25 5 246105 2178402 386 Y 19 mile 28 5 241393 2178943 387 Y 20 Mauna Kea State Park 5 235410 2185698 388 Y 21 1 mile up rd with check station and Palila 5 225629 2193365 389 Y 22 2 mile up rd with check station and Palila 5 226442 2193577 390 Y 23 3 mile up rd with check station and Palila 5 227349 2194535 391 Y 24 4 mile up rd with check station and Palila. At gate for "Mauna Kea Forest 5 228322 2195092 Reserve Puu Laau" Forest Reserve Puu Laau" 392 Z 1 ~ 1 mile E of barrier on Lower Cane Haul Rd. 5 239016 2225052 393 Z 2 1 mile east of Z1 5 240371 2224155 394 Z 3 1.2 miles from Z2, at intersection of Mauka rd. & Lower Cane Haul rd. 5 240126 2223634 395 Z 4 0.5 miles from Hwy 19 on Airstrip rd at sharp right hand turn. 5 238864 2222620 396 Z 5 1.0 mile from Z4 5 237194 2222778 397 Z 6 1.0 mile from Z5 5 235682 2223467 398 Z 7 0.95 miles from Z6 at Mauka pullout 5 234212 2223577 399 Z 8 1.15 miles from Z7 at Mauka rd pullout 5 232420 2224054
88 89
bb bbb b bbbb b b
b b b b bbbbbb b b bbbb b bb b bbb bbbbb
b bbb b bbbbb b b bb b bbbb b bb b bbbb bb bb bb b bb bbbbbbbb b bbbb b bb bbbbbbb bbbbbbbb bbb bbb bbbb bbb bb bb b bbbb bbbbbbbbbbb bb bbbbb bbb bbbb bb b bbbb b b bbbbbb bb bbbbbb bbbbb bbb bbbbb bbbbb b bb bbb bbbb b b bb b bbbb bbb b bb bbbbbbbb bbbb b b b bb bbbbbbbb bb bbbb b b bb bb b
bbb bb b bb bbbbb bbb bb bbbb bbbbbb bbbb b bb bbb bb b bbbbbbbb bbb bb b b bbbb bbbbbbbb b bbbbbbbbbbb b b b bbbbbbb b bbbbb bbb bbb N b January survey points (399)
0 1020304050Kilometers
Figure A.2. Locations of the January 1998 and 1999 survey points.
90
APPENDIX B
‘Io Survey Results
91
Table B.1. Summary of ‘io density and absolute abundance (all ages classes combined) estimates by habitat type, calculated by program DISTANCE from point counts during January 1998. Effective detection radius (EDR) and detection probability (P) based on global detection function: 520.0 ± 59.1, 0.1768 ± 0.0396.
No. Total No. 'Io No. Poi- Obs- Esti- Enc. of Habitata nts vd. mateb SE %CV 95%CI df Ratec 'Iod All Habitats 399 78 ------1,660
Fallow 34 7 0.0024 0.0011 46.0 0.0010-0.0059 58 0.21 42 Sugarcane Exotic Trees, 54 11 0.0024 0.0011 45.8 0.0010-0.0060 87 0.20 178 Shrubs, Grasses Orchards 44 13 0.0035 0.0012 34.6 0.0018-0.0068 98 0.30 26
Grass 42 7 0.0029 0.0009 46.5 0.0008-0.0049 68 0.17 154 Dominated Shrub 15 1 0.0019 0.0009 44.4 0.0008-0.0046 93 0.07 290 Dominated Mature Native 56 9 0.0033 0.0011 33.7 0.0017-0.0064 119 0.16 192 Forest Native-Exotic 55 16 0.0015 0.0011 72.0 0.0004-0.0061 19 0.29 44 Forest Exurban 16 2 0.0004 0.0003 73.8 0.0001-0.0016 78 0.13 61
Pioneer Native 65 2 0.0008 0.0008 102.6 0.0001-0.0059 16 0.03 91 Forest Native Forest 13 10 0.0092 0.0040 43.03 0.0040-0.0214 23 0.77 582 With Grass Mamane-Naio 5 0 ------Forest Urban ------
Lava ------a Habitats are shown in Fig.1. b Density estimate is the number of hawks/hectare. c Encounter rate is the number of hawks expected to be observed per point. d Total number of hawks in each habitat was calculated by multiplying the density estimate by the area of each habitat (Fig.1). Total number of hawks in all habitats and for the entire island is the summation of the total number of hawks in each habitat.
