\documentclass[10pt]{article}

\usepackage{fullpage}
\usepackage{setspace}
\usepackage{parskip}
\usepackage{titlesec}
\usepackage[section]{placeins}
\usepackage{xcolor}
\usepackage{breakcites}
\usepackage{lineno}
\usepackage{hyphenat}





\PassOptionsToPackage{hyphens}{url}
\usepackage[colorlinks = true,
            linkcolor = blue,
            urlcolor  = blue,
            citecolor = blue,
            anchorcolor = blue]{hyperref}
\usepackage{etoolbox}
\makeatletter
\patchcmd\@combinedblfloats{\box\@outputbox}{\unvbox\@outputbox}{}{%
  \errmessage{\noexpand\@combinedblfloats could not be patched}%
}%
\makeatother


\usepackage{natbib}




\renewenvironment{abstract}
  {{\bfseries\noindent{\abstractname}\par\nobreak}\footnotesize}
  {\bigskip}

\titlespacing{\section}{0pt}{*3}{*1}
\titlespacing{\subsection}{0pt}{*2}{*0.5}
\titlespacing{\subsubsection}{0pt}{*1.5}{0pt}


\usepackage{authblk}


\usepackage{graphicx}
\usepackage[space]{grffile}
\usepackage{latexsym}
\usepackage{textcomp}
\usepackage{longtable}
\usepackage{tabulary}
\usepackage{booktabs,array,multirow}
\usepackage{amsfonts,amsmath,amssymb}
\providecommand\citet{\cite}
\providecommand\citep{\cite}
\providecommand\citealt{\cite}
% You can conditionalize code for latexml or normal latex using this.
\newif\iflatexml\latexmlfalse
\providecommand{\tightlist}{\setlength{\itemsep}{0pt}\setlength{\parskip}{0pt}}%

\AtBeginDocument{\DeclareGraphicsExtensions{.pdf,.PDF,.eps,.EPS,.png,.PNG,.tif,.TIF,.jpg,.JPG,.jpeg,.JPEG}}

\usepackage[utf8]{inputenc}
\usepackage[ngerman,english]{babel}



\usepackage{float}








\begin{document}

\title{Behavioural adaption of Scaly-sided Merganser (Mergus squamatus) to
habitats with different water depth: different activity profile but the
same foraging energetics}



\author[1]{Peizhong Liu}%
\author[2]{Meihan Liu}%
\author[3]{Dongyang Xiao}%
\author[1]{Ying He}%
\author[1]{Rong Fan}%
\author[1]{Cai Lv}%
\author[4]{Li Wen}%
\author[5]{Zeng Qing}%
\author[1]{Guangchun Lei}%
\affil[1]{Beijing Forestry University School of Ecology and Nature Conservation}%
\affil[2]{Beijing Forestry University College of Forestry}%
\affil[3]{The People's Government of Shangqing Town, Yingtan}%
\affil[4]{NSW Office of Environment and Heritage}%
\affil[5]{Center for East Asian-Australasian Flyway Studies, Beijing Forestry University, Beijing, China}%


\vspace{-1em}



  
  \date{May 23, 2024}


\begingroup
\let\center\flushleft
\let\endcenter\endflushleft
\maketitle
\endgroup





\selectlanguage{english}
\begin{abstract}
Abstract: Throughout evolutionary history, animals are finely tuned to
adjust their behaviors corresponding to environmental variations.
Behavioral flexibility represents an important component of a species'
adaptive capacity in the face of rapid anthropogenetic environmental
change, and knowledge of animal behaviours is increasingly recognized in
conservation biology. In aquatic ecosystem, variation of water depth is
a key factor affecting the availability of food, thus the foraging
behaviours of many waterbirds, especially piscivores. In this study, we
compared the foraging behaviours of Scaly-sided Merganser (Mergus
squamatus), an endangered migratory diving duck endemic to east Asia, in
habitats with different water depth, using video camera records obtained
from the known wintering sites during three winters from 2018-2020.
Further, the energy expenditure of foraging behavior profile and energy
intake based on fish sizes were calculated to study the foraging
energetics. In total, 200 effective video footages that contained 1,086
minutes with 17,995 behaviours and 163 events of catching fish were
recorded. Results showed that 1) time length for fishing (including
eye-submerging, head-dipping, diving and food handling) of Mergus
squamatus in shallow waters was significantly more than in deep waters;
2) Mergus squamatus spent significantly more time for preparing
(including vigilance, preening and swimming) in deep waters than in
shallow waters; 3) the mean catch rate was 0.28 fish/minute in shallow
waters, which is significantly higher than the value of 0.13 fish/minute
in deep waters; 4) despite the distinct foraging behaviour profiles and
energy intakes, Mergus squamatus showed similar energetics in shallow
and deep waters. We concluded that Mergus squamatus is a good example of
behavioural flexibility that aligns with expectations of optimum
foraging theory, in that it behaves in accordance to resource
availability in different environments, resulting in high foraging
efficiency. The behavioural flexibility can be related to its evolution
history.%
\end{abstract}%



\sloppy


\textbf{Behavioural adaption of Scaly-sided Merganser (\emph{Mergus
squamatus}) to habitats with different water depth: different activity
profile but the same foraging energetics}

Peizhong Liu \textsuperscript{1,2}, Meihan Liu \textsuperscript{3},
Dongyang Xiao \textsuperscript{4}, Ying He \textsuperscript{1,2}, Rong
Fan\textsuperscript{1,2}, Cai Lu \textsuperscript{1,2}, Li
Wen\textsuperscript{5,6}, Qing Zeng \textsuperscript{1,2*} and Guangchun
Lei \textsuperscript{1,2*}

\textsuperscript{1} Centre for East Asian-Australasian Flyway Studies,
Beijing Forestry University, Beijing 100083, China;
peizhongliu@bjfu.edu.cn (P.L.); Abbyisxyz33@bjfu.edu.cn (Y.H.);
fanrong1119@bjfu.edu.cn (R.F.); cailu@bjfu.edu.cn (C.L.)

\textsuperscript{2} School of Ecology and Nature Conservation, Beijing
Forestry University, Beijing 100083, China

\textsuperscript{3} The college of Forestry, Beijing Forestry
University, Beijing 100083, China; MeihanLiu@bjfu.edu.cn (M.L.)

\textsuperscript{4} The People's Government of Shangqing Town, Yingtan,
335004, China; ssmerganser@163.com (D.X.)

\textsuperscript{5} NSW Department of Planning, Industry and
Environment, Science, Economics and Insights Division, Sydney 2150,
Australia; li.wen@environment.nsw.gov.au (L.W.)

