# Shared population trends but no annual synchrony in duck species across Europe and North America

David J Messmer, Matthieu Guillemain, Mark C Drever, Tom Langendoen, Robert G Clark

► To cite this version:

David J Messmer, Matthieu Guillemain, Mark C Drever, Tom Langendoen, Robert G Clark. Shared population trends but no annual synchrony in duck species across Europe and North America. European Journal of Wildlife Research, 2025, 71 (2), pp.22. 10.1007/s10344-025-01895-7. hal-04964492

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<figure><img src="image_1.png" /></figure>

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# Shared population trends but no annual synchrony in duck species across Europe and North America

David J. Messmer<fnref n="1" />,<fnref n="4" />,<fnref n="6" /> ID · Matthieu Guillemain<fnref n="2" /> · Mark C. Drever<fnref n="3" /> · Tom Langendoen<fnref n="5" /> · Robert G. Clark<fnref n="1" />,<fnref n="4" />

Received: 6 September 2024 / Revised: 2 January 2025 / Accepted: 15 January 2025

© Crown 2025

## Abstract

Few studies have explored population dynamics of species sharing life-history traits and common environmental drivers but living in widely separated regions or continents. Large-scale climate cycles can impact habitats and populations over broad geographic areas and may act as global forces shaping animal population dynamics. We tested for synchronous population dynamics of eight ecologically equivalent duck species in Western Europe (WEU) and central North America (NA) from 1976 to 2019. We investigated the extent to which the Atlantic Multi-Decadal Oscillation (AMO) may have induced shared climatic conditions on the breeding areas of these populations and whether the index was correlated with duck population dynamics. Evidence of annual and long-term population synchrony was assessed by estimating correlation in annual growth rates and population abundances, respectively. Shared (increasing) long-term trends in WEU and NA were found in four species-pairs, but no species-pair had synchronous population growth on an annual basis. Three species-pairs sharing trends were positively correlated with the AMO index which increased during the study period. Positive cycling of the AMO was correlated with increased temperature and precipitation in breeding areas of both continents, which may have produced favorable conditions (earlier springs, more ponds) for some duck populations. Differences in the local effects of weather on environmental conditions and other continent-specific extrinsic factors may mask annual synchrony in the response of continental populations to climate. Potential links between the AMO trends and extrinsic factors such as shared changes in anthropogenic drivers (e.g., climate and land use change) should be addressed in future studies.

**Keywords** Anatidae · Atlantic multi-decadal oscillation · Climate variability · Population dynamics · Population synchrony

## Introduction

Large-scale environmental variation can impact population processes of geographically separated organisms that share life-history traits, giving rise to synchrony in population

dynamics. In some taxa, variation in survival and reproductive rates have been linked to fluctuations in large-scale climatic and oceanographic conditions, and changes in land use (Stenseth et al. 2002; Stenseth et al. 2003; Scharlemann et al. 2004; Zhao et al. 2019; Michel et al. 2021). These mechanisms have been documented to synchronize populations, via the Moran effect (reviewed by Liebhold et al. 2004), or by shared trophic mechanisms such as bottom-up timing of resource pulses or top-down predation pressures (Nudds 1992; Koons et al. 2014). In birds, population synchrony has been documented at biome and continental scales (Liebhold et al. 2004; Michel et al. 2016), however, mechanisms for shared dynamics have not been well characterized. Likewise, studies of synchrony between continents are rare. Investigations that address mechanistic hypotheses for cross-continental synchrony could provide deeper insights into global forces affecting animal populations (Ranta et al. 1997).

Populations of ecologically equivalent species may be expected to react similarly across continents to the extent that large-scale climatic variation similarly shapes their habitats,

<figure><img src="image_2.png" /></figure>

<footnote>David J. Messmer
dmessmer@gmail.com</footnote>

<footnote n="1">¹ Department of Biology, University of Saskatchewan,
Saskatoon, Saskatchewan, Canada</footnote>

<footnote n="2">² Service Conservation et Gestion Durable des Espèces
Exploitées, Office Français de la Biodiversité, Arles, France</footnote>

<footnote n="3">³ Environment & Climate Change Canada, Delta,
British Columbia, Canada</footnote>

<footnote n="4">⁴ Environment & Climate Change Canada, Saskatoon,
Saskatchewan, Canada</footnote>

<footnote n="5">⁵ Wetlands International, Ede, The Netherlands</footnote>

<footnote n="6">⁶ Present Address: Montana Fish, Wildlife and Parks, 1420
East 6th Avenue, Helena, MT 59620, USA</footnote>
trophic interactions, or energy requirements. Population synchrony may be evident as a shared trend or population cycle, or as covariation of annual growth rates. Covariation in annual growth rates is not a pre-condition for shared long-term trends, but they may nonetheless be driven by common underlying factors. For instance, two continents could have similar environmental changes over decades (e.g., warming climate) but fluctuations in the environment may not be temporally coincident each year. The effects could be buffered differently on each continent by natural or human-mediated factors such as local weather, lags in habitat or predator community responses, or agricultural and water protection policies (Eglington and Pearce-Higgins 2012).

