Non-invasive Sampling of Odours From Two Big Cats for Wildlife Conservation

Non-invasive Sampling of Odours From Two Big Cats for Wildlife Conservation | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Non-invasive Sampling of Odours From Two Big Cats for Wildlife Conservation BV ADITI, CHENA DESAI, DARSHAN SREENIVAS, UMA RAMAKRISHNAN, SHANNON OLSSON This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8895773/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 9 You are reading this latest preprint version Abstract Chemical cues play an important role in mammalian communication, often reflecting an individual’s physiological state. Non-invasive sampling of such informative cues holds great potential for wildlife monitoring. Endangered apex predators such as big cats are elusive and challenging to monitor. While existing monitoring techniques estimate numbers or densities, they often fail to provide crucial demographic and physiological information. We applied a customized field sampling technique to sample volatiles from urine and faeces of captive Bengal tigers and Indian leopards of known age and sex, and from urine of identified wild Bengal tigers of known age, sex, and reproductive status. Volatiles extracted from these samples were analysed using Thermal Desorption- Gas Chromatography-Mass Spectrometry. The random forest algorithm was used to identify compounds that might be cues for species, age, sex, and reproductive state. Species classification accuracy was consistently high with both urine (0.79 + 0.009) and scat (0.75 + 0.029) volatiles. Classification accuracy of urine volatiles was high for females and young individuals in leopards and tigers, but lower for males and old individuals. Scat volatiles performed better across groups. We also identified putative chemical markers for epilepsy and reproductive state in tigers. This study presents the first chemical characterization of tiger and leopard scats and the first sampling of tiger odours from the wild. Our simple and cost-effective method of sampling tiger and leopard odours offers a novel method of chemical fingerprinting to monitor populations in situ. Importantly, this sampling method and analytical pipeline is broadly applicable to other mammalian species for conservation and ecological studies. Chemical ecology sex identification volatiles tigers leopards age Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 INTRODUCTION Olfactory cues are an important means of communication in mammalian societies (Beauchamp et al. 1976 ; Brennan and Kendrick 2006). Such cues are typically contained in a mixture of chemicals many with relatively high volatility, transported through excretions and secretions (Ache and Young 2005 ; Burger 2005 ). Volatile organic compounds (VOCs) are known to be crucial in signalling for mate choice, territory marking, reproduction, species, and individual identity among a large number of species​ (Brennan and Kendrick 2006; Amo and Ruiz Rodríguez 2023). While VOCs are not always emitted for intentional signalling, conspecifics can often extract information about fitness and reproductive state, and heterospecifics can infer prey and predator presence ​(Beauchamp et al. 1976 ; Fromhage and Henshaw 2022). Such VOCs are considered to be cues rather than signals, and could be honest indicators of physiological status (Candolin 2003 ). With the recognition of emerging infectious diseases and inbreeding depression as a threat to the viability of wild populations, it has become increasingly important to identify and track health status in situ (Shumake 1977 ; Daszak 2000 ; Artois et al. 2009 ). Determining the age structure and sex ratio of wild populations is also pivotal to management (Roach and Carey 2014; Kappeler et al. 2023 ). VOCs could potentially inform health and reproductive status (Zala et al. 2004; Kean et al. 2011 ; Manzoli et al. 2019 ). Additionally, identifying sex pheromones could help plan ex situ conservation of threatened species (Dehnhard 2011 ; Leal 2017 ). VOCs that indicate age, sex, individuality, health and reproduction have been identified in several species (see Raymer et al. 1984 for wolf; Hagey and Macdonald 2003 for Giant panda; Grosbois et al. 2007 for Antarctic prions; Kean et al. 2011 for otters; Buljubasic and Buchbauer 2015 for human diseases; Noonan et al. 2019 for European badgers; Uetake et al. 2017 for domestic cats; Jones et al. 2021 for maned wolf; Walker et al. 2024 for dingoes). Sampling of informative VOCs could provide crucial insights into the physiological or health status of wild endangered species, complementing demographic and habitat-based assessments. (Meinwald and Eisner 2008 ; Soso et al. 2014 )​. Unlike serological sampling, sampling odours from breath, urine, faeces, and body requires minimal intrusion into organisms’ bodies making these techniques of immense value to diagnostics (Cumeras et al. 2014 ; Rodríguez-Hernández et al. 2022 ). Unfortunately, in situ chemical sampling techniques have not been exploited much for conservation research due to technical difficulties of sample collection, handling, and storage. VOCs have been mostly used in wildlife management to bait individuals either for camera trapping or to physically capture ‘problem’ individuals (Lindgren et al., 1995 .; Whitehead et al. 2008 ; Joubert et al. 2020 ; Lu et al. 2024 ). The use of VOCs has also been explored as a solution to invasive species affecting native flora and fauna (Favaro et al. 2024 ). There have been very few studies on VOC fingerprint molecules for monitoring wild animal populations such as in early diagnosis of wildlife diseases (Pavlou and Turner 2000 ; Bayn et al. 2013 ; Cumeras et al. 2014 ; Stahl et al., 2015 ) and for species identification (Burnham et al. 2008 ). Being apex predators, large felids play a crucial role in maintaining ecosystems (Tossens et al. 2025 ). Felid populations face several threats and they are currently amongst the most endangered mammals on earth, with several populations facing high extinction risks from inbreeding depression and diseases (eg. cheetah Castro-Prieto et al. 2010; lion Roelke-Parker et al. 2010 ; tiger Gilbert et al. 2014 ). Monitoring felid population dynamics and health should be an important part of conservation efforts, but is hampered by the elusive nature of these species (Munson et al. 2010). Current monitoring techniques include non-invasive techniques such as camera trapping and genetic sampling (Karanth 1995 ; Mondol et al. 2009; Jhala et al. 2015) that can gather information about population size, sex ratio, connectivity, and behaviour patterns, but have limited applicability in sampling age, health, and reproductive parameters (Harmsen et al. 2017 ; Anile and Devillard 2018; Joubert et al. 2020 ). Tigers and leopards are threatened big cats and are an important focus for conservation and management in their range countries (Tisdell et al. 2007; Goodrich et al. 2022 ; Ghoddousi and Khorozyan 2023). Being a solitary species, their social systems are maintained by indirect cues, particularly olfaction (Smith et al. 1989; Allen et al. 2021 ). Olfactory cues are deposited through faeces (scats), urine, clawing, cheek rubbing, and body rolling​ (Schaller 1968; Sunquist 1981 ; du P. Bothma and le Richet 1995; Soini et al. 2012 ). The urine of tigers sprayed into the environment with the tail held perpendicular to the body is one of the most well-observed behaviours of tigers ( Schaller 1967; Smith et al. 1989). The smell is known to persist for days (Schaller 1967) and is said to be similar to the odour of Basmati rice or popcorn (Brahmachary and Sarkar 1990)​. Behavioural studies with radio-collared and captive tigers indicate increased marking behaviour in the presence of individuals of the same sex and during periods of reproductive activity​ (Brahmachary et al. 1992 ; Soini et al. 2012 ). Females mark more frequently when in estrus, and males are known to mark in response to a female in estrus (Smith et al. 1989). In the wild, both leopards and tigers mark at the borders of their territory more frequently than in the interiors both leopards and tigers (Smith et al. 1989; Rafiq et al. 2020) Studies on the VOC composition of captive tigers and leopards found a high concentration of fatty acids, an unidentified fraction that appears in adulthood, and several ketones, lactones, alcohols, esters, and carboxylic acids in the headspace​ (Brahmachary et al. 1992 ; Poddar-Sarkar 1996 ; Andersen 1998 ; Poddar-Sarkar and Brahmachary 2004; Burger et al. 2008 ; Apps et al. 2014 ; Soso and Koziel 2016 ). There are no studies on odour compounds in scats of tigers, but several studies on domestic cats and canids that identify odour cues for age and sex​ (Apps et al. 2012 ; Uetake et al.,2017.; Miyazaki et al. 2018 ; Yamaguchi et al. 2019 ). Based on the behavioural and odour information known from tigers, we hypothesize that VOC profiles can indicate age, reproductive and health status in scat and urine. We investigate these questions through samples of urine and scat from captive as well as wild tigers, and from identified individuals of known age, sex, and health status. In this study, we address the following questions: i) Can tiger and leopard volatile compounds be sampled non-invasively for chemical analysis and identification? ii) Do the scats and urine of tigers and leopards contain odour profiles that differ with respect to a) age, b) sex, c) reproductive status, and d) health? iii) Can VOCs be used as a diagnostic tool for the age, sex, health, and reproductive status of tigers and leopards? By answering these questions, we lay the foundation for a practical volatile sampling method which enables the collection of biologically relevant information of two big cats. METHODS Odourant sample collection and sampling strategy. Scat and urine samples of tigers and leopards of known identity in captivity were sampled non-invasively in Bannerghatta Biological Park in Bengaluru, Karnataka for 18 weeks from June 2021 to November 2021 as well as in Kamala Nehru Zoological Park, Ahmedabad, and Sayajibaug zoo, Vadodara, in Gujarat, for 16 weeks from February 2022 to April 2022. The zoo biologists shared details about the age, sex, and health conditions of the individuals sampled. None of the captive tigers were reproductively active. Individual wild tigers were observed and sampled in Ranthambore Tiger Reserve in the Northwestern state of Rajasthan for a total of seven months from February 2022 to June 2022 and May 2023 to June 2023. The Reserve's semi-arid climate and high density of tigers make it an ideal location for spotting tigers. Extensive monitoring and isolation of this population allow researchers to identify and track tigers of known identity, age, sex, reproductive stage, and health conditions. Information about the territory of individual tigers was used to scour the area and spot individuals based on indirect signs such as pugmarks and the behaviour of prey animals. When spotting the individuals, information about their age, sex, appearance, and marking spots was noted. Appearance suggestive of reproductive status was noted: such as a swollen belly due to pregnancy and prominent mammary glands or being accompanied by cubs younger than six-month-old, indicating lactation. Once the individuals left the area, the fecal or urine samples were collected for odour analysis. Urine and scat samples of captive individuals were collected from the floor of cages in the morning by zookeepers under our supervision and did not require physical contact with the captive animals. We aimed to collect at least five replicates of urine and scat from each individual and maintained a difference of at least two weeks between replicates from the same individual. Wild samples were collected after the individual left the area, which was mostly within minutes of marking but sometimes up to an hour after marking. In a single marking event, an individual might mark several times in different areas, and these samples were considered technical replicates. Samples from the same individual collected on different days in separate marking events were considered biological replicates. Urine samples were collected for odour analysis by swabbing spray areas with sterile cotton, while wearing sterile gloves, and storing the cotton in sterilized (treated with ethanol and baked at 270 degrees Celsius) 30 ml Borosil glass vials (Fig. 1 ). Boluses of scat were similarly collected. The vials were sealed with aluminium foil and parafilm, maintained at 4 degrees Celsius during transport to lab (basecamp in field) where the solid space volatile extraction was carried out and then transferred to -20 degrees Celsius for long-term storage. Since noninvasively collected samples would include volatiles from the environment, environmental controls were also collected, along with the samples. Various substrates in the zoo and the wild were sampled at a distance of about 3 metres or more from the marking to avoid volatiles from scats or urine. Pebbles, soil, grass, leaf litter and different tree barks were collected, and odours were extracted as with samples. Odours from sterile cotton were also collected. Permissions for zoo sampling were obtained from Gujarat State Forest Department, Karnataka State Forest Department and Central Zoo Authority of India and for wild sampling from Chief Wildlife Warden, Rajasthan Forest Department. Details of sampling letters can be found in Supplementary Table 1. The sampling protocol was approved by the Institutional Biosafety Committee of NCBS-TIFR. Solid Phase volatile extraction. Solid-phase extraction (SPE) was carried out as in Nair et al. 2018 , and Nordström et al. 2017 , using polydimethylsiloxane (PDMS) tubes procured from Carl Roth (Rotilabo®–silicone tube) of 1.5 mm inner diameter and 3.5 mm outer diameter. PDMS tubes were preconditioned for four hours by soaking approximately 5 mm pieces in a 1:1 mixture of acetonitrile and methanol. They were then dried using ultra-high-purity nitrogen gas and conditioned in a Gerstel Tube Conditioner by heating at 210°C over the stream of nitrogen gas at 5 L/min (4 bar constant pressure) for 3 hours (Kallenbach et al. 2014 ; Nordström et al. 2017 ; Nair et al. 2018 ). The entire process was repeated twice, following which the tubes were stored in -20 degrees Celsius in amber vials till use. Headspace sampling was conducted by exposing four PDMS tubes suspended on a copper wire over the top of glass vials containing urine or scat samples for 4 hours (Fig. 2 ) (Nair et al. 2018 ). The vials were sealed with aluminium foil and parafilm during sampling to prevent odours from escaping or other contaminants from entering the vial. The headspace sampling was conducted within a few hours of sample collection. After sampling, the tubes were stored in sterile 2 ml amber glass vials at -20 degrees Celsius. Thermal desorption- Gas Chromatography-Mass spectrometry. The volatiles were isolated and identified using a Thermal Desorption Unit-Gas Chromatography-Mass Spectrometer setup. Samples collected on PDMS tubes were introduced via a Gerstel MultiPurpose Sampler (MPS), which desorbs the volatiles from the PDMS tubes, cryofocusses them, and directly introduces them to GC-MS. Gerstel Thermal Desorption Unit (TDU) in conjunction with Cooled Injection System (CIS 4) was used, which was controlled by the Gerstel Modular Analytical Systems Controller C506 and the Gerstel Maestro 1 software. Analysis was performed on an Agilent 7890B gas chromatograph coupled with a 5977A MSD mass spectrometer with HP-5 MS column (30 m × 0.25 mm id, 0.25 µm film thickness) and helium as the carrier gas at a 1 ml/min flow rate. The column oven was kept at 40°C for 1 min, increased to 180°C at a rate of 5°C/min, and finally increased to 270°C (with a 30 min holding temperature) in the second ramp at 25°C/min. The transfer line between the GC and MS was maintained at 250°C, whereas the source and quadrupole temperatures were 230 and 150°C, respectively. Ionization was performed in electron impact mode with an ionization energy of 70 eV. Detailed parameters can be found in Nair et al.,2018. GC-MS data integration, peak extraction, clean up and compound identification. GC-MS acquisition was performed using Agilent MassHunter Workstation software B.07.02.1938, and qualitative analysis was carried out by MassHunter Qualitative Analysis Version B.07.00. Peak integration for urine and scat samples was carried out using Chemstation with a peak width of 0.1 minute, Area and height rejection of 10000 units, relative height 1%, and relative area 0.5%. This data was extracted into .csv files, which were run through a custom Python script to identify unique peaks by combining Retention Time (RT) and Base Peak (BP) values. The script also removed RT- BP combinations present in environmental control files and contaminating peaks such as from substrate and handling (adapted from Nair et al., 2018 ). Area of peaks with the same BP +/- 0.3 RT were summed up and since these tend to be from compounds with peak widths higher than 0.1 minute. An internal standard present in PDMS is the peak octamethylcyclotetrasiloxane was used to normalize all peak areas (Kallenbach et al., 2014 ). Finally, only volatiles detected in 15% (10% for the analysis of disease) of the samples were retained for downstream analysis ensuring that retained compounds were consistently observed across samples and further removed any environmental volatiles from uncommon substrates. Potential analytes of interest were identified using a combination of three methods, similar to (Nordström et al. 2017 and (Nair et al. 2018 ): A) Comparing mass spectral data of the unknown peaks with library spectra [National Institute of Standards and Technology (NIST)], B) Comparing peak Kovat’s retention index (using C8– C40 alkanes standard, Sigma Aldrich, Bangalore, India), and C) Comparing to authentic standards (that were commercially available) run with the same GC column and oven parameters as samples. Random forest analysis: A Random Forest (RF) classification framework was used to identify the most informative volatiles since this approach has been found to be effective in low signal-to-noise ratio data (Nair et al. 2018 ; Ranganathan and Borges 2010 ). The Python library Scikit-learn (Pedregosa et al. 2011) was used to carry out Random Forest for the classification of urine and scat volatiles into the following categories: Species: tiger and leopard Sex: male and female and Age: old (more than 10 years of age) and young (less than 10 years of age) Reproductive state: Non-reproductive and reproductive (lactating and pregnant) and Health status: healthy and unhealthy. The random forest approach used here is based on (Ranganathan and Borges 2010 ; 2011) which accommodates smaller sample size. 100 independent RF classifier runs with 100 trees and a unique random seed were trained on the full dataset for each analysis. For the wild urine samples, only one sample per marking event was used per run, and we cycled through multiple technical replicates to ensure exclusion of pseudoreplicates in the same run. Gini importance was recorded per run and five top features with highest average over all runs were identified. The differences in the top-ranked volatiles between the different categories examined were visualized with jitter and dot-whisker plots (where the dot is the mean and whiskers are 95 percent confidence intervals) using the Seaborn library (Waskom 2021 ). Subsequently, we evaluated classification performance using the top three to five overall features by carrying out 5-fold CV accuracy for individual volatiles as well as volatile combinations across 10 independent runs with 100 trees each and visualized the classification accuracy using confusion matrix. RESULTS Non-invasive sampling of volatiles from big cat excretions. Scat and urine samples were collected from nine captive tiger individuals and sixteen captive leopards. Although we attempted to sample 5 replicates for each individual, sample availability at the time of collection varied and we were able to sample 1 to 5 replicates per individual (on an average three replicates per individual). We also collected 14 environmental controls. The number of replicates per individual and other relevant details is listed in Supplementary Table 2. During sample collection in Bannerghatta Biological Park, one of the individuals was being treated for epileptic seizures and died under treatment. This remains the only known health-compromised individual we were able to sample. From the wild, we collected 144 urine samples from 28 individually identified tigers of different age and reproductive status and 27 environmental controls from different substrates (Supplementary Table 3). Notably, 21 of these samples were from four pregnant or lactating females. Forty-five of the urine samples collected from wild were excluded during the filtering following GC-MS analyses, because they had 10 or fewer volatiles detected. The remaining 107 samples included technical replicates and the final sample sizes for age and sex classification are provided in Supplementary Table 4. We were not able to sample any scats from identified tiger individuals in the wild but unidentified scats were sampled and found to have similar volatile profiles as the zoo samples. Likewise, we were not able to acquire any samples from identified leopards in the wild. Representative chromatograms for samples collected in this study are in Fig. 3 . Although our focus was on identifying diagnostic volatiles and not creating an exhaustive list of all tiger and leopard compounds, we carried out compound identification of the major peaks and further identified compounds that were deemed significant by the random forest analysis. Supplementary Tables 5 and 6 summarize the volatiles and the criteria for identification for each volatile. Volatiles differences between tigers and leopards. Based on Gini values over 100 random forest runs, three urine volatiles and three scat volatiles emerged as consistent predictors for distinguishing species (Fig. 4 ). Among urine volatiles, γ-dodecalactone, 2-decanone and N-isopentylidene isopentylamine were found to be elevated in tiger samples. In scat, δ-valerolactam was higher in tigers whereas p-cresol and 2-ethylhexanol were higher in leopard scats (Fig. 4 ). The highest classification accuracy for urine volatiles was achieved using a combination of γ-dodecalactone and 2-dodecanone (0.79 + 0.009; 5-fold CV). For scat volatiles, the best classification accuracy was achieved when using a combination of all three volatiles in Fig. 4 (0.75 + 0.029; 5-fold CV). Misclassification error rate was higher for tigers in the urine-based classification and higher for leopards in the scat-based classification. Scat and urine volatiles differences between age and sex in leopards.Age and sex differences in leopards could be consistently determined from six urine volatiles (Fig. 5 ). 