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Aim Ecological data collected by the general public are valuable for addressing a wide range of ecological research and conservation planning, and there has been a rapid increase in the scope and volume of data available. However, data from eBird or other large‐scale projects with volunteer observers typically present several challenges that can impede robust ecological inferences. These challenges include spatial bias, variation in effort and species reporting bias. Innovation We use the example of estimating species distributions with data from eBird, a community science or citizen science (CS) project. We estimate two widely used metrics of species distributions: encounter rate and occupancy probability. For each metric, we critically assess the impact of data processing steps that either degrade or refine the data used in the analyses. CS data density varies widely across the globe, so we also test whether differences in model performance are robust to sample size. Main conclusions Model performance improved when data processing and analytical methods addressed the challenges arising from CS data; however, the degree of improvement varied with species and data density. The largest gains we observed in model performance were achieved with 1) the use of complete checklists (where observers report all the species they detect and identify, allowing non‐detections to be inferred) and 2) the use of covariates describing variation in effort and detectability for each checklist. Occupancy models were more robust to a lack of complete checklists. Improvements in model performance with data refinement were more evident with larger sample sizes. In general, we found that the value of each refinement varied by situation and we encourage researchers to assess the benefits in other scenarios. These approaches will enable researchers to more effectively harness the vast ecological knowledge that exists within CS data for conservation and basic research.

Aim The Area of Occupancy (AOO) of a species is often utilized to assess extinction risk for determining IUCN Red List status. However, the recommended raw‐counts method of summing occupied grid cells likely reflects only sampling effort, as the majority of species have not been sampled across their entire range at the fine grains required by IUCN. More accurate measurements can be generated at coarser grains (so‐called atlas data) as false absences are reduced. If we fit the occupancy‐area relationship to these data, we can extrapolate the relationship down to estimate occupancy at finer grains. Numerous models have been proposed to carry out such occupancy downscaling, but have only been tested on a limited range of species. Methods We test the ability of downscaling models to recover fine grain AOO against the raw‐counts method for 28,900 virtual species with a wide range of prevalence and aggregation characteristics, subsampled to reflect common spatial biases in sampling effort. We address several questions for ensuring accurate downscaling: How to generate accurate atlas data? How far can we accurately extrapolate the occupancy‐area relationship given perfect data? Can occupancy downscaling overcome false absences at fine grain sizes? And how does sampling bias and coverage affect accuracy? Results Downscaling was more accurate than the raw‐counts method in all scenarios except where sampling coverage was very high and/or the sampling bias was positively related to the species distribution. However, if atlas data contained many false absences, then even downscaling under‐estimated actual occupancy. Main conclusions Occupancy downscaling has the potential to be a useful tool for estimating AOO for IUCN Red List assessments, especially when sampling coverage is low and the currently recommended method is ineffective. However, its application should be tailored to the species’ characteristics, as well as the sampling coverage and bias of the species’ records.

Bayesian population models can be exceedingly slow due, in part, to the choice to simulate discrete latent states. Here, we discuss an alternative approach to discrete latent states, marginalization, that forms the basis of maximum likelihood population models and is much faster. Our manuscript has two goals: (1) to introduce readers unfamiliar with marginalization to the concept and provide worked examples and (2) to address topics associated with marginalization that have not been previously synthesized and are relevant to both Bayesian and maximum likelihood models. We begin by explaining marginalization using a Cormack- Jolly-Seber model. Next, we apply marginalization to multistate capture–recapture, community occupancy, and integrated population models and briefly discuss random effects, priors, and pseudo-R². Then, we focus on recovery of discrete latent states, defining different types of conditional probabilities and showing how quantities such as population abundance or species richness can be estimated in marginalized code. Last, we show that occupancy and site-abundance models with auto-covariates can be fit with marginalized code with minimal impact on parameter estimates. Marginalized code was anywhere from five to >1,000 times faster than discrete code and differences in inferences were minimal. Discrete latent states and fully conditional approaches provide the best estimates of conditional probabilities for a given site or individual. However, estimates for parameters and derived quantities such as species richness and abundance are minimally affected by marginalization. In the case of abundance, marginalized code is both quicker and has lower bias than an N-augmentation approach. Understanding how marginalization works shrinks the divide between Bayesian and maximum likelihood approaches to population models. Some models that have only been presented in a Bayesian framework can easily be fit in maximum likelihood. On the other hand, factors such as informative priors, random effects, or pseudo-R² values may motivate a Bayesian approach in some applications. An understanding of marginalization allows users to minimize the speed that is sacrificed when switching from a maximum likelihood approach. Widespread application of marginalization in Bayesian population models will facilitate more thorough simulation studies, comparisons of alternative model structures, and faster learning.

