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“Weight of evidence” as a tool for evaluating disease in wildlife: An example assessing parasitic infection in Northern bobwhite (Colinus virginianus)

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“Weight of evidence” as a tool for evaluating disease in wildlife: An example assessing parasitic infection in Northern bobwhite (Colinus virginianus)

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The potential of parasites to affect host abundance has been a topic of heated contention within the scientific community for some time, with many maintaining that issues such as habitat loss are more important in regulating wildlife populations than diseases. This is in part due to the difficulty in detecting and quantifying the consequences of disease, such as parasitic infection, within wild systems. An example of this is found in the Northern bobwhite quail (Colinus virginanus), an iconic game bird that is one of the most extensively studied vertebrates on the planet. Yet, despite countless volumes dedicated to the study and management of this bird, bobwhite continue to disappear from fields, forest margins, and grasslands across the United States in what some have referred to as “our greatest wildlife tragedy”. Here, we will discuss the history of disease and wildlife conservation, some of the challenges wildlife disease studies face in the ever-changing world, and how a “weight of evidence” approach has been invaluable to evaluating the impact of parasites on bobwhite in the Rolling Plains of Texas. Through this, we highlight the potential of using “weight of the evidence” to better understand the complex effects of diseases on wildlife and urge a greater consideration of the importance of disease in wildlife conservation.
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International Journal for Parasitology: Parasites and Wildlife 13 (2020) 27–37
Available online 31 July 2020
2213-2244/© 2020 The Authors. Published by Elsevier Ltd on behalf of Australian Society for Parasitology. This is an open access article under the CC BY-NC-ND
license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
“Weight of evidenceas a tool for evaluating disease in wildlife: An
example assessing parasitic infection in Northern bobwhite
(Colinus virginianus)
Cassandra Henry
1
, Matthew Z. Brym
1
, Kalin Skinner, Kendall R. Blanchard, Brett J. Henry,
Alyssa L. Hay, Jessica L. Herzog, Aravindan Kalyanasundaram, Ronald J. Kendall
*
Wildlife Toxicology Laboratory, Texas Tech University, Lubbock, TX, USA
ARTICLE INFO
Keywords:
Bobwhite
Conservation
Parasites
Weight of evidence
Wildlife disease
ABSTRACT
The potential of parasites to affect host abundance has been a topic of heated contention within the scientic
community for some time, with many maintaining that issues such as habitat loss are more important in regu-
lating wildlife populations than diseases. This is in part due to the difculty in detecting and quantifying the
consequences of disease, such as parasitic infection, within wild systems. An example of this is found in the
Northern bobwhite quail (Colinus virginanus), an iconic game bird that is one of the most extensively studied
vertebrates on the planet. Yet, despite countless volumes dedicated to the study and management of this bird,
bobwhite continue to disappear from elds, forest margins, and grasslands across the United States in what some
have referred to as our greatest wildlife tragedy. Here, we will discuss the history of disease and wildlife
conservation, some of the challenges wildlife disease studies face in the ever-changing world, and how a weight
of evidence approach has been invaluable to evaluating the impact of parasites on bobwhite in the Rolling
Plains of Texas. Through this, we highlight the potential of using weight of the evidenceto better understand
the complex effects of diseases on wildlife and urge a greater consideration of the importance of disease in
wildlife conservation.
1. Introduction to the history of disease in wildlife conservation
Aldo Leopold, considered by many as the father of wildlife man-
agement, penned that disease was underestimated in wildlife conser-
vation in his 1933 treatise Game Management, a work that would go
on to become a cornerstone for wildlife management in North America.
Now in 2020, with climate change, habitat degradation, invasive spe-
cies, and growing human populations eroding the wild heritage Leopold
sought so fervently to protect, these words are more pertinent than the
day they were written. Yet, it was only recently that wildlife diseases
became a New Frontierin conservation (Fagerstone, 2014; Friend,
2014), likely due to the persistent paradigm that diseases are a natural
regulatory mechanism of healthy populations with the ultimate outcome
being one in which the host was not harmed (Elton, 1931; Lack, 1954).
However, Leopold looked past this narrow view of diseases, stressing the
need to consider the effects of factors such as microbes, parasites, con-
taminants, malnourishment, and any combination thereof, a perspective
which was far ahead of its time. Today, prominent wildlife disease re-
searchers have adopted similar views, with Wobeser (2006) dening
disease as ‘‘any impairment that interferes with or modies the perfor-
mance of normal functions, including responses to environmental fac-
tors such as nutrition, toxicants, and climate; infectious agents; inherent
or congenital defects; or combinations of these factors’’. Hereafter, we
will use this denition of disease as it accounts for the complexity
associated with disease impacts on wildlife populations and may thus
provide greater insight into the topic.
However, the history of diseases in the United States is long and
varied (Fig. 1). Surges in disease reports, which were often initiated due
to mortality being large and conspicuous (Plowright, 1988), were typi-
cally followed by an initiative that addressed the disease because the
public demanded a response (Kadlec, 2002; Friend, 2014). Concerns for
disease would eventually wane as other concerns took precedence. For
example, people became more worried about chemical contaminants
and heart disease after Rachel Carson published the seminal book Silent
* Corresponding author.
E-mail address: Ron.Kendall@ttu.edu (R.J. Kendall).
1
These authors contributed equally to this work.
