First Symposium on Steller’s and White-tailed Sea Eagles in East Asia pp. 45-57, 2000
UETA, M. & MCGRADY, M.J. (eds) Wild Bird Society of Japan, Tokyo Japan

Numbers and current status of the population of Steller’s Sea Eagle
on Sakhalin Island
Vladimir B. MASTEROV1, Mikhail U. SOLOVIEV1 & Vladimir B. ZYKOV2
1. Department of Vertebrate Zoology, Biological Faculty of the Moscow State University, 119899 Moscow,
Russia. e-mail: eagle@soil.msu.ru
2. Information Center "Fauna", Komsomolskaya str., 241 a -14, 693000 Uzno-Sakhalinsk, Russia.
e-mail:fauna@sakhmail.sakhalin.ru

Abstract. A predictive model of spatial distribution of nesting territories of Steller’s Sea Eagle
Haliaeetus pelagicus was constructed using GIS. A habitat map was created by vectorization ofsatellite imagery into unequal area polygons, grouped according to geobotanical and landscapecharacteristics. Logistic regression was used to model presence of a territory in a polygon. Using thismethod the model predicted that 434 potential nesting territories exist on Sakhalin. Evaluation of bird
numbers was carried out using counts along line transects of varying length. After estimating linear
density using jack-knife resembling, the density was extrapolated to unsurveyed fragments of coastline
on the basis of similarity of their landscape characteristics. The total estimated number of birds for
Sakhalin is 560 birds. Population age-structure estimation of the fraction of adult birds on Sakhalin was
64.2%. Mortality from fledging to maturity was estimated at 75.8%, with average annual mortality ofjuveniles reaching 25%. Average reproductive success for territorial pairs on Sakhalin was 0.795
fledgling per pair (N = 70). Estimated population growth rate using Leslie matrix model was -0.0024,
indicating a slow decline in the Sakhalin eagle population. Because of this even a relatively small
decrease in survival or fertility could lead to a rapid decline in the population size.

INTRODUCTION
The breeding range of the Steller’s Sea Eagle Haliaeetus pelagicus includes the Okhot
seacoast, Kamchatka, Lower Amur River, Sakhalin Island and Kuril Islands. Remoteness anddifficult access to these areas has probably contributed to population stability. These same
factors make this species one of the least studied birds of prey in the Palearctic. Lobkov (1988)
estimates the Steller’s Sea Eagle population to be 7,000-7,500 birds. On Sakhalin the breeding
range of Steller’s Sea Eagle includes shoreline and the lower reaches of rivers in the northernpart of the island, from Tyk Bay in the north-east to the Terpenia Cape in the east (Fig. 1).
Northern Sakhalin and the adjoining sea shelf is the principal oil and gas province of theRussian Far East region. In 1997 preparations were made for large scale development of shelf

46

Fig. 1. Breeding range of Steller’s Sea Eagle on Sakhalin.

fields by Exxon, SADECO, Marathon Oil, Mitsui Bussan, McDermott, Shell, and Mitsubishi.
It is estimated that full development of the field will occur over 25-30 years. Ten off-shore
drilling platforms will be established, each sinking up to 200 wells. Pipelines will cross 625
km of sea bottom and 700 km of dry land. Gas and oil will be transported along the shore by
shuttle tankers making up to 120 runs per year. Severe environment and complicated seismic
and ice conditions in the region increase the possibility of accidents, like drilling rig collisions,pipeline ruptures, and tanker wrecks similar to the Exxon Valdez accident.
Environmental pollution and habitat deterioration may destroy trophic chains of shelf andwetland ecosystems. Most endangered species inhabiting seaside areas participate in thetrophic chains of marine ecosystems and are vulnerable to occasional fluctuations in amount ofavailable food caused by technogenic deterioration of this environment (Terborgh & Winter1980, Diamond 1984, Pimm 1984). This is especially true for the Steller’s Sea Eagle, which
occupies the upper level of the seaside trophic pyramid.
The absence of basic information on the recent status of the Steller’s Sea Eagle
population and its habitats in Sakhalin does not allow for an objective evaluation of thepotential impact of oil development on this vulnerable species. This study evaluates the
population numbers and demography of the Steller’s Sea Eagle at Sakhalin, and develops amodel of spatial distribution of principal breeding habitats.
Evaluation of population status requires knowledge of not only numbers, but also sex andage ratios, mortality in different age classes, mean life expectancy, and reproductive success.

