Climatic drivers of chytrid prevalence in the critically endangered Admirable Redbelly Toad

Climatic drivers of chytrid prevalence in the critically endangered Admirable Redbelly Toad | 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 Climatic drivers of chytrid prevalence in the critically endangered Admirable Redbelly Toad Mariana Retuci Pontes, Michelle Abadie, Luisa Ribeiro, Guilherme Augusto-Alves, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4281618/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Global warming is driving shifts in rainfall and temperature patterns, and projections indicate an increase in frequency and intensity of climate anomalies. These changes influence wildlife disease dynamics, affecting pathogen development, host behavior, physiology, and disease susceptibility. Understanding the intricate interplay between climatic anomalies and emerging pathogens in amphibian is essential to inform conservation efforts targeted towards this highly threatened vertebrate group. In-situ research is recommended as a conservation action by the International Union for Conservation of Nature (IUCN 2023) for the microendemic and Critically Endangered amphibian Melanophryniscus admirabilis (Admirable Redbelly Toad). We therefore investigated the seasonal climatic fluctuations and climatic anomalies affecting infections by the waterborne chytrid Batrachochytrium dendrobatidis (Bd) in this sole surviving population, which holds significant conservation concern. We found links between high Bd prevalence, monthly low rainfall and rainfall deficit. Additionally, an increase in Bd prevalence was associated with temperatures exceeding historical averages. These findings suggests that climatic anomalies play a crucial role in Bd transmission and infection status among toads, probably due their aggregation behavior in few available pools during drier and warmer periods. Despite the current low prevalence of Bd and infection loads, the projected escalation of climatic anomalies might render M. admirabilis uniquely susceptible to synergistic interactions between Bd and extreme climatic conditions. The insights gained from this study can improve the conservation efforts and underscore the intricate relationship between climatic anomalies and chytrid infection, shedding light on potential vulnerabilities within threatened amphibian populations. Atlantic Forest Batrachochytrium dendrobatidis Brazil Climate change Conservation Melanophryniscus admirabilis Figures Figure 1 Figure 2 Figure 3 1. INTRODUCTION The modifications resulting from the expansion of human populations have led to an increased frequency and intensity of climatic extremes (Seneviratne et al. 2021). Rainfall and temperature patterns have globally shifted in response to global warming (Seneviratne et al. 2021), and climatic anomalies are projected to increase in frequency and intensity (Sillmann et al. 2013) . Climatic anomalies can alter entire ecosystems (Frank et al. 2015; Bardgett and Caruso, 2020) , extending their impact also over wildlife disease dynamics (Cohen et al. 2020; Greenspan et al. 2020; Rohr and Cohen, 2020) . This intricate interplay occurs through a wide range of mechanisms, encompassing shifts in pathogen development (Nnadi and Carter, 2021) , and alteration in host behavior and physiological traits (Staudinger et al. 2013; Bozinovic and Pörtner, 2015) that often lead to increased susceptibility to diseases (Bradley et al. 2019) . Wildlife disease dynamics are influenced by micro and macro-climatic variables (Harvell et al. 2003; Boser et al. 2021) , often involving synergistic interactions between pathogens and their hosts (Rohr and Raffel, 2010, Altizer et al. 2013). The waterborne fungal pathogen Batrachochytrium dendrobatidis (hereafter Bd ) causes the disease chytridiomycosis in amphibians and has been implicated in population declines and extinctions globally (Scheele et al. 2019) . Moreover, alterations in temperature and rainfall patterns are known to impact the onset of breeding phenology in amphibians (Dalpasso et al. 2023). Amphibian Bd infection could be also influenced by seasonal temperature and rainfall patterns (Ruggeri et al. 2018; Turner et al. 2021) . Consequently, accelerated climate variability could synergistically drive amphibians to the extinction path, as amphibians are already the most endangered vertebrate taxon according to the recent assessment led by the International Union for Conservation of Nature (IUCN) assessment (IUCN 2023; Luedtke et al. 2023) . The Bd -amphibian system thus provides an opportunity to investigate the impact of climate anomalies on disease dynamics in formally endangered species, such as the Admirable Redbelly Toad, Melanophryniscus admirabilis (Bufonidae), from southern Brazil, a region with widespread occurrence of Bd . This microendemic Neotropical species is classified as Critically Endangered (CR) by the IUCN redlist of threatened species (IUCN 2023) and by the Brazilian redlist (Brasil 2022). This species is included into public conservation policies of Brazil and has become a global success story and symbol of hope for amphibian conservation (Fonte et al. 2022). Additionally, chytridiomycosis outbreaks were classified as the greatest concern among the ten direct threats to the species (Abadie et al. unpublished results), further highlighting the urgency of understanding and addressing the intricate interplay between climate, disease, and the conservation of M. admirabilis (IUCN 2023). Melanophryniscus admirabilis uses temporary small polls filled by rainfall as vocalization and breeding site (Di-Bernardo et al. 2006) . Similarly, Bd depends on water for its growth, survival, and dispersion (Berger et al. 2005), although it can be transported by other non-amphibian vectors ( e.g. , Pontes et al. 2018; Toledo et al. 2021; Prado et al. 2023) . Therefore, rainfall and their anomalies could significantly impact both the reproductive biology of M. admirabilis and pathogen infection dynamic (Ruggeri et al. 2018; Moura-Campos et al. 2021) . Temperature also plays an important role in successful reproduction of the Admirable Redbelly Toad, since this species depends on the duration of shallow pools, which can quickly evaporate under high temperatures (Abadie et al. unpublished results). Additionally, temperature can also influence Bd lifecycle, and despite Bd exhibiting varying thermal tolerance (Voyles et al. 2017) , temperature can induce alterations in Bd life history (Woodhams et al. 2008; Muletz-Wolz et al. 2019) and play a major role in determining the Bd infection loads in hosts (Bielby et al. 2022) . Amphibians demonstrate increased susceptibility to chytridiomycosis when experiencing anomalies in environmental temperatures (Clare et al. 2016; Cohen et al. 2019a; Serrano et al. 2022) . Furthermore, the ability of hosts to mount innate immune responses against Bd can be considerably impaired by ambient temperature modification (Grogan et al. 2018). Hence, seasonal and historical variation in temperature and rainfall are recognized as relevant environmental variables likely influencing Bd infection dynamics in M. admirabilis. Alternatively, the environmental context can benefit amphibians in mitigating Bd infections (Karavlan and Venesky, 2016). For instance, Bd growth is significantly suppressed at temperatures above 25 °C (Piotrowski et al. 2004; Stevenson et al. 2013) , thus, predicted increases in average global temperatures could suppress pathogen growth in amphibians’ skin. However, the interaction of Bd infection and warming could lead to an increase in mortality of cool-adapted host species at higher temperatures, despite lower infection loads (Neely et al. 2020) . This suggests that even when temperatures approach the upper thermal limit of the pathogen, Bd infection may cause declines in cool-adapted montane frogs due to the combined pressures of pathogen infection and warming-related stress (Neely et al. 2020) . Specifically, Bd infection can lead to host stress (Bielby et al. 2015) , with downstream impacts on host body condition and fitness (Campbell et al. 2019; Pontes et al. 2021; Bosch et al. 2023) . Bd infection has also been linked to population declines in wild amphibians through sublethal effects that reduce host fitness (Chatfield et al. 2013; Valenzuela-Sánchez et al. 2017; Brannelly et al. 2018; Palomar et al. 2023 ), extending beyond immediate consequences to affect long-term population dynamics and persistence (Valenzuela-Sánchez et al. 2017; Palomar et al. 2023). Understanding these broader consequences and Bd infection dynamics is vital for effective conservation strategies for the Critically Endangered Admirable Redbelly Toad, particularly in light of its higher vulnerability to extinction due the stochastic events (Fonte et al. 2022). Considering the pivotal role of climatic variables in predicting amphibian host-pathogen dynamics, we aimed to tested whether the local monthly climatic fluctuations and climatic anomalies would induce changes in Bd dynamics in M. admirabilis . As this toad depends on temporary pools to breed, we hypothesized that seasonal fluctuations in temperature and rainfall impact the Bd dynamics, and we expect that periods with higher temperatures and low rainfall will result in higher Bd prevalence and infection loads. Additionally, we hypothesized that the M. admirabilis population will experience higher Bd prevalence in periods with rainfall deficit, as the scarcity of pools would lead them to aggregate. Warming can reduce host immune capacity due to heat-induced stress (Cohen et al. 2019b; Neely et al. 2020) , and may also contribute to the drying up of pools. Consequently, we expect higher Bd prevalence and infection loads in period when temperature exceeds the historical average. Finally, considering sublethal effects caused by Bd infection (Valenzuela-Sánchez et al. 2017; Palomar et al. 2023; Wu, 2023) , we expect that Bd infection status has consequences on host body condition. Combined, our goals will allow us to elucidate the disease dynamics of a critically endangered micro-endemic tropical species. 