The Atlantic Multi-Decadal Oscillation (AMO) is a climate cycle known to affect marine and terrestrial ecosystems at broad scales in Europe and North America (Nye et al. 2014). The AMO effects on terrestrial vertebrate populations have only recently begun to be explored (Nye et al. 2014; Boyd and Fox 2013; Hinsley et al. 2016; Michel et al. 2021). Over the past decade our understanding of large-scale climate patterns linked to the AMO have improved, and the AMO is now recognized as a leading indicator of climate variability in many regions (Nye et al. 2014). Increases in North Atlantic Sea surface temperature across the northern hemisphere produce positive phases of the AMO, with concomitant warming of terrestrial temperatures, earlier onset of spring-like conditions and, at least in Europe, greater summer precipitation (Sutton and Hodson 2005; Knight et al. 2006; Nigam et al. 2011). Warmer and wetter conditions may benefit survival and reproduction of ducks by improving habitat conditions (Dzus and Clark 1998; Krapu et al. 2000). Thus, we anticipated that the increasing phase of the AMO could have immediate positive impacts on ducks evident in annual growth rates, or through more gradual mechanisms that shape habitats and thereby longer-term trends of populations. For example, increases in wetland area or abundance, beneficial to ducks, may lag behind increases in precipitation as water storage in wetland basins or near-surface water tables gradually build up over several years (Ballard et al. 2014; LaBaugh et al. 2018).

Here, we test for evidence of synchrony in annual population growth rates and long-term trends of ecologically or taxonomically equivalent species-pairs of dabbling and diving ducks from Western Europe (WEU) and central North America (NA) (Table 1). We investigate the extent to which the Atlantic Multi-Decadal Oscillation (AMO) may have induced shared climatic conditions on the breeding areas of both continents and, if synchrony in populations is found, we evaluate whether the AMO could be acting as a synchronizing environmental factor for these populations of ducks. We also characterized temporal relationships between the AMO and continent-specific temperature and precipitation patterns because putative linkages between oceanographic and terrestrial climatic conditions have not been adequately quantified.

# Materials and methods

## Duck population surveys

We used 44 years of duck population counts from WEU and NA, 1976–2019. Ranges of duck species span large areas of each continent, with several species having a Holartic distribution over WEU and NA, although ringing and genetic data suggest very limited exchange of individuals between WEU and NA (e.g., Guillemain and Elmberg 2014, for common teal *Anas crecca*). Counts from WEU represent minimum population estimates and are conducted during mid-winter and are standardized and coordinated in WEU countries encompassing much of the core wintering range of focal species, in an area often termed the North-West European flyway. Survey methods are provided by Delany (2005) and data were compiled by Wetlands International (see synthesis at iwc.wetlands.org). Briefly, volunteer ornithologist observers (including professionals and amateurs) counted ducks by species from the ground in a coordinated manner during the week of 15 January each year over thousands of sites. Counts were conducted over a relatively short period to reduce potential for double-counting. During very severe winters, it is possible that some species migrate outside of the survey region in search of suitable foods (e.g. Spain; [Dalby et al. 2013; Ogilvie 1983; Ridgill and Fox 1990]); however, we use state-space models in our investigation (described below) which accommodate these short-term anomalous movements as observation errors (relative to the true unobserved population dynamics). Concerns over some species wintering progressively farther north in WEU because of warming winter conditions have been raised, but such shifts have occurred largely within the survey region so far (Dalby et al. 2013; Lehikoinen et al. 2013) and should not affect our investigation.

