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The peregrine falcon (Falco peregrinus) and the gyrfalcon (Falco rusticolus) are top avian predators of Arctic ecosystems. Although existing monitoring efforts are well established for both species, collaboration of activities among Arctic scientists actively involved in research of large falcons in the Nearctic and Palearctic has been poorly coordinated. Here we provide the first overview of Arctic falcon monitoring sites, present trends for long-term occupancy and productivity, and summarize information describing abundance, distribution, phenology, and health of the two species. We summarize data for 24 falcon monitoring sites across the Arctic, and identify gaps in coverage for eastern Russia, the Arctic Archipelago of Canada, and East Greenland. Our results indicate that peregrine falcon and gyrfalcon populations are generally stable, and assuming that these patterns hold beyond the temporal and spatial extents of the monitoring sites, it is reasonable to suggest that breeding populations at broader scales are similarly stable. We have highlighted several challenges that preclude direct comparisons of Focal Ecosystem Components (FEC) attributes among monitoring sites, and we acknowledge that methodological problems cannot be corrected retrospectively, but could be accounted for in future monitoring. Despite these drawbacks, ample opportunity exists to establish a coordinated monitoring program for Arctic-nesting raptor species that supports CBMP goals.
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TERRESTRIAL BIODIVERSITY IN A RAPIDLY CHANGING ARCTIC
Status and trends of circumpolar peregrine falcon and gyrfalcon
populations
Alastair Franke, Knud Falk , Kevin Hawkshaw, Skip Ambrose,
David L. Anderson, Peter J. Bente, Travis Booms, Kurt K. Burnham,
Johan Ekenstedt, Ivan Fufachev, Sergey Ganusevich, Kenneth Johansen,
Jeff A. Johnson, Sergey Kharitonov, Pertti Koskimies,
Olga Kulikova, Peter Lindberg, Berth-Ove Lindstro
¨m, William G. Mattox,
Carol L. McIntyre, Svetlana Mechnikova, Dave Mossop,
Søren Møller, O
´lafur K. Nielsen, Tuomo Ollila, Arve Østlyngen,
Ivan Pokrovsky, Kim Poole, Marco Restani, Bryce W. Robinson,
Robert Rosenfield, Aleksandr Sokolov, Vasiliy Sokolov,
Ted Swem, Katrin Vorkamp
Received: 26 April 2019 / Revised: 23 September 2019 / Accepted: 18 November 2019
Abstract The peregrine falcon (Falco peregrinus) and the
gyrfalcon (Falco rusticolus) are top avian predators of
Arctic ecosystems. Although existing monitoring efforts
are well established for both species, collaboration of
activities among Arctic scientists actively involved in
research of large falcons in the Nearctic and Palearctic has
been poorly coordinated. Here we provide the first
overview of Arctic falcon monitoring sites, present trends
for long-term occupancy and productivity, and summarize
information describing abundance, distribution, phenology,
and health of the two species. We summarize data for 24
falcon monitoring sites across the Arctic, and identify gaps
in coverage for eastern Russia, the Arctic Archipelago of
Canada, and East Greenland. Our results indicate that
peregrine falcon and gyrfalcon populations are generally
stable, and assuming that these patterns hold beyond the
temporal and spatial extents of the monitoring sites, it is
reasonable to suggest that breeding populations at broader
scales are similarly stable. We have highlighted several
challenges that preclude direct comparisons of Focal
Ecosystem Components (FEC) attributes among
monitoring sites, and we acknowledge that
methodological problems cannot be corrected
retrospectively, but could be accounted for in future
monitoring. Despite these drawbacks, ample opportunity
exists to establish a coordinated monitoring program for
Arctic-nesting raptor species that supports CBMP goals.
Keywords Arctic CBMP Falco peregrinus
Falco rusticolus Long-term trends Occupancy
Productivity
INTRODUCTION
The Arctic Council’s Biodiversity Working Group devel-
oped a pan-Arctic biodiversity monitoring plan to detect
and report on long-term changes in Arctic biodiversity
(Christensen et al. 2018). The plan recognizes a suite of
Focal Ecosystem Components (FECs) and associated FEC
attributes (e.g., abundance, distribution, demography,
phenology, health) that are considered to be suitable indi-
cators for ecological monitoring at the scale of the Arctic.
The Terrestrial Expert Monitoring Group (TEMG) of the
Circumpolar Biodiversity Monitoring Programme (CBMP)
identified the peregrine falcon (Falco peregrinus) and the
gyrfalcon (Falco rusticolus) as FECs (Christensen et al.
2018) due to their role as top predators within Arctic food
webs. Although location-specific surveys vary in spatial
and temporal extent, both species have received consider-
able long-term monitoring effort (Fig. 1). The work pre-
sented here is a synopsis of Arctic-wide monitoring of
peregrine falcons and gyrfalcons, and addresses the need to
integrate the state of knowledge for these species within the
context of CBMP monitoring priorities. The objectives of
this study were to (1) identify long-term monitoring sites;
(2) acquire, share, and collate attribute-specific data for
Arctic-based peregrine falcon and gyrfalcon projects; (3)
present empirically derived trends associated with FEC
Electronic supplementary material The online version of this
article (https://doi.org/10.1007/s13280-019-01300-z) contains sup-
plementary material, which is available to authorized users.
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Fig. 1 Peregrine falcon (a); gyrfalcon (b, white morph); occupancy survey conducted by snowmobile in Nunavut, Canada (c); gyrfalcon
occupancy survey conducted on skis in Finnmark, Norway (d); typical breeding habitat in the peat bogs of Norrbotten, Sweden with helicopter
assistance to access nests to estimate productivity (e); gyrfalcon survey in typical habitat in Iceland (f); productivity survey conducted by boat in
Low Arctic, Nunavut, Canada (g); continuous monitoring of gyrfalcon productivity using motion sensitive scouting camera (upper left) on the
Seward Peninsula, Alaska, United States (h); productivity survey in typical breeding habitat in Low Arctic South Greenland requires climbing
equipment to access nests (i); typical sandy cliff breeding habitat for peregrine falcons on the Yamal Peninsula, Russia (j); photos: E. Hedlin, K.
Falk, A. Franke, K. Johansen, P. Lindberg, D. Bergman, B. Robinson, S. Møller, and D. Nowak
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attribute demography; (4) summarize information for other
essential and recommended CBMP FEC attributes; (5)
identify challenges associated with disparate application of
survey methods that currently hamper comparisons among
research groups, and (6) suggest minimum standards for
future coordinated monitoring.
NATURAL HISTORY OF ARCTIC FALCONS
AS ECOSYSTEM COMPONENTS
The peregrine falcon is a medium-sized raptor with long,
pointed wings, dark hood and face, with distinct dark malar
stripe, slate gray back, and barred belly, legs, and tail (see
Fig. 1). Compared to the peregrine falcon, the gyrfalcon is
larger, with more rounded and broader wings, and longer tail
(see Fig. 1). Gyrfalcons have three main color morphs:
black, gray, and white. Both species exhibit reverse sex-
dimorphism (Ferguson-Lees et al. 2001). Both species are
highly territorial, and nesting territories are generally con-
sidered to be associated with rugged terrain (particularly
coastal, lake-shore and river-side cliffs, and rock outcrops),
but peregrine falcons also utilize thermokarst bluffs in
northern Alaska (Ritchie 2014), and commonly nest on the
ground in the peat bogs of Fennoscandia (Lindberg et al.
1988). Both species occasionally nest in trees where old stick
nests (typically built by common ravens Corvus corax or
rough-legged buzzards Buteo lagopus) are available. Nest-
ing territories are typically regularly spaced, particularly in
areas where breeding habitat and prey availability are uni-
formly distributed (Newton 1988). Although they share
some similarities in ecology and life history attributes (e.g.,
reproductive life span, number of offspring, survivorship),
peregrine falcons and gyrfalcons differ with regard to
migratory behavior, foraging and breeding ecology, and
degree of specialization. To varying degrees, these factors
are influenced by natural disturbance regimes, such as cycles
in prey abundance (Barichello and Mossop 2011; Koskimies
2011; Nielsen 2011), or potentially from anthropogenic
disturbance (Tucker et al. 2019). Both species, however, are
exposed to the effects of climate change, including shifts in
weather regimes that can affect breeding phenology and
success directly (Franke et al. 2010; Bente 2011; Anctil et al.
2014; Lamarre et al. 2017), or indirectly from habitat loss
mediated through shrubification (Johansen and Østlyngen
2011; Wheeler et al. 2018), and changes in food supply
(Newton 1979; Poole 1987; Barichello and Mossop 2011;
Nielsen 2011).
In the Palearctic, the distribution of the nominate pere-
grine falcon F. p. peregrinus includes the Sub-Arctic and
Low Arctic of northernmost Fennoscandia and westernmost
Russia; birds from this population are medium-range
migrants wintering in western and southern Europe, or
northern Africa (Ganusevich et al. 2004; Lindberg 2008;
Saurola et al. 2013). The Siberian peregrine falcon F. p.
calidus (hereafter referred to as calidus) is distributed
throughout tundra areas of Russia to the Bering Strait—it is
considered the Palearctic equivalent to the Arctic peregrine
falcon F. p. tundrius (White 1968) in the Nearctic (hereafter
referred to as tundrius).
The peregrine falcon is typically considered to be a
generalist predator that predominantly consumes avian
prey, but also regularly consumes small mammals where
they are available (Lindberg 1983; Court et al. 1988;
Bradley and Oliphant 1991; Ganusevich 2006; Dawson
et al. 2011). For gyrfalcons, Lagopus spp. (L. lagopus, L.
muta and L. leucura) hereafter referred to as ptarmigan
(Fuglei et al. 2019) unless specified otherwise are invari-
ably cited as critically important prey, particularly in late
winter and early spring (Booms et al. 2008; Barichello and
Mossop 2011; Koskimies 2011; Nielsen 2011; Robinson
et al. 2019). In some parts of the range, seabirds, Arctic
ground squirrels (Urocitellus parryii), Arctic hares (Lepus
arcticus), and passerines are also important gyrfalcon prey,
especially in the breeding season (Poole 1987).
METHODS
Identification of monitoring sites and FEC attributes
An informal network of biologists (Arctic Falcon Specialist
Group; AFSG) with a research focus on Arctic-breeding
peregrine falcons and gyrfalcons was established on the basis
of two CBMP-TEMG workshops (Sweden, 2016, and Ice-
land, 2017), two gyrfalcon workshops hosted by the Icelandic
Institute of Natural History and the Raptor Group Finnmark
in cooperation with the Arctic University of Norway (Tromsø
2014 and 2015, respectively), and by inviting known experts
to participate in the network. The AFSG identified monitor-
ing sites throughout the circumpolar Arctic, and used web-
based applications to acquire, share, and collate data that
describe study area characteristics (Tables S1 and S2), as well
as details describing survey effort and design, number of
surveys completed annually, timing of surveys, type of
observation platform, and sampling design (Tables 1and 2).
