Journal of Threatened
Taxa | www.threatenedtaxa.org | 26 January 2026 | 18(1): 28151–28166
ISSN 0974-7907 (Online) | ISSN 0974-7893 (Print)
https://doi.org/10.11609/jott.9725.18.1.28151-28166
#9725 | Received 28 February 2025 | Final received 31 October 2025 |
Finally accepted 31 December 2025
Biological validation of fecal
glucocorticoid and triiodothyronine measures in free-ranging Golden-headed Lion
Tamarins (Kühl, 1820), (Mammalia: Primates: Callitrichidae: Leontopithecus
chrysomelas): effects of the stress of capture and body condition
Roberto Fiorini-Torrico 1 ,
Leonardo de Carvalho Oliveira 2 , Damián Escribano 3 ,
José Joaquín Cerón 4 & Kristel Myriam de Vleeschouwer
5
1,2 Programa de Pós-graduação em
Ecologia e Conservação da Biodiversidade, Applied Ecology and Conservation Lab,
Universidade Estadual de Santa Cruz, Rod. Jorge Amado km. 16, 45662-900 Ilhéus,
BA, Brazil.
1,5 Centre for Research and Conservation,
Royal Zoological Society of Antwerp, Koningin Astridplein 26, B-2018 Antwerp,
Belgium.
2 Departamento de Ciências,
Faculdade de Formação de Professores, Universidade do Estado do Rio de Janeiro,
R. Francisco Portela 1470, 24435-005 São Gonçalo, RJ, Brazil.
2 Bicho do Mato Instituto de
Pesquisa, Av. Cônsul Antônio Cadar 600, 30360-082 Belo Horizonte, MG, Brazil.
3,4 Interdisciplinary Laboratory of
Clinical Analysis of the University of Murcia (Interlab-UMU), Regional, Campus
of International Excellence ‘Campus Mare Nostrum’, University of Murcia, Campus
de Espinardo s/n, 30100 Murcia, Spain.
1 beto.torrini@gmail.com
(corresponding author), 2 leonardoco@gmail.com, 3 det20165@um.es,
4 jjceron@um.es, 5 kristel.devleeschouwer@kmda.org
Editor: Aniruddha Belsare,
Auburn University, Albama, USA. Date of publication: 26 January 2026 (online & print)
Citation:
Fiorini-Torrico, R., L. de C. Oliveira, D. Escribano, J.J. Cerón & K.M. de
Vleeschouwer (2026). Biological validation of fecal glucocorticoid and
triiodothyronine measures in free-ranging Golden-headed Lion Tamarins (Kühl,
1820), (Mammalia: Primates: Callitrichidae: Leontopithecus chrysomelas):
effects of the stress of capture and body condition. Journal of Threatened Taxa 18(1): 28151–28166. https://doi.org/10.11609/jott.9725.18.1.28151-28166
Copyright: © Fiorini-Torrico et al. 2026. Creative Commons Attribution 4.0 International License.
JoTT allows unrestricted use, reproduction, and distribution of this article in
any medium by providing adequate credit to the author(s) and the source of
publication.
Funding:
This study received financial
support from the Centre for Research and Conservation of the Royal Zoological
Society of Antwerp through the Flemish Ministry of Economy, Science and
Innovation (R. Fiorini-Torrico’s doctoral scholarship and logistic field support), and from the Rufford Foundation (Rufford Small Grant No.
29410-1).
Competing interests: The authors declare no competing interests.
Author details, Author
contributions & Acknowledgments: See end of this article.
Author details: R. Fiorini-Torrico was a PhD student in the
Postgraduate Program in Ecology and Conservation Biology (PPGECB) at the State
University of Santa Cruz. He is currently a postdoctoral researcher at the same
institution and the research coordinator of Project
BioBrasil. L.C. Oliveira is an adjunct professor in the
Science Department at the State University of Rio de Janeiro and an associate
professor in PPGECB. D. Escribano is a postdoctoral researcher in the
Animal Production Department and the Interdisciplinary Laboratory of Clinical
Analysis (Interlab-UMU) at Murcia University. J.J. Cerón is a full professor in the Animal
Medicine and Surgery Department at Murcia University and
the leader of Interlab-UMU. K.M. De Vleeschouwer is a senior research coordinator
at the Antwerp ZOO Centre for Research and Conservation (CRC) and the director
of Project BioBrasil.
Author contributions: R. Fiorini-Torrico conceptualized the research
goals, collected the samples and data, conducted the formal analysis, and wrote
and edited the manuscript. L.C. Oliveira supervised the project execution and
provided critical reviews and commentary. D. Escribano contributed to lab
analysis, supervised sample collection and lab
techniques, and reviewed and commented on the manuscript. J.J. Cerón supervised
lab work, provided essential lab resources, and offered critical reviews and
suggestions. K.M. De Vleeschouwer supervised research activities, provided necessary field resources, and reviewed and commented on the
manuscript.