Population estimates of breeding ducks in mid-continent NA were obtained from surveys conducted by the United States Fish and Wildlife Service and the Canadian Wildlife Service (https://www.fws.gov/birds/surveys-and-data/migratory-bird-data-center.php), following standard operating procedures which are documented by Smith (1995). The survey area covers the primary duck breeding habitats in central North America and any changes in distributions of breeding ducks during the study period have occurred primarily within the survey area. Briefly, aerial surveys were flown annually over the same transects starting in the U.S. prairies, then traversing the Canadian prairies and parklands and extending northward across the western boreal forest in Canada and Alaska. All ducks were assigned to species and social grouping (pairs, singles, groups, flocks) which are used to estimate the number of breeding pairs present. The sum of breeding pairs over all transects in the study
<table><caption>**Table 1** Characteristics of duck species representing eight pairs of ecological analogues in Western Europe and North America</caption><thead><tr><th>Species-analogue</th><th>Species</th><th>Continent</th><th>Life-History</th><th>Foraging</th><th>Diet</th><th>Migration</th></tr></thead><tbody><tr><td>1</td><td>Northern pintail (<em>Anas acuta</em>)</td><td>Europe</td><td>Intermediate</td><td>Dabbler</td><td>Seeds</td><td>Long</td></tr><tr><td>1</td><td>Northern pintail</td><td>North America</td><td>Intermediate</td><td>Dabbler</td><td>Seeds</td><td>Long</td></tr><tr><td>2</td><td>Common teal (<em>Anas crecca</em>)</td><td>Europe</td><td>Fast</td><td>Dabbler</td><td>Seeds</td><td>Long</td></tr><tr><td>2</td><td>American green-winged teal (<em>Anas carolinensis</em>)</td><td>North America</td><td>Fast</td><td>Dabbler</td><td>Seeds</td><td>Long</td></tr><tr><td>3</td><td>Northern shoveler (<em>Spatula clypeata</em>)</td><td>Europe</td><td>Fast</td><td>Dabbler</td><td>Invertebrates</td><td>Short</td></tr><tr><td>3</td><td>Northern shoveler</td><td>North America</td><td>Fast</td><td>Dabbler</td><td>Invertebrates</td><td>Short</td></tr><tr><td>4</td><td>Gadwall (<em>Mareca strepera</em>)</td><td>Europe</td><td>Intermediate</td><td>Dabbler</td><td>Herbivore</td><td>Short</td></tr><tr><td>4</td><td>Gadwall</td><td>North America</td><td>Intermediate</td><td>Dabbler</td><td>Herbivore</td><td>Short</td></tr><tr><td>5</td><td>Eurasian wigeon (<em>Mareca penelope</em>)</td><td>Europe</td><td>Intermediate</td><td>Dabbler</td><td>Herbivore</td><td>Long</td></tr><tr><td>5</td><td>American wigeon (<em>Mareca americana</em>)</td><td>North America</td><td>Intermediate</td><td>Dabbler</td><td>Herbivore</td><td>Short</td></tr><tr><td>6</td><td>Tufted duck (<em>Aythya fuligula</em>)</td><td>Europe</td><td>Intermediate</td><td>Diver</td><td>Mixed</td><td>Short</td></tr><tr><td>6</td><td>Ring-necked duck (<em>Aythya collaris</em>)</td><td>North America</td><td>Intermediate</td><td>Diver</td><td>Mixed</td><td>Short</td></tr><tr><td>7</td><td>Common pochard (<em>Aythya ferina</em>)</td><td>Europe</td><td>Intermediate</td><td>Diver</td><td>Herbivore</td><td>Short</td></tr><tr><td>7</td><td>Redhead (<em>Aythya americana</em>)</td><td>North America</td><td>Intermediate</td><td>Diver</td><td>Herbivore</td><td>Short</td></tr><tr><td>8</td><td>Greater Scaup (<em>Aythya marila</em>)</td><td>Europe</td><td>Slow</td><td>Diver</td><td>Invertebrates</td><td>Long</td></tr><tr><td>8</td><td>Greater scaup</td><td>North America</td><td>Slow</td><td>Diver</td><td>Invertebrates</td><td>Long</td></tr></tbody></table>

Species are characterized by relative life-history pace (slow, intermediate, fast). Also shown are dominant foraging mode and diet, and migration distance between breeding and wintering areas. All life-history information was summarized from Baldassarre (2014) and Kear (2005)

area, corrected for visibility, is the population estimate. In the prairie-parkland region of the U.S. and Canada, visibility corrections rates are derived from ground counts of ducks made by revisiting sub-sets of wetlands along aerial survey transects. A constant visibility correction factor was applied to counts of ducks in the boreal forest and farther north (Smith 1995). Observers do not differentiate greater scaup (*Aythya marila*) from lesser scaup (*Aytha affinis*) on the survey; however, field studies indicate that lesser scaup are rare on the tundra where most greater scaup breed, therefore we used only survey strata in tundra regions to estimate greater scaup populations.

