Dutch Centre for Field Ornithology

Biodiversity monitoring at large spatial and temporal scales is essential for informing conservation policies. The International Waterbird Census (IWC) is one of the longest-running global citizen science monitoring schemes, providing critical information to several international agreements. However, analyzing IWC count data poses statistical challenges, including zero inflation, overdispersion, spatial autocorrelation, and missing data. While various modeling approaches have been used to estimate waterbird population size and trends, their ability to handle these issues and the implications for trend estimates remain unassessed. Using IWC count data from five species in the East Atlantic Flyway, we compared four modeling approaches: TRIM (TRends and Indices for Monitoring data), LORI (Low-Rank Interactions), and two generalized linear mixed models (GLMMs) with simple or optimized parametrizations. We benchmarked their performance in addressing zero inflation, overdispersion, and spatial autocorrelation across different realistic sampling designs (i.e., alternative dataset configurations). Our results highlight significant limitations in commonly used methods. Simple GLMMs, TRIM, and LORI generally failed to mitigate both zero inflation and overdispersion. In contrast, optimized GLMMs improved model convergence and better addressed these issues by selecting appropriate probability distributions. However, no single distribution performed consistently well across species and sampling designs. Spatial structures were effective in reducing spatial autocorrelation in most cases. We recommend a careful species-specific selection of statistical methods when analyzing count data, as inadequate models may misrepresent population trends and thus misguide conservation efforts. Future research should explore the integration of advanced hierarchical and spatio-temporal models to improve inference from large-scale citizen science datasets.

Abstract Highly pathogenic avian influenza (HPAI) is a threat to poultry production. It is desirable to be able to forecast HPAI outbreaks to allow for the implementation of elevated biosecurity measures. The Bird Flu Radar tool is an early warning system for HPAI based on wild bird movement and abundance. Here we develop the wild bird movement component of the Bird Flu Radar model by exploiting abundance data, which have greater spatio‐temporal coverage than movement (ring‐recovery or tracking) data. We explore two approaches for estimating bird movement from abundance data, building on recent migratory connectivity studies. In the first, week‐to‐week movement between areas of high abundance was estimated using a graph‐theoretic approach, with abundance in the intervening area also informing connectivity between locations. In the second, movement from breeding areas to wintering areas and back was simulated using an individual‐based model, the parameter values of which were calibrated for each species using weekly abundance maps. The output pseudo‐movements from the individual‐based model were easily integrated into the long‐distance movement model in the early warning system for HPAI, to update the long‐distance movement estimates for all 25 wild bird study species. Overall, we find that there are fundamental shortcomings of abundance data for inferring bird movement. However, when the accuracy of abundance‐derived pseudo‐movements can be confirmed, then they can complement ring‐recovery or tracking data. Spatio‐temporal coverage is still sparser for movement data than for abundance data, and so efforts to develop methods to exploit abundance data are likely to be useful in future endeavours estimating bird movement, and in downstream applications such as forecasting HPAI transmission.

De stijgende vraag binnen de gezondheidzorg leidt normaliter tot een stijging van de kosten. Om de betaalbaarheid en de kwaliteit van zorg voor de toekomst te kunnen garanderen, is een hoge mate van doelmatigheid noodzakelijk. Daar kan capaciteitsmanagement in belangrijke mate aan bijdragen. Capaciteitsmanagement is erop gericht om de vraag naar en het aanbod van zorg zo goed mogelijk op elkaar af te stemmen. Met capaciteitsmanagement zoeken we een goede balans tussen enerzijds een goede benutting van de beschikbare capaciteit en anderzijds een goede toegankelijkheid van de zorg. In dit hoofdstuk presenteren we een model dat op veel afdelingen toegepast kan worden om de capaciteit en de benutting ervan transparant te maken. Ter toelichting tonen we twee casussen: een unit van een afdeling Beeldvorming, de unit Magnetic Resonance Imaging (MRI), en de afdeling Centrale endoscopie.

Drone use has increased sharply worldwide over the past decade, leading to more frequent interactions with wildlife. The rapid advancement of drones for ecological monitoring and research has further contributed to these encounters, which may disturb animal behavior, such as triggering flight responses in birds. Therefore, best-practice guidelines are urgently needed to help operators and site managers minimize disturbances. This study aimed to establish safe operating distances for seven common colonial breeding bird species: black-headed gull ( Chroicocephalus ridibundus ), herring gull ( Larus argentatus ), lesser black-backed gull ( Larus fuscus ), Sandwich tern ( Thalasseus sandvicensis ), common tern ( Sterna hirundo ), Eurasian spoonbill ( Platalea leucorodia ), and great cormorant ( Phalacrocorax carbo ). We assessed the effects of professional and consumer-grade drones flying at altitudes between 5 and 50 meters on the flight responses of these species at breeding sites in the Dutch Wadden Sea. Of 1492 drone flights, 7.4% caused disturbances, defined as more than 10% of birds becoming airborne. Flight initiation distance (FID), the distance between a bird and the drone at the moment of flight response, varied by species. Sandwich terns and common terns had the largest FID (>170 m), followed by black-headed gulls (>160 m), herring gulls and lesser black-backed gulls (>60 m), while great cormorants and Eurasian spoonbills had the shortest (~5 m). When selecting drone flight locations, we recommend considering species-specific FID and using the maximum diagonal FID as a guideline. Disturbance decreases with altitude, so flights should be conducted at 50 meters or higher whenever possible. These findings provide concrete guidelines to inform policy and promote the responsible use of drones in wildlife research and management.

