\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,greek,english]{babel}



\usepackage{float}








\begin{document}

\title{Differences in Native and Invasive Fish Larval Occupancy and Detection
Probabilities in the Upper Mississippi River}



\author[1]{David J. Yff}%
\author[1]{Michael J. Weber}%
\affil[1]{Iowa State University of Science and Technology Department of Natural Resource Ecology and Management}%


\vspace{-1em}



  
  \date{May 19, 2024}


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





\selectlanguage{english}
\begin{abstract}
The Upper Mississippi River (UMR) represents one invasion front to
bigheaded carps \emph{Hypopthalmichthys} spp. in North America. Agencies
often sample larvae to determine the conditions that bigheaded carp
reproduction occurs, but the ability for conventional ichthyoplankton
sampling to detect bigheaded carp reproduction compared to native fish
is unknown. We used occupancy models to estimate larval bigheaded carp
and native fish larvae detection probabilities and assessed how habitat
type, Julian date, river discharge, and water temperature affect
occupancy. We sampled larvae in pools 18-20 of the UMR every two weeks
at the Iowa, Skunk, and Des Moines River confluences in backwater, side
channel, and thalweg habitats. Detection probabilities increased with
water volume filtered and was lower for larval bigheaded carp than
freshwater drum, gizzard shad, and percids. Freshwater drum and
bigheaded carp larvae had higher detection in thalweg and channel border
habitats compared to backwaters. Occupancy of bigheaded carp peaked on
June 19 \textsuperscript{th} at 20\selectlanguage{ngerman}°C, increased with discharge, and
declined with coefficient of variation (CV) of water temperature and
discharge. Gizzard shad and percids occupancy peaked on May 24
\textsuperscript{th} and increased with CV of water temperature while
occupancy of freshwater drum peaked on July 3 \textsuperscript{rd},
decreased with CV of water temperature, and increased with water
temperature. Our results indicate bigheaded carp are more difficult to
detect than native larvae and identified conditions associated with
larval occupancy that can be used to maximize detection and better
understand when, where, and under what conditions larvae are present
while accounting for imperfect detection.%
\end{abstract}\selectlanguage{ngerman}%



\sloppy


\textbf{Differences in Native and Invasive Fish Larval Occupancy and
Detection Probabilities in the Upper Mississippi River}

Running title: Larval fish occupancy and detection

David J. Yff and Michael J. Weber

Natural Resource Ecology and Management, Iowa State University, Ames, IA
50011, USA

* Corresponding author: David.yff@gmail.com

\textbf{ACKNOWLEDGEMENTS}

Partial funding for this project was provided by the Iowa Department of
Natural Resources and US Fish and Wildlife Service. We thank numerous
graduate students (C. Camacho, C. Sullivan, A. Matthews, and N.
Tillotson) and technicians that spent countless hours assisting with
larval fish sample collection and processing.

\textbf{Abstract:} The Upper Mississippi River (UMR) represents one
invasion front to bigheaded carps \emph{Hypopthalmichthys} spp. in North
America. Agencies often sample larvae to determine the conditions that
bigheaded carp reproduction occurs, but the ability for conventional
ichthyoplankton sampling to detect bigheaded carp reproduction compared
to native fish is unknown. We used occupancy models to estimate larval
bigheaded carp and native fish larvae detection probabilities and
assessed how habitat type, Julian date, river discharge, and water
temperature affect occupancy. We sampled larvae in pools 18-20 of the
UMR every two weeks at the Iowa, Skunk, and Des Moines River confluences
in backwater, side channel, and thalweg habitats. Detection
probabilities increased with water volume filtered and was lower for
larval bigheaded carp than freshwater drum, gizzard shad, and percids.
Freshwater drum and bigheaded carp larvae had higher detection in
thalweg and channel border habitats compared to backwaters. Occupancy of
bigheaded carp peaked on June 19\textsuperscript{th} at 20\selectlanguage{ngerman}°C, increased
with discharge, and declined with coefficient of variation (CV) of water
temperature and discharge. Gizzard shad and percids occupancy peaked on
May 24\textsuperscript{th} and increased with CV of water temperature
while occupancy of freshwater drum peaked on July 3\textsuperscript{rd},
decreased with CV of water temperature, and increased with water
temperature. Our results indicate bigheaded carp are more difficult to
detect than native larvae and identified conditions associated with
larval occupancy that can be used to maximize detection and better
understand when, where, and under what conditions larvae are present
while accounting for imperfect detection.

Key Words: ichthyoplankton, Silver Carp, Bighead Carp, Freshwater Drum,
Gizzard Shad, percids, distribution models, sampling efficiency

\textbf{1 \textbar{} INTRODUCTION}

Aquatic invasions have become common and are one of the greatest threats
to aquatic ecosystems worldwide ( Alexander et al., 2015; Gherardi,
2007; Sala et al., 2000) by altering nutrient cycling (Vanni, 2021),
food webs (DeBoer et al., 2018), and abundance and distribution of
native species (Gallardo et al., 2016; Weber \& Brown, 2011). Currently,
bigheaded carps (\emph{Hypothalmichthys moltrix}
and\emph{Hypopthalmichthys nobilis} ) are some of the most problematic
aquatic invasive species that have spread rapidly and broadly in North
America with adverse ecosystem effects (DeBoer et al., 2018; Solomon et
al., 2016; Tillotson et al., 2022). Pelagic planktivores native to China
and a small portion of eastern Russia (Kolar et al., 2007), bigheaded
carp were introduced to the United States for aquaculture and sewage
treatment resulting in their eventual escapement to natural waters where
populations rapidly increased (Kolar et al., 2005). Since their initial
escapement in the early 1980s, the Mississippi River has served as an
invasion highway throughout the central United States. The Upper
Mississippi River (UMR) is currently one of the primary invasion fronts
for bigheaded carp in the Midwestern United States due to a series of
locks and dams that have slowed their upstream expansion (Fritts et al.,
2021; Tripp et al., 2013; Whitledge et al., 2019). Lock and Dam 19
specifically represents a major barrier to their northern expansion (
Larson et al., 2017; Fritts et al., 2021; Tripp et al., 2013), although
adults have been captured as far north as pool 2 (U.S. Geological
Survey, 2022).

While adult bigheaded carp have been captured up to pool 2, reproduction
has only been documented to pool 16 (Camacho et al., 2023; Larson et
al., 2017). Fish reproductive phenology is the product of many
environmental conditions (Krabbenhoft et al., 2014; Yang et al. 2021)
and quantifying fish reproduction provides critical temporal, spatial,
population, and community metrics in relation to environmental
conditions (Pritt et al., 2015; Quist et al. 2004). Seasonality in
concert with water temperature is often considered necessary for
successful reproduction by triggering the release of gametes (Pankhurst
\& Porter, 2003; Werner, 2002). Bigheaded carp require water
temperatures \textgreater{} 17°C to initiate reproduction, with
reproductive activity occurring up to 30°C (DeGrandchamp et al., 2007;
Kocovsky et al., 2012; Schrank et al., 2001). Alternatively,
reproduction of native fishes is generally initiated at cooler
temperatures and occurs over a more narrow range (e.g.,
walleye\emph{Sander vitreus} , 5 to 10°C; Bozek et al., 2011; gizzard
shad\emph{Dorosoma cepedianum} , 10 to 21°C; Becker, 1983; freshwater
drum\emph{Aplodinotus grunniens} , 18 to 25°C; Swedberg and Walburg,
1970). Beyond temperature, changing river discharge strongly affects
reproductive activity in many invasive and native lotic fishes
(Humphries et al., 2002; King et al., 2016; Dudley \& Platania, 2007)
including bigheaded carp (e.g., Kolar et al., 2007; Schrank et al.,
2001).

Beyond environmental conditions, spatial variation in riverine habitats
can influence where invasive and native fish reproduce (Camacho et al.,
2023; Kolar et al., 2007). In rivers, spawning habitat relates to
channel position such as channel border, thalweg, and backwaters due to
differences in river discharge and species spawning requirements. Larval
habitat use often corresponds to their reproductive guild (Holland,
1986). Some species such as bigheaded carp and freshwater drum spawn in
the open water environments of the thalweg where eggs passively drift
until they hatch and reach sizes that allow increased mobility to escape
the current (Becker, 1983). Other species reproduce in the lower
velocities in channel borders and backwaters that provide cover for eggs
and developing larvae (e.g., walleye) or passively drift downstream
(e.g., gizzard shad; Holland, 1986; Simon, 1998). Consequently, while
most lotic larval fish assessments focus on thalweg collections, larval
occupancy may vary among taxa and habitats.