These two data sets represent the best available information on the dynamics of geographically extensive duck populations on each continent. Although the surveys rely on different field protocols and are carried out during different seasons, data were comparable in being recorded in the same sampling regions during a relatively short time interval each year (mid-January in WEU, May in NA) after most hunting has occurred (hunting seasons were generally closed in most WEU countries by the end of January) and

prior to the main influx of juvenile birds that occurs during the breeding season. Eight species-pairs were analyzed (Table 1), representing populations of the same, or ecologically equivalent (sharing same general ecologies and life-histories) species on opposite sides of the Atlantic. We excluded mallard (*Anas platyrhynchos*) populations because massive releases of pen-raised mallards in WEU could confound the winter counts of wild birds (Champagnon et al. 2013).

## Summarizing the AMO to evaluate synchrony

We obtained monthly indices of the Atlantic Multi-decadal Oscillation (AMO) from the NOAA web site (https://www.esrl.noaa.gov/psd/data/timeseries/AMO/) for the period 1976–2019. If we detected synchrony in a species-pair’s annual growth rates (discussed below), we summarized the AMO index as either the mean of the twelve monthly values (AMO<sub>annual</sub>) prior to surveys on each continent, or as the mean of the six-month summer period (April to September; AMO<sub>A-S</sub>) before surveys. In cases of absent annual
synchrony, but presence of shared long-term trends, we averaged monthly AMO values from June to May for both continents. This allowed us to evaluate the explanatory power of AMO for long-term trends of species-pairs in the same model and is commensurate with mechanisms producing a gradual change in habitat conditions.

## Relationship between AMO and climatic variables

While the effects of the AMO on weather patterns in Europe are reasonably well-characterized, there is little direct information on the relationship within the NA breeding area. To determine whether the AMO leads to similar climatic conditions on both continents, we extracted temperature and precipitation data over continental breeding areas from the Climate Research Unit v4.02 time series (CRU TS v4.02; [Harris et al. 2014]). These data are gridded (0.5 × 0.5°) monthly summaries based on interpolation between global land-based meteorological stations. Because we were not directly incorporating these continent-specific data into our duck population modeling, we used a slightly longer time series (1971–2019) to evaluate the relationships. We delineated areas of core breeding habitat and summarized climate on each continent. For NA this was simply the area covered by the May breeding duck survey (described above). For WEU we used the cumulative area identified as core breeding range for ducks in our analysis from Scott and Rose (1996), and truncated this breeding area to the East following Guillemain et al. (2017) to more accurately reflect the likely geographic origin of ducks wintering in WEU.

We summarized the monthly values in these study areas into 3 annual periods: i) pre-breeding (January–May for precipitation and April–May for temperature); ii) breeding (June–August); and iii) annual (January–December). The longer pre-breeding period for precipitation represents the effect of accumulated snowpack and spring precipitation on spring wetland conditions, while the shorter breeding period for temperature reflects the relative timing of spring. To assess annual synchrony in weather we calculated correlation of detrended weather variables. We detrended each time series by taking the residuals of a simple linear regression of response-by-year. To evaluate shared long-term trend, we regressed each weather variable by year and tested whether slopes differed between continents with a ‘continent × year’ interaction term.

## Population and observation models

Population estimates for ducks on both continents are subject to observation errors. The magnitude of these errors is a function of sampling variability, imperfect detection, and an inability to optimally time surveys for each species in each

year (Kéry and Schaub 2012). For example, timing of migration or nesting phenology vary by species and these could influence “availability” along survey routes. To accommodate this observation error, we used a state-space modeling (SSM) framework that, by incorporating an explicit model for observation error, can reduce observation error impacts on parameter estimation and inference made in the population model (Clark and Bjørnstad 2004; Dennis et al. 2006).

WEU and NA surveys follow a standardized protocol from year-to-year and were conducted by trained personnel, so we assumed that observation errors (i.e., over- or under-counting, sampling variance) are random from year-to-year, and can be approximated by a log-normal probability distribution (Lebreton 2009). Log-normal observation errors imply that observation errors are proportional to population size on the real scale. We allowed differing and uncorrelated observation error ($\sigma_{obs}^2$) for counts ($y_{i,t}$) for each continent $i$ and year $t$, using the multivariate normal (MVN) distribution.

$$ \ln(y_{i,t}) \sim \text{MVN}\left(0, \begin{bmatrix} \sigma_{\text{obs EU}}^2 & 0 \\ 0 & \sigma_{\text{obs NA}}^2 \end{bmatrix}\right) \quad (1) $$

