\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[T2A]{fontenc}
\usepackage[ngerman,greek,polish,english]{babel}



\usepackage{float}








\begin{document}

\title{Identity and density of parasite exposures alter the outcome of
co-infections}



\author[1]{Chloe Ramsay}%
\author[1]{Jason Rohr}%
\affil[1]{University of Notre Dame}%


\vspace{-1em}



  
  \date{May 05, 2024}


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





\selectlanguage{english}
\begin{abstract}
Although research has focused on density-dependent responses to single
parasite infections, much less in known about how parasite density
affects the more common scenario in nature, co-infections. We
investigate how parasite density alters co-infection dynamics by
simultaneously exposing Cuban treefrogs (\emph{Osteopilus
septentrionalis}), in all pairwise combinations and at a range of doses,
to: the nematode \emph{Aplectana hamatospicula}, the chytrid fungus
(\emph{Batrachochytrium dendrobatidis}), and Ranavirus. The latter two
parasites are implicated in widespread amphibian declines. We found that
all pairwise co-infections were density dependent, but some were
positively and others negatively density dependent, and these effects
drove host pathology. Also, all co-infections were highly asymmetric --
strong in one direction and weak in the other -- consistent with weak
and asymmetric interactions dominating food webs and mutualistic
networks. These findings suggest that the null expectation for
co-infections should be that they are density-dependent, asymmetric, and
important to host health.%
\end{abstract}%



\sloppy


\textbf{Introduction:}

Co-infections, where hosts are infected with more than one parasite at a
time, are extremely common (Greub \emph{et al.} 2000; Kim \emph{et
al.}2003; Swanson \emph{et al.} 2006). Co-infections can be important
because they can cause variation in disease progression that can have
significant negative or positive effects on the health of hosts by
altering resistance (\emph{i.e} ., ability to reduce the abundance of
parasites) or tolerance (\emph{i.e} ., ability to reduce the per capita
cost of parasites to maintain health) to parasites. For example, HIV
infection reduced resistance to and mortality by a
\emph{Mycobacterium}that causes tuberculosis in humans (Corbett \emph{et
al.} 2003), whereas co-infection with helminths improved resistance and
reduced the spread of bovine tuberculosis in African buffalo populations
(Ezenwa \& Jolles 2015). Mice co-infected with influenza virus and
\emph{Legionella pneumophila} were less tolerant of tissue damage
associated with infection than singly infected mice (Jamieson \emph{et
al.} 2013).

Co-infecting parasites can interact directly or indirectly within hosts
(Kuris \& Lafferty 1994; de Roode \emph{et al.} 2004). For parasites to
interact directly, they typically infect the same tissue of hosts or use
the same resources. This is common when parasites are closely related to
each other. For example, when testing genetically
divergent\emph{Plasmodium chabaudi} clones, strong competition between
the strains was predicted by strain identity (Bell \emph{et al.} 2006).
Indirect interactions between parasites are often mediated by the host
immune system. These indirect interactions thus can play a role in
disease progression even if the parasites are unlikely to ever come into
contact within the host. For example, macroparasites activate the T
helper 2 (Th2) arm of the immune system (Paul \& Zhu 2010),
microparasites activate the Th1 arm of the immune system, and fungal
infections can activate the Th17 arm (Berger 2000; Blanco \& Garcia
2008; Zelante \emph{et al.} 2009). If two parasites activate the same
portion of the host immune system (e.g. co-infection with two
microparasites), they have the potential to inhibit one another by
activating immune responses that combat both parasites, which is often
referred to as cross-immunity (Johnson \& Buller 2011). If two parasites
activate different branches of the host immune system, they have the
potential to facilitate one another. This is because the Th1 and Th2
arms limit one another and therefore hosts have trouble upregulating
both simultaneously (Abbas \emph{et al.} 1996; Morel \& Oriss 1998;
Yazdanbakhsh \emph{et al.} 2002). As an example, mice infected
with\emph{Toxoplama gondii} mounted a Th1 response and it limited the
host's ability to mount a Th2 response against subsequent
\emph{Heligmosomoides polygyrus} infection (Ahmed \emph{et al.} 2017).

Because co-infecting parasites interact with one another and the
environment of the host, community ecology principles, such as negative
density dependence, may alter host health and inform our understanding
of co-infections (Pedersen \& Fenton 2007; Johnson \emph{et al.} 2015).
Negative density dependence predicts that the strength of competition
between species can depend on their densities, with potential impacts
for community assembly (Chesson \& Kuang 2008). Hence, all else being
equal between species, the species at the higher density should
outcompete the one at the lower density. Although there are many studies
on the effects of parasite density or dose on single-species infections
(Khuroo 1996; Pearman \emph{et al.} 2004; Garner \emph{et al.} 2009;
Echaubard \emph{et al.} 2010), few studies have examined how parasite
density or dose alters co-infections and associated disease progression
(Ge \emph{et al.} 2012; Niczyporuk \emph{et al.} 2014). The terms
density and dose will be used interchangeably throughout the remainder
of the manuscript. Of the few studies that have considered this, they
have either focused on closely related parasite taxa (Ge \emph{et
al.}2012) or included other variables in their design, such as
vaccination, making it difficult to parse the effects of density of
co-infecting parasites on disease progression (Niczyporuk \emph{et al.}
2014). Hosts are often concomitantly exposed to multiple parasites in
nature, and due to the spatiotemporal variation in abundance of
parasites that a host might encounter, co-infection with multiple
parasites at different densities is more likely in the wild than
co-infections with identical parasites densities. Thus, our experiment
aims to test how co-infection with varying doses alters the outcome of
co-infections and disease in amphibians.

