BUSCADOR RECOLECTA

[Methods] Author contributions: Monasterio, Beukema and Gómes lead field (lizard sampling) and lab (estimation of thermal limits and measurement of body weights) work, and Monasterio and Araújo designed experiments. Herrando-Pérez conceived the idea of the two research manuscripts (Functional Ecology, Journal of Animal Ecology) and submitted the data to Dryad. Funding: MBA partly funded through CGL2011-26852 project of the Spanish Ministry of Economy and Competitiveness. Field and experimental work funded by IC&DT 1/SAESCTN/ALENT-07-0224-FEDER-001755 project led by MBA. Acknowledgements: We thank the Biological Station of “El Ventorrillo” for hosting the field team and for providing the thermal experimental facilities essential for this research. We also thank Tim Leerschool, Filipe Serrano and Matthijs Hollanders for their support in the field. Collection permits: Samples, experiments and use of experimental animals supported for Portuguese populations by permits 360 to 362/2014/CAPT and 550 to 552/2014/CAPT (Instituto da Conservação da Natureza e das Florestas), and for Spanish populations by permits (autonomous communities in parenthesis hereafter) SGYB/EF/FJRH Re-9H/13 & SGYB/AF/DBP Re-79y131/14 (Andalucía), 2014-500201724/2014/02343 & INAGA/5000201/24/2013/04434 (Aragón), DGMEN/SEN/avp_13_025_aut & DGMEN/SEN/avp_14_020_aut (Castilla La Mancha), P/CYL/101/2013 & EP/CYL/106/2014 (Castilla y León), CN0023/14/ACA1587(14) (Extremadura), 2566/RX131316//clave031/2013 & 2241/RX123724//clave018/2014 (Galicia), and 10/033298.9/13 & 10/013907.9/14 (Madrid). [Usage Notes] Content of dataset: Critical Thermal Maxima (CTmax) and Critical Thermal Minima (CTmax) and body weights of 304 male individuals belonging to 59 populations and 15 species of Iberian lizards (Dryad doi: 10.5061/dryad.1553pc3). Body weight, CTmax and CTmin available for all populations except the Moncayo/Soria/Spain population of Podarcis muralis for which CTmin was not measured. Dataset set used in two research manuscripts: Intraspecific variation in lizard heat tolerance alters estimates of climate impact / Journal of Animal Ecology (doi: 10.1111/1365-2656.12914) and Heat tolerance is more variable than cold tolerance across species of Iberian lizards after controlling for intraspecific variation / Functional Ecology (in press). Versions of dataset: the first version of the dataset contained CTmax data alone (Journal of Animal Ecology), species names, population codes, locality names (with region, country, lat/long), the second version of the dataset (Functional Ecology) contains the latter information along with CTmin and body-weight data while the locality names and lat/long have been refined., The widespread observation that heat tolerance is less variable than cold tolerance (‘cold-tolerance asymmetry’) leads to the prediction that species exposed to temperatures near their thermal maxima should have reduced evolutionary potential for adapting to climate warming. However, the prediction is largely supported by species-level global studies based on single estimates of both physiological metrics per taxon. We ask if cold-tolerance asymmetry holds for Iberian lizards after accounting for intraspecific variation in critical thermal maxima (CTmax) and minima (CTmin). To do so, we quantified CTmax and CTmin for 58 populations of 15 Iberian lizard species (299 individuals). Then, we randomly selected one population from each study species (population sample = 15 CTmax and CTmin values), tested for variance homoscedasticity across species, and repeated the test for thousands of population samples as if we had undertaken the same study thousands of times, each time sampling one different population per species. The ratio of variances in CTmax to CTmin across species varied up to 16-fold depending on the populations chosen. Variance ratios show how much CTmax departs from the cross-species mean compared to CTmin, with a unitary ratio indicating equal variance of both thermal limits. Sampling one population per species was six times more likely to result in the observation of greater CTmax variance (‘heat-tolerance asymmetry’) than cold-tolerance asymmetry. The null hypothesis of equal variance was twice as likely for cases of cold-tolerance asymmetry than for the opposite scenario. Range-wide, population-level studies that quantify heat and cold tolerance of individual species are urgently needed to ascertain the global prevalence of cold-tolerance asymmetry. While broad latitudinal clines of cold tolerance have been strongly supported, heat tolerance might respond to smaller-scale climatic and habitat factors hence go unnoticed in global studies. Studies investigating physiological responses to climate change should incorporate the extent to which thermal traits are characteristic of individuals, populations and/or species., British Ecological Society, Award: 4496-5470. European Union, Award: IC&DT 1/SAESCTN/ALENT-07-0224-FEDER-001755. Spanish Ministry of Economy and Competitiveness, Award: CGL2011-26852., Peer reviewed

