High number of HPAI H5 virus infections and antibodies in wild carnivores in the Netherlands, 2020-2022

In October 2020, a new lineage of a clade 2.3.4.4b HPAI virus of the H5 subtype emerged in Europe, resulting in the largest global outbreak of HPAI to date, with unprecedented mortality in wild birds and poultry. The virus appears to have become enzootic in birds, continuously yielding novel HPAI virus variants. The recently increased abundance of infected birds worldwide increases the probability of bird-mammal contact, particularly in wild carnivores. Here, we performed molecular and serological screening of over 500 dead wild carnivores and sequencing of RNA positive materials. We show virological evidence for HPAI H5 virus infection in 0.8%, 1.4%, and 9.9% of animals tested in 2020, 2021, and 2022 respectively, with the highest proportion of positives in foxes, polecats and stone martens. We obtained near full genomes of 7 viruses and detected PB2 amino acid substitutions known to play a role in mammalian adaptation in three sequences. Infections were also found in without neurological signs or mortality. Serological evidence for infection was detected in 20% of the study population. These findings suggests that a high proportion of wild carnivores is infected but undetected in current surveillance programmes. We recommend increased surveillance in susceptible mammals, irrespective of neurological signs or encephalitis

A species-level trait dataset of bats in Europe and beyond

Knowledge of species' functional traits is essential for understanding biodiversity patterns, predicting the impacts of global environmental changes, and assessing the efficiency of conservation measures. Bats are major components of mammalian diversity and occupy a variety of ecological niches and geographic distributions. However, an extensive compilation of their functional traits and ecological attributes is still missing. Here we present EuroBatrait 1.0, the most comprehensive and up-to-date trait dataset covering 47 European bat species. The dataset includes data on 118 traits including genetic composition, physiology, morphology, acoustic signature, climatic associations, foraging habitat, roost type, diet, spatial behaviour, life history, pathogens, phenology, and distribution. We compiled the bat trait data obtained from three main sources: (i) a systematic literature and dataset search, (ii) unpublished data from European bat experts, and (iii) observations from large-scale monitoring programs. EuroBatrait is designed to provide an important data source for comparative and trait-based analyses at the species or community level. the dataset also exposes knowledge gaps in species, geographic and trait coverage, highlighting priorities for future data collection.Additional co-authors: Lisette Cantú-Salazar, Dina K. N. Dechmann, Tiphaine Devaux, Katrine Eldegard, Sasan Fereidouni, Joanna Furmankiewicz, Daniela Hamidovic, Davina L. Hill, Carlos Ibáñez, Jean-François Julien, Javier Juste, Peter Kaňuch, Carmi Korine, Alexis Laforge, Gaëlle Legras, Camille Leroux, Grzegorz Lesiński, Léa Mariton, Julie Marmet, Vanessa A. Mata, Clare M. Mifsud, Victoria Nistreanu, Roberto Novella-Fernandez, Hugo Rebelo, Niamh Roche, Charlotte Roemer, Ireneusz Ruczyński, Rune Sørås, Marcel Uhrin, Adriana Vella, Christian C. Voigt & Orly Razgou