Given the network of environmental conditions for fish reproduction,
along with the uncertainty of ichthyoplankton sampling, determining
occurrence of riverine fish reproductive events can be difficult. High
spatio-temporal variability in larval catches is common (Cyr et al.,
1992; Leonardsson et al., 2016; Michaletz \& Gale, 1999; Weber et al.,
2021). Therefore, it is difficult to determine when, where, and under
what conditions fish reproduction occurs, particularly when detection
probability is imperfect. Additionally, adult bigheaded carps are
difficult to capture compared to adult native fishes (Bouska et al.,
2017), but whether or not differences in sampling efficiency also exist
at the larval phase is unknown. Occupancy (\selectlanguage{greek}Ψ\selectlanguage{english}) and detection (\emph{p} )
modeling offers a quantitative method of estimating the true presence of
species in a system by accounting for imperfect detections based on
discrete encounters over temporal or spatial scales (MacKenzie et al.,
2002). Within fisheries, occupancy and detection modeling has been
primarily used to describe distribution of adult fishes (Potoka et al.,
2016; Schumann et al., 2020; Sullivan et al., 2018;), but models are
plastic and have been adapted to evaluate age-0 fish habitat use
(Burdick et al., 2008; Falke et al., 2010, 2012), timing of reproduction
events associated with environmental conditions (Falke et al., 2010;
Peoples and Frimpong, 2011; Pritt et al., 2014), and recruitment of
cryptic invaders (Weber \& Brown, 2019). These models also provide
sample size requirements to achieve desired detection probabilities,
improving sampling designs and monitoring programs (Kelly et al., 2021;
Kuehne \& Olden, 2016; Rodtka et al., 2015). Consequently, occupancy
models can serve as a useful tool for assessing reproductive dynamics of
bigheaded carp along leading edges of invasion where reproduction may be
limited, and spawning events can be brief and difficult to detect.

Our objectives were to estimate occupancy and detection probability of
bigheaded carp larvae and native fish taxa in relation to spatial and
environmental variation. Next, we quantified cumulative detection
probabilities to estimate sampling effort required to detect bigheaded
carp larvae compared to native species. First, we hypothesized bigheaded
carp larval occupancy would be higher in the thalweg compared to other
habitats and positively related to water temperature and river
discharge. Second, we hypothesized bigheaded carp larval occupancy would
be lower than native fishes and lower in Mississippi River pools along
the leading edge of population expansion than already established native
fish populations. Finally, we hypothesized larval detection
probabilities would be lower for bigheaded carp than native taxa.

\textbf{2 \textbar{} METHODS}

\textbf{2.1 \textbar{} Study Area}

The Upper Mississippi River extends from the Mississippi River
headwaters in Minnesota to its confluence with the Missouri River just
north of St. Louis, MO. This portion of the river is impounded by 29
locks and dams and highly channelized to allow for barge traffic. Our
study focuses on pools 18 to 20 from just upstream of the Iowa River
confluence to just downstream of the Des Moines River confluence (Figure
1). Along this reach, there are three main tributaries: the Iowa River
on pool 18, the Skunk River on pool 19, and the Des Moines River on pool
20 (Figure 1). These locations represent the furthest upstream extent of
most bigheaded carp reproduction in the Upper Mississippi River (Camacho
et al., 2023; La Hood et al., 2023; Larson et al., 2017), with some
evidence of reproduction up to Pool 16 (Larson et al., 2017).

\textbf{2.2 \textbar{} Ichthyoplankton Sampling}

We collected ichthyoplankton samples every 10 days during daylight hours
from late April to September in 2014 to 2018. Sites were located 1 km
upstream and downstream and at the confluence of each tributary for a
total of nine sample locations (Figure 1). Each site consisted of three
tows, one at each different habitat types including a backwater,
thalweg, and channel border. We used ichthyoplankton tows (0.5 m
diameter, 2.5 m length, and 500 \selectlanguage{greek}µ\selectlanguage{english}m mesh net) to collect larval fishes by
conducting tows parallel to the flow at speeds to maintain no upstream
or downstream movement for a total of four minutes. We preserved larval
samples in 95\% ethanol and recorded water flow through each net using a
General Oceanics 2030R flowmeter mounted at the mouth of the
ichthyoplankton net which we used to calculate water volume
(m\textsuperscript{3}) filtered through the net. Across all sites and
years, we collected a total of 1,776 ichthyoplankton samples.

In the laboratory, we sorted and cleared ichthyoplankton samples from
debris with a minimum of two different individuals until no further
larvae were found. We identified larvae to the lowest taxonomic level
possible with visual identification using techniques described by Auer
(1982) and Chapman (2006). We identified larval fishes (ventral
fin-folds present) to family apart from certain taxa such as bigheaded
carp and freshwater drum that could be identified down to genus or
species. We selected bigheaded carp, freshwater drum, gizzard shad, and
Percidae for analysis due to variable reproductive strategies and
frequency of occurrence in our samples. We were only able to visually
identify larvae down to family Clupeidae, but are referenced as `shad'
hereafter, as gizzard shad are the dominant taxa found in the study
reach. Bigheaded carp and drum are both pelagic broadcast spawners while
shad and percids tend to spawn in lower water velocity environments of
channel borders and backwaters (Kolar et al., 2007; Holland 1986). Shad
and percids tend to spawn earlier during cooler water temperatures,
bigheaded carps tend to spawn later in the year during warmer water
temperatures, and freshwater drum spawning tends to be protracted across
a broad range of water temperatures (Becker, 1983; Bozek et al., 2011;
Kocovsky et al., 2012; Swedberg \& Walburg, 1970).

\textbf{2.3 \textbar{} Environmental Data}

We collected temporal, hydrological, and thermal conditions associated
with each ichthyoplankton sample. We used Julian date to account for
temporal variation in larval fish presence based on seasonal variation
in spawning for each taxon, regardless of environmental conditions.
Next, we acquired hydrological data from United States Geological Survey
and United States Army Corps of Engineers gauging stations nearest each
site (Supplemental data). We calculated average weekly river discharge
(m\textsuperscript{3}/s) and coefficient of variation (CV) of each
sample to estimate the magnitude and variability in hydrological
conditions prior to sampling. Finally, we calculated average and CV of
weekly river temperature (\selectlanguage{ngerman}°C) using linear regression for each tributary
based on field water temperature observations compared to gauging
station values (Supplemental data).

\textbf{2.4 \textbar{} Statistical Analysis}

We developed occupancy and detection models using Program MARK
accounting for imperfect detection (MacKenzie et al., 2002). There are
four main assumptions for occupancy and detection modeling (MacKenzie et
al., 2018). First, we assume populations are closed; our sampling on a
day and at the three sites associated with a tributary (nine
ichthyoplankton tows) all occurred within an hour to meet the assumption
of no births, deaths, immigration, or emigration during a sampling
event. The next assumption states occupancy and detection probabilities
are constant among sites or that heterogeneity in these parameters is
accounted for using covariates; we used spatial and environmental
covariates to account for spatial and temporal heterogeneity of both
parameters. The third assumption is detection histories are independent
among sites; we accounted for this assumption through temporal
replication where we sampled every 10 d and larvae were \textless{} 7 d
old (Camacho et al., 2023; M. Weber, unpublished data), ensuring we did
not repetitively sample the same larval across multiple sampling events.
Finally, the model assumes no false positive detections; we selected
taxa that had low ambiguity in visual identification and genetically
identified a subset of bigheaded carp larvae to verify identification
accuracy (see Camacho et al., 2023 for more details).

We developed encounter histories for each larval taxon and sample date
as presence/absence (0 or 1) at each site upstream, downstream, or at
the confluence of the major tributary. For example, an encounter history
could be comprised of bigheaded carp only collected at the Des Moines
River confluence and not at upstream or downstream locations (encounter
history 010) or upstream and downstream but not within the confluence
(encounter history 101). Occupancy modeling allows the use of covariates
to improve model estimates and evaluate occupancy and detection under a
range of environmental conditions. We assessed the effect of water
volume filtered through the ichthyoplankton net as an effect of sampling
effort on detection probability. We also assessed the effects of Julian
date, mean and CV of weekly water temperature (°C), and discharge
(m\textsuperscript{3}/s) on site occupancy. We evaluated collinearity of
covariates with a Pearson's product-moment correlation analysis (all r
\textless{} 0.6) before including them in occupancy and detection
models. To ensure normality, we centered and scaled all covariates using
z-scores prior to analysis. We assessed quadratic effects of Julian date
and weekly river temperature on occupancy probability, as we sampled
prior to and after hypothesized peak spawning periods and linear models
would be inappropriate. We assessed all other covariates as linear
effects. We assessed detection models by first comparing species and
habitat models before adding additional effects of environmental
covariates. Next, we retained the most supported detection model to
evaluate species and habitat effects on occupancy. Finally, we assessed
potential effects of environmental covariates on occupancy while
retaining the most supported species and habitat effects. We ranked
models based on Akaike's Information Criterion corrected for sample size
(\selectlanguage{greek}Δ\selectlanguage{english}AIC\emph{\textsubscript{c}} ) and AIC\emph{\textsubscript{c}} model
weight (\emph{w\textsubscript{i}} ; Burnham et al., 2011). We considered
models ranked [?] 2 \selectlanguage{greek}Δ\selectlanguage{english}AIC\emph{\textsubscript{c}} from the top model as
competitive in analyses. Finally, we calculated detection probabilities
under increasing sampling size (cumulative detection probability) using
the most supported detection model (e.g., Kelly et al., 2021).

