**Preassessment Data Report #6:**

**Detection probabilities for bird carcasses on beaches of Unalaska
Island, Alaska, following the wreck of the M/V *Selendang Ayu***

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G. V. Byrd^1^

J. H. Reynolds^2^

*^1^U. S. Fish and Wildlife Service, Alaska Maritime National Wildlife
Refuge, 95 Sterling Highway, Suite 1, Homer, AK 99603*

*^2^U. S. Fish and Wildlife Service, Division of Natural Resources,
MS-221, 1011 E. Tudor Road, Anchorage, AK 99503*

This document should be referenced as:

Byrd, G.V. and J.H. Reynolds. 2006a. Detection probabilities for bird
carcasses on beaches of Unalaska Island, Alaska, following the wreck of
the M/V Selendang Ayu. U.S. Fish and Wildlife Service, Alaska Maritime
National Wildlife Refuge, Homer, AK.

cover photo:

Carcass collection team on beach segment SKS 4, with flagged oiled bird
carcass in the foreground, following the wreck of the M/V Selendang Ayu,
Unalaska Island (photo taken 26 December 2004 by staff of the Alaska
Maritime National Wildlife Refuge).

**ABSTRACT**

Bird carcass surveys were conducted as part of the pre-assessment phase
of response to the M/V *Selendang Ayu* oil spill off the coast of
Unalaska Island. The probability a survey team would detect an oiled
carcass present on the beach was expected to be less than 100%. To
estimate the detection probability a field study was conducted in which
two survey teams each made two passes on a number of beaches. The
probability of a single team detecting an oiled carcass on a single pass
was then estimated using standard mark-recapture models. Less than 50%
of all carcasses present on a beach segment were detected in a single
pass by a survey team. The relatively low detection probability and low
persistence rates (Byrd and Reynolds 2006b) indicate that only a very
small proportion of all deposited carcasses were counted during beach
searches on Unalaska Island.

**INTRODUCTION**

On 8 December 2004, the M/V *Selendang Ayu* ran aground and broke in
half in rough seas off Unalaska Island, Alaska (53°38\'N, 167° 07\'W).
An estimated 354,218 gallons of oil (339,538 gallons of bunker oil \[IFO
380\] and 14,680 gallons of marine diesel and miscellaneous oils) were
discharged. Numerous bird carcasses were recovered during beach searches
in the months following the spill as part of the typical pre-assessment
phase of response to an oil spill, which includes collecting data from
which to estimate the total number of animals affected by the event
(Ford *et al.*, 1987; Page *et al*., 1990; Piatt *et al.*, 1990; Burger,
1992a, Flint *et al.* 1999). Recovered carcasses represent only a
fraction of the total number deposited on beaches (Flint *et al.* 1999)

Carcasses found by observers on a specific beach at any given time after
a mortality event are a result of three processes: (1) the rate at which
carcasses are deposited on beaches, (2) their persistence once on the
beach, and (3) the probability of observers detecting them when
surveying the beach (Flint *et al.* 1999). These components vary
depending on site and environmental characteristics present in each
specific mortality event. For example, carcass deposition rate can vary
with factors such as beach type (Bodkin and Jameson, 1991, Flint *et
al.* 1999), persistence rates can vary with factors such as beach type,
time since deposition, weather, tidal activity, carcass size and
scavenger activity (Bodkin and Jameson, 1991; Burger, 1992b, 1993; Van
Pelt and Piatt, 1995, Ford et al. 1996, Fowler and Flint 1997, Ford in
press), and detection probabilities can vary with factors such as beach
type and weather conditions like presence or absence of snow (Fowler and
Flint 1997).

Detection probability is specifically defined as the probability that a
carcass known to be on the beach will be found by a searcher. Detection
probabilities of carcasses can be estimated using mark-recapture
(Pollock *et al.*, 1990).

This report summarizes carcass detection probability estimates for beach
surveys on Unalaska Island, Alaska in January 2005. Carcass persistence
rate estimates are reported in a companion document (Byrd and Reynolds
2006b).

