Digital technology plays an increasingly important role in wildlife management and conservation, by enhancing monitoring capabilities and reshaping human-wildlife interactions. However, the transformative potential of these digital solutions for coexistence remains unclear. This paper presents a novel framework to assess the transformative potential of digital systems in wildlife management and conservation, focusing on two key factors: Digital Maturity, which evaluates technical sophistication of digital systems, and Systemic Depth, which measures their capacity for enabling lasting change. We used this framework to evaluate 524 studies in a systematic literature review in wildlife management and conservation, and found that although sometimes higher Digital Maturity or Systemic Depth was achieved, overall the transformative potential of applied digital systems was still low. Studies that scored high emphasize interdisciplinary collaboration, adaptability, data sharing, and technologies such as machine learning. This research highlights achieving transformative potential requires a holistic approach integrating ecological, social, and technological perspectives.

Weasel Mustela nivalis and stoat Mustela erminea are important specialist predators whose populations are suspected to be declining across Europe. Predominantly hunting rodents, they play a key role in shaping the population dynamics of small herbivorous mammals. Despite their ecological significance, these species have remained relatively understudied due to their elusive nature, and many questions regarding their ecology and conservation remain unanswered. In recent years, these small predators have attracted growing attention, supported by new methodologies that allow more effective research. In June 2025, a group of European researchers convened at the first ‘European Small Mustelid Meeting’ to assess the current state of small mustelid research, with a focus on weasels and stoats, and identify priorities for the future. Here, we synthesize the current research on weasels and stoats across Europe and propose six key directions for future small mustelid research: (1) the optimisation of monitoring techniques and data collection protocols; (2) the upscaling of species distribution models to a continental level; (3) the ecological role of small mustelids in the food web; (4) the influence of climate change on their moulting phenology; (5) the impact of environmental contaminants on small mustelids; and (6) the gathering of genetic material to analyze genetic diversity across Europe. We hope these will enable a robust assessment of the conservation status of weasels and stoats across Europe. We invite researchers working on or interested in these fascinating small predators to join our collaborative effort to advance research and conservation of small mustelids in Europe.

Drönare utrustade med termiska kameror har under senare år utvecklats till ett potentiellt verktyg för övervakning av klövvilt. Syftet med denna studie var att genomföra en första utvärdering av drönarbaserad inventering av älg för att på sikt kunna utveckla rekommendationer för en kvalitetssäkrad metodik inom svensk viltförvaltning. Studien genomfördes på uppdrag av Naturvårdsverket och omfattade inventeringar i tre studieområden i norra och mellersta Sverige. Resultaten visade att både manuella och automatiserade inventeringar med drönare kan användas för att uppskatta älgtäthet. Under de kalla och molniga vinterförhållandena som rådde vid inventeringarna skattades upptäckningsgraden till nära 100 %. Inventeringar av GPS-märkta älgar och parallella flygningar genomförda av olika piloter visade att i princip samtliga älgar som fanns inom inventeringsområdena kunde återfinnas. Simuleringar baserade på totalinventeringar visade att stickprovsbaserade inventeringar med provytor kan ge användbara täthetsskattningar, men att den nödvändiga täckningsgraden varierar beroende på hur älgarna är fördelade i landskapet. I områden där älgarna var måttligt koncentrerade i landskapet bedöms cirka 20–30 % av arealen ofta vara tillräckligt, medan upp till 50 % kan behöva inventeras i områden där älgarna uppträder mer koncentrerat. För skattning av könskvot och antal kalvar per hondjur krävs generellt större stickprov än för att enbart skatta täthet. Studien visar också att det är möjligt att bestämma kön och ålder hos observerade älgar med hjälp av zoombilder, men att detta kräver mer tid, högkvalitativ bildinsamling och erfaren bedömning. Viktiga begränsningar utgörs av väderberoende, drönarnas räckvidd och nuvarande regelverk för flygning inom synhåll (VLOS). För att möjliggöra effektiv inventering av större områden rekommenderas fortsatt utveckling av metoder för flygning bortom visuell siktlinje (BVLOS), liksom standardisering av metodik, utbildning och kvalitetssäkring. Sammantaget visar resultaten att drönare har stor potential som ett komplement till befintliga metoder för älgövervakning och viltförvaltning.

