Badger Meles meles as Ecosystem Engineer and Its Legal Status in Europe

Simple Summary

The European badger, listed in Bern Convention (protected fauna species), is also known as an important ecosystem engineer that creates new microhabitats among its setts suitable for the establishment of many plant and animal species. Badger setts are areas with topsoil disturbance and hence are places with higher species diversity than undisturbed surroundings. Much new data concerning the importance of badgers in ecosystem engineering indicates that the way badger populations are managed in Europe should be reconsidered. Thus, the aim of this study was to review the impact of badgers on shaping of species diversity in forest ecosystems with special attention to their legal status across Europe. The badger is hunted on 69.3% of the continent for 1.5–12 months per year. The real problem with management of this species concerns a quarter of its range in Europe, where the species can be hunted in winter and spring during mating season and during parturition. Reducing the hunting season to a maximum of three months in late autumn (September to November) seems to be a better approach. To prevent the negative effects of overhunting, special attention should be paid to population monitoring.

Abstract

The European badger plays an important role as a natural factor shaping species diversity in forests. Its extensive setts can be used by many other animals as shelters. Soil perturbations in their setts support plant communities that differ from the matrix landscape. The badger is also an effective seed disperser. We investigated its role as an ecosystem engineer in preserving species diversity and discussed its legal status across Europe. In most European countries (69.3% of the continent), the badger is hunted, sometimes year-round. The hunting season lasting through winter until early spring may have a negative effect on badger populations, especially when cubs are born in February. Although this species is Red Listed in 19 European countries (with categories ranging from LC to EN), the badger is strictly protected by law in 30.7% of its European range. A reduction in badger populations may limit its ecosystem services (seed dispersal, topsoil disturbances, microhabitat creation). Much new data on the importance of badgers in ecosystem engineering has allowed us to reconsider how we manage badger populations.

Breaking down population density into different components to better understand its spatial variation

BACKGROUND

Population size and densities are key parameters in both fundamental and applied ecology, as they affect population resilience to density-dependent processes, habitat changes and stochastic events. Efficient management measures or species conservation programs thus require accurate estimates of local population densities across time and space, especially for continuously distributed species. For social species living in groups, population density depends on different components, namely the number of groups and the group size, for which relative variations in space may originate from different environmental factors. Whether resulting spatial variations in density are mostly triggered by one component or the other remains poorly known. Here, we aimed at determining the magnitude of the spatial variation in population densities of a social, group-living species, i.e. the European badger Meles meles, in 13 different sites of around 50 km² across France, to decipher whether sett density, group size or proportion of occupied sett variation is the main factor explaining density variation. Besides the intrinsic factors of density variation, we also assessed whether habitat characteristics such as habitat fragmentation, urbanisation, and resource availability, drove both the spatial variation of density components and local population densities.

RESULTS

We proposed a new standardised approach combining use of multiple methods, namely distance sampling for estimating the density of occupied sett clusters, i.e. group density, and camera and hair trapping for genetic identification to determine the mean social group size. The density of adult badgers was on average 3.8 per km² (range 1.7-7.9 per km²) and was positively correlated with the density of sett clusters. The density of adult badgers per site was less related to the social group size or to the proportion of occupied sett clusters. Landscape fragmentation also explained the spatial variation of adult badger density, with highly fragmented landscapes supporting lower adult densities. Density components were linked differently to environmental variables.

CONCLUSIONS

These results underline the need to break down population density estimates into several components in group-living species to better understand the pattern of temporal and spatial variation in population density, as different components may vary due to different ecological factors.

How far from the road should land cover be assessed? A case study on mesopredator mortality on roads

