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The extraordinary number of species in the tropics when compared to the extra-tropics is probably the most prominent and consistent pattern in biogeography, suggesting that overarching processes regulate this diversity gradient. A major challenge to characterizing which processes are at play relies on quantifying how the frequency and determinants of tropical and extra-tropical speciation, extinction, and dispersal events shaped evolutionary radiations. We address this question by developing and applying spatiotemporal phylogenetic and paleontological models of diversification for tetrapod species incorporating paleoenvironmental variation. Our phylogenetic model results show that area, energy, or species richness did not uniformly affect speciation rates across tetrapods and dispute expectations of a latitudinal gradient in speciation rates. Instead, both neontological and fossil evidence coincide in underscoring the role of extra-tropical extinctions and the outflow of tropical species in shaping biodiversity. These diversification dynamics accurately predict present-day levels of species richness across latitudes and uncover temporal idiosyncrasies but spatial generality across the major tetrapod radiations. 

Growing threats to biodiversity demand timely, detailed information on species occurrence, diversity and abundance at large scales. Camera traps (CTs), combined with computer vision models, provide an efficient method to survey species of certain taxa with high spatio-temporal resolution. We test the potential of CTs to close biodiversity knowledge gaps by comparing CT records of terrestrial mammals and birds from the recently released Wildlife Insights platform to publicly available occurrences from many observation types in the Global Biodiversity Information Facility. In locations with CTs, we found they sampled a greater number of days (mean = 133 versus 57 days) and documented additional species (mean increase of 1% of expected mammals). For species with CT data, we found CTs provided novel documentation of their ranges (93% of mammals and 48% of birds). Countries with the largest boost in data coverage were in the historically underrepresented southern hemisphere. Although embargoes increase data providers' willingness to share data, they cause a lag in data availability. Our work shows that the continued collection and mobilization of CT data, especially when combined with data sharing that supports attribution and privacy, has the potential to offer a critical lens into biodiversity. This article is part of the theme issue ‘Detecting and attributing the causes of biodiversity change: needs, gaps and solutions’. 

Abstract AimSpecies distribution models (SDMs) that integrate presence‐only and presence–absence data offer a promising avenue to improve information on species' geographic distributions. The use of such ‘integrated SDMs’ on a species range‐wide extent has been constrained by the often limited presence–absence data and by the heterogeneous sampling of the presence‐only data. Here, we evaluate integrated SDMs for studying species ranges with a novel expert range map‐based evaluation. We build new understanding about how integrated SDMs address issues of estimation accuracy and data deficiency and thereby offer advantages over traditional SDMs. LocationSouth and Central America. Time Period1979–2017. Major Taxa StudiedHummingbirds. MethodsWe build integrated SDMs by linking two observation models – one for each data type – to the same underlying spatial process. We validate SDMs with two schemes: (i) cross‐validation with presence–absence data and (ii) comparison with respect to the species' whole range as defined with IUCN range maps. We also compare models relative to the estimated response curves and compute the association between the benefit of the data integration and the number of presence records in each data set. ResultsThe integrated SDM accounting for the spatially varying sampling intensity of the presence‐only data was one of the top performing models in both model validation schemes. Presence‐only data alleviated overly large niche estimates, and data integration was beneficial compared to modelling solely presence‐only data for species which had few presence points when predicting the species' whole range. On the community level, integrated models improved the species richness prediction. Main ConclusionsIntegrated SDMs combining presence‐only and presence–absence data are successfully able to borrow strengths from both data types and offer improved predictions of species' ranges. Integrated SDMs can potentially alleviate the impacts of taxonomically and geographically uneven sampling and to leverage the detailed sampling information in presence–absence data. 

Abstract Species occurrence data are foundational for research, conservation, and science communication, but the limited availability and accessibility of reliable data represents a major obstacle, particularly for insects, which face mounting pressures. We presentBeeBDC, a newRpackage, and a global bee occurrence dataset to address this issue. We combined >18.3 million bee occurrence records from multiple public repositories (GBIF, SCAN, iDigBio, USGS, ALA) and smaller datasets, then standardised, flagged, deduplicated, and cleaned the data using the reproducibleBeeBDC R-workflow. Specifically, we harmonised species names (following established global taxonomy), country names, and collection dates and, we added record-level flags for a series of potential quality issues. These data are provided in two formats, “cleaned” and “flagged-but-uncleaned”. TheBeeBDCpackage with online documentation provides end users the ability to modify filtering parameters to address their research questions. By publishing reproducibleRworkflows and globally cleaned datasets, we can increase the accessibility and reliability of downstream analyses. This workflow can be implemented for other taxa to support research and conservation. 

A high-resolution map of ant diversity allows an assessment of how well biodiversity centers overlap across taxa. 

Abstract MotivationTrait‐based studies remain limited by the quality and scope of the underlying trait data available. Most of the existing trait databases treat species traits as fixed across time, with any potential temporal variation in the measured traits being unavailable. This is despite the fact that many species are well known to show plasticity in their trait characteristics over the course of the year. This data paper describes a compilation of species‐specific dietary preferences and their known intra‐annual variation for over 10,000 of the world's extant bird species (SAviTraits 1.0). Information on dietary preferences was obtained from the Cornell Lab of Ornithology Birds of the World (BOW) online database. Textual descriptions of species' dietary preferences were translated into semi‐quantitative information denoting the proportion of dietary categories utilized by each species. Temporal variation in dietary attributes was captured at a monthly temporal resolution. We describe the methods for data discovery and translation and present tools for summarizing the annual variability of avian dietary preferences. Altogether, we were able to document a seasonal variability in dietary attributes for a total of 1031 species (ca. 10%). For the remaining species, the dietary attributes were either temporally stationary or the information on temporal variability of the diet was not available. Main Types of Variable ContainedTemporally‐varying dietary traits for birds. Spatial Location and GrainN/A. Time Period and GrainVariation in diet was captured at a monthly temporal resolution. Major Taxa and Level of MeasurementBirds, species level. Software Format.csv/.rds