Connected to this observation model, we specified a discrete Gompertz population model to represent the dynamics of duck populations. This model has been applied to ducks (Sæther et al. 2008; Lebreton 2009; Ross et al. 2015) and more generally to vertebrate populations with synchronous annual birth pulses and growth rates subject to environmental stochasticity and density dependence (Royama 1992; Lande et al. 2003). The Gompertz model implies a concave density dependence between the previous year’s population size and the current year’s population growth. Using the natural log (ln) of population size ($N_{i,t}$) $t$, the model takes the linear form:

$$ \ln(N_{i,t}) = x_{i,t} = \theta_i \times x_{i,t-1} + r_i + \varepsilon_{i,t} \quad (2) $$

where $\theta_i$ is the density dependence coefficient, $r_i$ is the population growth rate from low populations (i.e., mathematically, from $N=1$), and $\varepsilon_{i,t}$ is the unexplained variation in growth rate caused by environmental stochasticity. We assume $\varepsilon_{i,t}$ is multivariate log-normally distributed (MVN), where $\rho$ is the correlation of fluctuations in the population growth rate between the WEU and NA populations:

$$ \varepsilon_{i,t} \sim \text{MVN}\left(0, \begin{bmatrix} \sigma_{\text{EU}}^2 & \rho \\ \rho & \sigma_{\text{NA}}^2 \end{bmatrix}\right) \quad (3) $$

The estimate of $\rho$ for each cross-continental species-pair is a measure of linear correlation between population fluctuations (i.e., annual synchrony). If we detected synchronous annual growth rates (95% credible intervals for $\rho$ did not overlap 0), we then evaluated whether fluctuations in the
AMO could explain them by extending eq. 2. with an addi-
tive term to estimate effects of the AMO covariates.

Regardless of whether annual synchrony was detected,
we also tested for shared long-term trends by estimating the
correlation between the population abundance estimates of
species-pairs. We did this via *post-hoc* analysis of the poste-
rior distribution samples for population abundances in each
species-year from the SSM population model in eq. 2. It is
possible that climate fluctuations do not detectably influence
annual duck dynamics, but that populations are nevertheless
influenced by gradual changes in habitat conditions (sensu
Hefley et al. 2016) produced by long-term climate trends
associated with the AMO index. To test this, we again used
*post-hoc* analysis of the SSM posterior distribution samples
for continental population estimates. We rescaled these time
series to mean=0 and SD=1 and pooled these data for each
species-pair. We regressed the population estimates against the
AMO index with an interaction term to test for a difference in
the association with the AMO for each continental population.

Bayesian model fitting

We estimated parameters of the above SSMs in a Bayesian
framework with Markov chain Monte Carlo (MCMC) simu-
lations in JAGS (Plummer 2003) using the jagsUI package in
R (Kellner 2015; R Core Team 2017). Parameter estimates
for environmental covariates and environmental stochastic-
ity are believed to be robust using these methods despite
potential difficulties in estimating intrinsic growth rate and
density dependence (coefficients *r* and *θ* from eq. 2; [Roy
et al. 2016]). We only report estimates for parameters regard-
ing our main hypotheses.

All model parameters were given uninformative priors
relative to the plausible biological values of the parameters:
θ and *r* were specified as *Normal*(0, σ=4), standard devia-
tions for process and observation error were specified as *Uni-
form*(0,3), ρ *Uniform*(-1, 1), and initial population sizes were
*x*₁,ᵢ~*LogNormal*(y₁,ᵢ, σ=1). We ran 3 chains for 100,000 itera-
tions with a burn-in of 10,000 and thinning interval of 5. We
monitored convergence with the criterion that parameters of
interest would have Brooks-Gelman-Rubin statistic, *r̂* < 1.05
(Brooks and Gelman 1998), and by visual confirmation of
well-mixed chains (Kéry 2010). Model adequacy was evalu-
ated by calculating a Bayesian *p* value for the sum of residuals
of observed and simulated “ideal” datasets with values near
0.5 considered adequate (Gelman et al. 1996).

Data deposition

North American survey data can be freely downloaded from
the U.S. Fish and Wildlife Service web site: https://www.
fws.gov/birds/surveys-and-data/migratory-bird-data-center.

php. European data may be obtained by contacting Wetlands
International (https://iwc.wetlands.org). Climate data are
freely available from the University of East Anglia website:
https:// crudata.uea.ac.uk/cru/data/hrg/. AMO indices are
available from the NOAA website: https://www.esrl.noaa.
gov/psd/data/timeseries/AMO/.