**Methods**

*Study Design*

Following a reconnaissance, all beaches in the oil spill area were
classified to one of four types: *exposed* -- high impact beaches
normally exposed to waves, often with steep angles indicating frequent
impacts; *catchment* -- beaches with areas where large amounts of debris
had accumulated; *protected* -- beaches not normally exposed to waves
from the open sea; *unavailable* -- segments that were either too short
(\< 100m) or not safely accessible by the Tiglax-based crew. . The spill
area was comprised of 18% exposed beaches, 6% catchment, 31% protected,
and 45% non-accessible coast (cliffs or other unwalkable segments of
coastline). Beach segments were defined based on physical shore zone
character following Owens and Sergy (2000).

Resources allowed implementation of the detection study on a maximum of
five beach segments. Five beach segments were selected from the
stratified random sample of exposed, catchment, and protected beaches
selected for the Tiglax-based beached animal surveys (Byrd et al. 2005).
The detection study selection was stratified in order to assess effects
of beach type. The five beaches were purposively selected within each
strata so that there were two exposed, one catchment, and two protected.

All beach surveys were conducted by three-person teams. Two teams (each
with three members) of trained observers were used to conduct the
detection study during the last few days of the first week of the
pre-assessment beach surveys. The teams followed regular beach survey
protocol during the detection study (Byrd et al. 2005). The detection
study employed carcasses where they were naturally deposited on each
study beach rather than artificially placed carcasses.

The probability that a carcass present on a beach was detected by a team
on a single survey was estimated using a slight modification of the
protocol outlined in Nichols et al. (2000). One team made a single pass
of the selected beach segment, searching for carcasses in the normal
method employed for the Pre-Assessment beach surveys (Byrd et al. 2005).
Rather than immediately collecting carcasses, the team recorded each
carcass' location and subtly marked it in a manner which would not
increase detection, e.g., by place flagging underneath the carcass or a
nearby large rock or log so that it could not be seen, and then clearly
noted its location in field notes or using a GPS receiver. The second
team, having not watched the first team's efforts, searched the same
beach segment using the same process, again marking and leaving each
detected carcass in place as described for the first team. Each team
then independently repeated the search, making a second pass back down
the beach segment, again leaving each detected carcass in place after
recording its location, recording whether or not it was already marked,
and by whom, and, if unmarked, subtly marking it in a manner which would
not increase detection. After both teams had made two independent
passes, all carcasses were collected. This design produced a set of
detected carcasses each with two detection histories: one from each
team's two passes.

*Analysis*

Conditional on the number of carcasses detected in a beach segment, the
dual-detection histories follow a Cormack-Jolly-Seber design for a
closed population, allowing use of standard mark-recapture models for
estimating mean detection rate (Pollock et al. 1990).

Nine models were considered, allowing for potential variation in
detection probability (P) across beaches, across beach type (Catchment,
Protected, Exposed), across team (1 or 2), and/or across survey pass
(first, second).

Pbtp detection probability varies with b - Beach, t- Team, and p - Pass.

Pbttp detection probability varies with bt - Beach Type, Team and Pass;

Pb.p detection probability varies with Beach and Pass, remains equal
across Teams;

Pbt.p detection probability varies with Beach Type and Pass, remains
equal across Teams;

Pbtt. detection probability varies with Beach Type and Team, remains
equal across Passes;

P.tp detection probability varies with Team and Pass, remains equal
across Beaches;

Pbt.. detection probability varies with Beach Type, remains equal across
Teams and Passes;

P..p detection probability varies with Passes, remains equal across
Beaches and Teams;

P\... detection probability remains equal for each Beach, Team and Pass.

Each model was fit, using maximum likelihood methods, in program MARK
(White and Burnham 1999). When there were competing plausible models,
model selection uncertainty was accounted for in the parameter
estimates, standard errors and confidence intervals by model averaging
using AIC (Akaike Information Criteria) weights (Burnham and Anderson
2002). Summary graphs were made in S-Plus 6.2 (Insightful, Inc.,
Seattle, WA.).

**Results**

Detection studies were conducted on 5 beach segments (Appendix 1).
However, data from the catchment and protected beaches were pooled for
analysis due to the small number of carcasses found. Thus the beach type
factor was redefined as Catchment/Protected versus Exposed.

Models P..p and P.tp were identified as the best (Table 1),
demonstrating detection systematically varied with pass and among teams.
Not surprisingly, detection probability increased on the second pass,
roughly from 40% to 70% (Table 2, Figure 1). While statistically
significant, the magnitude of the effect of team was inconsequential
compared to the effect of pass (Figure 1, Table 2). The estimated
detection rate for a beach survey team making a single pass was 41%
(weighted average of first pass detection probabilities across teams and
beaches using weights proportional to 1/(standard error)\^2, Table 2).