2. METHODS 2.1 Study site and field sampling The only know site for M. admirabilis is located in municipality of Arvorezinha, State of Rio Grande do Sul, Brazil (52°18’’W, 28°51’S), in the Southern portion of the Atlantic Forest (Di-Bernardo et al. 2006) . The climate is humid subtropical, and seasons (autumn, winter, spring, and summer) are differentiated by temperature (Zepner et al. 2021) . We conducted our study along ~ 400 m on the Forqueta river’s bank, where most individuals of this microendemic species (range size of 1.6 km 2 , IUCN, 2023) concentrate to breed on temporary pools formed on flat rock outcrops. We surveyed the site at least twice a year, from September 2019 to December 2022 (exclusively between September and December), totaling nine field campaigns (Table 1). We captured each toad using new disposable latex gloves and swabbed the skin using MedicalWire MW113 swabs, following standard swabbing protocols (Hyatt et al. 2007). To calculate the body condition of each toad, we measured the snout-vent length (SVL) of each individual using a digital caliper with a precision of 0.01 mm and the body mass using a field scale with precision of 0.1 g. After sampling, we immediately released all toads at the exact point of capture. We applied a photo-identification standardized procedure (Bardier et al. 2019; Caorsi et al. 2012) as a mark-recapture method. The ventral region of each toad was photographed (Figure S1), and we used the Wild-ID open-source software (Bolger et al. 2012) to identify recaptures. The software compares all images for pairwise similarity and returns the 20 top-ranked potential matches for each focal image; all recaptures were visually confirmed afterwards. This mark-recapture method has been successfully applied to M. admirabilis (Fonte et al. 2022) and other species of Melanophryniscus (Caorsi et al. 2012; Bardier et al. 2019) due to their black, brown, or green background with red, yellow, white, green, or orange spots on their belly (Figure S1). 2.2 Pathogen detection and quantification To assess a sensitivity performance parameter for Bd diagnostic in our QuantStudio™ 6 Real-Time PCR equipment, we performed a series of replicate standard curves, totaling 20 replicates per standard concentration to calculate the limit of detection “LoD”. LoD is defined as the lowest amount of target DNA sequence that can be detected with 95 % probability. We ran a dilution series of a known amount of total Bd DNA, ranging from 1.83 x 10 5 GE/µL to 10 -3 GE/µL. Each plate included 4 technical replicates of each standard concentration, resulting in a total of 32 standards samples per plate, as well as 4 negative controls consisted of DNA-free water. Bd DNA was extracted from a culture (isolate CLFT 159, global panzootic lineage) using PrepMan ULTRA® (Life Technologies). For the qPCR assay, we utilized a final volume of 25 µL, containing 5 μL of template DNA, 12.5 μL of TaqMan Fast Master Mix (Applied Biosystem), 3.75 μL of ddH2O, 1.25 μL of forward primer (ITS-1 Chytr CCTTGATATAATACAGTGTGCCATATGTC, 18 μM), 1.25 μL of reverse primer (5.8S Chytr AGCCAAGAGATCCGTTGTCAAA, 18 μM), and 1.25 μL of probe (Chytr MGB2 GCAGTCGAACAAAAT, 5 μM). We used thermal cycling at 50 °C for 2 minutes and 95 ºC for 20 seconds, followed by 50 cycles at 95 ºC for 1 second and 60 °C for 20 seconds. The outcome of our analysis indicated that the lowest standard concentration with detection rate of 95 % or greater detection was 0.1 copies per reaction (1.83 x 10 -1 GE/μL) (Table S1, Figure S2). To determine the presence and infection loads of Bd in each swab sample, we extracted DNA from skin swabs using PrepMan ULTRA® (Life Technologies). To quantify Bd infection loads, we used a Taqman® qPCR Assay (Life Technologies) with standards ranging from 10 -1 to 10 3 genomic equivalents of zoospores, hereafter referred as GE (Boyle et al. 2004; Lambertini et al. 2013). We considered samples to be Bd -positive ( Bd + ) when the infection loads were ≥ 0.1 GE. 2.3 Abiotic data We obtained the mean temperature for the 15 days leading up to the sampling from two automated weather station located approximately 23 and 37 km from the study site ( Instituto Nacional de Meteorologia do Brasil ). We used 15 d prior to sampling based on the Bd life cycle (i.e. this period is enough to allow at least 1 generation of Bd ; Berger et al. 2005). To assess temperature anomaly metrics, we used the TerraClimate dataset (Abatzoglou et al. 2018) . We calculated the deviation from the historical temperatures by subtracting the historical monthly mean temperature over the past 50 years from the mean temperature of the target periods. These temperature deviations (ºC) were calculated for one, two, and three months preceding our sampling, incorporating one-month lagged deviations. The resulting deviation values could be negative for colder-than-average months, and positive for warmer-than-average months. Additionally, we recorded the accumulated rainfall for each month prior to sampling using data from a neighboring hydrometeorological station located at a similar altitude, 5.5 km from the study site ( Agência Nacional de Águas ). To assess rainfall anomaly metrics, we calculated the deviation from historical rainfall by subtracting the historical monthly mean of accumulated rainfall over the past 50 years from the mean accumulated rainfall of the target periods (Abatzoglou et al. 2018) . Like our temperature anomaly metrics, we extracted rainfall deviations (mm) for one, two, and three months prior to the sampled month. This analysis provided us with negative values for dryer-than-average months and positive values for wetter-than-average months. 2.4 Data analyses and modelling For statistical analysis, we employed two model selection approach. Firstly, to screen for important climatic anomaly metrics explaining Bd prevalence and infections loads, we employed a model selection approach based on Generalized Linear Models (GLM), thus reducing potential multicollinearity bias in downstream pruned models. Based on the Akaike Information Criterion (AIC) (Mazerolle, 2006), the three-month temperature deviation, and two-month rainfall deviation were the best predictor explaining Bd prevalence. Additionally, two-month temperature deviation was the best predictor explaining Bd infection load, while three-month rainfall deviation was the best predictor variable. A detailed description of these models can be found in the supplementary information (Table S2). Secondly, to test for the potential effect of monthly climatic fluctuations and climatic anomalies explaining Bd prevalence and infection loads, we employed a model selection approach based on GLMs. For Bd prevalence, we fit a GLM with binomial distribution and logit link function. We also fit a Gaussian GLM with log link function, with Bd infection loads (log10-transformed GE; only Bd + samples) as the response variable. The explanatory variables in the global models were: year, month, mean temperature of the 15 days prior to sampling date, accumulated monthly rainfall from the month prior to sampling date, and climatic anomaly metrics depicting temperature deviation and rainfall deviation. For each GLM, we included year, month ( Bd prevalence) and season (warm or cold, Bd infection load model) and as fixed effects. A detailed description of these models can be found in the supplementary information (Table S3). We ran models with all possible combination of explanatory variables, and we ranked the most parsimonious models by employing a backward stepwise procedure based on the Akaike Information Criterion (AIC) (Mazerolle, 2006; Table S3). Finally, to investigate any significant differences in body condition between Bd infected and uninfected toads (explanatory categorical variable), we performed a Student’s t -test, including data of body condition from adult males sampled until August 2021 (n = 155). We performed a linear regression analysis to test for the potential effect of Bd infection loads on body condition of Bd + males (n = 33). The body condition metric utilized the Scaled Mass Index (SMI) approach, based on standardized major axis regression between mass and snout−vent length (Peig and Green, 2009) . We excluded females from this analysis because the presence of eggs could bias our results. All statistical analyses were performed using R version 2023.3.1 (R Core Team 2022). 3. RESULTS We took 339 skin swab samples from 305 individual toads, and overall Bd prevalence was 15.9 % (54 Bd + ; n = 339; Table 1 for the prevalence data at each sampling event), and the mean infection loads in Bd + toads was 73.58 GE, ranging from 0.1 – 2,112.45 GE ± 293.36 SD (Table 1 for infection loads data at each sampling event). Bd prevalence and infection loads were higher in August (Figure 1), with a prevalence of 22.14 % (31 Bd + ; n = 140) and a mean Bd infection loads of 103.50 GE ± 383.14 SD. Our most parsimonious GLM model explaining Bd prevalence in the Admirable Redbelly Toads showed that month ( z = 4.084, P < 0.01) and increased temperature deviation ( z = 4.555, P < 0.001; Figure 2A) predicted higher Bd prevalence. Conversely, rainfall ( z = -4.241, P < 0.001; Figure 2B) and rainfall deviation (z = -4.735, P < 0.001; Figure 2C) negatively affected Bd prevalence during our sampling timeframe (Table 2). Our best-fit model explaining Bd infection loads included month, year, temperature, and temperature deviation (Table S3). However, we did not find statistically significant effect of climatic seasonal and climatic anomaly metrics in Bd infection loads. We did not observe significant difference in SMI between infected and uninfected toads ( t-value = -0.64, df = 47.114, P = 0.519). Additionally, we did not find a significant correlation between SMI and infection loads of Bd + individuals ( P = 0.394; Figure S3). A total of 305 toads were captured once, 29 captured twice, five captured three times, and one was captured four times. Regarding Bd infection status over time, a total of seven recaptured toads were found infected at least once. They gained infection seven times, while they cleared Bd infection only three times (Figure 3). 