2,4-Di-Tert-Butyl Phenol (2,4-DTBP), N-isopentylidene isopentylamine and Indole were higher in urine of young leopards. 2,4-DTBP was also associated with sex differences-it was higher in female leopards while phenol and indole were higher in urine of male leopards (Fig. 5 ). The highest classification accuracy for age was obtained with a combination of 2,4-DTBP and N-isopentylidene isopentylamine (0.65 + 0.029; 5-fold CV) but the misclassification error rate was high for old leopards. Highest classification accuracy for sex was achieved with 2,4-DTBP alone but misclassification error rate was high for Fig. 5 (0.55 + 0.03; 5-fold CV). Six scat volatiles (Fig. 6 ) that are top predictors in identifying age and sex were identified (Supplementary Table 2). Isovaleric acid, δ-valerolactam and γ-dodecalactone were elevated in young leopards. Methoxy acetic acid, phenylethyl alcohol and 2-dodecanone were higher in male leopards (Fig. 6 ). The classification accuracy for age was highest with a combination of δ-valerolactam and γ-dodecalactone (0.65 + 0.029; 5-fold CV). The classification accuracy for sex was highest for a combination of methoxyacetic acid and phenylethyl alcohol (0.61 + 0.06; 5-fold CV). Scat and urine volatiles differences between age and sex in tigers. Four tiger urine volatiles consistently differed with age and sex (Fig. 7 ). 2,4-DTBP and an adamantane-like compound was higher in females while γ-dodecalactone was higher in male tiger urine samples. 2,4-DTBP, Phenylethyl alcohol and γ-dodecalactone were higher in old tigers. The highest classification accuracy for sex was achieved with a combination of 2,4-DTBP and the adamantane-like compound (0.64 + 0.01; 5-fold CV) whereas 2,4-DTBP alone (0.55 + 0;5-fold CV) gave the highest classification accuracy for age. However, the misclassification error rate for old (40%) and male (50%) tigers was higher. We found four tiger scat volatiles consistently differing with age and sex (Fig. 8 ). Methoxyacetic acid, isovaleric acid and δ-valerolactam were higher in male tiger scat samples whereas isovaleric acid, γ-dodecalactone and dimethyl trisulfide were higher in old tigers. The highest classification accuracy for sex was achieved with methoxyacetic acid alone (0.71 + 0.057;5-fold CV) whereas the highest classification accuracy for age was achieved with γ-dodecalactone alone (0.63 + 0.048;5-fold CV). However, again, the misclassification error rate for old tigers was high at 53%. Putative chemical cues for reproductive and health state in tigers. During pilot experiments where we used glasswool to collect urine samples, a sample of a lactating female tiger showed peaks at retention time 18 to 23 minutes that were absent from a non-lactating sample (Fig. 9 A). The identity of this peak could not be accurately elucidated but appeared to be a pentose-like compound. The volatiles from samples of lactating, pregnant and non-reproductive females collected using PDMS were analysed using random forest. The top predictor was found to be nonanol, which was much higher in lactating and pregnant females than non-reproductive females (Fig. 9 B). We could not sample scats for varying reproductive states. We sampled both scat and urine for one captive tiger that was being treated for epilepsy and died during the course of treatment. We found elevated levels of dimethyl tetrasulphide in scats of the epileptic tiger but could not detect any distinctive volatiles in the urine (Fig. 9 C). Due to the limited sample size for these attributes, we did not attempt to assess the classification accuracy for the tested groups. DISCUSSION Chemical secretions may harbour info chemicals that could offer non-invasive tools for wildlife monitoring and diagnostics (Cumeras et al. 2014 ; Burnham et al. 2008 ; Jones et al. 2021 ). As conservation increasingly moves towards precision monitoring of diseases, reproduction, and fitness effects at the individual level, chemical ecology could provide powerful insight into non-invasive wildlife diagnostics by enabling collection and analysis of informative volatiles (Vet 1999; Meinwald and Eisner 2008 ; Soso et al. 2014 ). However, such studies have been limited; primarily due to technical challenges in sampling wild and often elusive nature of species. These technical challenges include obtaining and storing the sample, extracting volatiles, and identifying the compound. Recent advancements have addressed these challenges, with innovative sampling methods explicitly developed for wildlife research (Kücklich et al. 2017 ; Nair et al. 2018 ; Thompson et al. 2020 ). In this study, we utilized one such method to investigate volatile organic compounds (VOCs) in two charismatic carnivore species known for their scent-marking behaviour- a topic of interest to both scientists and laypersons (Brahmachary et al. 1992 ; Poddar-Sarkar and Brahmachary 2004). We used a sorbent (polydimethylsiloxane; PDMS) to extract volatiles from the headspace of scats and urine and analysed them as per Nair et al., 2018 . Given the popularity of these carnivores, prior research had focussed on the chemical characterization and understanding the origin of odours. Our study is the first attempt to sample tiger odours in the wild, wherein we identified volatiles that differ in sex, age and reproductive status in tigers and evaluated their potential as a diagnostic test. It is also the first attempt in sampling leopard odours non-invasively from individuals of known age and sex. Territorial marking is one of the most frequently observed behaviours in tigers, prompting us to design a field sampling approach that involved following identified individuals to collect urine and scat samples. Like many field-based studies, this work faced unavoidable constraints. We could not sample scats from identified tigers in the wild (similar to Khan et al. 2020 ). Leopards are more nocturnal and elusive; we could not sample identified individuals in the wild. Hence, our identified tiger scat and all leopard samples are solely from captive individuals. We aimed to sample individuals of known age, sex, and health status. However, captive tigers were not reproductively active, and the zoo staff regularly managed their health through vaccinations and medical treatment, limiting our ability to study odours related to reproduction and health conditions. In contrast, wild samples included individuals in different reproductive states. These challenges reflect the difficulty of working with elusive and endangered species rather than flaws in study design. Despite these limitations, this is, to our knowledge, the first study to elucidate identified volatiles for tigers and leopards, offering critical baselines for future work. While sampling urine, we observed that different substrates had different levels of urine retention: trees absorbed the liquid component of urine quickly, leaving only a faint smell, while urine sprayed on rocks and soil generally retained a strong-smelling liquid, which could yield better results. Nevertheless, the odours from urine sometimes lasted for hours and even days at temperatures as high as 48 degrees Celsius. Our final dataset included volatiles sampled irrespective of the substrate on which the urine was sprayed. Scats contain a large proportion of non-host material, such as dietary remains and microbes, and their odour cues could also vary significantly with diet (Depauw et al. 2013 ). We also found halogenated compounds in tiger scats, which might be from the environment (e.g. cleaning chemicals used for cleaning cages). Scats degrade quickly in summer and could get washed away in the rainy season, making this a reliable sampling strategy only in winter. In contrast, urine samples produced clearer signals and could be sampled in winter and summer. However, scat volatiles were more effective in identifying tiger samples and classifying sex. Urine volatiles were more effective in classifying leopards, but there was a high misclassification rate for old and male individuals in both leopards and tigers. One reason for this pattern could be the statistical bias of machine learning algorithms towards learning patterns of the majority class in imbalanced datasets (Khoshgoftaar et al. 2007). The lower sample size for old and male individuals could have led to lower sensitivity in detecting these groups. We did not apply class balancing techniques to avoid introducing artificial variation, especially in light of the small dataset. We report misclassification rates and class distributions transparently, and interpret results in light of sample size limitations. In spite of these limitations, biological explanations cannot be ruled out particularly because the sample size skew is mainly towards sex classification in tiger urine samples. The observed patterns could also result from higher individual variation in old and male individuals due to physiological and microbiome changes (Wilson and Harrison 1983; Worsley et al. 2024 ). Old males are thought to be subject to lower selective pressure for sexual and territorial signalling, leading to a loss of a faded or inconsistent chemical signature (Garratt et al. 2011 ). The species level patterns in volatile differences might also offer insights into the biological role of specific VOCs. The higher amounts of specific urine volatiles in tigers compared to leopards may indicate the role of these compounds in dominance-related signalling (such as in blackbucks: Rajagopal et al. 2018 ). In contrast, variations in scat volatiles can be more plausibly attributed to differences in diet (Farrell et al. 2000 ; Depauw et al. 2013 ). Another significant challenge in analysing volatile samples collected in situ is the high noise-to-signal ratio, complicating data interpretation. Previous studies have employed supervised clustering techniques to address this issue (Ranganathan and Borges 2010 ; Nair et al. 2018 ; Noonan et al. 2019 ). For our analysis, we opted for the Random Forest algorithm, which has previously demonstrated efficacy with PDMS-based volatile data (Nair et al. 2018 ). Random forest algorithms have strong classification ability and provide variable importance measures, which are important for biological interpretation (Breiman 2001 ). We modified this approach as per (Ranganathan and Borges 2010 ) to optimize its performance for our study and ensure reproducibility. Since our samples contained many environmental volatiles, we extensively sampled different substrates to subtract the environmental volatiles and retain only putative tiger and leopard compounds. The pipeline outlined here for generating input data and analyses can be adapted for other species. The musky, sweet, and fruity smells of tiger and leopard urine come from γ-dodecalactone, δ-valerolactam, heptanoic acid, decanoic acid, phenol, and indole. Several of these volatiles have been reported from the urine of other carnivore species, including previous studies on tiger, leopard and lion urine (Brahmachary et al. 1992 ; Andersen and Vulpius 1999 ; Poddar-Sarkar and Brahmachary 2004; Burger et al. 2008 ; Tomberlin et al. 2017; Soso and Koziel 2016 ; McLean et al. 2021 , Root-Gutteridge et al. 2025). Long-chain fatty acids such as palmitic acid and oleic acid are thought to prevent the fast release of volatiles, helping the smell compounds stay in the environment long after it is released (Poddar-Sarkar 1996 ). We also found sulphur-containing compounds such as dimethyl trisulphide. This study did not detect the compound 2-acetyl-1-pyrroline, which is supposed to be the cause of the popcorn-like smell in tiger urine (Brahmachary and Sarkar 1990). This study was the first attempt to characterize volatile compounds in tiger and leopard faeces. We found several volatiles identified previously from the faeces of other carnivores: indole, isovaleric acid, methyl pentanoic acid, and naphthalene (Apps et al. 2012 ; Uetake et al, 2017.; Barja et al. 2023 ). We surveyed literature for occurrences in other species of the volatiles found to be important predictors in tigers. γ-dodecalactone was higher in the urine of tigers and scats of young leopards and differed with age and sex in tiger urine and with age in tiger scats. An isomer of this compound, δ -dodecalactone, was identified in a previous study on tiger urine and found to differ with sex in the urine of the maned wolf (Jones et al. 2021 ). γ-dodecalactone was also identified in Siberian hamster urine and found to increase with aggression (Rendon et al. 2016 ). Isovaleric acid, phenol, δ-valerolactam, ethyl hexanol, phenylethyl alcohol, indole, dimethyl trisulfide, and p-cresol are reported in many carnivores, including lions, tigers, and leopards (Raymer et al. 1984 ; Kean et al. 2011 ; Soso and Koziel 2016 ; Mitchell et al. 2018 ; Jones et al. 2021 ). 2-Decanone is found in many insects and anal gland secretions of ferrets (Crump 1980 ; Zhang et al. 2005 ), whereas 2-dodecanone is found in many insects and Defassa waterbuck body odour (Gikonyo et al. 2002 ). Dimethyl tetrasulphide is reported in microorganisms (Tellez et al. 2001 ). Nonanol, higher in lactating and pregnant tigers, is a common aliphatic compound in many insects (Duffield, 1981 )). N-Isopentylidene isopentylamine imine is a compound commonly found in putrefying substances and is thought to be a component of the smell of aquatic animals (Jones et al. 2022 ). Our results demonstrate the promise of an inexpensive, easy-to-use, and non-invasive method for sampling age, sex, and reproductive parameters in wild tigers and leopards using VOCs. VOC sampling could provide valuable complementary insights in landscapes where camera trapping, genetic and hormone-based methods deliver inconclusive results, and can also be useful for cryptic physiological parameters such as age and disease status. Camera trap images are often unreliable in detecting and estimating age and reproductive status of felids (Joubert et al. 2020 , Lu et al. 2024 ). Recent approaches to ageing based on telomere and methylation patterns are limited by high individual variation (Lemaître et al. 2022 ; Pepke 2024). Similarly genetic approaches to sexing from non-invasive samples have been found to have variable success rates (Robertson and Gemmell 2006 ; Nichols and Spong 2017; Turcu et al. 2023 ). Hormonal approaches are not sufficiently validated in non-invasive sources and require intensive pre-processing (Shutt et al. 2012; Terwissen et al. 2014 ). To the best of our knowledge, our volatilomics approach proposed here is a uniquely field-applicable and cost effective method for non-invasively estimating the age and reproductive states of tigers and leopards. However, we were unable to sample cubs since they do not typically mark their territories. This emphasizes the need to use camera trapping along with VOC monitoring since cubs can be detected on camera traps. In addition to demographic monitoring, a volatilomics approach can further address management challenges. For example, it could be used to identify individuals that have consumed human flesh based on scat volatiles for diet and to track the fitness effects of inbreeding. Volatiles also have great potential to diagnose health parameters, as shown with prior work (Cumeras et al. 2014 ; Sha et al. 2024 ) and suggested with the four samples of one tiger individual in our dataset. The elevated dimethyl tetrasulfide detected in the four samples from one captive tiger being treated for epileptic seizures should be interpreted cautiously since it is based on a single individual and therefore no diagnostic inference can be drawn from this isolated case. However, this makes the case for the need of a systematic study of routine health complications in tigers and associated VOCs which could enable early detection and prevention of diseases in big cats. Importantly, our sampling was restricted only to one population of wild tigers. Volatiles can change with diet, and their stability might vary with weather, temperature, and other environmental variables. Sampling across tiger and leopard populations would better test the generality and robustness of these volatile markers. This study demonstrates how volatilomics approaches hold the potential to obtain many different kinds of information from wild populations. Integrating the volatilomics approach to microbiome, genetics, and behavioural data could provide valuable insights into scent communication in felids (Archie and Theis 2011 ; Stockley et al. 2013 ; Fialová et al. 2020 ). Studies on big cat behaviour could help design bioassays that test whether the volatiles found in this study are also involved in tiger and leopard communication. The current limitation with conducting such bioassays is a lack of information about big cat behaviour: for example, how would a male tiger react to a female's urine versus a male's urine? Future work could integrate field behaviour studies with bioassays in captive populations to elucidate the role of volatiles in signalling and communication (Root-Gutteridge et al. 2025). The identification of such compounds could greatly help in identification of tiger and leopard attractants and deterrents as well as pheromones which can aid ex situ breeding programs. Inbreeding avoidance has been found to be mediated through odours in several species (Pfaff et al. 2004 ; Hagelin 2007 ; Boulet et al. 2009; Bonadonna and Sanzaguilar 2012). Although such mechanisms are thought to evolve mostly in species where kin are encountered frequently (which is not the case in these big cats), the reliance on chemical communication in a solitary species suggests that their odours might encode information about fitness and inbreeding. For instance, inbreeding depression in sex hormones might reflect in volatiles associated with testosterone or female hormones and odour signals of inbreeding have been identified in insects (Ilmonen et al. 2009 ; van Bergen et al., 2013; Menzel et al. 2016). Generating genetic as well as chemical data could help detect the possible presence of such odours and mechanisms in big cats. To conclude, our success in reliably sampling volatiles and distinguishing individuals by age and sex demonstrates the potential of this approach as a powerful, non-invasive tool for wildlife monitoring and is applicable to other species. With further validation, volatilomics could be integrated into conservation strategies for wild tiger populations, aiding in demographic assessments, health diagnostics, and long-term population management. Declarations Conflicts of Interest: The authors have no conflicts of interest to declare. Funding: This work was supported by National Geographic Society (EC-68219R-20 to BVA), National Centre for Biological Sciences-TIFR (UR and SO), Bangalore and Ahmedabad University (CD). Author contributions: BVA: Conceptualization, Data curation, Funding acquisition, Methodology, Investigation: field work, lab work, formal analysis, Visualization, Writing – original draft, Writing-review and editing, Project administration; CD: Investigation: field work; DS: Software, UR and SO: Conceptualization, Methodology, Supervision, Validation, Writing-review and editing, Project administration, Funding acquisition Author Contribution BVA: Conceptualization, Data curation, Funding acquisition, Methodology, Investigation: field work, lab work, formal analysis, Visualization, Writing – original draft, Writing-review and editing, Project administration; CD: Investigation: field work; DS: Software, UR and SO: Conceptualization, Methodology, Supervision, Validation, Writing-review and editing, Project administration, Funding acquisition Acknowledgement BVA received fellowship support from NCBS-TIFR, Bangalore and CD from University Grants Commission, India. We thank the NCBS Mass Spectrometry Facility for enabling the analysis. The authors acknowledge Mujahid Khan, Krishna Avatar, Vasim, Kritagnya Vadar, Prerak Pathak, Faizee Ali Khan, and Samar Ahmad for assistance with field sampling; and Nelum Wickramsinghe and Bhaavya Malpani for assistance with lab work. We thank Dr. Ratna Ghoshal, Zoos of Baroda, Ahmedabad and Bangalore for facilitating the zoo sample collection and Prof. Kamala Jayanthi for sharing reagents. We thank Jyoti Nair, Srinivas, Yuvaraj Ranganathan and Harindra L. Baraiya for inputs on analysis and Prasenjeet Yadav for picture of tiger marking territory in Figure 1. Data Availability GC-MS data is available with the corresponding author upon reasonable request. In the event of acceptance, the data will be made public through an online repository. References Ache BW, Young JM (2005) Olfaction: Diverse Species. Conserved Principles Neuron 48(3):417–430. https://doi.org/10.1016/j.neuron.2005.10.022 Allen ML, Heiko U, Wittmer, Emmarie P, Alexander, Wilmers CC (2021) Ontogeny of Scent Marking Behaviours in an Apex Carnivore. 