A necessary component of elimination programmes for wildlife disease is effective surveillance. The ability to distinguish between disease freedom and non‐detection can mean the difference between a successful elimination campaign and new epizootics. Understanding the contribution of different surveillance methods helps to optimize and better allocate effort and develop more effective surveillance programmes. We evaluated the probability of rabies virus elimination (disease freedom) in an enzootic area with active management using dynamic occupancy modelling of 10 years of raccoon rabies virus (RABV) surveillance data (2006–2015) collected from three states in the eastern United States. We estimated detection probability of RABV cases for each surveillance method (e.g. strange acting reports, roadkill, surveillance‐trapped animals, nuisance animals and public health samples) used by the USDA National Rabies Management Program. Strange acting, found dead and public health animals were the most likely to detect RABV when it was present, and generally detectability was higher in fall–winter compared to spring–summer. Found dead animals in fall–winter had the highest detection at 0.33 (95% CI: 0.20, 0.48). Nuisance animals had the lowest detection probabilities (~0.02). Areas with oral rabies vaccination (ORV) management had reduced occurrence probability compared to enzootic areas without ORV management. RABV occurrence was positively associated with deciduous and mixed forests and medium to high developed areas, which are also areas with higher raccoon (Procyon lotor) densities. By combining occupancy and detection estimates we can create a probability of elimination surface that can be updated seasonally to provide guidance on areas managed for wildlife disease. Synthesis and applications. Wildlife disease surveillance is often comprised of a combination of targeted and convenience‐based methods. Using a multi‐method analytical approach allows us to compare the relative strengths of these methods, providing guidance on resource allocation for surveillance actions. Applying this multi‐method approach in conjunction with dynamic occupancy analyses better informs management decisions by understanding ecological drivers of disease occurrence.

Aim Recent studies suggest insect declines in parts of Europe; however, the generality of these trends across different taxa and regions remains unclear. Standardized data are not available to assess large‐scale, long‐term changes for most insect groups but opportunistic citizen science data are widespread for some. Here, we took advantage of citizen science data to investigate distributional changes of Odonata. Location Germany. Methods We compiled over 1 million occurrence records from different regional databases. We used occupancy‐detection models to account for imperfect detection and estimate annual distributions for each species during 1980–2016 within 5 × 5 km quadrants. We also compiled data on species attributes that were hypothesized to affect species’ sensitivity to different drivers and related them to the changes in species’ distributions. We further developed a novel approach to cluster groups of species with similar patterns of distributional change to represent multispecies indicators. Results More species increased (45%) than decreased (29%) or remained stable (26%) in their distribution (i.e. number of occupied quadrants). Species showing increases were generally warm‐adapted species and/or running water species, while species showing decreases were cold‐adapted species using standing water habitats such as bogs. Time series clustering defined five main patterns of change—each associated with a specific combination of species attributes, and confirming the key roles of species’ temperature and habitat preferences. Overall, our analysis predicted that mean quadrant‐level species richness has increased over most of the time period. Main conclusions Trends in Odonata provide mixed news—improved water quality, coupled with positive impacts of climate change, could explain the positive trends of many species. At the same time, declining species point to conservation challenges associated with habitat loss and degradation. Our study demonstrates the great value of citizen science and the work of natural history societies for assessing large‐scale distributional change.