92
Table B.2. Summary of ‘io density and absolute abundance (all ages classes combined) estimates by habitat type, calculated by program DISTANCE from point counts during June 1998. Effective detection radius (EDR) and detection probability based on global detection function: 650.0 ± 40.7, 0.1477 ± 0.0185.
No. Total No. 'Io No. Poi- Obs- Esti- Enc. of Habitata nts vd. mateb SE %CV 95%CI df Ratec 'Iod All Habitats 677 178 ------1,457
Fallow 53 29 0.0040 0.0011 27.0 0.0024-0.0068 83 0.55 70 Sugarcane Exotic Trees, 61 20 0.0024 0.0010 42.0 0.0011-0.0053 72 0.33 174 Shrubs, Grasses Orchards 46 17 0.0028 0.0009 31.0 0.0015-0.0051 64 0.37 21
Grass 89 15 0.0013 0.0004 30.0 0.0007-0.0023 127 0.17 99 Dominated Shrub 51 4 0.0006 0.0004 61.5 0.0002-0.0019 54 0.08 68 Dominated Mature Native 51 19 0.0027 0.0007 27.8 0.0016-0.0046 78 0.37 405 Forest Native-Exotic 71 13 0.0015 0.0005 30.8 0.0008-0.0027 99 0.18 87 Forest Exurban 68 5 0.0006 0.0003 53.4 0.0002-0.0015 75 0.07 16
Pioneer Native 66 8 0.0009 0.0004 43.7 0.0004-0.0021 77 0.12 153 Forest Native Forest 63 48 0.0057 0.0012 21.0 0.0038-0.0087 135 0.76 364 With Grass Mamane-Naio 22 0 ------Forest Urban 17 0 ------
Lava 19 0 ------a Habitats are shown in Fig.1. b Density estimate is the number of hawks/hectare. c Encounter rate is the number of hawks expected to be observed per point. d Total number of hawks in each habitat was calculated by multiplying the density estimate by the area of each habitat (Fig.1). Total number of hawks in all habitats and for the entire island is the summation of the total number of hawks in each habitat.
93
Table B.3. Summary of ‘io density and absolute abundance (all ages classes combined) estimates by habitat type, calculated by program DISTANCE from point counts during September 1998. Effective detection radius (EDR) and detection probability based on global detection function: 577.3 ± 41.1, 0.1069 ± 0.0153.
No. Total No. 'Io No. Poi- Obs- Esti- Enc. of Habitata nts vd. mateb SE %CV 95%CI df Ratec 'Iod All Habitats 677 144 ------1,289
Fallow 67 27 0.0038 0.0010 27.7 0.0022-0.0065 114 0.40 66 Sugarcane Exotic Trees, 52 10 0.0019 0.0008 40.4 0.0008-0.0041 66 0.19 137 Shrubs, Grasses Orchards 41 16 0.0038 0.0012 31.5 0.0021-0.0070 62 0.39 29
Grass 98 18 0.0017 0.0006 33.2 0.0009-0.0033 140 0.18 134 Dominated Shrub 35 1 0.0003 0.0003 101.0 0.0000-0.0020 35 0.03 32 Dominated Mature Native 57 7 0.0012 0.0006 48.0 0.0005-0.0031 67 0.12 180 Forest Native-Exotic 73 20 0.0025 0.0008 30.3 0.0014-0.0046 113 0.27 148 Forest Exurban 76 13 0.0017 0.0006 36.4 0.0008-0.0034 103 0.17 49
Pioneer Native 63 9 0.0014 0.0007 51.7 0.0005-0.0038 72 0.14 231 Forest Native Forest 48 23 0.0045 0.0012 27.0 0.0026-0.0076 86 0.48 283 With Grass Mamane-Naio 24 0 ------Forest Urban 5 0 ------
Lava 38 0 ------a Habitats are shown in Fig.1. b Density estimate is the number of hawks/hectare. c Encounter rate is the number of hawks expected to be observed per point. d Total number of hawks in each habitat was calculated by multiplying the density estimate by the area of each habitat (Fig.1). Total number of hawks in all habitats and for the entire island is the summation of the total number of hawks in each habitat.