**DISCUSSION**

Carcass detection probability was less than 100% on every beach survey
(Table 1). This was also observed in the only other oil spill study to
estimate carcass detection probability by searching for naturally
deposited carcasses in a spill zone (Fowler and Flint 1997). A single
search by either team is estimated to detect less than half the
carcasses known to be present (Table 2).

Bird carcass detection probabilities in natural habitats have been
reported ranging from 45-93%, with generally lower probabilities on
beaches than in other terrestrial habitats (Tobin and Dolbeer 1990,
Philibert et al. 1993, Linz et al. 1991, Fowler and Flint 1997).

Considering detection on just beaches, the estimates reported here are
lower than those reported in a study of king eider carcasses (Fowler and
Flint 1997). This is likely due to study differences in carcass size and
cryptic coloration. Most carcasses in the current study were of species
with smaller bodies than king eiders. Additionally, most "carcasses" in
the current study were heavily scavenged and consisted of only a few
fragments, such as a wing, which were much more difficult to detect
compared to a large, fresh and intact whole bird.

Detection probability did not vary significantly across beach type
(Catchment/Protected vrs Exposed) (Table 1). While detection probability
varied significantly across search teams, the effect was relatively
small (Table 2) compared to that reported in other studies (Tobin and
Dolbeer 1990, Philibert et al. 1993, Linz et al. 1991).

**Conclusions and Recommendations**

The relatively low detection probabilities and low persistence rates
(Byrd and Reynolds 2006b) indicate that only a very small proportion of
all carcasses would be counted during beach searches on Unalaska Island.
These results emphasize the importance of estimating these parameters
for each incident as such estimates are essential for modeling total
mortality associated with specific events (Flint et al. 1999).

**ACKNOWLEDGEMENTS**

Paul Flint made essential contributions to this report. Tremendous
thanks to the following individuals for the their assistance in the
pre-assessment studies and in reviewing the report: the crew of the R/V
Tiglax - Kevin Bell, Dan McNulty, Dennis Haunschild, John Faris, Dan
Erickson, Joe Isenhour, Bob Ward, Eric Nelson; Jeff Williams, Leslie
Slater, Becky Howard, Bill Schaff, Greg McClelland, Ty Wyatt, Janis
Krukof, Kent Sundseth, Jeff Lewis, [C]{.underline}ris Dippel, Andy
Aderman, Don Dragoo, Arthur Kettle, Greg Thomson, Steve Kendall, Gary
Wheeler, Pat Walsh, Fred Broerman, Ken Gates, Kristine Sowl, Thomas
Siekaniec, Clay McDermott, Delia Person, Michael Winfree, Suzann
Speckman, Merban Cebrian, Jennie Wetzel, Ingrid Harrald, and R. Glenn
Ford.

**REFERENCES**

Bodkin, J. L., and R. J. Jameson. 1991. Patterns of seabird and marine
mammal carcass deposition along the central California coast, 1980-1986.
Canadian Journal of Zoology 69:1149-1155.

Burger, A. E. 1992a. The effects of oil pollution on seabirds off the
west coast of Vancouver Island. In The Ecology, Status, and Conservation
of Marine and Shoreline Birds on the West Coast of Vancouver Island (K.
Vermeer, R. W. Butler & K. H. Morgan, eds.), pp. 120-128. Occasional
Paper No. 75, Canadian Wildlife Service, Ottawa, Canada.

Burger, A. E. 1992b. Beached bird surveys in British Columbia, annual
report, March 1992. Unpubl. rep., Emergency Services Branch, British
Columbia Environment, Victoria, BC, Canada, 27 pp.

Burger, A. E. 1993. Beached bird surveys in British Columbia, annual
report, March 1993. Unpubl. rep., Emergency Services Branch, British
Columbia Environment, Victoria, BC, Canada, 19 pp.

Burnham, K. P., and D. R. Anderson. 2002 . Model Selection and
multimodel inference: a practical information-theoretic approach. Second
edition. Springer-Verlag, New York Inc., New York, New York.

Byrd, G.V., J. Reynolds, G. Ford, J. Piatt, and P. Flint. 2005. Beached
animal surveys near the wreck of the Selendang Ayu on Unalaska Island,
Alaska: a pre-assessment plan. U.S. Fish and Wildlife Service, Alaska
Maritime National Wildlife Refuge, Homer, Alaska.