1. https://doi.org/10.1163/15685394X-bja10127 Amo L, Magdalena Ruiz Rodríguez (2023) Editorial: The Importance of Olfaction in Intra- and Interspecific Communication, II. Front Ecol Evol 11. https://doi.org/10.3389/fevo.2023.1261271 Andersen KF, Vulpius T (1999) Urinary Volatile Constituents of the Lion, Panthera Leo. Chem Senses 24(2):179–189. https://doi.org/10.1093/chemse/24.2.179 Andersen KF (1998) Chemocommunication and Social Behaviour in Three Panthera Species in Captivity, with Particular Reference to the Lion, P.Leo. 13. https://doi.org/10.17863/CAM.16416 Anile S, and Sebastien Devillard (2018) Camera-Trapping Provides Insights into Adult Sex Ratio Variability in Felids. Mammal Rev 48(3):168–179. https://doi.org/10.1111/mam.12120 Apps P, Mmualefe L, Jordan NR, Golabek KA, Weldon McNutt J (2014) The ‘Tomcat Compound’ 3-Mercapto-3-Methylbutanol Occurs in the Urine of Free-Ranging Leopards but Not in African Lions or Cheetahs. Biochem Syst Ecol 53(April):17–19. https://doi.org/10.1016/j.bse.2013.12.013 Apps P, Mmualefe L, Weldon J, McNutt (2012) Identification of Volatiles from the Secretions and Excretions of African Wild Dogs (Lycaon Pictus). J Chem Ecol 38(11):1450–1461. https://doi.org/10.1007/s10886-012-0206-7 Archie EA, Theis KR (2011) Animal Behaviour Meets Microbial Ecology. Anim Behav 82(3):425–436. https://doi.org/10.1016/j.anbehav.2011.05.029 Artois M, Bengis R, Delahay RJ et al (2009) Wildlife Disease Surveillance and Monitoring. In Management of Disease in Wild Mammals, edited by Richard J. Delahay, Graham C. Smith, and Michael R. Hutchings. Springer Japan. https://doi.org/10.1007/978-4-431-77134-0_10 Barja I, Piñeiro A, Ruiz-González A, Caro A, López P, and José Martín (2023) Evaluating the Functional, Sexual and Seasonal Variation in the Chemical Constituents from Feces of Adult Iberian Wolves (Canis Lupus Signatus). Sci Rep 13:6669. https://doi.org/10.1038/s41598-023-33883-9 Bayn A, Nol P, Tisch U, Rhyan J, Ellis CK, and Hossam Haick (2013) Detection of Volatile Organic Compounds in Brucella Abortus-Seropositive Bison. Anal Chem 85(22):11146–11152. https://doi.org/10.1021/ac403134f Beauchamp GK, Doty RL, Moulton DG, Mugford RA (1976) The Pheromone Concept in Mammalian Chemical Communication: A Critique. In Mammalian Olfaction, Reproductive Processes, and Behavior. Elsevier. https://doi.org/10.1016/b978-0-12-221250-5.50012-7 van Bergen E, Brakefield PM, Heuskin Stéphanie, Zwaan BJ, Caroline M, Nieberding n.d. The Scent of Inbreeding: A Male Sex Pheromone Betrays Inbred Males. Proceedings. Biological Sciences 280 (1758): 20130102. https://doi.org/10.1098/rspb.2013.0102 Bonadonna F, Ana Sanz-aguilar (2012) Kin Recognition and Inbreeding Avoidance in Wild Birds: The Fi Rst Evidence for Individual Kin-Related Odour Recognition. Anim Behav 84(3):509–513. https://doi.org/10.1016/j.anbehav.2012.06.014 Boulet Marylène, Charpentier MJ, and Christine M. Drea (2009) Decoding an Olfactory Mechanism of Kin Recognition and Inbreeding Avoidance in a Primate. BMC Evol Biol 9(1):1–11. https://doi.org/10.1186/1471-2148-9-281 Brahmachary R, Sarkar M, Dutta J (1990) The Aroma Of Rice … And Tiger. Nature 344:26 https://Doi.Org/10.1038/344026b0 Brahmachary RL, Sarkar MP, Dutta J (1992) Chemical Signals in the Tiger. In Chemical Signals in Vertebrates 6. Springer US. https://doi.org/10.1007/978-1-4757-9655-1_72 Breiman L (2001) Random Forests. Mach Learn 45(1):5–32. https://doi.org/10.1023/A:1010933404324 Brennan PA, Keith MK (2006b) Mammalian Social Odours: Attraction and Individual Recognition. Philosophical Trans Royal Soc B: Biol Sci 361(1476):2061–2078. https://doi.org/10.1098/RSTB.2006.1931 Buljubasic F, and Gerhard Buchbauer (2015) The Scent of Human Diseases: A Review on Specific Volatile Organic Compounds as Diagnostic Biomarkers. Flavour Fragr J 30(1):5–25. https://doi.org/10.1002/ffj.3219 Burger BV, Viviers MZ, Bekker JPI et al (2008) Chemical Characterization of Territorial Marking Fluid of Male Bengal Tiger, Panthera Tigris. 659–671. https://doi.org/10.1007/s10886-008-9462-y Burger BV (2005) Mammalian Semiochemicals. In The Chemistry of Pheromones and Other Semiochemicals II: -/-, edited by Stefan Schulz. Springer. https://doi.org/10.1007/b98318 Burnham E, Bender LC, Eiceman GA, Prasad S, and Karisa M. Pierce (2008) Use of Volatile Organic Components in Scat to Identify Canid Species. J Wildl Manage 72(3):792–797. https://doi.org/10.2193/2007-330 Candolin U (2003) The Use of Multiple Cues in Mate Choice. Biol Rev 78(4):575–595. https://doi.org/10.1017/S1464793103006158 Castro-Prieto A, Wachter B, and Simone Sommer (2010) Cheetah Paradigm Revisited: MHC Diversity in the World’s Largest Free-Ranging Population. Mol Biol Evol 28(4):1455–1468. https://doi.org/10.1093/molbev/msq330 Crump DR (1980) Anal Gland Secretion of the Ferret (Mustela Putorius formaFuro). J Chem Ecol 6(4):837–844. https://doi.org/10.1007/BF00990407 Cumeras R, Cheung WHK, Gulland F, Goley D, Cristina ED (2014) Chemical Analysis of Whale Breath Volatiles: A Case Study for Non-Invasive Field Health Diagnostics of Marine Mammals. Metabolites 4:790–806. https://doi.org/10.3390/metabo4030790 Daszak P (2000) Emerging Infectious Diseases of Wildlife– Threats to Biodiversity and Human Health. Science 287 (5452): 443–49. https://doi.org/10.1126/science.287.5452.443 Dehnhard M (2011) Mammal Semiochemicals: Understanding Pheromones and Signature Mixtures for Better Zoo-Animal Husbandry and Conservation. Int Zoo Yearbook 45(1):55–79. https://doi.org/10.1111/j.1748-1090.2010.00131.x Depauw S, Hesta M, Whitehouse-Tedd K, Vanhaecke L, Verbrugghe A, Janssens GPJ (2013) Animal Fibre: The Forgotten Nutrient in Strict Carnivores? First Insights in the Cheetah. J Anim Physiol Anim Nutr 97(1):146–154. https://doi.org/10.1111/j.1439-0396.2011.01252.x Duffield R (1981) 2-Nonanol In The Exocrine Secretion Of The Nearctic Caddisfly, Rhyacophila Fuscula (Walker) (Rhyacophilidae: Trichoptera). 2-Nonanol In The Exocrine Secretion Of The Nearctic Caddisfly, Rhyacophila Fuscula (Walker) (Rhyacophilidae: Trichoptera) Farrell LE, Roman J, Sunquist ME (2000) Dietary Separation of Sympatric Carnivores Identified by Molecular Analysis of Scats. Mol Ecol 9(10):1583–1590. https://doi.org/10.1046/J.1365-294X.2000.01037.X Favaro R, Pettersson M, Thöming G et al (2024) The Use of Volatile Organic Compounds in Preventing and Managing Invasive Plant Pests and Pathogens. Front Hortic 3. https://doi.org/10.3389/fhort.2024.1379997 Fialová J, Třebický Vít, Kuba R, Stella D, Binter J, Havlíček J (2020) Losing Stinks! The Effect of Competition Outcome on Body Odour Quality. Philosophical Trans Royal Soc B: Biol Sci 375(1800):20190267. https://doi.org/10.1098/rstb.2019.0267 Fromhage L, and Jonathan M. Henshaw (2022) The Balance Model of Honest Sexual Signaling. Evolution. Int J Org Evol 76(3):445–454. https://doi.org/10.1111/evo.14436 Garratt M, Stockley P, Armstrong SD, Beynon RJ, Hurst JL (2011) The Scent of Senescence: Sexual Signalling and Female Preference in House Mice. J Evol Biol 24(11):2398–2409. https://doi.org/10.1111/j.1420-9101.2011.02367.x Ghoddousi A (2023) and I. Khorozyan. Panthera Pardus Ssp. Tulliana. The IUCN Red List of Threatened Species 2023: E. T15961A50660903. https://api.pelewg.net/storage/projects/1716645050009-IUCN%20Red%20List%20account_2023.pdf Gikonyo NK, Hassanali A, Peter GN, Njagi, Peter M, Gitu, Midiwo JO (2002) Odor Composition of Preferred (Buffalo and Ox) and Nonpreferred (Waterbuck) Hosts of Some Savanna Tsetse Flies. J Chem Ecol 28(5):969–981. https://doi.org/10.1023/a:1015205716921 Gilbert M, Miquelle DG, Goodrich JM et al (2014) Estimating the Potential Impact of Canine Distemper Virus on the Amur Tiger Population (Panthera Tigris Altaica) in Russia. PLoS ONE 9(10):e110811. https://doi.org/10.1371/JOURNAL.PONE.0110811 Goodrich J, Wibisono H, Miquelle D et al (2022) Panthera Tigris. The IUCN Red List of Threatened Species 2022: E. T15955A214862019. https://sintas.or.id/wp-content/uploads/2022/11/IUCN-Tiger-2022.pdf Grosbois V, Bonadonna F, Bessiere J-M, Miguel E, and Pierre Jouventin (2007) Individual Odor Recognition in Birds: An Endogenous Olfactory Signature on Petrels’ Feathers? J Chem Ecol 33(9):1819–1829. https://doi.org/10.1007/s10886-007-9345-7 Hagelin JC (2007) Odors and Chemical Signaling. Reproductive Biology and Phylogeny of Birds, Part B: Sexual Selection, Behavior, Conservation, Embryology and Genetics. CRC Hagey L, and Edith Macdonald (2003) CHEMICAL CUES IDENTIFY GENDER AND INDIVIDUALITY IN GIANT PANDAS (Ailuropoda Melanoleuca). J Chem Ecol No 6, vol. 29 Harmsen BJ, Rebecca J, Foster E, Sanchez et al (2017) Long Term Monitoring of Jaguars in the Cockscomb Basin Wildlife Sanctuary, Belize; Implications for Camera Trap Studies of Carnivores. PLoS ONE 12(6):e0179505. https://doi.org/10.1371/journal.pone.0179505 Ilmonen P, Stundner G, Thoß M, Dustin JP (2009) Females Prefer Scent Outbred Males 10:1–10. https://doi.org/10.1186/1471-2148-9-104 Tomberlin JK, Crippen TL, Wu G, Griffin AS, Wood TK, Kilner RM (2016) Indole An E Conserved Influencer of Behavior across Kingdoms. Bioessays https://onlinelibrary.wiley.com/doi/10.1002/bies.201600203 Jhala YV, Qureshi Q, and R. (eds) (2015) Gopal. Status of Tigers in India 2014. National Tiger Conservation Authority, New Delhi & The Wildlife Institute of India, Dehradun, no. June: 1–25 Jones BC, Melissa M, Rocker, Russell SJ, Keast et al (2022) Systematic Review of the Odorous Volatile Compounds That Contribute to Flavour Profiles of Aquatic Animals. Reviews Aquaculture 14(3):1418–1477. https://doi.org/10.1111/raq.12657 Jones MK, Thomas B, Huff EW, Freeman, and Nucharin Songsasen (2021) Differential Expression of Urinary Volatile Organic Compounds by Sex, Male Reproductive Status, and Pairing Status in the Maned Wolf (Chrysocyon Brachyurus). PLoS ONE 16(8):e0256388. https://doi.org/10.1371/journal.pone.0256388 Joubert CJ, Tarugara A, Clegg BW, Gandiwa E, Muposhi VK (2020) A Baited-Camera Trapping Method for Estimating the Size and Sex Structure of African Leopard (Panthera Pardus) Populations. MethodsX 7. January101042. https://doi.org/10.1016/j.mex.2020.101042 Kallenbach M, Oh Y, Eilers EJ, Veit D, Ian T, Baldwin, Meredith CS (2014) A Robust, Simple, High-Throughput Technique for Time-Resolved Plant Volatile Analysis in Field Experiments. Plant J 78(6):1060–1072. https://doi.org/10.1111/tpj.12523 Kappeler PM, Benhaiem S, Fichtel C et al (2023) Sex Roles and Sex Ratios in Animals. Biol Rev 98(2):462–480. https://doi.org/10.1111/brv.12915 Karanth K, Ullas (1995) Models Biol Conserv 71(3):333–338. https://doi.org/10.1016/0006-3207(94)00057-W . Estimating Tiger Panthera Tigris Populations from Camera-Trap Data Using Capture—Recapture Katsuji Uetake T, Abumi T, Suzuki S Hisamatsu, Minoru (2017) and Fukuda. Volatile Faecal Components Related to Sex and Age in Domestic Cats (Felis Catus) Kean EF, Carsten T, Müller, Chadwick EA (2011) Otter Scent Signals Age, Sex, and Reproductive Status. Chem Senses 36(6):555–564. https://doi.org/10.1093/chemse/bjr025 Khan A, Patel K, Bhattacharjee S et al (2020) Are Shed Hair Genomes the Most Effective Noninvasive Resource for Estimating Relationships in the Wild? Ecol Evol 10(11):4583–4594. https://doi.org/10.1002/ece3.6157 Khoshgoftaar TM, Golawala M (2007) and Jason Van Hulse. An Empirical Study of Learning from Imbalanced Data Using Random Forest. 19th IEEE International Conference on Tools with Artificial Intelligence(ICTAI 2007) 2 (October): 310–17. https://doi.org/10.1109/ICTAI.2007.46 Kücklich M, Möller M, Marcillo A et al (2017) Different Methods for Volatile Sampling in Mammals. PLoS ONE 12(8):e0183440. https://doi.org/10.1371/journal.pone.0183440 Leal WS (2017) Reverse Chemical Ecology at the Service of Conservation Biology. Proceedings of the National Academy of Sciences 114 (46): 12094–96. https://doi.org/10.1073/pnas.1717375114 Lemaître J-F, Rey B, Gaillard J-M et al (2022) DNA Methylation as a Tool to Explore Ageing in Wild Roe Deer Populations. Mol Ecol Resour 22(3):1002–1015. https://doi.org/10.1111/1755-0998.13533 Lindgren PMF, Thomas P, Sullivan, Douglas RC (1995) Review of Synthetic Predator Odor Semiochemicals as Repellents for Wildlife Management in the Pacific Northwest Lu Z, Whitton R, Strand T, Chen Y (2024) Review of Predator Emitted Volatile Organic Compounds and Their Potential for Predator Detection in New Zealand Forests. Forests 15(2):227. https://doi.org/10.3390/f15020227 Manzoli A, Steffens C, Paschoalin RT et al (2019) Sens Actuators B 282:609–616. https://doi.org/10.1016/j.snb.2018.11.109 . Volatile Compounds Monitoring as Indicative of Female Cattle Fertile Period Using Electronic Nose. McLean S, Nichols DS, Davies NW (2021) Volatile Scent Chemicals in the Urine of the Red Fox, Vulpes Vulpes. PLoS ONE 16(3):e0248961. https://doi.org/10.1371/journal.pone.0248961 Meinwald J, Eisner T (2008) Chemical Ecology in Retrospect and Prospect. Proceedings of the National Academy of Sciences 105 (12): 4539–40. https://doi.org/10.1073/pnas.0800649105 Menzel F, Radke René, and Susanne Foitzik (2016) Odor Diversity Decreases with Inbreeding in the Ant Hypoponera Opacior. Evolution 70(11):2573–2582. https://doi.org/10.1111/evo.13068 Mitchell J, Kyabulima S, Businge R, Cant MA, Nichols HJ (2018) Kin Discrimination via Odour in the Cooperatively Breeding Banded Mongoose. Royal Soc Open Sci 5(3):171798. https://doi.org/10.1098/rsos.171798 Miyazaki M, Miyazaki T, Nishimura T, Hojo W, and Tetsuro Yamashita (2018) The Chemical Basis of Species, Sex, and Individual Recognition Using Feces in the Domestic Cat. J Chem Ecol 44(4):364–373. https://doi.org/10.1007/s10886-018-0951-3 Mondol, Samrat K, Ullas Karanth, and Uma Ramakrishnan (2009) Why the Indian Subcontinent Holds the Key to Global Tiger Recovery. PLoS Genet 5(8). https://doi.org/10.1371/journal.pgen.1000585 Munson L, Terio KA, Ryser-Degiorgis M-P, Lane EP, Courchamp F. Wild felid diseases: conservation implications and management strategies. Biology and conservation of wild felids 237 (2010): 259.Wilson, M. C., and, Harrison DE (1983) Decline in Male Mouse Pheromone with Age. Biology of Reproduction 29 (1): 81–86. https://doi.org/10.1095/biolreprod29.1.81 Nair JV, Shanmugam PV, Karpe SD, Ramakrishnan U, and Shannon Olsson (2018) An Optimized Protocol for Large-Scale in Situ Sampling and Analysis of Volatile Organic Compounds. Ecol Evol 8(11):5924–5936. https://doi.org/10.1002/ece3.4138 Nichols RV, Göran, Spong (2017) An eDNA-Based SNP Assay for Ungulate Species and Sex Identification. Diversity 9(3):33. https://doi.org/10.3390/d9030033 Noonan MJ, Tinnesand HV, Carsten T, Müller F, Rosell DW, Macdonald, and Christina D. Buesching (2019) Knowing Me, Knowing You: Anal Gland Secretion of European Badgers (Meles Meles) Codes for Individuality, Sex and Social Group Membership. J Chem Ecol 45(10):823–837. https://doi.org/10.1007/s10886-019-01113-0 Nordström K, Dahlbom J, Pragadheesh VS et al (2017) In Situ Modeling of Multimodal Floral Cues Attracting Wild Pollinators across Environments. Proceedings of the National Academy of Sciences 114 (50): 13218–23. world. https://doi.org/10.1073/pnas.1714414114 Bothma P, du J and E. A. N. le Richet. 1995. Evidence of the Use of Rubbing, Scent-Marking Andscratching-Posts by Kalahari Leopards. J Arid Environ 29 (4): 511–517. https://doi.org/10.1016/S0140-1963(95)80023-9 Pavlou AK, Turner APF (2000) Sniffing out the Truth: Clinical Diagnosis Using the Electronic Nose. Clinical Chemistry and Laboratory Medicine (CCLM). 38(2):99–112. https://doi.org/10.1515/CCLM.2000.016 Pedregosa, Fabian & Varoquaux, Gael & Gramfort, Alexandre & Michel, Vincent & Thirion,Bertrand & Grisel, Olivier & Blondel, Mathieu & Prettenhofer, Peter & Weiss, Ron &Dubourg, Vincent & Vanderplas, Jake & Passos, Alexandre & Cournapeau, David & Brucher,Matthieu & Perrot, Matthieu & Duchesnay, Edouard & Louppe, Gilles. (2012). Scikit-learn:Machine Learning in Python. Journal of Machine Learning Research. 12. Pepke, Michael L. 2024. “Telomere Length Is Not a Useful Tool for Chronological Age Estimation in Animals.” BioEssays 46 (2): 2300187. https://doi.org/10.1002/bies.202300187. Pfaff DW, Kavaliers M, Choleris E, and A Anders (2004) Olfactory-Mediated Parasite Recognition and Avoidance: Linking Genes to Behavior. 46:272–283. https://doi.org/10.1016/j.yhbeh.2004.03.005 Poddar-Sarkar M (1996) The Fixative Lipid of Tiger Pheromone. J Lipid Mediat Cell Signal 15(1):89–101. https://doi.org/10.1016/S0929-7855(96)00547-0 Poddar-Sarkar, Mousumi, Brahmachary RL (2004) Putative Chemical Signals of Leopard. Anim Biology 54(3):255–259. https://doi.org/10.1163/1570756042484692 Kasim Rafiq NR, Jordan C, Meloro AM, Wilson MW, Hayward SA, Wich JW, McNutt Scent-Marking Strategies of a Solitary Carnivore: Boundary and Road Scent Marking in the Leopard. Anim Behav 161 (March): 115–126. https://doi.org/10.1016/j.anbehav.2019.12.016 Rajagopal T, Archunan G, Geraldine P (2018) and Chellam Balasundaram. Assessment of Dominance Hierarchy through Urine Scent Marking and Its Chemical Constituents in Male Blackbuck Antelope Cervicapra, a Critically Endangered Species Assessment of Dominance Hierarchy through Urine Scent Marking and Its Chemical Constituents. Behavioural Processes 85 (1): 58–67. https://doi.org/10.1016/j.beproc.2010.06.007 Ranganathan Y, Borges RM (2010) Reducing the Babel in Plant Volatile Communication: Using the Forest to See the Trees. Plant Biol 12(5):735–742. https://doi.org/10.1111/j.1438-8677.2009.00278.x Ranganathan Y, and Renee M. Borges (2011) To Transform or Not to Transform. Plant Signal Behav 6(1):113–116. https://doi.org/10.4161/psb.6.1.14191 Raymer J, Wiesler D, Novotny M, Asa C, Seal US, Mech LD (1984) Volatile Constituents of Wolf (Canis Lupus) Urine as Related to Gender and Season. Experientia 40(7):707–709. https://doi.org/10.1007/BF01949734 Rendon NM, Helena A, Soini, Melissa-Ann L, Scotti MV, Novotny, Demas GE (2016) Urinary Volatile Compounds Differ across Reproductive Phenotypes and Following Aggression in Male Siberian Hamsters. Physiol Behav 164(October):58–67. https://doi.org/10.1016/j.physbeh.2016.05.034 Roach DA (2014) and James R. Carey. Population Biology of Aging in the Wild. Annual Review of Ecology, Evolution, and Systematics 45 (Volume 45, 2014): 421–43. https://doi.org/10.1146/annurev-ecolsys-120213-091730 Robertson BC, Gemmell NJ (2006) PCR-Based Sexing in Conservation Biology: Wrong Answers from an Accurate Methodology? Conserv Genet 7(2):267–271. https://doi.org/10.1007/s10592-005-9105-6 Rodríguez-Hernández P, Cardador MJ, Arce L, Rodríguez-Estévez V (2022) Analytical Tools for Disease Diagnosis in Animals via Fecal Volatilome. Crit Rev Anal Chem 52(5):917–932. https://doi.org/10.1080/10408347.2020.1843130 Roelke-Parker ME, Munson L, Packer C et al (2010) A Canine Distemper Virus Epidemic in Serengeti Lions (Panthera Leo) (Vol 379, Pg 441, 1996). Nature 464 (7290): 942. https://doi.org/Doi%252010.1038/Nature08888 Holly Root-Gutteridge, de Kock N, Young M, Gill AC, Penny JA, Pike TW, Daniel S, Mills (2025) Common Scents? A Review of Potentially Shared Chemical Signals in the Order Carnivora. Chem Senses 50(January):bjaf019. https://doi.org/10.1093/chemse/bjaf019 Sha T, Fei W, Zhao Y, and Lin Bai (2024) Volatile Organic Compounds in Urine Reveals Distinct Diagnostic Signatures for Gastric Cancer. Preprint. 26. https://doi.org/10.21203/rs.3.rs-4609159/v1 Shumake SA (1977) The Search for Applications of Chemical Signals in Wildlife Management. In Chemical Signals in Vertebrates, edited by Dietland Müller-Schwarze and Maxwell M. Mozell. Springer US. https://doi.org/10.1007/978-1-4684-2364-8_20 Shutt K, Setchell JM, and Michael Heistermann (2012) Non-Invasive Monitoring of Physiological Stress in the Western Lowland Gorilla (Gorilla Gorilla Gorilla): Validation of a Fecal Glucocorticoid Assay and Methods for Practical Application in the Field. Gen Comp Endocrinol 179(2):167–177. https://doi.org/10.1016/j.ygcen.2012.08.008 Smith JL, David CM (1989) and Dale Miquellet. Scent Marking in Free-Ranging Tigers, Panthera Tigris. 