47
Deficiencies in these data sets mean that only a preliminary assessment of the Steller’s Sea
Eagle population can be made.

METHODS
Population numbers were evaluated using line transect counts in 1997-98 and aerial
surveys in 1989-91. Birds and nests were assigned to the following categories:• adult birds: older than 5 years in definitive plumage• immature: less than 5 years old with different extent of brown in plumage• nest territory: area within 400 m of the nest. The nest territory included the active and all
old nests belonging to the pair. If the pair was breeding, the active nest was used as theterritory centre.
• territorial pair: pair of adult eagles occupying a nesting territory. In any one year, theseincluded successfully breeding pairs, as well as pairs that failed, and pairs for whom theresult of breeding was unknown.
• successfully breeding pairs: pairs that successfully raised eaglets to the late nestling stage.
Counts were carried out along line transects of constant width and varying length thatcovered segments of the shoreline and lower reaches of rivers. Preliminary surveys revealed
that 85% of 140 eagle nests on the Lower Amur and on Sakhalin were located within 300 m ofshoreline, and were distributed within distance categories in the following proportions: 0100 m - 53%; 101-200 m - 19.5%; 201-300 m - 12.5%. The remaining 15% were found up to1300 m from the shore. Relative to the forest edge nests were distributed in the following way:
0-50 m - 71%; 51-100 m - 14%; 101-150 m - 7%; the remaining 8% of nests were found at a
distance 151 to 350 m from the forest edge.
Eagle numbers: Adult and immature birds were usually observed along the shoreline,
near the forest edge, or on single trees, stones and poles. Accordingly, number of birds(nests) per kilometre of shoreline was chosen to evaluate the linear density of eagles. Adult
birds and nests were easily located from boat or aircraft. During surveys on foot, undercount
was related to forest cover and terrain features which obscured the observer’s view of eagle,
and was not related to the distance these were from the transect. Accordingly, a 250 m buffer
on either side of the transect line, (which encompassed at least 90% of nests), was used fordensity estimates. The total length of transects was 908 km.
Nest counts: To estimate density and spatial distribution of nest territories, shoreline
habitats were delineated from satellite imagery. Habitats were treated as potentially suitable ifthey fell within a 3 km buffer of the seashore, or within 1 km of the lower stretches of rivers
and their floodplains > 3 km from the mouth. Vectorization was carried out using MapInfo
Professional 4.1, creating a habitat map comprised of unequal area polygons, grouped
according to geobotanical and landscape characteristics (Fig. 2). In total, 5 principal groups ofhabitats were distinguished:

48

Fig. 2. Principal groups of Steller’s Sea Eagle habitats on Sakhalin.

1. forest-like habitats, 7 types:• larch forest Larix gmelini with Marsh Tea Ledum palustre, mosses and lichens, L1• larch forest with rhododendron (Lapland Rhododendron Rhododendron lapponicum), L2• larch forest with Japanese Stone Pine Pinus pumila, L3• larch forest with Yeddo Spruce Picea jezoensis, marsh tea and mosses, L4• larch forest with Yeddo Spruce and Khingan Fir Abies nephrolepis, L5• larch forest with Erman’s Stone Birch Betula ermani, L6• burnt logged woodland, L7
2. tundra-like habitats, 3 types:• mar’ with dwarf-shrubs, lichens, small lakes, sedge-tussocks Carex elata, M1• seaside sand tundra, M2• larch and birch forest tundra, with Dwarf Birch Betula nana, M3
3. floodplain, 3 types:• non-forest floodplain (rock, meadow, shrub), F1• non-forest floodplain with larch belts on terraces, F2• poplar floodplain, F3
4. shoreline habitats, including hill slopes and seaside rocks, 3 types:• rocks, S1• tundra-like or meadow-like slopes, S2• spruce and larch forest on sandy and rocky cliffs, S3
5. spits (incl. sand spits in bays, tidal spits and small islands), SH