4. DISCUSSION Our study revealed that seasonal climatic fluctuations and climatic anomaly metrics are linked with Bd prevalence in M. admirabilis . Anomalies such as rainfall deficit, combined with temperatures that exceed the historical average, were key in predicting Bd infection risk in this amphibian species. Consequently, our findings suggest that with the projected increase of climatic anomalies over the next decades (Sillmann et al. 2013), the only known Admirable Redbelly Toad population may face a scenario of increasing Bd pressure. In agreement with our predictions, the Admirable Redbelly Toads were more likely to have higher Bd prevalence when rainfall in the previous month was low, as well in periods of rainfall deficit. Strikingly, this population also have higher Bd prevalence when the temperatures of the preceding three month exceeded the historical average. This species relies on small temporary pools for reproduction ( Di-Bernardo et al. 2006, Bordignon et al. unpublished results ) that depend on rainfall and evaporation. Hence, dry and warmer periods can rapidly lead to the drying up of shallow pools, directly or indirectly imposing physiological stress and forcing toads to aggregate in the fewer deeper pools that remain available over longer periods of time (Rohr and Palmer, 2013; Moura-Campos et al. 2021) . These aggregations serve as a significant reservoir of infective Bd zoospores (Longo et al. 2010; Becker et al. 2016) , increasing the likelihood of Bd transmission when toads interact (Malagon et al. 2020; Moura-Campos et al. 2021). Additionally, population size and contact rates among toads were also linked with higher Bd prevalence in other Melanophryniscus species (Pontes et al. 2021). Although not measured in this study, the seasonal demography of M. admirabilis may also play a role in Bd infections dynamic in the only known population of this species. Thus, our findings suggest that M. admirabilis may be particularly vulnerable to synergistic interactions between Bd and climatic anomalies, as rainfall deficit and warming not only facilitate the spread of Bd, but also reduce the availability of pools for reproduction. Climatic variables were not correlated with Bd infection loads in M. admirabilis population, which experiences low Bd infection loads. As Bd infection depends on interaction between the thermal performance of the pathogen and the host (Cohen et al. 2017), even at low infection level, the synergistic effects of warming and Bd could result in host mortality in cool-adapted anurans (Neely et al. 2020) . This implies that the combined effects of Bd infection and climate change, mainly temperature anomalies, might be underestimated, as Bd affect the amphibian persistence even with low prevalence and infection loads (Valenzuela-Sánchez et al. 2017; Palomar et al. 2023) . This highlights the significance of population-level impacts of Bd (Valenzuela-Sánchez et al. 2017) that may potentially lead to slow and steady long-term declines. Consequently, in light of the projected increase in temperature anomalies (Sillmann et al. 2013) , future studies on the thermal tolerance of the Admirable Redbelly Toads and its interaction with Bd infection become essential for a comprehensive understanding of the consequences of accelerated climate change on this species. Contrary to our predictions, our findings suggest that body condition was not linked with Bd . Evidence of sublethal effects of Bd on body condition are rarely observed in wild populations that do not experience chytridiomycosis-related mortality. However, it is worth noting that even at low infection levels, Bd could lead to impaired skin physiology ( i.e., skin integrity, osmoregulation, and hormone production) (Wu, 2023) . Additionally, Bd is known to dramatically alter the amphibian skin microbiome (Becker et al. 2017; Becker et al. 2019) and it is known that the presence of the bacteria Serratia marcensis could also be playing an important structural role in skin microbiome health in our focal amphibian species (Ienes-Lima et al. 2023a, 2023b; Woodhams et al. 2023) . Furthermore, the capture-mark-recapture analysis showed that although the Admirable Redbelly Toads demonstrated the ability to clear Bd infection, they still gained more infection than managed to clear over time. The probability of becoming Bd + higher than the probability of clearance is a characteristic of population on a path of slow decline (Palomar et al. 2023) . Therefore, tracking individual Bd infection status over time is crucial for future assessments of the population heath. Melanophryniscus species could be affected by climate change in different ways, including the reduction of suitable habitat (Zank et al. 2014) . This study represents the first long-term investigation of Bd prevalence and infection loads and its climatic drivers in the Admirable Redbelly Toad sole population. With trends in global warming, higher disease risk is expected in cool-adapted organisms (Rohr and Cohen, 2020) , as the case of various Melanophryniscus populations. Therefore, studies that investigate the interactive effects of disease and climate change must be conducted to safeguard endangered amphibian species, as interactions between warming and infection could still lead to population declines (Neely et al. 2020) . While chytridiomycosis may not pose an immediate threat to the microendemic Admirable Redbelly Toads, common stressors such as herbicides (Da-Silva et al. 2023) and anthropic impact (Ienes-Lima et al. 2023a) could amplify the fitness impacts of climate change (Greenspan et al. 2017; Rohr and Palmer, 2013) . We strongly advocate for the continuation of research with Bd and its interaction with other prevalent pathogens in the southern Brazil, such as Ranavirus (Ruggeri et al. 2023) , on M. admirabilis sole population. Surveying both pathogens mainly in dryer periods is especially crucial for its conservation, considering their vulnerability to declines resulting from stochastic events. Declarations Acknowledgements We thank Debora W. Bordignon, Patrick Colombo, Maria Eduarda B. Cunha, Gabriel Schubert R. Costa, Natália D. Vargas, Isis S. Homrich, Bibiana T. Dasoler, Tiago Quaggio and Luís Fernando M. Fonte for assistance with logistics and fieldwork. We thank Graziela Civa and Neusa Civa for their support in Arvorezinha. M.R.P. thanks Idea Wild for providing several pieces of field equipment. We also thank Gabriel Schubert R. Costa for technical assistance throughout in data compilation. Funding This work was supported by São Paulo Research Foundation (FAPESP 2020/00099-0, 2018/23622-0, 2019/03170-0, 2016/25358-3, 2022/11096-8); the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior – Brasil (CAPES - Finance Code 001); the National Council for Scientific and Technological Development (CNPq 300896/2016-6, 302834/2020-6); the Fundação Grupo Boticário, Brazil (1062_20161); the Rufford Foundation (22286-1), and the National Centre for Research and Conservation of Reptiles and Amphibians of the Chico Mendes Institute for Biodiversity Conservation -RAN/ICMBio, Brazil. Ethics approval All applicable institutional and national guidelines for the care and use of animals were followed. This work was conducted under permits by Instituto Chico Mendes de Conservação da Biodiversidade (SISBio #72718), Sistema Nacional de Gestão do Patrimônio Genético e do Conhecimento Tradicional Associado (SisGen #A3D44D1). This work was approved by Unicamp Animal Care and Ethics Committee (CEUA #5581-1/2020). Competing interests The authors have no relevant financial or non-financial interests to disclose. Author contributions M.R.P. and L.F.T. designed the study. M.R.P, M.A., G.A.A. and M.B.M. carried out the fieldwork. M.R.P and L.P.R. carried out the molecular analysis. M.R.P and G.C.B analyzed the data. MRP drafted the manuscript. All authors critically revised the manuscript and approved the final manuscript. Data Availability The data that support the findings of this study openly available in the Dryad Digital Repository: https://doi.org/10.5061/dryad.0zpc86754 References Abatzoglou J, Dobrowski S, Parks S, Hegewisch KC (2018) TerraClimate, a high-resolution global dataset of monthly climate and climatic water balance from 1958–2015. Sci Data 5:170191. https://doi.org/10.1038/sdata.2017.19 Agência Nacional das Águas (ANA) (2023) https://www.gov.br/ana/pt-br (accessed 25 January 2023). 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Total refers to the general Bd prevalence and mean of infection load and SD. Year Month Bd prevalence ( Bd + / n) Mean Bd infection load 2019 September 13.33 % (2/15) 0.35 ± 0.33 December 26.28 % (11/41) 23.20 ± 48.47 2020 August 13.63 % (6/44) 3.19 ± 3.84 November 1.40 % (1/71) 16.67 2021 August 34.78 % (16/46) 155.05 ± 523.53 September 11.10 % (1/9) 0.78 December 4.65 % (2/43) 81.88 ± 114.69 2022 August 18 % (9/50) 78.74 ± 151.76 November 30 % (6/20) 54.64 ± 93.24 Total 15.92 % (54/339) 73.58 ± 293.36 Table 2. Estimates from Generalized Linear Models testing the effects of each predictor variable on Batrachochytrium dendrobatidis ( Bd ) prevalence in Melanophryniscus admirabilis . Statistically significant predictor variables are shown in bold. Predictors Estimate Std. Error z P Bd prevalence Intercept 329.046 431.644 0.762 0.446 Year -0.171 0.213 -0.802 0.432 Month 1.404 0.343 4.084 < 0.001 Temperature deviation 1.557 0.341 4.555 < 0.001 Rainfall -0.015 0.003 -4.241 < 0.001 Rainfall deviation -0.030 0.066 -4.735 < 0.001 Additional Declarations No competing interests reported. Supplementary Files SIChytridMadmirabilisBiodiversityandConservation.docx Cite Share Download PDF Status: Posted Version 1 posted 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-4281618","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":292546738,"identity":"c0b94d23-2a99-44db-b3e3-f5b4e3cb416a","order_by":0,"name":"Mariana Retuci Pontes","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA4UlEQVRIiWNgGAWjYHACNijN2PgASPLwEatFAqil2QCkhY2AcmQtDGwSyJbiBLrth589YNxjU2dw/HBb5dccOxk2BuaHj27g0WJ2Js3cgOFZmoTBmcS227LbkoEOYzM2zsGn5UCCmQTDgcMSBjcY225LbmMGauFhk8ar5fzzb0At/8FaiiW31ROh5UYOyJYDYC2MH7cdJkbLmzKJhAPJkjPPJDZLM247zsPGTMgv59O3SXw4YMfPd/z4w48/t1Xb87M3P3yMTwsYJEBpZh4wSUg5MmD8QYrqUTAKRsEoGDEAAJrYRbLpCOblAAAAAElFTkSuQmCC","orcid":"","institution":"State University of Campinas","correspondingAuthor":true,"prefix":"","firstName":"Mariana","middleName":"Retuci","lastName":"Pontes","suffix":""},{"id":292546739,"identity":"2524c678-593e-4db6-a826-402d5ac9b5d0","order_by":1,"name":"Michelle Abadie","email":"","orcid":"","institution":"Instituto Chico Mendes de Conservação da Biodiversidade","correspondingAuthor":false,"prefix":"","firstName":"Michelle","middleName":"","lastName":"Abadie","suffix":""},{"id":292546740,"identity":"c6fc1254-b832-491b-be6b-2ddb902915c2","order_by":2,"name":"Luisa Ribeiro","email":"","orcid":"","institution":"State University of Campinas","correspondingAuthor":false,"prefix":"","firstName":"Luisa","middleName":"","lastName":"Ribeiro","suffix":""},{"id":292546743,"identity":"243eb54d-f441-472f-b6c2-4a63da81afeb","order_by":3,"name":"Guilherme Augusto-Alves","email":"","orcid":"","institution":"State University of Campinas","correspondingAuthor":false,"prefix":"","firstName":"Guilherme","middleName":"","lastName":"Augusto-Alves","suffix":""},{"id":292546745,"identity":"271ed9e3-9ab5-4777-8fee-17e1e2d26325","order_by":4,"name":"Márcio Borges-Martins","email":"","orcid":"","institution":"Federal University of Rio Grande do Sul","correspondingAuthor":false,"prefix":"","firstName":"Márcio","middleName":"","lastName":"Borges-Martins","suffix":""},{"id":292546747,"identity":"c31621fb-f56d-44a5-93b8-ca02a070d15a","order_by":5,"name":"C. Guilherme Becker","email":"","orcid":"","institution":"Pennsylvania State University","correspondingAuthor":false,"prefix":"","firstName":"C.","middleName":"Guilherme","lastName":"Becker","suffix":""},{"id":292546749,"identity":"0c24ecee-e97e-45e1-abfc-5e368c1908a5","order_by":6,"name":"L. Felipe Toledo","email":"","orcid":"","institution":"State University of Campinas","correspondingAuthor":false,"prefix":"","firstName":"L.","middleName":"Felipe","lastName":"Toledo","suffix":""}],"badges":[],"createdAt":"2024-04-17 11:35:54","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-4281618/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4281618/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":55069468,"identity":"8f6322ec-2447-4993-8dc4-3df3ba4d6f59","added_by":"auto","created_at":"2024-04-22 06:00:44","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":42524,"visible":true,"origin":"","legend":"\u003cp\u003eProportion of \u003cem\u003eMelanophryniscus admirabilis\u003c/em\u003e toads infected with \u003cem\u003eBatrachochytrium dendrobatidis \u003c/em\u003e(\u003cem\u003eBd\u003c/em\u003e) and proportion of genomic equivalents of zoospores (GE) by months.