Despite extensive conservation efforts worldwide, biodiversity loss continues, particularly in tropical regions. It is, therefore, essential to develop biodiversity monitoring methods that can be effectively scaled up in both time and space, enabling wildlife managers to quickly assess and respond to changes in populations or communities. We explored the effectiveness of combining camera traps with acoustic methods to survey seed dispersing birds and mammals. We deployed arboreal and terrestrial camera traps alongside AudioMoth sound recorders with varying recording schedules to survey 220 sampling locations across five distinct sites in Madagascar’s eastern humid forests, though acoustic analyses were limited to one site. Based on all three methods (arboreal, terrestrial camera trap and AudioMoths), we successfully identified 78

Abstract Camera traps (CTs) are widely used in wildlife monitoring, but sampling design choices can introduce significant biases in trapping rates (TR) that, depending on the evaluated parameter, can be propagated to dependent estimates (e.g., density). This study evaluates the effect of camera height placement on TR across five experiments encompassing 172 paired sampling points (i.e., with a low and a high camera per point) in four biomes across Europe, North America and Africa. We analysed data of 49 vertebrate species, ranging from small mammals and birds to large ungulates and carnivores (0.013–461 kg), using generalised linear and multinomial models to assess how TR varies with body mass and camera height. Our results show that lower camera placements significantly increase TR for small (0–10 kg) and medium‐sized species (11–50 kg), while the opposite is found in larger animals. Simultaneous detections by both high‐ and low‐placed cameras increased with body mass, but small species were often missed by high cameras alone. Camera height introduces systematic biases in TR, affecting its comparability across time and space. For multispecies monitoring, lower cameras (30–50 cm above ground) offer better overall performance, though higher placements may be more suitable for large‐bodied focal species. We recommend consistent, standardised height measurements in long‐term monitoring to ensure reliable TR‐based inferences and validate the recommendation of using target species' shoulder height when monitoring single species. This study provides the most comprehensive cross‐continental evaluation of camera height effects to date and offers empirically grounded guidance for optimising sampling design in wildlife monitoring.

Climate change has reduced the duration of seasonal snow cover in many areas, leading to seasonal coat colour-changing species being colour mismatched against their environment for increasingly long periods. This mismatch in camouflage can lead to increased predation, potentially resulting in population-level effects. Here we investigate how mountain hare (Lepus timidus) camouflage is influenced by climate change-induced reductions in snow cover over a 60-year period. We quantified the degree of camouflage mismatch using multiannual (2011-2018) camera trap data from 678 camera traps spread across an environmental gradient in Norway spanning from 58° N to 69° N, and from coastal to inland areas. We coupled this camouflage data with a 60-year snow cover time series on a national scale, creating two 30-year averages of snow cover duration (1959-1988 and 1989-2018). We investigated how climate change-induced reductions in snow cover correlate with coat colour camouflage and resulting mismatch. Specifically, we analysed how mountain hare coat colour mismatch varied between camera trap locations with varying reductions in the number of snow days between the two 30-year averages. We also investigated how 2011-2018 mountain hare moult phenology compared to 1959-1966 and 2011-2018 average snow cover, respectively. Coat colour mismatch was highest in areas with the greatest reductions in the number of snow days. Additionally, 2011-2018 moult phenology better matched 1959-1966 than 2011-2018 snow patterns. Collectively, our results indicate that mountain hares are not adjusting their moult phenology fast enough to track the pace at which snow cover is declining.

Global biodiversity is declining as human impacts increase and mammals, especially carnivores, are declining particularly quickly. Small carnivores (such as in the Guloninae subfamily) are less frequently considered than large carnivores, despite also being affected by biodiversity declines, because their status and population ecology are exceedingly difficult to assess. Although all but one Guloninae species are globally listed as Least Concern by the International Union for Conservation of Nature (IUCN), this designation obscures conservation challenges and does not include local population declines. Proactive efforts to improve population persistence in regions of most concern may prevent species from becoming globally threatened in the future. We briefly introduce the 11 Guloninae species, highlight collective challenges, and synthesize possible options focused on recovery and conservation. To inform our paper, we conducted a 3-phase process to gather expert opinions: an online survey, an in-person prioritization exercise of online results, and directed in-person group discussions. We focused efforts within the international Martes Working Group consisting of species experts. We followed the IUCN and Conservation Measures Partnership (CMP) threats and actions classifications nomenclature to enable cross-project learning and data aggregation. From our results, the largest described global threat to Guloninae was ‘Climate Change’ (e.g., ecosystem encroachment; changes in temperature regimes) as most Guloninae species appear to have a narrow thermal range where persistence is possible. The largest threat at the jurisdictional level was ‘Biological Resource Use’ (e.g., hunting and collecting terrestrial animals; logging and wood harvesting). The identified action needed to further Guloninae conservation and recovery was ‘Land/Water Management’ (e.g., ecosystem and natural process re-creation; site/area stewardship). We identified unifying themes threatening and benefitting Guloninae; but given the wide geographic range of Guloninae species, the many countries involved, and the diversity of ecosystems with different levels of human impacts, conservation actions need to be locally appropriate. Our paper synthesizes natural history and guidance from experts to provide a foundation for future research efforts and conservation actions for Guloninae conservation.