Amphibians are the most highly threatened vertebrate taxa partly due to
the spread of parasites (Wake \& Vredenburg 2008). To address this aim,
we exposed Cuban treefrogs (\emph{Osteopilus septentrionalis)} to
pairwise co-infections of the following parasite
species:\emph{Batrachochytrium dendrobatidis} (Bd), Ranavirus,
and\emph{Aplectana hamatospicula} . Importantly, we tested how the dose
of each species affected co-infection and disease progression. Bd is a
chytrid fungus that is associated with extinctions and population
declines of amphibians globally (Berger \emph{et al.} 1998;
Skerratt\emph{et al.} 2007; Kilpatrick \emph{et al.} 2010). The
infectious zoospores of this parasite enter the skin of amphibians and
fuse the keratinous portions of the skin (Kilpatrick \emph{et al.}
2010). This limits osmoregulation and can cause cardiac arrest (Voyles
\emph{et al.}2009). Ranavirus is a virus that causes mass mortality in
amphibians also on a global scale (Green \emph{et al.} 2002; Gray
\emph{et al.}2009). Ranavirus is from the family \emph{Iridoviridae} and
it replicates in the internal organs of ectothermic vertebrates, causing
hemorrhaging of these organs, particularly in the liver and kidneys
(Gantress \emph{et al.} 2003; Gray \emph{et al.} 2009). These two
parasites are microparasites, meaning that they are small and that they
can replicate internally in the host, leading to higher parasite loads
even without repeated exposure (Rojas \emph{et al.} 2005;
Rosenblum\emph{et al.} 2012). Alternatively, we tested a macroparasite,
the nematode \emph{A. hamatospicula,} which is a common parasite of
amphibians in the Southeastern US and Latin America (Baker 1987; Vhora
\& Bolek 2013; Ortega \emph{et al.} 2015). \emph{A.
hamatospicula}infects the host when juveniles penetrate the skin and
migrate to the amphibian gastrointestinal tract (Knutie \emph{et al.}
2017b). There, they mature into adults eventually passing juveniles
through the feces that can re-infect the frogs (Knutie \emph{et al.}
2017b). Parasitic worms, Ranavirus, and Bd frequently co-occur in
amphibian hosts in the wild (Hoverman \emph{et al.} 2012; Stutz \emph{et
al.} 2018; Watters\emph{et al.} 2018). In fact, in a biodiversity
hotspot in the Peruvian Andes, up to 50\% of frogs were co-infected with
Ranavirus and Bd (Warne\emph{et al.} 2016).

The goals for this study were to test if the dose of parasite exposure
alters 1) the load of the co-infecting parasite (\emph{i.e} .,
resistance), 2) survival or growth rate of the host, and 3) the host's
ability to tolerate infections. These goals were motivated by several
hypotheses. First, we hypothesized that the load of one infecting
parasite would be negatively associated with the exposure dose of the
co-infecting parasite because of density-dependent competition. We also
hypothesized that the advantage a parasite has when it is at a high
density would be amplified if the co-infecting parasite activates a
similar immune response (\emph{i.e.,} are both microparasites) and
lessened or potentially facilitated if the co-infecting parasite
activates a different immune response (\emph{i.e.,} a micro- and
microparasite). Second, we hypothesize that co-infection will decrease a
host's tolerance (\emph{e.g.} a host's ability to maintain their health
despite high infection loads) when the co-infecting species are
facilitative and increase host tolerance when they inhibit one another.

\textbf{Methods:}

\emph{Animal Husbandry}

Cuban treefrog tadpoles (\emph{Osteopilus septentrionalis} ) were
collected from kiddy pools (140 L) filled with water in the University
of South Florida Botanical Gardens (Tampa, FL, USA) in August 2016.
Individuals were raised in plastic containers filled to 11 L with
artificial spring water (ASW) at densities of 20-30 tadpoles/container
and were fed \emph{ad libitum} every other day a mixture crushed fish
flakes (United Pet Group, Inc., Blacksburg, VA, USA), spirulina (NOW
foods, Bloomingdale, IL, USA), in an agar block (Fisher BioReagents,
Pittsburgh, PA, USA). Tadpoles were moved to new containers with fresh
ASW weekly. Used plastic containers were washed by hand, bleached,
rinsed with deionized (DI) water, and dried weekly. Once tadpoles grew
back legs lids were placed on the container to prevent escape. When
metamorphosing frogs grew front legs, frogs were housed in 57.75
cm\textsuperscript{3} sterilized plastic cups containing an unbleached
paper towel and 10 mL of ASW. After metamorphosis frogs were held in
sterilized plastic cups containing an unbleached paper towel wet with
ASW and frogs were fed 2-week-old crickets \emph{ad libitum} twice a
week. Containers were also changed weekly and cleaned as described
above. All frogs were housed at 25 \selectlanguage{ngerman}°C with a 12 h photoperiod.

\emph{Experimental Design}

To examine how the dose of parasite exposures affects host-parasite
dynamics, we exposed frogs to one of 28 total parasite treatments.
Treatments included exposure to Ranavirus alone, Bd alone, \emph{A.
hamatospicula} alone, all pairwise combinations of these parasites at a
range of densities, and controls (no exposure). In each of the pairwise
co-infection treatments hosts were exposed to one parasite at an
intermediate density and the second parasite at one of a range of
densities (one of four potential densities) in all possible combinations
(Table 1). There were six individuals for each treatment group
(\emph{n=6} ), and twelve control individuals (\emph{n=12} ), for a
total of 174 frogs.

\emph{Parasite culture}

\emph{A. hamatospicula} were collected from the gastrointestinal tract
of euthanized Cuban treefrogs. Cuban treefrogs were collected from
Flatwoods Wilderness Park (Tampa, FL, USA). After extraction, worms were
stored in Petri dishes (15 x 150 mm; \emph{n} \selectlanguage{english}[?] 5 per dish) filled with
2 mL of DI water and gastrointestinal content from the infected
amphibians in dark conditions. After the adult female worms laid larval
worms (J1 larvae), they were kept for at least 14 days to ensure that
larval worms reached the infectious stage (J3 larvae). Petri dishes with
2mL of DI water and gastrointestinal content from uninfected frogs
collected to act as a sham treatment.

Ranavirus (FV3) was cultured in fathead minnow (\emph{Pimephales
promelas} ) cells and maintained at -80degC in minimal essential medium
(MEM).

Bd (SRS-JEL 212 strain) in a 1\% tryptone solution was aliquoted into
Petri dishes previously filled with 1\% agar and 1 \% tryptone gel. Bd
was grown at 23degC for seven days until zoosporangia had matured and were
releasing zoospores, after which, 1 mL of DI water was added to the
Petri dishes and gently mixed to encourage zoospore release. To asses Bd
zoospore concentration, we poured this solution into a beaker and
diluted it until we counted a final Bd density of
10\textsuperscript{5}zoospores/mL using a hemocytometer. Plates with a
sterile 1\% tryptone solution without Bd were stored and washed
identically to the Bd plates to produce sham treatments.