Acknowledgments: The authors thank Dr. Laurence
Culot and Dr. Marina Salas for their valuable input on earlier drafts of this
manuscript. They also thank Project BioBrasil and the involved
private owners, Interlab-UMU, the Applied Ecology and Conservation Lab (LEAC),
and the Bicho do Mato Research Institute for supporting this project. Finally,
they thank Igor Inforzato, Sofia Bernal and Camila Andrade for their crucial
help with sample and data collection during captures.
Abstract: Glucocorticoids (GCs) and thyroid hormones
(THs), along with other physiological mediators, modulate the responses that
allow lifelong adaptation to predictable and unpredictable environmental
challenges. This has sparked the interest of primatologists who, with the
advent of non-invasive sampling techniques, have been able to investigate
changes in GCs and, more recently, THs under field conditions. These techniques
need a validation process to ensure that the measurements are biologically
meaningful for the species and the matrix being studied. Here, we aimed to
validate the measurement of GC and triiodothyronine (T3) metabolites (fGCs and
fT3, respectively) in the feces of wild Golden-headed Lion Tamarins (GHLTs; Leontopithecus
chrysomelas), inhabiting highly disturbed forest patches in southern Bahia,
Brazil. We assessed the effects of capture, body condition (weight and score),
sex, dominance status, and group identity on the levels of fGCs and fT3 in
samples collected during capture events and regular group-monitoring days. We
found that capture and handling had a significant impact on both fGCs and fT3,
whereas body condition score was relevant only to the variation in fT3 levels.
These findings confirm the notion that the procedure of capture is a suitable
acute stressor to validate non-invasive hormone measures and that fT3 is a
promising marker for studying the fluctuations in energetic condition. Overall,
our results demonstrate that a simple biological approach is sufficient to
verify the applicability of non-invasive GC and TH determinations in fecal
samples of wild GHLTs.
Keywords: Cortisol, hormones, Lion
Tamarins, metabolites, non-invasive, thyroid hormones, wild.
INTRODUCTION
Hormones are chemical messengers
that regulate a wide range of bodily
functions to maintain homeostasis in the face of environmental change (McEwen
& Wingfield 2003; Nelson & Kriegsfeld 2017). They coordinate a series
of physiological and behavioral adjustments through which animals appropriately
respond to environmental and social cues, resulting in certain fitness outcomes
(Higham 2016). Given their central role, hormones have been the focus of
research across various fields (Palme 2005; Schwarzenberger 2007), including
primatology. With the development of non-invasive and field-based techniques,
researchers can now measure endocrine markers in matrices like feces or urine
from wild primates, without altering their behavior or hormonal status
(Schwarzenberger 2007). Moreover, these advances allow field observations to be
combined with non-invasive endocrine monitoring, providing valuable insights
into the adaptive aspects of hormone secretion and behavior (Cooke et al. 2014;
Fiorini-Torrico et al. 2024) as well as impacts of human activities on the
physiology of wild primates (Hodges & Heistermann 2011).
Glucocorticoids (GCs) are widely
used in conservation research due to their mediation of the physiological
stress response (Busch & Hayward 2009). This process initiates with the
activation of the vertebrate hypothalamic-pituitary-adrenal (HPA) axis
triggered by predictable or unpredictable environmental perturbations,
ultimately leading to the secretion of GCs (Dantzer et al. 2014). These GC
elevations then modulate energy allocation to cope with a variety of physical,
metabolic, and psychological stressors (Emery-Thompson 2017). If GC increases
are short-term, they enhance survival by promoting escape from noxious stimuli
(Wingfield et al. 1998). Chronic elevations entail reductions in individual
health and longevity (Sheriff et al. 2011; Beehner & Bergman 2017).
Thyroid hormones (THs) are also
involved in vertebrate energy balance, but their non-invasive study in wildlife
is more recent (Wasser et al. 2010). The synthesis of the two major forms of
THs, thyroxine (T4) and triiodothyronine (T3), is controlled by the
hypothalamic-pituitary-thyroid (HPT) axis. While the latter form is
biologically more active, the former serves as a peripheral reservoir for T3 production
via conversion (Behringer et al. 2018; Deschner et al. 2020). Given THs’
particular sensitivity to nutritional deficits, which results in a lower
metabolic rate (Eales 1988), it has been suggested that measuring both GCs and
THs can help differentiate energetic from psychological influences
(Emery-Thompson 2017), as well as distinct strategies to maintain energy
balance (Wasser et al. 2010; Dias et al. 2017; Touitou et al. 2021).
To ensure the reliability of
hormone measurements, it is essential to validate the hormonal assay for the
species and matrix being investigated (Sheriff et al. 2011). Once GCs and THs
are released into the bloodstream, they are metabolized by the liver and
subsequently excreted into urine or the gut via the kidneys and bile ducts,
respectively (Palme 2005; Behringer & Deschner 2017; Visser et al. 2017).