\textbf{3 \textbar{} RESULTS}

We collected bigheaded carp larvae in pools 18 to 20 of the Mississippi
River in 53 of 592 sample site-years (na\selectlanguage{ngerman}ïve \selectlanguage{greek}Ψ \selectlanguage{english}= 0.09). Native larvae
were captured more frequently, with freshwater drum (n = 223 of 592
site-years; na\selectlanguage{ngerman}ïve \selectlanguage{greek}Ψ \selectlanguage{english}= 0.38) captured most frequently followed by shad (n
= 141 of 592 site-years; na\selectlanguage{ngerman}ïve \selectlanguage{greek}Ψ \selectlanguage{english}= 0.24) and percids (n = 132 of 592
site-years; na\selectlanguage{ngerman}ïve \selectlanguage{greek}Ψ \selectlanguage{english}= 0.22). Thalweg and channel border habitats
accounted for the most bigheaded carp (77\%) and drum (78\%) collections
while shad and percids had similar overall collections among habitats
(29 to 36\%). We captured the most bigheaded carp between Julian days
138 to 240 when water temperatures ranged from 17.6 to 26.6\selectlanguage{ngerman}°C and during
the highest weekly discharge conditions (mean = 4,124
m\textsuperscript{3}/s, SD = 1,057). We captured percids the earliest
(day 113) during the narrowest time (range = 113 to 228, mean = 160, SD
= 32), coldest temperatures (mean = 19.9°C, SD = 5), and second highest
weekly discharge (mean = 3,629 m\textsuperscript{3}/s, SD = 1,251). We
captured freshwater drum the latest (day 256) across the widest range of
days (range = 122 to 256, mean = 189, SD = 33) associated with highest
weekly temperatures (mean = 23.4 °C, SD = 2.9) and lower discharge (mean
= 3,321 m\textsuperscript{3}/s, SD = 1,061). Finally, we collected shad
on a similar time frame as freshwater drum (range = 120 to 256, mean =
174, SD = 29), with similar water temperature to bigheaded carp (range =
15.1 to 27.7°C, mean = 22.2 °C, SD = 3), under similar discharge
conditions to percids (mean = 3,587 m\textsuperscript{3}/s, SD = 1,100).

\textbf{3.1 \textbar{} Detection Models}

Our most supported detection probability model while assessing taxa
effects indicated differences in bigheaded carp and freshwater drum
detections while shad and percids had similar detection
(\selectlanguage{greek}Δ\selectlanguage{english}AIC\textsubscript{\emph{c}} = 0.00, \emph{w\textsubscript{i}} = 0.69;
Table 1). The second ranked model with each taxonomic group estimated
separately also received support (\selectlanguage{greek}Δ\selectlanguage{english}AIC\emph{\textsubscript{c}} =
1.62,\emph{w\textsubscript{i}} = 0.31; Table 1). Next, we assessed
potential variation in detection probability for taxa among habitats.
Our most supported model indicated detection of bigheaded carp and
freshwater drum was similar between thalweg and channel border habitats
combined that had different detection compared to backwater habitats
(\selectlanguage{greek}Δ\selectlanguage{english}AIC\textsubscript{\emph{c}} = 0.00, \emph{w\textsubscript{i}} = 0.33;
Table 1). In contrast, detection probability was similar among habitats
for shad and percids (Table 1). Other model combinations receiving
support include thalweg and channel border habitats combined for all
taxa (\selectlanguage{greek}Δ\selectlanguage{english}AIC\textsubscript{\emph{c}} = 1.20, \emph{w\textsubscript{i}} =
0.18) and all habitats separate for carp and freshwater drum
(\selectlanguage{greek}Δ\selectlanguage{english}AIC\textsubscript{\emph{c}} = 1.29, \emph{w\textsubscript{i}} = 0.17;
Table 1). The final step of detection model selection was assessing the
effect of water volume filtered (i.e., sampling effort) to the top taxa
model. The addition of water volume filtered to all taxa
(\selectlanguage{greek}Δ\selectlanguage{english}AIC\emph{\textsubscript{c}} =0.00,\emph{w\textsubscript{i}} = 0.35;
Table 1) was the most supported model, whereas water volume filtered
applied to only bigheaded carp and shad and percids
(\selectlanguage{greek}Δ\selectlanguage{english}AIC\textsubscript{\emph{c}} = 1.48,\emph{w\textsubscript{i}} = 0.17)
or only to drum and shad/percids (\selectlanguage{greek}Δ\selectlanguage{english}AIC\textsubscript{\emph{c}} = 2.00,
\emph{w\textsubscript{i}} = 0.33; Table 1) were also considered
competitive models.

The most supported model estimated bigheaded carp detection
probabilities higher in the thalweg and channel border habitat
(\emph{p}= 0.15, 95\% CI = 0.09 to 0.22) than in the backwater (\emph{p}
= 0.09, 95\% CI = 0.05 to 0.17), but estimates had overlapping
confidence intervals (Figure 2). Drum detection probability was also
higher in the thalweg and channel border (\emph{p} = 0.40, 95\% CI =
0.35 to 0.45) compared to the backwater (\emph{p} = 0.20, 95\% CI = 0.15
to 0.26) while shad and percid detection probability was similar across
all three habitats (\emph{p} = 0.27, 95\% CI = 0.23 to 0.31; Figure 2).
Detection of bigheaded carp within each habitat tended to be lower than
native fishes (Figure 2). Water volume filtered had a positive effect on
detection estimates for all taxa/habitat combinations (\selectlanguage{greek}β \selectlanguage{english}= 0.12, 95\% CI
= 0.01 to 0.23) where detection probability of bigheaded carp increased
from 0.15 to 0.48, detection of freshwater drum increased from 0.34 to
0.77, and detection of shad and percids increased from 0.24 to 0.34 as
water volume filtered increased from 30 m\textsuperscript{3} to 50
m\textsuperscript{3} (Figure 3).

Differences in detection probabilities among taxa resulted in
differences in cumulative detection curves and the number of
ichthyoplankton samples needed to detect each taxonomic group. Under the
average water volume filtered (30.12 m\textsuperscript{3}), bigheaded
carp required the most ichthyoplankton samples (25 backwater or 14
thalweg/channel border) to reach a 90\% detection probability, 1.4 to 5
times as many samples as native taxa (Figure 4). Freshwater drum
required 5 to 10 samples and shad/percids required 8 samples to reach a
90\% probability of detection. By increasing the water volume filtered
to 40 m\textsuperscript{3} we observed a 60\% to 108\% decrease in the
samples required to achieve a 90\% detection probability compared to the
average sample volume (9 to 15 samples for bigheaded carp, 4 to 8
samples for freshwater drum, and 7 samples for shad and percids (Figure
4).