Contents lists available at ScienceDirect
International Journal for Parasitology: Parasites and Wildlife
journal homepage: www.elsevier.com/locate/ijppaw
https://doi.org/10.1016/j.ijppaw.2020.07.009
Received 24 June 2020; Received in revised form 27 July 2020; Accepted 27 July 2020
International Journal for Parasitology: Parasites and Wildlife 13 (2020) 27–37
28
Fig. 1. Timeline depicting the history of wildlife diseases in the United States: blue boxes are for disease reports and outbreaks, green for improvements to disease
research, and red for events that hindered disease research. Abbreviations: foot-and-mouth disease (FMD), Smoot-Hawley Tariff Act (SHTA), State-Federal Coop-
erative Brucellosis Eradication Program (SFCBER), Bear River Research Station (BRRS), Wildlife Disease Investigations Laboratory (WDIL), Southeastern Cooperative
Wildlife Disease Study (SCWDS), epizootic hemorrhagic disease (EHD), World Organisation for Animal Healths (OIE), National Wildlife Research Center (NWRC), U.
S. Fish and Wildlife Service (USFWS). References: 1. Antolin et al. (2002), 2. Creel (1941), 3. Anderson (1978), 4. Locke and Friend (1987), 5. McCoy and Chapin
(1912), 6. Wherry and Lamb (1914), 7. Meagher and Meyer (1994), 8. Clements (2007), 9, Bachrach (1968), 10. Busch and Parker (1972), 11. USFWS (1991), 12.
Tunnicliff and Marsh (1935), 13. Brooks and Buchanan (1970), 14. Elton (1931), 15. Brown (2007), 16. CDFW 2019, 17. Friend (2014), 18. SCWDS 2019, 19. Shope
et al. (1960), 20. Cohen (2000), 21. Cross et al. (2013), 22. Samuel et al. (2007), 23. Carvalho et al. (2017), 24. Dobson and Hudson (1986), 25. Jones et al. (2008),
26. Berger et al. (1998), 27. Laurance et al. (1996), 28. Collins and Crump (2009), 29. OIE 2008, 30. Voyles et al. (2015), 31. Fagerstone (2014), 32. USFWS (2016),
33. Scheele et al. (2019). (For interpretation of the references to colour in this gure legend, the reader is referred to the Web version of this article.)
C. Henry et al.
International Journal for Parasitology: Parasites and Wildlife 13 (2020) 27–37
29
Springin 1962 and the Surgeon General announced that we should
“close the book on infectious disease in 1969 (Cohen, 2000; Friend,
2014).
Despite this, progress has been made regarding wildlife disease
research and conservation, particularly considering that prior to 2000
wildlife diseases were largely ignored unless they affected game species
or livestock (Fagerstone, 2014; Cunningham et al., 2017; Preece et al.,
2017). For example, the lessons learned from chytridiomycosis, which
has been implicated in the decline or extinction of 501 amphibian spe-
cies (Scheele et al., 2019), facilitated a quicker response to white-nose
syndrome in bats, with the pathogen being identied and manage-
ment plans in place within four years (Voyles et al., 2015). Then in 2011,
the National Wildlife Research Center (NWRC) listed wildlife diseases as
a priority for the rst time on their research needs assessment (Tobin
et al., 2012; Fagerstone, 2014). Unfortunately, the wildlife diseases that
still gain the most attention either cause massive die-offs, affect game
species, domestic animals, or humans (Deem et al., 2001; Friend, 2014;
Polley and Thompson, 2015); meanwhile diseases with less obvious but
substantial effects are overlooked (Wobeser, 2006; Wood and Johnson,
2015). Moreover, the interactions between disease and other variables
are largely unknown, and while our understanding of the ecological
inuence of parasites has improved, it is still very much incomplete
(Hern´
andez and Peterson, 2007; Kendall et al., 2010; Tompkins et al.,
2011; Wood and Johnson, 2015).
The growing human presence has also been implicated in the spread
and proliferation of wildlife diseases through environmental contami-
nants, land use changes, shifts in animal populations, and climate
change (Daszak et al., 2000, 2001; Deem et al., 2001; Dobson and
Foufopoulos, 2001). Some of these factors, such as environmental con-
taminants, are directly correlated with intensication of wildlife dis-
eases (Boroˇ
skov´
a et al., 1995; Bichet et al., 2013), whereas others like
climate change have more insidious effects (Lafferty, 2009). In Table 1,
we provide a broad overview of the various ways in which human ac-
tivities may exacerbate the impact of wildlife diseases, citing specic
examples of each. While this overview is by no means a comprehensive
account of the subject, it serves to emphasize the potentially increased
ecological role of wildlife diseases, and heightened importance of dis-
ease management in the Anthropocene. This is especially true consid-
ering the potentially catastrophic effects of diseases may be obscured by
the intricate associations present in wild systems (McCallum, 2000;
Friend et al., 2001). But how then, do we approach the problem of
unraveling these complex interactions and determine the true impact of
diseases on wildlife?
2. Weight of evidence and its uses
In order to determine the ultimate impacts of diseases on wildlife, it
is necessary to assess specic effects on population attributes through
randomized and controlled studies. However, as discussed in the
previous section, the impacts of diseases are often discreet, dynamic,
and inuenced by multiple interacting variables. Furthermore, correla-
tive associations may be the only evidence that diseases are inuencing
a particular system and designing and implementation of empirical
studies to assess these impacts for every population potentially affected
by disease may not be possible. It is therefore necessary to determine
whether further study of a system potentially at risk of being compro-
mised by disease is needed.