Small mustelids are increasingly recognized as species requiring conservation attention. In recent years, several camera-based methodologies have been developed to study them, but studies comparing different methods are still rare. To identify the most effective method to study small mustelid populations, we compared two camera-based monitoring methods in the Italian Alps. We also examined the effects of sampling session and habitat type on the occupancy probability and tested the “umbrella effect” of these methods for rodents. After superimposing a 700 × 700 m grid on an Alpine valley (Maritime Alps Natural Park, northwestern Italy), we surveyed 36 cells over three separate 45-day sessions from June to October 2023. In each cell, we employed (1) an “Alpine Mostela”, a foldable PVC box containing a camera trap and a PVC 9 cm Ø tube, and (2) a stand-alone trail camera. All devices were located at least 150 m from the others, and salmon oil was used as bait in half of the cells. To compare the methods, we used a single-season Bayesian occupancy model. The detection probability of stoats was higher with unbaited Alpine Mostelas and baited external cameras. We found the highest occupancy probability in the second session and non-forested habitats. Bait use positively affected the number of non-target videos. In this study, unbaited Alpine Mostelas and baited external cameras demonstrated reliable performance in detecting stoats. However, with the Alpine Mostela accomplishing slightly better results with much fewer non-target videos, it emerged as the preferred choice for long-term stoat monitoring.

Camera trapping has become crucial in wildlife research, enabling detailed observations of elusive and nocturnal species with limited human interference. The use of occupancy modeling to analyze camera trap data is rapidly increasing, aiding in the assessment of species distribution, multispecies dynamics, and the presence of different states of a species (e.g., reproducing or non-reproducing), while considering imperfect detection. Multistate occupancy models, which capture these different states, are particularly effective tools. However, the design of camera trap studies-typically involving large grids with a limited number of cameras and animal observations-often results in sparse data and low detection probabilities, impacting model performance (e.g., convergence) and inference reliability (e.g., accuracy and precision) in basic occupancy models. The effect of these factors on more complex models (e.g., multistate occupancy models) remains largely unexplored. Here, we conducted a series of simulations with varying detection probabilities, numbers of sites, and survey periods for both single- and multistate occupancy models, to evaluate the impact of these factors on model performance and reliability. Our results revealed that multistate models require higher detection probabilities compared to the single-state models. Additionally, minimum needed detection probabilities decreased as the number of surveys increased for all models. Furthermore, the number of sites required was substantially higher for multistate models compared to single-state models. We conclude that when detection probabilities are low, occupancy models encounter difficulties in fitting and produce unreliable results. Strategies such as deploying clustered cameras, targeted camera placement (e.g., at frequent wildlife paths) or using bait to increase detection rates could be used to address these issues but may introduce other biases. The gained model performance from higher detection probabilities might outweigh these biases. Moreover, different data aggregation strategies in combination with increasing the length of the study can increase detection probabilities, addressing reliability issues; however, this is not always feasible due to time constraints (e.g., season-based research questions). This study highlights key thresholds and considerations for improving the use of multistate occupancy models using camera trap data, aiding in the design of more effective wildlife research studies.