1–10 Soini HA, Susan U, Linville D, Wiesler AL, Posto DR, Williams, and Milos V. Novotny (2012) Investigation of Scents on Cheeks and Foreheads of Large Felines in Connection to the Facial Marking Behavior. J Chem Ecol 38(2):145–156. https://doi.org/10.1007/s10886-012-0075-0 Soso SB, Koziel JA (2016) Analysis of Odorants in Marking Fluid of Siberian Tiger (Panthera Tigris Altaica) Using Simultaneous Sensory and Chemical Analysis with Headspace Solid-Phase Microextraction and Multidimensional Gas Chromatography-Mass Spectrometry-Olfactometry. Molecules 21(7):1–22. https://doi.org/10.3390/molecules21070834 Soso SB, Jacek A, Koziel A, Johnson YJ, Lee, Sue Fairbanks W (2014) Analytical Methods for Chemical and Sensory Characterization of Scent-Markings in Large Wild Mammals: A Review. Sensors 14(3):4428–4465. https://doi.org/10.3390/s140304428 Stahl RS, Ellis CK, Nol P, Waters WR, Palmer M, VerCauteren KC (2015) Fecal Volatile Organic Compound Profiles from White-Tailed Deer (Odocoileus virginianus) as Indicators of Mycobacterium bovis Exposure or Mycobacterium bovis Bacille Calmette-Guerin (BCG) Vaccination PLoS ONE 10(6): e0129740. https://doi.org/10.1371/journal.pone.0129740 Stockley P, Bottell L, Hurst JL (2013) Wake up and Smell the Conflict: Odour Signals in Female Competition. Philosophical Trans Royal Soc B: Biol Sci 368(1631). https://doi.org/10.1098/rstb.2013.0082 Sunquist ME (1981) The Social Organization of Tigers (Panthera Tigris) in Royal Chitawan National Park. Nepal. mcdougal Tellez MR, Kevin K, Schrader, and Mozaina Kobaisy (2001) Volatile Components of the Cyanobacterium Oscillatoria Perornata (Skuja). J Agric Food Chem 49(12):5989–5992. https://doi.org/10.1021/jf010722p Terwissen CV, Mastromonaco GF, Murray DL (2014) Enzyme Immunoassays as a Method for Quantifying Hair Reproductive Hormones in Two Felid Species. Conserv Physiol 2(1):cou044. https://doi.org/10.1093/conphys/cou044 Thompson CL, Kimberly N, Bottenberg AW, Lantz, Maria AB, de Oliveira LCO, Melo, and Christopher J. Vinyard (2020) What Smells? Developing in-Field Methods to Characterize the Chemical Composition of Wild Mammalian Scent Cues. Ecol Evol 10(11):4691–4701. https://doi.org/10.1002/ece3.6224 Tisdell C, Nantha HS, and Clevo Wilson (2007) Endangerment and Likeability of Wildlife Species: How Important Are They for Payments Proposed for Conservation? Ecol Econ 60(3):627–633. https://doi.org/10.1016/j.ecolecon.2006.01.007 Tossens S, Drouilly M, Lhoest S, Vermeulen Cédric, and Jean-Louis Doucet (2025) Wild Felids in Trophic Cascades: A Global Review. Mammal Rev 55(1):e12358. https://doi.org/10.1111/mam.12358 Turcu M-C, Paștiu AI, Bel LV, Dana LP (2023) A Comparison of Feathers and Oral Swab Samples as DNA Sources for Molecular Sexing in Companion Birds. Animals 13(3):525. https://doi.org/10.3390/ani13030525 Tuttle RH, George B (1968) Schaller Am Anthropol 70 (3): 649–650. https://doi.org/10.1525/aa.1968.70.3.02a01090 Vet, Louise EM (1999) From Chemical to Population Ecology: Infochemical Use in an Evolutionary Context. J Chem Ecol 25(1):31–49. https://doi.org/10.1023/A:1020833015559 Walker BJJ, Mike Letnic MP, Bucknall L, Watson, Neil RJ (2024) Male Dingo Urinary Scents Code for Age Class and Wild Dingoes Respond to This Information. Chem Senses 49(January):bjae004. https://doi.org/10.1093/chemse/bjae004 Waskom M (2021) J Open Source Softw 6(60):3021. https://doi.org/10.21105/joss.03021 . Seaborn: Statistical Data Visualization. Whitehead AL, Edge K-A, Smart AF, Hill GS, and Murray J. Willans (2008) Large Scale Predator Control Improves the Productivity of a Rare New Zealand Riverine Duck. Biol Conserv 141(11):2784–2794. https://doi.org/10.1016/j.biocon.2008.08.013 Worsley SF, Charli S, Davies CZ, Lee et al (2024) Longitudinal Gut Microbiome Dynamics in Relation to Age and Senescence in a Wild Animal Population. Mol Ecol 33(16):e17477. https://doi.org/10.1111/mec.17477 Yamaguchi MS, Holly H, Ganz AW, Cho et al (2019) Bacteria Isolated from Bengal Cat (Felis Catus × Prionailurus Bengalensis) Anal Sac Secretions Produce Volatile Compounds Potentially Associated with Animal Signaling. PLoS ONE 14(9):e0216846. https://doi.org/10.1371/journal.pone.0216846 Zala SM, Potts WK, and Dustin J. Penn (2004) Scent-Marking Displays Provide Honest Signals of Health and Infection. Behav Ecol 15(2):338–344. https://doi.org/10.1093/beheco/arh022 Zhang JX, Soini HA, Bruce KE et al (2005) Putative Chemosignals of the Ferret (Mustela Furo) Associated with Individual and Gender Recognition. Chem Senses 30(9):727–737. https://doi.org/10.1093/chemse/bji065 Additional Declarations No competing interests reported. Supplementary Files SupplementaryTablesRevisedBVAditiJCE.docx Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 15 Mar, 2026 Reviews received at journal 15 Mar, 2026 Reviews received at journal 12 Mar, 2026 Reviewers agreed at journal 02 Mar, 2026 Reviewers agreed at journal 27 Feb, 2026 Reviewers invited by journal 25 Feb, 2026 Editor assigned by journal 24 Feb, 2026 Submission checks completed at journal 23 Feb, 2026 First submitted to journal 16 Feb, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8895773","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":595606229,"identity":"6c363aff-d8a3-4fd2-bf73-916297324b6d","order_by":0,"name":"BV ADITI","email":"data:image/png;base64,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","orcid":"","institution":"National Centre for Biological Sciences","correspondingAuthor":true,"prefix":"","firstName":"BV","middleName":"","lastName":"ADITI","suffix":""},{"id":595606230,"identity":"be208b86-efd2-4403-8e28-2d7893706990","order_by":1,"name":"CHENA DESAI","email":"","orcid":"","institution":"Ahmedabad University","correspondingAuthor":false,"prefix":"","firstName":"CHENA","middleName":"","lastName":"DESAI","suffix":""},{"id":595606231,"identity":"25c2a44f-32f6-4f58-b517-14a51d58b692","order_by":2,"name":"DARSHAN SREENIVAS","email":"","orcid":"","institution":"National Centre for Biological Sciences","correspondingAuthor":false,"prefix":"","firstName":"DARSHAN","middleName":"","lastName":"SREENIVAS","suffix":""},{"id":595606232,"identity":"419207ca-8719-4d15-910d-f74d2d658a14","order_by":3,"name":"UMA RAMAKRISHNAN","email":"","orcid":"","institution":"National Centre for Biological Sciences","correspondingAuthor":false,"prefix":"","firstName":"UMA","middleName":"","lastName":"RAMAKRISHNAN","suffix":""},{"id":595606233,"identity":"d2811744-bf0f-4ec4-9474-27ffa67a1b7e","order_by":4,"name":"SHANNON OLSSON","email":"","orcid":"","institution":"National Centre for Biological Sciences","correspondingAuthor":false,"prefix":"","firstName":"SHANNON","middleName":"","lastName":"OLSSON","suffix":""}],"badges":[],"createdAt":"2026-02-16 19:38:25","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8895773/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8895773/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":103505991,"identity":"8d99694a-fede-4c65-b03c-ad16c1d85280","added_by":"auto","created_at":"2026-02-26 13:33:45","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1143904,"visible":true,"origin":"","legend":"\u003cp\u003ea) A tiger spraying urine to mark its territory b) Collection of urine samples in situ\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8895773/v1/5eefb348b35c96537d0033b1.png"},{"id":103335581,"identity":"74dea707-421a-42e9-a103-e61835bb6e97","added_by":"auto","created_at":"2026-02-24 14:28:53","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":332127,"visible":true,"origin":"","legend":"\u003cp\u003eSolid Phase Extraction of head phase volatiles using PDMS (outline of vial is generated using Sora AI)\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-8895773/v1/713ae02a7709b45483a1394e.png"},{"id":103506308,"identity":"32c50b4c-70a6-4153-8e9a-3653021db0e4","added_by":"auto","created_at":"2026-02-26 13:35:07","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":457330,"visible":true,"origin":"","legend":"\u003cp\u003eRepresentative total ion chromatograms for each type of sample and environmental controls with prominent peaks labelled. Identified volatiles are listed in Supplementary Tables 5 and 6.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-8895773/v1/9e18951c03f6a801deac105f.png"},{"id":103335588,"identity":"664a51b3-6b46-4fe0-abaa-0950eab54e47","added_by":"auto","created_at":"2026-02-24 14:28:54","extension":"jpeg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":115259,"visible":true,"origin":"","legend":"\u003cp\u003ea) b) and c) are Jitter and dot-whisker plots of urine volatiles that differ between leopards and tigers and d) presents the confusion matrix for species classification based on volatiles in a) and b). e), f) and g) are Jitter and dot-whisker plots of scat volatiles that differ between leopards and tigers and h) presents the confusion matrix for species classification based on volatiles in e), f) and g).\u003c/p\u003e","description":"","filename":"floatimage4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8895773/v1/e15c6aa6477bcc20a3f5439c.jpeg"},{"id":104397547,"identity":"3675eefc-cb1b-4c79-bcc2-658d7f7606a8","added_by":"auto","created_at":"2026-03-11 11:51:09","extension":"jpeg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":105190,"visible":true,"origin":"","legend":"\u003cp\u003ea) b) and c) are jitter and dot-whisker plots of leopard urine volatiles that differ with sex and d) presents the confusion matrix for sex classification based on volatiles in a) and b). e), f) and g) are jitter and dot-whisker plots of leopard urine volatiles that differ with age and h) presents the confusion matrix for age classification based on volatiles in e), f) and g).\u003c/p\u003e","description":"","filename":"floatimage5.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8895773/v1/c7939c89a7d9fbda98ff87b8.jpeg"},{"id":103506213,"identity":"e6bbc5f8-eea4-40d4-8dea-1527aac204fe","added_by":"auto","created_at":"2026-02-26 13:34:38","extension":"jpeg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":109215,"visible":true,"origin":"","legend":"\u003cp\u003ea) b) and c) are jitter and dot-whisker plots of leopard scat volatiles that differ with sex and d) presents the confusion matrix for sex classification based on volatiles in a) and b). e), f) and g) are jitter and dot-whisker plots of leopard scat volatiles that differ with age and h) presents the confusion matrix for age classification based on volatiles in e), f) and g).\u003c/p\u003e","description":"","filename":"floatimage6.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8895773/v1/cb8728d68a430272016a177d.jpeg"},{"id":103335583,"identity":"e3ca540d-a942-4752-b3b0-7fca1e110fce","added_by":"auto","created_at":"2026-02-24 14:28:54","extension":"jpeg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":198850,"visible":true,"origin":"","legend":"\u003cp\u003ea) b) and c) are jitter and dot-whisker plots of tiger urine volatiles that differ with sex and d) presents the confusion matrix for sex classification based on volatiles in a) and b). e), f) and g) are jitter and dot-whisker plots of tiger urine volatiles that differ with age and h) presents the confusion matrix for age classification based on volatiles in e), f) and g).\u003c/p\u003e","description":"","filename":"floatimage7.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8895773/v1/f066d3a9ce845b3967b8af81.jpeg"},{"id":103506679,"identity":"726b7436-c709-4b62-87bb-c7a1dc913a02","added_by":"auto","created_at":"2026-02-26 13:38:49","extension":"jpeg","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":109058,"visible":true,"origin":"","legend":"\u003cp\u003ea) b) and c) are jitter and dot-whisker plots of tiger scat volatiles that differ with sex and d) presents the confusion matrix for sex classification based on volatiles in a). e), f) and g) are jitter and dot-whisker plots of tiger scat volatiles that differ with age and h) presents the confusion matrix for age classification based on volatiles in f).\u003c/p\u003e","description":"","filename":"floatimage8.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8895773/v1/544c18ddeb2d487f2abec808.jpeg"},{"id":103506814,"identity":"5e6e362f-2070-4ecc-b4ee-d1a1932973ea","added_by":"auto","created_at":"2026-02-26 13:39:34","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":471290,"visible":true,"origin":"","legend":"\u003cp\u003eA. Chromatograms of tiger urine volatiles extracted from glass wool. B. Jitter and dot-whisker plots of tiger urine volatiles differing between reproductive and non-reproductive state. C. Jitter and dot-whisker plots of tiger scat volatiles differing between epileptic and non-epileptic tigers. #Sampled right before death of epileptic tiger.\u003c/p\u003e","description":"","filename":"floatimage9.png","url":"https://assets-eu.researchsquare.com/files/rs-8895773/v1/0c3c19a0e6c0366ed8375b38.png"},{"id":104407264,"identity":"9f2b119a-81dd-4553-8815-ccf75a1d31a8","added_by":"auto","created_at":"2026-03-11 12:36:19","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3844646,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8895773/v1/ba38ff98-c2d6-4ef5-b4b4-8ac41230702d.pdf"},{"id":103506093,"identity":"1c858cb9-7c9d-428d-8691-23aec39eb787","added_by":"auto","created_at":"2026-02-26 13:34:04","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":43288,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTablesRevisedBVAditiJCE.docx","url":"https://assets-eu.researchsquare.com/files/rs-8895773/v1/78b29958a4ec3fc9be7df69f.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eNon-invasive Sampling of Odours From Two Big Cats for Wildlife Conservation\u003c/p\u003e","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eOlfactory cues are an important means of communication in mammalian societies (Beauchamp et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e1976\u003c/span\u003e; Brennan and Kendrick 2006). Such cues are typically contained in a mixture of chemicals many with relatively high volatility, transported through excretions and secretions (Ache and Young \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Burger \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). Volatile organic compounds (VOCs) are known to be crucial in signalling for mate choice, territory marking, reproduction, species, and individual identity among a large number of species​ (Brennan and Kendrick 2006; Amo and Ruiz Rodr\u0026iacute;guez 2023). While VOCs are not always emitted for intentional signalling, conspecifics can often extract information about fitness and reproductive state, and heterospecifics can infer prey and predator presence ​(Beauchamp et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e1976\u003c/span\u003e; Fromhage and Henshaw 2022). Such VOCs are considered to be cues rather than signals, and could be honest indicators of physiological status (Candolin \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2003\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eWith the recognition of emerging infectious diseases and inbreeding depression as a threat to the viability of wild populations, it has become increasingly important to identify and track health status in situ (Shumake \u003cspan citationid=\"CR97\" class=\"CitationRef\"\u003e1977\u003c/span\u003e; Daszak \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2000\u003c/span\u003e; Artois et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). Determining the age structure and sex ratio of wild populations is also pivotal to management (Roach and Carey 2014; Kappeler et al. \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). VOCs could potentially inform health and reproductive status (Zala et al. 2004; Kean et al. \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Manzoli et al. \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Additionally, identifying sex pheromones could help plan ex situ conservation of threatened species (Dehnhard \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Leal \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). VOCs that indicate age, sex, individuality, health and reproduction have been identified in several species (see Raymer et al. \u003cspan citationid=\"CR89\" class=\"CitationRef\"\u003e1984\u003c/span\u003e for wolf; Hagey and Macdonald 2003 for Giant panda; Grosbois et al. \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2007\u003c/span\u003e for Antarctic prions; Kean et al. \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2011\u003c/span\u003e for otters; Buljubasic and Buchbauer 2015 for human diseases; Noonan et al. \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2019\u003c/span\u003e for European badgers; Uetake et al. 2017 for domestic cats; Jones et al. \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2021\u003c/span\u003e for maned wolf; Walker et al. \u003cspan citationid=\"CR117\" class=\"CitationRef\"\u003e2024\u003c/span\u003e for dingoes). Sampling of informative VOCs could provide crucial insights into the physiological or health status of wild endangered species, complementing demographic and habitat-based assessments. (Meinwald and Eisner \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Soso et al. \u003cspan citationid=\"CR102\" class=\"CitationRef\"\u003e2014\u003c/span\u003e)​. Unlike serological sampling, sampling odours from breath, urine, faeces, and body requires minimal intrusion into organisms\u0026rsquo; bodies making these techniques of immense value to diagnostics (Cumeras et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Rodr\u0026iacute;guez-Hern\u0026aacute;ndez et al. \u003cspan citationid=\"CR93\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Unfortunately, in situ chemical sampling techniques have not been exploited much for conservation research due to technical difficulties of sample collection, handling, and storage. VOCs have been mostly used in wildlife management to bait individuals either for camera trapping or to physically capture \u0026lsquo;problem\u0026rsquo; individuals (Lindgren et al., \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e1995\u003c/span\u003e.; Whitehead et al. \u003cspan citationid=\"CR119\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Joubert et al. \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Lu et al. \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The use of VOCs has also been explored as a solution to invasive species affecting native flora and fauna (Favaro et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). There have been very few studies on VOC fingerprint molecules for monitoring wild animal populations such as in early diagnosis of wildlife diseases (Pavlou and Turner \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e2000\u003c/span\u003e; Bayn et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Cumeras et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Stahl et al., \u003cspan citationid=\"CR103\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) and for species identification (Burnham et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2008\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eBeing apex predators, large felids play a crucial role in maintaining ecosystems (Tossens et al. \u003cspan citationid=\"CR113\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Felid populations face several threats and they are currently amongst the most endangered mammals on earth, with several populations facing high extinction risks from inbreeding depression and diseases (eg. cheetah Castro-Prieto et al. 2010; lion Roelke-Parker et al. \u003cspan citationid=\"CR94\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; tiger Gilbert et al. \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Monitoring felid population dynamics and health should be an important part of conservation efforts, but is hampered by the elusive nature of these species (Munson et al. 2010). Current monitoring techniques include non-invasive techniques such as camera trapping and genetic sampling (Karanth \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e1995\u003c/span\u003e; Mondol et al. 2009; Jhala et al. 2015) that can gather information about population size, sex ratio, connectivity, and behaviour patterns, but have limited applicability in sampling age, health, and reproductive parameters (Harmsen et al. \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Anile and Devillard 2018; Joubert et al. \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eTigers and leopards are threatened big cats and are an important focus for conservation and management in their range countries (Tisdell et al. 2007; Goodrich et al. \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Ghoddousi and Khorozyan 2023). Being a solitary species, their social systems are maintained by indirect cues, particularly olfaction (Smith et al. 1989; Allen et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Olfactory cues are deposited through faeces (scats), urine, clawing, cheek rubbing, and body rolling​ (Schaller 1968; Sunquist \u003cspan citationid=\"CR108\" class=\"CitationRef\"\u003e1981\u003c/span\u003e; du P. Bothma and le Richet 1995; Soini et al. \u003cspan citationid=\"CR100\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). The urine of tigers sprayed into the environment with the tail held perpendicular to the body is one of the most well-observed behaviours of tigers ( Schaller 1967; Smith et al. 1989). The smell is known to persist for days (Schaller 1967) and is said to be similar to the odour of Basmati rice or popcorn (Brahmachary and Sarkar 1990)​. Behavioural studies with radio-collared and captive tigers indicate increased marking behaviour in the presence of individuals of the same sex and during periods of reproductive activity​ (Brahmachary et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e1992\u003c/span\u003e; Soini et al. \u003cspan citationid=\"CR100\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Females mark more frequently when in estrus, and males are known to mark in response to a female in estrus (Smith et al. 1989). In the wild, both leopards and tigers mark at the borders of their territory more frequently than in the interiors both leopards and tigers (Smith et al. 1989; Rafiq et al. 2020)\u003c/p\u003e \u003cp\u003eStudies on the VOC composition of captive tigers and leopards found a high concentration of fatty acids, an unidentified fraction that appears in adulthood, and several ketones, lactones, alcohols, esters, and carboxylic acids in the headspace​ (Brahmachary et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e1992\u003c/span\u003e; Poddar-Sarkar \u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e1996\u003c/span\u003e; Andersen \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e1998\u003c/span\u003e; Poddar-Sarkar and Brahmachary 2004; Burger et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Apps et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Soso and Koziel \u003cspan citationid=\"CR101\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). There are no studies on odour compounds in scats of tigers, but several studies on domestic cats and canids that identify odour cues for age and sex​ (Apps et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Uetake et al.,2017.; Miyazaki et al. \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Yamaguchi et al. \u003cspan citationid=\"CR121\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Based on the behavioural and odour information known from tigers, we hypothesize that VOC profiles can indicate age, reproductive and health status in scat and urine. We investigate these questions through samples of urine and scat from captive as well as wild tigers, and from identified individuals of known age, sex, and health status. In this study, we address the following questions: i) Can tiger and leopard volatile compounds be sampled non-invasively for chemical analysis and identification? ii) Do the scats and urine of tigers and leopards contain odour profiles that differ with respect to a) age, b) sex, c) reproductive status, and d) health? iii) Can VOCs be used as a diagnostic tool for the age, sex, health, and reproductive status of tigers and leopards? By answering these questions, we lay the foundation for a practical volatile sampling method which enables the collection of biologically relevant information of two big cats.