Weight of evidence (WOE) is “… an inferential process that assem-
bles, evaluates, and integrates evidence to perform a technical inference
in an assessmentused by the U.S. Environmental Protection Agency for
a variety of assessments (Suter et al., 2017). The WOE approach is also
effective for evaluating scenarios post hoc, where data is typically limited
and/or only correlative (Forbes and Calow, 2002). Consequently, WOE
may provide a valuable tool to investigate other multivariate problems
outside of risk assessment, such as determining the causes of wildlife
population declines. Adaptations of WOE have been effectively used in
this regard by researchers investigating the effects of multiple stressors
on aquatic systems (Lowell et al., 2000; Adams, 2005; Burkhardt-Holm
and Scheurer, 2007).
For instance, Burkhardt-Holm and Scheurer (2007) employed a WOE
approach to identify potential causes for the decline in brown trout
(Salmo trutta) by using an adaptation of the WOE framework developed
by Forbes and Calow (2002). In this, they used a series of 7 questions to
assess the plausibility, exposure, correlation, threshold, specicity, ex-
periments, and then removal of the variable of interest. These 7 ques-
tions promote a rigorous way of evaluating data that does not discount
the plausibility of factors for which there may be only limited and/or
correlative data. This method allowed Burkhardt-Holm and Scheurer
(2007) to overcome uncertainty and confounding variables to positively
identify proliferative kidney disease as the most likely cause of brown
trout declines in half of their study areas. However, despite the success
of WOE based studies in assessing population stressors in aquatic sys-
tems, to our knowledge, similar evaluations are lacking in terrestrial
environments, which are also subject to an array of complex and vari-
able stressors.
Here, the seven questions proposed by Burkhardt-Holm and Scheurer
(2007) (Fig. 2a) were modied to specically address disease(s) in
wildlife populations (Fig. 2b). The original questions were robust and
widely applicable, and this allowed us to adhere closely to the original
framework, with 1 question remaining unchanged and 4 others only
being rephrased to incorporate the disease aspect. However, 2 of the
questions were modied to better evaluate the potential impacts of
diseases given the complex nature and specic characteristics of the
topic. Namely, thresholds of infection in diseases are often difcult to
discern and concrete thresholds are typically unavailable. Thus, ques-
tion 4 is now used to determine whether there is an apparent threshold
in which the disease elicits an observable or quantiable response in the
individual host, and this leads to question 5, which considers if this
Table 1
Examples for various anthropogenic factors and their inuence on wild systems.
Organism Anthropogenic Factor Result Reference
Sparrows Pollution Trace metals increase susceptibility to malaria Bichet et al. (2013)
Rats Pollution Chronic exposure to lead at low concentrations leads to immunosuppression Bendich et al. (1981)
Timber rattlesnakes Habitat
fragmentation
Inbreeding depression and pathogenic fungal outbreak Clark et al. (2011)
Lesser Antillean
bullnch
Habitat
fragmentation
Increased prevalence of two blood parasites Perez-Rodriguez et al., 2018
Bumble bees Habitat
fragmentation
Decreased genetic diversity and increased pathogen prevalence Cameron et al. (2011)
Christmas Island rat Animal translocation Introduction of black rats causes outbreak of trypanosomiasis and eventual
extinction
Wyatt et al. (2008)
Bighorn sheep Introduced diseases Livestock diseases hinder conservation efforts due to lack of resistance in bighorn
sheep
Singer et al. (2001); Clifford et al.
(2009)
Harbor seals Climate change Migratory changes in harp seals cause exposure to phocine distemper virus Jensen et al. (2002)
Great pond snail Climate change High ambient temperatures cause reduced immune defense Sepp¨
al¨
a and Jokela, 2010
C. Henry et al.
International Journal for Parasitology: Parasites and Wildlife 13 (2020) 27–37
30
Fig. 2. Flow diagrams showing a weight of evidence framework using the (A) 7 questions proposed by Burkhardt-Holm and Scheurer (2007) and the (B) modied
questions for addressing disease(s) in wildlife.
C. Henry et al.
International Journal for Parasitology: Parasites and Wildlife 13 (2020) 27–37
31
effect may be impactful at the population level. Structuring the ques-
tions in this way permits a better evaluation of the impacts a disease may
have on a populations as highly pathogenic diseases present at a low
frequency may have less of an impact on a population than a widespread
disease with subtle symptoms (McCallum and Dobson, 1995).
3. Bobwhite, their decline, and the possible role of parasites
Bobwhite are an iconic species and one of the most extensively
studied and heavily managed gamebirds (Rosene, 1969; Scott, 1985;
Hern´
andez et al., 2013). While bobwhite declines have been noted since
the late 1800s (Stoddard, 1931; Rosene, 1969), systematic surveys of
bird abundance in the 1960s reinforced the severity and signicance of
these declines (Sauer et al., 2013), as did documentation of widespread
localized extinctions of bobwhite (Brennan et al., 2007; Palmer et al.,
2012). This has led to a great deal of effort to determine and mitigate
factors contributing to bobwhite declines, and many consider habitat
loss and degradation to be the primary threat to bobwhite across their
range (Palmer et al., 2012; Hern´
andez et al., 2013). However, bobwhite
are also inuenced by other factors, including predation (Rollins and
Carroll, 2001), weather (Lusk et al., 2002), contaminants (Ertl et al.,
2018), diseases (Peterson, 2007), and climate change (Guthery et al.,
2000), which interact to exert a cumulative effect on bobwhite pop-
ulations (Hern´
andez and Peterson, 2007; Hern´
andez et al., 2013).