[Methods] Data obtained from an acoustic telemetry experiment. The acoustic detection sequence was imported to R software to apply a Hidden Markov Model to separate the active and rest states and obtain the circadian-related traits., This dataset contains the necessary data to replicate the work entitled 'Circadian-related behavioural types in free-living marine fish revealed by high-throughput telemetry'. The data were obtained through a high-resolution acoustic telemetry experiment tracking a population of pearly razorfish between April and September 2019. The time series of detections were imported into the R computing environment. We discretized the detections generated by the individuals into bins of 5 minutes (time-steps). We fitted a Hidden Markov Model (HMM) to probabilistically assign two behavioural states to each temporal bin: rest (R) or active (A). We used a zero-inflated Poisson HMM implemented in the ziphsmm package. During these months, two different periods in the reproduction of this species were included: the pre-spawning period and the spawning period. For this purpose, the data were separated into two different datasets: the pre-spawning period dataset, which contains all individuals tracked for at least seven days between April 30 and May 31, and the spawning period dataset, which includes all individuals tracked for at least seven days between June 15 and July 31. The data between June 1 and June 15 were discarded due to maintenance tasks on the acoustic receivers. The data from August and September were discarded due to low data yields. Finally, a third dataset was created, which includes individuals tracked for at least seven days in each period. The three datasets are configured in the same manner, with ID as the identifier for each individual, Day as the tracking date, Dayn as the day of the trial, Awakening Time as the activity onset time in minutes relative to sunrise, Rest Onset as the rest onset time in minutes relative to sunset, RelActivityDuration as the active hours (calculated as the difference between the awakening time and rest onset) relative to daylight hours (calculated as the difference between sunrise and sunset), RelRestDuration as the resting hours (calculated as the difference between the rest onset time and awakening time of the next day) relative to night hours (calculated as the difference between sunset and sunrise of the next day), RelRestMidpoint as the midpoint of the rest relative to the middle of the night, Sex, Size (cm), Period, CHL as the concentration of chlorophyll (Relative Fluorescence Units, RFU), CurrentDirection as the direction in degrees of the surface current, CurrentSpeed as the speed in m/s of the surface current, Light as the daily mean light (lux), O2 as the concentration of dissolved oxygen in water (mV), Salinity (PSU), Temperature as the daily mean temperature (ºC), WavesHeight as the daily mean wave height (m), and WindSpeed as the speed in m/s of the wind., The research was carried out within the framework of the activities of the Spanish Government through the "Maria de Maeztu Centre of Excellence" accreditation to IMEDEA (CSIC-UIB) (CEX2021-001198). The CLOCKS I+D+I project funded this work (grant no. PID2019-104940GA-I00) funded by MCIN/AEI/10.13039/501100011033 and the FSE invierte en tu futuro. The telemetry system was financed by the German Federal Ministry of Education and Research (Grant No. #033W024A)., With funding from the Spanish government through the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2021-001198)., Pre-Spawning_Dataset, Spawning_Dataset, BothPeriods_Dataset., Peer reviewed

