Estonian Environmental Research Center (Estonia)

The recovery of wolves (Canis lupus) across Europe is a notable conservation success in a region with extensive human alteration of landscapes and high human population densities. We provide a comprehensive update on wolf populations in Europe, estimated at over 21,500 individuals by 2022, representing a 58% increase over the past decade. Despite the challenges of high human densities and significant land use for agriculture, industry, and urbanization, wolves have demonstrated remarkable adaptability and increasing population trends in most European countries. Improved monitoring techniques, although varying in quality and scope, have played a crucial role in tracking this recovery. Annually, wolves kill approximately 56,000 domestic animals in the EU, a risk unevenly distributed and differently handled across regions. Damage compensation costs 17 million EUR every year to European countries. Positive economic impacts from wolf presence, such as those related to reducing traffic accidents with wild ungulates or supporting wildlife tourism, remain under studied. Wolf recovery in Europe is supported by diverse policy and legal instruments such as LIFE programs, stakeholder platforms, as well as the EU Habitats Directive and the Bern Convention. Coexisting with newly established wolf populations in Europe entails managing impacts on human activities, including livestock depredation, competition for game, and fear of attacks on humans, amidst varying social and political views on wolf recovery. Sustainable coexistence continues to operate in evolving and complex social, economic, and political landscapes, often characterized by intense debates regarding wolf policies.

Short-term exposure to ground-level ozone in cities is associated with increased mortality and is expected to worsen with climate and emission changes. However, no study has yet comprehensively assessed future ozone-related acute mortality across diverse geographic areas, various climate scenarios, and using CMIP6 multi-model ensembles, limiting our knowledge on future changes in global ozone-related acute mortality and our ability to design targeted health policies. Here, we combine CMIP6 simulations and epidemiological data from 406 cities in 20 countries or regions. We find that ozone-related deaths in 406 cities will increase by 45 to 6,200 deaths/year between 2010 and 2014 and between 2050 and 2054, with attributable fractions increasing in all climate scenarios (from 0.17% to 0.22% total deaths), except the single scenario consistent with the Paris Climate Agreement (declines from 0.17% to 0.15% total deaths). These findings stress the need for more stringent air quality regulations, as current standards in many countries are inadequate.

Food supply stands out as one of the most critical drivers of population demographics by limiting reproductive rates. In this study, we assessed fluctuations in diet composition and monitored various reproductive parameters over a nine-year period in a Golden Eagle population in an Eastern European peatland. The identification of 2439 prey specimens from 84 species revealed that the studied eagles primarily preyed upon birds (constituting 78.3% of prey numbers and 67.2% of prey biomass) and less on mammals (21.6% and 32.8%, respectively). Grouse emerged as the most important prey group (31% and 27%), followed by waterfowl (17%) and hares (8% and 14%). The most significant prey species, both in terms of numbers and weight, were the Black Grouse, Mountain Hare, Common Crane, and Capercaillie. The share of the Black Grouse decreased, while those of the White-fronted Goose, Roe Deer, and hares increased. The food niche, as measured by the Levins’ index, was broad (6.6), and it expanded during the study. On average, 58.3% of Golden Eagle pairs initiated breeding annually, with 69.1% successfully completing it, and 0.41 young per occupied territory were produced annually; there was pronounced interannual variation in reproductive performance. These fluctuations were associated with the shares of White-fronted Goose, Capercaillie, Mountain Hare and Roe Deer in the diet, suggesting that these species may be gaining increasing importance for the Golden Eagle, particularly following the decline of the Black Grouse.

Operators depend on reliable Q-margin estimates to reliably operate wide-band Optical Spectrum Services. We use long-term performance tracking in live Raman-enabled links to derive service margins for a 375-GHz Optical Spectrum Service.