\textsuperscript{6} Department of Earth and Environmental Sciences,
Macquarie University, Sydney 2109, Australia

\textsuperscript{*}Correspondence: zengqing@bjfu.edu.cn (Q.Z.) and
leiguangchun@bjfu.edu.cn (G.L.), School of Ecology and Nature
Conservation, Beijing Forestry University, Beijing 100083, China.

\textbf{Abstract:} Throughout evolutionary history, animals are finely
tuned to adjust their behaviors corresponding to environmental
variations. Behavioral flexibility represents an important component of
a species' adaptive capacity in the face of rapid anthropogenetic
environmental change, and knowledge of animal behaviours is increasingly
recognized in conservation biology. In aquatic ecosystem, variation of
water depth is a key factor affecting the availability of food, thus the
foraging behaviours of many waterbirds, especially piscivores. In this
study, we compared the foraging behaviours of Scaly-sided Merganser
(\emph{Mergus squamatus} ), an endangered migratory diving duck endemic
to east Asia, in habitats with different water depth (Shallow water:
0-40cm; Deep water: 40-300cm), using video camera records obtained from
the known wintering sites during three winters from 2018-2020. Further,
the energy expenditure of foraging behavior profile and energy intake
based on fish sizes were calculated to study the foraging energetics. In
total, 200 effective video footages that contained 1,086 minutes with
17,995 behaviours and 163 events of catching fish were recorded. Results
showed that 1) time length for fishing (including eye-submerging,
head-dipping, diving and food handling) of \emph{Mergus squamatus} in
shallow waters was significantly more than in deep waters; 2)
\emph{Mergus squamatus}spent significantly more time for preparing
(including vigilance, preening and swimming) in deep waters than in
shallow waters; 3) the mean catch rate was 0.28 fish/minute in shallow
waters, which is significantly higher than the value of 0.13 fish/minute
in deep waters; 4) despite the distinct foraging behaviour profiles and
energy intakes,\emph{Mergus squamatus} showed similar energetics in
shallow and deep waters. We concluded that \emph{Mergus squamatus} is a
good example of behavioural flexibility that aligns with expectations of
optimum foraging theory, in that it behaves in accordance to resource
availability in different environments, resulting in high foraging
efficiency. The behavioural flexibility can be related to its evolution
history.

\textbf{Keywords} : Foraging behaviours adaption; Foraging energetics;
In-stream habitats; Morphological specialization.



\textbf{1. Introduction}

Wild animals have been constantly subjected to environmental
fluctuations during their evolutionary history, and have evolved to
match physiology and behaviour to the predictable environmental
variations in their natural habitats (Schmidt-Nielsen, 1997). Adjusting
behaviour is often the first response when environmental conditions are
altered (Snell-Rood, 2013). Behavioural responses are not always
adaptive, but the ability of wildlife to behave appropriately in
response to environmental changes is crucial for their survival (Sih,
Ferrari, \& Harris, 2011; Wong \& Candolin, 2015). Behavioural
plasticity could allow species to adjust behaviour to suit the
conditions of its immediate environment and, in so doing, increase its
fitness (Van Buskirk, Candolin, \& Wong, 2012).

Among all adaptive tactics, foraging behaviours are most advantageous
and allow the species to navigate diverse landscapes while efficiently
searching for food (Schoener, 1971), and gain physiological,
survivorship, and fitness benefits (Hadfield \& Strathmann, 1996). For
example, Great knots (\emph{Calidris tenuirostris} ) extended their
feeding time and adjusted their food selection to adapt the suddenly
decline of original main food (Zhang et al., 2019).

Some young salmonid fishes clearly decrease their foraging behaviours
from still water habitats to slow-running waters to fast-running waters
(Tunney \& Steingr\selectlanguage{ngerman}ímsson, 2012). To assess animals' foraging plasticity
in a changing environment, habitat--behaviour interactions within the
wide array of environmental conditions are to be characterized (Gilmour
et al., 2018).

Flexible and specialized foraging strategies are dependent on the
stability of available resources in habitats (West-Eberhard, 1989). For
most waterbirds, water depth might be the primary of habitat quality
(Zeng, Lu, et al., 2018). Different water depths mean different species,
sizes and quantities of food and therefore a key factor to affect their
foraging behaviours and techniques (Giraldo et al., 2017; Harvey \&
Stewart, 1991).

Scaly-sided Merganser (\emph{Mergus squamatus} ) is endemic to east Asia
and is listed as globally endangered (BirdLife \& International, 2017).
It's a habitat specialist, which occurs on clear, flowing rivers in the
mountainous regions (Zeng, Wei, \& Lei, 2018). It mainly breeds in
southeastern Russia, and northeast China, and winters in the central and
southern China, especially middle and lower Yangtze River (Zeng, Wei, et
al., 2018; Zhao \& Pao, 1998). \emph{M. squamatus} is an opportunist
piscivore who selects the most abundant food source (Zhao \& Pao, 1998),
such as fish and macroinvertebrates. It has long thin hooked bill with
many serrations at the tip (Zhao \& Pao, 1998) and is adapted to active
hunting of moving prey in water column. \emph{M. squamatus} mainly takes
two foraging modes: diving and head-dipping (Solovieva, 2013; Zhao \&
Pao, 1998). In breeding areas, \emph{M. squamatus} usually immerses its
head into shallow waters to pick aquatic insects and use diving
techniques to catch fish in deep waters (Solovieva, 2013; Zhao \& Pao,
1998). Foraging strategy and energy budgets of \emph{M. squamatus} were
unknown in the wintering grounds (Solovieva, 2013).

The loss of lateral and longitudinal connectivity of free-flowing rivers
through flow regulations such as damming presents a major threat to
global freshwater biodiversity (Barbarossa et al., 2020; Dudgeon, 2019;
Tonkin, Heino, \& Altermatt, 2018) including the obligated freshwater
megafauan (He et al., 2019) and foragers such as waterbirds (Zeng, Lu,
et al., 2018). Knowledge of animal behaviour is fundamental in
understanding and mitigating the effects of habitat loss and
fragmentation. In this study, using three years (from 2018 to 2020) of
video footages of \emph{M. squamatus} foraging at the wintering habitats
with different water depths, we aim to evaluate the extent to which
foraging behaviour flexibility and plasticity exist. We also compare the
foraging energetics in different habitats by estimating the behavior
energy costs, fish catch rates, and energy intakes. We use these
findings to highlight the risk of the rapid anthropogenic environmental
changes to habitat specialists (Sih et al., 2011).