\emph{Parasite exposures}

Two days before parasite exposure, individuals were moved to an
environmental chamber kept at 17degC because Cuban treefrogs can clear Bd
at higher temperatures (McMahon \emph{et al.} 2014; Cohen \emph{et
al.}2017). In the co-infection treatments, the host was exposed to one
parasite at an intermediate, fixed dose and to the other parasite at a
dose that ranged from low to high for each of the tested parasites
(Garner \emph{et al.} 2009; Echaubard \emph{et al.} 2010;
Hoverman\emph{et al.} 2010; Gervasi \emph{et al.} 2013; Knutie \emph{et
al.}2017a; Knutie \emph{et al.} 2017b). For the microparasites Bd and
Ranavirus, doses ranged from 10\textsuperscript{3} to
10\textsuperscript{5} zoospores or plaque forming units (PFU),
respectively, and the intermediate dose was 10\textsuperscript{4} (Table
1). For the macroparasite \emph{A. hamatospicula} , doses ranged from 15
to 60 J3 larvae and the intermediate dose was 30 (Table 1). These doses
were applied to frogs held in Petri dishes (25 x 100 mm). Frogs received
the doses for their randomly assigned treatment as 1-mL of DI water with
Bd zoospores, or with J3 \emph{A. hamatospicula} , or a 69 \selectlanguage{greek}µ\selectlanguage{english}l aliquot of
MEM with Ranavirus. All hosts also received sham exposures for parasites
to which they were not exposed to ensure that each frog received
identical treatments with the exception of the parasite. For example,
hosts co-exposed to Bd and \emph{A. hamatospicula} , received a 69 \selectlanguage{greek}µ\selectlanguage{english}l
aliquot of MEM without Ranavirus. Control individuals received sham
treatments for all three parasites.

\emph{Amphibian responses to parasites}

To measure amphibian growth, frogs were weighed weekly for four weeks.
Individuals were also checked twice daily for mortality. If mortality
occurred, frogs were weighed and swabbed for Bd and/or Ranavirus and/or
dissected to assess \emph{A. hamatospicula} loads in their
gastrointestinal tract, depending on their treatment group. All
surviving frogs were euthanized and dissected 28 days after initial
parasite exposure. Growth rates were calculated as the final mass minus
the initial mass divided by weeks spent alive (g wk\textsuperscript{-1})

\emph{Assessing parasite loads}

To assess loads of Ranavirus, hosts were swabbed five times around the
mouth and cloaca on days 2, 4, and 8. To assess Bd load, hosts were
swabbed five times from hip to toe on both rear legs on days 8, 16, and
24 after exposure. Swabs were placed in 2 mL sterile microcentrifuge
tubes and stored at -80\selectlanguage{ngerman}°C for later processing. \emph{A. hamatospicula}
loads were assessed by checking the frog's feces weekly for larval worms
and dissecting individuals and checking their gastrointestinal tract for
adult worms either when they experienced mortality or at the end of the
experiment.

DNA from each swab was extracted using a Qiagen DNEasy Blood \& Tissue
Kit and analyzed using quantitative polymerase chain reaction (qPCR;
Boyle \emph{et al.} 2004; Picco \emph{et al.} 2007). Days 16 and 4, for
Bd and Ranavirus respectively, were chosen for statistical analyses
after initial qPCR analyses, where we analyzed subsets of swabs across
treatments across days. From these initial analyses these days were
chosen as optimal time points for assessing load differences as they
were both early enough for individuals to not have experienced mortality
from the infections, but also late enough to address parasite
establishment (Gray \emph{et al.} 2009; Voyles \emph{et al.} 2009).

\emph{Statistical Analyses}

All analyses were run with R version 3.6.1 (R Core Team 2019). Plots
were created using the \emph{visreg} package and \emph{visreg} function
(Breheny \& Burchett 2019). Survival plots were created using
the\emph{survminer} package and \emph{ggsurvplot} function
(Kassambara\emph{et al.} 2019).

\emph{How do changing doses of parasite affect the resistance to the
fixed dose, co-infecting parasite?}

To test how the interaction between the identity of a co-infecting
parasite and its dose alter the load of Ranavirus or Bd, we conducted a
generalized linear model (glm) with a negative binomial error
distribution. For \emph{A. hamatospicula} load, we used logistic
regression (\emph{glm} function) with a binomial error distribution,
where the dependent variable was defined as the number of larvae that
successfully infected (penetrated the host, migrated to gut, and reached
maturity) over the total number of larvae to which the hosts were
exposed. The independent variables for all of the above models were the
crossed dose and identity of the changing-dose parasite. Dose was
expressed as a proportion of the highest possible dose hosts were
exposed to for each parasite. Altering dose to be a proportion allowed
us to make comparisons across doses even though the quantity of dose we
exposed hosts to varied widely for macro- and microparasites. For this
and all further described analyses Tukey Post-hoc tests were run to
compare among parasite identities when the main effect or interaction
were significant (\emph{multcomp} package and \emph{glht} function
(Hothorn 2010).

\emph{How do parasite dose and identity affect host growth, survival,
and tolerance?}

To test how the interaction between the identity of a co-infecting
parasite and its dose affect host growth we conducted general linear
models. To address change in host weight, growth rate was calculated as
weight of the host at the end of experiment or on the day of death
divided by the total weeks alive (g/week) and used as the dependent
variable. The identity of the fixed dose parasite, the identity of the
changing dose parasite, and the dose of the changing dose parasite were
used as crossed independent variables. To test how these same factors
affected tolerance based on growth, this same model was repeated with
the addition of parasite load of the fixed-dose parasite as a third,
crossed independent variable.

To address how the identity of the co-infecting parasites and dose of
exposure affected host survival, we conducted a survival analysis (using
the \emph{survival} package and the \emph{coxph} function (Therneau \&
Lumley 2019) with host survival as the dependent variable. The identity
of the fixed- and changing-dose parasites, as well as the dose of the
changing-dose parasite, were crossed independent variables. To test how
these same factors affected tolerance based on survival, this same model
was repeated with the addition of parasite load of the fixed-dose
parasite as a third, crossed independent variable.

\textbf{Results}

\emph{How do changing doses of parasites affect resistance to the fixed
dose, co-infecting parasite?}

Analyses revealed a significant negative association between the dose of
the co-infecting parasite and the load of Ranavirus, regardless of the
identity of the co-infecting parasite (\selectlanguage{greek}χ\selectlanguage{ngerman}²\textsubscript{1}=4.07,\emph{p}
=0.04; Fig. 1). For \emph{A. hamatospicula} , there was an interaction
between the identity and the dose of the changing-dose parasite
(\selectlanguage{greek}χ\selectlanguage{ngerman}²\textsubscript{1}=12.42, \emph{p} \textless{}0.001). Dose of Bd was
associated negatively with \emph{A. hamatospicula}(\emph{p}
\textless{}0.001; Fig. 2), whereas dose of Ranavirus was not
significantly associated with \emph{A. hamatospicula} load (\emph{p}
=0.22; Fig. 2).