A comprehensive analysis of autocorrelation and bias in home range estimation

Home range estimation is routine practice in ecological research. While advances in animal tracking technology have increased our capacity to collect data to support home range analysis, these same advances have also resulted in increasingly autocorrelated data. Consequently, the question of which home range estimator to use on modern, highly autocorrelated tracking data remains open. This question is particularly relevant given that most estimators assume independently sampled data. Here, we provide a comprehensive evaluation of the effects of autocorrelation on home range estimation. We base our study on an extensive data set of GPS locations from 369 individuals representing 27 species distributed across five continents. We first assemble a broad array of home range estimators, including Kernel Density Estimation (KDE) with four bandwidth optimizers (Gaussian reference function, autocorrelated-Gaussian reference function [AKDE], Silverman´s rule of thumb, and least squares cross-validation), Minimum Convex Polygon, and Local Convex Hull methods. Notably, all of these estimators except AKDE assume independent and identically distributed (IID) data. We then employ half-sample cross-validation to objectively quantify estimator performance, and the recently introduced effective sample size for home range area estimation ((Formula presented.)) to quantify the information content of each data set. We found that AKDE 95% area estimates were larger than conventional IID-based estimates by a mean factor of 2. The median number of cross-validated locations included in the hold-out sets by AKDE 95% (or 50%) estimates was 95.3% (or 50.1%), confirming the larger AKDE ranges were appropriately selective at the specified quantile. Conversely, conventional estimates exhibited negative bias that increased with decreasing (Formula presented.). To contextualize our empirical results, we performed a detailed simulation study to tease apart how sampling frequency, sampling duration, and the focal animal´s movement conspire to affect range estimates. Paralleling our empirical results, the simulation study demonstrated that AKDE was generally more accurate than conventional methods, particularly for small (Formula presented.). While 72% of the 369 empirical data sets had >1,000 total observations, only 4% had an (Formula presented.) >1,000, where 30% had an (Formula presented.) <30. In this frequently encountered scenario of small (Formula presented.), AKDE was the only estimator capable of producing an accurate home range estimate on autocorrelated data.Fil: Noonan, Michael J.. National Zoological Park; Estados Unidos. University of Maryland; Estados UnidosFil: Tucker, Marlee A.. Senckenberg Gesellschaft Für Naturforschung; . Goethe Universitat Frankfurt; AlemaniaFil: Fleming, Christen H.. University of Maryland; Estados Unidos. National Zoological Park; Estados UnidosFil: Akre, Thomas S.. National Zoological Park; Estados UnidosFil: Alberts, Susan C.. University of Duke; Estados UnidosFil: Ali, Abdullahi H.. Hirola Conservation Programme. Garissa; KeniaFil: Altmann, Jeanne. University of Princeton; Estados UnidosFil: Antunes, Pamela Castro. Universidade Federal do Mato Grosso do Sul; BrasilFil: Belant, Jerrold L.. State University of New York; Estados UnidosFil: Beyer, Dean. Universitat Phillips; AlemaniaFil: Blaum, Niels. Universitat Potsdam; AlemaniaFil: Böhning Gaese, Katrin. Senckenberg Gesellschaft Für Naturforschung; Alemania. Goethe Universitat Frankfurt; AlemaniaFil: Cullen Jr., Laury. Instituto de Pesquisas Ecológicas; BrasilFil: de Paula, Rogerio Cunha. National Research Center For Carnivores Conservation; BrasilFil: Dekker, Jasja. Jasja Dekker Dierecologie; Países BajosFil: Drescher Lehman, Jonathan. George Mason University; Estados Unidos. National Zoological Park; Estados UnidosFil: Farwig, Nina. Michigan State University; Estados UnidosFil: Fichtel, Claudia. German Primate Center; AlemaniaFil: Fischer, Christina. Universitat Technical Zu Munich; AlemaniaFil: Ford, Adam T.. University of British Columbia; CanadáFil: Goheen, Jacob R.. University of Wyoming; Estados UnidosFil: Janssen, René. Bionet Natuuronderzoek; Países BajosFil: Jeltsch, Florian. Universitat Potsdam; AlemaniaFil: Kauffman, Matthew. University Of Wyoming; Estados UnidosFil: Kappeler, Peter M.. German Primate Center; AlemaniaFil: Koch, Flávia. German Primate Center; AlemaniaFil: LaPoint, Scott. Max Planck Institute für Ornithologie; Alemania. Columbia University; Estados UnidosFil: Markham, A. Catherine. Stony Brook University; Estados UnidosFil: Medici, Emilia Patricia. Instituto de Pesquisas Ecológicas (IPE) ; BrasilFil: Morato, Ronaldo G.. Institute For Conservation of The Neotropical Carnivores; Brasil. National Research Center For Carnivores Conservation; BrasilFil: Nathan, Ran. The Hebrew University of Jerusalem; IsraelFil: Oliveira Santos, Luiz Gustavo R.. Universidade Federal do Mato Grosso do Sul; BrasilFil: Olson, Kirk A.. Wildlife Conservation Society; Estados Unidos. National Zoological Park; Estados UnidosFil: Patterson, Bruce. Field Museum of National History; Estados UnidosFil: Paviolo, Agustin Javier. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Puerto Iguazú | Universidad Nacional de Misiones. Instituto de Biología Subtropical. Instituto de Biología Subtropical - Nodo Puerto Iguazú; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Nordeste; ArgentinaFil: Ramalho, Emiliano Esterci. Institute For Conservation of The Neotropical Carnivores; Brasil. Instituto de Desenvolvimento Sustentavel Mamirauá; BrasilFil: Rösner, Sascha. Michigan State University; Estados UnidosFil: Schabo, Dana G.. Michigan State University; Estados UnidosFil: Selva, Nuria. Institute of Nature Conservation of The Polish Academy of Sciences; PoloniaFil: Sergiel, Agnieszka. Institute of Nature Conservation of The Polish Academy of Sciences; PoloniaFil: Xavier da Silva, Marina. Parque Nacional do Iguaçu; BrasilFil: Spiegel, Orr. Universitat Tel Aviv; IsraelFil: Thompson, Peter. University of Maryland; Estados UnidosFil: Ullmann, Wiebke. Universitat Potsdam; AlemaniaFil: Ziḝba, Filip. Tatra National Park; PoloniaFil: Zwijacz Kozica, Tomasz. Tatra National Park; PoloniaFil: Fagan, William F.. University of Maryland; Estados UnidosFil: Mueller, Thomas. Senckenberg Gesellschaft Für Naturforschung; . Goethe Universitat Frankfurt; AlemaniaFil: Calabrese, Justin M.. National Zoological Park; Estados Unidos. University of Maryland; Estados Unido