AFSG members reviewed the list of ‘essential’ and ‘rec-
ommended’ FEC attributes identified by the CBMP-TEMG
(Christensen et al. 2013), and selected occupancy and pro-
ductivity (parameters of FEC attribute ‘demography’; see
Millsap 2018 for example) to be of greatest utility for past
and ongoing monitoring efforts of Arctic falcon species (see
Table S3 for assessment of all FEC attributes). Franke et al.
(2017) defined occupancy as the quotient of the count of
occupied nesting territories and the count of known nesting
territories that were fully surveyed in a given breeding
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season (i.e., two or more surveys). Productivity is defined as
the number of young that reach the minimum acceptable age
for assessing success (80 % of normal fledging age), and
should be reported as the number of young produced per
territorial pair, or per occupied territory in a particular year
(Steenhof and Newton 2007). We define a population as a
group of organisms of the same species occupying a partic-
ular space (i.e., monitoring sites) at a particular time (i.e.,
monitoring duration), with the potential to breed with each
other (Krebs 2001). Terminology used throughout follows
recommendations outlined in Franke et al. (2017).
Trend analysis
Data exploration was carried out following the protocol
described in Zuur et al. (2010). Specifically, we used his-
tograms and kernel density plots to inspect raw values for
normality. In addition, we applied the Shapiro–Wilk test
(w) for normality to assess whether pvalues were [0.05,
and w= 1 (Shapiro and Wilk 1965). We used boxplots to
detect outliers; however, none of the extreme values
observed were considered to be outside of the range of
natural variation, and all data points were retained.
Because we anticipated non-linear trends in occupancy
and productivity, General Additive Models (GAMs) were
used to estimate temporal trends as follows:
Yi¼oþfYeari
ðÞþei;ð1Þ
where Yirepresents the ith observation of the FEC attribute
parameter of interest, ois the intercept, fYeari
ðÞis the
smoothing function, and eirepresents a vector that contains
prediction residuals. Each GAM was estimated using the
mgcv package (Wood 2016) in R (R Development Core
Team 2017). The amount of smoothing was limited to a
maximum of 10 degrees of freedom, and estimated using
restricted maximum likelihood (Wood 2016). We limited
Table 1 Monitoring period (years in bold = ongoing monitoring), sampling regime, and within season survey effort for peregrine falcons
Site
ID
a
Monitoring site Occupancy based on
presence of
b
Survey
period
c
Sampling regime
d
Platform Pre-
laying
Incubation Brood
rearing
Occupancy estimate
f
1 Norrbotten (Se) Adult(s), egg/young 1972–2018 Stratified Partial Ground, air 4(X?Y?Z?G)/N
2 Finnmark (No) Adult(s), egg/young,
other evidence
1987–2018 Random Full Ground, air 44 4 (X?Y?Z?G)/N
3 Lapland (Fi) Adult(s), egg/young 1981–2018 Stratified Partial Ground, air 4(X?Y?Z?G)/N
4 Kola Peninsula (Ru) Adult(s), egg/young,
other evidence
1980–2018 Census Partial Ground 4(X?Y?Z?G)/N
5 Nenetskiy Ridge (Ru) Adult(s), egg/young 20092014 Stratified Partial Ground 4(X?Y)/N
6 Kolguev Island (Ru) adult(s), egg/young 2013–2018 Stratified Partial Ground 4(X?Y)/N
7 Schuchya River (Ru) Adult(s), egg/young 19882016 Census Partial Ground 4
8 Yamal (Ru) Adult(s), egg/young 1999–2018 Census Partial Ground 44(X?Y)/N
9 Taimyr (Ru) Adult(s), egg/young 20002013
e
Census Partial Ground 4
10 Seward Peninsula (US) Adult(s), egg/young 1998–2018 Census Full
e
Air, ground 4
e
4
e
(X?Y?Z?G)/N
13 Colville River (US) Adult(s), egg/young 1952–2018
e
Census Full Ground 44(X?Y?Z?G)/N
14 Yukon River (US) Adult(s), egg/young 1966–2015 Census Full Ground 44
15 Yukon/Peel Rivers (Ca) Adult(s), egg/young 1970–2018 Census Partial Ground 4(X?Y?Z?G)/N
16 North Slope Yukon (Ca) Adult(s), egg/young 1973–2015 Census Partial Ground 4(X?Y?Z?G)/N
17 Mackenzie River (Ca) Adult(s), egg/young 1970–2015
e
Census Partial Air, ground 4
18 Hope Bay (Ca) Adult(s), egg/young 19831986 Census Full Air, ground 44
19 Rankin Inlet (Ca) Adult(s), egg/young 1982–2018 Census Full Ground 44 4 (X?Y?Z?G)/N
20 Mary River (Ca) Adult(s), egg/young 2011–2018 Census Partial Air, ground 44 4 (X?Y?Z?G)/N
21 Northwest Greenland Adult(s), egg/young 1993–2018 Census Partial Air, ground 4(X?Y?Z?G)/N
22 Central West Greenland Adult(s), egg/young 1972–2017
e
Census Partial Air, ground 4(X?Y?Z?G)/N
23 South Greenland Adult(s), egg/young 1981–2018 Stratified Full/partial Ground 4
e
4(X?Y?Z?G)/N
a
See Fig. 2
b
Other evidence—egg shell fragments, molted feathers or down, recent excrement, fresh prey remains
c
Bold indicates monitoring is ongoing
d
Census—all known nesting territories checked systematically; stratified—sub-set of all known nesting territories checked systematically; random—random
selection of known nesting territories checked; full—known nesting territories receive multiple visits per breeding season; partial—single visits, or only in brood-
rearing period
e
Discontinuous
f
Sensu Nielsen (2011): X= successful nest, nesting attempt, or pair—one in which at least one young reaches the minimum acceptable age for assessing success
(Steenhof et al. 2017), Y= unsuccessful nest, nesting attempt, or pair—a laying pair that failed before nestlings reached the minimum acceptable age for assessing
success, Z= non-laying Pair—a mated pair that fails to lay at least 1 egg in a given year (Steenhof et al. 2017), G= single non-laying individual—a non-mated
individual evidenced by an absence of territorial behavior, or reproductive-related activity, N=count of known nesting territories surveyed
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Fig. 2 Trends (black lines) in peregrine falcon occupancy (black circles) and productivity (open circles) estimated using general additive models (see Table 3numerical outputs) for monitoring
sites distributed throughout the circumpolar Arctic. Gray bands represent 95 % confidence intervals. See Methods for definitions of occupancy and productivity. Light purple refers to Sub-
Arctic, medium purple to Low Arctic, and dark purple to High Arctic
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trend analysis to monitoring sites with data spanning 10 or
more years, and for each monitoring site we excluded years
in which fewer than 10 nesting territory visits were
completed.
After fitting each GAM, we validated model fit using
histograms and kernel density plots to inspect the residuals
for normality. We assessed homogeneity of variance by
plotting residual values against fitted values, and inspected
each plot to ensure that points were uniformly distributed.
Model outputs for each GAM included estimates of the
grand mean for each FEC attribute of interest for each
monitoring site (i.e., the intercept term). Effective degrees
of freedom (edf) dictate the amount of smoothing estimated
for each GAM, where higher values indicated less
smoothing (more undulating) and lower values indicate
more smoothing (less undulating). Numerical smoothing
terms must be interpreted in conjunction with the associ-
ated GAM graphical output. For example, a trend (where
time is the covariate) with edf = 1.0 that is accompanied by
significant pvalue would be interpreted as a straight line
that deviates from horizontal. However, inspection of the
graphical output would be required to assess the degree of
incline or decline, taking into consideration the confidence
intervals and deviance explained. Similarly, a trend with
edf = 1.0 that is accompanied by non-significant pvalue
would be interpreted as a straight line that does not deviate
from horizontal (i.e., neither increasing nor decreasing),
but inspection the graphical output (trend line and associ-
ated confidence intervals) is recommended to support the
conclusion that no incline or decline is present.
Summary of other FEC attributes
To provide an overview of other CBMP FEC attributes, we
conducted a literature search using the Web of Science
database for journal articles, conference proceedings, and
books using the following keywords: abundance, phenol-
ogy, Arctic, climate change, Falco rusticolus,Falco
peregrinus, genetic diversity, gyrfalcon, long-term trends,
peregrine, prey cycles, and pollutants.