Carnivore guilds play a vital role in ecological communities by cascading trophic effects, energy and nutrient transfer, and stabilizing or destabilizing food webs. Consequently, the structure of carnivore guilds can be critical to ecosystem patterns. Body size is a crucial influence on intraguild interactions, because it affects access to prey resources, effectiveness in scramble competition, and vulnerability to intraguild predation. Coyotes (Canis latrans), bobcats (Lynx rufus), gray foxes (Urocyon cinereoargenteus), raccoons (Procyon lotor), red foxes (Vulpes vulpes), and striped skunks (Mephitis mephitis) occur sympatrically throughout much of North America and overlap in resource use, indicating potential for interspecific interactions. Although much is known about the autecology of the individual species separately, little is known about factors that facilitate coexistence and how interactions within this guild influence distribution, habitat use, and temporal activity of the smaller carnivores. To assess how habitat autecology and interspecific interactions affect the structure of this widespread carnivore guild, we conducted a large-scale, non-invasive carnivore survey using an occupancy modeling framework. We deployed remote cameras during 3-week surveys to detect carnivores at 1,118 camera locations in 357 2.6-km2 sections (3–4 cameras/section composing a cluster) in the 16 southernmost counties of Illinois (16,058 km2) during January–April, 2008–2010. We characterized microhabitat at each camera location and landscape-level habitat features for each camera cluster. In a multistage approach, we used information-theoretic methods to evaluate competing models for detection, species-specific habitat occupancy, multispecies co-occupancy, and multiseason (colonization and extinction) occupancy dynamics. We developed occupancy models for each species to represent hypothesized effects of anthropogenic features, prey availability, landscape complexity, and vegetative land cover. We quantified temporal activity patterns of each carnivore species based on their frequency of appearance in photographs. Further, we assessed whether smaller carnivores shifted their diel activity patterns in response to the presence of potential competitors. Of the 102,711 photographs of endothermic animals, we recorded photographs of bobcats (n = 412 photographs), coyotes (n = 1,397), gray foxes (n = 546), raccoons (n = 40,029), red foxes (n = 149), and striped skunks (n = 2,467). Bobcats were active primarily during crepuscular periods, and their activity was reduced with precipitation and higher temperatures. The probability of detecting bobcats decreased after a bobcat photograph was recorded, suggesting avoidance of remote cameras after the first encounter. Across southern Illinois, bobcat occupancy at the camera-location and camera-cluster scale (ψ̂local = 0.24 ± 0.04, camera cluster ψ̂cluster = 0.75 ± 0.06) was negatively influenced by anthropogenic features and infrastructure. Bobcats had high rates of colonization (γ̂ = 0.86) and low rates of extinction (ε̂ = 0.07), suggesting an expanding population, but agricultural land was less likely to be colonized. Nearly all camera clusters were occupied by coyotes (ψ̂cluster = 0.95 ± 0.03). At the local scale, coyote occupancy (ψ̂local = 0.58 ± 0.03) was higher in hardwood forest stands with open understories than in other areas. Compared to coyotes, gray foxes occupied a smaller portion of the study area (ψ̂local = 0.13 ± 0.01, ψ̂cluster = 0.29 ± 0.03) at all scales. At the scale of the camera cluster, gray fox occupancy was highest in fragmented areas with high proportions of forest, and positively related to anthropogenic features within 100% home-range buffers. Red foxes occupied a similar proportion of the study area as gray foxes (ψ̂local = 0.12 ± 0.02, ψ̂cluster = 0.26 ± 0.04) but were more closely associated with anthropogenic features. Only anthropogenic feature models made up the 90% confidence set at all scales of analysis for red foxes. Extinction probabilities at the scale of the camera cluster were higher for both gray foxes (ε̂ = 0.57) and red foxes (ε̂ = 0.35) than their colonization rates (gray fox γ̂ = 0.16, red fox γ̂ = 0.06), suggesting both species may be declining in southern Illinois. Striped skunks occupied a large portion of the study area (ψ̂local = 0.47 ± 0.01, ψ̂cluster = 0.79 ± 0.03) and were associated primarily with anthropogenic features. Raccoons were essentially ubiquitous within the study area, being photographed in 99% of camera clusters. We observed little evidence for spatial partitioning based on interspecific interactions, with the exception of the gray fox-coyote pairs, and found that habitat preferences were more important in structuring the carnivore community. Habitat had a stronger influence on the occupancy of foxes than did the presence of bobcats. However, the level of red fox activity was negatively correlated with bobcat activity. Gray fox occupancy and the number of detections within occupied sites were reduced in camera clusters occupied by coyotes but not bobcat occupancy. Overall, gray fox occupancy was highest at camera locations with fewer hardwood and more conifer trees. However, gray foxes were more likely to occupy camera locations in hardwood stands than conifer stands if coyotes were also present indicating that hardwood stands may enhance gray fox-coyote coexistence. The 2 fox species appeared to co-occur with each other at the local scale more frequently than expected based on their individual selection of habitat. Similarly, occupancy of camera location by red foxes was higher when coyotes were present. These positive spatial associations among canids may be a response to locally high prey abundance or unmeasured habitat variables. Activity levels of raccoons, bobcats, and coyotes were all positively correlated. Overall, our co-occurrence and activity models indicate competitor-driven adjustments in space use among members of a carnivore community might be the exception rather than the norm. Nevertheless, although our results indicate that gray foxes and red foxes currently