\textbf{3.2 \textbar{} Occupancy Models}

We retained the most supported detection probability model structure for
each taxa when assessing various larval fish occupancy model
combinations. Similar to detection models, the combination of shad and
percids, with carp and freshwater drum occupancy estimated separately,
received the most support (\selectlanguage{greek}Δ\selectlanguage{english}AIC\emph{\textsubscript{c}} =
0.00,\emph{w\textsubscript{i}} = 0.44; Table 2). Other likely
combinations include all taxa estimated separately
(\selectlanguage{greek}Δ\selectlanguage{english}AIC\emph{\textsubscript{c}} = 1.63, \emph{w\textsubscript{i}} = 0.20)
and freshwater drum estimated separately from bigheaded carp, shad, and
percids (\selectlanguage{greek}Δ\selectlanguage{english}AIC\emph{\textsubscript{c}} = 1.78, \emph{w\textsubscript{i}}
= 0.18; Table 2). Through the addition of habitat to this taxa model
structure, the most supported model included backwater estimated
separately and thalweg combined with channel border habitats for shad
and percids (\selectlanguage{greek}Δ\selectlanguage{english}AIC\emph{\textsubscript{c}} = 0.00,
\emph{w\textsubscript{i}} = 0.21; Table 2). Two of the six top and
competitive model structures incorporated this habitat grouping among
different taxa (Table 2). Finally, we added environmental covariates to
determine the combination that best improved the taxa \selectlanguage{ngerman}× habitat model.
The most supported taxa × habitat × environmental covariate model
(\selectlanguage{greek}Δ\selectlanguage{english}AIC\emph{\textsubscript{c}} = 0.00, \emph{w\textsubscript{i}} = 0.69)
incorporated Julian date and CV temperature for all taxa with the added
effect of temperature on bigheaded carp and freshwater drum (Table 2).
Bigheaded carp were the only taxonomic group to retain both discharge
and CV discharge in the top model (Table 2).

Freshwater drum occupancy among all habitats (\selectlanguage{greek}Ψ \selectlanguage{english}= 0.84, 95\% CI = 0.73
to 0.91) was higher than bigheaded carp (\selectlanguage{greek}Ψ \selectlanguage{english}= 0.29, 95\% CI = 0.15 to
0.47) and shad and percids in backwaters (\selectlanguage{greek}Ψ \selectlanguage{english}= 0.53, 95\% CI = 0.41 to
0.66) or thalweg/channel border (\selectlanguage{greek}Ψ \selectlanguage{english}= 0.42, 95\% CI = 0.34 to 0.51).
Julian day had a quadratic effect on occupancy probability for all taxa:
shad and percids occupancy was highest on day 144 (May
24\textsuperscript{th}) followed by bigheaded carp on day 170 (June
19\textsuperscript{th}) and freshwater drum on day 184 (July
3\textsuperscript{rd}; Figure 5). Bigheaded carp (\selectlanguage{greek}β \selectlanguage{english}= -0.63, 95\% CI =
-1.03 to -0.23) and freshwater drum (\selectlanguage{greek}β \selectlanguage{english}= -0.89, 95\% CI = -1.24 to
-0.55) occupancy declined with increased variation in weekly water
temperature while shad and percids occupancy increased with increasing
water temperature CV (\selectlanguage{greek}β \selectlanguage{english}= 0.33, 95\% CI = 0.16 to 0.51; Figure 5).
Weekly water temperatures also had a quadratic effect on occupancy of
bigheaded carp and freshwater drum: bigheaded carp occupancy was highest
at 20.7\selectlanguage{ngerman}°C and drum was highest at 23.9°C (Figure 5). Bigheaded carp
occupancy was also positively related to mean weekly discharge (\selectlanguage{greek}β \selectlanguage{english}=
1.29, 95\% CI = 0.19 to 2.39) whereas the slope estimate of CV discharge
incorporated zero (\selectlanguage{greek}β \selectlanguage{english}= -0.01, 95\% CI = -0.35 to 0.36; Figure 5).

\textbf{4 \textbar{} DISCUSSION}

Our study demonstrates differences in our ability to detect invasive and
native larval fish presence accounting for various environmental
conditions. Detection probabilities for bigheaded carp were lower than
native taxa and required more samples to detect their presence.
Detection probability estimates increased with water volume filtered for
all species, but detection also varied among habitats for carp and
freshwater drum, indicating spatial differences in sampling efficiency.
Similar to detection, bigheaded carp occupancy was generally lower than
native species, suggesting they have a narrower range of environmental
conditions suitable for reproduction. Temporal and thermal environmental
covariates improved occupancy probabilities among all species, while
hydrological covariates were only beneficial to bigheaded carp
occupancy.

Occupancy and detection models indicate some habitat separation among
taxa. On average, bigheaded carp and drum detection probabilities were
higher in thalweg and channel border habitats, whereas detection
probability of shad and freshwater drum was similar among habitats.
Pelagophil fishes, such as bigheaded carp and drum, reproduce in open
water conditions (Balon, 1975; Welcomme et al., 2006) associated with
the higher velocity thalweg and channel border river channel habitats.
Larval fishes in these habitats are likely younger and passively
drifting with the current (Holland, 1986), potentially making them
easier to capture. Alternatively, larval bigheaded carp can migrate out
of the main channel to areas with lower velocity at 5 to 6 days of age
and larger, more developed larvae that are better swimmers may be more
likely to avoid the ichthyoplankton net (Chapman and George, 2011; Roth
et al., 2023). In contrast to detection, occupancy of carp and
freshwater drum was similar among habitats, suggesting that all habitats
are used by larval carp and drum. Thus, if the objective is to simply
document bigheaded carp reproductive success, focusing sampling efforts
in the thalweg would be more efficient. Alternatively, shad and percid
detection was similar among habitats but occupancy was higher in
backwater habitats than thalweg and channel borders, consistent with
conventional reproductive guild classification for both shad
(litho-pelagophil) and percids (lithophil; Simon, 1998). While not
directly considered in this study, larval habitat selection can change
during later developmental stages due to gas bladder inflation and
increased horizontal mobility (Chapman and George, 2011). While we
limited our occupancy and detection models to sub-juvenile stages, there
may exist occupancy and detection habitat variation among sizes, ages,
and developmental stages due to changes in mobility.

Native and invasive larval occupancy both varied temporally and were
influenced by environmental conditions. Bigheaded carp reproduce in
rivers during May through June when water temperatures exceed 17\selectlanguage{ngerman}°C, with
peak reproduction occurring at 22 to 26°C (Schrank et al., 2001), though
protracted spawning documented into the fall can occur in some systems
(Coulter et al., 2013; Papoulias et al., 2006). Freshwater drum
typically spawn between May and June in the Upper Mississippi River
(Butler, 1965) when water temperatures are between 18 to 25°C (Swedberg
\& Walburg, 1970). Shad spawn over a broad temporal window with
reproduction occurring from late April into early August with water
temperatures between 10 to 21°C (Becker, 1983), whereas
percids\emph{,}such as walleye, spawn the earliest from late April to
early May with water temperatures ranging from 5 to 10°C (Becker, 1983;
Bozek et al., 2011). Similarly, we found maximum occupancy estimates
corresponded with Julian dates for bigheaded carp (June
19\textsuperscript{th}), freshwater drum (July 3\textsuperscript{rd}),
and shad and percids (May 24\textsuperscript{th}) that were typically at
the upper limits of their documented spawning periods. This trend was
mirrored in maximum occupancy occurring from freshwater drum when water
temperatures was 23.9°C, whereas the water temperature for carp (20.7°C)
was well within their recorded temperature limits and even lower than
the cited temperature range for peak reproduction (22-26°C; Schrank et
al., 2001). Maximum bigheaded carp occupancy in the Upper Mississippi
River occurring below the peak reproduction threshold is likely due to
stability of water temperatures in this region throughout our sampling
period (mean water temperature of 22°C from April to August). In
addition to mean temperature, increasing temperature variation led to
lower occupancy probabilities for carp and drum, but an increase in
occupancy probability for shad/percids. Fluctuations in water
temperature can negatively influence bigheaded carp reproduction due to
disruption in oogenesis (Majdoubi et al., 2022) and can reduce egg
viability of other fishes (Van Der Kraak \& Pankhurst, 2011), indicating
post-spawning temperature stability could promote larval survival.

Larval occupancy among taxonomic groups was primarily affected by
temporal and thermal variation; however, bigheaded carp occupancy also
increased with mean river discharge and may have been negatively
affected by variability in discharge. Discharge and water temperature
are central catalysts of bigheaded carp reproduction (Camacho et al.,
2023; Kolar et al., 2007; Lohmeyer \& Garvey, 2009; Schrank et al.,
2001). Adult bigheaded carp move upstream in spring with increasing
discharge and spawn during peak flows when water temperature exceeds
17°C (DeGrandchamp et al., 2007; Kocovsky et al., 2012; Schrank et al.,
2001). Effects of variation in discharge on bigheaded carp reproduction
are less understood. With increasing variation in discharge, our models
suggested a slight negative effect on bigheaded carp larval occupancy,
although the slope overlapped zero. Schaick et al., (2023) observed a
similar relationship between larval bigheaded carp densities and
variable discharge and theorized sustained, high magnitude discharged
events were preferred for bigheaded carp reproduction. While discharge
is also often cited as a major driver of reproduction for lotic fishes
(Dudley \& Platania, 2007; King et al., 2016; Humphries et al., 2002),
we did not find an effect of discharge on native larval fish occupancy,
potentially because peaks in discharge were not synchronized with
appropriate spawning temperatures or because native taxa are more
adapted to flow regimes (Lytle \& Poff, 2004). Alternatively, discharge
may not affect the occurrence of reproduction (e.g., occupancy), but
could affect the magnitude of reproduction (e.g., larval densities) and
still be responsible for large versus small year-classes (Weber et al.,
2021).

