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Costa Rica has benefited from effective vaccination campaigns to eliminate canine rabies virus infections. Still, the virus has endured, spread by vampire bats (Desmodus rotundus) to cattle, with rare but [...]

The close phylogenetic relationship between humans and great apes results in similarities in infection susceptibility and a high potential for pathogen exchange (2,2). Despite this zoonotic potential, previous studies of [...]

Brain atlases are important reference resources for accurate anatomical description of neuroscience data. Open access, three-dimensional atlases serve as spatial frameworks for integrating experimental data and defining regions-of-interest in analytic workflows. However, naming conventions, parcellation criteria, area definitions, and underlying mapping methodologies differ considerably between atlases and across atlas versions. This lack of standardized description impedes use of atlases in analytic tools and registration of data to different atlases. To establish a machine-readable standard for representing brain atlases, we identified four fundamental atlas elements, defined their relations, and created an ontology model. Here we present our Atlas Ontology Model (AtOM) and exemplify its use by applying it to mouse, rat, and human brain atlases. We discuss how AtOM can facilitate atlas interoperability and data integration, thereby increasing compliance with the FAIR guiding principles. AtOM provides a standardized framework for communication and use of brain atlases to create, use, and refer to specific atlas elements and versions. We argue that AtOM will accelerate analysis, sharing, and reuse of neuroscience data.

The Hawaiian Islands have been identified as a global biodiversity hotspot. We examine the Normalized Difference Vegetation Index (NDVI) using Climate Data Records products (0.05 × 0.05°) to identify significant differences in NDVI between neutral El Niño-Southern Oscillation years (1984, 2019) and significant long-term changes over the entire time series (1982-2019) for the Hawaiian Islands and six land cover classes. Overall, there has been a significant decline in NDVI (i.e., browning) across the Hawaiian Islands from 1982 to 2019 with the islands of Lānai and Hawaii experiencing the greatest decreases in NDVI (≥44%). All land cover classes significantly decreased in NDVI for most months, especially during the wet season month of March. Native vegetation cover across all islands also experienced significant declines in NDVI, with the leeward, southwestern side of the island of Hawaii experiencing the greatest declines. The long-term trends in the annual total precipitation and annual mean Palmer Drought Severity Index (PDSI) for 1982-2019 on the Hawaiian Islands show significant concurrent declines. Primarily positive correlations between the native ecosystem NDVI and precipitation imply that significant decreases in precipitation may exacerbate the decrease in NDVI of native ecosystems. NDVI-PDSI correlations were primarily negative on the windward side of the islands and positive on the leeward sides, suggesting a higher sensitivity to drought for leeward native ecosystems. Multi-decadal time series and spatially explicit data for native landscapes provide natural resource managers with long-term trends and monthly changes associated with vegetation health and stability.

Biodiversity monitoring is an almost inconceivable challenge at the scale of the entire Earth. The current (and soon to be flown) generation of spaceborne and airborne optical sensors (i.e., imaging spectrometers) can collect detailed information at unprecedented spatial, temporal, and spectral resolutions. These new data streams are preceded by a revolution in modeling and analytics that can utilize the richness of these datasets to measure a wide range of plant traits, community composition, and ecosystem functions. At the heart of this framework for monitoring plant biodiversity is the idea of remotely identifying species by making use of the 'spectral species' concept. In theory, the spectral species concept can be defined as a species characterized by a unique spectral signature and thus remotely detectable within pixel units of a spectral image. In reality, depending on spatial resolution, pixels may contain several species which renders species-specific assignment of spectral information more challenging. The aim of this paper is to review the spectral species concept and relate it to underlying ecological principles, while also discussing the complexities, challenges and opportunities to apply this concept given current and future scientific advances in remote sensing.