RESULTS
Identification of monitoring sites
Researchers from the Arctic Council states representing 24
monitoring sites contributed information describing
Table 2 Monitoring period (years in bold = ongoing monitoring), sampling regime, and within season survey effort for gyrfalcons
Site
ID
a
Monitoring site Occupancy based on
presence of
b
Survey
period
c
Sampling regime
d
Platform Pre-
laying
Incubation Brood
rearing
Occupancy estimate
f
1 Norrbotten (Se) Adult(s), egg/young 1997–2018 Stratified Full/partial Ground, air 4
e
4(X?Y?Z?G)/N
2 Finnmark (No) Adult(s), egg/young,
other evidence
2000–2018 Census Full Air, ground 44(X?Y?Z?G)/N
3 Lapland (Fi) Adult(s), egg/young,
other evidence
1990–2018 Census Full Ground, air 44(X?Y?Z?G)/N
4 Kola Peninsula (Ru) Adult(s), egg/young,
other evidence
2007–2018 Census Partial Ground 4(X?Y?Z?G)/N
7 Schuchya River (Ru) Adult(s), egg/young 2006–2016 Census Partial Ground 4(X?Y)/N
10 Seward Peninsula (US) Adult(s), egg/young 1998–2018 Census Full
e
Air, ground 4
e
4(X?Y?Z?G)/N
11 Denali Nat. Park (US) Adult(s), egg/young 2006–2018 Census Full Air, ground 44
12 South Yukon (Ca) Adult(s), egg/young 1981–2018 Random Partial Air 4(X?Y?Z?G)/N
13 Colville River (US) Adult(s), egg/young 1981–2018 Census Partial Ground 4(X?Y?Z?G)/N
16 North Slope Yukon (Ca) Adult(s), egg/young 1974–2015 Random Partial Air 4(X?Y?Z?G)/N
18 Hope Bay (Ca) Adult(s), egg/young 19821991 Census Partial Ground 4(X?Y?Z?G)/N
21 Northwest Greenland Adult(s), egg/young 1993–2018 Census Partial Air, ground 4(X?Y?Z?G)/N
22 Central West Greenland Adult(s), egg/young 19722005 Census Partial Air, ground 4(X?Y?Z?G)/N
24 Northeast Iceland Adult(s), egg/young,
other evidence
1981–2018 Census Full Ground 44(X?Y?Z?G)/N
a
See Fig. 3
b
Other evidence—egg shell fragments, molted feathers or down, recent excrement, fresh prey remains
c
Bold indicates monitoring is ongoing
d
Census—all known nesting territories checked systematically; stratified—sub-set of all known nesting territories checked systematically; random—random
selection of known nesting territories checked; full—known nesting territories receive multiple visits per breeding season; partial—single visits, or only in
brood-rearing period
e
Discontinuous
f
X= successful nest, nesting attempt, or pair—one in which at least one young reaches the minimum acceptable age for assessing success (Steenhof et al. 2017),
Y= unsuccessful nest, nesting attempt, or pair—a laying pair that failed before nestlings reached the minimum acceptable age for assessing success, Z= non-
laying Pair—a mated pair that fails to lay at least 1 egg in a given year (Steenhof et al. 2017), G= single non-laying individual—a non-mated individual
evidenced by an absence of territorial behavior, or reproductive-related activity, N= Count of known nesting territories surveyed
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Fig. 3 Trends (black lines) in gyrfalcon occupancy (black circles) and productivity (open circles) estimated using general additive models (see Table 4numerical outputs) for monitoring sites
distributed throughout the circumpolar Arctic. Gray bands represent 95 % confidence intervals. See Methods for definitions of occupancy and productivity. Light purple refers to Sub-Arctic,
medium purple to Low Arctic, and dark purple to High Arctic
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existing monitoring efforts, and assessing trends in occu-
pancy and productivity for peregrine falcons and gyrfal-
cons. We summarized information from 11 monitoring
sites where both species were surveyed, ten involving
peregrine falcons only, and three involving gyrfalcons
only. Fourteen monitoring sites were in the Nearctic and
ten were in the Palearctic. The most significant gaps in
coverage exist for eastern Russia, the Arctic Archipelago of
Canada, and East Greenland. Monitoring sites consisted of
stretches of rivers (or coastline) several hundred kilometers
long, or inland areas ranging in size from 100 to
84 000 km
2
(Tables S1 and S2) located between 60°N and
77°N. Depending on time of year, landscape type, and
spatial extent of study areas, surveys were conducted by
snowmobile, on foot (including skis), all-terrain vehicle,
boat, and helicopter (Tables 1and 2; Fig. 1). In almost all
areas, monitoring required accessing occupied nests to
record productivity data. Duration of monitoring projects
ranged from 5 to 66 years; 14 projects covered 30 years or
more, and four were up to 10 years in duration. In total,
monitoring was conducted over approximately 800 field
seasons combined, and as of 2018, 21 projects were active,
Table 3 Model structure, smoothing terms, and overall trends for peregrine falcon occupancy (top panel) and productivity (bottom panel) for
monitoring sites distributed throughout the circumpolar Arctic. The intercept estimates the grand mean. Effective degrees of freedom (edf) were
estimated using restricted maximum likelihood, where higher values indicate less smoothing and lower value indicate more smoothing. D(%)
equals the proportion of the null deviance explained by the model and pis the significance level (p\0.005 in bold) and n= number of years in
which 10 or more nesting territory visits were completed. Trend indicates whether the time series remained stable, or had decreased or increased
over the course of the monitoring period
Site# Site Occupancy *s(year) Smoothing terms Trend
Intercept SE edf pvalue D(%) n
1 Norrbotten (Se) 0.69 0.02 1.00 0.001 55.1 19 Decrease
3 Lapland (Fi) 0.68 0.01 2.24 < 0.001 81.4 38 Decrease
4 Kola Peninsula (Ru) 0.67 0.02 4.20 0.084 44.3 25 Stable
8 Yamal Peninsula (Ru) 0.67 0.03 1.00 0.006 58.2 11 Decrease
13 Colville River (US) 0.50 0.01 6.73 < 0.001 96.8 27 Increase
14 Yukon River (US) 0.48 \0.01 7.48 < 0.001 99.2 47 Increase
15 Yukon/Peel Rivers (Ca) 0.73 0.02 3.68 < 0.001 72.3 24 Stable
16 North Slope (Ca) 0.32 0.03 4.48 0.001 81.3 17 Increase
17 Mackenzie River (Ca) 0.60 0.02 1.00 0.001 80.31 10 Increase
19 Rankin Inlet (Ca) 0.74 0.01 1.52 0.428 6.6 35 Stable
20 Mary River (Ca)
21 Northwest Greenland
22 Central West Greenland 0.72 0.01 5.80 < 0.001 80.3 35 Stable
23 South Greenland 0.85 0.02 1.74 0.634 12.7 18 Stable
Site# Site Productivity *s(year) Smoothing terms Trend
Intercept SE edf pvalue D(%) n
1 Norrbotten (Se) 1.69 0.08 1.00 0.230 7.5 21 Stable
3 Lapland (Fi) 1.55 0.05 1.64 0.098 14.2 38 Stable
4 Kola Peninsula (Ru) 1.70 0.13 2.39 0.042 52.4 15 Increase
8 Yamal Peninsula (Ru)
13 Colville River (US) 1.25 0.06 1.35 0.023 26.0 27 Decrease
14 Yukon River (US) 1.48 0.05 3.93 0.001 39.8 47 Stable
15 Yukon/Peel Rivers (Ca) 1.15 0.04 2.75 < 0.001 84.2 24 Increase
16 North Slope (Ca)
17 Mackenzie River (Ca) 1.44 0.12 1.72 0.318 33.9 10 Stable
19 Rankin Inlet (Ca) 1.10 0.08 1.77 0.045 20.2 35 Decrease
20 Mary River (Ca)
21 Northwest Greenland
22 Central West Greenland 2.31 0.05 3.82 0.043 36.1 33 Stable
23 South Greenland 1.85 0.06 5.28 < 0.001 62.8 35 Decrease
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and these have the greatest potential to form the basis for
future coordinated monitoring (Tables 1and 2).
Trends in occupancy
Peregrine falcon data from Rankin Inlet (n= 35 years),
Kola Peninsula (n= 25 years), central West Greenland
(n= 35 years), South Greenland (n= 18 years), and Peel
and Yukon Rivers (n= 24 years), all suggest stable trends
in occupancy (Fig. 2, Table 3). GAM results for Rankin
Inlet and South Greenland indicate that long-term occu-
pancy has been linear (non-significant pvalues and low edf
scores). GAM results indicate that occupancy in central
West Greenland has been non-linear (significant pvalues
associated with high edf scores), showing increases
through the 1970s and 1980s, which have since declined
from a peak that occurred around 1990 to levels similar to
those recorded in the mid-1980s. Results from the Kola
Peninsula suggest that occupancy has varied over time (high
edf score), but are associated with a non-significant pvalue
and overlapping confidence intervals that suggest overall
stability. Although results from the Peel/Yukon River drai-
nages suggest that occupancy has varied through time (high
edf score and significant pvalue), rates of occupancy from
2010 to 2015 were similar to those observed in the 1970s,
having declined from the mid-1990s.
Increasing trends in peregrine falcon occupancy were
noted for the Mackenzie River (n= 10 years), Yukon River
(n= 47 years), North Slope (n= 17 years), and Colville
River, (n= 27 years; Fig. 2, Table 3). GAM results from
Table 4 Model structure, smoothing terms, and overall trends for gyrfalcon occupancy (top panel) and productivity (bottom panel) for
monitoring sites distributed throughout the circumpolar Arctic. The intercept estimates the grand mean. Effective degrees of freedom (edf) were
estimated using restricted maximum likelihood, where higher values indicate less smoothing and lower value indicate more smoothing. D%
equals the proportion of the null deviance explained by the model and pis the significance level (p\0.005 in bold) n= number of years in
which 10 or more nesting territory visits were completed. Trend indicates whether the time series remained stable, or had decreased or increased
over the course of the monitoring period
Site# Site Occupancy s(year) Smoothing terms Trend
Intercept SE edf pvalue D(%) N
1 Norrbotten (Se) 0.41 0.02 5.57 < 0.001 90.4 16 Stable
2 Finnmark (No) 0.44 0.02 5.03 0.001 77.9 19 Stable
3 Lapland (Fi) 0.51 0.02 5.18 < 0.001 74.8 24 Stable
4 Kola Peninsula (Ru) 0.50 0.06 1.71 0.563 25.7 10 Stable
7 Schuchya River (Ru) 0.44 0.04 1.72 0.175 39.6 11 Stable
10 Seward Peninsula (US) 0.33 0.01 0.92 0.004 51.0 14 Decrease
11 Denali National Park (US) 0.71 0.01 1.00 0.686 0.62 29 Stable
12 South Yukon (Ca) 0.78 0.01 7.34 < 0.001 78.6 35 Decrease
13 Colville River (US) 0.36 0.03 1.00 0.938 0.03 22 Stable
16 North Slope (Ca) 0.75 0.02 3.42 0.028 63.8 15 Stable
21 Northwest Greenland 0.45 0.04 1.92 0.464 31.9 10 Stable
24 Northeast Iceland 0.62 0.01 7.83 < 0.001 82.0 37 Stable
Site# Site Productivity *s(year) Smoothing terms Trend
Intercept SE edf pvalue D(%) N
1 Norrbotten (Se) 2.13 0.15 1.62 0.303 19.8 16 Stable
2 Finnmark (No) 1.36 0.14 1.54 0.205 19.9 19 Stable
3 Lapland (Fi) 1.09 0.09 3.34 0.035 45.4 24 Stable
4 Kola Peninsula (Ru)
7 Schuchya River (Ru) 1.75 0.13 1.00 0.304 11.6 11 Stable
10 Seward Peninsula (US) 1.50 0.11 1.32 0.739 7.24 14 Stable
11 Denali National Park (US) 1.45 0.10 1.00 0.481 1.85 29 Stable
12 South Yukon (Ca) 1.12 0.08 1.88 0.007 30.1 35 Decrease
13 Colville River (US) 1.20 0.09 5.84 0.007 74.14 20 Decrease
16 North Slope (Ca) 2.59 0.10 1.00 0.473 4.03 15 Stable
21 Northwest Greenland 2.75 0.14 1.00 0.236 17.0 10 Stable
24 Northeast Iceland 1.31 0.06 1.00 0.516 1.22 37 Stable
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the Mackenzie River indicate a shallow but steady increase
over time (significant pvalue and low edf score). Occu-
pancy on the Colville River increased from early 1980
through early 1990 (significant pvalue and high edf score),
and stabilized thereafter (Fig. 2, Table 3). On the Yukon
River in Alaska, results indicate a steady increase
throughout the monitoring period (significant pvalue
associated with non-overlapping confidence intervals).
Results from the North Slope indicate a non-linear trend
over the course of the monitoring period (high edf score,
significant pvalue, and non-overlapping confidence inter-
vals). Inspection of the graphical output indicates occu-
pancy declined through the 1980s, increased through the
1990s, and stabilized thereafter.