While bobwhite have been undergoing a general decline since the
late 1800s, more recently, researchers have documented bobwhite
populations faltering in places that have long been considered strong-
holds for the species (Brennan et al., 2007; Rollins, 2007). One of
these areas is the West Texas Rolling Plains, a region where the domi-
nant land use type (rangeland) is conducive to quail management and
where land may often be managed for bobwhite (Rollins, 2007;
Hern´
andez and Guthery, 2012). Despite this, in 2010 bobwhite pop-
ulations in the Rolling Plains failed to irrupt during a year where plen-
tiful rainfall and quality habitat led to predictions of a quail boom. This
led to the launch of Operation Idiopathic Decline (OID), a collaborative
research effort to investigate the impact of contaminants and diseases on
bobwhite from the region. During OID, researchers from major Texas
universities collaboratively surveyed bobwhite in the Rolling Plains and
found a high prevalence of eyeworms (Oxyspirura petrowi) and caecal
worms (Aulonocephalus pennula; =A. lindquisti), with infection rates as
high as 66% and 91%, respectively (Bruno, 2014).
Even though this was not the rst time these parasites had been re-
ported in bobwhite from the Rolling Plains (Jackson and Green, 1965;
Jackson, 1969), OID marked the beginning of a determined investiga-
tion into the potential of parasitic infection to affect bobwhite in the
area. Prior to OID, diseases, including parasites, were generally viewed
as inconsequential in terms of bobwhite management (Stoddard, 1931;
Rollins, 2002; Peterson, 2007), despite some researchers arguing for a
greater consideration of their impacts (Robel, 1993; Brennan, 2002;
Peterson, 2007). This perspective set the paradigm for bobwhite con-
servation, and to this day, habitat and land management practices are
the predominant means of maintaining local bobwhite populations
(Hern´
andez and Guthery, 2012). However, even in areas where habitat
is carefully and specically managed for quail, such as the Rolling Plains
Quail Research Ranch (RPQRR), bobwhite populations continue to
follow the boom and bust cycles characteristic of the species (Thog-
martin et al., 2002; Rollins, 2018; Texas Parks and Wildlife Department ,
2019). While proper habitat management is a foundation for successful
bobwhite conservation, the cause of bobwhite population uctuations
remains undetermined (Guthery, 2002; Hern´
andez et al., 2002) and
bobwhite continue to experience a range-wide decline (Sauer et al.,
2013). This suggests that additional factors are inuencing bobwhite
abundance, and it is possible that parasites have a greater effect on
bobwhite populations than previously purported.
4. Using the WOE framework to investigate the role of parasites
in the bobwhite decline
Using a WOE approach that integrates data from eld and laboratory
studies, augmented by the observations and collaboration of local
landowners and quail hunters, may yield a more comprehensive un-
derstanding of how parasites affect bobwhite population dynamics. This
method is employed by the Wildlife Toxicology Laboratory (WTL) at
Texas Tech University when investigating the implications of O. petrowi
and A. pennula in bobwhite of the Rolling Plains. Oxyspirura petrowi and
A. pennula are parasitic nematodes that infect the eyes and caeca,
respectively, of their denitive hosts, and undergo an indirect life cycle
requiring an insect intermediate host for transmission (Chandler, 1935;
Addison and Anderson, 1969; Peterson, 2007). This indirect life cycle
further exacerbates the already complex task of understanding the
consequence of infection, making the WOE approach particularly valu-
able in this instance.
We compiled what was, to our knowledge, all available information
regarding A. pennula and O. petrowi in bobwhite. We then subjected this
information to the series of 7 questions discussed in section 2. In doing
so, we can establish whether the research conducted thus far holds
enough weight to warrant continued investigations into this issue and
demonstrate the value of a WOE approach. We begin by addressing the
rst of the 7 fundamental questions, that of plausibility.
4.1. Question 1: Does the proposed impact of the disease(s) make sense
logically and scientically?
In 1979, Anderson and May provided the theoretical justication for
the ability of parasites to suppress host abundance to the extent in which
this results in cyclical uctuations of host populations (Anderson and
May 1979; May and Anderson, 1979). Since then, our understanding of
host parasite interactions has advanced from this theoretical foundation,
to one in which parasites are increasingly recognized for their potential
to affect hosts at the population scale and higher, even when the effects
are not immediately apparent (Tompkins et al., 2011). This increasing
recognition of parasites as a mechanism affecting host population dy-
namics is mirrored with regards to the effects of parasites on bobwhite in
the Rolling Plains ecoregion of West Texas.