49
Location of nests and nest territories were determined using GPS. Linear density of nest
territories was assessed by determining shoreline length for every habitat type within eachcount, and then estimating density and its error using jack-knife resembling techniques (Tukey
1958, Efron 1982) with counts as sample units.
A predictive model of the spatial distribution of nest territories was constructed using
logistic regression to model presence of territory within a particular polygon from continuous(polygon area, perimeter, coastline length, length of a border with floodplain) and categorical(habitat types) predictors. Continuous predictors were log-transformed to normalise theirdistribution. Coefficients for logistic regression were derived from models constructed in areas
which were thoroughly surveyed, and census adequacy was close to absolute.
Prior to bird counts the shoreline of north-east Sakhalin was split into a series of nonoverlapping transects, each of which covered easily definable fragments of coastline. Birds
observed in the course of the surveys were assigned to these fragments. After estimating linear
density using a jack-knife approach, coastline transects were placed into one of 5 categories
according to density. This classification was used for further extrapolation of density inunsurveyed areas and in estimating the total number using the following formulae from Coli
(1979) for estimating standard error:

where s2Dh = density variance in the surveyed fragments, zh = total area of category h, nh =number of fragments in category h. A correction for underestimation was introduced byregressing density index on absolute density and then evaluated in the areas that were surveyed
more than once.

RESULTS AND DISCUSSION
Number and spatial distribution of nest territories
Evaluation of nest numbers and modelling of their spatial distribution was madeseparately for 3 groups of polygons. The first group included polygons adjacent to coastline.
The second, polygons within 3 km from the coast, but separated from it by other polygons.
The last group was represented by polygons adjacent to floodplain habitats.
To make results of logistic regression more interpretable we reduced the number of
habitat categories. The occurrence of each of the 17 initial habitat types within the nesting
territories was examined. If a habitat type did not occur in more than 10% of the territories,
then it was aggregated into a group called ‘select’. This resulted in the following groups ofhabitats: forest (L1, L2, L4), tundra (M1, M2, M3), floodplain (F1, F2, F3), shore cliffs (S2)and “Select” (Table 1). Overall the model was significant (χ2 test, P < 0.001, McFadden’s
Rho-Squared = 0.294).
As the number of polygons without nests was substantially larger than the number of
inhabited polygons, the model, adjusted to include all available observations, tends to predict

50
absence in a satisfactory way, but will not adequately predict presence. To resolve thisproblem we used Cohen’s κ for calibrating the threshold probability value that best reduces theadjusted probability values to 0 (nest absence) or 1 (nest presence) (Guisan et al. 1998). The
selected threshold value is the one that provides the best κ between adjusted and observed
probability values from the calibration dataset. The best κ for above model was 0.595 (ASE =0.006), and corresponded to a threshold probability of 0.36. Classification of calibration
dataset using this probability yielded results presented in Table 2.
Results of logistic regression for polygons not adjacent to shoreline are presented in Table
3. Overall the model was significant (χ2 test, P = 0.008, McFadden’s Rho-Squared = 0.110).
The best κ for the above model was 0.255 (ASE = 0.123), and corresponded to a thresholdprobability of 0.175. Classification of calibration dataset using this probability yielded resultspresented in Table 4.
Results of logistic regression for the 3rd group of polygons (floodplain habitats) arepresented in Table 5. Overall the model was significant (χ2 test, P ≤ 0.001, McFadden’s RhoSquared = 0.255). The best κ for the above model was 0.504 (ASE = 0.103), and corresponded
to a threshold probability of 0.385. Classification of calibration dataset using this probability
yielded results presented in Table 6.
Results of nest distribution modelling for areas other than the training sample arepresented at Figure 3. Given that threshold probabilities were 0.36, 0.175 and 0.385 for threegroups of habitat patches, the model predicts the number of nest territories to be 233 in the 3 mseaside zone, and 33 within the floodplain zones of the northwest. As the dependent variablein the logistic model was binary and accepted only presence or absence values, a correction wasnecessary to account for multiple nest territories within a small fraction of patches. The
correction coefficient (ratio of the total number of nests in a training sample to the number ofpatches with nests) was 1.33 for shoreline
habitats, and 1.35 for floodplain habitats.
Table 1. Logistic regression results for
Therefore, the total number of nest territories ofpolygons bordering shoreline.
Steller’s Sea Eagles on Sakhalin, after correcting
P
Independent variable
CONSTANT
0.000
for census incompleteness, is estimated at 434.
Lg polygon perimeter
0.006
We also evaluated eagle nest numbers by
Lg length of coastline
0.001
extrapolating count data for the total area offloodplain habitat
0.729
suitable habitats. Nest density values by habitats
forest habitat
0.213
tundra habitat
0.759
estimated from count data using jack-knife
shoreline cliffs and terraces
0.045
resembling are presented in Table 7. The total
Table 2. Classification of calibration dataset using adjusted threshold probability of 0.36
(adjacent to shoreline)
Actual Choice
polygons without nest
polygons with nest