Decreasing trends in peregrine falcon occupancy were
observed for Norrbotten (n= 19 years), Lapland
(n= 38 years), and Yamal Peninsula (n= 11 years).
However, the validity of these trends is uncertain, and it is
possible that they are confounded with survey methods (see
Discussion for details).
For the gyrfalcon, stable trends in occupancy were
identified (non-significant pvalues and low edf scores) in
Denali National Park (n= 29 years), Colville River
(n= 22 years), Northwest Greenland (n= 10 years), and
Schuchya River (n= 11) throughout their respective
monitoring periods (Fig. 3, Table 4). Despite an apparent
non-linear trend for occupancy on the Kola Peninsula
(n= 10), GAM results reveal (Fig. 3, Table 4) that occu-
pancy has also remained constant through time (non-sig-
nificant pvalue, low edf score, and overlapping confidence
intervals). Although stable over the long-term, gyrfalcon
occupancy in Iceland (n= 37) exhibited regular cycles
(significant pvalue combined with high edf score). Trends
for Finnmark (n= 19), Norrbotten (n= 16), North Slope
(n= 15), and Lapland (n= 24) all exhibited non-linear
patterns (increasing trend followed by a period of
decreasing occupancy) which are supported by GAM
results (significant pvalue, high edf score, and non-over-
lapping confidence intervals). A similar non-linear trend
(significant pvalue, high edf score, and non-overlapping
confidence intervals) is apparent for the North Slope where
occupancy initially decreased in the 1980s followed by an
increase in the 1990s (Fig. 3, Table 4).
Decreasing trends in gyrfalcon occupancy were
observed for the Seward Peninsula (n= 14 years) and
South Yukon (n= 35 years). The apparent decline on the
Seward Peninsula has been constant (significant pvalue,
low edf score, and non-overlapping confidence intervals),
whereas the overall decline in occupancy for the South
Yukon exhibits non-linear trends (Fig. 3, Table 4). None of
the 11 monitoring sites recorded trends indicative of in-
creasing occupancy in gyrfalcon populations.
Trends in productivity
For the peregrine falcon, stable trends in productivity were
noted for Norrbotten (n= 21 years), Lapland
(n= 38 years), and Mackenzie River (n= 10 years). All
exhibit non-significant pvalues, low edf scores, and
overlapping confidence intervals consistent with constant
productivity through time (Fig. 2, Table 3). GAM results
for the Yukon River (n= 47 years) and central West
Greenland (n= 33 years) indicate that peregrine falcon
productivity was non-linear (moderately high edf, signifi-
cant pvalue, and non-overlapping confidence intervals);
however, inspection of the trend lines for each population
shows overall long-term stability (Fig. 2, Table 3).
Increasing trends in peregrine falcon productivity were
observed for the Yukon/Peel River drainages
(n= 24 years) and the Kola Peninsula (n= 15 years). Data
exhibit weak non-linearity (relatively low edf scores
accompanied by significant pvalues and non-overlapping
confidence intervals), and inspection of the trend lines for
each population supports the numerical evidence for
increased productivity (Fig. 2, Table 3).
Decreasing trends in peregrine falcon productivity were
recorded for Rankin Inlet (n= 35 years) and the Colville
River (n= 27 years). GAM results exhibit low edf scores
accompanied by significant pvalues and non-overlapping
confidence intervals which indicate linear change through
time (Fig. 2, Table 3). Inspection of the trend lines for each
population indicates that productivity in both populations
declined marginally throughout the monitoring period.
South Greenland (n= 35 years) exhibited high edf scores
accompanied by a significant pvalue and non-overlapping
confidence intervals which indicate non-linear change
through time. Inspection of the trend line indicates a period
of relative stability followed by a decline over the last
decade.
For gyrfalcons, stable trends in productivity were
observed for Norrbotten (n= 16 years), Finnmark
(n= 19 years), Schuchya River (n= 11 years), Seward
Peninsula (n= 14 years), Denali (n= 29 years), North
Slope (n= 15 years), Northwest Greenland (n= 10 years),
Iceland (n= 37 years), and Lapland (n= 24 years). Other
than Lapland, all exhibited non-significant pvalues, low
edf scores, and overlapping confidence intervals associated
with linear patterns through time. Inspection of trend lines
for each of these populations is consistent with GAM
results (Fig. 3, Table 4). Lapland exhibited a non-linear
trend where productivity increased through the late 1990s/
early 2000s, decreasing since.
None of the 11 monitoring sites recorded trends
indicative of increasing productivity in gyrfalcon
populations.
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ADecreasing trend in gyrfalcon productivity is evident
for South Yukon (n= 35 years), where data exhibited a
low edf score accompanied by a significant pvalue and
non-overlapping confidence intervals, all of which indicate
linear change through time. Inspection of the trend line
indicates that productivity declined throughout the moni-
toring period. However, for the Colville River
(n= 20 years), GAM results indicate a non-linear trend
(high edf score, significant pvalue, and non-overlapping
confidence intervals). Inspection of the trend line reveals a
cyclic patter with overall downward trend through the
monitoring period (Fig. 3, Table 4).
Other FEC attributes
Although demographic parameters were reported regularly,
results for other FEC attributes were not reported consis-
tently among monitoring sites. Here we summarize infor-
mation pertinent to FEC attributes other than demography.
Abundance
The current population of peregrine falcons in the Arctic
exceeds 20 000 pairs (Table S4), which is likely an
underestimate (Franke 2016). Throughout North America
and Europe, the peregrine falcon experienced widespread
population declines from the 1950s through 1970s due to
organochlorine pesticides (Peakall and Kiff 1979; Peakall
et al. 1983; Risebrough and Peakall 1988; Court et al.
1990; Henny et al. 1994; Johnstone et al. 1996; Franke
et al. 2010). By the 1970s, the nominate race F. p. pere-
grinus in the Palearctic was virtually extirpated, including
in northern Fennoscandia (Lindberg et al. 1988), where it is
considered to be recovering. In North America, the species
was extirpated over its range east of the Rocky Mountains
and south of the boreal forest by 1975 (Fyfe et al. 1976).
However, in most tundrius and calidus populations, the
effects of organochlorine pesticides are thought to have
been less severe compared to populations south of the
Arctic biome (Burnham and Mattox 1984; Mattox and
Seegar 1988; Falk et al. 2018). Most contemporary pere-
grine falcon populations are considered to be recovered
(White et al. 2013a). For example, populations in Alaska
and northern Fennoscandia have experienced considerable
increases in abundance. In sub-arctic Fennoscandia, the
peregrine population recovered from a low of 65 pairs in
1975 (Lindberg et al. 1988) to approximately 750 pairs by
2017 (Table S4). Increasing abundance of northern pere-
grine falcon populations is also supported by standardized
autumn migration counts. For example, counts at Falsterbo,
Sweden, increased from an annual average of 2.5 birds/
year from 1973 to 1983 to 88 birds/year from 2005 to 2015
(Kjelle
´n2018). Similar data from eastern North America
show annual average of nine peregrine falcons/year from
1972 to 1981, increasing to 63 birds/year from 2009 to
2018 (Hawk Mountain International 2019).
The total population (i.e., Arctic-wide) of gyrfalcons is
estimated to be fewer than 11 000 pairs (Table S4). No
long-term changes in population size/density have been
reported for gyrfalcons (Barichello and Mossop 2011;
Bente 2011; Koskimies 2011; Nielsen 2011). Johansen and
Østlyngen (2011) reported no change in the number of
gyrfalcon nesting attempts from two 11-year periods sep-
arated by 150 years. The gyrfalcon was not affected by
pesticide residues that affected the peregrine (Booms et al.
2008).
Phenology
Breeding phenology (e.g., laying date, hatching date)
summaries for each monitoring site are reported in
Table S5. Although data describing breeding phenology are
likely estimable for most monitoring sites, analyses of
long-term trends are currently only available for two sites:
for peregrine falcons breeding along the Mackenzie River,
breeding advanced 1.5 to 3.6 days decade
-1
depending on
latitude, from 1985 to 2010 (Carrie
`re and Matthews 2013).
Similarly, hatching date in peregrine falcons in South
Greenland advanced 0.9 days decade
-1
during the period
from 1981 to 2017 (Falk and Møller unpubl.). There are
currently no data available on changes in gyrfalcon phe-
nology, but the two species may respond differently: for
example, although low spring temperatures are associated
with later arrival of gyrfalcons at nesting territories in
Nunavut, there was no effect on laying dates (Poole and
Bromley 1988).
Spatial structure
Across the Palearctic tundra biome, the peregrine falcon
generally breeds farther north than the gyrfalcon, whereas
the opposite is true in the Nearctic (Pokrovsky and Lecomte
2011). In the Nearctic, tundrius breeds north of the tree-line,
wherever suitable nesting habitat and sufficient prey are
present, from Alaska throughout northern Canada, to
Greenland, where breeding occurs to at least to latitude 77°N
(Burnham et al. 2012; White et al. 2013a). Tundrius inter-
grades with Falco peregrinus anatum throughout the North
American taiga, forming a cline of variation. Tundrius and
calidus are long-distance migrants (Yates et al. 1988; White
et al. 2013a). Tundrius winters throughout South and Central
America, the Caribbean Islands, as well as the southern
United States, and Mexico (Yates et al. 1988; Mattox and
Restani 2014). In the Palearctic, calidus intergrades with the
F.p. peregrinus towards the south and west, and with F.p.
japonicus in NE Siberia (White et al. 2013a). Calidus winters
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mainly from the Mediterranean and eastwards across South
and Southeast Asia (Dixon et al. 2017; Sokolov et al. 2018),
but some individuals winter as far south as southern Africa
(Meyburg et al. 2017). Yates et al. (1988) concluded that
breeding populations originating in the western and eastern
portions of the North American Arctic and sub-Arctic tend to
separate longitudinally during outward migration. A similar
migratory pattern exists for peregrine falcons breeding in
northern Eurasia, which also separate longitudinally (Dixon
et al. 2012; Sokolov et al. 2018). Peck et al. (2018) estimated
the breeding distribution and habitat selection of the pere-
grine falcon in Nunavut, Canada, and indicated that pere-
grine falcons selected nesting territories in rugged terrain, in
areas with higher than average summer temperatures, pro-
ductive land cover types, lower mean elevations, and lower
mean summer precipitation. Gyrfalcons inhabit tundra and
taiga regions from 82°N in Greenland to the sub-Arctic as far
south as 55°N in Alaska and Canada, and 51°N at Kamchatka
in Russia (Pokrovsky and Lecomte 2011). The gyrfalcon is a
year-round resident in Iceland, the only country where it is
not sympatric with the peregrine falcon. The large islands
distributed from Svalbard (Norway) to Severnaya Zemlya
(Russia) have not been colonized by either species. In North
America and Fennoscandia, the gyrfalcon is generally con-
sidered to be a northern resident (Booms et al. 2008) as many
breeding-aged birds remain within the breeding range
throughout the year (Cade 1982; Poole and Bromley 1988).