The challenge of defining and cataloging the building blocks of the brain requires a standardized approach to naming neurons and organizing knowledge about their properties. The US Brain Initiative Cell Census Network, Human Cell Atlas, Blue Brain Project, and others are generating vast amounts of data and characterizing large numbers of neurons throughout the nervous system. The neuroscientific literature contains many neuron names (e.g. parvalbumin-positive interneuron or layer 5 pyramidal cell) that are commonly used and generally accepted. However, it is often unclear how such common usage types relate to many evidence-based types that are proposed based on the results of new techniques. Further, comparing different types across labs remains a significant challenge. Here, we propose an interoperable knowledge representation, the Neuron Phenotype Ontology (NPO), that provides a standardized and automatable approach for naming cell types and normalizing their constituent phenotypes using identifiers from community ontologies as a common language. The NPO provides a framework for systematically organizing knowledge about cellular properties and enables interoperability with existing neuron naming schemes. We evaluate the NPO by populating a knowledge base with three independent cortical neuron classifications derived from published data sets that describe neurons according to molecular, morphological, electrophysiological, and synaptic properties. Competency queries to this knowledge base demonstrate that the NPO knowledge model enables interoperability between the three test cases and neuron names commonly used in the literature.

The stimulating peripheral activity to relieve conditions (SPARC) program is a US National Institutes of Health-funded effort to improve our understanding of the neural circuitry of the autonomic nervous system (ANS) in support of bioelectronic medicine. As part of this effort, the SPARC project is generating multi-species, multimodal data, models, simulations, and anatomical maps supported by a comprehensive knowledge base of autonomic circuitry. To facilitate the organization of and integration across multi-faceted SPARC data and models, SPARC is implementing the findable, accessible, interoperable, and reusable (FAIR) data principles to ensure that all SPARC products are findable, accessible, interoperable, and reusable. We are therefore annotating and describing all products with a common FAIR vocabulary. The SPARC Vocabulary is built from a set of community ontologies covering major domains relevant to SPARC, including anatomy, physiology, experimental techniques, and molecules. The SPARC Vocabulary is incorporated into tools researchers use to segment and annotate their data, facilitating the application of these ontologies for annotation of research data. However, since investigators perform deep annotations on experimental data, not all terms and relationships are available in community ontologies. We therefore implemented a term management and vocabulary extension pipeline where SPARC researchers may extend the SPARC Vocabulary using InterLex, an online vocabulary management system. To ensure the quality of contributed terms, we have set up a curated term request and review pipeline specifically for anatomical terms involving expert review. Accepted terms are added to the SPARC Vocabulary and, when appropriate, contributed back to community ontologies to enhance ANS coverage. Here, we provide an overview of the SPARC Vocabulary, the infrastructure and process for implementing the term management and review pipeline. In an analysis of >300 anatomical contributed terms, the majority represented composite terms that necessitated combining terms within and across existing ontologies. Although these terms are not good candidates for community ontologies, they can be linked to structures contained within these ontologies. We conclude that the term request pipeline serves as a useful adjunct to community ontologies for annotating experimental data and increases the FAIRness of SPARC data.

Abstract: Southern California is a biodiversity hotspot and home to over 23 million people. Over recent decades the annual wildfire area in the coastal southern California region has not significantly changed. Yet how fire regime will respond to future anthropogenic climate change remains an important question. Here, we estimate wildfire probability in southern California at station scale and daily resolution using random forest algorithms and downscaled earth system model simulations. We project that large fire days will increase from 36 days/year during 1970–1999 to 58 days/year under moderate greenhouse gas emission scenario (RCP4.5) and 71 days/year by 2070–2099 under a high emission scenario (RCP8.5). The large fire season will be more intense and have an earlier onset and delayed end. Our findings suggest that despite the lack of a contemporary trend in fire regime, projected greenhouse gas emissions will substantially increase the fire danger in southern California by 2099.