1. Land use changes in Europe contribute to the decline of once-abundant species. While these declines are well documented for some species, other, more elusive species could quietly disappear. As a result, small mustelids are believed to be declining across their historical range. Their small size and elusive ecology make small mustelids challenging to monitor and thus remain understudied. In this study, we tested the effectiveness of three camera trap-based methods to monitor common weasel Mustela nivalis, stoat Mustela erminea, and European polecat Mustela putorius. 2. We deployed unenclosed, semi-enclosed, and fully enclosed camera traps in a clustered design incorporating all methods during the fall of 2023 in two extensive agricultural areas in the Netherlands. Using a multi-scale occupancy approach, we assessed (1) how detection probabilities differ among the three camera trap methods for each small mustelid species and (2) how scent-based lures and placement near passages influenced detection probabilities. 3. We found that weasels had the highest detection probability in fully enclosed camera traps placed within clusters containing a scent-based lure. The detection probability of stoats was highest in fully enclosed camera traps, regardless of the presence or absence of lure, as well as in unenclosed camera traps with no lure nearby. Polecats had the highest detection probability in unenclosed camera traps, regardless of lure presence, and in semi-enclosed camera traps without lure nearby. Placing camera traps near passages increased detection probability for all three species. 4. Practical implication: This study advances monitoring protocols for small mustelids, a group facing suspected population declines despite limited data. We highlight different detection probabilities among three mustelid species using various camera-trap methods. Camera trap placement and species-specific use of scent-based lures, beneficial for weasels but not for stoats or polecats, should be considered by researchers and wildlife managers. Combining fully enclosed and unenclosed camera traps enhances species detection and offers broader ecological insights by monitoring other prey and predator mammals as bycatch. Our findings provide practical guidance for large-scale monitoring efforts of small mustelids across Europe.

Camera traps have transformed the way we monitor wildlife and are now routinely used to address questions from a wide range of ecological and conservation aspects. Sampling design optimization and a better understanding of drivers determining the precision of detection rates (i.e. the number of detections per unit of effort) are important methodological issues. Little attention has been focused on the effect of placing more than one camera on each sampling point (hereafter, clustered design), and/or rotating (i.e. redeploying) the cameras to new placements during the sampling period. We explored the differences in the precision of detection rates between clustered vs. single camera designs when cameras remained in the same location during the study. Furthermore, the effect of keeping the placement of cameras fixed or rotating them (i.e. moving them to new locations during the sampling period), when a limited number of camera devices are available, was also evaluated. We used simulations and field data to test differences in detection rate precision for the different sampling designs. We simulated three different population distributions (random, trail-based and aggregated) and three abundance scenarios. The simulations were validated with a field experiment focused on eight species with different behavioural traits, including artiodactyls, carnivores, lagomorphs, and birds. When a fixed number of sampling points were monitored simultaneously, clustered designs generally resulted in an increase in the precision of detection rates compared to single designs. The absolute reduction in the coefficient of variation by clustered designs was on average 0.07 units (min: 0.01, max: 0.15), which represents an average relative reduction in CV of 31% (min:6%, max:44%). An improvement in precision was also observed as a higher number of sampling points was used for all population distributions and sampling designs tested. When a fixed number of cameras were available, rotating the cameras to independent locations improved precision (an absolute reduction of 0.19 CV units) when monitoring aggregated populations, but not for random and trail-based population distributions. Synthesis and applications: Our research provides a guideline for wildlife managers and researchers to improve the precision of camera trap detection rates and optimize resource allocation. In general, the study design should accommodate the behaviour of the target species (e.g. spatial aggregation and abundance), monitoring program logistic resources (both human and economic) and study area characteristics (e.g. accessibility and vandalism).

1. Weasels (genus Mustela and Neogale) are of management concern as declining native species in some regions and invasive species in others. Regardless of the need to conserve or remove weasels, there is increasingly a need to use non-invasive monitoring methods to assess population trends.2. We conducted a literature review and held the first ever International Weasel Monitoring Symposium to synthesise information on historical and current non-invasive monitoring techniques for weasels. We also explored current limitations, opportunities, and areas of development to guide future research and long-term monitoring.3. Our literature search revealed that in the past 20 years, camera traps were the most commonly used non-invasive monitoring method (62% of studies), followed by track plates or scent stations designed to collect footprints (23%) and walking transects for tracks in snow or soil (8.7%).4. Experts agreed that the most promising non-invasive monitoring techniques available include use of citizen scientist reporting, detection dogs, detecting tracks, non-invasive genetic surveys, and enclosed or unenclosed camera trap systems. Because each technique has benefits and limitations, using a multi-method approach is likely required.5. There is a need for strong commitment to dedicated monitoring that is replicated over space and time such that trend data can be ascertained to better inform future management action. The diversity of non-invasive monitoring methods now available makes such monitoring possible with relatively minor commitments of funding and effort.