\textbf{2. Material and Methods}

\textbf{2.1 Study area}

This study was conducted in a 5 km reach of the Shangqing River in
Jiangxi province (Fig. 1), a tributary of Yangtze River. The site is a
major \emph{M. squamatus} wintering ground, providing foraging habitat
for a population of about 50 individuals every year (Wang et al., 2010).
The average annual temperature is 16.7 \selectlanguage{english} and the average annual
precipitation is 1816 mm. Both sides of the river were covered by
forest. There are many gravel bars and islands in this river reach,
providing ideal habitats for \emph{M. squamatus} to forage and roost
((Zeng et al., 2015)). The water depth varies from 0 to 3 meters.
Considering the different foraging behaviours, we classified areas with
water depth up to 40 cm as shallow and those greater than 40 cm as deep
(Fig. 1).\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image1/image1}

\end{center}
\end{figure}

Figure 1. The study area in Shangqing River and its location in the
Yangtze River basin

\textbf{2.2 Behaviour recordings and identification}

Video recording was often used to monitor the foraging behaviour in a
natural complex environment (Bruijn, Vosteen, Vet, Smid, \& Boer, 2021).
In this study, video footages (Nikon P900S) were taken from six fixed
locations (3 for each habitat types, Fig. 1) to record the foraging
activities of \emph{M. squamatus} in three winters (2018-2020).
Recording was initiated when a bird started a foraging bout (see below)
and the camera then followed the bird till it finished the foraging or
disappeared from the range of view. Based on field observation and
examining the videos, we defined the duration of a foraging bout as the
time interval encompassing the descending, swimming, diving, and the
subsequent resting on the water surface and taking off (Table 1). Each
foraging bout could last for 3-15 minutes and contained multiple
activities.

We focused on the foraging behaviours of individuals, which were
identified as 8 activities from 3 related types: fishing, preparing and
other social activities (Table 1). Here we distinguished two main
fishing behaviours: diving and head-dipping (Fig. 2). While diving is
mainly performed in deep waters, head-dipping is the main fishing tactic
in shallow waters. The length of time that a \emph{M. squamatus} spent
in each behaviour was divided by the length of the foraging bout to give
the percent of time spent in each behaviour.

Table 1. Description of identified behaviours of Scaly-sided Merganser

\emph{M. squamatus}\selectlanguage{english}
\begin{longtable}[]{@{}llll@{}}
\toprule
\textbf{No.} & \textbf{Type} & \textbf{Behaviour} &
\textbf{Description}\tabularnewline
\midrule
\endhead
1 & Fishing & Eye-submerging & Submerging eyes into water\tabularnewline
2 & & Head-dipping & Submerging head under surface water\tabularnewline
3 & & Diving & Diving under surface water\tabularnewline
4 & & Food handling & Handling fish on the water surface\tabularnewline
5 & Preparing & Vigilance & Looking around to detect and avoid threats
of predation and intraspecific competition\tabularnewline
6 & & Swimming & Swimming on the surface of the water\tabularnewline
7 & & Preening & Any maintenance done to feathers, including
straightening and oiling feathers\tabularnewline
8 & Others & Social interacting & Intraspecific interaction and
interspecific interaction\tabularnewline
\bottomrule
\end{longtable}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image2/image2}

\end{center}
\end{figure}

Figure 2. The identified foraging behaviours of \emph{M. squamatus} at
different water depth

\textbf{2.3 Video analysis}

All videos were analyzed in Boris Video v7.9.1. BORIS (Behavioural
Observation Research Interactive Software, University of Torino) is a
free, open-source and multiplatform standalone program that allows a
user-specific coding environment to be set for a computer-based review
of previously recorded videos or live observations (Friard \& Gamba,
2016). The software has been used in study behaviour of human, farm
animals, and wildlife (Aletta, Lepore, Kostara-Konstantinou, Kang, \&
Astolfi, 2016). In BORIS, once the coding process is completed, the
program can extract a time-budget for single or grouped observation
automatically and present as an at-a-glance summary of the main
behaviour features (Friard \& Gamba, 2016). Data of behaviour duration
and frequency was recorded and conversed to excel files.

\textbf{2.4 Energy budget}

Energy gain We estimated the energy gain of every successful fishing
event. First, the prey size was determined by comparing the catch with
the beak volume of \emph{M. squamatus} , and was assigned to one of the
five following classes: 0.5 volume, 1 volume, 1.5 volume, 2 volume, 2.5
volume of beak (Fig 3). Based on the fish survey at Shangqing River, the
average weight of the fish with one beak size was 14.1 g. As the energy
content of the fish is approximately 4.0 KJ/g (Gremillet, Schmid, \&
Culik, 1995) and the assimilation efficiency is assumed to be 80\%
(Feltham, 1995), the energy gain can then be calculated as:

Energy gained=45.12 x fish size (1)\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image3/image3}

\end{center}
\end{figure}

Figure 3. Photos shows fish sizes in relation with the beak of M.
squamatus. Fish size is used to estimate energy gain.

Energy expenditure Energy expenditure was calculated using the observed
foraging activity profile and the Basal Metabolic Rate (BMR). The BMR
was determined to use the Aschoff-Pohl equation (Aschoff \& Pohl, 1970):

BMR=307.5 Body Mass\textsuperscript{0.734} (2)

The BMR coefficients of different behaviours were sourced from the
published studies on Common Merganser \emph{Mergus Merganser} , Lesser
snow Goose and Black duck (Table 2). Because the BMR coefficient of
other activities including socializing, preening and food handling
varies greatly from literature, moreover, these activities account for
only a small fraction of the total foraging time (less than 4.2\% of the
total, see Table 3 below), we excluded them in calculating energy
balance. The weight data (i.e. male 1125--1400 g, female 870--1100 g)
of\emph{M. squamatus} were obtained from (Kear \& Hulme, 2005).
Therefore, the BMR of male and female \emph{M. squamatus} was calculated
as 365.00 KJ/day and 304.12 KJ/day, respectively. We assumed that the
mean BMR of\emph{M. squamatus} was 334.56 KJ/day and the energy
expenditure was each foraging behaviour BMR by multiplying the behaviour
time rate.