\u003c/p\u003e","description":"","filename":"Fig1.png","url":"https://assets-eu.researchsquare.com/files/rs-4281618/v1/455c8108c896ea1121c4ad98.png"},{"id":55069469,"identity":"82c8db2e-42a3-43f4-a848-54249e428c6a","added_by":"auto","created_at":"2024-04-22 06:00:44","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":114776,"visible":true,"origin":"","legend":"\u003cp\u003eVisualization of the Generalized Linear Model (GLM) fit for \u003cem\u003eBatrachochytrium dendrobatidis\u003c/em\u003e (\u003cem\u003eBd\u003c/em\u003e) prevalence. Temperature deviation (ºC) (a), accumulated monthly rainfall (mm) (b) and two-month rainfall deviation (mm) (c).\u003c/p\u003e","description":"","filename":"Fig2.png","url":"https://assets-eu.researchsquare.com/files/rs-4281618/v1/b79800d417fe6fbaa8d3cb67.png"},{"id":55069942,"identity":"de94fc40-a9b8-4a03-bd7f-c36bb42fe219","added_by":"auto","created_at":"2024-04-22 06:08:44","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":140800,"visible":true,"origin":"","legend":"\u003cp\u003eIndividual variation in \u003cem\u003eBatrachochytrium dendrobatidis \u003c/em\u003e(\u003cem\u003eBd\u003c/em\u003e)\u003cem\u003e \u003c/em\u003einfection loads (log genomic equivalents of zoospores, GE) in \u003cem\u003eMelanophryniscus admirabilis\u003c/em\u003e toads\u003cem\u003e \u003c/em\u003e(lines connect the same individual). Values below zero indicate an uninfected sample.\u003c/p\u003e","description":"","filename":"Fig3.png","url":"https://assets-eu.researchsquare.com/files/rs-4281618/v1/9d52da48fd66e21266194152.png"},{"id":58900300,"identity":"32c57688-02ba-4bc5-a706-ca7636caa0c2","added_by":"auto","created_at":"2024-06-23 23:46:30","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":781767,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4281618/v1/b7234941-5a07-4b12-a929-1a6673c77c32.pdf"},{"id":55069471,"identity":"dbc39212-8b4f-4eac-b3da-71eef0c98314","added_by":"auto","created_at":"2024-04-22 06:00:45","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":3227835,"visible":true,"origin":"","legend":"","description":"","filename":"SIChytridMadmirabilisBiodiversityandConservation.docx","url":"https://assets-eu.researchsquare.com/files/rs-4281618/v1/2ac527c8371a04fa10a0b9e8.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Climatic drivers of chytrid prevalence in the critically endangered Admirable Redbelly Toad","fulltext":[{"header":"1. INTRODUCTION","content":"\u003cp\u003eThe modifications resulting from the expansion of human populations have led to an increased frequency and intensity of climatic extremes (Seneviratne et al. 2021). Rainfall and temperature patterns have globally shifted in response to global warming (Seneviratne et al. 2021), and climatic anomalies are projected to increase in frequency and intensity\u0026nbsp;\u003cspan lang=\"EN-US\"\u003e(Sillmann et al. 2013)\u003c/span\u003e. Climatic anomalies can alter entire ecosystems\u0026nbsp;\u003cspan lang=\"EN-US\"\u003e(Frank et al. 2015; Bardgett and Caruso, 2020)\u003c/span\u003e, extending their impact also over wildlife disease dynamics\u0026nbsp;\u003cspan lang=\"EN-US\"\u003e(Cohen et al. 2020; Greenspan et al. 2020; Rohr and Cohen, 2020)\u003c/span\u003e. This intricate interplay occurs through a wide range of mechanisms,\u0026nbsp;encompassing\u0026nbsp;shifts in\u0026nbsp;pathogen development\u0026nbsp;\u003cspan lang=\"EN-US\"\u003e(Nnadi and Carter, 2021)\u003c/span\u003e, and alteration in host behavior and physiological traits\u0026nbsp;\u003cspan lang=\"EN-US\"\u003e(Staudinger et al. 2013; Bozinovic and P\u0026ouml;rtner, 2015)\u003c/span\u003e that often lead to increased susceptibility to diseases\u0026nbsp;\u003cspan lang=\"EN-US\"\u003e(Bradley et al. 2019)\u003c/span\u003e.\u003c/p\u003e\n\u003cp\u003eWildlife disease dynamics are influenced by micro and macro-climatic variables\u0026nbsp;\u003cspan lang=\"EN-US\"\u003e(Harvell et al. 2003; Boser et al. 2021)\u003c/span\u003e, often involving synergistic interactions between pathogens and their hosts\u0026nbsp;\u003cspan lang=\"EN-US\"\u003e(Rohr and Raffel, 2010, Altizer et al. 2013).\u003c/span\u003e The waterborne fungal pathogen \u003cem\u003eBatrachochytrium dendrobatidis\u0026nbsp;\u003c/em\u003e(hereafter \u003cem\u003eBd\u003c/em\u003e) causes the disease chytridiomycosis in amphibians and has been implicated in population declines and extinctions globally\u0026nbsp;\u003cspan lang=\"EN-US\"\u003e(Scheele et al. 2019)\u003c/span\u003e.\u0026nbsp;Moreover, alterations in temperature and rainfall patterns are known to impact the onset of breeding phenology in amphibians (Dalpasso et al. 2023). Amphibian \u003cem\u003eBd\u003c/em\u003e infection could be also influenced by seasonal temperature and rainfall\u0026nbsp;\u003cspan lang=\"EN-US\"\u003epatterns (Ruggeri et al. 2018; Turner et al. 2021)\u003c/span\u003e. Consequently, accelerated climate variability could synergistically drive amphibians to the extinction path, as amphibians are already the most endangered vertebrate taxon according to the recent assessment led by the International Union for Conservation of Nature (IUCN) assessment\u0026nbsp;\u003cspan lang=\"EN-US\"\u003e(IUCN 2023; Luedtke et al. 2023)\u003c/span\u003e. The \u003cem\u003eBd\u003c/em\u003e-amphibian system thus provides an opportunity to investigate the impact of climate anomalies on disease dynamics in formally endangered species, such as the Admirable Redbelly Toad, \u003cem\u003eMelanophryniscus admirabilis\u003c/em\u003e (Bufonidae), from southern Brazil, a region with widespread occurrence of \u003cem\u003eBd\u003c/em\u003e. This microendemic Neotropical species is classified as Critically Endangered (CR) by the IUCN redlist of threatened species\u0026nbsp;\u003cspan lang=\"EN-US\"\u003e(IUCN 2023)\u003c/span\u003e and by the Brazilian redlist (Brasil 2022). This species is included into public conservation policies of Brazil and has become a global success story and symbol of hope for amphibian conservation (Fonte et al. 2022). Additionally,\u0026nbsp;chytridiomycosis outbreaks were classified as the greatest concern among the ten direct threats to the species (Abadie et al. unpublished results), further highlighting the urgency of understanding and addressing the intricate interplay between climate, disease, and the conservation of \u003cem\u003eM. admirabilis\u003c/em\u003e (IUCN 2023).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eMelanophryniscus admirabilis\u003c/em\u003e uses temporary small polls filled by rainfall as vocalization and breeding site\u0026nbsp;\u003cspan lang=\"EN-US\"\u003e(Di-Bernardo et al. 2006)\u003c/span\u003e. Similarly, \u003cem\u003eBd\u003c/em\u003e depends on water for its growth, survival, and dispersion (Berger et al. 2005), although it\u003cem\u003e\u0026nbsp;\u003c/em\u003ecan be transported by other non-amphibian vectors\u0026nbsp;\u003cspan lang=\"EN-US\"\u003e(\u003cem\u003ee.g.\u003c/em\u003e, Pontes et al. 2018; Toledo et al. 2021; Prado et al. 2023)\u003c/span\u003e. Therefore, rainfall and their anomalies could significantly impact both the reproductive biology of \u003cem\u003eM. admirabilis\u003c/em\u003e and pathogen infection dynamic\u0026nbsp;\u003cspan lang=\"EN-US\"\u003e(Ruggeri et al. 2018; Moura-Campos et al. 2021)\u003c/span\u003e. Temperature also plays an important role in successful reproduction\u0026nbsp;of the\u0026nbsp;Admirable Redbelly Toad, since this species depends on the duration of shallow pools, which can quickly evaporate under high temperatures (Abadie et al. unpublished results). Additionally, temperature can also influence \u003cem\u003eBd\u003c/em\u003e lifecycle, and despite \u003cem\u003eBd\u003c/em\u003e exhibiting varying thermal tolerance\u0026nbsp;\u003cspan lang=\"EN-US\"\u003e(Voyles et al. 2017)\u003c/span\u003e, temperature can induce alterations in \u003cem\u003eBd\u003c/em\u003e life history\u0026nbsp;\u003cspan lang=\"EN-US\"\u003e(Woodhams et al. 2008; Muletz-Wolz et al. 2019)\u003c/span\u003e and play a major role in determining the \u003cem\u003eBd\u0026nbsp;\u003c/em\u003einfection loads in hosts\u0026nbsp;\u003cspan lang=\"EN-US\"\u003e(Bielby et al. 2022)\u003c/span\u003e. Amphibians demonstrate increased susceptibility to chytridiomycosis when experiencing anomalies in environmental temperatures\u0026nbsp;\u003cspan lang=\"EN-US\"\u003e(Clare et al. 2016; Cohen et al. 2019a; Serrano et al. 2022)\u003c/span\u003e. Furthermore, the ability of hosts to mount innate immune responses against \u003cem\u003eBd\u003c/em\u003e can be considerably impaired by ambient temperature modification\u0026nbsp;\u003cspan lang=\"EN-US\"\u003e(Grogan et al. 2018).\u003c/span\u003e Hence, seasonal and historical variation in temperature and rainfall are recognized as relevant environmental variables likely influencing \u003cem\u003eBd\u003c/em\u003e infection dynamics in \u003cem\u003eM. admirabilis.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eAlternatively, the environmental context can benefit amphibians in mitigating \u003cem\u003eBd\u003c/em\u003e infections\u0026nbsp;\u003cspan lang=\"EN-US\"\u003e(Karavlan and Venesky, 2016).