Results

Shared weather patterns associated with the AMO

Regardless of the months summarized, the AMO fluctuated
annually and increased from the beginning to the end of the
study period, indicating a gradual increase in North Atlantic
Sea surface temperatures during the study period (Fig. 1).
There was also a clear upward trend in temperatures in core
breeding areas during each of the annual, pre-breeding, and
breeding periods, except during the pre-breeding months in
NA (April to May; Fig. 2). Annual fluctuations in detrended
temperature were positively correlated between continents
during the breeding season months (Fig. 2) and detrended
temperature was positively correlated with AMO<sub>annual</sub> during
the breeding season on both continents (r<sub>NA</sub>=0.30, p=0.05;
r<sub>WEU</sub>=0.31, p=0.03) and annually in NA (r<sub>NA</sub>=0.40,
p<0.01).

WEU trends for precipitation were positive during all periods and over nearly all regions of the study area (Fig. 3b). In NA there was little evidence of linear trend except a slight increase in summer precipitation (β̂<sub>summer</sub> =0.32, 95% CI: −0.12, 0.60). However, unlike WEU, there appeared to be contrasting regional trends with much of the prairie region having positive increases in precipitation (Fig. 3a). This is corroborated by pond counts recorded in the prairie region of the NA duck survey which have

<figure><img src="image_3.png" /><figcaption>**Fig. 1** Time series of annual mean Atlantic Multidecadal Oscillation index during our study period (bold lines 1976–2019) and a longer period 1950–2019 for context</figcaption></figure>
<figure><img src="image_4.png" /><figcaption>**Fig. 2** Long-term trends in temperature and precipitation during pre-breeding, breeding, and full-year on each continent (top panels), and annual correlation of temperature and precipitation between continents. Long-term trend panels (top row) show slopes and 95% confidence intervals (CI) for the linear regression model evaluating annual trend in temperature and precipitation from the CRU TS v4.02 dataset, 1971–2019. Slope for precipitation is the estimated change in the sum of precipitation (mm) per year and temperature is °C per year. Annual correlation panels (bottom row) show Pearson correlation and 95% CI between continental study areas for annual estimates of detrended temperature and precipitation data from CRU TS v4.02 dataset, 1971–2019</figcaption></figure>

documented increased wetness during the study period (U.S. Department of Interior 2018). Detrended precipitation was negatively correlated across continents during the pre-breeding months (January to May) and over the full calendar year, but there was no correlation during the breeding season. Annual fluctuations in the detrended precipitation were

positively correlated with detrended AMO<sub>annual</sub> in WEU only ($r=0.39, p=0.01$).

## Duck population synchrony

Duck population estimates derived from the SSM framework resulted in a mechanistic smoothing of the time series (Bolker 2008) when compared with naïve counts of ducks (Figs. 4 and 5). Still, there was substantial annual variability and a general trend for greater estimates towards the end of the time series in several species of ducks in WEU and NA. We found no correlations in annual population growth rates, indicating a lack of annual synchrony for species-pairs from WEU and NA (Fig. 6A). Correlations ranged from -0.13 (95% CRI: -0.63, 0.44) in scaup-greater scaup comparison to 0.33 (95% CRI: -0.48, 0.94) in the gadwall-gadwall comparison.

Looking next to shared long-term trends, we found positive correlations among SSM estimated population sizes for teal, gadwall, shoveler and ring-necked duck-tufted duck species-pairs and a negative correlation between the redhead-pochard pair (Fig. 6B). We detected no correlation among species pairs for northern pintail, wigeon, and scaup. Results obtained below with the covariate AMO<sub>A-S</sub> were qualitatively similar to AMO<sub>annual</sub> and were not considered further.

Of the 5 species-pairs with correlated population estimates, each became progressively larger during the extended positive (warmer) phase of the AMO, except pochard which decreased. The slope of the AMO-population estimate relationships were statistically

<figure><img src="image_5.png" /><figcaption>**Fig. 3** Spatial heterogeneity in the trend of total annual precipitation from the CRU TS v4.02 in the North American (A) and Western European (B) breeding areas, 1971–2019. Slope for precipitation is the estimated change in the sum of precipitation (mm) per year</figcaption></figure>