Metabolites that reach the intestine are further broken down; as a result, most
of the substances found in feces are conjugated forms of native GCs and THs
(Touma & Palme 2005; Palme 2019). Consequently, all immunoassays, typically
chosen to measure fecal metabolites, must be analytically validated for
precision, accuracy, sensitivity, and specificity (Higham 2016). This not only
guarantees that potential effects of storage, extraction, and laboratory
protocols are accounted for, but also ensures that antibodies cross-react with
target metabolites without major interference from other substances in the
sample matrix (Hodges & Heistermann 2011).
In addition to analytical validation,
studies should determine whether assays show biologically meaningful variations
in the species physiology (Touma & Palme 2005). This can be done either
through a physiological or a biological approach (Touma & Palme 2005).
Physiological validation normally involves inducing changes in circulating
hormone levels by administering a specific drug to later evaluate whether such
changes are reflected in the excreted metabolites (Behringer & Deschner
2017). Furthermore, if repeated sample collection is possible, this type of
experiment provides an opportunity to explore the lag-time between the
stimulation of hormone secretion and its excretion in feces or urine (Hodges
& Heistermann 2011; Behringer & Deschner 2017). Physiological
validation can be very invasive, which is a concern when studying threatened
species or wild individuals. In that case, biological validation may be more
appropriate (Behringer & Deschner 2017). This alternative examines the
levels of non-invasive markers in relation to a state or event known to alter
the secretion of target hormones (Touma & Palme 2005). For GC metabolites,
specifically, biological validation can be performed through procedures like
capture, confinement, translocation, new housing conditions, disturbances by human
presence or natural diurnal fluctuations in excreted GCs (reviewed by Touma
& Palme 2005 and Higham 2016). For TH metabolites, this has been achieved
by assessing the influence of caloric restriction or low body mass (reviewed by
Behringer et al. 2018), as well as the impact of infectious diseases (Dias et
al. 2017).
In this study, we explore the
effect of a series of intrinsic and stress-related factors on the levels of
fecal GC and T3 metabolites, hereafter referred to as fGCs and fT3. We do so to
validate the quantification of these markers in wild Golden-headed Lion
Tamarins (Leontopithecus chrysomelas; GHLTs; Image 1), an
endangered primate species restricted to the Southern Bahian Atlantic Forest in
Brazil. More specifically, we evaluate the stress response of GHLTs to
temporary capture and handling, predicting that fGC levels in samples collected
during capture events will be higher than fGC levels during group monitoring
days. We further examine the impact of body condition, predicting that higher
body mass and better nutritional status (reflected by a qualitative body score)
will both correspond with higher fT3 levels. We also assess the differences in
fGCs and fT3 in relation to GHLTs’ group identity, sex, and dominance status.
Currently, there is no published study on the levels of T3 in Lion Tamarins,
and only a few studies have used GCs in wild and captive populations of Lion
Tamarins to address different hypotheses (e.g., Bales et al. 2002, 2005, 2006;
Henry et al. 2013; Costa et al. 2020; Kaisin et al. 2023), including those that
focused exclusively on the validation of the techniques (Wark et al. 2016; Bertoli
et al. 2019). Therefore, this study adds to the literature showing the
potential of non-invasive hormone analyses to understand the physiological
responses of wild primates and may serve to better inform conservation actions
for this and other threatened species.
MATERIALS AND METHODS
Study subjects
We studied 32 individuals
belonging to four habituated groups of GHLTs (named ELI, MRO, OZA and RIB), all
of which are monitored with radiotelemetry and captured routinely as part of
the ongoing long-term research project BioBrasil (De Vleeschouwer &
Oliveira 2017). The GHLT groups move freely in an area that comprises various
privately owned farms located in the municipality of Una in South Bahia (see
map in Image 2, geographic coordinates of field base: -15.285° S, -39.134° W).
The study area is a mosaic of disturbed forest fragments of various sizes and
an agricultural matrix that includes crop plantations (mainly cocoa, rubber,
coffee, banana, and cassava), pastures, open fields, and unpaved roads (De
Vleeschouwer & Oliveira 2017). The predominant natural vegetation in this
region is classified as the Southern Bahian Moist Forest (Gouvêa et al. 1976)
and the climate is characterized by an annual average temperature of 24 °C and
precipitation of 2,500 mm, with no marked seasonality (Mori et al. 1983).
Following Miller et al. (2003),
we categorized age of individuals into infants (<3 months), juveniles (3–12
months), subadults (12–18 months) and adults (>18 months). Dominance
hierarchy and age of adult and subadult GHLTs were assessed based on historical
group composition data from Project BioBrasil, behavioral observations, and
information provided by BioBrasil’s field assistants, who were able to recount
the breeding history and relatedness of GHLTs over a longer period. Studies on
Golden Lion Tamarins Leontopithecus rosalia (GLTs) show that dominant
and subordinate breeders (males or females), within the same group, rarely
display aggressive interactions and, instead, frequently engage in mutual
affiliation, which is something typical of cooperative-breeding social
structures (Baker et al. 1993, 2002). Despite that, dominance relationships of
both males and females can be classified by examining a set of behaviors that
indicate their status and roles within their social context (Baker et al.