Table 2. Published basal metabolic rate (BMR) coefficients of different
foraging activities\selectlanguage{english}
\begin{longtable}[]{@{}llll@{}}
\toprule
\textbf{Behaviour} & \textbf{BMR Coefficient} & \textbf{Species} &
\textbf{Reference}\tabularnewline
\midrule
\endhead
Diving & 3.2 & Common Merganser & (Newson \& Hughes,
1998)\tabularnewline
Head-dipping & 2.5 & Lesser Snow Goose & (J\selectlanguage{ngerman}ónsson \& Afton,
2006)\tabularnewline
Eye-submerged & 2.0 & Lesser Snow Goose & (J\selectlanguage{ngerman}ónsson \& Afton,
2006)\tabularnewline
Vigilance & 2.0 & Common Merganser & (Newson \& Hughes,
1998)\tabularnewline
Swimming & 2.3 & Black Duck & (Beerens, Gawlik, Herring, \& Cook,
2011)\tabularnewline
\bottomrule
\end{longtable}

\textbf{2.5 Statistical analyses}

To simplify the comparison of behaviour differences in shallow and deep
habitat, the eight identified behaviours were group into three main
classes (i.e. Fishing, searching, and resting, Table 1). As the three
behaviour variables were expressed as a percentage of the total length
of foraging bout, they are not independent (i.e. summed to 1), we used
generalised multivariate models within Bayesian framework using the R
(Team, 2019) package ``brms'' (B\selectlanguage{ngerman}ürkner, 2017). We also we tested three
error distribution families: Beta, Gamma, and Gaussian to account for
the potentially non-normal distribution. Difference in energy balance
was also tested using Bayesian models.

\textbf{3. Results}

During 90 days of the three winters, we obtained a total of 200
effective video footages, which contained 1,086 minutes of 17,995
foraging activities (Table 3). Among these valid for-aging bouts, 84
were in shallow waters habitats and 116 were in deep waters. Of these
foraging bouts, we observed 98 successful fishing events. A total of 163
fish were caught as there were occasions that a bird captured more than
one in a single foraging bout.

\textbf{3.1. General pattern of behaviour profiles}

Not surprisingly, the birds spent most time in activities relating to
obtaining food including diving, head-dipping, eye-submerging, and
vigilance, and food handling, preening and other social activities such
as intraspecific interaction took only a fraction of a foraging bout
(Table 3).

For each foraging activity, diving took the longest time with mean
duration of 13.13 seconds (SD = 7.12) followed by swimming (5.22 ±
6.59s), preening (4.69 ± 4.17s) and vigilance (4.06 ± 2.69s),
socializing (3.83 ± 3.12s) and food handling (3.19± 4.77s). While the
frequency for head-dipping and eye-submerging were the highest (4.40 ±
5.51 and 5.75 ± 5.48 times/minute, respectively), they took the least
time (2.60 ± 0.92s and 1.89 ± 0.07s, respectively). Moreover, the
standard deviation (SD) of the attributes (i.e. frequency, duration and
proportion) for most behaviours were relatively large comparing with the
mean, suggesting the highly variable behavioural profiles of the bird.

Table 3. Summary of the foraging behaviours of \emph{M. squamatus}during
wintering in Shangqing River, China\selectlanguage{english}
\begin{longtable}[]{@{}llllllll@{}}
\toprule
\begin{minipage}[b]{0.12\columnwidth}\raggedright\strut
\textbf{Behaviour}\strut
\end{minipage} & \begin{minipage}[b]{0.12\columnwidth}\raggedright\strut
\textbf{No of} \textbf{observations}\strut
\end{minipage} & \begin{minipage}[b]{0.12\columnwidth}\raggedright\strut
\textbf{Frequency (times/min)}\strut
\end{minipage} & \begin{minipage}[b]{0.12\columnwidth}\raggedright\strut
\textbf{Frequency (times/min)}\strut
\end{minipage} & \begin{minipage}[b]{0.12\columnwidth}\raggedright\strut
\textbf{Duration (second)}\strut
\end{minipage} & \begin{minipage}[b]{0.12\columnwidth}\raggedright\strut
\textbf{Duration (second)}\strut
\end{minipage} & \begin{minipage}[b]{0.12\columnwidth}\raggedright\strut
\textbf{Proportion (\%)}\strut
\end{minipage} & \begin{minipage}[b]{0.12\columnwidth}\raggedright\strut
\textbf{Proportion (\%)}\strut
\end{minipage}\tabularnewline
\midrule
\endhead
\begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\textbf{Mean}\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\textbf{SD}\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\textbf{Mean}\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\textbf{SD}\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\textbf{Mean}\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
\textbf{SD}\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
Eye-submerging\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
6,857\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
5.75\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
5.48\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
1.89\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
0.07\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
18.11\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
17.25\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
Head-dipping\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
5,421\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
4.40\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
5.51\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
2.60\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
0.92\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
19.04\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
23.51\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
Vigilance\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
3,032\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
2.89\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
1.66\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
4.06\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
2.69\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
19.93\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
12.60\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
Diving\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
1,487\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
1.48\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
1.50\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
13.13\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
7.12\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
32.64\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
28.81\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
Swimming\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
693\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
0.68\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
0.78\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
5.22\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
6.59\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
5.97\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
8.64\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
Handling\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
162\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
0.27\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
0.52\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
3.19\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
4.77\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
2.06\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
4.69\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
Preening\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
240\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
0.16\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
0.26\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
4.69\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
4.17\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
1.19\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
3.02\strut
\end{minipage}\tabularnewline
\begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
Social interacting\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
103\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
0.09\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
0.16\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
3.83\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
3.12\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
1.05\strut
\end{minipage} & \begin{minipage}[t]{0.10\columnwidth}\raggedright\strut
1.97\strut
\end{minipage}\tabularnewline
\bottomrule
\end{longtable}

\textbf{3.2. Foraging behaviors at different habitats}

The bird showed distinct behaviour profiles in deep and shallow
habitats. While the duration of a foraging bout was only slightly higher
in shallow than in deep habitats (Fig. 4A), the proportion of time spent
in each activity classes differed significantly. Specifically, while the
bird spent significantly more time in getting ready for fishing in deep
waters (Fig. 4B), the time for fishing was significantly greater in
shallow waters (Fig. 4C). In addition, time for social interaction was
significantly higher in shallow waters (Fig. 4D).

In both habitats, more time was spent for fishing than other activities.
In deep waters, the bird spent an average of 62.8\%, 36.3\% and 0.9\% of
the foraging time on fishing, preparing, and social interaction,
respectively. In shallow waters, the values were 81.8\%, 16.8\%, and
1.4\%. Fishing behaviours were mainly diving (87.3\%) in deep water and
head-dipping (53.7\%) and eye submerging in shallow water (43.1\%).
Pre-paring behaviours were mainly vigilance in both deep waters (88.6\%)
and shallow waters (75.5\%).\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image4/image4}

\end{center}
\end{figure}

Figure 4. The difference in foraging behaviours of Scaly-sided
Merganser\emph{Mergus squamatus} in deep and shallow habitats. The mean
(dots) and the 95\% credible intervals (vertical bars) are based on
4,000 posterior draws of the fitted models. Note the different scale of
Y-axis. A) Foraging duration in seconds; B) Proportion of preparing; C)
Proportion of fishing; and D) Proportion of other activities.