Abstract. Particulate matter (PM) has become a major concern in terms of human health and climate impact. In particular, the source apportionment (SA) of organic aerosols (OA) present in submicron particles (PM1) has gained relevance as an atmospheric research field due to the diversity and complexity of its primary sources and secondary formation processes. Moreover, relatively simple but robust instruments such as the Aerosol Chemical Speciation Monitor (ACSM) are now widely available for the near-real-time online determination of the composition of the non-refractory PM1. One of the most used tools for SA purposes is the source-receptor positive matrix factorisation (PMF) model. Even though the recently developed rolling PMF technique has already been used for OA SA on ACSM datasets, no study has assessed its added value compared to the more common seasonal PMF method using a practical approach yet. In this paper, both techniques were applied to a synthetic dataset and to nine European ACSM datasets in order to spot the main output discrepancies between methods. The main advantage of the synthetic dataset approach was that the methods' outputs could be compared to the expected “true” values, i.e. the original synthetic dataset values. This approach revealed similar apportionment results amongst methods, although the rolling PMF profile's adaptability feature proved to be advantageous, as it generated output profiles that moved nearer to the truth points. Nevertheless, these results highlighted the impact of the profile anchor on the solution, as the use of a different anchor with respect to the truth led to significantly different results in both methods. In the multi-site study, while differences were generally not significant when considering year-long periods, their importance grew towards shorter time spans, as in intra-month or intra-day cycles. As far as correlation with external measurements is concerned, rolling PMF performed better than seasonal PMF globally for the ambient datasets investigated here, especially in periods between seasons. The results of this multi-site comparison coincide with the synthetic dataset in terms of rolling–seasonal similarity and rolling PMF reporting moderate improvements. Altogether, the results of this study provide solid evidence of the robustness of both methods and of the overall efficiency of the recently proposed rolling PMF approach.

Particulate Matter (PM) has become a major concern in terms of human health and climate impact. In particular, the source apportionment (SA) of organic aerosols (OA) present in submicron particles (PM1) has gained relevance as an atmospheric research field due to the diversity and complexity of its primary sources and secondary formation processes. Moreover, relatively simple but robust instruments such as the Aerosol Chemical Speciation Monitor (ACSM) are now widely available for the near real-time online determination of the composition of the non-refractory PM1. One of the most used tools for SA purposes is the source-receptor Positive Matrix Factorization (PMF) model. Even though the recently developed rolling PMF technique has already been used for OA SA on ACSM datasets, no study has assessed its added value concerning the more common seasonal PMF method from a practical approach yet. In this paper, both techniques were applied to a synthetic dataset and to nine European ACSM datasets in order to spot the main output discrepancies between methods. The main advantage of the synthetic dataset approach was that the methods’ outputs could be compared to the expected ‘true’ values, i.e. the original synthetic dataset values. This approach revealed similar apportionment results amongst methods, but differing with respect to the truth, although the rolling PMF profile adaptability feature has been proven advantageous. Also, these results highlighted the impact of the profile anchor on the solution. In the multi-site study, while differences were generally not significant when considering year-long periods, their importance grew towards shorter time spans, as in intra-month or intra-day cycles. Rolling PMF performed better than seasonal PMF globally for the ambient datasets investigated here as far correlation with external measurements is concerned, especially in periods between seasons. The results of this comparison also support rolling PMF benefits even though output discrepancies with seasonal PMF were scarce. Altogether, the results of this study provide solid evidence of the robustness of both methods and on the overall efficiency of the recently-proposed rolling PMF approach.

Beekeepers have various options to control the parasitic mite Varroa destructor in honey bee colonies, but no empirical data are available on the methods they apply in practice. We surveyed 28,409 beekeepers maintaining 507,641 colonies in 30 European countries concerning Varroa control methods. The set of 19 different Varroa diagnosis and control measures was taken from the annual COLOSS questionnaire on honey bee colony losses. The most frequent activities were monitoring of Varroa infestations, drone brood removal, various oxalic acid applications and formic acid applications. Correspondence analysis and hierarchical clustering on principal components showed that six Varroa control options (not necessarily the most used ones) significantly contribute to defining three distinctive clusters of countries in terms of Varroa control in Europe. Cluster I (eight Western European countries) is characterized by use of amitraz strips. Cluster II comprises 15 countries from Scandinavia, the Baltics, and Central-Southern Europe. This cluster is characterized by long-term formic acid treatments. Cluster III is characterized by dominant usage of amitraz fumigation and formed by seven Eastern European countries. The median number of different treatments applied per beekeeper was lowest in cluster III. Based on estimation of colony numbers in included countries, we extrapolated the proportions of colonies treated with different methods in Europe. This suggests that circa 62% of colonies in Europe are treated with amitraz, followed by oxalic acid for the next largest percentage of colonies. We discuss possible factors determining the choice of Varroa control measures in the different clusters.