94
Table B.4. Summary of ‘io density and absolute abundance (all ages classes combined) estimates by habitat type, calculated by program DISTANCE from point counts during January 1999. Effective detection radius (EDR) and detection probability based on global detection function: 597.8 ± 54.9, 0.1239 ± 0.0228.
No. Total No. 'Io No. Poi- Obs- Esti- Enc. of Habitata nts vd. mateb SE %CV 95%CI df Ratec 'Iod All Habitats 399 72 ------1,061
Fallow 27 3 0.0010 0.0006 58.5 0.0003-0.0032 32 0.11 17 Sugarcane Exotic Trees, 74 25 0.0029 0.0010 34.5 0.0015-0.0058 121 0.34 215 Shrubs, Grasses Orchards 37 9 0.0022 0.0010 44.3 0.0009-0.0052 51 0.24 17
Grass 37 9 0.0022 0.0010 44.3 0.0009-0.0052 51 0.24 170 Dominated Shrub 13 1 0.0007 0.0007 101.7 0.0001-0.0051 13 0.08 79 Dominated Mature Native 42 10 0.0022 0.0009 41.7 0.0010-0.0049 61 0.24 324 Forest Native-Exotic 53 9 0.0015 0.0006 42.2 0.0007-0.0035 76 0.06 89 Forest Exurban 18 1 0.0005 0.0005 101.7 0.0001-0.0037 18 0.06 15
Pioneer Native 85 4 0.0004 0.0003 63.4 0.0001-0.0015 99 0.05 71 Forest Native Forest 9 1 0.0010 0.0010 101.7 0.0001-0.0074 9 0.11 64 With Grass Mamane-Naio 4 0 ------Forest Urban ------
Lava ------a Habitats are shown in Fig.1. b Density estimate is the number of hawks/hectare. c Encounter rate is the number of hawks expected to be observed per point. d Total number of hawks in each habitat was calculated by multiplying the density estimate by the area of each habitat (Fig.1). Total number of hawks in all habitats and for the entire island is the summation of the total number of hawks in each habitat.
95
APPENDIX C
Island Habitat Map
96
Habitat types on the island of Hawaii (total area: 1,047,087) 150,785 ha. Mature Native Forest 63,337 ha. Mature Native Forest with Grass Understory 166,152 ha. Pioneer Native Forest N 23,650 ha. High Elevation Pioneer Native Forest 53,411 ha. Mamane-Naio Native Forest 58,301 ha. Native-Exotic Forest 73,307 ha. Exotic Trees, Shrubs, Grasses 0 102030Kilometers 17,413 ha. Fallow Sugarcane 7,628 ha. Orchards 77,444 ha. Grass Dominated 114,155 ha. Shrub Dominated 20,709 ha. High Elevation Shrubs-Grasses 156,921 ha. Lava 29,288 ha. Exurban 34,547 ha. Urban
Figure C.1. Island of Hawaii map showing 15 habitat types and the land area (ha) associated with each.
97
APPENDIX D
‘Io Nest Locations
98
% %% % %
% % % % % %
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%
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% % % % %% % % %% %% %% %
% % %
N Coastline % 1998 hawk nests Major roads 0 1020304050Kilometers 305 m Contour lines
Figure D.1. Locations of active ‘io nests (n = 50) during the 1998 field season.
99
% %%% % % % % % % % % % % % %% %
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% %
%
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% % % % % % % % % % % %%%% % % %% %%% %%% %
% % % %
%
N Coastline % 19991998 hawk nests Major roads 0 1020304050Kilometers 305 m Contour lines
Figure D.2. Locations of active ‘io nests (n = 62) during the 1999 field season.
100
APPENDIX E
Results From Environmental Contaminant Analyses
101
Table E.1. Concentrations of organochorines and PCBs measured in five Hawaiian hawk eggs. Concentrations are ppm fresh wet weight. The lower limit of detection for organochlorines and PCBs was 0.01, and 0.05 for toxophene. A procedural blank indicated no background contamination of analytical equipment or reagents. Results of duplicate analyses and spike recoveries for all contaminants were within acceptable ranges for method precision and accuracy. USFWS Patuxent Analytical Control Facility analyzed the eggs.