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cp\u003eOdourant sample collection and sampling strategy. Scat and urine samples of tigers and leopards of known identity in captivity were sampled non-invasively in Bannerghatta Biological Park in Bengaluru, Karnataka for 18 weeks from June 2021 to November 2021 as well as in Kamala Nehru Zoological Park, Ahmedabad, and Sayajibaug zoo, Vadodara, in Gujarat, for 16 weeks from February 2022 to April 2022. The zoo biologists shared details about the age, sex, and health conditions of the individuals sampled. None of the captive tigers were reproductively active. Individual wild tigers were observed and sampled in Ranthambore Tiger Reserve in the Northwestern state of Rajasthan for a total of seven months from February 2022 to June 2022 and May 2023 to June 2023. The Reserve's semi-arid climate and high density of tigers make it an ideal location for spotting tigers. Extensive monitoring and isolation of this population allow researchers to identify and track tigers of known identity, age, sex, reproductive stage, and health conditions. Information about the territory of individual tigers was used to scour the area and spot individuals based on indirect signs such as pugmarks and the behaviour of prey animals. When spotting the individuals, information about their age, sex, appearance, and marking spots was noted. Appearance suggestive of reproductive status was noted: such as a swollen belly due to pregnancy and prominent mammary glands or being accompanied by cubs younger than six-month-old, indicating lactation. Once the individuals left the area, the fecal or urine samples were collected for odour analysis.\u003c/p\u003e \u003cp\u003eUrine and scat samples of captive individuals were collected from the floor of cages in the morning by zookeepers under our supervision and did not require physical contact with the captive animals. We aimed to collect at least five replicates of urine and scat from each individual and maintained a difference of at least two weeks between replicates from the same individual. Wild samples were collected after the individual left the area, which was mostly within minutes of marking but sometimes up to an hour after marking. In a single marking event, an individual might mark several times in different areas, and these samples were considered technical replicates. Samples from the same individual collected on different days in separate marking events were considered biological replicates.\u003c/p\u003e \u003cp\u003eUrine samples were collected for odour analysis by swabbing spray areas with sterile cotton, while wearing sterile gloves, and storing the cotton in sterilized (treated with ethanol and baked at 270 degrees Celsius) 30 ml Borosil glass vials (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Boluses of scat were similarly collected. The vials were sealed with aluminium foil and parafilm, maintained at 4 degrees Celsius during transport to lab (basecamp in field) where the solid space volatile extraction was carried out and then transferred to -20 degrees Celsius for long-term storage.\u003c/p\u003e \u003cp\u003eSince noninvasively collected samples would include volatiles from the environment, environmental controls were also collected, along with the samples. Various substrates in the zoo and the wild were sampled at a distance of about 3 metres or more from the marking to avoid volatiles from scats or urine. Pebbles, soil, grass, leaf litter and different tree barks were collected, and odours were extracted as with samples. Odours from sterile cotton were also collected.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003ePermissions for zoo sampling were obtained from Gujarat State Forest Department, Karnataka State Forest Department and Central Zoo Authority of India and for wild sampling from Chief Wildlife Warden, Rajasthan Forest Department. Details of sampling letters can be found in Supplementary Table\u0026nbsp;1. The sampling protocol was approved by the Institutional Biosafety Committee of NCBS-TIFR.\u003c/p\u003e \u003cp\u003eSolid Phase volatile extraction. Solid-phase extraction (SPE) was carried out as in Nair et al. \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e2018\u003c/span\u003e, and Nordstr\u0026ouml;m et al. \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e2017\u003c/span\u003e, using polydimethylsiloxane (PDMS) tubes procured from Carl Roth (Rotilabo\u0026reg;\u0026ndash;silicone tube) of 1.5 mm inner diameter and 3.5 mm outer diameter. PDMS tubes were preconditioned for four hours by soaking approximately 5 mm pieces in a 1:1 mixture of acetonitrile and methanol. They were then dried using ultra-high-purity nitrogen gas and conditioned in a Gerstel Tube Conditioner by heating at 210\u0026deg;C over the stream of nitrogen gas at 5 L/min (4 bar constant pressure) for 3 hours (Kallenbach et al. \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Nordstr\u0026ouml;m et al. \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Nair et al. \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). The entire process was repeated twice, following which the tubes were stored in -20 degrees Celsius in amber vials till use. Headspace sampling was conducted by exposing four PDMS tubes suspended on a copper wire over the top of glass vials containing urine or scat samples for 4 hours (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) (Nair et al. \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). The vials were sealed with aluminium foil and parafilm during sampling to prevent odours from escaping or other contaminants from entering the vial. The headspace sampling was conducted within a few hours of sample collection. After sampling, the tubes were stored in sterile 2 ml amber glass vials at -20 degrees Celsius.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThermal desorption- Gas Chromatography-Mass spectrometry. The volatiles were isolated and identified using a Thermal Desorption Unit-Gas Chromatography-Mass Spectrometer setup. Samples collected on PDMS tubes were introduced via a Gerstel MultiPurpose Sampler (MPS), which desorbs the volatiles from the PDMS tubes, cryofocusses them, and directly introduces them to GC-MS. Gerstel Thermal Desorption Unit (TDU) in conjunction with Cooled Injection System (CIS 4) was used, which was controlled by the Gerstel Modular Analytical Systems Controller C506 and the Gerstel Maestro 1 software. Analysis was performed on an Agilent 7890B gas chromatograph coupled with a 5977A MSD mass spectrometer with HP-5 MS column (30 m \u0026times; 0.25 mm id, 0.25 \u0026micro;m film thickness) and helium as the carrier gas at a 1 ml/min flow rate. The column oven was kept at 40\u0026deg;C for 1 min, increased to 180\u0026deg;C at a rate of 5\u0026deg;C/min, and finally increased to 270\u0026deg;C (with a 30 min holding temperature) in the second ramp at 25\u0026deg;C/min. The transfer line between the GC and MS was maintained at 250\u0026deg;C, whereas the source and quadrupole temperatures were 230 and 150\u0026deg;C, respectively. Ionization was performed in electron impact mode with an ionization energy of 70 eV. Detailed parameters can be found in Nair et al.,2018.\u003c/p\u003e \u003cp\u003eGC-MS data integration, peak extraction, clean up and compound identification. GC-MS acquisition was performed using Agilent MassHunter Workstation software B.07.02.1938, and qualitative analysis was carried out by MassHunter Qualitative Analysis Version B.07.00. Peak integration for urine and scat samples was carried out using Chemstation with a peak width of 0.1 minute, Area and height rejection of 10000 units, relative height 1%, and relative area 0.5%. This data was extracted into .csv files, which were run through a custom Python script to identify unique peaks by combining Retention Time (RT) and Base Peak (BP) values. The script also removed RT- BP combinations present in environmental control files and contaminating peaks such as from substrate and handling (adapted from Nair et al., \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Area of peaks with the same BP +/- 0.3 RT were summed up and since these tend to be from compounds with peak widths higher than 0.1 minute. An internal standard present in PDMS is the peak octamethylcyclotetrasiloxane was used to normalize all peak areas (Kallenbach et al., \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2014\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eFinally, only volatiles detected in 15% (10% for the analysis of disease) of the samples were retained for downstream analysis ensuring that retained compounds were consistently observed across samples and further removed any environmental volatiles from uncommon substrates. Potential analytes of interest were identified using a combination of three methods, similar to (Nordstr\u0026ouml;m et al. \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e2017\u003c/span\u003e and (Nair et al. \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e2018\u003c/span\u003e): A) Comparing mass spectral data of the unknown peaks with library spectra [National Institute of Standards and Technology (NIST)], B) Comparing peak Kovat\u0026rsquo;s retention index (using C8\u0026ndash; C40 alkanes standard, Sigma Aldrich, Bangalore, India), and C) Comparing to authentic standards (that were commercially available) run with the same GC column and oven parameters as samples.\u003c/p\u003e \u003cp\u003eRandom forest analysis: A Random Forest (RF) classification framework was used to identify the most informative volatiles since this approach has been found to be effective in low signal-to-noise ratio data (Nair et al. \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Ranganathan and Borges \u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). The Python library Scikit-learn (Pedregosa et al. 2011) was used to carry out Random Forest for the classification of urine and scat volatiles into the following categories:\u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eSpecies: tiger and leopard\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eSex: male and female and\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eAge: old (more than 10 years of age) and young (less than 10 years of age)\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eReproductive state: Non-reproductive and reproductive (lactating and pregnant) and\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eHealth status: healthy and unhealthy.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003cp\u003eThe random forest approach used here is based on (Ranganathan and Borges \u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; 2011) which accommodates smaller sample size. 100 independent RF classifier runs with 100 trees and a unique random seed were trained on the full dataset for each analysis. For the wild urine samples, only one sample per marking event was used per run, and we cycled through multiple technical replicates to ensure exclusion of pseudoreplicates in the same run. Gini importance was recorded per run and five top features with highest average over all runs were identified. The differences in the top-ranked volatiles between the different categories examined were visualized with jitter and dot-whisker plots (where the dot is the mean and whiskers are 95 percent confidence intervals) using the Seaborn library (Waskom \u003cspan citationid=\"CR118\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Subsequently, we evaluated classification performance using the top three to five overall features by carrying out 5-fold CV accuracy for individual volatiles as well as volatile combinations across 10 independent runs with 100 trees each and visualized the classification accuracy using confusion matrix.\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cp\u003eNon-invasive sampling of volatiles from big cat excretions. Scat and urine samples were collected from nine captive tiger individuals and sixteen captive leopards. Although we attempted to sample 5 replicates for each individual, sample availability at the time of collection varied and we were able to sample 1 to 5 replicates per individual (on an average three replicates per individual). We also collected 14 environmental controls. The number of replicates per individual and other relevant details is listed in Supplementary Table\u0026nbsp;2. During sample collection in Bannerghatta Biological Park, one of the individuals was being treated for epileptic seizures and died under treatment. This remains the only known health-compromised individual we were able to sample.\u003c/p\u003e \u003cp\u003eFrom the wild, we collected 144 urine samples from 28 individually identified tigers of different age and reproductive status and 27 environmental controls from different substrates (Supplementary Table\u0026nbsp;3). Notably, 21 of these samples were from four pregnant or lactating females. Forty-five of the urine samples collected from wild were excluded during the filtering following GC-MS analyses, because they had 10 or fewer volatiles detected. The remaining 107 samples included technical replicates and the final sample sizes for age and sex classification are provided in Supplementary Table\u0026nbsp;4. We were not able to sample any scats from identified tiger individuals in the wild but unidentified scats were sampled and found to have similar volatile profiles as the zoo samples. Likewise, we were not able to acquire any samples from identified leopards in the wild. Representative chromatograms for samples collected in this study are in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAlthough our focus was on identifying diagnostic volatiles and not creating an exhaustive list of all tiger and leopard compounds, we carried out compound identification of the major peaks and further identified compounds that were deemed significant by the random forest analysis. Supplementary Tables\u0026nbsp;5 and 6 summarize the volatiles and the criteria for identification for each volatile.\u003c/p\u003e \u003cp\u003eVolatiles differences between tigers and leopards. Based on Gini values over 100 random forest runs, three urine volatiles and three scat volatiles emerged as consistent predictors for distinguishing species (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Among urine volatiles, γ-dodecalactone, 2-decanone and N-isopentylidene isopentylamine were found to be elevated in tiger samples. In scat, δ-valerolactam was higher in tigers whereas p-cresol and 2-ethylhexanol were higher in leopard scats (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). The highest classification accuracy for urine volatiles was achieved using a combination of γ-dodecalactone and 2-dodecanone (0.79\u0026thinsp;+\u0026thinsp;0.009; 5-fold CV). For scat volatiles, the best classification accuracy was achieved when using a combination of all three volatiles in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e (0.75\u0026thinsp;+\u0026thinsp;0.029; 5-fold CV). Misclassification error rate was higher for tigers in the urine-based classification and higher for leopards in the scat-based classification.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eScat and urine volatiles differences between age and sex in leopards.Age and sex differences in leopards could be consistently determined from six urine volatiles (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). 2,4-Di-Tert-Butyl Phenol (2,4-DTBP), N-isopentylidene isopentylamine and Indole were higher in urine of young leopards. 2,4-DTBP was also associated with sex differences-it was higher in female leopards while phenol and indole were higher in urine of male leopards (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). The highest classification accuracy for age was obtained with a combination of 2,4-DTBP and N-isopentylidene isopentylamine (0.65\u0026thinsp;+\u0026thinsp;0.029; 5-fold CV) but the misclassification error rate was high for old leopards. Highest classification accuracy for sex was achieved with 2,4-DTBP alone but misclassification error rate was high for Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e (0.55\u0026thinsp;+\u0026thinsp;0.03; 5-fold CV).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eSix scat volatiles (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e) that are top predictors in identifying age and sex were identified (Supplementary Table\u0026nbsp;2). Isovaleric acid, δ-valerolactam and γ-dodecalactone were elevated in young leopards. Methoxy acetic acid, phenylethyl alcohol and 2-dodecanone were higher in male leopards (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). The classification accuracy for age was highest with a combination of δ-valerolactam and γ-dodecalactone (0.65\u0026thinsp;+\u0026thinsp;0.029; 5-fold CV). The classification accuracy for sex was highest for a combination of methoxyacetic acid and phenylethyl alcohol (0.61\u0026thinsp;+\u0026thinsp;0.06; 5-fold CV).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eScat and urine volatiles differences between age and sex in tigers. Four tiger urine volatiles consistently differed with age and sex (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e). 2,4-DTBP and an adamantane-like compound was higher in females while γ-dodecalactone was higher in male tiger urine samples. 2,4-DTBP, Phenylethyl alcohol and γ-dodecalactone were higher in old tigers. The highest classification accuracy for sex was achieved with a combination of 2,4-DTBP and the adamantane-like compound (0.64\u0026thinsp;+\u0026thinsp;0.01; 5-fold CV) whereas 2,4-DTBP alone (0.55\u0026thinsp;+\u0026thinsp;0;5-fold CV) gave the highest classification accuracy for age. However, the misclassification error rate for old (40%) and male (50%) tigers was higher.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eWe found four tiger scat volatiles consistently differing with age and sex (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e). Methoxyacetic acid, isovaleric acid and δ-valerolactam were higher in male tiger scat samples whereas isovaleric acid, γ-dodecalactone and dimethyl trisulfide were higher in old tigers. The highest classification accuracy for sex was achieved with methoxyacetic acid alone (0.71\u0026thinsp;+\u0026thinsp;0.057;5-fold CV) whereas the highest classification accuracy for age was achieved with γ-dodecalactone alone (0.63\u0026thinsp;+\u0026thinsp;0.048;5-fold CV). However, again, the misclassification error rate for old tigers was high at 53%.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003ePutative chemical cues for reproductive and health state in tigers. During pilot experiments where we used glasswool to collect urine samples, a sample of a lactating female tiger showed peaks at retention time 18 to 23 minutes that were absent from a non-lactating sample (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003eA). The identity of this peak could not be accurately elucidated but appeared to be a pentose-like compound. The volatiles from samples of lactating, pregnant and non-reproductive females collected using PDMS were analysed using random forest. The top predictor was found to be nonanol, which was much higher in lactating and pregnant females than non-reproductive females (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003eB). We could not sample scats for varying reproductive states. We sampled both scat and urine for one captive tiger that was being treated for epilepsy and died during the course of treatment. We found elevated levels of dimethyl tetrasulphide in scats of the epileptic tiger but could not detect any distinctive volatiles in the urine (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003eC). Due to the limited sample size for these attributes, we did not attempt to assess the classification accuracy for the tested groups.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eChemical secretions may harbour info chemicals that could offer non-invasive tools for wildlife monitoring and diagnostics (Cumeras et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Burnham et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Jones et al. \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). As conservation increasingly moves towards precision monitoring of diseases, reproduction, and fitness effects at the individual level, chemical ecology could provide powerful insight into non-invasive wildlife diagnostics by enabling collection and analysis of informative volatiles (Vet 1999; Meinwald and Eisner \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Soso et al. \u003cspan citationid=\"CR102\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). However, such studies have been limited; primarily due to technical challenges in sampling wild and often elusive nature of species. These technical challenges include obtaining and storing the sample, extracting volatiles, and identifying the compound. Recent advancements have addressed these challenges, with innovative sampling methods explicitly developed for wildlife research (K\u0026uuml;cklich et al. \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Nair et al. \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Thompson et al. \u003cspan citationid=\"CR111\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). In this study, we utilized one such method to investigate volatile organic compounds (VOCs) in two charismatic carnivore species known for their scent-marking behaviour- a topic of interest to both scientists and laypersons (Brahmachary et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e1992\u003c/span\u003e; Poddar-Sarkar and Brahmachary 2004). We used a sorbent (polydimethylsiloxane; PDMS) to extract volatiles from the headspace of scats and urine and analysed them as per Nair et al., \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e2018\u003c/span\u003e. Given the popularity of these carnivores, prior research had focussed on the chemical characterization and understanding the origin of odours. Our study is the first attempt to sample tiger odours in the wild, wherein we identified volatiles that differ in sex, age and reproductive status in tigers and evaluated their potential as a diagnostic test. It is also the first attempt in sampling leopard odours non-invasively from individuals of known age and sex.