\u003c/span\u003e For instance, \u003cem\u003eBd\u003c/em\u003e growth is significantly suppressed at temperatures above 25 \u0026deg;C\u0026nbsp;\u003cspan lang=\"EN-US\"\u003e(Piotrowski et al. 2004; Stevenson et al. 2013)\u003c/span\u003e, thus, predicted increases in average global temperatures could suppress pathogen growth in amphibians\u0026rsquo; skin. However, the interaction of \u003cem\u003eBd\u003c/em\u003e infection and warming could lead to an increase in mortality of cool-adapted host species at higher temperatures, despite lower infection loads\u0026nbsp;\u003cspan lang=\"EN-US\"\u003e(Neely et al. 2020)\u003c/span\u003e. This suggests that even when temperatures approach the upper thermal limit of the pathogen, \u003cem\u003eBd\u003c/em\u003e infection may cause declines in cool-adapted montane frogs due to the combined pressures of pathogen infection and warming-related stress\u0026nbsp;\u003cspan lang=\"EN-US\"\u003e(Neely et al. 2020)\u003c/span\u003e. Specifically, \u003cem\u003eBd\u003c/em\u003e infection can lead to host stress\u0026nbsp;\u003cspan lang=\"EN-US\"\u003e(Bielby et al. 2015)\u003c/span\u003e, with downstream impacts on host body condition and fitness\u0026nbsp;\u003cspan lang=\"EN-US\"\u003e(Campbell et al. 2019; Pontes et al. 2021; Bosch et al. 2023)\u003c/span\u003e\u003cem\u003e. Bd\u003c/em\u003e infection has also been linked to population declines in wild amphibians through sublethal effects that reduce host fitness\u0026nbsp;\u003cspan lang=\"EN-US\"\u003e(Chatfield et al. 2013; Valenzuela-S\u0026aacute;nchez et al. 2017; Brannelly et al. 2018; Palomar et al. 2023\u003c/span\u003e), extending beyond immediate consequences to affect long-term population dynamics and persistence\u0026nbsp;\u003cspan lang=\"EN-US\"\u003e(Valenzuela-S\u0026aacute;nchez et al. 2017; Palomar et al. 2023).\u003c/span\u003e Understanding these broader consequences and \u003cem\u003eBd\u003c/em\u003e infection dynamics is vital for effective conservation strategies for the Critically Endangered Admirable Redbelly Toad, particularly in light of its higher vulnerability to extinction due the stochastic events (Fonte et al. 2022).\u003c/p\u003e\n\u003cp\u003eConsidering the pivotal role of climatic variables in predicting amphibian host-pathogen dynamics, we aimed to tested whether the local monthly climatic fluctuations and climatic anomalies\u0026nbsp;would induce changes in \u003cem\u003eBd\u003c/em\u003e dynamics in \u003cem\u003eM. admirabilis\u003c/em\u003e. As this toad depends on temporary pools to breed, we hypothesized that seasonal fluctuations in temperature and rainfall impact the \u003cem\u003eBd\u003c/em\u003e dynamics, and we expect that periods with higher temperatures and low rainfall will result in higher \u003cem\u003eBd\u003c/em\u003e prevalence and infection loads. Additionally, we hypothesized that the \u003cem\u003eM. admirabilis\u0026nbsp;\u003c/em\u003epopulation will experience higher \u003cem\u003eBd\u003c/em\u003e prevalence in periods with rainfall deficit, as the scarcity of pools would lead them to aggregate. Warming can reduce host immune capacity due to heat-induced stress\u0026nbsp;\u003cspan lang=\"EN-US\"\u003e(Cohen et al. 2019b; Neely et al. 2020)\u003c/span\u003e, and may also contribute to the drying up of pools. Consequently, we expect higher \u003cem\u003eBd\u003c/em\u003e prevalence and infection loads in period when temperature exceeds the historical average. Finally, considering sublethal effects caused by \u003cem\u003eBd\u003c/em\u003e infection\u0026nbsp;\u003cspan lang=\"EN-US\"\u003e(Valenzuela-S\u0026aacute;nchez et al. 2017; Palomar et al. 2023; Wu, 2023)\u003c/span\u003e, we expect that \u003cem\u003eBd\u003c/em\u003e infection status has consequences on host body condition. Combined, our goals will allow us to elucidate the disease dynamics of a critically endangered micro-endemic tropical species.\u0026nbsp;\u003c/p\u003e"},{"header":"2.\tMETHODS ","content":"\u003cp\u003e\u003cstrong\u003e2.1 Study site and field sampling\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe only know site for \u003cem\u003eM. admirabilis\u003c/em\u003e is located in municipality of Arvorezinha, State of Rio Grande do Sul, Brazil (52\u0026deg;18\u0026rsquo;\u0026rsquo;W, 28\u0026deg;51\u0026rsquo;S), in the Southern portion of the Atlantic Forest \u003cspan lang=\"EN-US\"\u003e(Di-Bernardo et al. 2006)\u003c/span\u003e. The climate is humid subtropical, and seasons (autumn, winter, spring, and summer) are differentiated by temperature \u003cspan lang=\"EN-US\"\u003e(Zepner et al. 2021)\u003c/span\u003e. We conducted our study along\u0026nbsp;~ 400 m\u0026nbsp;on the Forqueta river\u0026rsquo;s bank, where most individuals of this microendemic species (range size of 1.6 km\u003csup\u003e2\u003c/sup\u003e, IUCN, 2023) concentrate to breed on temporary pools formed on flat rock outcrops. We surveyed the site at least twice a year, from September 2019 to December 2022 (exclusively between September and December), totaling nine field campaigns (Table 1). We captured each toad using new disposable latex gloves and swabbed the skin using MedicalWire MW113 swabs, following standard swabbing protocols (Hyatt et al. 2007). To calculate the body condition of each toad, we measured the snout-vent length (SVL) of each individual using a digital caliper with a precision of 0.01 mm and the body mass using a field scale with precision of 0.1 g. After sampling, we immediately released all toads at the exact point of capture.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWe applied a photo-identification standardized procedure \u003cspan lang=\"EN-US\"\u003e(Bardier et al. 2019; Caorsi et al. 2012)\u003c/span\u003e as a mark-recapture method. The ventral region of each toad was photographed (Figure S1), and we used the Wild-ID open-source software \u003cspan lang=\"EN-US\"\u003e(Bolger et al. 2012)\u003c/span\u003e to identify recaptures. The software compares all images for pairwise similarity and returns the 20 top-ranked potential matches for each focal image; all recaptures were visually confirmed afterwards. This mark-recapture method has been successfully applied to \u003cem\u003eM. admirabilis\u0026nbsp;\u003c/em\u003e(Fonte et al. 2022) and other species of \u003cem\u003eMelanophryniscus\u0026nbsp;\u003c/em\u003e\u003cspan lang=\"EN-US\"\u003e(Caorsi et al. 2012; Bardier et al. 2019)\u003c/span\u003e due to their black, brown, or green background with red, yellow, white, green, or orange spots on their belly (Figure S1).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.2 Pathogen detection and quantification\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo assess a sensitivity performance parameter for \u003cem\u003eBd\u003c/em\u003e diagnostic in our QuantStudio\u0026trade; 6 Real-Time PCR equipment, we performed a series of replicate standard curves, totaling 20 replicates per standard concentration to calculate the limit of detection \u0026ldquo;LoD\u0026rdquo;. LoD is defined as the lowest amount of target DNA sequence that can be detected with 95 % probability. We ran a dilution series of a known amount of total \u003cem\u003eBd\u003c/em\u003e DNA, ranging from 1.83 x 10\u003csup\u003e5\u003c/sup\u003e GE/\u0026micro;L to 10\u003csup\u003e-3\u003c/sup\u003e GE/\u0026micro;L. Each plate included 4 technical replicates of each standard concentration, resulting in a total of 32 standards samples per plate, as well as 4 negative controls consisted of DNA-free water. \u003cem\u003eBd\u003c/em\u003e DNA was extracted from a culture (isolate CLFT 159, global panzootic lineage) using PrepMan ULTRA\u0026reg; (Life Technologies).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFor the qPCR assay, we utilized a final volume of 25 \u0026micro;L, containing 5\u0026nbsp;\u0026mu;L of template DNA, 12.5\u0026nbsp;\u0026mu;L of TaqMan Fast Master Mix (Applied Biosystem), 3.75\u0026nbsp;\u0026mu;L of ddH2O, 1.25\u0026nbsp;\u0026mu;L of forward primer (ITS-1 Chytr CCTTGATATAATACAGTGTGCCATATGTC, 18\u0026nbsp;\u0026mu;M), 1.25\u0026nbsp;\u0026mu;L of reverse primer (5.8S Chytr AGCCAAGAGATCCGTTGTCAAA, 18\u0026nbsp;\u0026mu;M), and 1.25\u0026nbsp;\u0026mu;L of probe (Chytr MGB2 GCAGTCGAACAAAAT, 5\u0026nbsp;\u0026mu;M). We used thermal cycling at 50 \u0026deg;C for 2 minutes and 95 \u0026ordm;C for 20 seconds, followed by 50 cycles at 95 \u0026ordm;C for 1 second and 60 \u0026deg;C for 20 seconds. The outcome of our analysis indicated that the lowest standard concentration with detection rate of 95 % or greater detection was 0.1 copies per reaction (1.83 x 10\u003csup\u003e-1\u003c/sup\u003e GE/\u0026mu;L) (Table S1, Figure S2).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTo determine the presence and infection loads of \u003cem\u003eBd\u0026nbsp;\u003c/em\u003ein each swab sample, we extracted DNA from skin swabs using PrepMan ULTRA\u0026reg; (Life Technologies). To quantify \u003cem\u003eBd\u003c/em\u003e infection loads, we used a Taqman\u0026reg; qPCR Assay (Life Technologies) with standards ranging from 10\u003csup\u003e-1\u003c/sup\u003e to 10\u003csup\u003e3\u003c/sup\u003e genomic equivalents of zoospores, hereafter referred as GE \u003cspan lang=\"EN-US\"\u003e(Boyle et al. 2004; Lambertini et al. 2013).\u003c/span\u003e We considered samples to be \u003cem\u003eBd\u003c/em\u003e-positive (\u003cem\u003eBd\u003c/em\u003e\u003csup\u003e+\u003c/sup\u003e) when the infection loads were \u0026ge; 0.1 GE.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.3 Abiotic data\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe obtained the mean temperature for the 15 days leading up to the sampling from two automated weather station located approximately 23 and 37 km from the study site (\u003cem\u003eInstituto Nacional de Meteorologia do Brasil\u003c/em\u003e). We used 15 d prior to sampling based on the Bd life cycle (i.e. this period is enough to allow at least 1 generation of \u003cem\u003eBd\u003c/em\u003e; Berger et al. 2005). To assess temperature anomaly metrics, we used the TerraClimate dataset \u003cspan lang=\"EN-US\"\u003e(Abatzoglou et al. 2018)\u003c/span\u003e. We calculated the deviation from the historical temperatures by subtracting the historical monthly mean temperature over the past 50 years from the mean temperature of the target periods. These temperature deviations (\u0026ordm;C) were calculated for one, two, and three months preceding our sampling, incorporating one-month lagged deviations. The resulting deviation values could be negative for colder-than-average months, and positive for warmer-than-average months.