\textbf{3.3. Foraging gain at different water depth}

As for the fish catched at different water depth, the mean fish catch
rate was 0.28 fish per minute in shallow waters, which is significantly
higher than the value of 0.13 fish per minute in deep waters (Fig. 5A).
However, as the prey in shallow waters was smaller (data not shown), the
mean biomass of the fish captured was slightly greater in deep waters
(Fig. 5B).\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image5/image5}

\end{center}
\end{figure}

Figure 5. Fish catching rate (A) and biomass of captured fish (B) of the
Scaly-sided Merganser \emph{Mergus squamatus} in deep and shallow
habitats. The mean (dots) and the 95\% credible intervals (vertical
bars) are based on 4,000 posterior draws of the fitted models.

\textbf{3.4. Foraging energetics in shallow and deep waters}

Despite the distinct behavioural profiles in different habitats (Fig.
4), the \emph{M. squamatus} showed similar foraging energetics (Fig. 6),
suggesting that the birds can fish equally efficiently in both deep and
shallow waters. The estimate of mean net energy gains were 6.53 KJ/min
and 6.28 KJ/min in deep and shallow habitats, respectively, and the
standardized errors (SE) was comparably small (less than 0.50 in both
habitats, Fig. 6A). Energy gains through food intake were slightly
higher in deep waters (mean estimates were 6.99 KJ/min and 6.08 KJ/min
in deep and shallow waters, respectively, Fig. 6B). Again, SE was small
in comparison with the mean. The small SE suggested that the bird
performed stably during the three winters in both habitats. Although the
foraging energy costs were significantly higher in deep waters, this
difference did not affect the comparison of energy balance as they were
only a fraction of energy gain through food intake (generally less than
5\%, Fig. 6C).\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image6/image6}

\end{center}
\end{figure}

Figure 6. Foraging energetics of Scaly-sided Merganser \emph{Mergus
squamatus} in deep and shallow habitats. A) Net energy gain; B) Energy
gain from captured prey; and C) Predation cost. The mean (dots) and the
95\% credible intervals (vertical bars) are based on 10,000 posterior
draws of the fitted models. Note the different scale of Y-axis.

\textbf{4. Discussion}

Animal behavioural traits often show wide and consistent variation among
individuals (Dingemanse \& Wolf, 2013; Wolf \& Weissing, 2012) and this
variation has often been suggested to facilitate population persistence
in novel and variable environments (Sih et al., 2011). In the context of
rapid human-induced environmental change, such as habitat loss and
fragmentation, it's urgent to integrate animal behaviour and wildlife
conservation studies for maximizing outcomes (Berger-Tal et al., 2019;
Greggor et al., 2016; Sutherland, 1998).

We found that the predatory waterbird had similar energetics despite
distinct foraging methods, behaviour profiles, and foraging efficiency
in shallow- and deep-water habitats. These results suggest that
Scaly-sided Merganser is a good example of behavioural flexibility that
aligns with expectations of optimum foraging theory (OFT) (Pyke, 1984),
in that the duck behaves in accordance to resource availability in
different environments, resulting in high foraging efficiency. The
behavioural flexibility could be related to evolutionary adaptation
(Snell-Rood, 2013).

\textbf{4.1 Behaviour profiles are distinct}

\par\null

\textbf{4.2 Food gain and Energy balance is similar}

The two feeding strategies (i.e. head-dipping in shallow waters and
pursuit diving in deep waters) resulted in significantly different catch
rates, and apparently the duck was more efficacious in shallow waters
with a catch rates of 0.28 fish/minute (in comparison, the average catch
rate was 0.13 fish/minute in deep waters. Fig. 5A). This is in
consistency with studies on other piscivorous waterbirds. For example,
Shags (\emph{Phalacrocorax aristotelis} ) has higher prey--capture
performance in shallower (Wanless et al., 1993). The difference in
foraging catch rates could be linked to prey abundance and
vulnerability, which is strongly affected by water depth (Lantz, Gawlik,
\& Cook, 2011; Monaghan, Walton, Wanless, Uttley, \& Bljrns, 1994;
Schekkerman \& Beintema, 2007). As the key components of habitat
complexity for stream fish, water depth has an important effect on the
distributions and size of fish (Lonzarich \& Quinn, 1995; Rose, 2000)
and macroinvertebrates as well (Lantz et al., 2011). Small and juvenile
fish intended to inhabit shallow waters to avoid predatory fish (Blaber,
1980; Sheaves, 2006). In addition, it would be easier to catch a prey in
shallow waters.

Although more fish were caught in shallow waters, the total gains in
terms of biomass at different habitats were similar due to the larger
size of fish in deep waters. That's to say, the higher prey quality
offset the lower prey quantity in deep waters (Brodmann, Reyer,
Bollmann, Schl\selectlanguage{ngerman}äpfer, \& Rauter, 1997), resulting in slightly higher
energy gains (6.99±0.94, and 6.08±1.08 KJ/minute in deep waters and
shallow waters, respectively. Fig. 6B). However, the energy gains in
shallow waters may be underestimated as macroinvertebrates were excluded
in the study due to technical difficulty, and predation of
macroinvertebrates mainly occurs in shallow habitats.

Different foraging patterns imply highly different energy costs (Godfrey
\& Bryant, 2000). In deep waters, the bird spent significantly more time
in diving, which has high basal metabolic rate (Table 1 and (Leeuw,
1996)). The frequent pursuit diving resulted in significantly higher
energy cost in deeper water (Fig. 6C). However, as the forging energy
consumption of \emph{M. squamatus} was only a fraction of energy intake
(less than 10\%), it had little influence on the foraging energetics:
the net energy gain was slightly higher in deep waters but the
difference was not statistically significant (Fig. 6C).

\textbf{4.3 Optimal foraging theory}

Predatory animals may have a series of alternative foraging modes
(Kuwae, Miyoshi, Sassa, \& Watabe, 2010). The optimal foraging theory
(Pyke, 1984) predicts that decisions on foraging strategy, including
what, where and how to hunt, are based on a maximization of currencies
(Bautista, Tinbergen, \& Kacelnik, 2001). Therefore, in their natural
habitat, predators are expected to take different foraging strategies in
response to both prey abundance and vulnerability such that they attain
the highest energy intake rate.