EGG 1 EGG 2 EGG 3 EGG 4 EGG 5 CONTAMINANT 98N0014 98N0033 98N0047 99N005 99N0051
TOTAL DDTa 0.06 0.05 0.05 0.16 0.05 p,p' DDE < 0.01 0.01 < 0.01 0.12 < 0.01
TOTAL CHLORDANEb 0.04 0.04 0.05 0.05 0.05
PCB-TOTAL < 0.05 0.07 < 0.05 0.27 0.05
ENDRIN < 0.01 < 0.01 < 0.01 < 0.01 < 0.01
DIELDRIN < 0.01 < 0.01 < 0.01 < 0.01 < 0.01
MIREX < 0.01 < 0.01 < 0.01 < 0.01 < 0.01
HCB < 0.01 < 0.01 < 0.01 < 0.01 < 0.01
ALPHA BHC < 0.01 < 0.01 < 0.01 < 0.01 < 0.01
BETA BHC < 0.01 < 0.01 < 0.01 < 0.01 < 0.01
TOXAPHENE < 0.05 < 0.05 < 0.05 < 0.05 < 0.05
a Total DDT defined here as summed o,p'-DDD, o,p'-DDE, o,p'-DDT, p,p'-DDD, p,p'-DDE, and p,p'- DDT. b Total chlordane defined here as sum of alpha chlordane, cis-nonachlor, gamma chlordane, heptachlor epoxide, oxychlordane, and trans-nonachlor.
102
Table E.2. Concentrations of heavy metals measured in five Hawaiian hawk eggs. Concentrations are ppm fresh wet weight. A procedural blank indicated no background contamination of analytical equipment or reagents. Results of duplicate analyses and spike recoveries for all metals were within acceptable ranges for method precision and accuracy except for lead - results are discarded. USFWS Patuxent Analytical Control Facility analyzed the eggs.
EGG 1 EGG 2 EGG 3 EGG 4 EGG 5 METAL 98N0014 98N0033 98N0047 99N005 99N0051
Aluminum (Al)a 1.8 < 0.617 < 0.65 < 0.728 < 0.758
Arsenic (As)a < 0.063 < 0.0617 < 0.065 < 0.0728 < 0.0758
Boron (B)a 1.58 1.14 0.79 < 0.291 < 0.303
Barium (Ba)a < 0.126 < 0.123 < 0.13 < 0.146 < 0.152
Berylium (Be)a < 0.0126 < 0.0123 < 0.013 < 0.0146 < 0.0152
Cadmium (Cd)a < 0.0126 < 0.0123 < 0.013 < 0.0146 < 0.0152
Chromium (Cr)a < 0.063 0.33 0.34 0.61 0.58
Copper (Cu)a 1.61 0.91 0.68 0.73 0.51
Iron (Fe)a 7.27 15.44 8.72 9.2 15.23
Mercury (Hg)a < 0.0252 < 0.0247 < 0.026 < 0.0291 < 0.0303
Magnesium (Mg)a 77.04 74.12 87.2 96.52 97.5
Manganese (Mn)a 0.14 0.21 0.17 0.16 0.4
Molybdenum (Mo)a < 0.252 < 0.252 < 0.26 < 0.291 < 0.303
Nickel (Ni)a 0.14 0.32 0.18 0.44 0.57
Selenium (Se)a 0.07 0.12 0.11 0.07 0.17
Strontium (Sr)a < 0.063 0.35 0.3 0.09 < 0.0758
Vanadium (V)a < 0.063 < 0.0617 < 0.065 < 0.0728 < 0.0758
Zinc (Zn)a 5.57 6.87 5.22 4.82 4.86
a Detection limits for each metal were: Al (0.63 - 0.758), As (0.063 - 0.0758), B (0.252 - 0.303), Ba (0.126 - 0.152), Be (0.0126 - 0.0152), Cd (0.0126 - 0.0152), Cr (0.063 - 0.0758), Cu (0.063 -0.0758), Fe (0.63 - 0.758), Hg (0.0252 - 0.0303), Mg (0.63 - 0.758), Mn (0.126 - 0.152), Mo (0.252 - 0.303), Ni (0.063 -0.0758), Se (0.063 -0.0758), Sr (0.063 -0.0758), V (0.063 -0.0758), Zn (0.126 - 0.152).