While parasites have long been known to infect bobwhite of the
Rolling Plains, their signicance in terms of bobwhite conservation has
remained largely obscure. However, contemporary investigations of
parasites in the region have revealed epizootic events, a high preva-
lence, and the potential of two helminths, A. pennula and O. petrowi,
contributing to the declines of local bobwhite populations (Bruno, 2014;
Dunham et al., 2014a; Bruno et al., 2019a). Evidence exists of parasites
like Loa and Thelazia callipaeda, which are closely related to O. petrowi
(Xiang et al., 2013; Kalyanasundaram et al., 2018a), causing irritation
and impaired vision in their hosts (Otranto et al., 2004; Barua et al.,
2005; Nayak et al., 2016). Moreover, Kalyanasundaram et al. (2018a)
determined A. pennula to have a 90% relation to the ascarids, specically
Toxascaris leonine which is common parasite of cats and dogs that is
known to cause nutrient loss, weight loss, and death (Kalyanasundaram
et al., 2017).
In birds, similar intestinal parasites have also been documental to
cause inactivity, weight loss, growth reduction, and inammation of the
caecal mucosa in infected individuals (DeRosa and Shivaprasad, 1999;
Vandegrift et al., 2008; Nagarajan et al., 2012). Field studies have
demonstrated the capacity of parasites to exhibit effects on hosts at the
population level as well, as in the case of the caecal worm, Trichos-
trongylus tenuis, which suppressed populations of another Galiforme, the
red grouse (Lagopus scoticus), by reducing fecundity and increasing
susceptibility to predators (Hudson, 1986; Hudson et al., 1992, 1998).
As such, the potential of parasites to induce population decline in
bobwhite quail is being increasingly recognized as a plausible threat
which necessitates further investigation.
C. Henry et al.
International Journal for Parasitology: Parasites and Wildlife 13 (2020) 27–37
32
4.2. Question 2: Is there evidence that the population of interest is, or has
been exposed to the disease(s)?
The rst reported evidence of parasites in bobwhite from the Rolling
Plains of Texas came in the 1940s, when Webster and Addis (1945)
documented a number of parasites, including caecal worms (A. lind-
quisti). Further study into the parasite fauna of bobwhite in the Rolling
Plains did not occur until the 1960s, when Jackson and Green (1965)
conducted more rigorous assessments and found A. pennula and O. pet-
rowi to be relatively common in the regions quail. With the exception of
studies conducted by Rollins (1980) and Demarais et al. (1987) in the
late 1970s and early 1980s, research into parasitic infection of bobwhite
in Texas waned once again, until over 50 years later.
Villarreal et al. (2012) renewed the investigations into the O. petrowi
that infect bobwhite, nding 57% of bobwhite to be infected from 2007
to 2011, and during sampling from February 2010January 2011, 82%
of bobwhite were infected with A. pennula (Villarreal et al., 2016).
Additionally, OID sparked a proliferation of studies investigating the
impacts of parasites on bobwhite of the Rolling Plains and South Texas,
and these studies have documented A. pennula and O. petrowi to be
ubiquitous in quail throughout the region (Dunham et al., 2016a; Olsen
and Fedynich, 2016). In subsequent studies, Bruno et al. (2019b) found
40% of bobwhite sampled from 2011 to 2013 to be infected with O.
petrowi, while 73% were infected with A. pennula. However, Dunham
et al. (2014a) suspected previous surveys underreported eyeworm
prevalence as those studies only examined the nictitating membrane and
the surface of the eye. By examining eye-associated tissues as well,
Dunham et al. (2014a) found 97% of bobwhite infected with O. petrowi.
Today, the Rolling Plains is considered to be the epicenter of caecal
worm and eyeworm infection in bobwhite (Kubeˇ
cka et al., 2017), and
surveys regularly yield infection rates approaching 100% with infection
levels averaging >400 A. pennula and >30 O. petrowi (Henry et al., 2017;
Brym et al., 2018b; RPQRF, 2019).
Oxyspirura petrowi have also been documented in wild turkey
(Meleagris gallopavo; Kubeˇ
cka et al., 2018), songbirds (Dunham and
Kendall, 2014), lesser prairie-chickens (Tympanuchus pallidicinctus;
Dunham et al., 2014b), Gambels (Callipepla gambelii), and scaled quail
(Callipepla squamata) (Dunham and Kendall, 2017), while A. pennula
have been found in scaled quail (Dunham et al., 2017a) and wild turkey
(Hon et al., 1975). The wide range of hosts for O. petrowi and A. pennula
highlights the possibility that these parasites may be more widely
distributed that previously thought, and if bobwhite populations recover
the parasites may remain in reservoir hosts and be capable of infecting
bobwhite in the future.
4.3. Question 3: Is there evidence that the disease(s) is associated with
adverse effects in the population in either time or space?
Because wild bobwhite populations in the Rolling Plains are under
constant and simultaneous exposure to a variety of dynamic and inter-
acting stressors, determining a causative link between disease and its
effect(s) on bobwhite populations may be extremely difcult. Conse-
quently, correlative associations may provide a more pragmatic alter-
native into potential interactions as these may be the only available
evidence in these circumstances. Correlative associations are typically
supported by models of parasite induced host mortality (PIHM), which
predict lower parasite burdens in surviving hosts due to the concurrence
of host mortality and infection intensity (Wilber et al., 2016). However,
Wilber et al. (2016) cautioned that models alone do not provide
conclusive evidence of PIHM but should instead be used as a supplement
to experimentation and a comprehensive understanding of parasite host
interactions. Thus, we must also consider the cumulative effect of these
parasites in order to obtain a clearer picture of the parasitic pressurea
host may be facing (Bordes and Morand, 2009).