\u0026nbsp;Additionally, we recorded the accumulated rainfall for each month prior to sampling using data from a neighboring hydrometeorological station located at a similar altitude, 5.5 km from the study site (\u003cem\u003eAg\u0026ecirc;ncia Nacional de \u0026Aacute;guas\u003c/em\u003e). To assess rainfall anomaly metrics, we calculated the deviation from historical rainfall by subtracting the historical monthly mean of accumulated rainfall over the past 50 years from the mean accumulated rainfall of the target periods \u003cspan lang=\"EN-US\"\u003e(Abatzoglou et al. 2018)\u003c/span\u003e. Like our temperature anomaly metrics, we extracted rainfall deviations (mm) for one, two, and three months prior to the sampled month. This analysis provided us with negative values for dryer-than-average months and positive values for wetter-than-average months. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.4 Data analyses and modelling\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFor statistical analysis, we employed two model selection approach. Firstly, to screen for important climatic anomaly metrics explaining \u003cem\u003eBd\u003c/em\u003e prevalence and infections loads, we employed a model selection approach based on Generalized Linear Models (GLM), thus reducing potential multicollinearity bias in downstream pruned models. Based on the Akaike Information Criterion (AIC) (Mazerolle, 2006), the three-month temperature deviation, and two-month rainfall deviation were the best predictor explaining \u003cem\u003eBd\u003c/em\u003e prevalence. Additionally, two-month temperature deviation was the best predictor explaining \u003cem\u003eBd\u003c/em\u003e infection load, while three-month rainfall deviation was the best predictor variable. A detailed description of these models can be found in the supplementary information (Table S2).\u003c/p\u003e\n\u003cp\u003eSecondly, to test for the potential effect of monthly climatic fluctuations and climatic anomalies explaining \u003cem\u003eBd\u003c/em\u003e prevalence and infection loads, we employed a model selection approach based on GLMs. For \u003cem\u003eBd\u003c/em\u003e prevalence, we fit a GLM with binomial distribution and logit link function. We also fit a Gaussian GLM with log link function, with \u003cem\u003eBd\u003c/em\u003e infection loads (log10-transformed GE; only \u003cem\u003eBd\u003c/em\u003e\u003csup\u003e+\u003c/sup\u003e samples) as the response variable. The explanatory variables in the global models were: year, month, mean temperature of the 15 days prior to sampling date, accumulated monthly rainfall from the month prior to sampling date, and climatic anomaly metrics depicting\u0026nbsp;temperature deviation\u0026nbsp;and rainfall deviation.\u0026nbsp;For each GLM, we included year, month (\u003cem\u003eBd\u0026nbsp;\u003c/em\u003eprevalence) and season (warm or cold, \u003cem\u003eBd\u003c/em\u003e infection load model) and as fixed effects.\u0026nbsp;A detailed description of these models can be found in the supplementary information (Table S3).\u0026nbsp;We ran models with all possible combination of explanatory variables, and we ranked the most parsimonious models by employing a backward stepwise procedure based on the Akaike Information Criterion (AIC)\u0026nbsp;\u003cspan lang=\"EN-US\"\u003e(Mazerolle, 2006;\u003c/span\u003e Table S3).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFinally, to investigate any significant differences in body condition between \u003cem\u003eBd\u003c/em\u003e infected and uninfected toads (explanatory categorical variable), we performed a Student\u0026rsquo;s \u003cem\u003et\u003c/em\u003e-test, including data of body condition from adult males sampled until August 2021 (n = 155). We performed a linear regression analysis to test for the potential effect of \u003cem\u003eBd\u003c/em\u003e infection loads on body condition of \u003cem\u003eBd\u003c/em\u003e\u003csup\u003e+\u003c/sup\u003e males (n = 33). The body condition metric utilized the Scaled Mass Index (SMI) approach, based on standardized major axis regression between mass and snout\u0026minus;vent length\u0026nbsp;\u003cspan lang=\"EN-US\"\u003e(Peig and Green, 2009)\u003c/span\u003e.\u0026nbsp;We excluded females from this analysis because the presence of eggs could bias our results. All statistical analyses were performed using R version 2023.3.1 (R Core Team 2022).\u0026nbsp;\u003cbr\u003e\u0026nbsp;\u003c/p\u003e"},{"header":"3.\tRESULTS","content":"\u003cp\u003eWe took 339 skin swab samples from 305 individual toads, and overall \u003cem\u003eBd\u0026nbsp;\u003c/em\u003eprevalence was 15.9 % (54 \u003cem\u003eBd\u003c/em\u003e\u003csup\u003e+\u003c/sup\u003e; n = 339; Table 1 for the prevalence data at each sampling event), and the mean infection loads in \u003cem\u003eBd\u003c/em\u003e\u003csup\u003e+\u003c/sup\u003e toads was 73.58 GE, ranging from 0.1 \u0026ndash; 2,112.45 GE \u0026plusmn; 293.36 SD (Table 1 for infection loads data at each sampling event).\u0026nbsp;\u003cem\u003eBd\u003c/em\u003e prevalence and infection loads were higher in August (Figure 1), with a prevalence of 22.14 % (31\u0026nbsp;\u003cem\u003eBd\u003c/em\u003e\u003csup\u003e+\u003c/sup\u003e; n =\u0026nbsp;140) and a mean \u003cem\u003eBd\u003c/em\u003e infection loads of 103.50 GE\u0026nbsp;\u0026plusmn;\u0026nbsp;383.14 SD.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOur most parsimonious GLM\u0026nbsp;model explaining \u003cem\u003eBd\u003c/em\u003e prevalence in the Admirable Redbelly Toads showed that month (\u003cem\u003ez\u0026nbsp;\u003c/em\u003e= 4.084, \u003cem\u003eP\u0026nbsp;\u003c/em\u003e\u0026lt; 0.01) and increased temperature deviation (\u003cem\u003ez\u003c/em\u003e = 4.555, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001; Figure 2A) predicted higher \u003cem\u003eBd\u003c/em\u003e prevalence. Conversely, rainfall (\u003cem\u003ez\u003c/em\u003e = -4.241,\u003cem\u003e\u0026nbsp;P\u0026nbsp;\u003c/em\u003e\u0026lt; 0.001; Figure 2B) and rainfall deviation (z = -4.735, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001; Figure 2C) negatively affected \u003cem\u003eBd\u003c/em\u003e prevalence during our sampling timeframe (Table 2). Our best-fit model explaining \u003cem\u003eBd\u003c/em\u003e infection loads included month, year, temperature, and temperature deviation (Table S3). However, we did not find statistically significant effect of climatic seasonal and climatic anomaly metrics in \u003cem\u003eBd\u003c/em\u003e infection loads.\u003c/p\u003e\n\u003cp\u003eWe did not observe significant difference in SMI between infected and uninfected toads\u0026nbsp;(\u003cem\u003et-value\u003c/em\u003e = -0.64, \u003cem\u003edf\u003c/em\u003e = 47.114, \u003cem\u003eP\u003c/em\u003e = 0.519).\u0026nbsp;Additionally, we did not find a significant correlation between SMI and infection loads of \u003cem\u003eBd\u003c/em\u003e\u003csup\u003e+\u0026nbsp;\u003c/sup\u003eindividuals (\u003cem\u003eP\u003c/em\u003e = 0.394; Figure S3). A total of 305 toads were captured once, 29 captured twice, five captured three times, and one was captured four times. Regarding \u003cem\u003eBd\u003c/em\u003e infection status over time, a total of seven recaptured toads were found infected at least once. They gained infection seven times, while they cleared\u0026nbsp;\u003cem\u003eBd\u003c/em\u003e infection only three times (Figure 3).\u0026nbsp;\u003cbr\u003e\u0026nbsp;\u003c/p\u003e"},{"header":"4.\tDISCUSSION","content":"\u003cp\u003eOur study revealed that seasonal climatic fluctuations and climatic anomaly metrics are linked with \u003cem\u003eBd\u003c/em\u003e prevalence in \u003cem\u003eM. admirabilis\u003c/em\u003e. Anomalies such as rainfall deficit, combined with temperatures that exceed the historical average, were key in predicting \u003cem\u003eBd\u003c/em\u003e infection risk in this amphibian species. Consequently, our findings suggest that with the projected increase of climatic anomalies over the next decades\u0026nbsp;\u003cspan lang=\"EN-US\"\u003e(Sillmann et al. 2013),\u003c/span\u003e the only known Admirable Redbelly Toad population may face a scenario of increasing \u003cem\u003eBd\u003c/em\u003e pressure.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn agreement with our predictions, the\u0026nbsp;Admirable Redbelly Toads\u0026nbsp;were more likely to have higher \u003cem\u003eBd\u003c/em\u003e prevalence when rainfall in the previous month was low, as well in periods of rainfall deficit. Strikingly, this population also have higher \u003cem\u003eBd\u003c/em\u003e prevalence when the temperatures of the preceding three month exceeded the historical average. This species relies on small temporary pools for reproduction (\u003cspan lang=\"EN-US\"\u003eDi-Bernardo et al. 2006,\u0026nbsp;\u003c/span\u003e\u003cspan lang=\"EN-US\"\u003eBordignon et al. unpublished results\u003c/span\u003e\u003cspan lang=\"EN-US\"\u003e)\u003c/span\u003e that depend on rainfall and evaporation. Hence, dry and warmer periods can rapidly lead to the drying up of shallow pools, directly or indirectly imposing physiological stress and forcing toads to aggregate in the fewer deeper pools that remain available over longer periods of time\u0026nbsp;\u003cspan lang=\"EN-US\"\u003e(Rohr and Palmer, 2013; Moura-Campos et al. 2021)\u003c/span\u003e. These aggregations serve as a significant reservoir of infective \u003cem\u003eBd\u003c/em\u003e zoospores\u0026nbsp;\u003cspan lang=\"EN-US\"\u003e(Longo et al. 2010; Becker et al. 2016)\u003c/span\u003e, increasing the likelihood of \u003cem\u003eBd\u003c/em\u003e transmission when toads interact\u0026nbsp;\u003cspan lang=\"EN-US\"\u003e(Malagon et al. 2020; Moura-Campos et al. 2021).\u003c/span\u003e Additionally, population size and contact rates among toads were also linked with higher \u003cem\u003eBd\u003c/em\u003e prevalence in other \u003cem\u003eMelanophryniscus\u003c/em\u003e species (Pontes et al. 2021). Although not measured in this study, the seasonal demography of \u003cem\u003eM. admirabilis\u003c/em\u003e may also play a role in \u003cem\u003eBd\u003c/em\u003e infections dynamic in the only known population of this species. Thus, our findings suggest that \u003cem\u003eM. admirabilis\u003c/em\u003e may be particularly vulnerable to synergistic interactions between \u003cem\u003eBd\u003c/em\u003e and climatic anomalies, as rainfall deficit and warming not only facilitate the spread of \u003cem\u003eBd,\u0026nbsp;\u003c/em\u003ebut also reduce the availability of pools for reproduction.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eClimatic variables were not correlated with \u003cem\u003eBd\u003c/em\u003e infection loads in \u003cem\u003eM. admirabilis\u003c/em\u003e population, which experiences low \u003cem\u003eBd\u003c/em\u003e infection loads.\u0026nbsp;As \u003cem\u003eBd\u003c/em\u003e infection depends on interaction between the thermal performance of the pathogen and the host (Cohen et al. 2017), even at low infection level, the synergistic effects of warming and \u003cem\u003eBd\u003c/em\u003e could result in host mortality in cool-adapted anurans\u0026nbsp;\u003cspan lang=\"EN-US\"\u003e(Neely et al. 2020)\u003c/span\u003e.