Better in the dark: two Mediterranean amphibians synchronize reproduction with moonlit nights

In Amphibians, both positive and negative correlations between activity and full moon phase have been observed. In this study, we present data for two anuran species (<i>Hyla intermedia</i> and <i>Rana dalmatina</i>) studied in a hilly Mediterranean area of central Italy. We analysed, in a two-year survey, the relationships between the number of egg clutches laid each night and the moon phases by means of circular statistics. Moreover, the studied species exhibited clear oviposition site selection behaviour influenced, at least in <i>H. intermedia</i>, by moon phases. We observed the occurrence of an avoidance effect by amphibians for oviposition and specific egg-laying behaviour during moon phases around the full moon. This apparent lunar phobia was evident in both species when yearly data were pooled. On the other hand, while this pattern continued to be also evident in <i>H. intermedia</i> when single years were considered, in <i>R. dalmatina</i> it stood just in one year of study. Nonetheless, during cloudy nights, when moonlight arriving on the ground was low, the frogs' behaviour was similar to that observed in new moon phases. We interpreted the observed pattern as an anti-predatory strategy. Overall, comparisons between our own study and previous research suggest that there was insufficient evidence to establish any unequivocal patterns and that further research in this regard is needed

Focusing inversion technique applied to radar tomographic data

Traveltime tomography is a very effective tool to reconstruct acoustic, seismic or electromagnetic wave speed distribution. To infer the velocity image of the medium from the measurements of first arrivals is a typical example of ill-posed problem. In the framework of Tikhonov regularization theory, in order to replace an ill-posed problem by a well-posed one and to get a unique and stable solution, a stabilizing functional (stabilizer) has to be introduced. The stabilizer selects the desired solution from a class of solutions with a specific physical and/or geometrical property; e.g., the existence of sharp boundaries separating media with different petrophysical parameters. Usually stabilizers based on maximum smoothness criteria are used during the inversion process; in these cases the solutions provide smooth images which, in many situations, do not describe the examined objects properly. Recently a new algorithm of direct minimization of the Tikhonov parametric functional with minimum support stabilizer has been introduced; it produces clear and focused images of targets with sharp boundaries. In this research we apply this new technique to real radar tomographic data and we compare the obtained result with the solution generated by the more traditional minimum norm stabilizer.Comment: 4 pages, 1 figur

Spread-ing Uncertainty, Shrinking Birth Rates: A Natural Experiment for Italy

Many previous studies have documented the procyclicality of fertility to business cycles or labour market indicators in Western countries. However, part of the recent fertility decline witnessed since the Great Recession has been left unexplained by traditional measures. The present study advances the notion that birth postponement might have accelerated in response to rising uncertainty, which fuelled negative expectations and declining levels of confidence about the future. To provide empirical support for the causal effect of perceived uncertainty on birth rates, we focus on Italy’s sovereign debt crisis of 2011–2012 as a natural experiment. Perceived uncertainty is measured using Google trends for the term ‘spread’—which acted as somewhat of a barometer for the crisis both in the media and everyday conversations—to capture the general public’s degree of concern about the stability of Italian public finances. A regression discontinuity in time identifies the effect of perceived uncertainty on birth rates in Italy as a drop between 1.5% and 5%, depending on model specification

“Heaven” of Data Deficient Species: The Conservation Status of the Endemic Amphibian Fauna of Vietnam

Predicting the true status of Data Deficient (DD) species is a prominent theme in recent conservation biology, but there still is much debate regarding the conservation approach that should be used for DD taxa and no definitive conclusions are yet available. We review and analyse the current data available on the conservation status of amphibians in Vietnam, with an emphasis on the DD species. We also compare Vietnamese DD frequency of occurrence with other regions of the world, examine the extent of the range of taxa divided by Red List status, and explore the protection attributes of the taxa based on their inclusion within protected areas of Vietnam. We documented that the analysis of amphibians in Southeast Asia, and especially in Vietnam, substantially agrees with patterns highlighted by previous global research, and confirms the risk that several DD species may silently go extinct without their actual risk ever being recognized. Importantly, our study showed that fine-scale analyses are essential to highlight the potential drivers of extinction risk for the DD species of amphibians. A crucial next step for conservation policies in Vietnam (and in surrounding countries) is developing and implementing species-specific studies targeted at addressing each species’ drivers of extinction and determining science-based strategies for minimizing their extinction risk

Multiple-point statistical simulation for hydrogeological models: 3D training image development and conditioning strategies