Immature birds are much more likely to winter south of
breeding range (Potapov and Sale 2005). Icelandic gyrfal-
cons are entirely resident (Nielsen and Cade 1990), whereas
those in Russia are partly migratory, likely depending on
food availability (Potapov and Sale 2005). Greenlandic
gyrfalcons are generally short-distance migrants, but are also
known to winter on the pack ice where seabirds are available
(Burnham and Newton 2011). Although little information is
available for assessing changes in the spatial extent of the
breeding distribution of Arctic falcons, Burnham et al.
(2012) attributed increased numbers of peregrine falcon
nesting territories in Northwest Greenland to range expan-
sion made possible by ameliorating climatic conditions (i.e.,
spring and autumn extensions). In northern Russia, gyrfalcon
breeding distribution may have expanded due to availability
of stick nests (i.e., built by ravens or rough-legged buzzards)
on recently constructed anthropogenic features (e.g., railway
bridges and oil rigs) in areas that were previously devoid of
ravens (Morozov 2011, Appendix S1).
Temporal cycles
Apart from the widespread pesticide-induced population
decline and subsequent recovery of peregrine falcons,
breeding populations are known to be remarkably
stable with very little among-year variation in breeding
density and occupancy (Newton 1988). Although breeding
success (productivity) can be highly variable, it does not
manifest as cyclic patterns associated with prey, but rather
is likely due to effects of weather (Anctil et al. 2014;
Carlzon et al. 2018). Icelandic gyrfalcons exhibit cyclic
trends where occupancy lags spring density of ptarmigan
by four years (Nielsen 2011). Falkdalen et al. (2011)
indicated that reproductive rates of gyrfalcons in central
Sweden followed a three-year cycle where the count of
breeding pairs was related to the count of nestlings pro-
duced 3 years earlier, and that the best predictor of repro-
ductive success was the production of willow ptarmigan
chicks in the prior year. In Finland (with some nests bor-
dering on Sweden and Norway), Koskimies (2011) indi-
cated that ptarmigan species overwhelmingly dominated
the annual diet of gyrfalcons, and that fluctuations in
ptarmigan had a marked effect on reproductive success.
Mossop (2011) indicated the presence of stable, regular,
synchronous, 10-year cycles in gyrfalcons and ptarmigan in
Yukon, and (Barichello and Mossop 2011) reported higher
reproductive success in gyrfalcons (young fledged per nest)
when ptarmigan were abundant than when ptarmigan were
scarce.
Health
The negative health effects and associated global popula-
tion declines due to contamination from organochlorine
pesticides in peregrine falcons are well established (see
Hickey 1969; Cade et al. 1988). However, over the past
decades pesticide loads have declined to levels that do not
cause population effects (Wegner et al. 2005; Vorkamp
et al. 2009; Franke et al. 2010; Andreasen et al. 2018; Falk
et al. 2018).
Recent studies have shown that peregrine falcons are
exposed to several other contaminants. Brominated flame
retardants (BFRs) are compounds that, in some cases, are
persistent in the environment, bioaccumulative, and can
cause endocrine disruption (Darnerud 2008). Concentra-
tions of the brominated flame retardant, BDE-209, have
increased in peregrine falcon eggs from Greenland, and
peaked in eggs from Europe, likely due to regulation of the
compound (Vorkamp et al. 2018). Despite the potential
negative effects of these compounds, and their presence in
peregrine falcon populations in Europe and North America
(Guerra et al. 2012), there is currently no evidence indi-
cating detrimental health effects at the population level in
peregrine falcons. In addition to BFRs, peregrine falcon
eggs collected in South Greenland from 1986 to 2014 also
showed variable, but ongoing exposure to perfluoroalkyl
substances and polychlorinated naphthalenes (Vorkamp
et al. 2019). Barnes et al. (2019) documented widespread,
but low levels of mercury exposure in peregrines migrating
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from the northern latitudes of North America. Although the
concentration associated with toxic effects in peregrine
falcons is unknown, recent population growth of northern
peregrine falcon populations suggests that health effects
due to mercury exposure are currently of no consequence.
Analyses of contaminants in gyrfalcons indicate low con-
centrations of organochlorines and heavy metals. Where
gyrfalcons prey primarily on ptarmigan, they have low,
non-toxic body burdens of persistent contaminants; how-
ever, a shift in diet that incorporates migratory waterfowl
can result in higher concentrations of contaminants, par-
ticularly for mercury (Lindberg 1984; Jarman et al. 1994;
Matz et al. 2011). As part of a study to assess mercury
concentrations in marine and terrestrial birds, Burnham
et al. (2018) indicated that some peregrine falcons exhib-
ited mercury concentrations suggestive of medium risk for
toxicity (i.e., between 1000 and 3000 ng g
-1
wet weight).
Burnham et al. (2018) did not quantify mercury concen-
trations in adult gyrfalcons, and it is unknown whether
gyrfalcons have accumulated mercury to the same degree
that peregrine falcons have, although in museum specimens
from Greenland (1880–2000) the levels were roughly
comparable between the two species over time (Dietz et al.
2006).
Diversity
Despite considerable morphological variation among
peregrine falcon subspecies, White et al. (2013b) indicated
that haplotypes among 12 of the 19 recognized subspecies
(including tundrius, but not calidus) were broadly shared.
Using North American tissue samples collected pre-col-
lapse, Brown (2007) indicated that anatum and tundrius
were genetically indistinguishable from one another, but
could be differentiated from F. p. pealei. However, post-
recovery samples indicated that tundrius and anatum could
be differentiated due to increased genetic diversity within
southern anatum populations, likely due to use of exotic
subspecies for captive breeding during the recovery phase
(Brown 2007). Similarly, using Alaskan samples, Talbot
et al. (2017) indicated that although pealei could be
genetically differentiated from tundrius and anatum, the
latter two subspecies could not be distinguished geneti-
cally. Using samples collected during migration (1985 to
2007) at Padre Island, Texas, Johnson et al. (2010) found
little difference between tundrius and anatum, and sug-
gested that delineation between the two subspecies breed-
ing at northern latitudes was not justified. For gyrfalcons,
Johnson et al. (2007) indicated little genetic structure
among populations throughout a large portion of their
circumpolar distribution. Greenlandic and Icelandic popu-
lations were considered separate, whereas Norway, Alaska,
and Canada were identified as a single population consis-
tent with contemporary gene flow across Russia.
DISCUSSION
The work undertaken here represents the first formal col-
laboration among scientists involved in the Arctic Falcon
Specialist Group. Although disparate application of survey
methods among research groups currently hampers abso-
lute comparison of occupancy and productivity among
monitoring sites (see below for additional discussion), it
does not preclude relative comparison of trends at the scale
of the circumpolar Arctic, or regionally within the Nearctic
and Palearctic. From the standpoint of occupancy and
productivity, our results indicate that most peregrine falcon
and gyrfalcon populations are generally stable, and
assuming that these patterns hold beyond the temporal and
spatial extents of the monitoring sites we report on here, it
is reasonable to suggest that breeding populations at
broader scales are similarly stable.
At the scale of the circumpolar Arctic, occupancy trends
for peregrine falcons and gyrfalcons were available from
12 monitoring sites meeting the criteria for inclusion in
analyses, whereas productivity trends were available from
10 sites monitoring peregrine falcons and from 11 sites
monitoring gyrfalcons. For peregrine falcons, nine of 12
monitoring sites indicated that occupancy was either
stable or had increased over the course of monitoring, and
three monitoring sites resulted in trends that indicate
occupancy had declined. Seven of 10 peregrine falcon
monitoring sites presented productivity trends that were
either stable or increasing, and three resulted in trends that
had declined. For gyrfalcons at the circumpolar scale,
occupancy trends at 10 of 12 monitoring sites were found
to be stable or had increased, whereas occupancy at the two
remaining monitoring sites had declined. Productivity
trends for gyrfalcons at nine of 11 monitoring were stable,
none showed evidence of increased productivity, and two
presented trends that declined over the course of the
monitoring period.
Within the Nearctic only, peregrine falcon monitoring
has occurred at 12 monitoring sites, and eight had data sets
that involved monitoring at 10 or more nesting territories in
10 or more years. Occupancy trends at all of the peregrine
falcon monitoring sites in the Nearctic were either stable or
had increased. Productivity trends were available for seven
Nearctic monitoring sites, of which four were considered to
be stable or to have increased and three presented pro-
ductivity trends that had decreased. In the Palearctic,
peregrine falcon monitoring has occurred at nine moni-
toring sites, and four had data sets that involved annual
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monitoring at 10 or more nesting territories in 10 or more
years. Occupancy trends were considered to be stable at
one monitoring site, and three monitoring sited presented
trends that have declined. Two of the monitoring sites for
which declines were evident (Norrbotten and Lapland) are
located in close proximity to one another, and based on
these results, it may be tempting to suggest that a relatively
local decline in occupancy has occurred. However, in
Lapland, occupancy is considered to be biased high during
the 1980s as a result of failure to report nesting territories
that had been occupied, but did not produce young. We
attempted to account for this by excluding the data from
the 1980s (i.e., truncating early years); however, this had
no effect on the downward trend. In Norrbotten, it is
unclear whether the apparent decline in occupancy is due to
limitations in survey methods, or if it reflects the demog-
raphy of a recovering population (Lindberg et al. 1988).
More specifically, it is important to note that declining
occupancy that is evident in Norrbotten and Lapland is at
odds with abundance estimates, which clearly show that
counts have increased by 5–10 % annually since the 1990s
(Lindberg 2008). Peregrine falcon productivity trends in
the Palearctic were only available for three monitoring
sites, all of which were considered to be stable, or to have
increased.
Within the Nearctic only, gyrfalcon monitoring has
occurred at eight monitoring sites, of which six had data
sets that involved monitoring at 10 or more nesting terri-
tories in 10 or more years. Occupancy trends for gyrfalcons
in the Nearctic were stable at four monitoring sites, and
decreased at the remaining two, both of which were in the
western Nearctic. Productivity trends for gyrfalcons in the
Nearctic were available for six monitoring sites, four of
which were stable and two showed declines. Only the
South Yukon population in Canada had declines in both
occupancy and productivity, and it is interesting to note
that this population is most southernly located relative to
any other Nearctic monitoring sites. Within the Palearctic,
monitoring has occurred at six gyrfalcon monitoring sites,
all of which had data sets that involved monitoring at 10 or
more nesting territories in 10 or more years. Trends for
both occupancy and productivity were stable in all six
monitoring sites.
