The media and scientific literature are increasingly reporting an escalation of large carnivore attacks on humans in North America and Europe. Although rare compared to human fatalities by other wildlife, the media often overplay large carnivore attacks on humans, causing increased fear and negative attitudes towards coexisting with and conserving these species. Although large carnivore populations are generally increasing in developed countries, increased numbers are not solely responsible for the observed rise in the number of attacks by large carnivores. Here we show that an increasing number of people are involved in outdoor activities and, when doing so, some people engage in risk-enhancing behaviour that can increase the probability of a risky encounter and a potential attack. About half of the well-documented reported attacks have involved risk-enhancing human behaviours, the most common of which is leaving children unattended. Our study provides unique insight into the causes, and as a result the prevention, of large carnivore attacks on people. Prevention and information that can encourage appropriate human behaviour when sharing the landscape with large carnivores are of paramount importance to reduce both potentially fatal human-carnivore encounters and their consequences to large carnivores.

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The increasing trend of large carnivore attacks on humans not only raises human safety concerns but may also undermine large carnivore conservation efforts. Although rare, attacks by brown bears Ursus arctos are also on the rise and, although several studies have addressed this issue at local scales, information is lacking on a worldwide scale. Here, we investigated brown bear attacks (n = 664) on humans between 2000 and 2015 across most of the range inhabited by the species: North America (n = 183), Europe (n = 291), and East (n = 190). When the attacks occurred, half of the people were engaged in leisure activities and the main scenario was an encounter with a female with cubs. Attacks have increased significantly over time and were more frequent at high bear and low human population densities. There was no significant difference in the number of attacks between continents or between countries with different hunting practices. Understanding global patterns of bear attacks can help reduce dangerous encounters and, consequently, is crucial for informing wildlife managers and the public about appropriate measures to reduce this kind of conflicts in bear country.

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The deer ked [Lipoptena cervi (L. 1758) (Dipt., Hippoboscidae)] is a blood-sucking ectoparasite of cervids. The species has been resident in Sweden for more than two centuries, whereas in Finland ( approximately 50 years) and Norway ( approximately 30 years), it has established itself relatively recently. L. cervi may cause serious health problems in its natural hosts, act as a vector for zoonotic diseases, and pose a socioeconomic threat to forest-based activity. In this paper, we review the distribution and former expansion of the species in Fennoscandia. The current distribution of L. cervi appears bimodal, and the geographical range expansion of the species shows notable differences across Fennoscandia. The western population in Norway and Sweden has its northern edge of range at respective latitudes of 61 degrees N and 62 degrees N, whereas the eastern population in Finland reaches 65 degrees N. The future expansion of L. cervi is dependent on several interdependent extrinsic and intrinsic factors. International multidisciplinary collaboration is needed to achieve a synthesis on the factors affecting expansion rates and to understand the effects of L. cervi on wildlife, human health, and the rural societies of Fennoscandia.

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Net primary production (NPP) is an important ecological metric for studying forest ecosystems and their carbon sequestration, for assessing the potential supply of food or timber and quantifying the impacts of climate change on ecosystems. The global MODIS NPP dataset using the MOD17 algorithm provides valuable information for monitoring NPP at 1-km resolution. Since coarse-resolution global climate data are used, the global dataset may contain uncertainties for Europe. We used a 1-km daily gridded European climate data set with the MOD17 algorithm to create the regional NPP dataset MODIS EURO. For evaluation of this new dataset, we compare MODIS EURO with terrestrial driven NPP from analyzing and harmonizing forest inventory data (NFI) from 196,434 plots in 12 European countries as well as the global MODIS NPP dataset for the years 2000 to 2012. Comparing these three NPP datasets, we found that the global MODIS NPP dataset differs from NFI NPP by 26%, while MODIS EURO only differs by 7%. MODIS EURO also agrees with NFI NPP across scales (from continental, regional to country) and gradients (elevation, location, tree age, dominant species, etc.). The agreement is particularly good for elevation, dominant species or tree height. This suggests that using improved climate data allows the MOD17 algorithm to provide realistic NPP estimates for Europe. Local discrepancies between MODIS EURO and NFI NPP can be related to differences in stand density due to forest management and the national carbon estimation methods. With this study, we provide a consistent, temporally continuous and spatially explicit productivity dataset for the years 2000 to 2012 on a 1-km resolution, which can be used to assess climate change impacts on ecosystems or the potential biomass supply of the European forests for an increasing bio-based economy. MODIS EURO data are made freely available at ftp://palantir.boku.ac.at/Public/MODIS_EURO.

We used six models, ranging from simple parameter-sparse models to complex process-based 7 models: 3PG, 4C, ANAFORE, BASFOR, BRIDGING and FORMIND. For each model, the initial 8 degree of uncertainty about parameter values was expressed in a prior probability distribution. 9Inventory data for Scots pine on tree height and diameter, with estimates of measurement 10 uncertainty, were assembled for twelve sites, from four countries: Austria, Belgium, Estonia and 11Finland. From each country, we used data from two sites of the National Forest Inventories (NFI), 12 and one Permanent Sample Plot (PSP). The models were calibrated using the NFI-data and tested 13 against the PSP-data. Calibration was done both per country and for all countries simultaneously, 14 thus yielding country-specific and generic parameter distributions. We assessed model 15 performance by sampling from prior and posterior distributions and comparing the growth 16 predictions of these samples to the observations at the PSP"s. 17We found that BC reduced uncertainties strongly in all but the most complex model. 18 Surprisingly, country-specific BC did not lead to clearly better within-country predictions than 19 generic BC. BMC identified the BRIDGING model, which is of intermediate complexity, as the 20 most plausible model before calibration, with 4C taking its place after calibration. In this BMC, 21 model plausibility was quantified as the relative probability of a model being correct given the 22 information in the PSP-data. We discuss how the method of model initialisation affects model 23 performance. Finally, we show how BMA affords a robust way of predicting forest growth that 24 accounts for both parametric and model structural uncertainty. 25 26 27