Neither the identity of the co-infecting parasite
(\selectlanguage{greek}χ\selectlanguage{ngerman}²\textsubscript{1}=0.03, \emph{p} =0.86) nor its dose
(\selectlanguage{greek}χ\selectlanguage{ngerman}²\textsubscript{1}=0.01, \emph{p} =0.92) affected Bd load in
co-infected hosts.

\emph{How do parasite dose and identity affect host growth, survival,
and tolerance?}

The identity of both fixed (\emph{F} \textsubscript{2,157}=35.5,\emph{p}
\textless{}0.001) and changing dose parasites (\emph{F}
\textsubscript{2,157}=10.89, \emph{p} \textless{}0.001) were significant
predictors of weight change. For both the fixed- and changing-dose
parasites, growth was significantly higher for control hosts than
infected hosts (controls vs. Bd: fixed dose parasite and changing dose
parasite: \emph{p} \textless{}0.001; controls vs. \emph{A.
hamatospicula} : fixed dose parasite: \emph{p} =0.02, changing dose
parasite: \emph{p} =0.01; controls vs. Ranavirus: fixed dose
parasite:\emph{p} =0.01, changing dose parasite: \emph{p}
\textless{}0.01). Additionally, exposure to Bd at a fixed dose caused a
significant decrease in host growth rate (g/week) when compared to
exposure to\emph{A. hamatospicula} (Bd vs. \emph{A. hamatospicula} :
p\textless{}0.001) or Ranavirus (Bd vs. Ranavirus: p\textless{}0.001).
Dose of co-infecting parasite was not a significant predictor of weight
gain when all parasites were analyzed together (\emph{F}
\textsubscript{1,157}=1.75, \emph{p} =0.19), but dose of Bd was
negatively associated with host growth (\emph{F}
\textsubscript{1,46}=8.8, \emph{p} \textless{}0.005).

The identity of the fixed-dose parasite was the only significant
predictor of host survival (\emph{F}
\textsubscript{2,125}=17.03,\emph{p} \textless{}0.001), with exposure to
Bd significantly reducing host survival relative to Ranavirus (Bd vs.
Ranavirus:\emph{p} \textless{}0.001), \emph{A. hamatospicula} (Bd vs.
\emph{A. hamatospicula} : \emph{p} \textless{}0.001), and the uninfected
controls (Bd vs. control: \emph{p} \textless{}0.001; Fig.4).

We found no significant effects of dose or identity of the co-infecting
parasite on host tolerance of Ranavirus (Viral load x dose:\emph{F}
\textsubscript{1,37}=0.02, \emph{p} =0.9; Viral load x identity of
co-infecting parasite: \emph{F} \textsubscript{2,37}=1.89,\emph{p}
=0.17) or \emph{A. hamatospicula} (\emph{A. hamatospicula load}x dose:
\emph{F} \textsubscript{1,39}=0.49, \emph{p} =0.49; \emph{A.
hamatospicula} load x identity of co-infecting parasite\emph{: F}
\textsubscript{1,39}=0.02, \emph{p} =0.88).

However, dose and identity of the co-infecting parasite interacted to
affect host tolerance of Bd (Bd load x dose x identity:\emph{F}
\textsubscript{1,44}=6.0, \emph{p} =0.02). Tolerance (defined as less
negative slopes between parasite load and weight gain) of Bd based on
host weight gain was associated positively with the dose of \emph{A.
hamatospicula,} but negatively with the dose of Ranavirus (Fig. 5). We
found no significant effects of host tolerance when using host survival
as a metric for tolerance.

\textbf{Discussion:}

Hosts are frequently co-infected and there is spatiotemporal variation
in the densities of parasite that they encounter. We found that every
set of pairwise co-infections was density dependent. Additionally, each
was highly asymmetric and weak in one of the two directions, consistent
with other ecological interactions, such as the asymmetric and weak
interactions that dominate food webs (Paine 1992; McCann \emph{et
al.}1998) and mutualistic networks (Bascompte \emph{et al.} 2006). We
also found that the density of a co-infecting parasite has the potential
to alter the loads of the other co-infecting parasites and host
tolerance these infections.

In co-infections with Ranavirus and \emph{A. hamatospicula} , higher
doses of \emph{A. hamatospicula} lowered viral load (Fig. 1), but higher
doses of Ranavirus did not alter \emph{A. hamatospicula} load (Fig. 2).
The negative associations between \emph{A. hamatospicula} and Ranaviral
load are inconsistent with our hypothesis of positive density dependent
competition between macro- and microparasites. Given that viruses elicit
the Th1 arm of the immune system, whereas helminths upregulate the Th2
arm and these two arms are well-documented to be antagonistic in
vertebrate host taxa (Degen \emph{et al.} 2005; Graham 2008;
Salgame\emph{et al.} 2013), the expectation was that co-infection with
Ranavirus and \emph{A. hamatospicula} would be facilitative rather than
inhibitory. When the dose of Ranavirus was manipulated, there was a
non-significant trend in support of facilitation of \emph{A.
hamatospicula} that was consistent with the hypothesized positive
density dependence. In contrast, however, when \emph{A.
hamatospicula}was manipulated, there was significant inhibition of
Ranavirus or significant negative density dependence. This competition
is likely immune-mediated because these parasites are unlikely to
interact directly given that Ranavirus infects the liver and kidneys
(Gray\emph{et al.} 2009) and \emph{A. hamatospicula} lives in the
gastrointestinal tract (Knutie \emph{et al.} 2017b). Additionally, the
host immune response to these parasites might be further complicated by
the fact that \emph{A. hamatospicula} , in entering through the skin of
the amphibians, has to combat the complex chemical and physical defenses
present in the mucosa of amphibians (reviewed in Fites \emph{et
al.}2014) and Ranavirus does not when it is ingested, the method we used
for this experiment. Therefore, either this polarization between the Th1
and Th2 immune system does not differentiate as strongly because the
mucosal immune system combats parasites before they even enter the
amphibians or there is another mechanism responsible for this response.