As predicted by OPT, \emph{M. squamatus} showed high behavioural
flexibility by adjusting its foraging methods and behavior profiles in
shallow and deep areas. In deep waters, where prey abundance and
vulnerability are lower, \emph{M. squamatus} allocated most of the time
to repeated pursuit diving to minimize the foraging energy cost. This
strategy was awarded with bigger gains and resulting in comparable
energy gain as in shallow waters, where smaller preys are more abundant
and easier to catch. The wintering grounds of \emph{M. squamatus} are
mainly mountainous streams (Zhao \& Pao, 1998), which resources are
patchily distributed (Taylor \& Warren Jr, 2001). The behavioural
flexibility is critical for predators foraging in heterogeneous
environment (Abrahms et al., 2020), where prey is patchily distributed
and may be unpredictable for diving birds (Tessier \& Bost, 2020).

\textbf{5. Management implications and conclusions}

Overall, our findings highlight that the wintering \emph{M.
squamatus}has high behavioural flexibility adapted to the heterogeneous
foraging environment. However, its population is decreasing continuously
in recent decades and is listed as globally endangered by the IUCN
(BirdLife \& International, 2017). This gives an indication that the
rapid anthropogenic environmental changes may be excessing or even have
excessed the adaptive capacity of the species (Sih et al.,
2011).\emph{M. merganser} prefers to forage in clear, flowing river
reaches with relatively shallow waters depth (less than 10 m), which
provide diverse microhabitats, such as pools, glides, riffles,
sand/gravel bars, and islands, for fish and benthic macroinvertebrates
(Aadland, 1993).\emph{M. merganser} is morphologically specialized in
hunting moving prey in such environment (Kondratyev, 1999). The
evolutionary adaptation could lose its competitive advantages as human
pressures on existing habitats intensified (Lei et al., 2019) with
increasing water resource developments and other activities such as
sanding mining and fishing. These human pressions could dramatically
change the river landscape and decrease prey abundance. For example,
river regulation by damming increases water depth and reduces habitat
heterogeneity (Lei et al., 2019; Swales, 2018; Zeng, Lu, et al., 2018).
The endangered status of this iconic species demands researches on
estimating how much habitat, of what quality, is required to sustain its
population.

ACKNOWLEDGMENTS

We would like to thank The People's Government of Shangqing Town and
Forestry Bureau of Yingtan City.

Funding statement: This research was supported by supported by the
Fundamental Research Funds for the Central Universities (BLX202147).

Author contributions: Author Contributions: Conceptualization, P.L.,
Q.Z. and G.L.; Methodology, Q.Z. and L.W.; Investigation, P.L., M.L.,
D.X., Y.H. and R.F.; Writing---original draft preparation, P.L. and
M.L.; Writing---review and editing, Q.Z. and L.W.; Supervision, Q.Z.,
G.L. and C.L.; Project administration, C.L. and G.L. All authors have
read and agreed to the published version of the manuscript.

Data deposits: All data for analysis is available in Dryad.

\textbf{References}

Aadland, L. P. (1993). Stream habitat types: their fish assemblages and
relationship to flow. \emph{North American Journal of Fisheries
Management, 13} (4), 790-806.

Abrahms, B., Aikens, E. O., Armstrong, J. B., Deacy, W. W., Kauffman, M.
J., \& Merkle, J. A. (2020). Emerging perspectives on resource tracking
and animal movement ecology. \emph{Trends in ecology evolutionary
applications, 36} (4), 308-320.

Aletta, F., Lepore, F., Kostara-Konstantinou, E., Kang, J., \& Astolfi,
A. (2016). An experimental study on the influence of soundscapes on
people's behaviour in an open public space. \emph{Applied sciences, 6}
(10), 276.

Anderson, B. W., Reeder, M. G., \& Timken, R. L. (1974). Notes on the
feeding behavior of the Common Merganser (\emph{Mergus merganser}
).\emph{The Condor, 76} (4), 472-476.

Aschoff, J., \& Pohl, H. (1970). Der ruheumsatz von Vögeln als Funktion
der Tageszeit und der Körpergröße. \emph{Journal of Ornithology, 111}
(1), 38-47.

Barbarossa, V., Schmitt, R. J., Huijbregts, M. A., Zarfl, C., King, H.,
\& Schipper, A. M. (2020). Impacts of current and future large dams on
the geographic range connectivity of freshwater fish
worldwide.\emph{Proceedings of the National Academy of Sciences, 117}
(7), 3648-3655.

Bautista, L. M., Tinbergen, J., \& Kacelnik, A. (2001). To walk or to
fly? How birds choose among foraging modes. \emph{Proceedings of the
National Academy of Sciences, 98} (3), 1089-1094.

Beerens, J. M., Gawlik, D. E., Herring, G., \& Cook, M. I. (2011).
Dynamic habitat selection by two wading bird species with divergent
foraging strategies in a seasonally fluctuating wetland. \emph{The Auk,
128} (4), 651-662.

Berger-Tal, O., Greggor, A. L., Macura, B., Adams, C. A., Blumenthal,
A., Bouskila, A., Gotanda, K. M. (2019). Systematic reviews and maps as
tools for applying behavioral ecology to management and
policy.\emph{Behavioral Ecology, 30} (1), 1-8.

BirdLife International. (2017). \emph{Mergus squamatus} (amended version
of 2017 assessment). The IUCN Red List of Threatened Species 2017:
e.T22680488A118860238.

Blaber, S. (1980). Fish of Trinity Inlet system of north Queensland with
notes on the ecology of fish faunas of tropical Indo-Pacific
estuaries.\emph{Marine Freshwater Research, 31} (2), 137-146.

Brodmann, P. A., Reyer, H.-U., Bollmann, K., Schläpfer, A. R., \&
Rauter, C. (1997). The importance of food quantity and quality for
reproductive performance in alpine water pipits (\emph{Anthus
spinoletta} ). \emph{Oecologia, 109} (2), 200-208.

Bruijn, J. A. C. d., Vosteen, I., Vet, L. E. M., Smid, H. M., \& Boer,
J. G. d. (2021). Multi\selectlanguage{english}-camera field monitoring reveals costs of learning
for parasitoid foraging behaviour. \emph{Journal of Animal Ecology, 90}
, 1635-1646.

Burkner, P.-C. (2017). brms: An R package for Bayesian multilevel models
using Stan. \emph{Journal of statistical software, 80} (1), 1-28.

Carbone, C., \& Houston, A. (1994). Patterns in the diving behaviour of
the pochard, \emph{Aythya ferina} : a test of an optimality
model.\emph{Animal Behaviour, 48} (2), 457-465.