Understanding when, where, and under what conditions larval fishes are
present is strongly dependent on successfully capturing them given they
occur at a site. Drum, shad, and percids had higher detection
probabilities than bigheaded carp. Adult bigheaded carp are difficult to
capture (Bouska et al., 2017; Collins et al., 2015), but our results are
the first to document challenges associated with lower capture success
of invasive larvae compared to native taxa. Low detection of bigheaded
carp larvae can make it difficult to document reproductive events,
particularly along invasion fronts, resulting in misinformed population
status assessments with implications for management decisions. For
instance, efforts are underway in the Upper Mississippi River to install
barriers to slow or stop adult upstream movements into areas where
reproduction has not yet been documented. Sampling effort strongly
influenced our ability to detect larval fishes, but effects varied among
taxa. Biologists can improve larval detection probabilities by 1)
focusing sampling in the thalweg, 2) increasing the water volume
filtered per tow, and 3) increasing the number of tows collected per
site visit. While we collected three tows per site visit, cumulative
detection curves indicated we would need to collect 14 thalweg/channel
border samples to achieve 90\% detection probability of bigheaded carp
larvae. Alternatively, increasing the water volume filtered by 33\%
would reduce the sample size to 9 thalweg/channel border tows. These
results provide an adaptable and flexible framework to determine how
many samples to collect and how much water to filter based on river
conditions (e.g., debris load) and acceptable uncertainty in bigheaded
carp presence. Further, sampling could also be adjusted to determine
successful reproduction through targeted sampling based on habitat,
temporal, thermal, and hydrological effects on occupancy to optimize
future sampling to assess reproduction of cryptic invaders.

\textbf{DATA AVAILABILITY STATEMENT}

The data that support the findings of this study are available from the
corresponding author upon reasonable request.

\textbf{REFERENCES}

Alexander, M.E., Kaiser, H., Weyl, O.L.F., and Dick, J.T.A. 2015.
Habitat simplification increases the impact of a freshwater invasive
fish. Environ. Biol. Fishes \textbf{98} (2): 477--486.
doi:10.1007/s10641-014-0278-z.

Auer, N.A. 1982. Identification of larval fishes of the Great Lakes
Basin with emphasis on the Lake Michigan drainage. Great Lakes Fisheries
Commision, Special publication 82-3, Ann Arbor, Michigan.

Balon, E.K. 1975. Reproductive guilds of fishes: A proposal and
definition. J. Fish. Board Canada \textbf{32} (6): 821--864.
doi:10.1139/f75-110.

Becker, G.C. 1983. Fishes of Wisconsin. The University of Wisconsin
Press, Madison. doi:10.2307/1445079.

Bouska, W.W., Glover, D.C., Bouska, K.L., and Garvey, J.E. 2017. A
refined electrofishing technique for collecting Silver Carp:
implications for management. North Am. J. Fish. Manag. \textbf{37} (1):
101--107. doi:10.1080/02755947.2016.1240122.

Bozek, M., Baccante, D., and Lester, N. 2011. Walleye and sauger life
history. \emph{In} Biology, Management, and Culture of Walleye and
Sauger. \emph{Edited by} B.A. Barton. American Fisheries Society,
Bethesda, MD. pp. 233--301. doi:10.47886/9781934874226.

Burdick, S.M., Hendrixson, H.A., and VanderKooi, S.P. 2008. Age\selectlanguage{english}-0 Lost
River sucker and shortnose sucker nearshore habitat use in Upper Klamath
Lake, Oregon: a patch occupancy approach. Trans. Am. Fish.
Soc.\textbf{137} (2): 417--430. doi:10.1577/t07-072.1.

Burnham, K.P., Anderson, D.R., and Huyvaert, K.P. 2011. AIC model
selection and multimodel inference in behavioral ecology: some
background, observations, and comparisons. Behav. Ecol.
Sociobiol.\textbf{65} : 23--35. doi:10.1007/s00265-010-1029-6.

Butler, R.L. 1965. Freshwater drum, \emph{Aplodinotus grunniens} , in
the navigational impoundments of the Upper Mississippi River. Trans. Am.
Fish. Soc. \textbf{94} (4): 339--349.
doi:10.1577/1548-8659(1965)94{[}339:FDAGIT{]}2.0.CO;2.

Camacho, C.A., Sullivan, C.J., Weber, M.J., and Pierce, C.L. 2023.
Invasive carp reproduction phenology in tributaries of the Upper
Mississippi River. North Am. J. Fish. Manag. \textbf{43} (1): 61-80
doi:10.1002/nafm.10499.

Chapman, D.C. 2006. Early development of four cyprinids native to the
Yangtze River, China. U.S. Geol. Surv. Data Ser. 239: 51. Available from
https://pubs.er.usgs.gov/publication/ds239.

Collins, S.F., Butler, S.E., Diana, M.J., and Wahl, D.H. 2015. Catch
rates and cost effectiveness of entrapment gears for Asian carp: a
comparison of pound nets, hoop nets, and fyke nets in backwater lakes of
the Illinois River. North Am. J. Fish. Manag. \textbf{35} (6):
1219--1225. doi:10.1080/02755947.2015.1091799.

Coulter, A.A., Keller, D., Amberg, J.J., Bailey, E.J., and Goforth, R.R.
2013. Phenotypic plasticity in the spawning traits of bigheaded carp
(\emph{Hypophthalmichthys} spp.) in novel ecosystems. Freshw.
Biol.\textbf{58} (5): 1029--1037. doi:10.1111/fwb.12106.

Cyr, H., Downing, J.A., Lalonde, S., Baines, S.B., and Pace, M.L. 1992.
Sampling larval fish populations: choice of sample number and size.
Trans. Am. Fish. Soc. \textbf{121} (3): 356--368.
doi:10.1577/1548-8659(1992)121\textless{}0356:SLFPCO\textgreater{}2.3.CO;2.

DeBoer, J.A., Anderson, A.M., and Casper, A.F. 2018. Multi-trophic
response to invasive silver carp (\emph{Hypophthalmichthys molitrix} )
in a large floodplain river. Freshw. Biol. \textbf{63} (6): 597--611.
doi:10.1111/FWB.13097.

DeGrandchamp, K.L., Garvey, J.E., and Csoboth, L.A. 2007. Linking adult
reproduction and larval density of invasive carp in a large river.
Trans. Am. Fish. Soc. \textbf{136} (5): 1327--1334.
doi:10.1577/t06-233.1.

Dudley, R.K., and Platania, S.P. 2007. Flow regulation and fragmentation
imperil pelagic-spawning riverine fishes. Ecol. Appl. \textbf{17} (7):
2074--2086. doi:10.1890/06-1252.1

Falke, J.A., Bailey, L.L., Fausch, K.D., and Bestgen, K.R. 2012.
Colonization and extinction in dynamic habitats: an occupancy approach
for a Great Plains stream fish assemblage. Ecology \textbf{93} (4):
858--867. doi:10.1890/11-1515.1.

Falke, J.A., Fausch, K.D., Bestgen, K.R., and Bailey, L.L. 2010.
Spawning phenology and habitat use in a great plains, USA, stream fish
assemblage: an occupancy estimation approach. Can. J. Fish. Aquat.
Sci.\textbf{67} (12): 1942--1956. doi:10.1139/F10-109.

Fritts, A.K., Knights, B.C., Stanton, J.C., Milde, A.S., Vallazza, J.M.,
Brey, M.K., Tripp, S.J., Devine, T.E., Sleeper, W., Lamer, J.T., and
Mosel, K.J. 2021. Lock operations influence upstream passages of
invasive and native fishes at a Mississippi River high-head dam. Biol.
Invasions \textbf{23} : 771--794. doi:10.1007/s10530-020-02401-7.

Gallardo, B., Clavero, M., Sanchez, M.I., and Vila, M. 2016. Global
ecological impacts of invasive species in aquatic ecosystems. Glob.
Chang. Biol. \textbf{22} (1): 151--163. doi:10.1111/gcb.13004.

Gherardi, F. 2007. Biological invasions in inland waters: an
overview.\emph{In} Biological invaders in inland waters: Profiles,
distribution, and threats. \emph{Edited by} F. Gherardi Springer
Dordrecht, Netherlands. pp. 3--25. doi:10.1007/978-1-4020-6029-8\_1.