Fires can strongly change the vegetation structure and the availability of resources for wildlife, but fire suppression has long affected the natural role of fire in shaping boreal ecosystems in northern Europe. Recently, wildfires have increased in frequency, possibly due to global warming. In contrast to the boreal systems in North America, there have been few studies on responses of wildlife to wildfires in northern Europe. Based on the findings from North America, we predict that responses of wildlife to wildfire vary among wildlife species: where mammalian herbivores, such as moose Alces alces and mountain hare Lepus timidus, will be attracted to burnt areas following an increase in food availability, other species, such as reindeer Rangifer tarandus, are negatively impacted due to fire reducing their preferred food. We then tested our predictions by contrasting wildlife utilization of sites that burnt by wildfire in 2006 with nearby unburnt control sites in three areas in northern Sweden. To measure wildlife utilization, we used 72 camera traps, equally divided between the burnt and control sites, with two placement strategies: random and on wildlife trails. The cameras recorded 27 mammal and bird species during summer 2018. Species assemblage differed between burnt and control sites. Fieldfare Turdus pilaris used burnt sites more than control sites, while pine marten Martes martes and western capercaillie Tetrao urogallus used control sites more than burnt sites. We however did not find support for a positive effect of past forest fires on any of the observed wild mammals. We discuss how, due to the impact of forestry, forage-rich habitat may not be as limiting in Scandinavia as in the North-American context, potentially leading to recently burnt sites being less attractive to herbivores such as moose.

Wildlife must adapt to human presence to survive in the Anthropocene, so it is critical to understand species responses to humans in different contexts. We used camera trapping as a lens to view mammal responses to changes in human activity during the COVID-19 pandemic. Across 163 species sampled in 102 projects around the world, changes in the amount and timing of animal activity varied widely. Under higher human activity, mammals were less active in undeveloped areas but unexpectedly more active in developed areas while exhibiting greater nocturnality. Carnivores were most sensitive, showing the strongest decreases in activity and greatest increases in nocturnality. Wildlife managers must consider how habituation and uneven sensitivity across species may cause fundamental differences in human–wildlife interactions along gradients of human influence.

Habitat fragmentation is often highlighted as a driver of tick-borne disease hazard and spillover risk via reduction in biodiversity. However, habitat fragmentation can have divergent impacts on host, vector, and pathogen dynamics depending on the distribution of fragment sizes and the levels of connectivity to surrounding habitat, particularly when habitat fragments are embedded in an urban matrix. We examine how extreme habitat fragmentation influences host community composition in an urban landscape and determine its cascading impacts on Ixodes scapularis vector abundance and infection prevalence with human pathogenic Borrelia burgdorferi , Babesia microti , and Anaplasma phagocytophilum . We utilize camera–trapping and live mammal–trapping methods to quantify the availability of vertebrate hosts to questing larval ticks and relate relative host activity to the resulting density of nymphs and nymphal infection prevalence; the combination of these metrics determines the tick–borne disease hazard (i.e. the density of infected questing nymphs — DIN). We found that increased habitat connectivity in urban areas shifted the composition of the host community from human–adapted to forest–dependent species, species which inhabit forested habitats for all or a portion of their lifecycles. The resulting increased encounter probability between ticks and forest–dependent species increased the density of nymphs and nymphal infection prevalence with host–limited pathogens, B. microti and A. phagocytophilum , amplifying local tick-borne disease hazard. Host encounter probability of all species examined did not increase B. burgdorferi nymphal infection prevalence, likely due to the wider host range of this pathogen; whereas increased deer encounter probability decreased the nymphal infection prevalence of B. burgdorferi . These findings emphasize the importance of host identity, rather than host diversity, in shaping the heterogenous distribution of tick–borne pathogen risk in highly fragmented urban forest patches and suggest a non–linear association between disease risk and host biodiversity. ### Competing Interest Statement The authors have declared no competing interest.