2002). Therefore, to determine the dominance of adults and subadults, we
considered their involvement in chases during intergroup encounters and
intragroup aggression, their access to mates when females were expected to be
fertile, their participation in carrying and nursing infants, as well as the
frequency of mounts, copulations and arch-walks (Baker et al. 2002; Bales et
al. 2005, 2006).
All activities described here
involving captures, sample collection and monitoring were ethically approved by
the International Committee for the Conservation and Management of the Lion
Tamarins and the Brazilian Environmental Agency (ICMBio/SISBIO permit no.
23457-6).
Capture procedure
Study groups are captured twice a
year by a multidisciplinary and trained team of biologists, veterinarians, and
field assistants to replace radio-collars (model RI-2D, Holohil Systems Ltd.,
Ontario) on one or two adult individuals per group and to provide all
individuals with a tattoo number and a unique dye mark (Nyanzol Dye). In this
way, captures not only allow for the use of radiotelemetry to locate groups in
the field but also facilitate identifying individuals during subsequent
behavioral observations and sample collections.
Before capturing the GHLTs,
platforms baited with banana were assembled in an area regularly used by the
group (see Image 2), and Tomahawk traps were set up on these platforms
gradually. The traps were activated once there was evidence the groups frequently
visited the platform (De Vleeschouwer & Oliveira 2017; Catenacci et al.
2022). During capture days, traps were opened at 0500 h and monitored at
regular intervals (0800, 1000, 1200, 1400, & 1630) to verify whether
animals had been caught. Trapped GHLTs were taken to a nearby field laboratory
and, following a fasting period of two to three hours, anesthetized with a
combination of ketamine hydrochloride (dose 8–10 mg/kg) and midazolam (dose
0.25–0.5 mg/kg) to perform examinations (Catenacci et al. 2016; Costa et al.
2022). No infant GHLT was anesthetized or kept separate from its mother or
caregiver (Catenacci et al. 2022). Due to the COVID-19 pandemic, which
coincided with the present study, and the risk of spreading this disease to the
animals (Fedigan 2010), we reinforced biosafety measures for all team members
and shortened the handling time by limiting the collection of biometric data.
Nonetheless, key variables such as body mass, measured with a one-gram digital
scale after containment, and body condition score (see Table 1), determined
based on Clingerman & Summers (2005), were still collected. All recovered
animals were released either the same day before sunset or the following
morning at the location where they were caught (Costa et al. 2020). For a more
comprehensive description of the methods used during captures and examinations
of GHLTs consult Catenacci et al. (2022).
Sample collection and
preservation
Fresh, uncontaminated fecal
samples were collected under two different circumstances: 1) during two capture
events, one in April and the other in November 2021, including all four GHLT
groups – capture samples; and 2) over 11 months of full-day field observations
between December 2020 and October 2021, involving only MRO, OZA and RIB –
monitoring samples. In both cases, we focused our sampling effort on adult and
subadult individuals (see Table 2), as GC production increases and GC negative
feedback becomes less responsive with age (Sapolsky & Altmann 1991; Gust et
al. 2000). Samples were incidentally taken from juvenile and infant GHLTs,
which represented 6.25% of capture and 4.67% of monitoring samples. During
group monitoring days, feces were collected any time we observed an individual
defecate. During captures, samples were taken opportunistically at the field
lab following the fasting period. All samples were labelled with the date, the
time of collection, and the individual’s identity.
The time from when an individual
was found in a trap (between 0800 and 1630) until it defecated and feces were
collected was, on average, 4.80 ± 2.78
h. Importantly, before TH and GC metabolites are excreted in feces, their
circulating forms are metabolized and pass through the intestinal tract
(Behringer et al. 2018; Palme 2019). This introduces a delay time in the
appearance of the hormonal signals in feces which more or less corresponds to
the species’ gut transit time (Palme et al. 1996, 2005; Palme 2005; Touma &
Palme 2005). For some callitrichids, including GLTs, gut transit times range
from 2.65–6.30 h (Power & Oftedal 1996; reviewed by Lambert 1998). This
interval nearly coincides with the time elapsed before fecal samples were taken
from trapped individuals (as mentioned above), increasing the likelihood of
detecting hormonal changes caused by capture-related procedures.
Samples were stored inside 15 ml
polypropylene screw-cap tubes prefilled with 4 ml of 80% ethanol (Hodges &
Heistermann 2011), which is the preferred field preservation technique to
prevent microbial degradation when immediate freezing is not available
(Schwarzenberger 2007). Care was taken to ensure that stored samples were
completely submerged in ethanol before tightly closing the lid (Hunt &
Wasser 2003) and then transferred the tubes the same day of collection to a
freezer at -20°C, where samples remained for 30–149 days until oven dried (Khan
et al. 2002). To dry samples, we first let the alcohol evaporate overnight for
about 12 hours (Terio et al. 2002) and then placed samples inside a laboratory
oven at 50°C for 4 h (Gholib et al. 2018), at which point feces became crumbly
suggesting complete water loss. Finally,
samples were transferred to small, labelled plastic bags containing
oxygen absorbers, sealed them, and took them back to a freezer at -20 °C until
all samples were shipped to the lab for further processing.