\u003c/p\u003e \u003cp\u003eTerritorial marking is one of the most frequently observed behaviours in tigers, prompting us to design a field sampling approach that involved following identified individuals to collect urine and scat samples. Like many field-based studies, this work faced unavoidable constraints. We could not sample scats from identified tigers in the wild (similar to Khan et al. \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Leopards are more nocturnal and elusive; we could not sample identified individuals in the wild. Hence, our identified tiger scat and all leopard samples are solely from captive individuals. We aimed to sample individuals of known age, sex, and health status. However, captive tigers were not reproductively active, and the zoo staff regularly managed their health through vaccinations and medical treatment, limiting our ability to study odours related to reproduction and health conditions. In contrast, wild samples included individuals in different reproductive states. These challenges reflect the difficulty of working with elusive and endangered species rather than flaws in study design. Despite these limitations, this is, to our knowledge, the first study to elucidate identified volatiles for tigers and leopards, offering critical baselines for future work.\u003c/p\u003e \u003cp\u003eWhile sampling urine, we observed that different substrates had different levels of urine retention: trees absorbed the liquid component of urine quickly, leaving only a faint smell, while urine sprayed on rocks and soil generally retained a strong-smelling liquid, which could yield better results. Nevertheless, the odours from urine sometimes lasted for hours and even days at temperatures as high as 48 degrees Celsius. Our final dataset included volatiles sampled irrespective of the substrate on which the urine was sprayed. Scats contain a large proportion of non-host material, such as dietary remains and microbes, and their odour cues could also vary significantly with diet (Depauw et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). We also found halogenated compounds in tiger scats, which might be from the environment (e.g. cleaning chemicals used for cleaning cages). Scats degrade quickly in summer and could get washed away in the rainy season, making this a reliable sampling strategy only in winter. In contrast, urine samples produced clearer signals and could be sampled in winter and summer.\u003c/p\u003e \u003cp\u003eHowever, scat volatiles were more effective in identifying tiger samples and classifying sex. Urine volatiles were more effective in classifying leopards, but there was a high misclassification rate for old and male individuals in both leopards and tigers. One reason for this pattern could be the statistical bias of machine learning algorithms towards learning patterns of the majority class in imbalanced datasets (Khoshgoftaar et al. 2007). The lower sample size for old and male individuals could have led to lower sensitivity in detecting these groups. We did not apply class balancing techniques to avoid introducing artificial variation, especially in light of the small dataset. We report misclassification rates and class distributions transparently, and interpret results in light of sample size limitations. In spite of these limitations, biological explanations cannot be ruled out particularly because the sample size skew is mainly towards sex classification in tiger urine samples. The observed patterns could also result from higher individual variation in old and male individuals due to physiological and microbiome changes (Wilson and Harrison 1983; Worsley et al. \u003cspan citationid=\"CR120\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Old males are thought to be subject to lower selective pressure for sexual and territorial signalling, leading to a loss of a faded or inconsistent chemical signature (Garratt et al. \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). The species level patterns in volatile differences might also offer insights into the biological role of specific VOCs. The higher amounts of specific urine volatiles in tigers compared to leopards may indicate the role of these compounds in dominance-related signalling (such as in blackbucks: Rajagopal et al. \u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). In contrast, variations in scat volatiles can be more plausibly attributed to differences in diet (Farrell et al. \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2000\u003c/span\u003e; Depauw et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2013\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAnother significant challenge in analysing volatile samples collected in situ is the high noise-to-signal ratio, complicating data interpretation. Previous studies have employed supervised clustering techniques to address this issue (Ranganathan and Borges \u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Nair et al. \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Noonan et al. \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). For our analysis, we opted for the Random Forest algorithm, which has previously demonstrated efficacy with PDMS-based volatile data (Nair et al. \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Random forest algorithms have strong classification ability and provide variable importance measures, which are important for biological interpretation (Breiman \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2001\u003c/span\u003e). We modified this approach as per (Ranganathan and Borges \u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e2010\u003c/span\u003e) to optimize its performance for our study and ensure reproducibility. Since our samples contained many environmental volatiles, we extensively sampled different substrates to subtract the environmental volatiles and retain only putative tiger and leopard compounds. The pipeline outlined here for generating input data and analyses can be adapted for other species.\u003c/p\u003e \u003cp\u003eThe musky, sweet, and fruity smells of tiger and leopard urine come from γ-dodecalactone, δ-valerolactam, heptanoic acid, decanoic acid, phenol, and indole. Several of these volatiles have been reported from the urine of other carnivore species, including previous studies on tiger, leopard and lion urine (Brahmachary et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e1992\u003c/span\u003e; Andersen and Vulpius \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e1999\u003c/span\u003e; Poddar-Sarkar and Brahmachary 2004; Burger et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Tomberlin et al. 2017; Soso and Koziel \u003cspan citationid=\"CR101\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; McLean et al. \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2021\u003c/span\u003e, Root-Gutteridge et al. 2025). Long-chain fatty acids such as palmitic acid and oleic acid are thought to prevent the fast release of volatiles, helping the smell compounds stay in the environment long after it is released (Poddar-Sarkar \u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e1996\u003c/span\u003e). We also found sulphur-containing compounds such as dimethyl trisulphide. This study did not detect the compound 2-acetyl-1-pyrroline, which is supposed to be the cause of the popcorn-like smell in tiger urine (Brahmachary and Sarkar 1990).\u003c/p\u003e \u003cp\u003eThis study was the first attempt to characterize volatile compounds in tiger and leopard faeces. We found several volatiles identified previously from the faeces of other carnivores: indole, isovaleric acid, methyl pentanoic acid, and naphthalene (Apps et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Uetake et al, 2017.; Barja et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eWe surveyed literature for occurrences in other species of the volatiles found to be important predictors in tigers. γ-dodecalactone was higher in the urine of tigers and scats of young leopards and differed with age and sex in tiger urine and with age in tiger scats. An isomer of this compound, δ -dodecalactone, was identified in a previous study on tiger urine and found to differ with sex in the urine of the maned wolf (Jones et al. \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). γ-dodecalactone was also identified in Siberian hamster urine and found to increase with aggression (Rendon et al. \u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Isovaleric acid, phenol, δ-valerolactam, ethyl hexanol, phenylethyl alcohol, indole, dimethyl trisulfide, and p-cresol are reported in many carnivores, including lions, tigers, and leopards (Raymer et al. \u003cspan citationid=\"CR89\" class=\"CitationRef\"\u003e1984\u003c/span\u003e; Kean et al. \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Soso and Koziel \u003cspan citationid=\"CR101\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Mitchell et al. \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Jones et al. \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). 2-Decanone is found in many insects and anal gland secretions of ferrets (Crump \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e1980\u003c/span\u003e; Zhang et al. \u003cspan citationid=\"CR123\" class=\"CitationRef\"\u003e2005\u003c/span\u003e), whereas 2-dodecanone is found in many insects and Defassa waterbuck body odour (Gikonyo et al. \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). Dimethyl tetrasulphide is reported in microorganisms (Tellez et al. \u003cspan citationid=\"CR109\" class=\"CitationRef\"\u003e2001\u003c/span\u003e). Nonanol, higher in lactating and pregnant tigers, is a common aliphatic compound in many insects (Duffield, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e1981\u003c/span\u003e)). N-Isopentylidene isopentylamine imine is a compound commonly found in putrefying substances and is thought to be a component of the smell of aquatic animals (Jones et al. \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOur results demonstrate the promise of an inexpensive, easy-to-use, and non-invasive method for sampling age, sex, and reproductive parameters in wild tigers and leopards using VOCs. VOC sampling could provide valuable complementary insights in landscapes where camera trapping, genetic and hormone-based methods deliver inconclusive results, and can also be useful for cryptic physiological parameters such as age and disease status. Camera trap images are often unreliable in detecting and estimating age and reproductive status of felids (Joubert et al. \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2020\u003c/span\u003e, Lu et al. \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Recent approaches to ageing based on telomere and methylation patterns are limited by high individual variation (Lema\u0026icirc;tre et al. \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Pepke 2024). Similarly genetic approaches to sexing from non-invasive samples have been found to have variable success rates (Robertson and Gemmell \u003cspan citationid=\"CR92\" class=\"CitationRef\"\u003e2006\u003c/span\u003e; Nichols and Spong 2017; Turcu et al. \u003cspan citationid=\"CR114\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Hormonal approaches are not sufficiently validated in non-invasive sources and require intensive pre-processing (Shutt et al. 2012; Terwissen et al. \u003cspan citationid=\"CR110\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). To the best of our knowledge, our volatilomics approach proposed here is a uniquely field-applicable and cost effective method for non-invasively estimating the age and reproductive states of tigers and leopards. However, we were unable to sample cubs since they do not typically mark their territories. This emphasizes the need to use camera trapping along with VOC monitoring since cubs can be detected on camera traps.\u003c/p\u003e \u003cp\u003eIn addition to demographic monitoring, a volatilomics approach can further address management challenges. For example, it could be used to identify individuals that have consumed human flesh based on scat volatiles for diet and to track the fitness effects of inbreeding. Volatiles also have great potential to diagnose health parameters, as shown with prior work (Cumeras et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Sha et al. \u003cspan citationid=\"CR96\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) and suggested with the four samples of one tiger individual in our dataset. The elevated dimethyl tetrasulfide detected in the four samples from one captive tiger being treated for epileptic seizures should be interpreted cautiously since it is based on a single individual and therefore no diagnostic inference can be drawn from this isolated case. However, this makes the case for the need of a systematic study of routine health complications in tigers and associated VOCs which could enable early detection and prevention of diseases in big cats. Importantly, our sampling was restricted only to one population of wild tigers. Volatiles can change with diet, and their stability might vary with weather, temperature, and other environmental variables. Sampling across tiger and leopard populations would better test the generality and robustness of these volatile markers.\u003c/p\u003e \u003cp\u003eThis study demonstrates how volatilomics approaches hold the potential to obtain many different kinds of information from wild populations. Integrating the volatilomics approach to microbiome, genetics, and behavioural data could provide valuable insights into scent communication in felids (Archie and Theis \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Stockley et al. \u003cspan citationid=\"CR107\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Fialov\u0026aacute; et al. \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Studies on big cat behaviour could help design bioassays that test whether the volatiles found in this study are also involved in tiger and leopard communication. The current limitation with conducting such bioassays is a lack of information about big cat behaviour: for example, how would a male tiger react to a female's urine versus a male's urine? Future work could integrate field behaviour studies with bioassays in captive populations to elucidate the role of volatiles in signalling and communication (Root-Gutteridge et al. 2025). The identification of such compounds could greatly help in identification of tiger and leopard attractants and deterrents as well as pheromones which can aid ex situ breeding programs.\u003c/p\u003e \u003cp\u003eInbreeding avoidance has been found to be mediated through odours in several species (Pfaff et al. \u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Hagelin \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Boulet et al. 2009; Bonadonna and Sanzaguilar 2012). Although such mechanisms are thought to evolve mostly in species where kin are encountered frequently (which is not the case in these big cats), the reliance on chemical communication in a solitary species suggests that their odours might encode information about fitness and inbreeding. For instance, inbreeding depression in sex hormones might reflect in volatiles associated with testosterone or female hormones and odour signals of inbreeding have been identified in insects (Ilmonen et al. \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; van Bergen et al., 2013; Menzel et al. 2016). Generating genetic as well as chemical data could help detect the possible presence of such odours and mechanisms in big cats.\u003c/p\u003e \u003cp\u003eTo conclude, our success in reliably sampling volatiles and distinguishing individuals by age and sex demonstrates the potential of this approach as a powerful, non-invasive tool for wildlife monitoring and is applicable to other species. With further validation, volatilomics could be integrated into conservation strategies for wild tiger populations, aiding in demographic assessments, health diagnostics, and long-term population management.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003cstrong\u003eConflicts of Interest:\u003c/strong\u003e \u003cp\u003eThe authors have no conflicts of interest to declare.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding:\u003c/h2\u003e \u003cp\u003eThis work was supported by National Geographic Society (EC-68219R-20 to BVA), National Centre\u003c/p\u003e \u003cp\u003efor Biological Sciences-TIFR (UR and SO), Bangalore and Ahmedabad University (CD).\u003c/p\u003e \u003cp\u003eAuthor contributions: BVA: Conceptualization, Data curation, Funding acquisition, Methodology, Investigation: field work, lab work, formal analysis, Visualization, Writing \u0026ndash; original draft, Writing-review and editing, Project administration; CD: Investigation: field work; DS: Software, UR and SO: Conceptualization, Methodology, Supervision, Validation, Writing-review and editing, Project administration, Funding acquisition\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eBVA: Conceptualization, Data curation, Funding acquisition, Methodology, Investigation: field work, lab work, formal analysis, Visualization, Writing \u0026ndash; original draft, Writing-review and editing, Project administration; CD: Investigation: field work; DS: Software, UR and SO: Conceptualization, Methodology, Supervision, Validation, Writing-review and editing, Project administration, Funding acquisition\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eBVA received fellowship support from NCBS-TIFR, Bangalore and CD from University Grants Commission, India. We thank the NCBS Mass Spectrometry Facility for enabling the analysis. The authors acknowledge Mujahid Khan, Krishna Avatar, Vasim, Kritagnya Vadar, Prerak Pathak, Faizee Ali Khan, and Samar Ahmad for assistance with field sampling; and Nelum Wickramsinghe and Bhaavya Malpani for assistance with lab work. We thank Dr. Ratna Ghoshal, Zoos of Baroda, Ahmedabad and Bangalore for facilitating the zoo sample collection and Prof. Kamala Jayanthi for sharing reagents. We thank Jyoti Nair, Srinivas, Yuvaraj Ranganathan and Harindra L. Baraiya for inputs on analysis and Prasenjeet Yadav for picture of tiger marking territory in Figure 1.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eGC-MS data is available with the corresponding author upon reasonable request. In the event of acceptance, the data will be made public through an online repository.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAche BW, Young JM (2005) Olfaction: Diverse Species. Conserved Principles Neuron 48(3):417\u0026ndash;430. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.neuron.2005.10.022\u003c/span\u003e\u003cspan address=\"10.1016/j.neuron.2005.10.022\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAllen ML, Heiko U, Wittmer, Emmarie P, Alexander, Wilmers CC (2021) Ontogeny of Scent Marking Behaviours in an Apex Carnivore. 1. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1163/15685394X-bja10127\u003c/span\u003e\u003cspan address=\"10.1163/15685394X-bja10127\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAmo L, Magdalena Ruiz Rodr\u0026iacute;guez (2023) Editorial: The Importance of Olfaction in Intra- and Interspecific Communication, II. Front Ecol Evol 11. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3389/fevo.2023.1261271\u003c/span\u003e\u003cspan address=\"10.3389/fevo.2023.1261271\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAndersen KF, Vulpius T (1999) Urinary Volatile Constituents of the Lion, Panthera Leo. Chem Senses 24(2):179\u0026ndash;189. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/chemse/24.2.179\u003c/span\u003e\u003cspan address=\"10.1093/chemse/24.2.179\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAndersen KF (1998) Chemocommunication and Social Behaviour in Three Panthera Species in Captivity, with Particular Reference to the Lion, P.Leo. 13. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.17863/CAM.16416\u003c/span\u003e\u003cspan address=\"10.17863/CAM.16416\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAnile S, and Sebastien Devillard (2018) Camera-Trapping Provides Insights into Adult Sex Ratio Variability in Felids. Mammal Rev 48(3):168\u0026ndash;179. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/mam.12120\u003c/span\u003e\u003cspan address=\"10.1111/mam.12120\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eApps P, Mmualefe L, Jordan NR, Golabek KA, Weldon McNutt J (2014) The \u0026lsquo;Tomcat Compound\u0026rsquo; 3-Mercapto-3-Methylbutanol Occurs in the Urine of Free-Ranging Leopards but Not in African Lions or Cheetahs. Biochem Syst Ecol 53(April):17\u0026ndash;19. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.bse.2013.12.013\u003c/span\u003e\u003cspan address=\"10.1016/j.bse.2013.12.013\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eApps P, Mmualefe L, Weldon J, McNutt (2012) Identification of Volatiles from the Secretions and Excretions of African Wild Dogs (Lycaon Pictus). J Chem Ecol 38(11):1450\u0026ndash;1461. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s10886-012-0206-7\u003c/span\u003e\u003cspan address=\"10.1007/s10886-012-0206-7\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eArchie EA, Theis KR (2011) Animal Behaviour Meets Microbial Ecology. Anim Behav 82(3):425\u0026ndash;436. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.anbehav.2011.05.029\u003c/span\u003e\u003cspan address=\"10.1016/j.anbehav.2011.05.029\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eArtois M, Bengis R, Delahay RJ et al (2009) Wildlife Disease Surveillance and Monitoring. In Management of Disease in Wild Mammals, edited by Richard J. Delahay, Graham C. Smith, and Michael R. Hutchings. Springer Japan. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/978-4-431-77134-0_10\u003c/span\u003e\u003cspan address=\"10.1007/978-4-431-77134-0_10\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBarja I, Pi\u0026ntilde;eiro A, Ruiz-Gonz\u0026aacute;lez A, Caro A, L\u0026oacute;pez P, and Jos\u0026eacute; Mart\u0026iacute;n (2023) Evaluating the Functional, Sexual and Seasonal Variation in the Chemical Constituents from Feces of Adult Iberian Wolves (Canis Lupus Signatus). Sci Rep 13:6669. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/s41598-023-33883-9\u003c/span\u003e\u003cspan address=\"10.1038/s41598-023-33883-9\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBayn A, Nol P, Tisch U, Rhyan J, Ellis CK, and Hossam Haick (2013) Detection of Volatile Organic Compounds in Brucella Abortus-Seropositive Bison. Anal Chem 85(22):11146\u0026ndash;11152. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1021/ac403134f\u003c/span\u003e\u003cspan address=\"10.1021/ac403134f\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBeauchamp GK, Doty RL, Moulton DG, Mugford RA (1976) The Pheromone Concept in Mammalian Chemical Communication: A Critique. In Mammalian Olfaction, Reproductive Processes, and Behavior. Elsevier. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/b978-0-12-221250-5.50012-7\u003c/span\u003e\u003cspan address=\"10.1016/b978-0-12-221250-5.50012-7\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003evan Bergen E, Brakefield PM, Heuskin St\u0026eacute;phanie, Zwaan BJ, Caroline M, Nieberding n.d. The Scent of Inbreeding: A Male Sex Pheromone Betrays Inbred Males. Proceedings. Biological Sciences 280 (1758): 20130102. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1098/rspb.2013.0102\u003c/span\u003e\u003cspan address=\"10.1098/rspb.2013.0102\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBonadonna F, Ana Sanz-aguilar (2012) Kin Recognition and Inbreeding Avoidance in Wild Birds: The Fi Rst Evidence for Individual Kin-Related Odour Recognition. Anim Behav 84(3):509\u0026ndash;513. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.anbehav.2012.06.014\u003c/span\u003e\u003cspan address=\"10.1016/j.anbehav.2012.06.014\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBoulet Maryl\u0026egrave;ne, Charpentier MJ, and Christine M. Drea (2009) Decoding an Olfactory Mechanism of Kin Recognition and Inbreeding Avoidance in a Primate. BMC Evol Biol 9(1):1\u0026ndash;11. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/1471-2148-9-281\u003c/span\u003e\u003cspan address=\"10.1186/1471-2148-9-281\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBrahmachary R, Sarkar M, Dutta J (1990) The Aroma Of Rice \u0026hellip; And Tiger. Nature 344:26\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://Doi.Org/10.1038/344026b0\u003c/span\u003e\u003cspan address=\"https://Doi.Org/10.1038/344026b0\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBrahmachary RL, Sarkar MP, Dutta J (1992) Chemical Signals in the Tiger. In Chemical Signals in Vertebrates 6. Springer US. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/978-1-4757-9655-1_72\u003c/span\u003e\u003cspan address=\"10.1007/978-1-4757-9655-1_72\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBreiman L (2001) Random Forests. Mach Learn 45(1):5\u0026ndash;32. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1023/A:1010933404324\u003c/span\u003e\u003cspan address=\"10.1023/A:1010933404324\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBrennan PA, Keith MK (2006b) Mammalian Social Odours: Attraction and Individual Recognition. Philosophical Trans Royal Soc B: Biol Sci 361(1476):2061\u0026ndash;2078. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1098/RSTB.2006.1931\u003c/span\u003e\u003cspan address=\"10.1098/RSTB.2006.1931\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBuljubasic F, and Gerhard Buchbauer (2015) The Scent of Human Diseases: A Review on Specific Volatile Organic Compounds as Diagnostic Biomarkers. Flavour Fragr J 30(1):5\u0026ndash;25. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1002/ffj.3219\u003c/span\u003e\u003cspan address=\"10.1002/ffj.3219\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBurger BV, Viviers MZ, Bekker JPI et al (2008) Chemical Characterization of Territorial Marking Fluid of Male Bengal Tiger, Panthera Tigris. 659\u0026ndash;671. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s10886-008-9462-y\u003c/span\u003e\u003cspan address=\"10.1007/s10886-008-9462-y\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBurger BV (2005) Mammalian Semiochemicals. In The Chemistry of Pheromones and Other Semiochemicals II: -/-, edited by Stefan Schulz. Springer. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/b98318\u003c/span\u003e\u003cspan address=\"10.1007/b98318\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBurnham E, Bender LC, Eiceman GA, Prasad S, and Karisa M. Pierce (2008) Use of Volatile Organic Components in Scat to Identify Canid Species. J Wildl Manage 72(3):792\u0026ndash;797. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.2193/2007-330\u003c/span\u003e\u003cspan address=\"10.2193/2007-330\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCandolin U (2003) The Use of Multiple Cues in Mate Choice. Biol Rev 78(4):575\u0026ndash;595. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1017/S1464793103006158\u003c/span\u003e\u003cspan address=\"10.1017/S1464793103006158\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCastro-Prieto A, Wachter B, and Simone Sommer (2010) Cheetah Paradigm Revisited: MHC Diversity in the World\u0026rsquo;s Largest Free-Ranging Population. Mol Biol Evol 28(4):1455\u0026ndash;1468. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/molbev/msq330\u003c/span\u003e\u003cspan address=\"10.1093/molbev/msq330\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCrump DR (1980) Anal Gland Secretion of the Ferret (Mustela Putorius formaFuro). J Chem Ecol 6(4):837\u0026ndash;844. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/BF00990407\u003c/span\u003e\u003cspan address=\"10.1007/BF00990407\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCumeras R, Cheung WHK, Gulland F, Goley D, Cristina ED (2014) Chemical Analysis of Whale Breath Volatiles: A Case Study for Non-Invasive Field Health Diagnostics of Marine Mammals. Metabolites 4:790\u0026ndash;806. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3390/metabo4030790\u003c/span\u003e\u003cspan address=\"10.3390/metabo4030790\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDaszak P (2000) Emerging Infectious Diseases of Wildlife\u0026ndash; Threats to Biodiversity and Human Health. Science 287 (5452): 443\u0026ndash;49. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1126/science.287.5452.443\u003c/span\u003e\u003cspan address=\"10.1126/science.287.5452.443\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDehnhard M (2011) Mammal Semiochemicals: Understanding Pheromones and Signature Mixtures for Better Zoo-Animal Husbandry and Conservation. Int Zoo Yearbook 45(1):55\u0026ndash;79. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/j.1748-1090.2010.00131.x\u003c/span\u003e\u003cspan address=\"10.1111/j.1748-1090.2010.00131.x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDepauw S, Hesta M, Whitehouse-Tedd K, Vanhaecke L, Verbrugghe A, Janssens GPJ (2013) Animal Fibre: The Forgotten Nutrient in Strict Carnivores? First Insights in the Cheetah. J Anim Physiol Anim Nutr 97(1):146\u0026ndash;154. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/j.1439-0396.2011.01252.x\u003c/span\u003e\u003cspan address=\"10.1111/j.1439-0396.2011.01252.x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDuffield R (1981) 2-Nonanol In The Exocrine Secretion Of The Nearctic Caddisfly, Rhyacophila Fuscula (Walker) (Rhyacophilidae: Trichoptera). 2-Nonanol In The Exocrine Secretion Of The Nearctic Caddisfly, Rhyacophila Fuscula (Walker) (Rhyacophilidae: Trichoptera)\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFarrell LE, Roman J, Sunquist ME (2000) Dietary Separation of Sympatric Carnivores Identified by Molecular Analysis of Scats. Mol Ecol 9(10):1583\u0026ndash;1590. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1046/J.1365-294X.2000.01037.X\u003c/span\u003e\u003cspan address=\"10.1046/J.1365-294X.2000.01037.X\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFavaro R, Pettersson M, Th\u0026ouml;ming G et al (2024) The Use of Volatile Organic Compounds in Preventing and Managing Invasive Plant Pests and Pathogens. Front Hortic 3. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3389/fhort.2024.1379997\u003c/span\u003e\u003cspan address=\"10.3389/fhort.2024.1379997\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFialov\u0026aacute; J, Třebick\u0026yacute; V\u0026iacute;t, Kuba R, Stella D, Binter J, Havl\u0026iacute;ček J (2020) Losing Stinks! The Effect of Competition Outcome on Body Odour Quality. Philosophical Trans Royal Soc B: Biol Sci 375(1800):20190267. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1098/rstb.2019.0267\u003c/span\u003e\u003cspan address=\"10.1098/rstb.2019.0267\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFromhage L, and Jonathan M. Henshaw (2022) The Balance Model of Honest Sexual Signaling. Evolution. Int J Org Evol 76(3):445\u0026ndash;454. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/evo.14436\u003c/span\u003e\u003cspan address=\"10.1111/evo.14436\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGarratt M, Stockley P, Armstrong SD, Beynon RJ, Hurst JL (2011) The Scent of Senescence: Sexual Signalling and Female Preference in House Mice. J Evol Biol 24(11):2398\u0026ndash;2409. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/j.1420-9101.2011.02367.x\u003c/span\u003e\u003cspan address=\"10.1111/j.1420-9101.2011.02367.x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGhoddousi A (2023) and I. Khorozyan. Panthera Pardus Ssp. Tulliana. The IUCN Red List of Threatened Species 2023: E. T15961A50660903. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://api.pelewg.net/storage/projects/1716645050009-IUCN%20Red%20List%20account_2023.pdf\u003c/span\u003e\u003cspan address=\"https://api.pelewg.net/storage/projects/1716645050009-IUCN%20Red%20List%20account_2023.pdf\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGikonyo NK, Hassanali A, Peter GN, Njagi, Peter M, Gitu, Midiwo JO (2002) Odor Composition of Preferred (Buffalo and Ox) and Nonpreferred (Waterbuck) Hosts of Some Savanna Tsetse Flies. J Chem Ecol 28(5):969\u0026ndash;981. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1023/a:1015205716921\u003c/span\u003e\u003cspan address=\"10.1023/a:1015205716921\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGilbert M, Miquelle DG, Goodrich JM et al (2014) Estimating the Potential Impact of Canine Distemper Virus on the Amur Tiger Population (Panthera Tigris Altaica) in Russia. PLoS ONE 9(10):e110811. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1371/JOURNAL.PONE.0110811\u003c/span\u003e\u003cspan address=\"10.1371/JOURNAL.PONE.0110811\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGoodrich J, Wibisono H, Miquelle D et al (2022) Panthera Tigris. The IUCN Red List of Threatened Species 2022: E. T15955A214862019. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://sintas.or.id/wp-content/uploads/2022/11/IUCN-Tiger-2022.pdf\u003c/span\u003e\u003cspan address=\"https://sintas.or.id/wp-content/uploads/2022/11/IUCN-Tiger-2022.pdf\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGrosbois V, Bonadonna F, Bessiere J-M, Miguel E, and Pierre Jouventin (2007) Individual Odor Recognition in Birds: An Endogenous Olfactory Signature on Petrels\u0026rsquo; Feathers? J Chem Ecol 33(9):1819\u0026ndash;1829. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s10886-007-9345-7\u003c/span\u003e\u003cspan address=\"10.1007/s10886-007-9345-7\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHagelin JC (2007) Odors and Chemical Signaling. Reproductive Biology and Phylogeny of Birds, Part B: Sexual Selection, Behavior, Conservation, Embryology and Genetics. CRC\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHagey L, and Edith Macdonald (2003) CHEMICAL CUES IDENTIFY GENDER AND INDIVIDUALITY IN GIANT PANDAS (Ailuropoda Melanoleuca). J Chem Ecol No 6, vol. 29\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHarmsen BJ, Rebecca J, Foster E, Sanchez et al (2017) Long Term Monitoring of Jaguars in the Cockscomb Basin Wildlife Sanctuary, Belize; Implications for Camera Trap Studies of Carnivores. PLoS ONE 12(6):e0179505. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1371/journal.pone.0179505\u003c/span\u003e\u003cspan address=\"10.1371/journal.pone.0179505\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIlmonen P, Stundner G, Tho\u0026szlig; M, Dustin JP (2009) Females Prefer Scent Outbred Males 10:1\u0026ndash;10. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/1471-2148-9-104\u003c/span\u003e\u003cspan address=\"10.1186/1471-2148-9-104\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTomberlin JK, Crippen TL, Wu G, Griffin AS, Wood TK, Kilner RM (2016) Indole\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAn E Conserved Influencer of Behavior across Kingdoms. Bioessays\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://onlinelibrary.wiley.com/doi/10.1002/bies.201600203\u003c/span\u003e\u003cspan address=\"https://onlinelibrary.wiley.com/doi/10.1002/bies.201600203\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJhala YV, Qureshi Q, and R. (eds) (2015) Gopal. Status of Tigers in India 2014. National Tiger Conservation Authority, New Delhi \u0026amp; The Wildlife Institute of India, Dehradun, no. June: 1\u0026ndash;25\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJones BC, Melissa M, Rocker, Russell SJ, Keast et al (2022) Systematic Review of the Odorous Volatile Compounds That Contribute to Flavour Profiles of Aquatic Animals. Reviews Aquaculture 14(3):1418\u0026ndash;1477. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/raq.12657\u003c/span\u003e\u003cspan address=\"10.1111/raq.12657\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJones MK, Thomas B, Huff EW, Freeman, and Nucharin Songsasen (2021) Differential Expression of Urinary Volatile Organic Compounds by Sex, Male Reproductive Status, and Pairing Status in the Maned Wolf (Chrysocyon Brachyurus). PLoS ONE 16(8):e0256388. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1371/journal.pone.0256388\u003c/span\u003e\u003cspan address=\"10.1371/journal.pone.0256388\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJoubert CJ, Tarugara A, Clegg BW, Gandiwa E, Muposhi VK (2020) A Baited-Camera Trapping Method for Estimating the Size and Sex Structure of African Leopard (Panthera Pardus) Populations. MethodsX 7. January101042. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.mex.2020.101042\u003c/span\u003e\u003cspan address=\"10.1016/j.mex.2020.101042\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKallenbach M, Oh Y, Eilers EJ, Veit D, Ian T, Baldwin, Meredith CS (2014) A Robust, Simple, High-Throughput Technique for Time-Resolved Plant Volatile Analysis in Field Experiments. Plant J 78(6):1060\u0026ndash;1072. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/tpj.12523\u003c/span\u003e\u003cspan address=\"10.1111/tpj.12523\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKappeler PM, Benhaiem S, Fichtel C et al (2023) Sex Roles and Sex Ratios in Animals. Biol Rev 98(2):462\u0026ndash;480. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/brv.12915\u003c/span\u003e\u003cspan address=\"10.1111/brv.12915\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKaranth K, Ullas (1995) Models Biol Conserv 71(3):333\u0026ndash;338. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/0006-3207(94)00057-W\u003c/span\u003e\u003cspan address=\"10.1016/0006-3207(94)00057-W\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Estimating Tiger Panthera Tigris Populations from Camera-Trap Data Using Capture\u0026mdash;Recapture\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKatsuji Uetake T, Abumi T, Suzuki S Hisamatsu, Minoru (2017) and Fukuda. Volatile Faecal Components Related to Sex and Age in Domestic Cats (Felis Catus)\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKean EF, Carsten T, M\u0026uuml;ller, Chadwick EA (2011) Otter Scent Signals Age, Sex, and Reproductive Status. Chem Senses 36(6):555\u0026ndash;564. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/chemse/bjr025\u003c/span\u003e\u003cspan address=\"10.1093/chemse/bjr025\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKhan A, Patel K, Bhattacharjee S et al (2020) Are Shed Hair Genomes the Most Effective Noninvasive Resource for Estimating Relationships in the Wild? Ecol Evol 10(11):4583\u0026ndash;4594. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1002/ece3.6157\u003c/span\u003e\u003cspan address=\"10.1002/ece3.6157\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKhoshgoftaar TM, Golawala M (2007) and Jason Van Hulse. An Empirical Study of Learning from Imbalanced Data Using Random Forest. 19th IEEE International Conference on Tools with Artificial Intelligence(ICTAI 2007) 2 (October): 310\u0026ndash;17. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1109/ICTAI.2007.46\u003c/span\u003e\u003cspan address=\"10.1109/ICTAI.2007.46\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eK\u0026uuml;cklich M, M\u0026ouml;ller M, Marcillo A et al (2017) Different Methods for Volatile Sampling in Mammals. PLoS ONE 12(8):e0183440. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1371/journal.pone.0183440\u003c/span\u003e\u003cspan address=\"10.1371/journal.pone.0183440\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLeal WS (2017) Reverse Chemical Ecology at the Service of Conservation Biology. Proceedings of the National Academy of Sciences 114 (46): 12094\u0026ndash;96. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1073/pnas.1717375114\u003c/span\u003e\u003cspan address=\"10.1073/pnas.1717375114\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLema\u0026icirc;tre J-F, Rey B, Gaillard J-M et al (2022) DNA Methylation as a Tool to Explore Ageing in Wild Roe Deer Populations. Mol Ecol Resour 22(3):1002\u0026ndash;1015. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/1755-0998.13533\u003c/span\u003e\u003cspan address=\"10.1111/1755-0998.13533\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLindgren PMF, Thomas P, Sullivan, Douglas RC (1995) Review of Synthetic Predator Odor Semiochemicals as Repellents for Wildlife Management in the Pacific Northwest\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLu Z, Whitton R, Strand T, Chen Y (2024) Review of Predator Emitted Volatile Organic Compounds and Their Potential for Predator Detection in New Zealand Forests. Forests 15(2):227. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3390/f15020227\u003c/span\u003e\u003cspan address=\"10.3390/f15020227\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eManzoli A, Steffens C, Paschoalin RT et al (2019) Sens Actuators B 282:609\u0026ndash;616. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.snb.2018.11.109\u003c/span\u003e\u003cspan address=\"10.1016/j.snb.2018.11.109\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Volatile Compounds Monitoring as Indicative of Female Cattle Fertile Period Using Electronic Nose.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMcLean S, Nichols DS, Davies NW (2021) Volatile Scent Chemicals in the Urine of the Red Fox, Vulpes Vulpes. PLoS ONE 16(3):e0248961. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1371/journal.pone.0248961\u003c/span\u003e\u003cspan address=\"10.1371/journal.pone.0248961\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMeinwald J, Eisner T (2008) Chemical Ecology in Retrospect and Prospect. Proceedings of the National Academy of Sciences 105 (12): 4539\u0026ndash;40. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1073/pnas.0800649105\u003c/span\u003e\u003cspan address=\"10.1073/pnas.0800649105\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMenzel F, Radke Ren\u0026eacute;, and Susanne Foitzik (2016) Odor Diversity Decreases with Inbreeding in the Ant Hypoponera Opacior. Evolution 70(11):2573\u0026ndash;2582. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/evo.13068\u003c/span\u003e\u003cspan address=\"10.1111/evo.13068\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMitchell J, Kyabulima S, Businge R, Cant MA, Nichols HJ (2018) Kin Discrimination via Odour in the Cooperatively Breeding Banded Mongoose. Royal Soc Open Sci 5(3):171798. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1098/rsos.171798\u003c/span\u003e\u003cspan address=\"10.1098/rsos.171798\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMiyazaki M, Miyazaki T, Nishimura T, Hojo W, and Tetsuro Yamashita (2018) The Chemical Basis of Species, Sex, and Individual Recognition Using Feces in the Domestic Cat. J Chem Ecol 44(4):364\u0026ndash;373. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s10886-018-0951-3\u003c/span\u003e\u003cspan address=\"10.1007/s10886-018-0951-3\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMondol, Samrat K, Ullas Karanth, and Uma Ramakrishnan (2009) Why the Indian Subcontinent Holds the Key to Global Tiger Recovery. PLoS Genet 5(8). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1371/journal.pgen.1000585\u003c/span\u003e\u003cspan address=\"10.1371/journal.pgen.1000585\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMunson L, Terio KA, Ryser-Degiorgis M-P, Lane EP, Courchamp F. Wild felid diseases: conservation implications and management strategies. Biology and conservation of wild felids 237 (2010): 259.Wilson, M. C., and, Harrison DE (1983) Decline in Male Mouse Pheromone with Age. Biology of Reproduction 29 (1): 81\u0026ndash;86. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1095/biolreprod29.1.81\u003c/span\u003e\u003cspan address=\"10.1095/biolreprod29.1.81\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNair JV, Shanmugam PV, Karpe SD, Ramakrishnan U, and Shannon Olsson (2018) An Optimized Protocol for Large-Scale in Situ Sampling and Analysis of Volatile Organic Compounds. Ecol Evol 8(11):5924\u0026ndash;5936. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1002/ece3.4138\u003c/span\u003e\u003cspan address=\"10.1002/ece3.4138\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNichols RV, G\u0026ouml;ran, Spong (2017) An eDNA-Based SNP Assay for Ungulate Species and Sex Identification. Diversity 9(3):33. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3390/d9030033\u003c/span\u003e\u003cspan address=\"10.3390/d9030033\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNoonan MJ, Tinnesand HV, Carsten T, M\u0026uuml;ller F, Rosell DW, Macdonald, and Christina D. Buesching (2019) Knowing Me, Knowing You: Anal Gland Secretion of European Badgers (Meles Meles) Codes for Individuality, Sex and Social Group Membership. J Chem Ecol 45(10):823\u0026ndash;837. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s10886-019-01113-0\u003c/span\u003e\u003cspan address=\"10.1007/s10886-019-01113-0\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNordstr\u0026ouml;m K, Dahlbom J, Pragadheesh VS et al (2017) In Situ Modeling of Multimodal Floral Cues Attracting Wild Pollinators across Environments. Proceedings of the National Academy of Sciences 114 (50): 13218\u0026ndash;23. world. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1073/pnas.1714414114\u003c/span\u003e\u003cspan address=\"10.1073/pnas.1714414114\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBothma P, du J and E. A. N. le Richet. 1995. Evidence of the Use of Rubbing, Scent-Marking Andscratching-Posts by Kalahari Leopards. J Arid Environ 29 (4): 511\u0026ndash;517. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/S0140-1963(95)80023-9\u003c/span\u003e\u003cspan address=\"10.1016/S0140-1963(95)80023-9\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePavlou AK, Turner APF (2000) Sniffing out the Truth: Clinical Diagnosis Using the Electronic Nose. Clinical Chemistry and Laboratory Medicine (CCLM). 38(2):99\u0026ndash;112. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1515/CCLM.2000.016\u003c/span\u003e\u003cspan address=\"10.1515/CCLM.2000.016\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePedregosa, Fabian \u0026amp; Varoquaux, Gael \u0026amp; Gramfort, Alexandre \u0026amp; Michel, Vincent \u0026amp; Thirion,Bertrand \u0026amp; Grisel, Olivier \u0026amp; Blondel, Mathieu \u0026amp; Prettenhofer, Peter \u0026amp; Weiss, Ron \u0026amp;Dubourg, Vincent \u0026amp; Vanderplas, Jake \u0026amp; Passos, Alexandre \u0026amp; Cournapeau, David \u0026amp; Brucher,Matthieu \u0026amp; Perrot, Matthieu \u0026amp; Duchesnay, Edouard \u0026amp; Louppe, Gilles. (2012). Scikit-learn:Machine Learning in Python. Journal of Machine Learning Research. 12. Pepke, Michael L. 2024. \u0026ldquo;Telomere Length Is Not a Useful Tool for Chronological Age Estimation in Animals.\u0026rdquo; BioEssays 46 (2): 2300187. https://doi.org/10.1002/bies.202300187.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePfaff DW, Kavaliers M, Choleris E, and A Anders (2004) Olfactory-Mediated Parasite Recognition and Avoidance: Linking Genes to Behavior. 46:272\u0026ndash;283. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.yhbeh.2004.03.005\u003c/span\u003e\u003cspan address=\"10.1016/j.yhbeh.2004.03.005\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePoddar-Sarkar M (1996) The Fixative Lipid of Tiger Pheromone. J Lipid Mediat Cell Signal 15(1):89\u0026ndash;101. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/S0929-7855(96)00547-0\u003c/span\u003e\u003cspan address=\"10.1016/S0929-7855(96)00547-0\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePoddar-Sarkar, Mousumi, Brahmachary RL (2004) Putative Chemical Signals of Leopard. Anim Biology 54(3):255\u0026ndash;259. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1163/1570756042484692\u003c/span\u003e\u003cspan address=\"10.1163/1570756042484692\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKasim Rafiq NR, Jordan C, Meloro AM, Wilson MW, Hayward SA, Wich JW, McNutt Scent-Marking Strategies of a Solitary Carnivore: Boundary and Road Scent Marking in the Leopard. Anim Behav 161 (March): 115\u0026ndash;126. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.anbehav.2019.12.016\u003c/span\u003e\u003cspan address=\"10.1016/j.anbehav.2019.12.016\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRajagopal T, Archunan G, Geraldine P (2018) and Chellam Balasundaram. Assessment of Dominance Hierarchy through Urine Scent Marking and Its Chemical Constituents in Male Blackbuck Antelope Cervicapra, a Critically Endangered Species Assessment of Dominance Hierarchy through Urine Scent Marking and Its Chemical Constituents. Behavioural Processes 85 (1): 58\u0026ndash;67. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.beproc.2010.06.007\u003c/span\u003e\u003cspan address=\"10.1016/j.beproc.2010.06.007\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRanganathan Y, Borges RM (2010) Reducing the Babel in Plant Volatile Communication: Using the Forest to See the Trees. Plant Biol 12(5):735\u0026ndash;742. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/j.1438-8677.2009.00278.x\u003c/span\u003e\u003cspan address=\"10.1111/j.1438-8677.2009.00278.x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRanganathan Y, and Renee M. Borges (2011) To Transform or Not to Transform. Plant Signal Behav 6(1):113\u0026ndash;116. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.4161/psb.6.1.14191\u003c/span\u003e\u003cspan address=\"10.4161/psb.6.1.14191\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRaymer J, Wiesler D, Novotny M, Asa C, Seal US, Mech LD (1984) Volatile Constituents of Wolf (Canis Lupus) Urine as Related to Gender and Season. Experientia 40(7):707\u0026ndash;709. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/BF01949734\u003c/span\u003e\u003cspan address=\"10.1007/BF01949734\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRendon NM, Helena A, Soini, Melissa-Ann L, Scotti MV, Novotny, Demas GE (2016) Urinary Volatile Compounds Differ across Reproductive Phenotypes and Following Aggression in Male Siberian Hamsters. Physiol Behav 164(October):58\u0026ndash;67. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.physbeh.2016.05.034\u003c/span\u003e\u003cspan address=\"10.1016/j.physbeh.2016.05.034\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRoach DA (2014) and James R. Carey. Population Biology of Aging in the Wild. Annual Review of Ecology, Evolution, and Systematics 45 (Volume 45, 2014): 421\u0026ndash;43. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1146/annurev-ecolsys-120213-091730\u003c/span\u003e\u003cspan address=\"10.1146/annurev-ecolsys-120213-091730\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRobertson BC, Gemmell NJ (2006) PCR-Based Sexing in Conservation Biology: Wrong Answers from an Accurate Methodology? Conserv Genet 7(2):267\u0026ndash;271. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s10592-005-9105-6\u003c/span\u003e\u003cspan address=\"10.1007/s10592-005-9105-6\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRodr\u0026iacute;guez-Hern\u0026aacute;ndez P, Cardador MJ, Arce L, Rodr\u0026iacute;guez-Est\u0026eacute;vez V (2022) Analytical Tools for Disease Diagnosis in Animals via Fecal Volatilome. Crit Rev Anal Chem 52(5):917\u0026ndash;932. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1080/10408347.2020.1843130\u003c/span\u003e\u003cspan address=\"10.1080/10408347.2020.1843130\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRoelke-Parker ME, Munson L, Packer C et al (2010) A Canine Distemper Virus Epidemic in Serengeti Lions (Panthera Leo) (Vol 379, Pg 441, 1996). Nature 464 (7290): 942. https://doi.org/Doi%252010.1038/Nature08888\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHolly Root-Gutteridge, de Kock N, Young M, Gill AC, Penny JA, Pike TW, Daniel S, Mills (2025) Common Scents? A Review of Potentially Shared Chemical Signals in the Order Carnivora. Chem Senses 50(January):bjaf019. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/chemse/bjaf019\u003c/span\u003e\u003cspan address=\"10.1093/chemse/bjaf019\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSha T, Fei W, Zhao Y, and Lin Bai (2024) Volatile Organic Compounds in Urine Reveals Distinct Diagnostic Signatures for Gastric Cancer. Preprint. 26. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.21203/rs.3.rs-4609159/v1\u003c/span\u003e\u003cspan address=\"10.21203/rs.3.rs-4609159/v1\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShumake SA (1977) The Search for Applications of Chemical Signals in Wildlife Management. In Chemical Signals in Vertebrates, edited by Dietland M\u0026uuml;ller-Schwarze and Maxwell M. Mozell. Springer US. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/978-1-4684-2364-8_20\u003c/span\u003e\u003cspan address=\"10.1007/978-1-4684-2364-8_20\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShutt K, Setchell JM, and Michael Heistermann (2012) Non-Invasive Monitoring of Physiological Stress in the Western Lowland Gorilla (Gorilla Gorilla Gorilla): Validation of a Fecal Glucocorticoid Assay and Methods for Practical Application in the Field. Gen Comp Endocrinol 179(2):167\u0026ndash;177. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.ygcen.2012.08.008\u003c/span\u003e\u003cspan address=\"10.1016/j.ygcen.2012.08.008\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSmith JL, David CM (1989) and Dale Miquellet. Scent Marking in Free-Ranging Tigers, Panthera Tigris. 1\u0026ndash;10\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSoini HA, Susan U, Linville D, Wiesler AL, Posto DR, Williams, and Milos V. Novotny (2012) Investigation of Scents on Cheeks and Foreheads of Large Felines in Connection to the Facial Marking Behavior. J Chem Ecol 38(2):145\u0026ndash;156. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s10886-012-0075-0\u003c/span\u003e\u003cspan address=\"10.1007/s10886-012-0075-0\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSoso SB, Koziel JA (2016) Analysis of Odorants in Marking Fluid of Siberian Tiger (Panthera Tigris Altaica) Using Simultaneous Sensory and Chemical Analysis with Headspace Solid-Phase Microextraction and Multidimensional Gas Chromatography-Mass Spectrometry-Olfactometry. Molecules 21(7):1\u0026ndash;22. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3390/molecules21070834\u003c/span\u003e\u003cspan address=\"10.3390/molecules21070834\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSoso SB, Jacek A, Koziel A, Johnson YJ, Lee, Sue Fairbanks W (2014) Analytical Methods for Chemical and Sensory Characterization of Scent-Markings in Large Wild Mammals: A Review. Sensors 14(3):4428\u0026ndash;4465. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3390/s140304428\u003c/span\u003e\u003cspan address=\"10.3390/s140304428\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eStahl RS, Ellis CK, Nol P, Waters WR, Palmer M, VerCauteren KC (2015) Fecal Volatile Organic\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCompound Profiles from White-Tailed Deer (Odocoileus virginianus) as Indicators\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eof Mycobacterium bovis Exposure or Mycobacterium bovis Bacille Calmette-Guerin (BCG)\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVaccination PLoS ONE 10(6): e0129740. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1371/journal.pone.0129740\u003c/span\u003e\u003cspan address=\"10.1371/journal.pone.0129740\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eStockley P, Bottell L, Hurst JL (2013) Wake up and Smell the Conflict: Odour Signals in Female Competition. Philosophical Trans Royal Soc B: Biol Sci 368(1631). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1098/rstb.2013.0082\u003c/span\u003e\u003cspan address=\"10.1098/rstb.2013.0082\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSunquist ME (1981) The Social Organization of Tigers (Panthera Tigris) in Royal Chitawan National Park. Nepal. mcdougal\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTellez MR, Kevin K, Schrader, and Mozaina Kobaisy (2001) Volatile Components of the Cyanobacterium Oscillatoria Perornata (Skuja). J Agric Food Chem 49(12):5989\u0026ndash;5992. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1021/jf010722p\u003c/span\u003e\u003cspan address=\"10.1021/jf010722p\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTerwissen CV, Mastromonaco GF, Murray DL (2014) Enzyme Immunoassays as a Method for Quantifying Hair Reproductive Hormones in Two Felid Species. Conserv Physiol 2(1):cou044. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/conphys/cou044\u003c/span\u003e\u003cspan address=\"10.1093/conphys/cou044\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eThompson CL, Kimberly N, Bottenberg AW, Lantz, Maria AB, de Oliveira LCO, Melo, and Christopher J. Vinyard (2020) What Smells? Developing in-Field Methods to Characterize the Chemical Composition of Wild Mammalian Scent Cues. Ecol Evol 10(11):4691\u0026ndash;4701. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1002/ece3.6224\u003c/span\u003e\u003cspan address=\"10.1002/ece3.6224\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTisdell C, Nantha HS, and Clevo Wilson (2007) Endangerment and Likeability of Wildlife Species: How Important Are They for Payments Proposed for Conservation? Ecol Econ 60(3):627\u0026ndash;633. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.ecolecon.2006.01.007\u003c/span\u003e\u003cspan address=\"10.1016/j.ecolecon.2006.01.007\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTossens S, Drouilly M, Lhoest S, Vermeulen C\u0026eacute;dric, and Jean-Louis Doucet (2025) Wild Felids in Trophic Cascades: A Global Review. Mammal Rev 55(1):e12358. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/mam.12358\u003c/span\u003e\u003cspan address=\"10.1111/mam.12358\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTurcu M-C, Paștiu AI, Bel LV, Dana LP (2023) A Comparison of Feathers and Oral Swab Samples as DNA Sources for Molecular Sexing in Companion Birds. Animals 13(3):525. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3390/ani13030525\u003c/span\u003e\u003cspan address=\"10.3390/ani13030525\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTuttle RH, George B (1968) Schaller Am Anthropol 70 (3): 649\u0026ndash;650. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1525/aa.1968.70.3.02a01090\u003c/span\u003e\u003cspan address=\"10.1525/aa.1968.70.3.02a01090\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVet, Louise EM (1999) From Chemical to Population Ecology: Infochemical Use in an Evolutionary Context. J Chem Ecol 25(1):31\u0026ndash;49. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1023/A:1020833015559\u003c/span\u003e\u003cspan address=\"10.1023/A:1020833015559\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWalker BJJ, Mike Letnic MP, Bucknall L, Watson, Neil RJ (2024) Male Dingo Urinary Scents Code for Age Class and Wild Dingoes Respond to This Information. Chem Senses 49(January):bjae004. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/chemse/bjae004\u003c/span\u003e\u003cspan address=\"10.1093/chemse/bjae004\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWaskom M (2021) J Open Source Softw 6(60):3021. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.21105/joss.03021\u003c/span\u003e\u003cspan address=\"10.21105/joss.03021\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Seaborn: Statistical Data Visualization.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWhitehead AL, Edge K-A, Smart AF, Hill GS, and Murray J. Willans (2008) Large Scale Predator Control Improves the Productivity of a Rare New Zealand Riverine Duck. Biol Conserv 141(11):2784\u0026ndash;2794. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.biocon.2008.08.013\u003c/span\u003e\u003cspan address=\"10.1016/j.biocon.2008.08.013\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWorsley SF, Charli S, Davies CZ, Lee et al (2024) Longitudinal Gut Microbiome Dynamics in Relation to Age and Senescence in a Wild Animal Population. Mol Ecol 33(16):e17477. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/mec.17477\u003c/span\u003e\u003cspan address=\"10.1111/mec.17477\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYamaguchi MS, Holly H, Ganz AW, Cho et al (2019) Bacteria Isolated from Bengal Cat (Felis Catus \u0026times; Prionailurus Bengalensis) Anal Sac Secretions Produce Volatile Compounds Potentially Associated with Animal Signaling. PLoS ONE 14(9):e0216846. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1371/journal.pone.0216846\u003c/span\u003e\u003cspan address=\"10.1371/journal.pone.0216846\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZala SM, Potts WK, and Dustin J. Penn (2004) Scent-Marking Displays Provide Honest Signals of Health and Infection. Behav Ecol 15(2):338\u0026ndash;344. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/beheco/arh022\u003c/span\u003e\u003cspan address=\"10.1093/beheco/arh022\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang JX, Soini HA, Bruce KE et al (2005) Putative Chemosignals of the Ferret (Mustela Furo) Associated with Individual and Gender Recognition. Chem Senses 30(9):727\u0026ndash;737. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/chemse/bji065\u003c/span\u003e\u003cspan address=\"10.1093/chemse/bji065\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"journal-of-chemical-ecology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"joce","sideBox":"Learn more about [Journal of Chemical Ecology](https://www.springer.com/journal/10886)","snPcode":"10886","submissionUrl":"https://submission.nature.com/new-submission/10886/3","title":"Journal of Chemical Ecology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Chemical ecology, sex identification, volatiles, tigers, leopards, age","lastPublishedDoi":"10.21203/rs.3.rs-8895773/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8895773/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eChemical cues play an important role in mammalian communication, often reflecting an individual\u0026rsquo;s physiological state. Non-invasive sampling of such informative cues holds great potential for wildlife monitoring. Endangered apex predators such as big cats are elusive and challenging to monitor. While existing monitoring techniques estimate numbers or densities, they often fail to provide crucial demographic and physiological information. We applied a customized field sampling technique to sample volatiles from urine and faeces of captive Bengal tigers and Indian leopards of known age and sex, and from urine of identified wild Bengal tigers of known age, sex, and reproductive status. Volatiles extracted from these samples were analysed using Thermal Desorption- Gas Chromatography-Mass Spectrometry. The random forest algorithm was used to identify compounds that might be cues for species, age, sex, and reproductive state.\u003c/p\u003e \u003cp\u003eSpecies classification accuracy was consistently high with both urine (0.79\u0026thinsp;+\u0026thinsp;0.009) and scat (0.75\u0026thinsp;+\u0026thinsp;0.029) volatiles. Classification accuracy of urine volatiles was high for females and young individuals in leopards and tigers, but lower for males and old individuals. Scat volatiles performed better across groups. We also identified putative chemical markers for epilepsy and reproductive state in tigers. This study presents the first chemical characterization of tiger and leopard scats and the first sampling of tiger odours from the wild. Our simple and cost-effective method of sampling tiger and leopard odours offers a novel method of chemical fingerprinting to monitor populations in situ. Importantly, this sampling method and analytical pipeline is broadly applicable to other mammalian species for conservation and ecological studies.\u003c/p\u003e","manuscriptTitle":"Non-invasive Sampling of Odours From Two Big Cats for Wildlife Conservation","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-24 14:28:49","doi":"10.21203/rs.3.rs-8895773/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-03-15T23:42:08+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-15T06:28:50+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-12T18:34:53+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"66360638254128676083985271244073595460","date":"2026-03-02T16:12:16+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"155984309540584322368587292876629025283","date":"2026-02-27T18:36:33+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-02-25T11:51:23+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-02-24T15:49:23+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-02-23T11:35:19+00:00","index":"","fulltext":""},{"type":"submitted","content":"Journal of Chemical Ecology","date":"2026-02-16T19:12:29+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"journal-of-chemical-ecology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"joce","sideBox":"Learn more about [Journal of Chemical Ecology](https://www.springer.com/journal/10886)","snPcode":"10886","submissionUrl":"https://submission.nature.com/new-submission/10886/3","title":"Journal of Chemical Ecology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"9224c7cb-e7b5-482f-aabd-a38d350f5d46","owner":[],"postedDate":"February 24th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-17T00:38:21+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-24 14:28:49","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8895773","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8895773","identity":"rs-8895773","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}