Agroecosystems are experiencing a biodiversity crisis. Biodiversity monitoring is needed to inform conservation, but existing monitoring schemes lack standardisation and are biased towards birds, insects and plants. Automated monitoring techniques offer a promising solution, but while passive acoustic monitoring and remote sensing are increasingly used, the potential of camera traps (CTs) in farmland remains underexplored. We reviewed CT publications from the last 30 years and found only 59 articles that sampled farmland habitats in Europe. The main research topics addressed management or (avian) conservation issues, such as monitoring wildlife-livestock interactions, nest predation, and the use of feeders and water troughs. Fewer studies employed landscape-wide approaches to investigate species' habitat use or activity patterns over large agricultural areas. We discuss existing barriers to a more widespread use of CTs in farmland and suggest strategies to overcome them: boxed CTs tailored for small mammals, reptiles and amphibians, perch-mounted CTs for raptor monitoring and time-lapse imagery can help in overcoming the technical challenges of monitoring (small) elusive species in open habitats where misfires and missed detections are more frequent. Such approaches would also expand the taxonomic coverage of farmland monitoring schemes towards under-surveyed species and species groups. Moreover, the engagement of farmers in CT-based biodiversity monitoring programmes and advances in computer vision for image classification provide opportunities for low-cost, broad-scale and automated monitoring schemes. Research priorities that could be tackled through such CT applications include basic science topics such as unravelling animal space use in agricultural landscapes, and how this is influenced by varying agricultural practices. Management-related research priorities relate to crop damage and livestock predation by wildlife, disease transmission between wildlife and livestock, effects of agrochemicals on wildlife, and the monitoring and assessment of conservation measures. Altogether, CTs hold great, yet unexplored, potential to advance agroecological research. La biodiversit & agrave; degli ecosistemi agricoli & egrave; fortemente impoverita. Il monitoraggio della biodiversit & agrave; & egrave; fondamentale per informare ed attuare i piani di conservazione, ma gli schemi di monitoraggio esistenti non sono standardizzati e si concentrano su un numero limitato di specie, principalmente uccelli, insetti e piante. Le tecniche di monitoraggio automatizzato offrono una soluzione promettente, ma sebbene il monitoraggio acustico passivo e il telerilevamento siano sempre pi & ugrave; utilizzati, l'impiego di fototrappole in terreni agricoli ha un potenziale ancora poco esplorato. Abbiamo esaminato la letteratura scientifica degli ultimi 30 anni e abbiamo individuato soltanto 59 studi in cui il fototrappolaggio & egrave; stato utilizzato per monitorare la fauna selvatica in ambienti agricoli in Europa. I principali argomenti di ricerca riguardavano problemi gestionali o di conservazione della biodiversit & agrave; (soprattutto aviaria), come il monitoraggio delle interazioni tra fauna selvatica e bestiame domestico, la predazione dei nidi di uccelli e l'uso di mangiatoie e abbeveratoi da parte di animali selvatici. Un numero minore di studi ha utilizzato una prospettiva paesaggistica per indagare l'uso dell'habitat e i pattern di attivit & agrave; delle specie in regioni agricole estese. In questo articolo discutiamo gli ostacoli che possono aver impedito un uso pi & ugrave; diffuso delle fototrappole in ambiente agricolo e proponiamo delle strategie per superarli: l'allestimento di fototrappole 'in scatola' su misura per piccoli mammiferi, rettili e anfibi, e di fototrappole montate su trespoli per monitorare i rapaci, ed il fototrappolaggio in time-lapse sono alcune delle soluzioni alle sfide tecniche del monitoraggio di (piccole) specie elusive in spazi aperti, dove l'attivazione erronea o la mancata attivazione delle fototrappole & egrave; frequente. Questi approcci potrebbero contribuire ad ampliare la copertura tassonomica dei programmi di monitoraggio in ambienti agricoli, includendo specie finora poco studiate. Inoltre, il coinvolgimento degli agricoltori in programmi di fototrappolaggio e l'applicazione di sistemi di visione artificiale per la classificazione automatizzata delle foto consentirebbero di monitorare a basso costo, su larga scala, e con pipeline automatizzate. Tali applicazioni offrono importanti opportunit & agrave; di ricerca, consentendo, ad esempio, una comprensione pi & ugrave; approfondita dell'ecologia spaziale dell'agrobiodiversit & agrave; animale e di come questa sia influenzata da diverse pratiche agricole, di studiare i danni alle colture e la predazione del bestiame da parte della fauna selvatica, di monitorare la trasmissione di malattie tra animali selvatici e bestiame, di valutare l'impatto dei prodotti agrochimici sulla fauna selvatica e di verificare l'efficacia delle misure di conservazione della biodiversit & agrave;. Alla luce di queste osservazioni, le fototrappole costituiscono una valida risorsa, finora poco sfruttata, per favorire il progresso della ricerca agroecologica.