<figure><img src="image_6.png" /></figure>
<figure><img src="image_7.png" /><figcaption>**Fig. 4** Unadjusted annual population estimates (closed black circles; in thousands) of dabbling duck populations in Western Europe (WEU) and mid-continent North America (NA), 1976–2019, and state-space model population estimates (solid blue line) with 95%</figcaption></figure>

indistinguishable between continents for gadwall, shoveler, and teal species-pairs (95% confidence intervals for interaction terms broadly overlapped 0), however pochard and tufted duck were not related to AMO<sub>annual</sub>, whereas their

credible intervals (shaded). Species-pairs are composed of ecologically equivalent species on each continent (Table 1). Note the y-axis scales differ between species-pairs, and WEU and NA

congeners redhead and ring-necked duck were ($\hat{\beta}_{interaction}$ = 3.9 [95% CRI: 1.82, 5.93] and 2.83 [95% CRI: 0.85, 4.81], respectively; Fig. 7).
<figure><img src="image_8.png" /><figcaption>**Fig. 5** Unadjusted annual population estimates (closed black circles; in thousands) of diving duck populations in Western Europe (WEU) and mid-continent North America (NA), 1976–2019, and state-space model population estimates (solid blue line) with 95% credible intervals (shaded). Species-pairs are composed of ecologically equivalent species on each continent (Table 1). Note the y-axis scales differ between species-pairs, and WEU and NA</figcaption></figure>

## Discussion

Populations of ecologically similar duck species in Western Europe and North America fluctuated independently from year to year, with no indication that annual population growth rates were correlated for any species-pair. We speculate that annual environmental conditions or other factors must be sufficiently different to prevent year-by-year synchronization between continents. For instance, while breeding areas in both continents appear to have become warmer, and possibly wetter (see below), during the study period these long-term changes were not necessarily synchronized on an annual basis. Rather,

there were negative correlations between continents in annual and pre-breeding season precipitation and possibly annual temperature, despite shared long-term trajectories. Alternatively, we may have lacked power to detect annual synchrony because of nuisance variation caused by different timing of surveys on each continent (WEU survey in mid-January, NA survey in May), although the February–April period that separates the surveys is generally believed to be a time of low mortality (e.g., hunting seasons are closed on both continents) and hence small population change (Dugger et al. 1994).

Although annual cross-continental synchrony was not detected, several species-pairs shared increasing trends in

<figure><img src="image_9.png" /></figure>
<figure><img src="image_10.png" /><figcaption>**Fig. 6** Estimates of synchrony in A) annual duck population growth rates and B) long-term trends for eight species-analogues from Western Europe and North America. Estimates and 95% credible intervals are A) the correlation of growth rates or B) the correlation of population abundances of species-pairs estimated in Gompertz population models. REDH-POCH refers to Redhead/Pochard, and RNDU-TUDU refers to Ring-necked Duck/Tufted Duck species pairs</figcaption></figure>

population size during the study period. The increasing AMO phase observed over the same period was correlated with the increasing trends of species-pair's abundances and with increasing temperatures on both continents and increasing precipitation across most of the WEU study area and the prairie region of NA. These results corroborate other research associating the AMO with warmer and wetter conditions, albeit occurring over different time frames and geographies (Sutton and Hodson 2005; Knight et al. 2006; Nigam et al. 2011). They also lend further support to other research demonstrating links between the AMO and animal population dynamics (Nye et al. 2014; Boyd and Fox 2013; Hinsley et al. 2016; Michel et al. 2021). While spurious correlations in time series sharing trends are clearly possible, we discuss mechanisms below whereby AMO-induced climatic trends could gradually influence duck habitats and populations on both continents.

Because annual growth rates did not directly follow anomalies of the AMO, the hypothesized effects would have to occur gradually, impacting habitats, rather than immediately, by impacting duck survival and reproduction. Hefley et al. (2016) demonstrated that gradual changes in key resources can cause major changes in population size but can go undetected in density-dependent growth models such as the Gompertz or Ricker models. We therefore posit that gradual cumulative changes to landscapes (anthropogenic or natural) may have resulted from AMO's sustained influence on climate, such as warmer temperatures, and more ponds and associated food resources that improve duck reproductive success (Dzus and Clark 1998; Krapu et al. 2000) and, possibly, survival. Hinsley et al. (2016) proposed a similar climate-linked mechanism, involving a 1–2 year build-up in food supply to best explain timing of breeding by great tits (*Parus major*) in England.

The mechanism of increased precipitation associated with the AMO positively influencing duck populations is plausible. Variation in wetland area and abundance are important factors driving duck populations (Drever 2006; Walker et al. 2013), and wetlands are strongly influenced by patterns in precipitation building up over long time periods, often several years. (Ballard et al. 2014; LaBaugh et al. 2018). While we did not detect clear increases in precipitation across the full NA study area, the prairie region, which has the greatest density of breeding waterfowl (50–75% of those counted during the NA survey; [U.S. Department of Interior 2018]), did show increased precipitation during the study period. This regional pattern is further corroborated by pond counts recorded during the survey (U.S. Department of Interior 2018), and other research demonstrating increased summer precipitation over a similar area and time period (Shook and Pomeroy 2012). Unfortunately, because a time series of pond abundance or wetland flooding is not available for core breeding areas of WEU ducks, we are not able to make similar conclusions about the impacts of increased precipitation on wetland habitat there.