Most studies about the application of geostatistical simulations based on multiple-point statistics (MPS) to hydrogeological modelling focus on relatively fine-scale models and concentrate on the estimation of facies-level, structural uncertainty. Much less attention is paid to the use of input data and optimal construction of training images. For instance, even though the training image should capture a set of spatial geological characteristics to guide the simulations, the majority of the research still relies on 2D or quasi-3D training images. In the present study, we demonstrate a novel strategy for 3D MPS modelling characterized by: (i) realistic 3D training images, and (ii) an effective workflow for incorporating a diverse group of geological and geophysical data sets. The study covers an area of 2810 km2 in the southern part of Denmark. MPS simulations are performed on a subset of the geological succession (the lower to middle Miocene sediments) which is characterized by relatively uniform structures and dominated by sand and clay. The simulated domain is large and each of the geostatistical realizations contains approximately 45 million voxels with size 100 m × 100 m × 5 m. Data used for the modelling include water well logs, high-resolution seismic data, and a previously published 3D geological model. We apply a series of different strategies for the simulations based on data quality, and develop a novel method to effectively create observed sand/clay spatial trends. The training image is constructed as a small 3D voxel model covering an area of 90 km2. We use an iterative training image development strategy and find that even slight modifications in the training image create significant changes in simulations. Thus, the study underlines that it is important to consider both the geological environment, and the type and quality of input information in order to achieve optimal results from MPS modelling. In this study we present a possible workflow to build the training image and effectively handle different types of input information to perform large-scale geostatistical modellin

Functional traits predict species co-occurrence patterns in a North American Odonata metacommunity

The probability of occurrence of a given species in a target locality and assemblage is conditioned not only by environmental/climatic variables but also by the presence of other species (i.e., species co-occurrence). This framework, already complex in nature, becomes even more complicated if one considers the functional traits of species that, in turn, might influence the structure of metacommunities in various ways. Depending on the ecological and environmental setting, functional similarity (i.e., convergence in morphological and ecological traits) between species might either reduce their co-occurrence due to high niche overlap driving negative interactions or promote it if the similar traits are associated with local habitat suitability. Similarly, functional divergence might either promote species co-occurrence by limiting negative interactions through niche separation or reduce it through trait mediated environmental filtering. Therefore, discriminating between these alternative scenarios—predicting whether two species will tend to co-occur or not based on their traits—is extremely challenging. Here, we develop a novel protocol to tackle the challenge, and we demonstrate its effectiveness by showing that ecological species traits can predict species co-occurrence in a large dataset of North American Odonata. To this end, we first used the Hierarchical Modeling of Species Communities framework to quantify the pairwise species co-occurrence after controlling for environmental and climatic factors. Then, we used machine learning to generate models which proved capable of predict accurately the observed co-occurrence patterns from species functional traits. Our approach offers a generalizable analytical framework with the potential to clarify long-standing ecological questions

Mutual Avoidance in the Spectacled Salamander and Centipede: A Discrepancy between Exploratory Field and Laboratory Data

Interactions between amphibians and arthropods encompass a wide range of ecological relationships, predominantly characterized by predator–prey dynamics, with adult amphibians as the predators. In some instances, the roles are reversed. This study focuses on the potential predator-prey relationship between the spectacled salamander (Salamandrina perspicillata) and the centipede Scolopendra cingulata in Central Italy. Building upon previous research on chemical cue perception in amphibians, we investigated potential olfactory cue-mediated avoidance behaviours exhibited by S. perspicillata towards the potential predator S. cingulata through field observations and manipulative experiments. In a natural site, we estimated the degree of negative co-occurrence between the study species under shelters and found an avoidance pattern between S. perspicillata and S. cingulata in refuges. However, when the study species were forced to choose between sharing or not sharing a given shelter, through a manipulative experiment, the avoidance pattern was not confirmed. Potential determinants contributing to the avoidance pattern observed in nature are discussed. Our exploratory results represent a good example of how what often appears to be a strong observation-based pattern in natural settings needs to be carefully scrutinized. Hypotheses testing through experiments in controlled environments remains a valuable approach to exclude potentially misleading processes

The Use of Tail as a Minimal-Invasive Method to Detect a Large Set of Biochemical Responses in the Italian Wall Lizard Podarcis siculus (Rafinesque, 1810)

Conventional methods to analyze biochemical processes related to contaminant toxicity usually require the sacrifice of animals to collect tissues and organs. However, for ethical reasons and especially for endangered species, non- or minimal-invasive methods should be preferred. Among vertebrates, reptiles show a general decline worldwide and therefore the use of non- or minimal-invasive methods to measure some biochemical processes in these animals are encouraged. It is well known that most lizards use a common safety behavior implying the natural loss of tail in the case of predation events. Therefore, if common analyses testing contaminant toxicity could be performed in tail tissue, this method, not implying the sacrifice of the animals, could be considered as a good minimal-invasive method. The aim of this study is to test on wild Italian wall lizard Podarcis siculus the use of tail to detect a large set of biomarkers including oxidative stress (TOSCAROO, TOSCAOH, CAT, tGSH, MDA), biotransformation processes (EROD, GSTs) and neurotoxicity (AChE, BChE). All the biochemical responses, excluding EROD and MDA, resulted to be analytically detectable in tail tissues of P. siculus, although the mean values obtained with this minimal-invasive method were significantly lower than those obtained with invasive one