coexist with bobcats and coyotes, their distribution appears to be contracting on our study area. Coexistence of foxes with larger carnivores may be enhanced by temporal partitioning of activity and by habitat features that reduce vulnerability of intraguild predation. For instance, hardwood stands may contain trees with structure that enhances tree-climbing by gray foxes, a behavior that probably facilitates coexistence with coyotes. Efforts to enhance gray fox populations would likely benefit from increasing the amount of mature oakhickory forest. Additionally, the varying results from different scales of analyses underscore the importance of considering multiple spatial scales in carnivore community studies. Los gremios de carnívoros desempeñan un papel vital en las comunidades ecológicas causando efectos tróficos en cascada, afectando la transferencia de energía y nutrientes, y estabilizando o desestabilizando las redes alimentarias. En consecuencia, la estructura de los gremios de carnívoros puede ser crítica para los patrones de los ecosistemas. El tamaño corporal tiene una influencia crucial en las interacciones intragremio, ya que afecta el acceso a los recursos de presa, la eficacia en la competencia por explotación, y la vulnerabilidad a depredación intragremio. Los coyotes (Canis latrans), linces (Lynx rufus), zorros grises (Urocyon cinereoargenteus), mapaches (Procyon lotor), el zorro (Vulpes vulpes), y zorrillos rayados (Mephitis mephitis) occurren en simpatría en gran parte de América del Norte y se solapan en los recursos que utilizan, lo que indica un potencial para interacciones interespecíficas. Aunque se sabe mucho sobre la autoecología de las especies individuales por separado, poco se sabe acerca de los factores que facilitan la coexistencia y cómo las interacciones dentro de este gremio influencian la distribución, uso de hábitat, y actividad temporal de los carnívoros más pequeños. Para evaluar cómo la autecología del hábitat y las interacciones interespecíficas afectan la estructura de este gremio carnívoro de amplia distribución, realizamos un muestreo de carnívoros no invasivo a gran escala, utilizando un marco de modelos de ocupación. Instalamos cámaras remotas en muestreos de 3 semanas para detectar carnívoros en 1118 locaciones-cámara en 357 secciones de 2.6 km2 (3–4 cámaras / sección conformaron una agrupación) en los 16 condados de más al sur de Illinois (16058 km2) entre enero y abril de 2008–2010. Caracterizamos el microhábitat en cada locación-cámara y las características del hábitat a nivel de paisaje para cada agrupación de cámaras. Con un enfoque de etapas múltiples, utilizamos métodos de teoría de información para evaluar modelos competitivos de detección, ocupación del hábitat de especies específicas, co-ocupación multi-especies, y dinámicas de ocupación multi-especies y multi-estación (colonización y extinción). Desarrollamos modelos de ocupación para cada especie para representar efectos hipotéticos de características antropogénicas, disponibilidad de presas, complejidad del paisaje, y cobertura vegetal. Cuantificamos los patrones de actividad temporal de cada especie carnívora en función de su frecuencia de aparición en fotografías. Además, evaluamos si los carnívoros más pequeños cambian sus patrones de actividad diaria en respuesta a la presencia de competidores potenciales. De las 102711 fotografías de animales endotérmicos, registramos fotografías de linces (n = 412 fotografías), coyotes (n = 1397), zorros grises (n = 546), mapaches (n = 40029), zorros rojos (n = 149), y zorrillos rayados (n = 2467). Los linces estuvieron activos principalmente durante períodos crepusculares, y su actividad se redujo con la precipitación y altas temperaturas. La probabilidad de detectar linces disminuyó después de reg

Competition is a widespread interaction among carnivores, ultimately manifested through one or more dimensions of the species' ecological niche. One of the most explicit manifestations of competitive interactions regards spatial displacement. Its interpretation under a theoretical context provides an important tool to deepen our understanding of biological systems and communities, but also for wildlife management and conservation. We used Bayesian multispecies occupancy models on camera-trapping data from multiple sites in Southwestern Europe (SWE) to investigate competitive interactions within a carnivore guild, and to evaluate how species' ecological traits are shaping coexistence patterns. Seventeen out of 26 pairwise interactions departed from a hypothesis of independent occurrence, with spatial association being twice as frequent as avoidance. Association behaviors were only detected among mesocarnivores, while avoidance mainly involved mesocarnivores avoiding the apex predator (n = 4) and mesocarnivore-only interactions (n = 2). Body mass ratios, defined as the dominant over the subordinate species body mass, revealed an important negative effect (β̂ = −0.38; CI95 = −0.81 to −0.06) on co-occurrence probability, and support that spatially explicit competitive interactions are mostly expressed by larger species able to dominate over smaller ones, with a threshold in body mass ratios of ∼4, above which local-scale intraguild coexistence is unlikely. We found a weak relationship between pairwise trophic niche overlap and the probability of coexistence (β̂ = −0.19; CI95 = −0.58 to 0.21), suggesting that competition for feeding resources may not be a key driver of competition, at least at the scale of our analysis. Despite local-scale avoidance, regional-scale coexistence appears to be maintained by the spatial structuring of the competitive environment. We provide evidence that SWE ecosystems consist of spatially structured competitive environments, and propose that coexistence among near-sized species is likely achieved through the interplay of “facultative” and “behavioral” character displacements. Factors influencing carnivore coexistence likely include context-dependent density and trait-mediated effects, which should be carefully considered for a sound understanding of the mechanisms regulating these communities.