In co-infections with Ranavirus and Bd, higher doses of Bd decreased
viral load (Fig. 1), but higher doses of Ranavirus did not impact Bd
load. We hypothesized negative density dependence between these
parasites because they are both microparasites that activate similar
arms of the host immune system (Berger 2000). We found evidence to
support this hypothesis, but only in one direction. Ranavirus was
outcompeted at higher Bd loads. Bd and Ranavirus are unlikely to
interact directly in the host because Bd infects the skin of amphibians
(Berger \emph{et al.} 2005) and Ranavirus infects the liver and kidneys
(Gray \emph{et al.} 2009), but results show that there is the potential
for Bd to inhibit Ranavirus infection through cross-immunity (Berger
2000). Interestingly, this pattern does not occur in the reverse
direction, suggesting that the immune response to combat Bd can
successfully combat Ranavirus, but the immune response to combat
Ranavirus cannot successfully combat Bd. Although our understanding of
whether amphibians can upregulate a Th17 immune response is limited
(Fites \emph{et al.} 2014), Th17 is frequently upregulated in
conjunction with Th1 immune responses to combat fungal infections in
other vertebrates (Blanco \& Garcia 2008). Therefore, this difference in
how host immune systems respond to Bd versus Ranavirus could make our
hypothesis of cross-immunity between these parasites overly simplistic.
Additionally, we found that our hosts are more susceptible to Bd
infection than the other parasites tested (Fig. 3, Fig. 4). Therefore,
if Bd mounts a mix of a Th1 and Th17 immune responses, the mounted Th1
response may function through cross-immunity to combat Ranavirus, but if
Ranavirus only mounts a Th1 response, that might not be a strong or
complex enough immune response to successfully combat Bd.

In co-infections with Bd and \emph{A. hamatospicula} , the dose of Bd
negatively impacted the load of \emph{A. hamatospicula} (Fig. 2), but
the dose of \emph{A. hamatospicula} did not alter the load of Bd. We
hypothesized positive density dependence for this interaction because Bd
and \emph{A. hamatospicula} likely activate different parts of the host
immune system, with Bd activating the Th1 and Th17 arms¸ although the
use of Th1 and/or Th17 to combat Bd is not fully characterized (Fites
2014), and \emph{A. hamatospicula} activating the Th2 arm (Berger 2000;
Paul \& Zhu 2010). We infected hosts simultaneously, so Bd would not be
established in the skin when \emph{A. hamatospicula} infects and
therefore it is unlikely that this direct interaction plays a role in
competitions between these parasites (Berger \emph{et al.} 2005;
Knutie\emph{et al.} 2017b). Therefore, interactions between parasites
are likely to be indirect and mediated by the host immune system.
Although not originally hypothesized, there is the potential that this
interaction could be largely driven by innate, instead of acquired,
immunity. For example, macrophages can combat both Bd (Fites 2014) and
helminth infections (Motran \emph{et al.} 2018) and short-term
upregulation of innate immune responses (\emph{i.e.} macrophages) could
be driving the decrease in \emph{A. hamatospciula} load at higher Bd
doses, especially if macrophages are more effective against \emph{A.
hamatsopicula} than Bd.

Host tolerance to Bd was significantly impacted by an interaction
between identity and dose of the co-infecting parasites. Tolerance
(defined as less negative slopes between parasite load and weight gain)
of Bd was associated positively with the dose of \emph{A.
hamatospicula}but negatively with the dose of Ranavirus (Fig. 5). This
pattern was not in keeping with our hypotheses that microparasites would
upregulate similar arms of the host immune system and therefore inhibit
each other, and co-infections with macro- and micro-parasites would
facilitate one another through tradeoffs in immune activation, causing
increases and decreases in host tolerance, respectively. In fact, we saw
the opposite pattern. Additionally, we found that exposure to Bd
significantly decreased host growth and survival relative to controls
and more so than any other parasite (Fig.3, Fig.4). This suggests that
Cuban treefrogs are particularly susceptible to Bd infection. Infection
with Ranavirus and \emph{A. hamatospicula} also decreased host growth
when compared to individuals without infections (Fig. 3). Therefore, the
fact we only found significant results on amphibian tolerance to Bd is
in keeping with our other results on host health. Our results suggest
that hosts are intolerant of Bd and Ranavirus co-infection, especially
at high doses. Mounting immune responses to combat these multiple deadly
and rapidly replicating microparasites is costly and could limit
resources that the host can allocate to other demanding processes such
as growth, leading to the observed patterns (Lochmiller \& Deerenberg
2000; Green\emph{et al.} 2002; Gray \emph{et al.} 2009; Kilpatrick
\emph{et al.}2010). However, the negative effects on host growth caused
by higher loads of Bd seem to be mediated by higher doses of \emph{A.
hamatospicula} , suggesting that hosts are more tolerant to macro- and
microparasite co-infections than micro- and microparasite
co-infections\emph{.} Additionally, these results indicate that
density-dependent competition plays a role in host tolerance to these
parasites and therefore host health.

All pairwise parasite comparisons were significantly impacted by dose.
Additionally, the directions of the interactions were variable, with
marginally positive and negative density dependent interactions.
However, the strength of these interactions was highly asymmetric and
always weak in one of the two directions. These results are consistent
with other ecological interactions, such as interactions in food webs
and in plant-pollinator networks, which often show asymmetric
interactions that are weak in one direction (Paine 1992; McCann \emph{et
al.} 1998; Bascompte \emph{et al.} 2006). Asymmetric interactions have
also been seen before in this co-infection system (Ramsay \& Rohr
submitted). These asymmetric interactions are thought to maintain
biodiversity and long-term co-existence by dampening oscillations
between the interacting individuals (Paine 1992; McCann \emph{et
al.}1998; Bascompte \emph{et al.} 2006). In this system, these patterns
were likely driven by indirect interactions mediated by the host immune
system and were drivers of host tolerance to these co-infections. Thus,
our results suggest that density can drive parasite interactions and
host health, but the direction and strength of these interactions vary.
Further studies on amphibian immune systems would help better elucidate
the mechanisms behind the density-dependent interactions we have found
in this system.

\textbf{Acknowledgements:} We would like to thank J. Hoverman for
supplying the Ranavirus and all the undergraduates who made this
experiment possible. Funds were provided by grants to J.R.R. from the
National Science Foundation (EF-1241889, IOS-1754868) and the National
Institutes of Health (R01GM109499, R01TW010286-01).

\textbf{References:}

1.

Abbas, A.K., Murphy, K.M. \& Sher, A. (1996). Functional diversity of
helper T lymphocytes. \emph{Nature} , 383, 787-793.

2.

Ahmed, N., French, T., Rausch, S., Kuhl, A., Hemminger, K., Dunay,
I.R.\emph{et al.} (2017). Toxoplasma Co-infection Prevents Th2
Differentiation and Leads to a Helminth-Specific Th1
Response.\emph{Frontiers in cellular and infection microbiology} , 7,
341.

3.

Baker, M.R. (1987). Synopsis of the Nematoda Parasitic in amphibians and
reptiles. \emph{Occasional papers in biology} , 11.

4.

Bascompte, J., Jordano, P. \& Olesen, J.M. (2006). Asymmetric
coevolutionary networks faciliate biodiversity
maintenance.\emph{Science} , 312, 431-433.