Human-wildlife conflicts are generally tackled using single-species studies and ensuing management solutions, ignoring species interactions that may moderate or augment these issues. We investigate the effects of interactions between four goose species foraging in the province of Friesland, the Netherlands, on species distributions, energetics, and consequent economic costs of agricultural damages and management, using an individual-based model. In Friesland, geese are allowed to graze on (semi-)natural grasslands and selected agricultural grasslands (accommodation areas), while they are scared off other agricultural grasslands (scaring areas). We show that interspecific competition and facilitation drive spatial redistribution of goose species. With increasing population sizes, most species are forced to increase foraging in the scaring areas, leading to more scaring events and more additional foraging to compensate for energy spent on fleeing behaviour. Our modelling results underline that careful consideration should be given to how management may affect the spatial distribution of foraging geese.Supplementary InformationThe online version contains supplementary material available at 10.1007/s13280-025-02206-9.

Wild birds serve as reservoirs and vectors for many different pathogens. Changes in their distribution and abundance, due to environmental change, will influence disease risk. We investigated potential changes in abundance for three commonly occurring species that are likely major drivers of a wide range of diseases: blackbirds, mallards and house sparrows. These are competent hosts for avian influenza and West Nile virus, among other pathogens. Using the Netherlands as a case study, we created random forest models for predicting the distribution and (relative) abundance of these species, both now (1991–2020) and in the future (2036–2065). The three species had different spatial distributions, largely related to their preferred habitat and food availability. In the future, mallard and house sparrow populations were predicted to increase, while there was little change for blackbirds. These changes in abundance have a potentially strong relationship with disease risk, since species abundance is linked to the size of pathogen reservoirs. We demonstrate this relationship by linking blackbird abundance to cases of Usutu virus in the Netherlands. Our work illustrates the potential value of forecasting (relative) abundance to estimate future disease risk and to assist planning of disease management actions.

Abstract Wild birds serve as reservoirs and vectors for many different pathogens and changes in their distribution and abundance due to environmental change will influence disease risk. We study three species which are highly abundant in north-western Europe and which can transmit a wide range of diseases including avian influenza and West Nile virus: blackbirds, mallards and house sparrows. Using the Netherlands as a case study, we created random forest models for predicting the distribution and abundance of these species, both now and in the future. Climate, land use and vegetative cover were all important predictors of bird abundance. The three species had different spatial distributions, largely related to their preferred habitat and food availability. In the future, mallard and house sparrow populations were predicted to increase, while there was little change for blackbirds. Quantifying the consequences of these abundance changes is complicated as there are many factors to consider, however increased pathogen reservoirs will likely increase disease risk and changes in distribution may affect local outbreak risk. The future abundance maps created in this study, and the methods used to create them, will be useful tools for disease modellers and policymakers to estimate future disease risk and to plan accordingly.

Usutu virus (USUV) is an emerging flavivirus that is maintained in an enzootic cycle with mosquitoes as vectors and birds as amplifying hosts. In Europe, the virus has caused mass mortality of wild birds, mainly among Common Blackbird (Turdus merula) populations. While mosquitoes are the primary vectors for USUV, Common Blackbirds and other avian species are exposed to other arthropod ectoparasites, such as ticks. It is unknown, however, if ticks can maintain and transmit USUV. We addressed this question using in vitro and in vivo experiments and field collected data. USUV replicated in IRE/CTVM19 Ixodes ricinus tick cells and in injected ticks. Moreover, I. ricinus nymphs acquired the virus via artificial membrane blood-feeding and maintained the virus for at least 70 days. Transstadial transmission of USUV from nymphs to adults was confirmed in 4.9% of the ticks. USUV disseminated from the midgut to the haemocoel, and was transmitted via the saliva of the tick during artificial membrane blood-feeding. We further explored the role of ticks by monitoring USUV in questing ticks and in ticks feeding on wild birds in the Netherlands between 2016 and 2019. In total, 622 wild birds and the Ixodes ticks they carried were tested for USUV RNA. Of these birds, 48 (7.7%) carried USUV-positive ticks. The presence of negative-sense USUV RNA in ticks, as confirmed via small RNA-sequencing, showed active virus replication. In contrast, we did not detect USUV in 15,381 questing ticks collected in 2017 and 2019. We conclude that I. ricinus can be infected with USUV and can transstadially and horizontally transmit USUV. However, in comparison to mosquito-borne transmission, the role of I. ricinus ticks in the epidemiology of USUV is expected to be minor.