Predicted Choice
Actualtotal polygons without nest polygons with nest
144
122
22
64
15
49

% of correctlypredicted
84.7
76.6

51
number estimated in this way was 339 territories, situated along sea coasts. The number
nests’ sites in the floodplains of North-Western Sakhalin was estimated at 47.
The spatial distribution of Steller’s Sea Eagle nest sites in Northern Sakhalin is presented
in Fig. 4. Not all territories were permanently occupied. Census data revealed that 31.5% of
nest sites had been deserted during the study period while the rest (68.5%, including 40.7% of
the total that were successful) remained occupied throughout. Also, the proportion of occupied
territories differed between coastline regions(Table 8). Low occupancy rates in Nabil, Nyivo,
Piltun, and Pomr’ Bays are probably be due toTable 3. Logistic regression results forpolygons not adjacent to shoreline.
the impact of human activities along the shore
Independent variablePand habitat differences (Masterov & Zykov
CONSTANT
0.0001992).
Lg polygon perimeter
Combined "Select" habitat

0.009
0.130

Table 4. Classification of calibration dataset using adjusted threshold probability of 0.175(not adjacent to shoreline).
Actual Choice
polygons without nest
polygons with nest

Actual
total
170
12

Predicted Choice
polygons without nest polygons with nest
160
10
8
4

% of correctlypredicted
94.2
50.0

Fig. 3. Predicted distribution of eagle nests
and their actual locations for a fraction ofstudied territory.

Table 5. Logistic regression results forthe polygons adjacent to floodplain.
Independent variable
CONSTANT
Lg polygon area
Floodplain habitat
Combined "Select" habitat

P
0.000
0.000
0.023
0.104

Table 6. Classification of calibration dataset using adjusted threshold probability of 0.385(adjacent to floodplain).
Actual Choice
polygons without nest
polygons with nest

Predicted Choice
Actualtotal polygons without nest polygons with nest
213
209
4
23
13
10

% of correctlypredicted
98.1
56.5

52
Bird numbers
Bird count data were obtained in different years
and during different periods within the breeding season,and required pre-processing to form a homogenous
sample. Mean density of eagles during autumn counts(September and October) were significantly lower than
the average for a summer months (June, July andAugust) (0.026 ± 0.018 and 0.112 ± 0.012 birds / km,
respectively, P < 0.05). These were excluded from ouranalyses. However, density indices for summer counts
in 1990 (June and August) and 1991(June and July)
did not differ (0.152 ± 0.010 and 0.112 ± 0.012 birds /km, P > 0.05), and these were pooled.
To estimate bird density indices from individualshoreline fragments were grouped into categories (Table9), which stratified the coast according to eagle density
Each transect was assigned to one of the density
categories, and these could include a number ofdifferent types of landscape. So, different landscapes
could have similar densities, and thus fall within one
density category. Extrapolation to unsurveyed
fragments of coastline was based on the similarity ofFig. 4. Spatial distribution of Steller’s
their landscape and geo-morphological characteristics to
Sea Eagles nest territories insurveyed areas, and allowed unsurveyed areas to be
Northern Sakhalin.
assigned to a density category. The total estimatednumber of birds for the shoreline at northeast of Sakhalin (2197.4 km) after correcting for countincompleteness is 551.2 (SE = 33.48).
An additional correction was introduced by dividing all counts by the number ofobservations made during relatively favourable and relatively unfavourable conditions and thenestimating the mean density between these groups. Estimated density (Y) was related toobserved density (X) according to the equation:
Y = -0.029 + 1.014 × X
using this method, the number of birds in north-east Sakhalin was estimated at 559. The
spatial distribution of Steller’s Sea Eagles in Northern Sakhalin is presented in Figure 5.
Demographic structure of population
The age structure of the population was assessed as the ratio of adult and immature birds
in counts. In 10 counts, we observed 480 eagles. Adults comprised 64.19 ± 11.18(SE)%, of
the population and immatures comprised 34.81 ± 12.61(SE)%. The age ratio was constant