5.

Bell, A.S., de Roode, J.C., Sim, D. \& Read, A.F. (2006). Within-host
compeition in genetically diverse malaria infections: parasite virulence
and competitive success. \emph{Evolution} , 60, 1358-1371.

6.

Berger, A. (2000). Th1 and Th2 responses: what are they? \emph{British
Medical Journal} , 321, 424.

7.

Berger, L., Hyatt, A.D., Speare, R. \& Longcore, J.E. (2005). Life cycle
stages of the amphibian chytrid \emph{Batrachochytrium dendrobatidis}
.\emph{Diseases of aquatic organisms} , 68, 51-63.

8.

Berger, L., Speare, R., Daszak, P., Green, D.E., Cunningham, A.A.,
Goggin, C.L. \emph{et al.} (1998). Chytridiomycosis causes amphibian
mortality associated with population declines in the rain forests of
Australia and Central America. \emph{Proceedings of the National Academy
of Sciences} , 95.

9.

Blanco, J.L. \& Garcia, M.E. (2008). Immune response to fungal
infections. \emph{Veterinary immunology and immunopathology} , 125,
47-70.

10.

Boyle, D.G., Boyle, D.B., Olsen, V., Morgan, A.T. \& Hyatt, A.D. (2004).
Rapid quantitative detection of chytridiomycosis (\emph{Batrachochytrium
dendrobatidis} ) in amphibian samples using real-time Taqman PCR
assay.\emph{Diseases of aquatic organisms} , 60, 141-148.

11.

Breheny, P. \& Burchett, W. (2019). visreg: Visualization of regression
models, R version 2.5-1.

12.

Chesson, P. \& Kuang, J.J. (2008). The interaction between predation and
competition. \emph{Nature} , 456, 235-238.

13.

Cohen, J.M., Venesky, M.D., Sauer, E.L., Civitello, D.J., McMahon, T.A.,
Roznik, E.A. \emph{et al.} (2017). The thermal mismatch hypothesis
explains host susceptibility to an emerging infectious
disease.\emph{Ecology letters} , 20, 184-193.

14.

Corbett, E.L., Watt, C.J., Walker, N., Maher, D., Williams, B.G.,
Raviglione, M.C. \emph{et al.} (2003). The growing burden of
Tuberculosis: global trends and interactions with the HIV
epidemic.\emph{Arch Intern Med} , 163, 1009-1021.

15.

de Roode, J.C., Culleton, R., Cheesman, S.J., Carter, R. \& Read, A.F.
(2004). Host heterogeneity is a determinant of competitive exclusion or
coexistence in genetically diverse malaria infections.\emph{Proceedings.
Biological sciences} , 271, 1073-1080.

16.

Degen, W.G., Daal, N., Rothwell, L., Kaiser, P. \& Schijns, V.E. (2005).
Th1/Th2 polarization by viral and helminth infection in birds. \emph{Vet
Microbiol} , 105, 163-167.

17.

Echaubard, P., Little, K., Pauli, B. \& Lesbarreres, D. (2010).
Context-dependent effects of ranaviral infection on northern leopard
frog life history traits. \emph{PloS one} , 5, e13723.

18.

Ezenwa, V.O. \& Jolles, A.E. (2015). Epidemiology. Opposite effects of
anthelmintic treatment on microbial infection at individual versus
population scales. \emph{Science} , 347, 175-177.

19.

Fites, J.S. (2014). Evasion of adaptive immune defenses by the lethal
chytrid fungus \emph{Batrachochytrium dendrobatidis} .
In:\emph{Biological Sciences} . Vanderbilt University, p. 269.

20.

Fites, J.S., Reinert, L.K., Chappell, T.M. \& Rollins-Smith, L.A.
(2014). Inhibition of local immune responses by the frog-killing fungus
Batrachochytrium dendrobatidis. \emph{Infection and immunity} , 82,
4698-4706.

21.

Gantress, J., Maniero, G.D., Cohen, N. \& Robert, J. (2003). Development
and characterization of a model system to study amphibian immune
responses to iridoviruses. \emph{Virology} , 311, 254-262.

22.

Garner, T.W.J., Walker, S., Bosch, J., Leech, S., Marcus Rowcliffe, J.,
Cunningham, A.A. \emph{et al.} (2009). Life history tradeoffs influence
mortality associated with the amphibian pathogenBatrachochytrium
dendrobatidis. \emph{Oikos} , 118, 783-791.

23.

Ge, S., Zheng, D., Zhao, Y., Liu, H., Wenbo, L., Sun, Q. \emph{et
al.}(2012). Evaluating viral interference between Influenza virus and
Newcastle disease virus using real-time reverse transcription-polymerase
chain reaction in chicken eggs. \emph{Virology} , 9, 1-8.

24.

Gervasi, S., Gondhalekar, C., Olson, D.H. \& Blaustein, A.R. (2013).
Host identity matters in the amphibian-Batrachochytrium dendrobatidis
system: fine-scale patterns of variation in responses to a multi-host
pathogen. \emph{PloS one} , 8, e54490.

25.

Graham, A.L. (2008). Ecological rules governing helminth-microparasite
coinfection. \emph{Proceedings of the National Academy of Sciences of
the United States of America} , 105, 566-570.

26.

Gray, M.J., Miller, D.L. \& Hoverman, J.T. (2009). Ecology and pathology
of amphibian ranaviruses. \emph{Diseases of aquatic organisms} , 87,
243-266.

27.

Green, D.E., Converse, K.A. \& Schrader, A.K. (2002). Epizootiology of
sixty-four amphibian morbidity and mortality events in the USA,
1996-2001. \emph{Annals New York Academy of Sciences} , 969.

28.

Greub, G., Ledergerber, B., Battegay, M., Grob, P., Perrin, L., Furrer,
H. \emph{et al.} (2000). Clinical progression, survival, and immune
recovery during antiretroviral therapy in patients with HIV-1 and
hepatitis C virus coinfection: the Swiss HIV Cohort Study. \emph{The
Lancet} , 356, 1800-1805.

29.

Hothorn, W. (2010). multcomp: simultaneous inference in general
parametric models, R package version 1.4-10.

30.

Hoverman, J.T., Gray, M.J. \& Miller, D.L. (2010). Anuran
susceptibilities to ranaviruses: role of species identity, exposure
route, and a novel virus isolate. \emph{Diseases of aquatic organisms} ,
89, 97-107.

31.

Hoverman, J.T., Mihaljevic, J.R., Richgels, K.L., Kerby, J.L. \&
Johnson, P.T. (2012). Widespread co-occurrence of virulent pathogens
within California amphibian communities. \emph{Ecohealth} , 9, 288-292.