[Description of methods used for collection/generation of data] The data derived from the laboratory were obtained through various standardised tests, and recorded to gather behavioural data. For exploration and activity, positional data were acquired via a deep-learning object detection algorithm /YOLOv5). In the case of boldness and aggression, data were obtained by subsequently reviewing the videos. Regarding chronotypes, data were obtained from an acoustic telemetry experiment, but here we present only the scores obtained in a previous study., This dataset encompasses all necessary data required to replicate the study, `Chronotypes-Personality behavioural syndromes in wild fish’. The data were obtained through standardised behavioural tests conducted under laboratory conditions on 63 Pearly Razorfish (Xyrichtys novacula) individuals between April and July of 2019. Over a week, the fish were maintained in isolated aquariums to test their behaviours, including exploration, activity, boldness, and aggression, conducted daily. A Raspberry Pi system, equipped with the YOLOv5 deep-learning automatic tracking algorithm, was used to record these tests and calculate the fish's minute-by-minute position, providing essential data for evaluating exploration and activity. This system also stored videos to retrospectively obtain boldness and aggression data. Each test included only those individuals with at least two measurements. After the laboratory period, the fish were tagged with acoustic tags and returned to the sea to measure their chronotypes; only individuals with at least seven consecutive days of data were considered. The chronotype data, obtained from a previous study, are represented here through the previously derived scores. These laboratory-based experimental data were analysed using R software. In the exploration context, positional data were translated into total active time (TimeOut), minimum distance to the toy (MinDistance), and time spent near the toy (TimeToy). For activity, the data were converted into total active time (TimeOut), total distance covered (Distance), areas (CoreArea and Area), and direction angles (MeanAngle and KappaAngle). A Principal Component Analysis (PCA) was conducted to obtain the scores for exploration, activity, and aggressiveness. Upon acquiring these scores, trait repeatability was computed using a Linear Mixed-Effects Model, fitting the experimental day (Day), the total length of the individual (Size), and the internal condition (Condition) as fixed factors, and the individual (ID) and the experimental week (Week) as random factors. The chronotype scores (Awakening Time and Rest Onset) were subsequently included in each dataset and refitted into the Linear Mixed-Effects Model, including chronotypes as fixed factors. Lastly, a Multivariate Generalised Linear Mixed Model was fit to each pair of laboratory-based traits to derive their correlations., The research was carried out within the framework of the activities of the Spanish Government through the "Maria de Maeztu Centre of Excellence" accreditation to IMEDEA (CSIC-UIB) (CEX2021-001198). The CLOCKS I+D+I project funded this work (grant no. PID2019-104940GA-I00) funded by MCIN/AEI/10.13039/501100011033 and the FSE invierte en tu futuro. The telemetry system was financed by the German Federal Ministry of Education and Research (Grant No. #033W024A). This work is a contribution of the Joint Researcher Unit IMEDEA-LIMIA., With funding from the Spanish government through the "Severo Ochoa Centre of Excellence" accreditation (CEX2021-001198)., Peer reviewed

Mantellid frogs present an extensive adaptive radiation endemic to Madagascar and Comoros, being the subfamily Mantellinae the most morphologically and ecologically diverse. The Mantellinae present key innovative evolutionary traits linked to their unique reproductive behavior, including the presence of femoral glands and a derived vomeronasal organ. In addition, previous studies pointed to size differentiation in playing an important role in species’ dispersal capacities and shaping of their geographic ranges. Despite the high phenotypic variation observed in this clade, to date an exhaustive morphological analysis of their anatomy has still not been performed, much less in relation to internal structures. Here, we present a comprehensive skeletal description of a mantellid species, Blommersia transmarina, from the island of Mayotte in the Indian Ocean, which has potentially undergone a process of moderate gigantism compared to other Blommersia species. We describe its intraspecific skeletal variation utilizing non-destructive volume renderings from μCT-scans, and characterize the presence of sexual dimorphism and size covariation in skeletal structures. Notably, we found numerous signs of hyperossification, a novel structure for mantellids: the clavicular process, and the presence of several appendicular sesamoids. Our findings suggest that skeletal phenotypic variation in this genus may be linked to biomechanical function for reproduction and locomotion., Peer reviewed

Peer reviewed

BiodivERsA2012-74 FP7, Peer reviewed