Holland, L.E. 1986. Distribution of early life history stages of fishes
in selected pools of the Upper Mississippi River.
Hydrobiologia\textbf{136} : 121--130. doi:10.1007/BF00051509

La Hood, B.M., Thomsen, T.C., Lenaerts, A.W., Tomczak, M.G., Szott,
E.A., Woiak, Z., Von Ruden, K.M., Bockrath, K.D., Irons, K.S., and
Lamer, J.T. 2021. Light trapping reveals multiple bigheaded carp spawns
upstream of lock and dam 19 in the Upper Mississippi River. North Am. J.
Fish. Manag \textbf{43} (1): 81-91. doi:10.1002/nafm.10630.

Humphries, P., Serafini, L.G., and King, A.J. 2002. River regulation and
fish larvae: variation through space and time. Freshw. Biol.\textbf{47}
(7): 1307--1331. doi:10.1046/j.1365-2427.2002.00871.x.

Kelly, B., Siepker, M.J., and Weber, M.J. 2021. Factors associated with
detection and distribution of native brook trout and introduced brown
trout in the Driftless Area of Iowa. Trans. Am. Fish. Soc.\textbf{150}
(3): 388--406. doi:10.1002/tafs.10295.

King, A.J., Gwinn, D.C., Tonkin, Z., Mahoney, J., Raymond, S., and
Beesley, L. 2016. Using abiotic drivers of fish spawning to inform
environmental flow management. J. Appl. Ecol. \textbf{53} (1): 34--43.
doi:10.1111/1365-2664.12542.

Kocovsky, P.M., Chapman, D.C., and McKenna, J.E. 2012. Thermal and
hydrologic suitability of Lake Erie and its major tributaries for
spawning of Asian carps. J. Great Lakes Res. \textbf{38} (1): 159--166.
doi:10.1016/j.jglr.2011.11.015.

Kolar, C.S., Chapman, D.C., Courtenay W.R., Jr., Housel, C.M., Williams,
J.D., and Jennings, D.P. 2005. Asian carps of the
genus\emph{Hypophthalmichthys} (Pisces, Cyprinidae) -- A biological
synopsis and environmental risk assessment. American Fisheries Society
Special Publication 33. Bethesda, Maryland.

Kolar, C.S., Chapman, D.C., Courtenay, W.R., Housel, C.M., Williams,
J.D., and Jennings, D.P. 2007. Bigheaded carps: a biological synopsis
and environmental risk assessment. American Fisheries Society, Bethesda,
Maryland. doi:10.47886/9781888569797.

Van Der Kraak, G., and Pankhurst, N.W. 2011. Temperature effects on the
reproductive performance of fish \emph{in} Global Warming: Implications
for Freshwater and Marine Fish. \emph{Edited by} C.M. Wood and D.G.
McDonald. Cambridge University Press. pp. 159--176.

Krabbenhoft, T.J., Platania, S.P., and Turner, T. 2014. Interannual
variation in reproductive phenology in a riverine fish assemblage:
implications for predicting the effects of climate change and altered
flow regimes. Freshw. Biol. \textbf{59} (8): 1744--1754.
doi:10.1111/fwb.12379.

Kuehne, L.M., and Olden, J.D. 2016. Environmental drivers of occupancy
and detection of olympic mudminnow. Trans. Am. Fish. Soc.\textbf{145}
(1): 17--26. doi: 10.1080/00028487.2015.1091383.

Larson, J.H., Knights, B.C., McCalla, S.G., Monroe, E., Tuttle-Lau, M.,
Chapman, D.C., George, A.E., Vallazza, J.M., and Amberg, J. 2017.
Evidence of Asian carp spawning upstream of a key choke point in the
Mississippi River. North Am. J. Fish. Manag. \textbf{37} (4): 903--919.
doi:10.1080/02755947.2017.1327901.

Leonardsson, K., Hudd, R., Veneranta, L., Huhmarniemi, A., and
Jokikokko, E. 2016. Optimal time and sample allocation for unicohort
fish larvae, sea-spawning whitefish (\emph{Coregonus lavaretus} s. l.)
as a case study. ICES J. Mar. Sci. \textbf{73} (2): 374--383.
doi:10.1093/icesjms/fsv178.

Lohmeyer, A.M., and Garvey, J.E. 2009. Placing the North American
invasion of Asian carp in a spatially explicit context. Biol.
Invasions\textbf{11} (4): 905--916. doi:10.1007/s10530-008-9303-5.

Lytle, D.A., and Poff, N.L. 2004. Adaptation to natural flow regimes.
Trends Ecol. Evol. \textbf{19} (2): 94--100.
doi:10.1016/j.tree.2003.10.002.

MacKenzie, D.I., Nichols, J.D., Lachman, G.B., Droege, S., Royle, A.A.,
and Langtimm, C.A. 2002. Estimating site occupancy rates when detection
probabilities are less than one. Ecology \textbf{83} (8): 2248--2255.
doi:10.1890/0012-9658(2002)083{[}2248:ESORWD{]}2.0.CO;2.

MacKenzie, D.I., Nichols, J.D., Royle, J.A., Pollock, K.H., Bailey,
L.L., and Hines, J.E. 2018. Occupancy estimation and modeling. 2nd
edition. Academic Press, Cambridge. doi:10.1016/C2012-0-01164-7.

Majdoubi, F.Z., Ouizgane, A., Farid, S., Mossetti, L., Droussi, M.,
Guerriero, G., and Hasnaoui, M. 2022. Fry survival rate as a predictive
marker of optimal production of silver carp (\emph{Hypophthalmichthys
molitrix} , Valenciennes 1844): A biostatistical study in Deroua Fish
Farm, Morocco. Proc. Zool. Soc. \textbf{75} (2): 152--160.
doi:10.1007/S12595-021-00383-5.

Michaletz, P.H., and Gale, C.M. 1999. Longitudinal gradients in age-0
gizzard shad density in large Missouri reservoirs. North Am. J. Fish.
Manag. \textbf{19} (3): 765--773.
doi:10.1577/1548-8675(1999)019\textless{}0765:lgiags\textgreater{}2.0.co;2.

Pankhurst, N.W., and Porter, M.J.R. 2003. Cold and dark or warm and
light: variations on the theme of environmental control of reproduction.
Fish Physiol. Biochem. \textbf{28} : 385--389. doi:
10.1023/B:FISH.0000030602.51939.50

Papoulias, D.M., Chapman, D., and Tillitt, D.E. 2006. Reproductive
condition and occurrence of intersex in bighead carp and silver carp in
the Missouri River. Hydrobiologia \textbf{571} : 355--360.
doi:10.1007/s10750-006-0260-7.

Peoples, B.K., and Frimpong, E.A. 2011. Among-pass, interregional, and
single- versus multiple-season comparisons of detection probabilities of
stream fishes. Trans. Am. Fish. Soc. \textbf{140} (1): 67--83.
doi:10.1080/00028487.2010.550237.

Potoka, K.M., Shea, C.P., and Bettoli, P.W. 2016. Multispecies occupancy
modeling as a tool for evaluating the status and distribution of darters
in the Elk River, Tennessee. Trans. Am. Fish. Soc. \textbf{145} (5):
1110--1121. doi:10.1080/00028487.2016.1201002.

Pritt, J.J., DuFour, M.R., Mayer, C.M., Roseman, E.F., and DeBruyne,
R.L. 2014. Sampling little fish in big rivers: larval fish detection
probabilities in two Lake Erie tributaries and implications for sampling
effort and abundance indices. Trans. Am. Fish. Soc. \textbf{143} (4):
1011--1027. doi:10.1080/00028487.2014.911204.

Pritt, J.J., Roseman, E.F., Ross, J.E., and Debruyne, R.L. 2015. Using
larval fish community structure to guide long-term monitoring of fish
spawning activity. North Am. J. Fish. Manag. \textbf{35} (2): 241--252.
doi:10.1080/02755947.2014.996687.

Quist, M.C., Pember, K.R., and Guy, C.S. 2004. Variation in larval fish
communities: implications for management and sampling designs in
reservoir systems. Fish. Manag. Ecol. \textbf{11} (2): 107--116. doi:
10.1046/j.1365-2400.2003.00381.x

Rodtka, M.C., Judd, C.S., Aku, P.K.M., and Fitzsimmons, K.M. 2015.
Estimating occupancy and detection probability of juvenile bull trout
using backpack electrofishing gear in a west-central Alberta watershed.
Can. J. Fish. Aquat. Sci. \textbf{72} (5): 742--750.
doi:10.1139/cjfas-2014-0175.