For instance, heavy precipitation during 2016 (RPQRF, 2016) led to
favorable conditions for the arthropod intermediate hosts of O. petrowi
and A. pennula (Branson, 2014; Kistler et al., 2016a; Almas et al., 2018;
Henry et al., 2018, 2020), which coupled with high bobwhite pop-
ulations (TPWD, 2019), created an environment rich in both interme-
diate and denitive hosts, an ideal situation for the proliferation of
parasites (Sures and Streit, 2001; Liccioli et al., 2014). This may have
facilitated the transmission of parasites leading to the increased infec-
tion levels of both O. petrowi and A. pennula during the spring of 2017
(Henry et al., 2017). The increased intensity of the parasites was
concomitant with greater difculty trapping bobwhite, and then a sub-
sequent die-off of bobwhite that was speculated to be due to PIHM.
Following the hunting season of 20172018, Brym et al. (2018c) also
reported difculty in trapping bobwhite, reinforcing previous reports
suggesting a scarcity of birds that may have resulted from the consis-
tently elevated parasite burdens documented throughout the region.
Commons et al. (2019) likewise documented difculty trapping amidst
high parasite burdens compared with previous years. This scarcity of
birds was found throughout the region when TPWD (2019) reported the
third lowest amount of bobwhite seen since 1978 in 2018, leading to
concern for localized extinctions of bobwhite. Ultimately, there appears
to be a correlation between high parasite burdens and reduced bobwhite
abundance, and this link needs to be investigated further.
4.4. Question 4: Does the disease(s) appear to have a biologically
meaningful threshold beyond which there is an observable/quantiable
response in the host?
While the widespread incidence of O. petrowi in the Rolling Plains
may have exposed a large proportion of bobwhite to infection, it is also
important to consider the intensity of these infections, as even highly
pathogenic organisms may have negligible effects on their hosts if pre-
sent only in low numbers (Fredensborg et al., 2004). Consequently,
Dunham et al. (2017a) developed infection level thresholds to provide a
systematic way of gauging the intensity of parasitic infection in
bobwhite; during which, a large proportion of bobwhite (48%) were
found to have lower eyeworm infections (<20 O. petrowi), while rela-
tively few (15%) were heavily parasitized (>40 O. petrowi). Dunham
et al. (2017a) hypothesized that this was due to highly infected in-
dividuals suffering reduced tness, which ultimately led to mortality,
and this is consistent with models of populations experiencing PIHM
discussed in section 4.3.
The hypothesis of Dunham et al. (2017a) is further supported as
throughout 2017 heavy parasite burdens were documented in bobwhite
that landowners observed ying into obstacles, being taken by preda-
tors, and two specimens that were hand captured (Brym et al., 2018a).
These anecdotal accounts of parasitized bobwhite exhibiting signs of
potential visual impairment parallel reports by Jackson (1969), who was
the rst to report such behavior in parasitized bobwhite. There was also
a bobwhite that was hand captured during the 20172018 hunting
season was severely emaciated and possessed an extreme caecal worm
infection (n =1722) (Brym et al., 2018c). Collection of a bobwhite with
such a high parasite load was unusual, as Dunham et al. (2017a) found
50% of bobwhite with <100 A. pennula and only 19% with >200, and
the high infection may have contribute to the birds condition given that
pathological changes were noted in the caeca of scaled quail infected
with >100 caecal worms (Rollins, 1980).
Hunters from the Rolling Plains continued to donate parasitized
bobwhite during the 20172018 hunting season, in which the highest
average intensities of both O. petrowi (n =44) and A. pennula (n =599)
were recorded (Brym et al., 2018b). This sample also exhibited an
increased proportion of birds in the strong and extreme infection level
range when compared to earlier surveys of parasites. Towards the end of
the hunting season, hunters began reporting fewer coveys and more
feather piles indicating predation that coincided with consistently
elevated parasites burdens (Brym et al., 2018c). Moreover, Kalyana-
sundaram et al. (2018b) documented an increase in Physaloptera sp. In
bobwhite infected with A. pennula and O. petrowi, leading them to
C. Henry et al.
International Journal for Parasitology: Parasites and Wildlife 13 (2020) 27–37
33
postulate that bobwhite with high levels of these parasites may be more
susceptible to co-infection with other helminths. These reports suggest
that at strong and extreme levels of infection a threshold is reached in
which bobwhite survival may be reduced and/or bobwhite become
immunocompromised.
4.5. Question 5: Does the individual response elicited by the disease(s)
extend to a quantiable impact on the host population?
Anecdotal accounts of eyeworm infected bobwhite from the Rolling
Plains exhibiting erratic behavior (Jackson, 1969) spurred concerns that
these parasites may be causing visual impairment by damaging struc-
tures within the eyes of infected individuals. Later, researchers con-
ducted pathological assessments of the eyes of infected bobwhite and
conrmed inammation and damage to the eye tissues and cornea of
bobwhite hosts, as well as hemorrhaging of nasolacrimal ducts (Bruno
et al., 2015; Dunham et al., 2015, 2016b; Hunter, 2016). Because
bobwhite are highly dependent on their sense of vision when foraging,
navigating their environment, and evading predators, the potential ef-
fects of impaired vision may be substantial. However, currently it is
unknown precisely how eyeworm infection impacts the visual acuity of
infected bobwhite and how this may impact their interaction with and
ability to survive in the environment. Although pathological evidence
suggests that damage is occurring and is supported by anecdotal ac-
counts of impaired vision in quail infected with O. petrowi (Brym et al.,
2018a, 2018c), additional research is necessary in order to evaluate the
effect of O. petrowi on bobwhite vision and overall impact it could have
on a population.
