The low survival rate of European hare leverets in arable farmland: evidence from the predation experiment.

The low survival rate of leverets may significantly contribute to steep population declines and slow recovery of European hares (Lepus europaeus). However, the leveret survival rate in farmlands with different landscape structures is poorly understood, and the existing evidence comes mainly from Western Europe. In this study, we explored the survival of leveret hare dummies along linear semi-natural habitats in homogeneous Central European arable farmland during the main part of the European hare reproduction period (March-April) in 2019 and 2020. The survival rate of hare leverets during the 14-day period was only 22.2%, and all predation events were recorded during the first six days of the experiment. Mammalian predators were responsible for 53.1% of predation events, avian predators for 40.8%, and agricultural operations for 6.1%. The red fox (Vulpes vulpes) was the dominant predator in our study area and was the primary cause of leveret dummy mortality (32.7%), but it also had the highest use-intensity and visit frequency of all of the study plots. Predation by avian predators was associated with patches of lower vegetation height and cover (such as plowed fields) and during daylight hours, whereas the opposite was true for mammalian predators. We propose that improving the habitat quality of arable landscapes by increasing the proportion and quality of extensively used non-farmed habitats (e.g., set-asides, wildflower areas, extensive meadows, fallow land, and semi-natural habitats on arable land) providing cover and shelter for leverets could be an effective management measure for reducing predation risk on leverets.

Fine-scale movement patterns and habitat selection of little owls (Athene noctua) from two declining populations.

Advances in bio-logging technology for wildlife monitoring have expanded our ability to study space use and behavior of many animal species at increasingly detailed scales. However, such data can be challenging to analyze due to autocorrelation of GPS positions. As a case study, we investigated spatiotemporal movements and habitat selection in the little owl (Athene noctua), a bird species that is declining in central Europe and verges on extinction in Denmark. We equipped 6 Danish food-supplemented little owls and 6 non-supplemented owls in the Czech Republic with high-resolution GPS loggers that recorded one position per minute. Nightly space use, measured as 95% kernel density estimates, of Danish male owls were on average 62 ha (± 64 SD, larger than any found in previous studies) compared to 2 ha (± 1) in females, and to 3 ± 1 ha (males) versus 3 ± 5 ha (females) in the Czech Republic. Foraging Danish male owls moved on average 4-fold further from their nest and at almost double the distance per hour than Czech males. To create availability data for the habitat selection analysis, we accounted for high spatiotemporal autocorrelation of the GPS data by simulating correlated random walks with the same autocorrelation structure as the actual little owl movement trajectories. We found that habitat selection was similar between Danish and Czech owls, with individuals selecting for short vegetation and areas with high structural diversity. Our limited sample size did not allow us to infer patterns on a population level, but nevertheless demonstrates how high-resolution GPS data can help to identify critical habitat requirements to better formulate conservation actions on a local scale.

The declining occurrence of moose (Alces alces) at the southernmost edge of its range raise conservation concerns.

The border region between Austria, the Czech Republic, and Germany harbors the most south-western occurrence of moose in continental Europe. The population originated in Poland, where moose survived, immigrated from former Soviet Union or were reintroduced after the Second World War expanded west- and southwards. In recent years, the distribution of the nonetheless small Central European population seems to have declined, necessitating an evaluation of its current status. In this study, existing datasets of moose observations from 1958 to 2019 collected in the three countries were combined to create a database totaling 771 records (observations and deaths). The database was then used to analyze the following: (a) changes in moose distribution, (b) the most important mortality factors, and (c) the availability of suitable habitat as determined using a maximum entropy approach. The results showed a progressive increase in the number of moose observations after 1958, with peaks in the 1990s and around 2010, followed by a relatively steep drop after 2013. Mortality within the moose population was mostly due to human interactions, including 13 deadly wildlife-vehicle collisions, particularly on minor roads, and four animals that were either legally culled or poached. Our habitat model suggested that higher altitudes (ca. 700-1,000 m a.s.l.), especially those offering wetlands, broad-leaved forests and natural grasslands, are the preferred habitats of moose whereas steep slopes and areas of human activity are avoided. The habitat model also revealed the availability of large core areas of suitable habitat beyond the current distribution, suggesting that habitat was not the limiting factor explaining the moose distribution in the study area. Our findings call for immediate transboundary conservation measures to sustain the moose population, such as those aimed at preventing wildlife-vehicle collisions and illegal killings. Infrastructure planning and development activities must take into account the habitat requirements of moose.

Evaluation of Spatio-Temporal Patterns of Predation Risk to Forest Grouse Nests in the Central European Mountain Regions.