Hormone extraction and assay
Extraction of fecal metabolites
and quantification of fGCs and fT3 were conducted in the Interdisciplinary
Laboratory of Clinical Analyses at Murcia University (Interlab-UMU), Spain,
between April and June 2022. To extract the metabolites, we followed a method
similar to that described in Wasser et al. (2000). First, large seeds, insect
parts and plant debris from crushed dried feces were removed (Foerster &
Monfort 2010), and weighed an aliquot of approximately 0.06 g (95.7% of the
aliquots had an average weight of 0.0599 g ± SD 0.0023). All aliquots were
pulverized and shaken for 15 h in 1 ml of analytical-grade methanol
(Gómez-Espinosa et al. 2014; Rangel-Negrín et al. 2015). Extracts were then
centrifuged at 3,500 rpm for 5 min, and 0.6 ml of supernatant was transferred
to a separate tube. Supernatants were then evaporated inside a vacuum
concentrator for 2 h, reconstituted with 0.15 ml of a PBS buffer, vortexed, and
stored at -80 °C until analysis.
Commercial enzyme immunoassays
(EIA) kits from IBL International GmbH for the determination of cortisol
(RE52061) and total triiodothyronine (RE55251) to respectively measure fGCs and
fT3 in our sample extracts. While the chosen T3 kit has already been validated
for T3 metabolites excreted in feces and urine of non-human primates (Behringer
et al. 2014; Cristóbal-Azkarate et al. 2016; Deschner et al. 2020; Sadoughi et
al. 2021; Touitou et al. 2021), the cortisol kit has thus far been tested in
teleosts (e.g., Nilsson et al. 2012; Cerqueira et al. 2017; Mazzoni et al.
2020) and some mammals (e.g., Brain et al. 2015; Almoosavi et al. 2021; Kaiser
et al. 2023) but not in non-human primates. To prevent alterations in the
assays, manufacturer’s instructions of use were strictly followed. The standard
curves for calibration of all 10 plates tested (5 for fGCs & 5 for fT3)
exhibited an accuracy of R2 = 0.98–1. Besides the coefficients of
variation (CV) for repeatability already provided by the manufacturer (cortisol:
intra-assay CV = 2.5–3.5 % and inter-assay CV = 2.1–5.2 %; total T3:
intra-assay CV = 3.59–6.61 % and inter-assay CV = 5.23–6.73 %), we performed,
prior to the analysis of main samples, an analytical validation on a small set
of fecal samples collected from captive GHLTs from Terra Natura in Benidorm
(Spain), following the same sample processing previously described. For both
the fGCs and fT3 quantification, it was found that intra and inter-assay CVs
were less than 15% and displacement curves obtained from serial dilutions of
fecal samples ran parallel to the standard hormone curves with a R2
close to 1.
Data analysis
The levels of fGCs and fT3 were
compared between groups of the predictor variables by applying ANOVA to
multiple mixed-effect models fitted with the ‘lmer’ function from the R package
lme4 (Bates et al. 2015). Because data contained repeated measures for the same
individual within and, in some cases, between groups, we consistently defined
the individual identity as a random factor throughout this analysis. Both fGC
and fT3 levels were transformed to logarithm with base 10 to conform with
assumptions of normality of residuals and homogeneity of variance, verified
each time data was reorganized. When dealing with fT3 levels measured in monitoring
samples, ANOVAs were used with aligned rank transformed data from package
ARTool (Wobbrock et al. 2011). If a significant effect was detected for a
certain variable, a post-hoc analysis was performed by least-square means from
package emmeans (Searle et al. 1980) or a contrast test provided by ARTool. We
began evaluating the effect of the stress of capture on both metabolites
considering the total number of samples (n = 289). We then split up the dataset
between capture and monitoring collections and removed data from juveniles and
infants to test the influence of sex, dominance, and dominance in interaction
with sex (dominance*sex) on fGCs and fT3 levels. Body condition score and body
weight were assessed only with capture samples, for the latter variable we
excluded juveniles from the dataset as body weight would not be comparable. To
explore the differences in group identity, we solely considered samples from
regular monitoring including all age categories. All statistical tests were run
in R version 4.3.2. (R Core Team 2023) and considered significant at p <
0.05.
Since diurnal variation in
hormone secretion may potentially confound the excretion of GCs and T3
metabolites (Sousa & Ziegler 1998; Foerster & Monfort 2010; Pizzutto et
al. 2015; Behringer et al. 2023), especially in species with rapid gut transit
time (Touma & Palme 2005; Rimbach et al. 2013) like GHLTs, we examined the
effect of collection time on the fGC and fT3 levels within the complete dataset
(all samples), as well as the separate datasets: monitoring and capture
samples. To conduct this preliminary analysis, we used linear mixed-effect
models (‘lmer’) for fGCs and generalized linear mixed-effect models (‘glmer’)
for fT3, with individual identity as random term and time of collection as
predictor. If collection time had a significant effect, we incorporated it as
an additional random factor in the formula of our main analysis to account for
the natural circadian fluctuations in the response variables.