Although directional changes in occupancy over time
can serve as a metric of population status (MacKenzie et al.
2003), we caution against conflating counts of occupied
nesting territories with counts of individual animals (or in
this case, with breeding pairs), and concluding that the
count of occupied nesting territories reflects local abun-
dance. Although exceptions exist, it is generally inappro-
priate to equate the status and count of nesting territories
(i.e., occupied or unoccupied) with the existence (or count)
of individuals capable of occupying them. In any given
year, it is not unusual for nesting territories to be unoc-
cupied despite the fact that individuals exist, and possess
the potential to occupy them. Thus, a low occupancy rate
does not necessarily imply local depletion in numbers of
animals, and a high occupancy rate does not necessarily
imply local gain in the number of animals. Exceptions to
this general pattern exist for surveys that have been con-
ducted on rivers only, where the entire river (i.e., all
habitat) has been regularly surveyed throughout the mon-
itoring period, and where previously unoccupied nesting
territories (i.e., during the monitoring period) are then
assumed to have been occupied at some historical point
prior to discovery. By back-casting the total count of
known territories to year one of the monitoring period
(regardless of the year in which the territory was first
deemed occupied), the denominator in the occupancy
equation becomes invariant. Under these conditions,
occupancy can serve as a proxy for local annual abun-
dance. In our study, only the Colville River and Yukon
River (USA) fit these criteria.
Multiple surveys within breeding seasons explicitly
account for detection error, and when combined with
census-like sampling designs are known to reduce bias due
to detection error (Ke
´ry and Schmidt 2008). Although
detection of nesting territories occupied by successful pairs
is straightforward, bias in estimates of occupancy can result
from non-detection of failed breeding pairs (i.e., failed
nesting attempt), non-laying pairs, and individuals that
remain cryptic during pre-laying and incubation. Failed
nesting attempts can easily go undetected, particularly
when nesting territories are visited only once per breeding
season, usually late in the breeding season when nest visits
are timed to coincide with the period when nestlings are of
an age for fitting leg bands. Bias can also be exacerbated by
lower survey effort during the initial few survey years, and
is further challenged by the presence of ephemeral nesting
territories that may be encountered in the first few years,
but which remain unoccupied in later years. These factors
drive occupancy towards 1.0 in the early years of the
monitoring, and the problem usually remains unresolved
until sufficient time has elapsed to account for irregularly
occupied nesting territories. Thus, a decline in occupancy
can represent an artifact of insufficient survey coverage,
and in these cases should not be interpreted as represen-
tative of a true decline in occupancy. Excluding the initial
few years of monitoring from a time series to account for
this is reasonable.
Detection is always imperfect, and estimating the pro-
portion of occupied sites without accounting for detection
error invariably leads to an underestimation of occupancy
(Ke
´ry and Schmidt 2008). Detection of occupied nesting
territories can be influenced by the type of observation
platform. For example, surveys conducted by fixed-wing
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aircraft preclude detailed inspection of nesting sites for
evidence of a nesting attempt (e.g., egg shell fragments,
molted feathers or down, recent excrement, fresh prey
remains) that is possible during ground-based and, to some
degree, helicopter surveys. However, aerial surveys allow
for rapid coverage of large spatial extents in remote areas
that can be challenging with ground-based surveys.
Detection probability of cliff-nesting raptors during aerial
surveys likely varies by observer experience and the
number of independent observers, seating arrangement in
the aircraft, platform type (fixed-wing vs. rotary-wing),
species, and location, but can be as high as 80 % (Booms
et al. 2010). Detection probability for well-designed
ground-based surveys is likely high and may approach 100
%, though this can also vary with variables such as terrain
ruggedness, timing of the visits, number and duration of
visits, weather, time of day, and observer experience.
However, it is relatively straightforward to include these
variables as part data collection process, and then use them
as covariates in the detection modeling process.
Survey effort and design typically varies according to
research priorities and capacity. Thus, we caution against
comparing estimates among monitoring sites that use
widely differing approaches to calculate estimates. Within
study populations, it is typical for a sub-set of all known
nesting territories to be regularly occupied, while others are
occupied only in certain years out of many. A stratified
sampling approach usually samples regularly occupied
territories, whereas census-like sampling designs typically
survey all known nesting territories (and intervening
habitat that may harbor breeding birds) regardless of
occupancy frequency. Logistics, funding limitations, and
research priorities have resulted in partial surveys, where
data collection was typically limited to only the brood-
rearing period resulting in underestimates of occupancy
and overestimates of productivity per occupied territory.
Furthermore, many researchers record the number of young
before nestlings have reached the recommended minimum
acceptable age, which can result in further overestimation
of productivity regardless of whether reproductive success
is measured per territorial pair or per occupied territory. In
reality, rather than estimating productivity per se (number
of young hatched from a single nesting attempt by a pair of
birds), many researchers actually report mean brood size
for nestlings aged 10 days or more, or alternately for
nestlings less than 10 days of age (see Franke et al. 2017
for distinction). These are important methodological
problems that most likely cannot be corrected retrospec-
tively, but could be accounted for in future monitoring.
Climate change has been identified as a major driver
affecting the biodiversity of Arctic ecosystems (Chris-
tensen et al. (2013). In this regard, warmer Arctic tem-
peratures have facilitated range expansion of pathogens
and parasites (Loiseau et al. 2012; Kutz et al. 2013; Van
Hemert et al. 2014), and Arctic-nesting falcons may
experience negative impacts from novel pathogens and
parasites. For example, Franke et al. (2016) reported the
first observations of nestling mortality due to biting black
flies in peregrines (F. p. tundrius), and suggested that
ongoing annual monitoring will be required to determine
whether hematophagous black flies (and other parasites and
pathogens) are to become a regular and frequently occur-
ring challenge for avian species raising altricial young in
the arctic (Lamarre et al. 2018). Similarly, shifts in plant
assemblages (Wheeler et al. 2015) may influence the dis-
tribution and demography of tundra-obligate species such
as the gyrfalcon. Species associated with dense shrubs and
taiga forest may benefit from range expansion, while tundra
obligates will potentially experience climate-induced
habitat loss and extirpation from historically occupied
areas. Increases in density, height, and distribution of
shrubs on tundra landscapes have already been reported in
Arctic and sub-Arctic biomes, and are predicted to continue
(Myers-Smith et al. 2015). Indeed, Johansen and Østlyngen
(2011) indicated that despite regular occupancy at 60 % of
historically used nesting territories, evidence of human
disturbance or environmental change including expansion
of birch (Betula pubescens) forests was evident at nesting
territories that had become irregularly used or experienced
long-term vacancy. Expansion of birch forest may benefit
willow ptarmigan, while simultaneously negatively
affecting rock ptarmigan, which prefer open habitat (My-
ers-Smith et al. 2015; Fuglei et al. 2019). Booms et al.
(2011) used fundamental niche to estimate backward and
forward projections of gyrfalcon distribution in Alaska.
Although results are entirely predictive and should be
interpreted cautiously, forward-models projected spatial
contraction of gyrfalcon distribution was likely. Backward
projections similarly suggested that gyrfalcon distribution
in Alaska had experienced climate-related spatial contrac-
tion in the past.
CONCLUSION
In general, organization of activities among Arctic scien-
tists actively involved in research of large falcons in the
Nearctic and Palearctic has been poorly coordinated.
However, ample opportunity exists to establish a coordi-
nated circum-Arctic monitoring program for both falcon
species (and potentially other raptors, e.g., rough-legged
hawks) that supports CBMP goals (Christensen et al. 2013)
including results shared directly with the CBMP Terrestrial
Bird Expert Network (see Box 1for specific
recommendations).
ÓRoyal Swedish Academy of Sciences 2019
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Box 1 Recommendations for future monitoring of Arctic falcons
A F
B G
C H
DI
E J
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We have highlighted several challenges that preclude
direct comparisons of FEC attributes among monitoring
sites, and have offered straightforward explanations for
existing deficiencies (see Box 1). Notwithstanding the
limitations associated with individual programs, we rec-
ommend that researchers conduct ‘full’ surveys that can
explicitly account for detection error, and combine these
repeated visits with census-like sampling designs which are
most robust. Second, we recommend that researchers
carefully consider whether their data reflect estimates of
productivity or mean brood size. These are critical issues
that most likely cannot be corrected retrospectively, but we
recommend that researcher explicitly account for this detail
in future monitoring.
Although we have offered discussion regarding under-
lying mechanisms (i.e., drivers of observed trends), anal-
yses that have been included here are limited to
presentation of temporal trends related to priority FEC
attributes (i.e., time is the only covariate in all models). We
therefore recommend that, in the short-term, a retrospective
analysis that involves correlating FEC attributes with other
covariates that are readily available (e.g., distance to dis-
turbance, temperature, and precipitation), be conducted
among monitoring sites. Considering evidence that shows
early lay-dates are associated with increased nestling sur-
vival for Arctic-nesting raptors (Anctil et al. 2014), and
that early lay-dates are associated with pre-laying body
condition (Lamarre et al. 2017), we recommend investi-
gating the broad scale relationship between lay-date (FEC
attribute ‘phenology’) and productivity. This would con-
tribute to an understanding of mechanisms affecting indi-
vidual reproductive success, particularly if these covariates
are used in conjunction with biotic (e.g., food supply) and
abiotic (e.g., temperature and precipitation) variables.
Acknowledgements Support to coordinate data acquisition and
compilation, and manuscript preparation was provided to AF by
Environment and Climate Change Canada, and to KF by the Danish
Cooperation for Environment in the Arctic (DANCEA) of the Danish
Environmental Protection Agency (MST-112-00276). We thank all
members of the Arctic Falcon Specialist Group for freely sharing their
data, and for contributing to the development of this manuscript. We
are particularly grateful to the volunteer field staff. AS, VS, and IF
were supported by Russian Fund for Basic Research and Yamal
Government; other funding agencies and permitting authorities of
each of the monitoring sites are too numerous to name; none of the
work presented here would be possible without their support.
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AUTHOR BIOGRAPHIES
Alastair Franke is Principle Investigator of the Arctic Raptors Pro-
ject, a research group working in Nunavut, Canada focused on
studying the ecology of Arctic-nesting raptors and their prey within
the context of climate change. He holds an adjunct professorship in
the Department of Biological Sciences at the University of Alberta,
Edmonton, Alberta, Canada.
Address: Department of Biological Sciences, University of Alberta,
CW 405, Biological Sciences Bldg., Edmonton, AB T6G 2E9,
Canada.
Address: Arctic Raptor Project, P.O. Box 626, Rankin Inlet, NT X0C
0G0, Canada.
e-mail: alastair.franke@ualberta.ca
Knud Falk (&) is an independent researcher and consultant on
Arctic biodiversity monitoring and management; since 1981, together
with Søren Møller, he has been leading the peregrine falcon moni-
toring project in South Greenland.