Dingemanse, N. J., \& Wolf, M. (2013). Between-individual differences in
behavioural plasticity within populations: causes and
consequences.\emph{Animal Behaviour, 85} (5), 1031-1039.

Dudgeon, D. (2019). Multiple threats imperil freshwater biodiversity in
the Anthropocene. \emph{Current Biology, 29} (19), R960-R967.

Feltham, M. (1995). Consumption of Atlantic salmon smolts and parr by
goosanders: estimates from doubly\selectlanguage{english}-labelled water measurements of captive
birds released on two Scottish rivers. \emph{Journal of Fish Biology,
46} (2), 273-281.

Fortin, D., Boyce, M. S., Merrill, E. H., \& Fryxell, J. M. (2004).
Foraging costs of vigilance in large mammalian herbivores. \emph{Oikos,
107} (1), 172-180.

Friard, O., \& Gamba, M. (2016). BORIS: a free, versatile open\selectlanguage{english}-source
event\selectlanguage{english}-logging software for video/audio coding and live
observations.\emph{Methods in ecology evolution, 7} (11), 1325-1330.

Gilmour, M. E., Castillo\selectlanguage{english}-Guerrero, J. A., Fleishman, A. B.,
Hernandez\selectlanguage{english}-Vazquez, S., Young, H. S., \& Shaffer, S. A. (2018).
Plasticity of foraging behaviors in response to diverse environmental
conditions. \emph{Ecosphere, 9} (7), e02301.

Giraldo, C., Ernande, B., Cresson, P., Kopp, D., Cachera, M.,
Travers\selectlanguage{english}-Trolet, M., \& Lefebvre, S. (2017). Depth gradient in the
resource use of a fish community from a semienclosed sea.\emph{Limnology
Oceanography, 62} (5), 2213-2226.

Godfrey, J., \& Bryant, D. (2000). State\selectlanguage{english}-dependent behaviour and energy
expenditure: an experimental study of European robins on winter
territories. \emph{Journal of Animal Ecology, 69} (2), 301-313.

Greggor, A. L., Berger-Tal, O., Blumstein, D. T., Angeloni, L.,
Bessa-Gomes, C., Blackwell, B. F., Fernandez-Juricic, E. (2016).
Research priorities from animal behaviour for maximising conservation
progress. \emph{Trends in ecology evolutionary applications, 31} (12),
953-964.

Gremillet, D., Schmid, D., \& Culik, B. (1995). Energy requirements of
breeding great cormorants Phalacrocorax carbo sinensis. \emph{Marine
ecology progress series, 121} , 1-9.

Guillemain, M., Fritz, H., \& Blais, S. (2000). Foraging methods can
affect patch choice: an experimental study in Mallard (\emph{Anas
platyrhynchos} ). \emph{Behavioural processes, 50} (2-3), 123-129.

Hadfield, M., \& Strathmann, M. (1996). Variability, flexibility and
plasticity in life histories of marine invertebrates. \emph{Oceanologica
acta, 19} (3-4), 323-334.

Harvey, B., \& Stewart, A. (1991). Fish size and habitat depth
relationships in headwater streams. \emph{Oecologia, 87} (3), 336-342.

He, F., Zarfl, C., Bremerich, V., David, J. N., Hogan, Z., Kalinkat, G.,
Jahnig, S. C. (2019). The global decline of freshwater
megafauna.\emph{Global Change Biology, 25} (11), 3883-3892.

Jonsson, J. E., \& Afton, A. D. (2006). Different time and energy
budgets of Lesser Snow Geese in rice-prairies and coastal marshes in
southwest Louisiana. \emph{Waterbirds, 29} (4), 451-458.

Kear, J., \& Hulme, M. (2005). Ducks, geese and swans: Species
accounts\emph{(Cairina} to \emph{Mergus)} (Vol. 2): Oxford University
Press.

Kondratyev, A. V. (1999). Foraging strategies and habitat use of sea
ducks breeding in northeast Russia. \emph{Ccasional Papers-Canadian
Wildlife Service} , 51-58.

Kuwae, T., Miyoshi, E., Sassa, S., \& Watabe, Y. (2010). Foraging mode
shift in varying environmental conditions by dunlin Calidris
alpina.\emph{Marine ecology progress series, 406} , 281-289.

Lantz, S. M., Gawlik, D. E., \& Cook, M. I. (2011). The effects of water
depth and emergent vegetation on foraging success and habitat selection
of wading birds in the Everglades. \emph{Waterbirds: The International
Journal of Waterbird Biology, 34} (4), 439-447.

Leeuw, J. J. d. (1996). Diving costs as a component of daily energy
budgets of aquatic birds and mammals: generalizing the inclusion of
dive-recovery costs demonstrated in tufted ducks. \emph{Canadian Journal
of Zoology, 74} (12), 2131-2142.

Lei, J., Jia, Y., Wang, Y., Lei, G., Lu, C., Saintilan, N., \& Wen, L.
(2019). Behavioural plasticity and trophic niche shift: How wintering
geese respond to habitat alteration. \emph{Freshwater Biology, 64} (6),
1183-1195.

Lonzarich, D. G., \& Quinn, T. P. (1995). Experimental evidence for the
effect of depth and structure on the distribution, growth, and survival
of stream fishes. \emph{Canadian Journal of Zoology, 73} (12),
2223-2230.

Monaghan, P., Walton, P., Wanless, S., Uttley, J., \& Bljrns, M. (1994).
Effects of prey abundance on the foraging behaviour, diving efficiency
and time allocation of breeding guillemots Uria aalge. \emph{Ibis, 136}
(2), 214-222.

Newson, S. E., \& Hughes, B. (1998). Diurnal activity and energy budgets
of Goosander Mergus merganser wintering on Chew Valley Lake, North
Somerset: influence of time of day and sex. \emph{Wildfowl, 49} (49),
173-180.

Nolet, B. A., Fuld, V. N., \& Van Rijswijk, M. E. (2006). Foraging costs
and accessibility as determinants of giving\selectlanguage{english}-up densities in a
swan\selectlanguage{english}-pondweed system. \emph{Oikos, 112} (2), 353-362.

Norberg, R. A. (1977). An ecological theory on foraging time and
energetics and choice of optimal food-searching method. \emph{The
Journal of Animal Ecology, 46} (2), 511-529.

Pyke, G. H. (1984). Optimal foraging theory: a critical
review.\emph{Annual review of Ecology Systematics, 15} (1), 523-575.