RESULTS
We found that diurnal variation
of metabolite excretion affected the levels of fT3 in the complete dataset (p =
0.022), and fGCs in the monitoring (p = 0.009) and capture (p = 0.048)
datasets. Therefore, in addition to individual identity, we defined collection
time as a random factor when using these datasets with the respective fecal
metabolite. As this was beyond the scope of our main research questions, we do
not discuss further how fGCs and fT3 reflect the GHLT’s circadian rhythms.
Effects of the stress of capture
and body condition
Concentrations of fGCs in capture
samples were significantly higher than in monitoring samples (F1, 267.92
= 36.81, p < 0.001) with mean levels of 6462.14 ± SEM 921.76 ng/g and 2712.3
± SEM 197.88 ng/g, respectively, for each collection type. Although the range
of fGC levels observed in monitoring samples (181.81–22065.65 ng/g) was wider
than that in capture samples (1020.81–21712.85 ng/g), the range of variation of
both collection types nearly overlapped (Figure 1A). On the contrary, fT3 values
measured in capture samples were significantly lower than in monitoring samples
(F1, 263.18 = 12.27, p < 0.001) with mean levels of 29.7 ± SEM
2.73 ng/g and 89.55 ± SEM 7.98 ng/g, respectively. Also, in contrast to fGCs,
the range of fT3 levels was much narrower in capture (9.86–74.44 ng/g) than in
monitoring samplings (10.76–848.61 ng/g), as shown in Figure 1B. We found no
significant effect of body weight on either metabolite. Body condition score of
captured individuals was significantly associated with variation in fT3 levels
(F1, 27 = 5.54, p = 0.026), this association linked higher fT3
concentrations to individuals with a better nutritional state (optimum versus
thin), see Figure 2A.
The effect of sex, dominance, and
group identity
Neither sex nor dominance was
associated with significant differences in the levels of fGCs or fT3 for any
collection type. Similarly, the interaction between sex and dominance was not
significant for any of the metabolites measured in the monitoring samples (see
Figure 3). There was a marginally significant effect of this interaction on the
fGCs levels in capture samples (F1, 17.28 = 3.58, p = 0.075).
Regarding only monitoring samples, group identity had a marginally significant
effect on fGC values (F2, 30 = 3.08, p = 0.061), whereas for fT3
this effect was significant (F2, 26.6 = 6.22, p = 0.006) with fT3
levels in MRO being higher than in OZA and RIB (Figure 4). Given that the
variation in fT3 among GHLT groups could potentially bias the previous results
regarding stress of capture, we ran an additional test for fT3 and type of
collection with individual identity nested within group membership as a random
factor in the model configuration. This test confirmed that the procedure of
capture has a significant effect on fT3 levels (F1, 120 = 9.81, p =
0.002) regardless of group identity.
DISCUSSION
Here we
demonstrated, through a simple biological approach, that fGCs and fT3 can be
reliably quantified in dried feces of wild GHLTs using commercially available
cortisol and total triiodothyronine EIA kits. To do so, we evaluated the
physiological response of individuals to the stress of capture and compared it
to a natural situation. Additionally, we assessed the relationship between body
condition and the metabolites of interest.
Importantly, the present study offers a different validation approach
from methodologies such as physiological validations, which normally allow
consecutive sampling of tested subjects after induced stress and are intended
to measure peak metabolite levels.
As
expected, GC excretion in individuals during capture and handling procedures
was, on average, higher than levels measured during the GHLT’s daily activity
throughout 11 months of sampling. This finding confirms the notion that the
activation of the HPA axis during procedures such as physical restraints,
captures, and transportation allow detecting GC alterations that show the
capacity of individuals to mount their stress response (Touma & Palme 2005;
Wikelski & Cooke 2006). Typically, fGC measurements in non-human primates
are validated by obtaining multiple samples from captive individuals before and
after a short-term stressor (e.g., capture, isolation, veterinary exam,
anaesthesia) or a procedure to pharmacologically stimulate the HPA-axis, such
as the adrenocorticotropic hormone (ACTH) challenge test (e.g., Heistermann et
al. 2006; Rangel-Negrín et al. 2009; Rimbach et al. 2013). With this,
researchers can delineate the fGC excretion profiles for each individual and
identify the peak values, defined as the fGC concentrations exceeding two
standard deviations above baseline (Gómez-Espinosa et al. 2014; Pizzutto et al.
2015; Wark et al. 2016). The latter value can correspond to the mean
pre-capture concentration (Gómez-Espinosa et al. 2014), or the mean
concentration calculated by iteratively excluding values greater than 2 SDs
from the mean (Pizzutto et al. 2015; Wark et al. 2016). Studies using this
approach have reported a lag time of 22.3–49.3 h in GLTs (n = 7; Wark et al.