Roth, D.R., Pesik, J.J., Effert-Fanta, E.L., Wahl, D.H., Colombo, R.E.
2023. Comparison of active and passive larval sampling gears in
monitoring reproduction of invasive bigheaded carps in large-river
tributaries. North Am. J. Fish. Manag. \textbf{43} (1): 35-45. doi:
10.1002/nafm.10548.

Sala, O.E., Chapin, F.S., Armesto, J.J., Berlow, E., Bloomfield, J.,
Dirzo, R., Huber-Sanwald, E., Huenneke, L.F., Jackson, R.B., Kinzig, A.,
Leemans, R., Lodge, D.M., Mooney, H.A., Oesterheld, M., Poff, N.L.R.,
Sykes, M.T., Walker, B.H., Walker, M., and Wall, D.H. 2000. Global
biodiversity scenarios for the year 2100. Science \textbf{287} (5459):
1770--1774. doi:10.1126/science.287.5459.1770.

Schaick, S.J., Moody-Carpenter, C.J., Effert-Fanta, E.L., Hanser, K.N.,
Roth, D.R., and Colombo, R.E. 2020. Bigheaded carp spatial reproductive
dynamics in Illinois and Wabash River tributaries. North Am. J. Fish.
Manag \textbf{43} (1): 101--111. doi:10.1002/nafm.10573.

Schrank, S.J., Braaten, P.J., and Guy, C.S. 2001. Spatiotemporal
variation in density of larval bighead carp in the Lower Missouri River.
Trans. Am. Fish. Soc. \textbf{130} (5): 809--814.
doi:10.1577/1548-8659(2001)130\textless{}0809:svidol\textgreater{}2.0.co;2.

Schumann, D.A., Colvin, M.E., Miranda, L.E., and Todd Jones-Farrand, D.
2020. Occurrence and co-occurrence patterns of gar in river-floodplain
habitats: methods to leverage species coexistence to benefit
distributional models. North Am. J. Fish. Manag. \textbf{40} (3):
622--637. doi:10.1002/nafm.10402.

Simon, T.P. 1998. Assessment of Balon's reproductive guilds with
application to midwestern North American freshwater fishes.
\emph{In}Assessing the Sustainability and Biological Integrity of Water
Resources Using Fish Communities. \emph{Edited by} T.P. Simon. CRC
Press. pp. 97--121. doi:10.1201/9781003068013-8.

Solomon, L.E., Pendleton, R.M., Chick, J.H., and Casper, A.F. 2016.
Long-term changes in fish community structure in relation to the
establishment of Asian carps in a large floodplain river. Biol.
Invasions \textbf{18} (10): 2883--2895. doi:10.1007/s10530-016-1180-8.

Sullivan, C.J., Weber, M.J., Pierce, C.L., and Camacho, C.A. 2018.
Influence of river discharge on grass carp occupancy dynamics in
south-eastern Iowa rivers. River Res. Appl. \textbf{35} (1): 60--67.
doi:10.1002/rra.3385.

Swedberg, D. V., and Walburg, C.H. 1970. Spawning and early life history
of the freshwater drum in Lewis and Clark Lake, Missouri River. Trans.
Am. Fish. Soc. \textbf{99} (3): 560--570.
doi:10.1577/1548-8659(1970)99\textless{}560:saelho\textgreater{}2.0.co;2.

Tillotson, N.A., Weber, M.J., and Pierce, C.L. 2022. Zooplankton
community dynamics along the bigheaded carp invasion front in the Upper
Mississippi River. Hydrobiologia \textbf{849} : 1659--1675.
doi:10.1007/s10750-022-04809-9.

Tripp, S., Brooks, R., Herzog, D., and Garvey, J. 2013. Patterns of fish
passage in the Upper Mississippi River. River Res. Appl. \textbf{30}
(8): 1056--1064. doi:10.1002/rra.2696.

U.S. Geological Survey. 2022. Nonindigenous Aquatic Species Database.
Available from http://nas.er.usgs.gov.

Vanni, M.J. 2021. Invasive mussels regulate nutrient cycling in the
largest freshwater ecosystem on Earth. \textbf{118} (8): 10--12.
doi:10.1073/pnas.2100275118.

Weber, M.J., and Brown, M.L. 2011. Relationships among invasive common
carp , native fishes and physicochemical characteristics in upper
Midwest (USA) lakes. Ecol. Freshw. Fish \textbf{20} (2): 270--278.
doi:10.1111/j.1600-0633.2011.00493.x

Weber, M.J., and Brown, M.L. 2019. Application of a robust design
occupancy model for assessing fish recruitment. Can. J. Fish. Aquat.
Sci. \textbf{76} (4): 561--568. doi:10.1139/cjfas-2018-0083.

Weber, M.J., Matthews, A., and Pierce, C.L. 2021. Effects of adult
biomass and environmental conditions on bigheaded carp reproductive
output. J. Fish Wildl. Manag. \textbf{12} (2): 373--382.
doi:10.3996/JFWM-20-068.

Welcomme, R.L., Winemiller, K.O., and Cowx, I.G. 2006. Fish
environmental guilds as a tool for assessment of ecological condition of
rivers. River Res. Appl. \textbf{22} (3): 377--396. doi:10.1002/rra.914.

Werner, R.G. 2002. Habitat Requirements. \emph{In} Fishery science: the
unique contributions of early life stages. \emph{Edited by} L.A. Fuiman
and R.G. Werner. Blackwell Science Ltd., Oxford, United Kingdom. pp.
161--182.

Whitledge, G.W., Knights, B.C., Vallazza, J.M., Larson, J.H., Weber,
M.J., Lamer, J.T., Phelps, Q.E., and Norman, J.D. 2019. Identification
of bighead carp and silver carp early-life environments and inferring
lock and Dam 19 passage in the Upper Mississippi River: insights from
otolith chemistry. Biol Invasions \textbf{21} : 1007--1020.
doi:10.1007/s10530-018-1881-2.

Yang, Z., Zhu, Q., Cao, J., Jin, Y., Zhao, N., Xu, W., Liu, H., Tang,
H., Qiao, Y., and Chen, X. 2021. Using a hierarchical model framework to
investigate the relationships between fish spawning and abiotic factors
for environmental flow management. Sci. Total Environ. \textbf{787} .
doi:10.1016/J.SCITOTENV.2021.147618.