There is a debate concerning the definition and extent of tropical dry forest biome and vegetation type at a global spatial scale. We identify the potential extent of the tropical dry forest biome based on bioclimatic definitions and climatic data sets to improve global estimates of distribution, cover, and change. We compared four bioclimatic definitions of the tropical dry forest biome-Murphy and Lugo, Food and Agriculture Organization (FAO), DryFlor, aridity index-using two climatic data sets: WorldClim and Climatologies at High-resolution for the Earth's Land Surface Areas (CHELSA). We then compared each of the eight unique combinations of bioclimatic definitions and climatic data sets using 540 field plots identified as tropical dry forest from a literature search and evaluated the accuracy of World Wildlife Fund tropical and subtropical dry broadleaf forest ecoregions. We used the definition and climate data that most closely matched field data to calculate forest cover in 2000 and change from 2001 to 2020. Globally, there was low agreement (< 58%) between bioclimatic definitions and WWF ecoregions and only 40% of field plots fell within these ecoregions. FAO using CHELSA had the highest agreement with field plots (81%) and was not correlated with the biome extent. Using the FAO definition with CHELSA climatic data set, we estimate 4,931,414 km2 of closed canopy (≥ 40% forest cover) tropical dry forest in 2000 and 4,369,695 km2 in 2020 with a gross loss of 561,719 km2 (11.4%) from 2001 to 2020. Tropical dry forest biome extent varies significantly based on bioclimatic definition used, with nearly half of all tropical dry forest vegetation missed when using ecoregion boundaries alone, especially in Africa. Using site-specific field validation, we find that the FAO definition using CHELSA provides an accurate, standard, and repeatable way to assess tropical dry forest cover and change at a global scale.

Aim: Palms are an iconic, diverse and often abundant component of tropical ecosystems that provide many ecosystem services. Being monocots, tree palms are evolutionarily, morphologically and physiologically distinct from other trees, and these differences have important consequences for ecosystem services (e.g., carbon sequestration and storage) and in terms of responses to climate change. We quantified global patterns of tree palm relative abundance to help improve understanding of tropical forests and reduce uncertainty about these ecosystems under climate change. Location: Tropical and subtropical moist forests. Time period: Current. Major taxa studied: Palms (Arecaceae). Methods: We assembled a pantropical dataset of 2,548 forest plots (covering 1,191 ha) and quantified tree palm (i.e., ≥10 cm diameter at breast height) abundance relative to co-occurring non-palm trees. We compared the relative abundance of tree palms across biogeographical realms and tested for associations with palaeoclimate stability, current climate, edaphic conditions and metrics of forest structure. Results: On average, the relative abundance of tree palms was more than five times larger between Neotropical locations and other biogeographical realms. Tree palms were absent in most locations outside the Neotropics but present in >80% of Neotropical locations. The relative abundance of tree palms was more strongly associated with local conditions (e.g., higher mean annual precipitation, lower soil fertility, shallower water table and lower plot mean wood density) than metrics of long-term climate stability. Life-form diversity also influenced the patterns; palm assemblages outside the Neotropics comprise many non-tree (e.g., climbing) palms. Finally, we show that tree palms can influence estimates of above-ground biomass, but the magnitude and direction of the effect require additional work. Conclusions: Tree palms are not only quintessentially tropical, but they are also overwhelmingly Neotropical. Future work to understand the contributions of tree palms to biomass estimates and carbon cycling will be particularly crucial in Neotropical forests.