1. Cities are rapidly expanding world-wide and there is an increasing urgency to protect urban biodiversity, principally through the provision of suitable habitat, most of which is in urban green spaces. Despite this, clear guidelines of how to reverse biodiversity loss or increase it within a given urban green space is lacking. 2. We examined the taxa- and species-specific responses of five taxonomically and functionally diverse animal groups to three key attributes of urban green space vegetation that drive habitat quality and can be manipulated over time: the density of large native trees, volume of understorey vegetation and percentage of native vegetation. 3. Using multi-species occupancy-detection models, we found marked differences in the effect of these vegetation attributes on bats, birds, bees, beetles and bugs. At the taxa-level, increasing the volume of understorey vegetation and percentage of native vegetation had uniformly positive effects. We found 30-120% higher occupancy for bats, native birds, beetles and bugs with an increase in understorey volume from 10% to 30%, and 10-140% higher occupancy across all native taxa with an increase in the proportion of native vegetation from 10% to 30%. However, increasing the density of large native trees had a mostly neutral effect. At the species-specific level, the majority of native species responded strongly and positively to increasing understorey volume and native vegetation, whereas exotic bird species had a neutral response. 4. Synthesis and applications. We found the probability of occupancy of most species examined was substantially reduced in urban green spaces with sparse understorey vegetation and few native plants. Our findings provide evidence that increasing understorey cover and native plantings in urban green spaces can improve biodiversity outcomes. Redressing the dominance of simplified and exotic vegetation present in urban landscapes with an increase in understorey vegetation volume and percentage of native vegetation will benefit a broad array of biodiversity.

PurposePridopidine is an investigational drug for Huntington disease (HD). Pridopidine was originally thought to act as a dopamine stabilizer. However, pridopidine shows highest affinity to the sigma-1 receptor (S1R) and enhances neuroprotection via the S1R in preclinical studies. Using [18F] fluspidine and [18F] fallypride PET, the purpose of this study was to assess in vivo target engagement/receptor occupancy of pridopidine to the S1R and dopamine D2/D3 receptor (D2/D3R) at clinical relevant doses in healthy volunteers (HVs) and as proof-of-concept in a small number of patients with HD.MethodsUsing [18F] fluspidine PET (300 MBq, 0–90 min), 11 male HVs (pridopidine 0.5 to 90 mg; six dose groups) and three male patients with HD (pridopidine 90 mg) were investigated twice, without and 2 h after single dose of pridopidine. Using [18F] fallypride PET (200 MBq, 0–210 min), four male HVs were studied without and 2 h following pridopidine administration (90 mg). Receptor occupancy was analyzed by the Lassen plot.ResultsS1R occupancy as function of pridopidine dose (or plasma concentration) in HVs could be described by a three-parameter Hill equation with a Hill coefficient larger than one. A high degree of S1R occupancy (87% to 91%) was found throughout the brain at pridopidine doses ranging from 22.5 to 90 mg. S1R occupancy was 43% at 1 mg pridopidine. In contrast, at 90 mg pridopidine, the D2/D3R occupancy was only minimal (~ 3%).ConclusionsOur PET findings indicate that at clinically relevant single dose of 90 mg, pridopidine acts as a selective S1R ligand showing near to complete S1R occupancy with negligible occupancy of the D2/D3R. The dose S1R occupancy relationship suggests cooperative binding of pridopidine to the S1R. Our findings provide significant clarification about pridopidine’s mechanism of action and support further use of the 45-mg twice-daily dose to achieve full and selective targeting of the S1R in future clinical trials of neurodegenerative disorders.Clinical Trials.gov Identifier: NCT03019289 January 12, 2017; EUDRA-CT-Nr. 2016-001757-41.