Byrd, G. V., and J. H. Reynolds. 2006b. Persistence rates of bird
carcasses on beaches of Unalaska Island, Alaska, following the wreck of
the M/V Selendang Ayu. U.S. Fish and Wildlife Service, Alaska Maritime
National Wildlife Refuge, Homer, Alaska.

Flint, P. L., A. C. Fowler, and R. F. Rockwell. 1999. Modeling losses of
birds associated with the oil spill from the M/V Citrus off St. Paul
Island, Alaska. Ecological Modeling 117:261-267.

Ford, R. G., G. W. Page, and H. R. Carter. 1987. Estimating mortality of
seabirds from oil spills. In Proceedings of the 1987 Oil Spill
Conference, pp. 747-751. American Petroleum Institute, Washington, DC,
USA.

Fowler, A. C., and P. L. Flint. 1997. Persistence rates and detection
probabilities of oiled King Eider carcasses on beaches of St. Paul
Island, Alaska. Marine Pollution Bulletin 34:522-526.

Linz, G. M., J. E. Davis, R. M Engeman, D. L. Otis, and M. L. Avery.
1991. Estimating survival of bird carcasses in cattail marshes. Wildlife
Society Bulletin 19:195-199.

Nichols, J. D., J. E. Hines, J. R. Sauer, F. W. Fallon, J. E. Fallon,
and P. J. Heglund. 2000. A double-observer approach for estimating
detection probability and abundance from point counts. The Auk 117:
393-408.

Page, G. W., H. R. Carter, and R. G. Ford. 1990. Numbers of seabirds
killed or debilitated in the 1986 Apex Houston oil spill in central
California. Studies in Avian Biology 14:164-174.

Philibert, H., G. Wobeser, and R. G. Clark. 1993. Counting dead birds:
examination of methods. Journal of Wildlife Diseases 29:284-289.

Piatt, J. F., C. J. Lensink, W. Butler, M. Kendziorek, and D. R.
Nysewander. 1990. Immediate impact of the Exxon Valdez oil spill on
marine birds. Auk 107:387-397.

Pollock, K. H., J. D. Nichols, J. E. Hines, and C. Brownie. 1990.
Statistical inference for capture-recapture experiments. Wildlife
Monographs 107:1-97.

Tobin, M. E., and R. A. Dolbeer. 1990. Disappearance and recoverability
of songbird carcasses in fruit orchards. Journal of Field Ornithology
61:237-242.

Van Pelt, T. I., and J. F. Piatt. 1995. Deposition and persistence of
beachcast seabird carcasses. Marine Pollution Bulletin 30:794-801.

White, G. S., and K. P. Burnham. 1999. Program MARK: survival estimation
from populations of marked birds. Bird Study (supplement):120-138.

Table 1. Model selection for probability of detecting bird carcasses
found at Unalaska Island study sites, Alaska in January 2005. AIC is the
Akaike Information Criterion (Burnham and Anderson 2002).

  ---------- --------- ---------- -------------- ------------- -------------
  Model      AIC       Delta AIC  AIC Weight     Model         Parameters
                                                 Likelihood    
                                                 (Relative)    

  P..p       297.52    0          0.64           1.000         2

  P.tp       300.13    2.60       0.17           0.272         4

  Pbt.p      301.62    4.09       0.08           0.129         4

  Pbtp       301.67    4.14       0.08           0.126         12

  Pb.p       305.52    7.99       0.01           0.018         6

  Pbttp      306.61    9.09       0.01           0.011         8

  P...       315.13    17.61      0.00           0.00          1

  Pbt..      317.15    19.63      0.00           0.00          2

  Pbtt.      320.41    22.89      0.00           0.00          4
  ---------- --------- ---------- -------------- ------------- -------------

Table 2. Estimated detection probabilities for bird carcasses on beaches
at Unalaska Island, Alaska in January 2005, based on AIC-weighted
model-averaging (Table 1).