People plant, remove, and manage urban vegetation in cities for varying purposes and to varying extents. The direct manipulation of plants affects the benefits people receive from plants. In synthesizing several studies of urban biodiversity in Los Angeles, we find that cultivated plants differ from those in remnant natural areas. This highlights the importance of studying cultivated plants in cities, which is crucial for the design and planning of sustainable cities. Residents have created a new urban biome in Los Angeles, and this has consequences for associated organisms, ultimately resulting in a responsibility for society to determine what type of biome we wish to create. Summary Urbanization is a large driver of biodiversity globally. Within cities, urban trees, gardens, and residential yards contribute extensively to plant biodiversity, although the consequences and mechanisms of plant cultivation for biodiversity are uncertain. We used Los Angeles, California, USA as a case study for investigating plant diversity in cultivated areas. We synthesized datasets quantifying the diversity of urban trees, residential yards, and community gardens in Los Angeles, the availability of plants from nurseries, and residents’ attitudes about plant attributes. Cultivated plant diversity was drastically different from remnant natural areas; compared to remnant natural areas, cultivated areas contained more exotic species, more than double the number of plant species, and turnover in plant functional trait distributions. In cultivated areas, most plants were intentionally planted and dominated by exotic species planted for ornamental purposes. Most tree species sampled in Los Angeles were available for sale in local nurseries. Residents’ preferences for specific plant traits were correlated with the trait composition of the plant community, suggesting cultivated plant communities at least partially reflect resident preferences. Our findings demonstrate the importance of cultivated species in a diverse megacity that are driven in part through commercial distribution. The cultivation of plants in Los Angeles greatly increases regional plant biodiversity through changes in species composition and functional trait distributions. The pervasive presence of cultivated species likely has many consequences for residents and the ecosystem services they receive compared with unmanaged or remnant urban areas.

The Research Resource Identifier (RRID) was introduced in 2014 to better identify biomedical research resources and track their use across the literature, including key digital resources such as databases and software. Authors include an RRID after the first mention of any resource used. Here, we provide an overview of RRIDs and analyze their use for digital resource identification. We quantitatively compare the output of our RRID curation workflow with the outputs of automated text mining systems used to identify resource mentions in text. The results show that authors follow RRID reporting guidelines well, and that our natural language processing based text mining was able to identify nearly all of the resources identified by RRIDs as well as thousands more. Finally, we demonstrate how RRIDs and text mining can complement each other to provide a scalable solution to digital resource citation.

Understanding the Tibetan Plateau’s role in environmental change has gained increasing scientificattention in light of warming and changes in landmanagement. We examine changes in greenness overthe Tibetan Plateau using the Normalized Difference Vegetation Index (NDVI) from the Global InventoryMonitoring and Modeling Study (GIMMS3g) to identify significant changes over the entire plateau, sixecoregions, and protected areas based on a multiyear time series of July imagery from 1982 to 2015. Wealso test whether there have been changes in human populations in protected areas. There has beenrelatively little change in mean NDVI over the Tibetan Plateau or ecoregions, however, there weresignificant changes at the pixel level. There are sixty-nine protected areas on the Tibetan Plateau; sixtytwoprotected areas had no significant change in mean NDVI and seven protected areas experienceda significant increase in NDVI. There has been an increase in population within protected areas from2000 to 2015; however, mean populations significantly increased in two protected areas and significantlydecreased in four protected areas. Results suggest a slow greening of the Tibetan Plateau,ecoregions, and protected areas, with a more rapid greening in northern Tibet at the pixel level. Mostprotected areas are experiencing minor changes in NDVI independent of human population.

Water utilities incentivize turf replacement to promote water conservation, but the effects of such programs have received limited evaluations. In 2014, the Metropolitan Water District of Southern California (MWD) undertook an unprecedented investment to incentive turf replacement throughout Southern California in response to a serious Statewide drought. MWD devoted $350 million to the program, resulting in more than 46,000 rebate payments (25,000 in Los Angeles County) to remove 15.3 million square meters of turf. The program implementation provided a unique opportunity to address research gaps on turf replacement implementation. We analyzed socioeconomic and spatial trends of program participants and assessed landscape changes from turf replacement using a random sample of properties (4% of LA County participants in 2014–16). Specifically, we used a novel and cost-effective approach Google Earth Street View to characterize landscapes in front yards and created a typology of land cover types. Results showed: post-replacement landscapes had a diversity of land cover types – diverse yards with several land cover types, as well as more homogenous yards with a single land cover such as woodchips, bare soil, gravel, and artificial turf. Analysis also indicated some evidence of “neighborhood adoption” effects. We describe the need for longitudinal studies to understand long-term effects of turf replacement and associated water use, and suggest that water utilities should also evaluate results in backyards, which requires site visits. This study provides a novel contribution that can be replicated over space and time to further knowledge of turf replacement program implementations and evaluation.

