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Numerous studies have been devoted to individual cases of horizontally acquired genes in fungi. It has been shown that such genes expand the hosts' metabolic capabilities and contribute to their adaptations as parasites or symbionts. Some studies have provided an extensive characterization of the horizontal gene transfer (HGT) in Dikarya. However, in the early diverging fungi (EDF), a similar characterization is still missing. In order to fill this gap, we have designed a computational pipeline to obtain a statistical sample of reliable HGT events with a low false discovery rate. We have analyzed 44 EDF proteomes and identified 829 xenologs in fungi ranging from Chytridiomycota to Mucoromycota. We have identified several patterns and statistical properties of EDF HGT. We show that HGT is driven by bursts of gene exchange and duplication, resulting in highly divergent numbers and molecular properties of xenologs between fungal lineages. Ancestrally aquatic fungi are generally more likely to acquire foreign genetic material than terrestrial ones. Endosymbiotic bacteria can be a source of useful xenologs, as exemplified by NOD-like receptors transferred to Mortierellomycota. Closely related fungi have similar rates of intronization of xenologs. Posttransfer gene fusions and losses of protein domains are common and may influence the encoded proteins' functions. We argue that there is no universal approach for HGT identification and inter- and intra-kingdom transfers require tailored identification methods. Our results help to better understand how and to what extent HGT has shaped the metabolic, adaptive, and immune capabilities of fungi. [ABSTRACT FROM AUTHOR]

Habitat use and preferences may be subject to spatial and temporal changes. However, long-term studies of species–habitat relationships are the exception. In the present research, long-term trends in habitat use by an alpine ungulate, the Tatra chamois Rupicapra rupicapra tatrica, were analyzed. We examined how environmental changes attributable to climate change, removal of sheep, and habituation to hikers, which took place over the last half-century have changed the spatial distribution of animals. Data on the localities of groups sighted between 1957 and 2013 during autumnal population surveys were used to evaluate habitat associations: these were correlated with year, group size, population size, and climatic conditions. The results indicate that the Tatra chamois is tending, over the long term, to lower its altitude of occurrence, reduce its average distance to hiking trails, and stay less often on slopes with a southerly aspect. These trends are independent of group size, population size, and the weather conditions prevailing during observations, though not for altitude, where increases in air temperature are related to finding chamois at higher elevations. The proportion of alpine meadows and slope in the places used by chamois is correlated with population size, while the proportion of areas with trees and/or shrubs is correlated with group size and air temperature, though long-term changes were not evident for these variables. To the best of our knowledge, this work is the first to document long-term trends in habitat use by ungulates. It shows that a species' ecology is influenced by human-induced changes: abandonment of pasturage, high-mountain tourism, and climate changes, which constitute the most probable reasons for this aspect of behavioral evolution in the Tatra chamois. [ABSTRACT FROM AUTHOR]

Noise, an obvious effect of urbanization, has a negative impact on animal vocalizations and the hunting efficiency of acoustic predators. However, the influence of noise pollution on the spatial distribution of populations remains understudied. The aim was to assess the factors shaping the distribution pattern of an acoustic predator (long-eared owl Asio otus) in an urban–farmland matrix. We hypothesized that the probability of an acoustic predator occurring decreases with growing nocturnal noise emission. This owl survey was conducted in Kraków (S Poland) on 79 randomly selected sample plots (1 km × 1 km). Six habitat variables (area of parks, woodlands, grassland, arable land, habitat diversity index, and noise pollution) were identified and correlated with the probability of the species' occurrence. Proximity to pedestrian routes and roads, habitat fragmentation, and noise intensity was also defined at nest sites and random sites. Long-eared owls occurred on 37% of the sample plots. Occupied plots had a greater area of grassland and arable land as well as a lower level of noise pollution than the unoccupied ones. A multivariate model revealed that area of grassland and nocturnal noise emission was significantly correlated with the probability of long-eared owls occurring and that the high probability of occurrence recorded on plots with large areas of grassland was reduced by noise pollution. The noise intensity recorded at nest sites was also significantly lower than at random sites. This study suggests that apart from habitat factors, the distribution of acoustic predators in an urban matrix is driven by noise pollution. This highlights the importance of proper landscape management, that is, maintaining large grassland areas and preventing noise from increasing within them. [ABSTRACT FROM AUTHOR]

Migratory animals provide a multitude of services and disservices--with benefits or costs in the order of billions of dollars annually. Monitoring, quantifying, and forecasting migrations across continents could assist diverse stakeholders in utilizing migrant services, reducing disservices, or mitigating human-wildlife conflicts. Radars are powerful tools for such monitoring as they can assess directional intensities, such as migration traffic rates, and biomass transported. Currently, however, most radar applications are local or small scale and therefore substantially limited in their ability to address large-scale phenomena. As weather radars are organized into continent-wide networks and also detect "biological targets," they could routinely monitor aerial migrations over the relevant spatial scales and over the timescales required for detecting responses to environmental perturbations. To tap these unexploited resources, a concerted effort is needed among diverse fields of expertise and among stakeholders to recognize the value of the existing infrastructure and data beyond weather forecasting. [ABSTRACT FROM AUTHOR]