2016) and 20–25 h in Black Lion Tamarins Leontopithecus chrysopygus(BLTs)
(n = 6; Bertoli et al. 2019) between the stressful event or the ACTH injection
and the first observed peak. Given such lag times, we presume that the
timeframe considered in this study (4.80 ± SD 2.78 h) is not long enough to
detect a peak in fGC excretion. The results simply indicate how the stress
response of GHLTs, as measured by fGCs, differs between capture events and
regular monitoring days, when habituated individuals move freely and interact
with their environment. It is possible that lag time before fGC peaks appear in
GHLTs will be similar to those found in congeneric species. To verify that, a
different experimental design needs to be used which would likely require
captive populations or free-ranging individuals to be retained in captivity to
ensure repeated fecal sampling for at least three days following an induced
stressor (Gómez-Espinosa et al. 2014; Wark et al. 2016; Bertoli et al. 2019).
Notably,
the amplitude of fGC response to capture was similar to the one detected during
monitoring days, especially regarding upper fGC concentrations. This may
indicate that GHLTs in our study area face environmental stressors that trigger
a stress response as intense as the one induced by capture and containment
(Johnstone et al. 2012). The study groups occupy fragments of disturbed forest
interspersed with agricultural areas (De Vleeschouwer & Oliveira 2017), a
landscape that probably presents particular environmental challenges, such as
high predation risk (Oliveira & Dietz 2011) or low opportunities to find
food and shelter (Kalbitzer & Chapman 2018), which could stimulate or even
sustain a GC elevation in the long term (Kaisin et al. 2021). It would be
interesting to compare our results with those from GHLTs in different
landscapes and explore the possible health consequences linked to an
over-stimulation of the stress responses (Romero et al. 2009) in GHLTs
occupying disturbed forests.
Contrary to
our expectations, fT3 levels were affected by the stress of capture, but
exhibited a response pattern opposite to that of fGCs. This significant effect
suggests that, similarly to fGCs, the lag time for the appearance of T3
metabolites in feces is comparable to the species’ gut passage time (Schaebs et
al. 2016; Behringer & Deschner 2017). Furthermore, the lower fT3 but higher
fGC levels in capture compared to monitoring samples raises the possibility of
a cross-talk or interaction between the HPA- and HPT-axis (Behringer et al.
2018; Touitou et al. 2021), although levels of fGCs and fT3 in capture samples
were not correlated, probably due to small sample size. It is frequently
suggested that TH levels are downregulated by the release of GCs, associated
with stressful situations (Burr et al. 1976; Behringer et al. 2018).
Physiological pathways leading to this TH suppression include the inhibition of
the thyroid stimulating hormone and the reduced conversion of T4 to T3
(Charmandari et al. 2005). For instance, Helmreich et al. (2005) found in male
Sprague-Dawley rats that mild-electric foot-shocks led to significantly lower
levels of serum T3 and, although corticosterone levels were not altered by this
experiment, certain HPA-axis components may participate in TH regulation. This
relationship may not be so straightforward, even when an acute stressor is
involved, as demonstrated for Guadalupe fur seals by DeRango et al. (2019), who
associated a capture event to a simultaneous reduction in T3 and an integrated
stress response comprising cortisol and corticosterone levels. Furthermore, the
potential cross-talk between T3 and GCs may have been confounded by food
restriction, performed in order to anesthetize trapped individuals. In fact,
various studies have successfully validated the measurement of T3 in primates
by linking reduced food intake to lower levels of T3 in urine and feces (Wasser
et al. 2010; Schaebs et al. 2016; Sadoughi et al. 2021). Regardless of the
possible explanations, our results for the stress of capture indicate that
under fearful situations, GC levels in GHLTs increase in order to promote
alertness and a freezing response (Charmandari et al. 2005; Korte et al. 2005)
while T3 decreases as a mechanism to modulate the metabolic rate and save
energy (Behringer & Deschner 2017; Gesquiere et al. 2018). Both changes
likely occur in preparation to future demands or additional stressors (Sapolsky
et al. 2000).
Another
aspect that links THs’ secretion to metabolic activity in relation to energy
balance is their response to weight gain or loss (Chatzitomaris et al. 2017).
Specifically, when high food quantity and quality is accompanied by high T4 and
T3 levels, bodyweight will normally increase (Behringer et al. 2018). In this
study, no association was found between adults and subadults’ body mass and fT3
levels, which could be attributed to the fact that weight values were not
scaled to specific body length of each individual (DeRango et al. 2019). We
measured this value (knee-to-heel distance) in some but not all sampled
individuals because of the limitation in handling time during capture imposed
by pandemic restrictions. Nonetheless, by using a semiquantitative body
condition score, a tendency of lower fT3 levels was identified to be related
with individuals presenting a bonier structure and a lesser amount of palpable
muscle and fat (Clingerman & Summers 2005). This is in line with evidence
that THs play a direct role in regulating the metabolism of brown adipose
tissues and skeletal muscles (López et al. 2013).