Address: Stockholm, Sweden.
e-mail: knudfalk@hotmail.com
https://www.vandrefalk.dk
Kevin Hawkshaw is a Ph.D. candidate at the University of Alberta
studying predator–prey interactions in peregrine falcons as part of the
Arctic Raptors Project based in Rankin Inlet, Nunavut, Canada.
Address: Department of Renewable Resources, University of Alberta,
Edmonton, Canada.
e-mail: hawkshaw@ualberta.ca
Skip Ambrose is a retired U.S. Fish and Wildlife Service wildlife
biologist, working primarily on Falco peregrinus anatum in interior
Alaska. He has surveyed the upper Yukon River for peregrine falcons
annually since 1973, and continues this effort after retirement.
Address: Fairbanks, USA.
e-mail: skipambrose@frontiernet.net
David L. Anderson is Director and founder of The Peregrine Fund’s
Gyrfalcon and Tundra Conservation Program and Adjunct Professor
in the Department of Biology at Boise State University. His research
interests include the ecology of forest canopies and canopy access
methods for science.
Address: The Peregrine Fund, 5668 W. Flying Hawk Lane, Boise, ID
83709, USA.
e-mail: danderson@peregrinefund.org
Peter J. Bente is a wildlife biologist with research interests focused
on the distribution, abundance, population trends, and ecological
relationships of cliff-nesting raptor communities in Boreal and Arctic
zones of Alaska.
Address: Alaska Department of Fish & Game, Juneau, USA.
e-mail: pjbente@cox.net
Travis Booms is a regional wildlife biologist for the Alaska
Department of Fish and Game conducting research on northern rap-
tors, songbirds, and mammals of conservation concern.
Address: Alaska Department of Fish & Game, Juneau, USA.
e-mail: travis.booms@alaska.gov
123 ÓRoyal Swedish Academy of Sciences 2019
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Kurt K. Burnham is President and founder of the High Arctic
Institute and has worked throughout Greenland for the past 28 years
studying peregrine falcons and gyrfalcons and their prey. Primary
research interests are in High Arctic ecosystems with a focus on
migratory strategies, pollutants, and population biology.
Address: High Arctic Institute, 603 10th Avenue, Orion, IL 61273,
USA.
e-mail: kburnham@higharctic.org
Johan Ekenstedt is an independent researcher that has studied the
ecology of gyrfalcons in Norrbotten County in Sweden since 1998
through a long-term monitoring project.
Address: Tavelsjo
¨, Sweden.
e-mail: jekenstedt@gmail.com
Ivan Fufachev is a researcher at the Arctic Research Station of
Institute of Plant and Animal Ecology of Ural branch of Russian
Academy of Sciences. He has studied birds of prey in Yamal
Peninsula since 2012.
Address: Arctic Research Station of Institute of Plant and Animal
Ecology Ural Branch, Russian Academy of Sciences, Zelenaya Gorka
Str., 21, Labytnangi, Yamal-Nenets Autonomous District, Russia
629400.
e-mail: fufa4ew@yandex.ru
Sergey Ganusevich is an independent researcher. In 1977, he dis-
covered the diverse raptor community on the Kola Peninsula and
since then has monitored the populations annually. His work as a
director of the Center for Rescue of Wild Animals focuses on
addressing the illegal trade of raptors and rehabilitation of poached
falcons back to the wild.
Address: Center for Rescue of Wild Animals (Independent Non-profit
Organization), Moscow, Russia.
e-mail: sganusevich@mail.ru
Kenneth Johansen is an independent researcher, who for the last
three decades have studied the ecology of gyrfalcons in Finnmark
County, Norway, through a long-term monitoring project.
Address: Raptor Group Finnmark, Alta, Norway.
e-mail: kennethalta@hotmail.com
Jeff A. Johnson is an associate professor in the Department of
Biological Sciences and Advanced Environmental Research Institute
at University of North Texas. His primary research interests are in
conservation and evolution biology focused on raptors and grouse.
Address: Department of Biological Sciences, Advanced Environ-
mental Research Institute, University of North Texas, 1155 Union
Circle, #310559, Denton, TX 76203, USA.
e-mail: jeff.johnson@unt.edu
Sergey Kharitonov is a leading research biologist of the Bird
Ringing Centre of Russia, A.N. Severtsov Institute of Ecology and
Evolution RAS, Ph.D., DSc.
Address: Bird Ringing Centre of Russia IEE RAS, Moscow, Russia
117312.
e-mail: serpkh@gmail.com
Pertti Koskimies worked at Zoological Museum, University of
Helsinki, for planning and running the monitoring program of Finnish
avifauna in the 1980s and 1990s. He is currently an independent
biologist specialized on gyrfalcon and osprey biology since the early
1990s.
Address: Kirkkonummi, Finland.
e-mail: pertti.koskimies@kolumbus.fi
Olga Kulikova has been studying Arctic raptor breeding and
migration in North-West Russia for the last decade and is a doctoral
candidate in The University of Konstanz (Germany) making a dis-
sertation on movement ecology of the rough-legged buzzard. She is
also currently employed in the Institute of Biological Problems of the
North in Magadan (Russia).
Address: Institute of Biological Problems of the North, 18 Portovaya
Street, Magadan, Russia 685000.
e-mail: gaerlach@gmail.com
Peter Lindberg is a senior researcher at the Department of Biological
and Environmental Sciences at Go
¨teborg University. He has con-
ducted a monitoring and conservation project for the peregrine falcon
since 1972. Main topics are population dynamics, reproduction, and
effects of contaminants. He has also studied raptors and rodent cycles
in Swedish Arctic Lapland.
Address: Department of Biological and Environmental Sciences,
University of Gothenburg, Box 463, 405 30 Go
¨teborg, Sweden.
e-mail: peter.lindberg@bioenv.gu.se
Berth-Ove Lindstro
¨mis an independent researcher that has studied
the ecology of gyrfalcons in Norrbotten County in Sweden since 1998
through a long-term monitoring project.
Address: Boden, Sweden.
e-mail: berthove.lindstrom@gmail.com
William G. Mattox (MA, Ph.D.) in 1972 initiated the first long-term
peregrine monitoring in central West Greenland and led it for
26 years.
Address: Conservation Research Foundation, 702 S. Spelman Ln,
Meridian, ID, USA.
e-mail: wgmattox2@earthlink.net
Carol L. McIntyre is a wildlife biologist at Denali National Park and
Preserve, Alaska, USA. Among her main interests is the ecology of
northern breeding raptors and their prey.
Address: US National Park Service, Alaska, USA.
e-mail: carol_mcintyre@nps.gov
Svetlana Mechnikova has monitored the raptors in southern Yamal
peninsula since 1986, and defended a doctoral thesis ‘‘Raptors of the
Southern Yamal: breeding and population dynamic.’’ She is also
interested in the site fidelity of raptors, especially rough-legged
buzzard.
Address: I. M. Sechenov First Moscow State Medical University
(Sechenov University), 119991 Trubetskaya 8, Moscow, Russia.
e-mail: mechnikova@yandex.ru
Dave Mossop is a professor emeritus and research scientist at the
Yukon Research Center of Yukon College, in Whitehorse, Canada.
His prime research interest is in understanding tundra community,
focusing mostly on willow ptarmigan and waterbirds as key-stone
species; gyrfalcon and peregrine falcon, top predators.
Address: Yukon Research Centre, Whitehorse, Canada.
e-mail: dmossop@yukoncollege.yk.ca
Søren Møller is an associate professor at Roskilde University,
Denmark. Since 1981, together with Knud Falk, he has been leading
the peregrine falcon monitoring project in South Greenland.
Address: Roskilde University, P.O. Box 260, 4000 Roskilde, Den-
mark.
e-mail: moller@ruc.dk
https://www.vandrefalk.dk
ÓRoyal Swedish Academy of Sciences 2019
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O
´lafur K. Nielsen is a wildlife ecologist at the Icelandic Institute for
Natural History. He is responsible for the monitoring of the Icelandic
rock ptarmigan population. His main research interests relate to
population dynamics of the rock ptarmigan and the role of food-web
connections including herbivore–plant, predator–prey, and parasite–
host interactions.
Address: Icelandic Institute of Natural History, Garðabær, Iceland.
e-mail: okn@ni.is
Tuomo Ollila is senior advisor at the Metsa
¨hallitus, Parks and
Wildlife. He is responsible for the monitoring of gyrfalcon and
peregrine falcon in Finland.
Address: Metsa
¨hallitus, Parks and Wildlife Finland, Rovaniemi,
Finland.
e-mail: tuomo.ollila@metsa.fi
Arve Østlyngen is current leader of the Raptor Group Finnmark,
responsible for long-term census program of gyrfalcons in western
Finnmark. He is also employed in monitoring golden eagles, pere-
grines, and rough-legged buzzards in sub-arctic Finnmark.
Address: Raptor Group Finnmark, Alta, Norway.
e-mail: aoestly@online.no
Ivan Pokrovsky is a postdoc at the Max-Planck Institute for
Ornithology (Germany) and senior researcher at the Institute of
Biological Problems of the North (Russia). His research interests
include bird migration and ecology of the northern populations and
ecosystems.
Address: Department of Migration, Max Planck Institute of Animal
Behavior, Am Obstberg 1, 78315 Radolfzell, Germany.
Address: Laboratory of Ornithology, Institute of Biological Problems
of the North FEB RAS, 18 Portovaya Str., Magadan, Russia 685000.
Address: Arctic Research Station, Institute of Plant & Animal Ecol-
ogy, UD RAS, 21 Zelyonaya Gorka, Labytnangi, Russia 629400.
e-mail: ivanpok@mail.ru
Kim Poole is an independent researcher who has studied and sur-
veyed raptors, with an emphasis on gyrfalcons, across the Canadian
Arctic for over 30 years.
Address: Aurora Wildlife Research, Nelson, Canada.
e-mail: kpoole@aurorawildlife.com
Marco Restani is a former professor of wildlife ecology. He cur-
rently consults on a range of environmental issues affecting wildlife
in the US Rocky Mountain Region.
Address: St. Cloud State University, St. Cloud, USA.
e-mail: Restani@stcloudstate.edu
Bryce W. Robinson is the director of Ornithologi: a Studio for Bird
Study, which aims to integrate visual media with research to better
communicate topics in ornithology. His research interests range
broadly within the study of avian life histories.
Address: The Peregrine Fund, and Ornithologi, Boise, USA.
e-mail: bryce@ornithologi.com
Robert Rosenfield is a professor of biology at the University of
Wisconsin – Stevens Point. He has conducted population surveys and
ecological studies of breeding peregrine falcons in central west
Greenland with UWSP undergraduate students for over 30 years. He
has also investigated the population and behavioral ecology of nesting
Cooper’s hawks in Wisconsin, USA, for 39 years.