Caecal worm infections have also been correlated with negative
impacts on bobwhite. For example, Dunham et al. (2017b) demon-
strated that birds with A. pennula are often found with only minimal
amounts of digesta in the caeca, while Lehmann (1953, 1984) associated
high burdens with lower levels of vitamin A and drought. These obser-
vations led the researchers to postulate that caecal worm infection could
reduce feed intake, impede digestion, and exacerbate periods of stress,
which are commonly associated with intestinal parasites (Petkeviˇ
cius,
2007). Due to the important functions of the avian caecum, such as
nutrient and water absorption, antibody production, and cellular
digestion (Clench and Mathias, 1995), disruption to its function may
indeed exacerbate periods of stress for bobwhite, such as drought and
food scarcity. In addition to being coincident with periods of low pre-
cipitation, caecal worm infections are also known to peak in winter
(Lehmann, 1953; Rollins, 1980; Blanchard et al., 2019), and both of
these periods typically result in high mortality for bobwhite (Hern´
andez
et al., 2005; Hern´
andez and Peterson, 2007). Furthermore, the effects of
A. pennula may not only be limited to survivability, but these worms
could also impede the breeding potential of bobwhite by reducing the
availability of vitamin A, a key nutrient for reproduction and survival
(Nestler, 1946), as well as diverting resources from reproduction. As
such, A. pennula may have the potential to impact bobwhite populations
through reduced survival and fecundity, although additional research is
needed to evaluate this potential impact at the population level.
4.6. Future work to address questions 6 and 7
While further studies are needed to determine if parasitic infection
elicits other specic biological effects in bobwhite and whether they
have a measurable impact at the population level, the WOE framework
accounts for the well-known difculty in determining these questions in
a wild system. This allows us to move to questions 6 and 7 in the
framework. Question 6 evaluates observed or specic effects that have
been documented in the laboratory. Currently, laboratory experiments
are underway, and the infection of bobwhite with O. petrowi in the
laboratory has been completely worked out, from intermediate host to
denitive host (Kalyanasundaram et al., 2019a). Challenge experiments
have also been conducted, which determined that eyeworm and caecal
worm glycoproteins elicit an immune response in bobwhite (Kalyana-
sundaram et al., 2019b), and O. petrowi can cause oxidative stress and
mount an immune response (Hunter, 2016). Multiple studies are in
development to better understand how parasites affect bobwhite
including: studies to replicate the life cycle of A. pennula within the
laboratory; studies to investigate the biological responses that O. petrowi
and A. pennula may elicit in bobwhite; and experiments to assess impacts
on the health and tness of infected individuals.
Finally, in regards to question 7, which entails assessing the response
of the bobwhite populations to the removal of parasites, eld studies as
those conducted by Hudson et al. (1998) on red grouse provide a model
for future work. However, the empirical studies by Hudson (1986) and
Hudson et al. (1992, 1998) investigating the potential of parasites to
affect population dynamics of red grouse took over 20 years to complete
and utilized a medicated grit. Studies such as these are currently hin-
dered as there are currently no anthelmintics registered for use in wild
bobwhite in the United States (Needham et al., 2007). Therefore,
experimental manipulation studies must await registration of a treat-
ment for wild bobwhite.
Nevertheless, a great deal of progress has been made to pave the way
for future work investigating the interactions between bobwhite and
parasites. Molecular techniques have been developed in order to non-
lethally assess parasitic infection in bobwhite via a cloacal swab or
feces sample that is evaluated by quantitative PCR (qPCR) and can
detect the DNA for as little as one egg (Kistler et al., 2016b; Kalyana-
sundaram et al., 2018c). These methods were then adapted for use at a
regional scale (Blanchard et al., 2018), as they are considered an
effective form of parasite monitoring (Gray et al., 2012) that provides a
valuable supplement to traditional methods (Archie et al., 2009). This
will be benecial for long term studies to non-lethally evaluate the ef-
fects of these parasites at the population level. Molecular techniques
may also be useful in understanding the transmission dynamics of par-
asites, which are often inuenced by climate (Harvell et al., 2002;
Benton et al., 2015). For example, Blanchard et al. (2019) used qPCR
and climatic variables to determine that temperature and precipitation
could inuence eyeworm and caecal worm egg shedding in bobwhite.
5. Conclusions
There is still much research needed to determine the full conse-
quences of O. petrowi and A. pennula on bobwhite, particularly since the
interactions of multiple parasites is understudied and not well under-
stood (Pedersen and Fenton, 2007; Bordes and Morand, 2011). How-
ever, this WOE based approach reveals that parasites should be
investigated further as they likely play a larger role in regulating
bobwhite populations than previously thought. By using WOE, the
pieces can begin to be assimilated and potential interactions may
become evident (Fig. 3). This would be invaluable to studies of wildlife
disease where it is impossible to control all factors and where disease
effects can be abstruse (May, 1988; Woolf et al., 1993).