  ----------- ------ ------ ------------- ---------- ------------ ---------------
  Beach       Pass   Team   Detection     Standard   95%          \% Variation
                            Probability   Error      Confidence   attributable to
                                                     Interval     Model
                                                                  Uncertainty

  CNB 3,10,19 1      1      0.400         0.066      0.280, 0.534 8.18

                     2      0.423         0.069      0.300, 0.557 7.56

              2      1      0.705         0.063      0.568, 0.811 9.73

                     2      0.708         0.064      0.569, 0.817 19.35

  KFP 9       1      1      0.396         0.064      0.278, 0.526 16.65

                     2      0.436         0.070      0.306, 0.575 27.40

              2      1      0.683         0.076      0.519, 0.811 46.19

                     2      0.710         0.065      0.569, 0.820 36.09

  KFP 10      1      1      0.402         0.055      0.300, 0.514 8.51

                     2      0.421         0.055      0.317, 0.531 7.78

              2      1      0.721         0.059      0.593, 0.820 34.56

                     2      0.683         0.059      0.558, 0.786 27.7
  ----------- ------ ------ ------------- ---------- ------------ ---------------

Figures

1\. Model-averaged detection probabilities (Table 2) by Beach (panel),
Pass (horizontal axis), and Team: for each pass, Team 1 is shown to the
left, Team 2 to the right. The effect of team and beach is minor
compared to the effect of pass. CNB beaches 3, 10 and 19 were pooled for
analysis. CNB -- Cannery Bay beach segments; KFP -- southern shore of
Makushin bay, east of Cape Starichkof.

Figure 1.

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height="2.8722222222222222in"}

Appendix 1. Summary of bird carcasses detected at study beaches on
Unalaska Island, Alaska, January 2005, by beach segment and team. Each
team made two passes, classifying each detected carcass as: YY --
Detected on both passes; YN - detected on first pass, not on second; NY
-- not detected on first pass, detected on second; and NN -- not
detected on either pass. Beach segments are identified in Byrd et al.
(2005); CNB -- Cannery Bay, KFP -- southern shore of Makushin Bay, east
of Cape Starichkof.

  ---------- ----------- ---------- ---------- ---------- ---------- ----------
  CNB 19     Protected   Team 2                                      

                         YY         YN         NY         NN         Total

  Team 1     YY          2          0          0          0          2

             YN          0          0          0          0          0

             NY          0          0          0          0          0

             NN          0          0          0                     

             Total       2          0          0                     
  ---------- ----------- ---------- ---------- ---------- ---------- ----------

  ---------- ----------- ---------- ---------- ---------- ---------- ----------
  CNB 3      Protected   Team 2                                      

                         YY         YN         NY         NN         Total

  Team 1     YY          0          0          0          0          0

             YN          0          0          0          0          0

             NY          0          0          0          0          0

             NN          0          0          1                     

             Total       0          0          1                     
  ---------- ----------- ---------- ---------- ---------- ---------- ----------

  ---------- ----------- ---------- ---------- ---------- ---------- ----------
  CNB 10     Protected   Team 2                                      

                         YY         YN         NY         NN         Total

  Team 1     YY          1          0          0          0          1

             YN          0          1          0          0          1

             NY          0          0          4          0          4

             NN          0          0          2                     

             Total       1          1          6                     
  ---------- ----------- ---------- ---------- ---------- ---------- ----------

  ---------- ----------- ---------- ---------- ---------- ---------- ----------
  CNB 3, 10, Catchment / Team 2                                      
  19         Protected                                               

                         YY         YN         NY         NN         Total

  Team 1     YY          3          0          0          0          3

             YN          0          1          0          0          1

             NY          0          0          4          0          4

             NN          0          0          3                     

             Total       3          1          7                     
  ---------- ----------- ---------- ---------- ---------- ---------- ----------

  ---------- ---------- ---------- ---------- ---------- ---------- ----------
  KFP 10     Exposed    Team 2                                      

                        YY         YN         NY         NN         Total

  Team 1     YY         11         0          2          1          14

             YN         0          1          0          0          1

             NY         2          0          0          5          7

             NN         2          0          3                     

             Total      15         1          5                     
  ---------- ---------- ---------- ---------- ---------- ---------- ----------

  ---------- ---------- ---------- ---------- ---------- ---------- ----------
  KFP 9      Exposed    Team 2                                      

                        YY         YN         NY         NN         Total

  Team 1     YY         3          0          0          0          3

             YN         0          0          0          0          0

             NY         0          0          1          0          1

             NN         1          1          3                     

             Total      4          1          4                     
  ---------- ---------- ---------- ---------- ---------- ---------- ----------