The methods used to assess the significance of land cover in the vicinity of a road for the mortality of mesopredators are diverse. In assessing the effect of land cover along the road on road causalities, scientists use various buffer sizes, or even no buffer along the road. The aim of this study was to verify how results of land cover effects on the mortality of mesopredators on roads may differ when analyzing various buffer sizes from the road. We assessed road causalities in the Warmian-Masurian voivodeship (Poland) from 3 consecutive years: 2015, 2016, and 2017. The roads were divided into equal sections of 2000 m each with buffer size of radius: 10, 250, 500, and 1000 m. We analyzed the number of road kills of red fox and European badger separately in a generalized linear model, whereas explanatory variables we used land cover types (based on the Corine Land Cover inventory) and traffic volume. Mean annual mortality from road collisions amounts to 2.36% of the red fox population and 3.82% of the European badger population. We found that the buffer size determines the results of the impact of land cover on mesocarnivore mortality on roads. The red fox differed from the European badger in response to land cover depending on the buffer size. The differences we have shown relate in particular to built-up areas. Our results indicate a 500-m buffer as best reflecting the land cover effects in road kills of both species. This was confirmed by model evaluation and a tendency to use or avoid the vicinity of human settlements of the analyzed species. We concluded that buffer size will probably affect mostly the significance of cover types that are spatially correlated with roads, positively or negatively. We suggest that the home range size of given species in local conditions should be assessed before determining the size of the buffer for analysis.

Altitude shapes the environmental drivers of large-scale variation in abundance of a widespread mammal species

AIM

Habitat quality and heterogeneity directly influence the distribution and abundance of organisms at different spatial scales. Determining the main environmental factors driving the variation in species abundance is crucial to understand the underlying ecological processes, and this is especially important for widely distributed species living in contrasting environments. However, the responses to environmental variation are usually described at relatively small spatial scales. Here, we studied the variation in abundance of a widely distributed mustelid, the European badger (Meles meles), across France.

LOCATION

The whole metropolitan France.

METHODS

We used (a) direct detections of 9,439 dead and living badgers, from 2006 to 2009, to estimate badger relative abundance in 703 small agricultural regions of metropolitan France and (b) a Bayesian modeling approach to identify the main environmental determinants influencing badger abundance.

RESULTS

Despite a continuous distribution of badger in France, we found large variation in badger abundance between regions, explained by environmental factors. Among a set of 13 environmental variables, we demonstrated that badger abundance in lowlands (<400 m a.s.l.) was mostly driven by biotic factors such as potential food resources (earthworm abundance and fruit crops) and forest fragmentation. Conversely, in mountainous areas, abiotic factors (i.e., soil texture and climate) drove the variation in badger relative abundance.

MAIN CONCLUSIONS

These results underline the importance of mapping the abundance of wildlife species based on environmental suitability and highlight the complexity of drivers influencing species abundance at such large spatial scales. Altitude shaped the environmental drivers (biotic vs. abiotic) that most influenced relative abundance of a widespread species. In the case of badger, such abundance maps are crucial to identify critical areas for species management as this mustelid is a main wild vector of bovine tuberculosis in several countries.

Modelling the Spatial Distribution of Asbestos—Cement Products in Poland with the Use of the Random Forest Algorithm

The unique set of physical and chemical properties of asbestos has led to its many industrial applications worldwide, of which roofing and facades constitute approximately 80% of currently used asbestos-containing products. Since asbestos-containing products are harmful to human health, their use and production have been banned in many countries. To date, no research has been undertaken to estimate the total amount of asbestos–cement products used at the country level in relation to regions or other administrative units. The objective of this paper is to present a possible new solution for developing the spatial distribution of asbestos–cement products used across the country by applying the supervised machine learning algorithm, i.e., Random Forest. Based on the results of a physical inventory taken on asbestos–cement products with the use of aerial imagery, and the application of selected features, considering the socio-economic situation of Poland, i.e., population, buildings, public finance, housing economy and municipal infrastructure, wages, salaries and social security benefits, agricultural census, entities of the national economy, labor market, environment protection, area of built-up surfaces, historical belonging to annexations, and data on asbestos manufacturing plants, best Random Forest models were computed. The selection of important variables was made in the R v.3.1.0 program and supported by the Boruta algorithm. The prediction of the amount of asbestos–cement products used in communes was executed in the randomForest package. An algorithm explaining 75.85% of the variance was subsequently used to prepare the prediction map of the spatial distribution of the amount of asbestos–cement products used in Poland. The total amount was estimated at 710,278,645 m2 (7.8 million tons). Since the best model used data on built-up surfaces which are available for the whole of Europe, it is worth considering the use of the developed method in other European countries, as well as to assess the environmental risk of asbestos exposure to humans.