We evaluated the spatiotemporal patterns of predation risk on black grouse nests using artificial nests that were monitored by camera traps in mountain areas with a small extant (Ore Mts.) and already extinct (Jeseníky Mts.) black grouse population. The overall predation rate of artificial nests was 56% and we found significant differences in survival rate courses over time between both study areas (68% Ore Mts. vs. 41%, Jeseníky Mts.). Within the time required for successful egg incubation (25 days), nest survival probability was 0.32 in the Ore Mts. and 0.59 in Jeseníky Mts. The stone marten (Martes foina) was the primary nest predator in both study areas (39% in total), followed by common raven (Corvus corax, 25%) and red fox (Vulpes vulpes, 22%). The proportion of depredated nests did not differ between habitat types (i.e., open forest interior, clearing, forest edge), but we recorded the effect of interaction of study area and habitat. In Ore Mts., the main nest predator was common raven with seven records (37%). The Eurasian jay (Garrulus glandarius) was responsible for most predation attempts in Jeseníky Mts. (five records, i.e., 83%), while in the Ore Mts., most predation attempts were done by red fox (six records, i.e., 38%).

The use of socio-economy in species distribution modelling: Features of rural societies improve predictions of barn owl occurrence.

Variation of habitats and resources important for farmland birds seems to be only partly captured by ordinary statistics on land-use and agricultural production. For instance, densities of rodents being prey for owls and raptors or structures of rural architecture providing nesting sites for many species are central for bird diversity but are not reported in any official statistics. Thus, modelling species distributions, population abundance and trends of farmland birds may miss important predictive habitat elements. Here, we involve local socio-economy factors as a source of additional information on rural habitat to test whether it improves predictions of barn owl occurrence in 2768 churches across Poland. Barn owls occurred in 778 churches and seemed to prefer old churches made of brick located in regions with a milder climate, higher share of arable land and pastures, low road density and low levels of light pollution. Including data on local unemployment, the proportion of elder citizens, commune income per citizen, the share of citizens with high education and share of farmers among working population improved the model substantially and some of these variables predicted barn owl occurrence better than several land-use and climate data. Barn owls were more likely to occur in areas with high unemployment, a higher proportion of older citizens in a local population and higher share of farmers among working population. Importantly, the socio-economy variables were correlated with the barn owl occurrence despite all climatic, infrastructure and land-use data were present in the model. We conclude that the socio-economy of local societies may add important but overlooked information that links to spatial variation in farmland biodiversity.

Automatic acoustic identification of individuals in multiple species: improving identification across recording conditions.

Many animals emit vocal sounds which, independently from the sounds' function, contain some individually distinctive signature. Thus the automatic recognition of individuals by sound is a potentially powerful tool for zoology and ecology research and practical monitoring. Here, we present a general automatic identification method that can work across multiple animal species with various levels of complexity in their communication systems. We further introduce new analysis techniques based on dataset manipulations that can evaluate the robustness and generality of a classifier. By using these techniques, we confirmed the presence of experimental confounds in situations resembling those from past studies. We introduce data manipulations that can reduce the impact of these confounds, compatible with any classifier. We suggest that assessment of confounds should become a standard part of future studies to ensure they do not report over-optimistic results. We provide annotated recordings used for analyses along with this study and we call for dataset sharing to be a common practice to enhance the development of methods and comparisons of results.

Correction: The assessment of biases in the acoustic discrimination of individuals.

[This corrects the article DOI: 10.1371/journal.pone.0177206.].

The assessment of biases in the acoustic discrimination of individuals.

Animal vocalizations contain information about individual identity that could potentially be used for the monitoring of individuals. However, the performance of individual discrimination is subjected to many biases depending on factors such as the amount of identity information, or methods used. These factors need to be taken into account when comparing results of different studies or selecting the most cost-effective solution for a particular species. In this study, we evaluate several biases associated with the discrimination of individuals. On a large sample of little owl male individuals, we assess how discrimination performance changes with methods of call description, an increasing number of individuals, and number of calls per male. Also, we test whether the discrimination performance within the whole population can be reliably estimated from a subsample of individuals in a pre-screening study. Assessment of discrimination performance at the level of the individual and at the level of call led to different conclusions. Hence, studies interested in individual discrimination should optimize methods at the level of individuals. The description of calls by their frequency modulation leads to the best discrimination performance. In agreement with our expectations, discrimination performance decreased with population size. Increasing the number of calls per individual linearly increased the discrimination of individuals (but not the discrimination of calls), likely because it allows distinction between individuals with very similar calls. The available pre-screening index does not allow precise estimation of the population size that could be reliably monitored. Overall, projects applying acoustic monitoring at the individual level in population need to consider limitations regarding the population size that can be reliably monitored and fine-tune their methods according to their needs and limitations.