Regarding the increased mean temperatures observed on both continents, there is evidence that population trends of many avian communities in Europe and NA are positively affected by temperature trends (Stephens et al. 2016). Counts of some duck species we investigated were included in Stephens et al. (2016) temperature-avian trend analyses, although surveys they used were separate from those in our study and not explicitly designed to monitor duck populations. Importantly, the similar climate-duck count patterns found herein and by Stephens et al. (2016) are based on independent data sets, providing some corroboration of each.

We have focused on changing climate as a likely cause of shared long-term temporal trends on each continent. Although harvest management has improved during the past several decades and this potentially resulted in less
<figure><img src="image_11.png" /><figcaption>**Fig. 7** Patterns of association between duck population estimates (standardized, from state-space models) and Atlantic Multidecadal Oscillation (AMO) in Western Europe and North America, 1976–2019. REDH-POCH refers to Redhead/Pochard, and RNDU-TUDU refers to Ring-necked Duck/Tufted Duck species pairs. The shaded regions are the 95% confidence interval for the slopes</figcaption></figure>

population impacts from harvest, we believe this alone cannot account for the strong positive trends in several duck populations on both continents. Rather, in NA, harvest regulations have been liberalized as populations have increased and duck harvest seems to track population sizes without clear evidence that it also depresses them (Cooch et al. 2014). Conservation efforts have intensified on both continents, but their extent is not commensurate with the observed increases in populations, and wetlands continue to be drained and degraded. Indeed, in North America, agricultural intensification appears to depress many other avian populations which overlap geographically with the core breeding range of our study species (Stanton et al. 2018; Zhao et al. 2019).

Fluctuations in the AMO could result in shared climate patterns on both continents discussed above and these changes might have gradually improved the breeding habitat and productivity or survival of ducks. However, it is also possible that the patterns in climate observed are caused by anthropogenic climate change or cycles in climate which are not fully characterized by the AMO. Furthermore, despite these possible links between climate indices and population trends, the possibility exists of confounding climate effects with long-term land use change (Eglington and Pearce-Higgins 2012). During the past 30 years, changes in agricultural technology and crops in WEU and NA have generally increased the availability and abundance of high-quality foods in winter, reducing food constraints among granivorous birds, especially several dabbling duck species. Conversely, differences in habitat use may help explain

why some species-pairs did not share trends or were negatively correlated. Changes in fish farming in Europe may be responsible for the recent decline of several WEU diving ducks, in particular the common pochard (Fox et al. 2016), whereas their congener in NA, the redhead, is not dependent on these habitats. Similarly, the decline of northern pintail in NA and not WEU seems to be due to the proclivity of NA populations to nest in cropland areas (rather than primarily boreal for WEU populations) where most nests are subsequently destroyed by predators or seeding activity (Devries et al. 2018; Buderman et al. 2020).

In conclusion, we have shown that populations of ecologically similar duck species on each continent fluctuate independently of each other on an annual basis, but that several species shared increasing trends during our study period. We posited gradual changes in climate, possibly induced by the AMO, as a plausible explanation. The link between the AMO and the shared climate patterns on each continent needs further investigation as do mechanisms by which changes in land use could also explain some portion of the trends in duck populations observed. To test hypothesized mechanisms (Ranta et al. 1995), it would be instructive to look for correlations in demographic rates that drive population change for species-pairs on each continent. For example, using vulnerability-corrected age ratios obtained from wing samples donated by hunters and band-recovery analyses could give insights into respective changes in reproductive and survival rates (Arnold et al. 2018) and whether the population change is driven by the same demographic rate on each continent.
**Acknowledgements** Acknowledgements – We sincerely thank the many dedicated individuals – professional and volunteer – who participated in annual surveys of birds across N.A. and western Europe.

**Author contribution** Author contributions – Conceived and designed the experiments: MG, DM, RGC. Analyzed the data: DM, MD. Wrote the paper: DM, RGC, MG, MD, TL. Conceived structure and content of manuscript: DM, RGC, MG, MD, TL.

**Funding** Open access funding provided by Environment & Climate Change Canada library. Funding for this study was provided by University of Saskatchewan, Environment and Climate Change Canada, and Office Français de la Biodiversité.

**Data availability** Data is openly available from sources identified in the methods section.

## Declarations

**Competing interests** The authors declare no competing interests.

**Open Access** This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

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