\textbf{TABLE 1.} Detection probability (p) models ranked by
\selectlanguage{greek}Δ\selectlanguage{english}AIC\textsubscript{c}. We compared 39 models and presented those with
\selectlanguage{greek}Δ\selectlanguage{english}AIC\textsubscript{c} [?] 3. All models included constant occupancy {[}\selectlanguage{greek}Ψ
\selectlanguage{english}(.){]}. We used top ranked species models for carp (bigheaded carp),
drum (freshwater drum), shad (Clupeidae), and percids to formulate
habitat models and top ranked habitat models to form environmental
models. Covariates include backwater (BW), thalweg (TH), channel border
(CB), and water volume filtered (VOL). (+) indicates additive effects,
(x) indicates interactive effects, and (=) indicates combined variables.\selectlanguage{english}
\begin{longtable}[]{@{}llll@{}}
\toprule
Model Structure & Parameters & \selectlanguage{greek}Δ\selectlanguage{english}AIC\emph{\textsubscript{c}} &
\emph{w\textsubscript{i}}\tabularnewline
\midrule
\endhead
\textbf{Species} & & &\tabularnewline
\emph{p}{[}carp + drum + (shad = percids){]}, \selectlanguage{english}\selectlanguage{greek}Ψ{[}.{]} & 4 & 0.00 &
0.69\tabularnewline
p{[}carp + drum + shad + percids{]}, \selectlanguage{english}\selectlanguage{greek}Ψ{[}.{]} & 5 & 1.62 &
0.31\tabularnewline
\textbf{Habitat} & & &\tabularnewline
\emph{p}{[}((BW + (TH = CB)) \selectlanguage{ngerman}× (carp + drum)) + ((BW = TH = CB) × shad =
percids){]}, \selectlanguage{english}\selectlanguage{greek}Ψ{[}.{]} & 6 & 0.00 & 0.33\tabularnewline
\emph{p}{[}(BW + (TH = CB)) \selectlanguage{ngerman}× (carp + drum + shad = percids){]},
\selectlanguage{english}\selectlanguage{greek}Ψ{[}.{]} & 7 & 1.20 & 0.18\tabularnewline
\emph{p}{[}((BW + TH + CB)) \selectlanguage{ngerman}× (carp + drum)) + ((BW = TH = CB) × shad =
percids){]}, \selectlanguage{english}\selectlanguage{greek}Ψ{[}.{]} & 8 & 1.29 & 0.17\tabularnewline
\emph{p}{[}((BW + TH + CB)) \selectlanguage{ngerman}× drum) + ((BW = TH = CB)) × carp × shad =
percids){]}, \selectlanguage{english}\selectlanguage{greek}Ψ{[}.{]} & 6 & 2.38 & 0.10\tabularnewline
\emph{p}{[}((BW + (TH = CB)) \selectlanguage{ngerman}× drum) + ((BW = TH = CB)) × carp × shad =
percids){]}, \selectlanguage{english}\selectlanguage{greek}Ψ{[}.{]} & 5 & 2.44 & 0.10\tabularnewline
\textbf{Environmental} & & &\tabularnewline
\emph{p}{[}VOL \selectlanguage{ngerman}× ((BW + (TH = CB)) × (carp + drum)) + ((BW = TH = CB)) ×
shad = percids){]}, \selectlanguage{english}\selectlanguage{greek}Ψ{[}.{]} & 7 & 0.00 & 0.35\tabularnewline
\emph{p}{[}(VOL \selectlanguage{ngerman}× (BW + (TH = CB)) × carp) + ((BW +(TH = CB)) × drum) +
(VOL × (BW = TH = CB)) × shad = percids){]}, \selectlanguage{english}\selectlanguage{greek}Ψ{[}.{]} & 7 & 1.48 &
0.17\tabularnewline
\emph{p}{[}((BW + (TH = CB)) \selectlanguage{ngerman}× carp) + (VOL × (BW + (TH = CB)) × drum) +
(VOL × (BW = TH = CB)) × shad = percids){]}, \selectlanguage{english}\selectlanguage{greek}Ψ{[}.{]} & 7 & 2.00 &
0.13\tabularnewline
\emph{p}{[}(VOL \selectlanguage{ngerman}× (BW + (TH = CB)) × (carp + drum)) + ((BW = TH = CB)) ×
shad = percids){]}, \selectlanguage{english}\selectlanguage{greek}Ψ{[}.{]} & 7 & 2.10 & 0.12\tabularnewline
\emph{p}{[}(VOL \selectlanguage{ngerman}× (BW + (TH = CB)) × carp) + ((BW +(TH = CB)) × drum) +
((BW = TH = CB)) × shad = percids){]}, \selectlanguage{english}\selectlanguage{greek}Ψ{[}.{]} & 7 & 2.91 &
0.08\tabularnewline
\bottomrule
\end{longtable}\selectlanguage{english}
\begin{longtable}[]{@{}llll@{}}
\toprule
Model Structure & Parameters & \selectlanguage{greek}Δ\selectlanguage{english}AIC\emph{\textsubscript{c}} &
\emph{w\textsubscript{i}}\tabularnewline
\midrule
\endhead
\textbf{Species} & & &\tabularnewline
\selectlanguage{english}\selectlanguage{greek}Ψ{[}carp + drum + (shad = percids){]} & 9 & 0.00 & 0.44\tabularnewline
\selectlanguage{english}\selectlanguage{greek}Ψ{[}carp + drum + shad + percids){]} & 10 & 1.63 & 0.20\tabularnewline
\selectlanguage{english}\selectlanguage{greek}Ψ{[}drum + (carp = shad = percids){]} & 8 & 1.78 & 0.18\tabularnewline
\selectlanguage{english}\selectlanguage{greek}Ψ{[}carp + percids + (drum = shad){]} & 9 & 2.92 & 0.10\tabularnewline
\textbf{Habitat} & & &\tabularnewline
\selectlanguage{english}\selectlanguage{greek}Ψ{[}carp + drum + ((BW + (TH = CB)) \selectlanguage{ngerman}× shad = percids){]} & 10 & 0.00 &
0.21\tabularnewline
\selectlanguage{english}\selectlanguage{greek}Ψ{[}carp + ((CB + (BW=TH) \selectlanguage{ngerman}× drum) + ((BW + (TH = CB)) × shad =
percids){]} & 11 & 1.55 & 0.10\tabularnewline
\selectlanguage{english}\selectlanguage{greek}Ψ{[}carp + ((BW + TH + CB) \selectlanguage{ngerman}× (drum + shad = percids)){]} & 11 & 1.58 &
0.10\tabularnewline
\selectlanguage{english}\selectlanguage{greek}Ψ{[}carp + drum + ((TH + (BW = CB)) \selectlanguage{ngerman}× (shad = percids)){]} & 10 & 1.83 &
0.09\tabularnewline
\selectlanguage{english}\selectlanguage{greek}Ψ{[}carp + drum + (shad = percids){]} & 9 & 1.91 & 0.08\tabularnewline
\selectlanguage{english}\selectlanguage{greek}Ψ{[}carp + ((BW + (TH = CB)) \selectlanguage{ngerman}× (drum + shad = percids)){]} & 11 & 1.93 &
0.08\tabularnewline
\textbf{Environmental} & & &\tabularnewline
\selectlanguage{english}\selectlanguage{greek}Ψ{[}JUL \selectlanguage{ngerman}× CVTEMP × ((TEMP × DIS × CVDIS × carp) + (TEMP × drum) + (shad
= percids)){]} & 14 & 0.00 & 0.69\tabularnewline
\selectlanguage{english}\selectlanguage{greek}Ψ{[}JUL \selectlanguage{ngerman}× CVTEMP × ((TEMP × DIS × carp) + (TEMP × drum) + (shad =
percids)){]} & 14 & 2.71 & 0.17\tabularnewline
\bottomrule
\end{longtable}

\textbf{TABLE 2.} Occupancy models evaluating species, habitat, and
environmental effects ranked by Akaike's information criterion
(\selectlanguage{greek}Δ\selectlanguage{english}AIC\textsubscript{c}). We assessed 67 models but just present models
with \selectlanguage{greek}Δ\selectlanguage{english}AIC\textsubscript{c} [?] 3. All models were made with the top ranked
detection model p{[}VOL \selectlanguage{ngerman}× ((BW + (TH = CB)) × carp × drum) + ((BW = TH =
CB)) × shad = percids){]}. We used top ranked species models for carp
(bigheaded carp), drum (freshwater drum), shad (Clupeidae), and percids
to formulate habitat models and top ranked habitat models to form
environmental models. Covariates include backwater (BW), thalweg (TH),
channel border (CB), Julian date (JUL), weekly water temperature (TEMP),
CV of temperature (CVTEMP), weekly river discharge (DIS), CV of
discharge (CVDIS). (+) indicates additive effects, (x) indicates
interactive effects, and (=) indicates combined variables.\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image1/image1}

\end{center}
\end{figure}

\textbf{FIGURE 1} . Ichthyoplankton sampling locations (stars) in pools
18-20 and associated major tributaries of the Upper Mississippi River
(UMR) during 2014-2018. Mississippi River sites are located 1 km
upstream and 1 km downstream of tributary confluences. Tributary sites
are located 1 km upstream of the confluence.\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image2/image2}

\end{center}
\end{figure}

\textbf{FIGURE 2} . Detection (top panel) and occupancy (bottom panel)
probability estimates (\selectlanguage{ngerman}± 95\% confidence intervals) across species,
habitat, and mean environmental covariates from the top ranked model.\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image3/image3}

\end{center}
\end{figure}

\textbf{FIGURE 3} . Invasive carp (top panel), freshwater drum (middle
panel), and gizzard shad and percids (bottom panel) detection (p)
probability (95\% confidence intervals, grey shaded region) in relation
to water volume (m\textsuperscript{3}) filtered through an
ichthyoplankton tow net.\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image4/image4}

\end{center}
\end{figure}

\textbf{FIGURE 4} . Cumulative detection probability (CDP \selectlanguage{ngerman}± 95\%
confidence intervals) for bigheaded carp (top panels), freshwater drum
(middle panels), and gizzard shad and percids (bottom panels) based on
the number of samples collected if 30 m\textsuperscript{3} (left column)
or 40 m\textsuperscript{3} (right column) of filtered water.\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image5/image5}

\end{center}
\end{figure}

\textbf{FIGURE 5} . Occupancy (\selectlanguage{greek}Ψ \selectlanguage{ngerman}± 95\% confidence intervals, grey
shaded region) of bigheaded carp (bottom), freshwater drum (middle row),
and gizzard shad and percids (top row) in relation to covariates
identified as important predictors for each taxa during model selection.

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