\u0026nbsp;This implies that the combined effects of \u003cem\u003eBd\u003c/em\u003e infection and climate change, mainly temperature anomalies, might be underestimated, as \u003cem\u003eBd\u003c/em\u003e affect the amphibian persistence even with low prevalence and infection loads\u0026nbsp;\u003cspan lang=\"EN-US\"\u003e(Valenzuela-S\u0026aacute;nchez et al. 2017; Palomar et al. 2023)\u003c/span\u003e. This highlights the significance of population-level impacts of \u003cem\u003eBd\u003c/em\u003e (Valenzuela-S\u0026aacute;nchez et al. 2017) that may potentially lead to slow and steady long-term declines. Consequently, in light of the projected increase in temperature anomalies\u0026nbsp;\u003cspan lang=\"EN-US\"\u003e(Sillmann et al. 2013)\u003c/span\u003e, future studies on the thermal tolerance of the\u0026nbsp;Admirable Redbelly Toads and its interaction with \u003cem\u003eBd\u003c/em\u003e infection become essential for a comprehensive understanding of the consequences of accelerated climate change on this species.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eContrary to our predictions, our findings suggest that\u0026nbsp;body condition was not linked with \u003cem\u003eBd\u003c/em\u003e. Evidence of sublethal effects of \u003cem\u003eBd\u0026nbsp;\u003c/em\u003eon body condition are rarely observed in wild populations that do not experience chytridiomycosis-related mortality. However, it is worth noting that even at low infection levels, \u003cem\u003eBd\u003c/em\u003e could lead to impaired skin physiology (\u003cem\u003ei.e.,\u003c/em\u003e skin integrity, osmoregulation, and hormone production)\u0026nbsp;\u003cspan lang=\"EN-US\"\u003e(Wu, 2023)\u003c/span\u003e. Additionally, \u003cem\u003eBd\u003c/em\u003e is known to dramatically alter the amphibian skin microbiome\u0026nbsp;\u003cspan lang=\"EN-US\"\u003e(Becker et al. 2017; Becker et al. 2019)\u003c/span\u003e and it is known that the presence of the bacteria \u003cem\u003eSerratia marcensis\u0026nbsp;\u003c/em\u003ecould also be playing an important structural role in skin microbiome health in our focal amphibian species\u0026nbsp;\u003cspan lang=\"EN-US\"\u003e(Ienes-Lima et al. 2023a, 2023b; Woodhams et al. 2023)\u003c/span\u003e. Furthermore, the capture-mark-recapture analysis showed that although the\u0026nbsp;Admirable Redbelly Toads\u0026nbsp;demonstrated the ability to clear \u003cem\u003eBd\u003c/em\u003e infection, they still gained more infection than managed to clear over time. The\u0026nbsp;probability of becoming \u003cem\u003eBd\u003csup\u003e+\u003c/sup\u003e\u0026nbsp;\u003c/em\u003ehigher than the probability of clearance is a characteristic of population on a path of slow decline\u0026nbsp;\u003cspan lang=\"EN-US\"\u003e(Palomar et al. 2023)\u003c/span\u003e. Therefore, tracking individual \u003cem\u003eBd\u003c/em\u003e infection status over time is crucial for future assessments of the population heath.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eMelanophryniscus\u0026nbsp;\u003c/em\u003especies could be affected by climate change in different ways, including the reduction of suitable habitat\u0026nbsp;\u003cspan lang=\"EN-US\"\u003e(Zank et al. 2014)\u003c/span\u003e. This study represents the first\u0026nbsp;long-term investigation of \u003cem\u003eBd\u003c/em\u003e prevalence and infection loads and its climatic drivers in the\u0026nbsp;Admirable Redbelly Toad sole\u0026nbsp;population. With trends in global warming, higher disease risk is expected in cool-adapted organisms\u0026nbsp;\u003cspan lang=\"EN-US\"\u003e(Rohr and Cohen, 2020)\u003c/span\u003e, as the case of various \u003cem\u003eMelanophryniscus\u0026nbsp;\u003c/em\u003epopulations.\u0026nbsp;Therefore, studies that investigate the interactive effects of disease and climate change must be conducted to safeguard endangered amphibian species, as interactions between warming and infection could still lead to population declines\u0026nbsp;\u003cspan lang=\"EN-US\"\u003e(Neely et al. 2020)\u003c/span\u003e. While chytridiomycosis may not pose an immediate threat to the microendemic\u0026nbsp;Admirable Redbelly Toads, common stressors such as herbicides (Da-Silva et al. 2023) and anthropic impact (Ienes-Lima et al. 2023a) could amplify the fitness impacts of climate change\u0026nbsp;\u003cspan lang=\"EN-US\"\u003e(Greenspan et al. 2017; Rohr and Palmer, 2013)\u003c/span\u003e. We strongly advocate for the continuation of research with \u003cem\u003eBd\u003c/em\u003e and its interaction with other prevalent pathogens in the southern Brazil, such as \u003cem\u003eRanavirus\u003c/em\u003e \u003cspan lang=\"EN-US\"\u003e(Ruggeri et al. 2023)\u003c/span\u003e,\u0026nbsp;on \u003cem\u003eM. admirabilis\u0026nbsp;\u003c/em\u003esole population. Surveying both pathogens mainly in dryer periods is especially crucial for its conservation, considering their vulnerability to declines resulting from stochastic events.\u0026nbsp;\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank Debora W. Bordignon, Patrick Colombo, Maria Eduarda B. Cunha, Gabriel Schubert R. Costa, Nat\u0026aacute;lia D. Vargas, Isis S. Homrich, Bibiana T. Dasoler, Tiago Quaggio and Lu\u0026iacute;s Fernando M. Fonte for assistance with logistics and fieldwork. We thank Graziela Civa and Neusa Civa for their support in Arvorezinha. M.R.P. thanks Idea Wild for providing several pieces of field equipment. We also thank Gabriel Schubert R. Costa for technical assistance throughout in data compilation.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by São Paulo Research Foundation (FAPESP 2020/00099-0, 2018/23622-0, 2019/03170-0, 2016/25358-3, 2022/11096-8); the Coordena\u0026ccedil;\u0026atilde;o de Aperfei\u0026ccedil;oamento de Pessoal de N\u0026iacute;vel Superior \u0026ndash; Brasil (CAPES - Finance Code 001); the National Council for Scientific and Technological Development (CNPq 300896/2016-6, 302834/2020-6); the Funda\u0026ccedil;\u0026atilde;o Grupo Botic\u0026aacute;rio, Brazil (1062_20161); the Rufford Foundation (22286-1), and the National Centre for Research and Conservation of Reptiles and Amphibians of the Chico Mendes Institute for Biodiversity Conservation -RAN/ICMBio, Brazil. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll applicable institutional and national guidelines for the care and use of animals were\u003c/p\u003e\n\u003cp\u003efollowed. This work was conducted under permits by Instituto Chico Mendes de Conserva\u0026ccedil;\u0026atilde;o da Biodiversidade (SISBio #72718), Sistema Nacional de Gest\u0026atilde;o do Patrim\u0026ocirc;nio Gen\u0026eacute;tico e do Conhecimento Tradicional Associado (SisGen #A3D44D1). This work was approved by Unicamp Animal Care and Ethics Committee (CEUA #5581-1/2020).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eThe authors have no relevant financial or non-financial interests to disclose.\u003c/em\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eM.R.P. and L.F.T. designed the study. M.R.P, M.A., G.A.A. and M.B.M. carried out the fieldwork. M.R.P and L.P.R. carried out the molecular analysis. M.R.P and G.C.B analyzed the data. MRP drafted the manuscript. All authors critically revised the manuscript and approved the final manuscript. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data that support the findings of this study openly available in the Dryad Digital Repository: https://doi.org/10.5061/dryad.0zpc86754\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eAbatzoglou J, Dobrowski S, Parks S, Hegewisch KC (2018) TerraClimate, a high-resolution global dataset of monthly climate and climatic water balance from 1958\u0026ndash;2015. Sci Data 5:170191. https://doi.org/10.1038/sdata.2017.19\u003c/li\u003e\n \u003cli\u003eAg\u0026ecirc;ncia Nacional das \u0026Aacute;guas (ANA) (2023) https://www.gov.br/ana/pt-br (accessed 25 January 2023).\u003c/li\u003e\n \u003cli\u003eAltizer S, Ostfeld RS, Johnson PTJ, Kutz S, Harvell D (2013) Climate change and infectious diseases: from evidence to a predictive framework.\u003cem\u003e\u0026nbsp;\u003c/em\u003eScience 341:514\u0026ndash;519. https://doi.org/10.1126/science.1239401\u003c/li\u003e\n \u003cli\u003eBardgett RD, Caruso T (2020) Soil microbial community responses to climate extremes: Resistance, resilience and transitions to alternative states. 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Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, pp 1513\u0026ndash;1766. https://10.1017/9781009157896.013\u003c/li\u003e\n \u003cli\u003eSerrano JA, Toledo LF, Sales LP (2022) Human impact modulates chytrid fungus occurrence in amphibians in the Brazilian Atlantic Forest. Perspect Ecol Conserv 20:256\u0026ndash;262. https://doi.org/10.1016/j.pecon.2022.05.002\u003c/li\u003e\n \u003cli\u003eSillmann J, Kharin VV, Zhang X, Zwiers FW, Bronaugh D (2013) Climate extremes indices in the CMIP5 multimodel ensemble: Part 1. Model evaluation in the present climate. J of Geophys Res Atmos 118:1716\u0026ndash;1733. https://doi.org/10.1002/jgrd.50203\u003c/li\u003e\n \u003cli\u003eStaudinger MD, Carter SL, Cross MS, Dubois NS, Duffy JE, Enquist C, Griffis R, Hellmann JJ, Lawler JJ, O\u0026rsquo;Leary J, Morrison SA, Sneddon L, Stein BA, Thompson LM, Turner W (2013) Biodiversity in a changing climate: A synthesis of current and projected trends in the US. Front Ecol Environ 11:465\u0026ndash;473. https://doi.org/10.1890/120272\u003c/li\u003e\n \u003cli\u003eStevenson LA, Alford RA, Bell SC, Roznik EA, Berger L, Pike DA (2013) Variation in thermal performance of a widespread pathogen, the amphibian chytrid fungus \u003cem\u003eBatrachochytrium dendrobatidis\u003c/em\u003e. PLoS One 8:e73830. https://doi.org/10.1371/journal.pone.0073830\u003c/li\u003e\n \u003cli\u003eToledo LF, Ruggeri J, Ferraz de Campos LL, Martins M, Neckel-Oliveira S, Breviglieri CPB (2021) Midges not only sucks, but may carry lethal pathogens to wild amphibians. Biotropica 53:722\u0026ndash;725. https://doi.org/10.1111/btp.12928\u003c/li\u003e\n \u003cli\u003eTurner A, Wassens S, Heard G, Peters A (2021) Temperature as a driver of the pathogenicity and virulence of amphibian chytrid fungus \u003cem\u003eBatrachochytrium dendrobatidis\u003c/em\u003e: A systematic review. J Wildl Dis 57:477\u0026ndash;494. https://doi.org/10.7589/JWD-D-20-00105\u003c/li\u003e\n \u003cli\u003eValenzuela-S\u0026aacute;nchez A, Schmidt BR, Uribe-Rivera DE, Costas F, Cunningham AA, Soto-Azat C (2017) Cryptic disease-induced mortality may cause host extinction in an apparently stable host-parasite system. Proc R Soc B 284:20171176.