53
Table 7. Nest density values (by habitats) estimated from count data using jack-knife resampling.
Habitatnon-forest floodplain (rocky, meadow, bushy), F1
non-forest floodplain with larch belts on terraces, F2
poplar floodplain, F3
larch forest (with marsh tea, mosses and lichens), L1
larch forest (with rhododendron), L2
larch forest (with dwarf Siberian pine), L3
larch forest (with Yeddo spruce, marsh tea and mosses), L4
larch forest (with spruce and fur) L5
larch forest (with Erman's birch) L6
burnt wood and logged woodmar' (with dwarf-shrubs, lichens, small lakes, sedgetussocks), M1
seaside sand tundra, M2
larch and birch forest tundra, with dwarf birch, M3rocks, S1
tundra-like or meadow-like slopes, S2
spruce and larch forest on sandy and rocky cliffs, S3seas spits (incl. Spits in bays, tidal spits and small islands),
SH

Length ofshoreline
(km)
67.56
56.98
37.84
122.78
80.68
22.29
6.26
40.26
4.49
2.75

Linear density(nests/km ofshoreline)
0.372
0.154
0.261
0.130
0.312
0.344
0.407
0.562
0.000
0.000

0.01570.01280.00600.00270.01550.00690.07010.00630.00000.0000295.210.112

0.0039519.14110.56
155.70
68.86
0.13

0.154
0.163
0.075
0.634
0.000

0.00240.00490.00390.10920.0000713.280.050

0.0080SE

Table 8. The fraction of inhabited territories in different coastline regions.
fraction of
Coastline region
inhabited nests (%)
Lunski Bay
16.0
Piltun Bay
Nabil Bay
7.1
Baikal Bay
Nyivo Bay
5.4
Pomr' Bay
Chaivo Bay
7.1
Schmidt Peninsulasealine from Ratmanova Cape to Lunski Bay
Coastline region

fraction of
inhabited nests (%)
5.4
16.0
3.6
25.1
14.3

Table 9. Shoreline categories according to difference in eagle density.
Category Density range
1
2
3
4
5

0.001-0.100
0.11-0.20
0.21-0.50
0.51-1.50>1.51

Number of Average density / Variance oftransects 1 km of coastline
density10
0.076
0.0009100.150
0.000926
0.306
0.004014
0.983
0.14204
6.609
21.3360

Length ofcoastline, km
459.5
422.4
491.1
102.2
13.3

throughout the reproductive period and similar between years (Table 10). Lobkov & Neifeldt(1986) provided similar values for the proportion of immature birds in Kamchatka - from
33.3% to 38%.
Average reproductive success per territorial pair in Sakhalin was 0.795 fledgling/pair (N= 70). Reproductive performance of successfully breeding pairs was 1.409 fledgling/pair (N =

54
Table 10. Age structure in different reproductive
periods and years.
PeriodAdults (%) Immature birds (%)
May-June
60.78
39.22
July-August
60.27
39.73
Year
1990
1991

Adults (%) Immature birds (%)
61.62
38.38
69.23
30.77

Fig. 5. The spatial distribution of Steller’s Sea Eagles inNorthern Sakhalin.