Address: University of Wisconsin – Stevens Point, Stevens Point,
USA.
e-mail: rrosenfi@uwsp.edu
Aleksandr Sokolov is a researcher at the Arctic Research Station of
Institute of Plant and Animal Ecology of Ural Branch of Russian
Academy of Sciences. He has studied terrestrial ecosystems, mainly
mammals and birds in Yamal Peninsula and the rest of Russian Arctic
since 1998.
Address: Arctic Research Station of Institute of Plant and Animal
Ecology Ural Branch, Russian Academy of Sciences, Zelenaya Gorka
Str., 21, Labytnangi, Yamal-Nenets Autonomous District, Russia
629400.
e-mail: sokhol@yandex.ru
Vasiliy Sokolov is a deputy director of the Institute of Plant and
Animal Ecology. His research interests focus on study of structure
and dynamic of Arctic bird species and their communities on Yamal
Peninsula, as well as the migration strategy of Arctic peregrines
breeding in northern Eurasia.
Address: Institute of Plant and Animal Ecology Ural Branch, Russian
Academy of Sciences, Ekaterinburg, Russia.
e-mail: vsokolov@inbox.ru
Ted Swem is a biologist with the Fish and Wildlife Service in
Fairbanks, Alaska, where he works in endangered species conserva-
tion and raptor population monitoring.
Address: U.S. Fish and Wildlife Service, Alaska, USA.
e-mail: ted_swem@fws.gov
Katrin Vorkamp is a senior scientist in environmental chemistry at
Aarhus University, Denmark. She works with Knud Falk and Søren
Møller on the contaminant exposure of the South Greenland peregrine
falcons.
Address: Department of Environmental Science, Aarhus University,
Roskilde, Denmark.
e-mail: kvo@envs.au.dk
123 ÓRoyal Swedish Academy of Sciences 2019
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... Falcons in this study area were reported in Franke et al. (2020), and the population was deemed stable in terms of nest site occupancy, but with a gentle decline over time in productivity. Via the same publication, most Peregrine Falcon populations were described as stable across the Arctic. ...
... Increased frequency and severity of precipitation are among the predicted changes to climate in many Arctic locations (Meredith et al. 2019), thus, incorporating weather variables into the MSFR, particularly into the linear models for attack rates would be another avenue of future study. Franke et al. (2020) presented Peregrine Falcon occupancy and productivity data from across the Arctic, with considerably heterogeneity noted across study areas. ...
Thesis
Full-text available
Species interactions are thought to underlie the stability of ecosystems, and nowhere is studying such interactions more important than the rapidly changing Arctic. The foraging behaviour of generalist consumers is influenced by the abundance of multiple resources, and generalists are thought to confer stability to resource populations. Surprisingly, explicit treatment of the diverse prey communities that many predators encounter in nature has been relatively rare, with most studies confined to predator-prey pairs. My thesis investigates the relationships between predator and multiple prey in an Arctic ecosystem on the western coast of Hudson Bay from 2015-17, using Peregrine Falcons (Falco peregrinus) as a model species. First, I set out to quantify prey abundance on the landscape using distance sampling for avian species and Arctic ground squirrels (Urocitellus parryii), and a combination of burrow counts and snap trapping for microtine rodents (lemmings and voles). Results of snap trapping indicated 2015 was a year of low microtine abundance, while abundance was highest in 2016 and slightly less high in 2017. Burrow counts and distance sampling data were analyzed using density surface modelling according to six habitat covariates, and results indicated that freshwater, productive vegetation, and low elevation were the most consistent predictors of avian abundance across species and groups. Terrain ruggedness positively influenced abundance for Arctic ground squirrels and microtine rodents, while Arctic ground squirrels specifically were more abundant at low elevation, in areas with little freshwater, and in areas with productive vegetation. Conversely, microtine burrow counts were higher in areas with freshwater that were far from the coast. Second, I analyzed the abundance of the most common prey types for Peregrine Falcons in relation to distance from falcon nests to evaluate evidence for a “landscape of fear” that structured prey distribution. I found songbird and goose abundance to be positively related to distance from falcon nests, and in the case of songbirds, this relationship was present even during falcon incubation, when prey consumption is relatively low. This I argue, likely indicated avoidance of breeding Peregrine Falcons when songbirds arrived in the study area and established territories. Goose abundance was only lower near falcon nests in late summer, when vulnerable goslings entered the population. Unexpectedly, duck abundance was negatively influenced by distance from falcon nests in late summer, which I argue was likely due to similar nesting habitat selection between Peregrine Falcons and Common Eiders (Somateria mollissima), which were the dominant duck species detected in surveys. Finally, I used distribution maps constructed using the aforementioned density surface models to fit a complex multispecies functional response model utilizing nearly 11,000 prey deliveries recorded by remote cameras placed at Peregrine Falcon nests. Considering uncertainty in prey identification, camera failures, and prey abundance estimates, the resulting model demonstrated negative impacts of microtine rodent (lemming and vole) abundance and food supplementation (from a concurrent experiment) on the consumption of other prey. This indicated a potential short-term mutualism between prey types as falcon diet shifted with the microtine rodent cycle, adding to a large body of literature demonstrating the indirect effects of microtine rodents on other Arctic fauna. Model predictions indicated a wide range of biomass consumption across nests. Predictions with a random effect of nest site-year combination differed substantially from those without, indicating potentially strong individual differences in foraging between breeding pairs in this population. Predicted biomass consumption was most strongly related to the abundance of small birds (songbirds and shorebirds), indicating Peregrine Falcon nestlings may face an energy shortage at nests with low local small bird abundance. Surprisingly, biomass consumption by nestlings was generally unrelated to experimental food supplementation, providing context for a previous study demonstrating higher nestling survival at supplemented nests. Overall, my thesis provides insight into how Peregrine Falcons, as apex predators of the Arctic, provision their offspring and mediate indirect interactions among prey, and is a rare investigation of predator functional responses in a multi-prey context.
... Many peregrine falcon populations (especially in Alaska, parts of Canada and northern Fennoscandia) have now largely recovered from dramatic reductions due to pesticide contamination during the 1970s (Franke 2020;this volume). Overall, Arctic peregrine populations now appear stable, with reports of a northward expansion among peregrines in Northwest Greenland (Burnham et al. 2012), as well as an advancing timing of breeding in several Arctic regions (Franke 2020), likely as a consequence of climate change. ...
... Many peregrine falcon populations (especially in Alaska, parts of Canada and northern Fennoscandia) have now largely recovered from dramatic reductions due to pesticide contamination during the 1970s (Franke 2020;this volume). Overall, Arctic peregrine populations now appear stable, with reports of a northward expansion among peregrines in Northwest Greenland (Burnham et al. 2012), as well as an advancing timing of breeding in several Arctic regions (Franke 2020), likely as a consequence of climate change. Gyrfalcon populations are also stable, although poaching is an increasing concern in some areas (Potapov 2011), and shrubification and a shrinking High Arctic climate zone may pose challenges in the future, mediated through impacts on their primary prey, ptarmigan (Booms et al. 2011). ...
... In this issue, circumpolar terrestrial bird FEC-attribute trends and monitoring coverage are discussed in three papers: Fuglei et al. (2020) focused on the Arctic-resident herbivores, rock ptarmigans (Lagopus muta), and willow ptarmigans (Lagopus lagopus); Franke et al. (2020) focused on top predators, the Arctic-resident gyrfalcon (Falco rusticolus), and the migrant peregrine falcon (Falco peregrinus); and Smith et al. (2020) reviewed the status of all main terrestrial bird populations (88 species included) according to functional groups (herbivore, insectivore, etc.), and 'flyways' (main migration routes) utilized by different populations. ...
... For the top avian predators, Franke et al. (2020) provided the first overview of monitoring sites for gyrfalcons and peregrine falcons. The authors analyzed long-term trends in occupancy and productivity and summarized information for recommended CBMP FEC attributes. ...
Article
This review provides a synopsis of the main findings of individual papers in the special issue Terrestrial Biodiversity in a Rapidly Changing Arctic. The special issue was developed to inform the State of the Arctic Terrestrial Biodiversity Report developed by the Circumpolar Biodiversity Monitoring Program (CBMP) of the Conservation of Arctic Flora and Fauna (CAFF), Arctic Council working group. Salient points about the status and trends of Arctic biodiversity and biodiversity monitoring are organized by taxonomic groups: (1) vegetation, (2) invertebrates, (3) mammals, and (4) birds. This is followed by a discussion about commonalities across the collection of papers, for example, that heterogeneity was a predominant pattern of change particularly when assessing global trends for Arctic terrestrial biodiversity. Finally, the need for a comprehensive, integrated, ecosystem-based monitoring program, coupled with targeted research projects deciphering causal patterns, is discussed.
... Adult and juvenile survival rates of gyrfalcons (Falco rusticolus) are currently unknown, despite an otherwise good knowledge of abundance and reproduction trends at the circumpolar scale (Franke et al., 2020), gene flow (Johnson et al., 2007;Booms et al., 2011), and diet as well as functional and numerical responses to changing prey density (Nielsen, 1999(Nielsen, , 2011. Indeed, this species population status is quantified with the number of territorial pairs and reproduction status (Franke et al., 2020, and refs. ...
Article
Full-text available
Knowledge of survival rates and their potential covariation with environmental drivers, for both adults and juveniles, is paramount to forecast the population dynamics of long-lived animals. Long-lived bird and mammal populations are indeed very sensitive to change in survival rates, especially that of adults. Here we report the first survival estimates for the Icelandic gyrfalcon ( Falco rusticolus ) obtained by capture-mark-recapture methods. We use a mark-recapture-recovery model combining live and dead encounters into a unified analysis, in a Bayesian framework. Annual survival was estimated at 0.83 for adults and 0.40 for juveniles. Positive effects of main prey density on juvenile survival (5% increase in survival from min to max density) were possible though not likely. Weather effects on juvenile survival were even less likely. The variability in observed lifespan suggests that adult birds could suffer from human-induced alteration of survival rates.
... For the climate data, the monthly temperature of the Community Climate System Model (version 4) output was downloaded from Coupled Model Intercomparison Project 5. The yearly mean temperature was calculated as the average of monthly temperature in the breeding season (May to July), a period that is vital to the breeding success of peregrines 79,80 . To quantify historical weather extremes, we downloaded the gridded daily minimum and maximum temperature data from Berkeley Earth Surface Temperature. ...
Article
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... However, the recent climate change extended the annual breeding window favouring the expansion of the peregrine falcons also in northern areas occupied by gyrfalcons (Burnham et al. 2019). However at broader scales, peregrine falcon and gyrfalcon populations are generally stable (Franke et al. 2020). ...
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