Transient species occur infrequently in a community over time and do not maintain viable local populations. Because transient species interact differently than non-transients with their biotic and abiotic environment, it is important to characterize the prevalence of these species and how they impact our understanding of ecological systems. We quantified the prevalence and impact of transient species in communities using data on over 19,000 community time series spanning an array of ecosystems, taxonomic groups, and spatial scales. We found that transient species are a general feature of communities regardless of taxa or ecosystem. The proportion of these species decreases with increasing spatial scale leading to a need to control for scale in comparative work. Removing transient species from analyses influences the form of a suite of commonly studied ecological patterns including species-abundance distributions, species-energy relationships, species-area relationships, and temporal turnover. Careful consideration should be given to whether transient species are included in analyses depending on the theoretical and practical relevance of these species for the question being studied.

Aim We examined the relative importance of competitor abundance and environmental variables in determining the species distributions of 175 bird species across North America. Unlike previous studies, which tend to model distributions in terms of presence and absence, we take advantage of a geographically extensive dataset of community time series to model the temporal occupancy of species at sites throughout their expected range. Location North America. Time period 2001–2015. Major taxa studied One hundred and seventy‐five bird species. Methods We calculated variation in temporal occupancy across species’ geographic ranges and used variance partitioning and Bayesian hierarchical models to evaluate the relative importance of (a) the abundance of potential competitors and (b) the environment (elevation, temperature, precipitation, vegetation index) for determining temporal occupancy. We also created a null model to test whether designated competitor species predicted variation in temporal occupancy better than non‐competitor species. Results On average, the environment explained more variance in temporal occupancy than competitor abundance, but this varied by species. For certain species, competitor abundance explained more variance than the environment. Migrant species with smaller range sizes and greater range overlap with competitors had a higher proportion of variance explained by competitor abundance than the environment. The abundance of competitor species had a stronger effect on focal species temporal occupancy than non‐competitor species in the null model. Main conclusions Temporal occupancy represents an underutilized method for describing species distributions that is complementary to presence/absence or abundance. Geographic variation in temporal occupancy was explained by both biotic and abiotic drivers, and abiotic drivers explained more variation in temporal occupancy than abundance on average. Species traits also play a role in determining whether variation in temporal occupancy is best explained by biotic or abiotic drivers. The results of our study can improve species distribution models, particularly by accounting for competitive interactions.

Introduction: Romiplostim has been approved in Europe since 2009 to treat patients with chronic primary immune thrombocytopenia (ITP). Using real-world data from seven European countries, we measured the effectiveness and safety outcomes within 24 weeks following romiplostim initiation by duration of ITP: less than 3 months (''newly diagnosed''), 3--12 months (''persistent''), and more than 12 months (''chronic''). Methods: Adults with ITP and C 1 romiplostim administration between 2009 and 2012 were included. Endpoints included durable platelet response, median platelet count, rescue therapy, bleeding and adverse events. We used inverse probability of censoring weighted esti-Supplementary Information The online version contains supplementary material available at

28Aim 29We examined the relative importance of competitor abundance and environmental variables in 30 determining the species distributions of 175 bird species across North America. Unlike previous 31 studies, which tend to model distributions in terms of presence and absence, we take advantage 32 of a geographically extensive dataset of community time series to model the temporal occupancy 33 of species at sites throughout their expected range. 34Location 35 North America. 36 37 2001-2015. 38 Major taxa studied 39 175 bird species. 40 Time period Methods 41We calculated variation in temporal occupancy across geographic range and used variance 42 partitioning and Bayesian hierarchical models to evaluate the relative importance of 1) the 43 abundance of potential competitors and 2) the environment (elevation, temperature, precipitation, 44 vegetation index) for determining temporal occupancy. We also created a null model to test 45 3 whether designated competitor species predicted variation in occupancy better than non-46 competitor species. 47 Results 48On average, the environment explained more variance in occupancy than competitor abundance, 49 but this varied by species. For certain species, competitor abundance explained more variance 50 than the environment. Species with larger range sizes, larger range overlap with competitors, and 51 that occurred at higher mean temperatures had a higher proportion of variance explained by the 52 environment than competitor abundance. The abundance of competitor species had a stronger 53 effect on focal species occupancy than non-competitor species in the null model. 54 Main conclusions 55Temporal occupancy represents a new way of describing species distributions that is 56 complementary to presence/absence or abundance. Geographic variation in temporal occupancy 57 was explained by both biotic and abiotic drivers, and abiotic drivers explained more variation in 58 temporal occupancy than abundance on average. Species traits also play a role in determining 59 whether variation in temporal occupancy is best explained by biotic or abiotic drivers. The 60 results of our study can improve species distribution models, particularly by accounting for 61 competitive interactions. 62 63 keywords: competition, environmental filtering, occupancy, spatial scale, species distribution, 64 species interactions 65 66 67 68

One of the primary methods for classifying a species range is the species distribution model (SDM), which predicts where species are most likely to occur based on a set of environmental factors (Freeman &