36). The sex ratio in eagle broods was 1:1 (Masterov 1998).
Mortality of immature birds was estimated assuming acquisition of complete adultplumage at the age of five years (Belopolski 1939). The ratio of adult to immature birds can be
represented by the equation:
2Sad4 / Br(Sad4 + Sad3 × Sim + Sad2 × Sim2 + Sad × Sim3 + Sim4) = 64.2 / 34.8 (1.8448),
where Sad is the survival rate of adults, Br is the reproductive success (0.795 fledgling /pair); Sim is the survival rate of immature birds.
Adequate information about mortality of adult Steller’s Sea Eagles is absent, but inBald Eagles it varies between 5 and 9% (Bowman et al. 1995). Adult birds’ mortality can beapproximately obtained from general equations relating mortality and average number ofchicks per brood (Paevski 1985).
Y = 7.48 × x + 3.06, r = 0.96 (Paevski 1985), where x is average brood size.
According to this equation mean annual mortality of adult eagles may be about 9%, andfrom knowledge of annual survival rate of adults (0.91) and reproductive success (0.795
fledgling/pair), we can calculate the survival of immature birds from fledging to 5 years of age
to be about 24.2%. Then annual survival (Sim) during first five years will be Sim5 = 0.242,
which gives Sim = 75% and average annual mortality of juveniles - 25%.
Annual mortality of young White-tailed Eagles was 27% in Scotland (Green et al. 1996),
which is also close to our estimates. Gerrard et al. (1978) showed that mortality of Bald Eagle

55
Table 11. Reproductive performance (number of female fledglings per female) and mortality of
Steller's Sea Eagle in different age groups.

Reproductive performance
Survival (%)

0-1
0
0.75

2-3
0
0.75

4-5
0
0.75

Age (year)6
7-8 9-10 11-12 13-14 150.300 0.398 0.398 0.398 0.398 0.380
0.91 0.91 0.91 0.91 0.91 0.90

Table 12. Population growth rate and sustainable age structure according to Lesli model.
Growth rate
-0.0024

1 years
17.5

Sustainable age structure (%)
2 years
3 years
4 years
13.3
9.9
7.3

Adult
52

chicks was 71.5% in the first year, 50.9% in the second, and 35% in the third. Overall, only
about 10% of Bald Eagle fledglings survive to maturity (Stalmaster 1987).
Average longevity of birds in natural conditions is an important demographic
characteristic which can be evaluated from body mass using generalised allometric equations(Lindstedt & Calder 1976, Paevski 1985). Mean life expectancy of Steller’s Sea Eagles is 15
years.
Using a Leslie matrix model (Usher 1972), demographic structure of a population can be
estimated using reproductive performance parameters, in the case of Steller’s Sea Eagles: thenumber of female fledglings per female and the survival rate for different age groups (Table
11). The natural logarithm of the main eigen value of the Leslie matrix (L) characterises the
population growth rate, while the corresponding eigen vector (V) characterises the sustainable
age structure (Table 12). The main eigen value of the Leslie matrix for Steller’s Sea Eagles on
Sakhalin is somewhat less than 1 (0.997) which indicates a slow decrease of the population size
at a rate of -0.0024.
Human-related habitat deterioration, pollution, and increasing disturbance may cause
decreases in reproductive success and survival of birds. Even relatively small decreases insurvival and fecundity in a population with low growth rate can lead to rapid decreases in
numbers (Usher 1976). This puts emphasis on the creation of protected territories (natural
refuges) in places where breeding sites of Steller’s Sea Eagles are concentrated.
Research carried out on the Bald Eagle demonstrated that a protected area within 800 mof the nest improved reproductive performance. And that all kinds of human activities,
including recreation, should be reduced in the vicinity of the nest through out the whole
breeding period, including the courtship period (Anthony & Isaacs 1989). In the case of
Steller’s Sea Eagles on Sakhalin this period corresponds to 20 March - 10 September. Also,
development in the autumn-winter period, such as logging, and pipe-line and road construction
should not be allowed within 400 m of the nest site (Grubb & King 1991). Disturbanceeffects not only nesting, but also feeding of eagles. Additional energy expenditures due todisturbance avoidance may lead to the reduction in the amount of food brought to chicks, areduced rate of nestling development and decreased reproductive success (Masterov 1992). To

56
avoid these effects undisturbed zones should be created around principal feeding localities
within a radius of 450 m (Knight 1984).

ACKNOWLEDGMENTS
Scientific and financial support was provided by Research Center Wild Bird Society ofJapan and NEC.

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