Robinson, B. G., \& Merrill, E. H. (2013). Foraging--vigilance
trade-offs in a partially migratory population: comparing migrants and
residents on a sympatric range. \emph{Animal Behaviour, 85} (4),
849-856.

Rose, K. A. (2000). Why are quantitative relationships between
environmental quality and fish populations so elusive? \emph{Ecological
Applications, 10} (2), 367-385.

Schekkerman, H., \& Beintema, A. J. (2007). Abundance of invertebrates
and foraging success of Black-tailed Godwit \emph{Limosa limosa} chicks
in relation to agricultural grassland management. \emph{Ardea, 95} (1),
39-54.

Schmidt-Nielsen, K. (1997). \emph{Animal physiology: adaptation and
environment} : Cambridge university press.

Schoener, T. W. (1971). Theory of feeding strategies. \emph{Annual
review of Ecology Systematics, 2} (1), 369-404.

Shao, M., \& Chen, B. (2017). Effect of sex, temperature, time and flock
size on the diving behavior of the wintering Scaly-sided Merganser
(\emph{Mergus squamatus} ). \emph{Avian Research, 8} (1), 1-7.

Shao, M., Shi, W., Zeng, B., \& Jiang, J. (2014). Diving Behavior of
Scaly-sided Merganser, \emph{Mergus squamatus} in Poyang Lake watershed,
China. \emph{Pakistan Journal of Zoology, 46} (1), 284-287.

Shao, M., Zeng, B., Tim, H., Chen, L., You, C., Wang, H., \& Dai, N.
(2012). Winter ecology and conservation threats of scaly-sided
Merganser\emph{Mergus squamatus} in Poyang Lake watershed, China.
\emph{Pakistan Journal of Zoology, 44} (2), 503-510.

Sheaves, M. (2006). Scale-dependent variation in composition of fish
fauna among sandy tropical estuarine embayments. \emph{Marine ecology
progress series, 310} , 173-184.

Sih, A., Ferrari, M. C., \& Harris, D. J. (2011). Evolution and
behavioural responses to human\selectlanguage{english}-induced rapid environmental
change.\emph{Evolutionary applications, 4} (2), 367-387.

Snell-Rood, E. C. (2013). An overview of the evolutionary causes and
consequences of behavioural plasticity. \emph{Animal Behaviour, 85} (5),
1004-1011.

Solovieva, D. (2013). Foraging behaviour and daily time budget of
Scaly-sided Merganser \emph{Mergus squamatus} breeding on Iman River,
Russia. \emph{Wildfowl, 53} (53), 205-214.

Sutherland, W. J. (1998). The importance of behavioural studies in
conservation biology. \emph{Animal Behaviour, 56} (4), 801-809.

Swales, S. (2018). The Use of Instream Habitat Improvement Methodology
Inmitigating the Adverse Effects of River Regulation on Fisheries.
In\emph{Alternatives in regulated river management} (pp. 185-208): CRC
Press.

Taylor, C. M., \& Warren Jr, M. L. (2001). Dynamics in species
composition of stream fish assemblages: environmental variability and
nested subsets. \emph{Ecology, 82} (8), 2320-2330.

R development core Team. (2019). A Language and Environment for
Statistical Computing, version 3.6.1.; R Foundation for Statistical
Computing: Vienna, Austria.

Tessier, E., \& Bost, C.-A. (2020). Behavioural adjustments during
foraging in two diving seabirds: king and macaroni penguins.\emph{Marine
Biology, 167} (9), 1-11.

Tonkin, J. D., Heino, J., \& Altermatt, F. (2018). Metacommunities in
river networks: The importance of network structure and connectivity on
patterns and processes. \emph{Freshwater Biology, 63} (1), 1-5.

Tunney, T. D., \& Steingrimsson, S. O. (2012). Foraging mode variation
in three stream\selectlanguage{english}-dwelling salmonid fishes. \emph{Ecology of Freshwater
Fish, 21} (4), 570-580.

Van Buskirk, J., Candolin, U., \& Wong, B. (2012). \emph{Behavioural
plasticity and environmental change} : Oxford University Press.

Wang, Z., Shan, J., Li, Y., Tu, X., Jia, D., Hao, X., Zhao, J. (2010).
Winter population status and endangered factors of scaly-sided merganser
(\emph{Mergus squamatus} ) in Jiangxi Province. \emph{Sichuan J. Zool,
29} , 597-600.

Wanless, S., Harris, M., \& Russell, A. (1993). Factors influencing
food\selectlanguage{english}-load sizes brought in by Shags Phalacrocorax aristotelis during
chick rearing. \emph{Ibis, 135} (1), 19-24.

West-Eberhard, M. J. (1989). Phenotypic plasticity and the origins of
diversity. \emph{Annual review of Ecology Systematics, 20} (1), 249-278.

Wolf, M., \& Weissing, F. (2012). Animal personalities: consequences for
ecology and evolution. \emph{Trends in ecology, 27} (8), 452-461.

Wong, B., \& Candolin, U. (2015). Behavioral responses to changing
environments. \emph{Behavioral Ecology, 26} (3), 665-673.

Ydenberg, R., \& Forbes, L. (1988). Diving and foraging in the Western
Grebe. \emph{Ornis Scandinavica, 19} (2), 129-133.

Zeng, Q., Lu, C., Li, G., Guo, Z.-B., Wen, L., \& Lei, G.-C. (2018).
Impact of a dam on wintering waterbirds' habitat use.\emph{Environmental
Conservation, 45} (4), 307-314.

Zeng, Q., Shi, L., Wen, L., Chen, J., Duo, H., \& Lei, G. (2015). Gravel
bars can be critical for biodiversity conservation: A case study on
Scaly-sided Merganser in South China. \emph{PLoS One, 10} (5), 1-13.

Zeng, Q., Wei, Q., \& Lei, G. (2018). Contribution of citizen science
towards cryptic species census: ``many eyes'' define wintering range of
the Scaly-sided Merganser in mainland China. \emph{Avian Research, 9}
(01), 63-72.

Zhang, S., Ma, Z., Choi, C., Peng, H., Melville, D. S., Zhao, T., Gils,
J. A. (2019). Morphological and digestive adjustments buffer
performance: How staging shorebirds cope with severe food
declines.\emph{Ecology evolutionary applications, 9} (7), 3868-3878.

Zhao, Z., \& Pao, Z. (1998). The foraging behaviour of the Scaly-sided
Merganser \emph{Mergus squamatus} in the Changbai Mountains and Xiao
Xingangling Mountains of China. \emph{Forktail, 14} , 76-77.

\selectlanguage{english}
\FloatBarrier
\end{document}