\u0026nbsp;https://doi.org/10.1098/rspb.2017.1176\u003c/li\u003e\n \u003cli\u003eVoyles J, Johnson LR, Rohr J, Kelly R, Barron C, Miller D, Minster J, Rosenblum EB (2017) Diversity in growth patterns among strains of the lethal fungal pathogen \u003cem\u003eBatrachochytrium dendrobatidis\u003c/em\u003e across extended thermal optima. Oecologia 184:363\u0026ndash;373. https://doi.org/10.1007/s00442-017-3866-8\u003c/li\u003e\n \u003cli\u003eWoodhams DC, Alford RA, Briggs CJ, Johnson M, Rollins-Smith LA (2008) Life-history trade-offs influence disease in changing climates: Strategies of an amphibian pathogen. Ecology 89:1627\u0026ndash;1639. https://doi.org/10.1890/06-1842.1\u003c/li\u003e\n \u003cli\u003eWoodhams DC, McCartney J, Walke JB, Whetstone R (2023) The adaptive microbiome hypothesis and immune interactions in amphibian mucus. Dev Comp Immunol 145:104690.\u0026nbsp;https://doi.org/10.1016/j.dci.2023.104690\u003c/li\u003e\n \u003cli\u003eWu NC (2023) Pathogen load predicts host functional disruption: A meta-analysis of an amphibian fungal panzootic. Funct Eco 37:900\u0026ndash;914. https://doi.org/10.1111/1365-2435.14245\u003c/li\u003e\n \u003cli\u003eZank C, Becker FG, Abadie M, Baldo D, Maneyro R, Borges-Martins M (2014) Climate change and the distribution of neotropical red-bellied toads (\u003cem\u003eMelanophryniscus\u003c/em\u003e, Anura, Amphibia): How to prioritize species and populations? PLoS One 9:e94625. https://doi.org/10.1371/journal.pone.0094625\u003c/li\u003e\n \u003cli\u003eZepner L, Karrasch P, Wiemann F, Bernard L (2021) ClimateCharts.net\u0026ndash;an interactive climate analysis web platform. Int J Digit Earth 14:338\u0026ndash;356. https://doi.org/10.1080/17538947.2020.1829112\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1.\u003c/strong\u003e Variation of \u003cem\u003eBatrachochytrium dendrobatidis\u0026nbsp;\u003c/em\u003e(\u003cem\u003eBd\u003c/em\u003e)\u0026nbsp;prevalence and infection loads in \u003cem\u003eMelanophryniscus admirabilis\u0026nbsp;\u003c/em\u003ebetween 2019 and 2022. \u003cem\u003eBd\u003c/em\u003e prevalence is the proportion of infected toads out of the total number of toads sampled. \u003cem\u003eBd\u0026nbsp;\u003c/em\u003einfection load is represented by the mean and standard deviation (SD) of zoospore genomic equivalents (GE) by year and month (only \u003cem\u003eBd\u003c/em\u003e\u003csup\u003e+\u003c/sup\u003e toads). Total refers to the general \u003cem\u003eBd\u0026nbsp;\u003c/em\u003eprevalence and mean of infection load and SD.\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eYear\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMonth\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eBd\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;prevalence (\u003cem\u003eBd\u003c/em\u003e\u003csup\u003e+\u003c/sup\u003e / n)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMean\u003cem\u003e\u0026nbsp;Bd\u003c/em\u003e infection load\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003e2019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSeptember\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e13.33 % (2/15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.35\u0026nbsp;\u0026plusmn;\u0026nbsp;0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eDecember\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e26.28 % (11/41)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e23.20\u0026nbsp;\u0026plusmn;\u0026nbsp;48.47\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003e2020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAugust\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e13.63 % (6/44)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3.19\u0026nbsp;\u0026plusmn; 3.84\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNovember\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.40 % (1/71)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e16.67\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\"\u003e\n \u003cp\u003e2021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAugust\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e34.78 % (16/46)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e155.05\u0026nbsp;\u0026plusmn;\u0026nbsp;523.53\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSeptember\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e11.10 % (1/9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.78\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eDecember\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.65 % (2/43)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e81.88\u0026nbsp;\u0026plusmn;\u0026nbsp;114.69\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\"\u003e\n \u003cp\u003e2022\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAugust\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e18 % (9/50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e78.74\u0026nbsp;\u0026plusmn;\u0026nbsp;151.76\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNovember\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e30 % (6/20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e54.64\u0026nbsp;\u0026plusmn;\u0026nbsp;93.24\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e15.92 % (54/339)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e73.58 \u0026plusmn; 293.36\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003e\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2.\u003c/strong\u003e Estimates from Generalized Linear Models testing the effects of each predictor variable on \u003cem\u003eBatrachochytrium dendrobatidis\u0026nbsp;\u003c/em\u003e(\u003cem\u003eBd\u003c/em\u003e) prevalence in \u003cem\u003eMelanophryniscus admirabilis\u003c/em\u003e. Statistically significant predictor variables are shown in bold.\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePredictors\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eEstimate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eStd. Error\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003ez\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003eBd\u003c/em\u003e prevalence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eIntercept\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e329.046\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e431.644\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.762\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.446\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eYear\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-0.171\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.213\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-0.802\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.432\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMonth\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.404\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.343\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.084\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt; 0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTemperature deviation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.557\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.341\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.555\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt; 0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eRainfall\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-0.015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-4.241\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt; 0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eRainfall deviation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-0.030\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.066\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e-4.735\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt; 0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Atlantic Forest, Batrachochytrium dendrobatidis, Brazil, Climate change, Conservation, Melanophryniscus admirabilis","lastPublishedDoi":"10.21203/rs.3.rs-4281618/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4281618/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Global warming is driving shifts in rainfall and temperature patterns, and projections indicate an increase in frequency and intensity of climate anomalies. These changes influence wildlife disease dynamics, affecting pathogen development, host behavior, physiology, and disease susceptibility. Understanding the intricate interplay between climatic anomalies and emerging pathogens in amphibian is essential to inform conservation efforts targeted towards this highly threatened vertebrate group. In-situ research is recommended as a conservation action by the International Union for Conservation of Nature (IUCN 2023) for the microendemic and Critically Endangered amphibian Melanophryniscus admirabilis (Admirable Redbelly Toad). We therefore investigated the seasonal climatic fluctuations and climatic anomalies affecting infections by the waterborne chytrid Batrachochytrium dendrobatidis (Bd) in this sole surviving population, which holds significant conservation concern. We found links between high Bd prevalence, monthly low rainfall and rainfall deficit. Additionally, an increase in Bd prevalence was associated with temperatures exceeding historical averages. These findings suggests that climatic anomalies play a crucial role in Bd transmission and infection status among toads, probably due their aggregation behavior in few available pools during drier and warmer periods. Despite the current low prevalence of Bd and infection loads, the projected escalation of climatic anomalies might render M. admirabilis uniquely susceptible to synergistic interactions between Bd and extreme climatic conditions. The insights gained from this study can improve the conservation efforts and underscore the intricate relationship between climatic anomalies and chytrid infection, shedding light on potential vulnerabilities within threatened amphibian populations.","manuscriptTitle":"Climatic drivers of chytrid prevalence in the critically endangered Admirable Redbelly Toad","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-04-22 06:00:40","doi":"10.21203/rs.3.rs-4281618/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"ff46df33-5819-4734-a0cd-371f6b95a786","owner":[],"postedDate":"April 22nd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-06-23T23:38:23+00:00","versionOfRecord":[],"versionCreatedAt":"2024-04-22 06:00:40","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4281618","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4281618","identity":"rs-4281618","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}