Evaluating expert-based habitat suitability information of terrestrial mammals with GPS-tracking data

Aim Macroecological studies that require habitat suitability data for many species often derive this information from expert opinion. However, expert-based information is inherently subjective and thus prone to errors. The increasing availability of GPS tracking data offers opportunities to evaluate and supplement expert-based information with detailed empirical evidence. Here, we compared expert-based habitat suitability information from the International Union for Conservation of Nature (IUCN) with habitat suitability information derived from GPS-tracking data of 1,498 individuals from 49 mammal species. Location Worldwide. Time period 1998-2021. Major taxa studied Forty-nine terrestrial mammal species. Methods Using GPS data, we estimated two measures of habitat suitability for each individual animal: proportional habitat use (proportion of GPS locations within a habitat type), and selection ratio (habitat use relative to its availability). For each individual we then evaluated whether the GPS-based habitat suitability measures were in agreement with the IUCN data. To that end, we calculated the probability that the ranking of empirical habitat suitability measures was in agreement with IUCN's classification into suitable, marginal and unsuitable habitat types. Results IUCN habitat suitability data were in accordance with the GPS data (> 95% probability of agreement) for 33 out of 49 species based on proportional habitat use estimates and for 25 out of 49 species based on selection ratios. In addition, 37 and 34 species had a > 50% probability of agreement based on proportional habitat use and selection ratios, respectively. Main conclusions We show how GPS-tracking data can be used to evaluate IUCN habitat suitability data. Our findings indicate that for the majority of species included in this study, it is appropriate to use IUCN habitat suitability data in macroecological studies. Furthermore, we show that GPS-tracking data can be used to identify and prioritize species and habitat types for re-evaluation of IUCN habitat suitability data

Survival and cause-specific mortality of European wildcat (Felis silvestris) across Europe