Primate
males and females normally differ in their strategies to achieve and maintain
social dominance which, as reviewed by Cavigelli & Caruso (2015), results
in dominant males having elevated metabolic demands due to the costs of
competition over access to mates, especially during periods of social
instability, whereas exclusion of quality food sources entails reduced energy
intake, particularly for subordinate females. Accordingly, one may predict that
dominant males and subordinate females will probably exhibit high GC but low T3
levels. Fecal glucocorticoid and fT3 concentrations across sex and dominance
status in adult and subadult GHLTs were statistically indistinguishable. Such
an absence of a dominance status effect is consistent with studies on
free-ranging male and female GLTs, at least with respect to fGC metabolites
(Bales et al. 2005, 2006). Furthermore, the pattern for fGCs coincides with a
hierarchy system, commonly attributed to cooperatively breeding species, where
subordinates are not subjected to high rates of aggression and usually rely on
close kin support (Abbott et al. 2003). On the other hand, although not investigated
here, it is likely that differences in fGCs in relation to female reproductive
status may be present in wild GHLTs, as observed in several other primate
species (e.g., Bales et al. 2005; Rimbach et al. 2013; Dias et al. 2017). To
address such question and more accurately define reproductive condition in
females, GC measures should be accompanied with the determination of estrogen
conjugates and pregnanediol glucuronide (De Vleeschouwer et al. 2000; French et
al. 2003).
During
group monitoring, it was observed that the MRO group was going through various
changes in composition which initiated with the death of the eldest dominant
male, then the emigration of females and finally, the disintegration of the
group with a single subordinate male using the original home range and
attempting to enter a neighboring group. Considering such a dramatic and likely
stressful group dynamic, one may presume higher fGC levels in MRO than in the
other two groups. This was not the case for fGCs, but it was for fT3 levels.
The significantly higher level of fT3 in MRO may point to the potential
influence of ecological factors, such as the availability of space and
associated access to food and shelter. Previous studies on GHLTs have reported
differences in home range and feeding behavior among groups using distinct
habitats (Oliveira et al. 2011; Costa et al. 2020), as may be generally
expected. Coutinho (2018) who worked with three of our study groups during an
earlier period, showed that groups have a substantial proportion of overlapping
home range and differ in the time devoted to feeding on plants and animals.
This requires additional investigation into the extrinsic factors that may
potentially lead to constraints in energy intake and explain this variation in
metabolic rate between groups.
CONCLUSION
This study
validates the measurement of GC and T3 metabolites in wild GHLTs’ fecal
samples, employing two commercial EIA kits. It also provides further evidence
that biological validation of hormonal measurements in wild individuals is an
effective alternative to traditional pharmacological challenges, provided the
tested factors are carefully considered. Taken together, the results show that
fGCs respond to the stress of capture and possibly, under acute stressors,
downregulate fT3 levels. While fT3 responded to changes in body condition and
therefore may have a more direct connection to energetic challenges.
Table 1. Description of the body
condition scores used during two capture events to categorize nutritional
status (body fat and muscle) of captured Golden-headed Lion Tamarins.
|
Body
condition score |
Definition |
|
1 |
Emaciated: very prominent
and easily palpable bones (hips, ribs, and spinal processes), very low to no
palpable muscle mass over the ilium or ischium, subcutaneous fat layer is
absent, very angular body, sunken anus between ischial callosities, and
protruding facial bones. |
|
2 |
Thin: prominent and
palpable bones, low muscle mass over the hips and back, low fat reserves and
subcutaneous fat layer, and angular body. |
|
3 |
Optimum: bones are
generally not visible but palpable to soft pressure, both muscle mass and fat
layer are well-developed giving the spine and hips a firm but smooth
touch. |
|
4 |
Overweight: bones are not
visible and only palpable to firm pressure, abundant subcutaneous fat layer,
and smooth and less defined body contour. |
|
5 |
Obese: bones are not
visible at all and difficult to palpate, abundant fat deposits (abdominal,
axillary, and inguinal region), difficult abdominal palpation due to large
amount of mesenteric fat, and body contour without definition. |
|
Adapted from Clingerman &
Summers (2005). |
|
Table 2. Number of fecal samples
per sex and dominance status collected during capture events and regular
monitoring days.
|
Collection type |
Number of
groups |
Number of
individuals |
Number of
fecal samples |
||||||
|
♀D |
♀S |
♂D |
♂S |
J & I |
♂U |
Total |
|||
|
Capture |
4 |
22 |
10 |
10 |
3 |
5 |
2 |
2 |
32 |
|
Monitoring |
3 |
25 |
39 |
54 |
68 |
83 |
12 |
1 |
257 |
Where adults and subadult
Golden-headed Lion Tamarins are differentiated in dominant females (♀D) and males (♂D), subordinate females (♀S) and males (♂S) or males with undetermined
dominance status (♂U). Juveniles and infants are
represented by “J & I”.
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