32.

Jamieson, A.M., Pasman, L., Yu, S., Gamradt, P., Homer, R.J., Decker,
T.\emph{et al.} (2013). Role of tissue protection in lethal respiratory
viral-bacterial coinfection. \emph{Science} , 340, 1230-1234.

33.

Johnson, P.T., de Roode, J.C. \& Fenton, A. (2015). Why infectious
disease research needs community ecology. \emph{Science} , 349, 1259504.

34.

Johnson, P.T.J. \& Buller, I.D. (2011). Parasite competition hidden by
correlated coinfection: using surveys and experiments to understand
parasite interactions. \emph{Ecology} , 92, 535-541.

35.

Kassambara, A., Kosinski, M., Biecek, P. \& Fabian, S. (2019). Drawing
survival curves using 'ggplot2'. \emph{R package version 0.4.6} .

36.

Khuroo, M.S. (1996). Ascariasis. \emph{Gastroenterology clinics of North
America} , 25, 553-577.

37.

Kilpatrick, A.M., Briggs, C.J. \& Daszak, P. (2010). The ecology and
impact of chytridiomycosis: an emerging disease of
amphibians.\emph{Trends in ecology \& evolution} , 25, 109-118.

38.

Kim, J., Chung, H.K. \& Chae, C. (2003). Association of porcine
circovirus 2 with porcine respiratory disease complex. \emph{The
Veterinary Journal} , 166, 251-256.

39.

Knutie, S.A., Shea, L.A., Kupselaitis, M., Wilkinson, C.L., Kohl, K.D.
\& Rohr, J.R. (2017a). Early-Life Diet Affects Host Microbiota and
Later-Life Defenses Against Parasites in Frogs. \emph{Integrative and
comparative biology} , 57, 732-742.

40.

Knutie, S.A., Wilkinson, C.L., Wu, Q.C., Ortega, C.N. \& Rohr, J.R.
(2017b). Host resistance and tolerance of parasitic gut worms depend on
resource availability. \emph{Oecologia} , 183, 1031-1040.

41.

Kuris, A.M. \& Lafferty, K.D. (1994). Community structure: larval
trematodes in snail hosts. \emph{Annual Review of Ecology and
Systematics} , 25, 189-217.

42.

Lochmiller, R.L. \& Deerenberg, C. (2000). Trade-offs in evolutionary
immunology: just what is the cost of immunity? \emph{Oikos} , 88, 87-98.

43.

McCann, K., Hastings, A. \& Huxel, G.R. (1998). Weak trophic
interactions and the balance of nature. \emph{Nature} , 395, 794-798.

44.

McMahon, T.A., Sears, B.F., Venesky, M.D., Bessler, S.M., Brown, J.M.,
Deutsch, K. \emph{et al.} (2014). Amphibians acquire resistance to live
and dead fungus overcoming fungal immunosuppression. \emph{Nature} ,
511, 224-227.

45.

Morel, P.A. \& Oriss, T.B. (1998). Crossregulation between Th1 and Th2
cells. \emph{Critical reviews in immunology} , 18, 275-303.

46.

Motran, C.C., Silvane, L., Chiapello, L.S., Theumer, M.G., Ambrosio,
L.F., Volpini, X. \emph{et al.} (2018). Helminth Infections: Recognition
and Modulation of the Immune Response by Innate Immune Cells.\emph{Front
Immunol} , 9, 664.

47.

Niczyporuk, J.S., Wo\selectlanguage{polish}ź\selectlanguage{english}niakowski, G., Czekaj, H. \& Samorek-Salamonowicz,
E. (2014). Interactions between Marek's disease virus Rispens/CVI988
vaccine strain and adenovirus field strain in chicken embryo fibroblast
(CEF) cultures. \emph{Polish Journal of Veterinary Sciences} , 17, 3-8.

48.

Ortega, N., Price, W., Campbell, T. \& Rohr, J. (2015). Acquired and
introduced macroparasites of the invasive Cuban treefrog, Osteopilus
septentrionalis. \emph{International journal for parasitology. Parasites
and wildlife} , 4, 379-384.

49.

Paine, R.T. (1992). Food-web analysis through field measurement of per
capita interaction strength. \emph{Nature} , 355, 73-75.

50.

Paul, W.E. \& Zhu, J. (2010). How are T(H)2-type immune responses
initiated and amplified? \emph{Nature reviews. Immunology} , 10,
225-235.

51.

Pearman, P.B., Garner, T.W., Straub, M. \& Greber, U.F. (2004). Response
of the Italian agile frog (Rana latastei) to a Ranavirus, frog virus 3:
a model for viral emergence in naive populations. \emph{Journal of
wildlife diseases} , 40, 660-669.

52.

Pedersen, A.B. \& Fenton, A. (2007). Emphasizing the ecology in parasite
community ecology. \emph{Trends in ecology \& evolution} , 22, 133-139.

53.

Picco, A.M., Brunner, J.L. \& Collins, J.P. (2007). Susceptibility of
the endangered California tiger salamander, Ambystoma californiense, to
ranavirus infection. \emph{Journal of wildlife diseases} , 43, 286-290.

54.

R Core Team (2019). R: a language and environement for statistical
computing. . In: \emph{R Foundation for Statistical Computing, Vienna,
Austria} .

55.

Ramsay, C. \& Rohr, J.R. (submitted). The application of community
ecology theory to co-infections in wildlife hosts. \emph{Ecology} .

56.

Rojas, S., Richards, K., Jancovich, J.K. \& Davidson, E.W. (2005).
Influence of temperature on Ranavirus infection in larval salamanders
Ambystoma tigrinum. \emph{Diseases of aquatic organisms} , 63, 95-100.

57.

Rosenblum, E.B., Poorten, T.J., Settles, M. \& Murdoch, G.K. (2012).
Only skin deep: shared genetic response to the deadly chytrid fungus in
susceptible frog species. \emph{Molecular ecology} , 21, 3110-3120.

58.

Salgame, P., Yap, G.S. \& Gause, W.C. (2013). Effect of helminth-induced
immunity on infections with microbial pathogens. \emph{Nat Immunol} ,
14, 1118-1126.

59.

Skerratt, L.F., Berger, L., Speare, R., Cashins, S., McDonald, K.R.,
Phillott, A.D. \emph{et al.} (2007). Spread of Chytridiomycosis Has
Caused the Rapid Global Decline and Extinction of Frogs.\emph{EcoHealth}
, 4, 125-134.

60.