Humans have transformed most landscapes across the globe, forcing other species to adapt in order to persist in increasingly anthropogenic landscapes. Wide-ranging solitary species, such as wild felids, struggle particularly in such landscapes. Conservation planning and management for their long-term persistence critically depends on understanding what determine survival and what are the main mortality risks. We carried out the first study on annual survival and cause-specific mortality of the European wildcat with a large and unique dataset of 211 tracked individuals from 22 study areas across Europe. Furthermore, we tested the effect of environmental and human disturbance variables on the survival probability. Our results show that mortalities were mainly human-caused, with roadkill and poaching representing 57% and 22% of the total annual mortality, respectively. The annual survival probability of wildcat was 0.92 (95% CI = 0.87–0.98) for females and 0.84 (95% CI = 0.75–0.94) for males. Road density strongly impacted wildcat annual survival, whereby an increase in the road density of motorways and primary roads by 1 km/km2 in wildcat home-ranges increased mortality risk ninefold. Low-traffic roads, such as secondary and tertiary roads, did not significantly affect wildcat's annual survival. Our results deliver key input parameters for population viability analyses, provide planning-relevant information to maintain subcritical road densities in key wildcat habitats, and identify conditions under which wildcat-proof fences and wildlife crossing structures should be installed to decrease wildcat mortality.This research was funded by: the German Federal Ministry of Transport and Digital Infrastructure (BMVI) as part of the mFund project “WilDa—Dynamic Wildlife–Vehicle Collision warning, using heterogeneous traffic, accident and environmental data as well as big data concepts” grant number 19F2014B; the Deutscher Akademischer Austauschdienst (DAAD) Research Grants, Short-Term Grants, 2020 (57507441); the Deutsche Wildtier Stiftung (DeWiSt). The data from Cabañeros National Park were collected in the frame of the project OAPN 352/2011 funded by Organismo Autónomo Parques Nacionales. MM was supported by a research contract Ramón y Cajal from the MINECO (RYC-2015-19231). FDR was supported by a postdoctoral contract funded by the University of Málaga through the grants program “Ayudas para la Incorporación de Doctores del I Plan Propio de Investigación de la Universidad de Málaga (Call 2019)”. PM was supported by UIDB/50027/2020 with funding from FCT/MCTES through national funds.Peer reviewe

EFFECTIVENESS OF MITIGATION MEASURES TO REDUCE ROAD MORTALITY IN THE NETHERLANDS: BADGER MELES MELES

In the 1900‘s, the badger population of the Netherlands was estimated to count 2500 to 3000 setts with over 4000 individuals. Between then and the 1960‘s, the number declined drastically and stayed low until the mid-1980‘s with about 400 setts in the whole of the Netherlands. In the 1980‘s a high percentage of the population, locally up to 25%, was killed yearly by road traffic. For this reason the Dutch government implemented mitigation measures such as fauna tunnels and fences. It was easy to monitor the use of such measures. By census we know that the population increased to around 5000 individuals in 2006. But were these “badger tunnels” effective: did the number of traffic victims at these tunnels decrease?To answer this question we analyzed data on badger traffic victims gathered by NGO Das &amp; Boom and the Center for Transport and Navigation (Rijkswaterstaat) between 1990 and 2006. First, we determined the distribution of victims over motorways, provincial roads and local roads. In absolute terms, most victims were reported from local roads. However, relative to the length of road in the range of the badger, most victims occur at provincial roads.Second, we tested whether taking mitigating measures resulted in a decrease of traffic victims. Realization of fauna tunnels resulted in a small but significant decrease in the local number of victims, but effects varied from site to site: at most sites, the number of victims was lower, but at some the number of victims was higher after implementation of the measure. Analysis on a local scale should provide a clearer picture of the effect of mitigation measures on badger mortality. Such a study was done in the area ‘Eindegooi’ where the increase of the population of badgers is spectacular. It appears that the increase is related to a package of measures taken in that area.The challenge for conservation now lies in minimizing victim numbers at local roads. As badger victims occur over a huge length of local roads, mitigation will be difficult. Still, a number of measures are feasible, for example locally designed tunnels and fences, decreasing speed limits or closing roads for through traffic, especially at ‘black spots’ with high numbers of victims