Abstract Camera trapping has revolutionized wildlife ecology and conservation by providing automated data acquisition, leading to the accumulation of massive amounts of camera trap data worldwide. Although management and processing of camera trap‐derived Big Data are becoming increasingly solvable with the help of scalable cyber‐infrastructures, harmonization and exchange of the data remain limited, hindering its full potential. There is currently no widely accepted standard for exchanging camera trap data. The only existing proposal, “Camera Trap Metadata Standard” (CTMS), has several technical shortcomings and limited adoption. We present a new data exchange format, the Camera Trap Data Package (Camtrap DP), designed to allow users to easily exchange, harmonize and archive camera trap data at local to global scales. Camtrap DP structures camera trap data in a simple yet flexible data model consisting of three tables (Deployments, Media and Observations) that supports a wide range of camera deployment designs, classification techniques (e.g., human and AI, media‐based and event‐based) and analytical use cases, from compiling species occurrence data through distribution, occupancy and activity modeling to density estimation. The format further achieves interoperability by building upon existing standards, Frictionless Data Package in particular, which is supported by a suite of open software tools to read and validate data. Camtrap DP is the consensus of a long, in‐depth, consultation and outreach process with standard and software developers, the main existing camera trap data management platforms, major players in the field of camera trapping and the Global Biodiversity Information Facility (GBIF). Under the umbrella of the Biodiversity Information Standards (TDWG), Camtrap DP has been developed openly, collaboratively and with version control from the start. We encourage camera trapping users and developers to join the discussion and contribute to the further development and adoption of this standard.

Species composition and densities of wild ungulate communities in Europe have changed over the last decades. As ungulates play an important role in the life-cycle of the tick species Ixodes ricinus, these changes could affect both the life-cycle of I. ricinus and the transmission of tick-borne pathogens like Borrelia burgdorferi (s.l.) and Anaplasma phagocytophilum. Due to morphological and behavioural differences among the ungulate species, these species might have different effects on the densities of questing I. ricinus, either directly through a bloodmeal or indirectly via the impact of ungulates on rodent numbers via the vegetation. In this study, we aimed to investigate these direct and indirect effects of five different ungulate species, fallow deer (Dama dama), roe deer (Capreolus capreolus), red deer (Cervus elaphus), moose (Alces alces), and wild boar (Sus scrofa), on the presence and abundance of I. ricinus ticks. In the summer of 2019, on 20 1 × 1 km transects in south-central Sweden that differed in ungulate community composition, we collected data on tick presence and abundance (by dragging a cloth), ungulate community composition (using camera traps), vegetation height (using the drop-disc method), temperature above field layer and rodent abundance (by snap-trapping). Using generalized linear mixed models we did not find any associations between vegetation height and tick presence/abundance or ungulate visitation frequencies, or between ungulate visitation frequencies and the presence/abundance of questing I. ricinus. The power of our analyses was, however, low due to very low tick and rodent numbers. We did find a negative association between adult ticks and air temperature, where we were more likely to find adult ticks if temperature in the field layer was lower. We conclude that more elaborate long-term studies are needed to elucidate the investigated associations. Such future studies should differentiate among the potential impacts of different ungulate species instead of treating all ungulate species as one group.

Information on the presence and abundance of a species is crucial for understanding key ecological processes but also for effective protection and population management. Collecting data on cryptic species, like small mustelids, is particularly challenging and often requires the use of non-invasive methods. Despite recent progress in the development of camera trap-based devices and statistical models to estimate the abundance of unmarked individuals, their application for studying this group of mammals is still very limited. We compared direct (live-trapping) and indirect (an enclosed camera-trapping approach—the Mostela system) survey methods to estimate the population size of weasels ( Mustela nivalis ) inhabiting open grasslands in Northeast Poland over a period of four years. We also live-trapped voles to determine prey availability. We used a Royle–Nichols model to estimate yearly (relative) abundance from the camera-trapping data in a Bayesian framework. The total number of live-captured weasels showed a similar change over time as the relative abundance of weasels estimated using camera-trap data. Moreover, estimates of weasel abundance increased with the availability of their main prey. Our study is part of a growing body of work showing that camera traps can provide a useful non-invasive method to estimate the relative abundance of small mustelids. Moreover, a combination of data from camera traps with statistical models allowed us to track the changes in weasel number over time. This information could be very useful for the conservation of small mustelids as well as their management in regions where they are invasive.