Stutz, W.E., Blaustein, A.R., Briggs, C.J., Hoverman, J.T., Rohr, J.R.
\& Johnson, P.T.J. (2018). Using multi-response models to investigate
pathogen coinfections across scales: insights from emerging diseases of
amphibians. \emph{Methods Ecol Evol} , 9, 1109-1120.

61.

Swanson, S.J., Neitzel, D., Reed, K.D. \& Belongia, E.A. (2006).
Coinfections acquired from ixodes ticks. \emph{Clin Microbiol Rev} , 19,
708-727.

62.

Therneau, T.M. \& Lumley, T. (2019). survival: Survival analysis, R
version 2.44-1.1.

63.

Vhora, M.S. \& Bolek, M.G. (2013). New host and distribution records for
Aplectana hamatospicula (Ascaridida: Cosmocercidae) in Gastrophryne
olivacea (Anura: Microhylidae) from the Great Plains U.S.A. \emph{The
Journal of parasitology} , 99, 417-420.

64.

Voyles, J., Young, S., Berger, L., Campbell, C., Voyles, W.F., Dinudom,
A. \emph{et al.} (2009). Pathogenesis of Chytridiomycosis, a cause of
catastrophic amphibian declines. \emph{Science} , 326, 582-585.

65.

Wake, D.B. \& Vredenburg, V.T. (2008). Colloquium paper: are we in the
midst of the sixth mass extinction? A view from the world of
amphibians.\emph{Proceedings of the National Academy of Sciences of the
United States of America} , 105 Suppl 1, 11466-11473.

66.

Warne, R.W., LaBumbard, B., LaGrange, S., Vredenburg, V.T. \& Catenazzi,
A. (2016). Co-Infection by Chytrid Fungus and Ranaviruses in Wild and
Harvested Frogs in the Tropical Andes. \emph{PloS one} , 11, e0145864.

67.

Watters, J.L., Davis, D.R., Yuri, T. \& Siler, C.D. (2018). Concurrent
Infection of Batrachochytrium dendrobatidis and Ranavirus among Native
Amphibians from Northeastern Oklahoma, USA. \emph{J Aquat Anim Health} ,
30, 291-301.

68.

Yazdanbakhsh, M., Kremsner, P.G. \& van Ree, R. (2002). Allergy,
Parasites, and the Hygiene Hypothesis. \emph{Science} , 296, 490-494.

69.

Zelante, T., De Luca, A., D'Angelo, C., Moretti, S. \& Romani, L.
(2009). IL-17/Th17 in anti-fungal immunity: what's new? \emph{Eur J
Immunol} , 39, 645-648.

\textbf{Table 1} . Hosts were co-exposed to one parasite at a fixed
density and a second parasite over a range of densities shown below.\selectlanguage{english}
\begin{longtable}[]{@{}lllll@{}}
\toprule
\textbf{Parasite} & & \textbf{Doses} & &\tabularnewline
\midrule
\endhead
Ranavirus (PFUs) & 1.00E+03 & 1.00E+04 & 4.50E+04 &
1.00E+05\tabularnewline
Bd (zoospores) & 1.00E+03 & 1.00E+04 & 4.50E+04 &
1.00E+05\tabularnewline
\emph{A. hamatospicula} (J3 larvae) & 15 & 30 & 45 & 60\tabularnewline
\bottomrule
\end{longtable}

\textbf{Fig. 1.} The proportional dose of either \emph{Batrachochytrium
dendrobatidis} or \emph{Aplectana hamatospicula} (there was no
difference between the two) was negatively related to load of Ranavirus
on \emph{Osteopilus septentrionalis} hosts
(\selectlanguage{greek}χ\selectlanguage{ngerman}²\textsubscript{1}=4.07,\emph{p} =0.04). Dose of co-infecting parasite
is provided as a proportion of the maximum dose such that 1.0 is the
highest dose and 0.0 is a host singly infected with Ranavirus. Shown is
shown as a conditional plot displaying the expected value (dashed line),
a confidence interval for the expected value (gray band), and partial
residuals (points).

\textbf{Fig. 2} . The dose of Batrachochytrium dendrobatidis (Bd) was
negatively associated with \emph{Aplectana hamatospicula} load (\emph{p}
\textless{}0.001), whereas the dose of Ranavirus (Rv) was not
significantly associated with A. hamatospicula load (\emph{p} =0.22;
Dose x parasite identity: \selectlanguage{greek}χ\selectlanguage{ngerman}²\textsubscript{1}=17.2,\emph{p}
\textless{}0.001). Dose of co-infecting parasite is provided as a
proportion of the maximum dose. Shown are conditional plots displaying
the expected value (dashed line), a confidence interval for the expected
value (gray band), and partial residuals (points).

\textbf{Fig. 3.} All three parasites reduced host growth rate relative
to hosts that were not infected, but Bactrachochytrium dendrobatidis
(Bd) was the most virulent of the parasites, reducing host growth
significantly more than \emph{Aplectana hamatospicula} (Ah) or Ranavirus
(Rv). Shown are conditional plots displaying the expected value (dashed
line), a confidence interval for the expected value (gray band), and
partial residuals (points). Treatments that share letters are not
different from one another based on a Tukey HSD multiple comparison
test.

\textbf{Fig. 4.} Hosts exposed to \emph{Bactrochochytrium
dendrobatidis}(Bd) as the fixed-dose parasite had significantly reduced
survival relative to hosts exposed to \emph{Aplectana hamatospicula}
(Ah;\emph{p} \textless{}0.001), Ranavirus (Rv; \emph{p}
\textless{}0.001) or no parasite (Control; \emph{p} \textless{}0.001),
regardless of the identity or dose of the changing dose parasite.
Survival curves shown as median survival (solid line) with the
associated 95\% confidence interval (grey band).

\textbf{Fig. 5.} Tolerance (defined as less negative slopes between
parasite load and growth rate) of \emph{Batrachochytrium
dendrobatidis}(Bd) was associated negatively with the dose of Ranavirus
(Rv,\textbf{A} ), but positively with the dose of \emph{Aplectana
hamatospicula} (Ah, \textbf{B} ). Shown are the conditional plots
displaying the expected value (dashed line), a confidence interval for
the expected value (gray band), and partial residuals (points).\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image1/image1}

\end{center}
\end{figure}

\textbf{Fig. 1.}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image2/image2}

\end{center}
\end{figure}

\textbf{Fig. 2} .\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image3/image3}

\end{center}
\end{figure}

\textbf{Fig. 3.}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image4/image4}

\end{center}
\end{figure}

\textbf{Fig. 4.}\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/image5/image5}

\end{center}
\end{figure}

\textbf{Fig. 5.}

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