The proliferation and impacts of disease amidst widespread and
rapid global change involve overarching, interrelated, and complex
processes, which may test the bounds of traditional methods of inquiry
(Plowright et al., 2008). In this ever-changing world, conventional
strategies for quail management, as well as the management of other
species, may be insufcient (Deem et al., 2001; Palmer et al., 2012), and
crisis management is not suitable for conserving a species either (Plo-
wright, 1988; Friend, 2014; Grant et al., 2017). Instead, multidisci-
plinary approaches are necessary and should be used when addressing
disease and conservation of a species (Daszak et al., 2000; Deem et al.,
2001; Plowright et al., 2008; Hoverman and Searle, 2016).
Thus, we suggest that WOE is a valuable tool for identifying potential
instances of signicant disease impacts. Although the WOE approach
cannot answer all the questions of how a disease impacts a wild popu-
lation, disease management requires acting with imperfect informa-
tion(Grant et al., 2017), and WOE provides an effective means of
C. Henry et al.
International Journal for Parasitology: Parasites and Wildlife 13 (2020) 27–37
34
investigating multiple lines of evidence in a systematic manner. How-
ever, WOE is not a replacement for empirical studies and should be used
to identify whether it is worthwhile to move forward with empirical
studies that are often logistically difcult in wild populations. Following
identication of a problem using WOE, empirical study and an active
adaptive management strategy could be adopted for more complete
insight into the complex nature of wildlife systems. This will help ach-
ieve immediate management needs while gaining knowledge that is
benecial to developing robust long-term strategies (McDonald-Madden
et al., 2010).
Declaration of competing interest
The authors declare no conict of interest.
Acknowledgements
We are grateful to the Park Cities Quail Coalition, USA (24A125),
Rolling Plains Quail Research Foundation, USA (23A582), and land-
owners for the continued support and funding that make this research
possible. We also thank Wildlife Toxicology Laboratory members for
their contribution to this work.
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... A WOE assessment can be used to investigate impacts from known agents on targets of concern by systematically examining multiple lines of evidence to identify potential causal factors in complex and noisy data (Forbes and Calow 2002). This approach has been applied to parasite-host interactions to implicate the causative agent of proliferative kidney disease (Tetracapsuloides bryosalmonae) in the decline of brown trout populations (Burkhardt-Holm and Scheurer 2007) and to evaluate the impact of parasites on northern bobwhite quail (Colinus virginanus) (Henry et al. 2020). Typically, WOE assessments are applied retrospectively after a source of exposure has been identified, a known exposure has occurred, and adverse impacts have been observed in a target of concern (Suter 1993;Forbes and Calow 2002). ...
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The Northern bobwhite quail (Colinus virginianus) is a popular game bird that has been experiencing a well-documented decline throughout Texas since the 1960s. While much of this decline has been attributed to habitat loss and fragmentation, recent studies have identified other factors that may also contribute to decreasing quail populations. Parasites, in particular, have become increasingly recognized as possible stressors of quail, and some species, particularly the eyeworm (Oxyspirura petrowi) and cecal worm (Aulonocephalus pennula) are highly prevalent in Texas quails. Eyeworm infection has also been documented in some passerines, suggesting helminth infection may be shared between bird species. However, the lack of comprehensive helminth surveys has rendered the extent of shared infection between quail and passerines in the ecoregion unclear. Thus, helminth surveys were conducted on bobwhite, scaled quail (Callipepla squamata), Northern mockingbirds (Mimus polyglottos), curve-billed thrashers (Toxistoma curvirostre), and Northern cardinals (Cardinalis cardinalis) to contribute data to existing parasitological gaps for birds in the Rolling Plains ecoregion of Texas. Birds were trapped across 3 counties in the Texas Rolling Plains from March to October 2019. Necropsies were conducted on 54 individuals (36 quail and 18 passerines), and extracted helminths were microscopically identified. Nematode, cestode, and acanthocephalan helminths representing at least 10 helminth species were found. Specifically, A. pennula and O. petrowi had the highest prevalence, and O. petrowi was documented in all of the study species. This research adds to the body of knowledge regarding parasitic infections in quail and passerines of the Rolling Plains ecoregion and highlights the potential consequences of shared infection of eyeworms among these bird species.
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The northern bobwhite quail (Colinus virginianus) is a popular gamebird in the Rolling Plains Ecoregion of West Texas. However, there has been a population decline in this area over recent decades. Consistent reports indicate a high prevalence of the eyeworm (Oxyspirura petrowi) and caecal worm (Aulonocephalus pennula), which may be of major influence on the bobwhite population. While research has suggested pathological consequences and genetic relatedness to other pathologically significant parasites, little is known about the influence of climate on these parasites. In this study, we examined whether seasonal temperature and precipitation influences the intensity of these parasites in bobwhite. We also analyzed quantitative PCR results for bobwhite feces and cloacal swabs against temperature and precipitation to identify climatic impacts on parasite reproduction in this region. Multiple linear regression analyses were used for parasite intensity investigation while binary logistic regression analyses were used for parasite reproduction studies. Our analyses suggest that caecal worm intensity, caecal worm reproduction, and eyeworm reproduction are influenced by temperature and precipitation. Temperature data was collected 15, 30, and 60 days prior to the date of collection of individual bobwhite and compared to qPCR results to generate a temperature range that may influence future eyeworm reproduction. This is the first preliminary study investigating climatic influences with predictive statistics on eyeworm and caecal worm infection of northern bobwhite in the Rolling Plains.
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