Acute water shortages for large metropolitan regions are likely to become more frequent as climate changes impact historic precipitation levels and urban population grows. California and Los Angeles County have just experienced a severe four year drought followed by a year of high precipitation, and likely drought conditions again in Southern California. We show how the embedded preferences for distant sources, and their local manifestations, have created and/or exacerbated fluctuations in local water availability and suboptimal management. As a socio technical system, water management in the Los Angeles metropolitan region has created a kind of scarcity lock-in in years of low rainfall. We come to this through a decade of coupled research examining landscapes and water use, the development of the complex institutional water management infrastructure, hydrology and a systems network model. Such integrated research is a model for other regions to unpack and understand the actual water resources of a metropolitan region, how it is managed and potential ability to become more water self reliant if the institutions collaborate and manage the resource both parsimoniously, but also in an integrated and conjunctive manner. The Los Angeles County metropolitan region, we find, could transition to a nearly water self sufficient system.

The use of misidentified and contaminated cell lines continues to be a problem in biomedical research. Research Resource Identifiers (RRIDs) should reduce the prevalence of misidentified and contaminated cell lines in the literature by alerting researchers to cell lines that are on the list of problematic cell lines, which is maintained by the International Cell Line Authentication Committee (ICLAC) and the Cellosaurus database. To test this assertion, we text-mined the methods sections of about two million papers in PubMed Central, identifying 305,161 unique cell-line names in 150,459 articles. We estimate that 8.6% of these cell lines were on the list of problematic cell lines, whereas only 3.3% of the cell lines in the 634 papers that included RRIDs were on the problematic list. This suggests that the use of RRIDs is associated with a lower reported use of problematic cell lines.

Abstract: The Third Pole (TP) is experiencing rapid warming and is currently in its warmest period in the past 2,000 years. This paper reviews the latest development in multidisciplinary TP research associated with this warming. The rapid warming facilitates intense and broad glacier melt over most of the TP, although some glaciers in the northwest are advancing. By heating the atmosphere and reducing snow/ice albedo, aerosols also contribute to the glaciers melting. Glacier melt is accompanied by lake expansion and intensification of the water cycle over the TP. Precipitation has increased over the eastern and northwestern TP. Meanwhile, the TP is greening and most regions are experiencing advancing phenological trends, although over the southwest there is a spring phenological delay mainly in response to the recent decline in spring precipitation. Atmospheric and terrestrial thermal and dynamical processes over the TP affect the Asian monsoon at different scales. Recent evidence indicates substantial roles that mesoscale convective systems play in the TP’s precipitation as well as an association between soil moisture anomalies in the TP and the Indian monsoon. Moreover, an increase in geohazard events has been associated with recent environmental changes, some of which have had catastrophic consequences caused by glacial lake outbursts and landslides. Active debris flows are growing in both frequency of occurrences and spatial scale. Meanwhile, new types of disasters, such as the twin ice avalanches in Ali in 2016, are now appearing in the region. Adaptation and mitigation measures should be taken to help societies’ preparation for future environmental challenges. Some key issues for future TP studies are also discussed.

Bartonella, the causative agent of bartonellosis, is a genus of gram-negative bacteria. Bartonellosis causes a range of symptoms from severe to life-threatening (e.g., endocarditis and meningitis). Clinical syndromes from Bartonella [...]

Background: Tracking the spread of antibiotic resistant bacteria is critical to reduce global morbidity and mortality associated with human and animal infections. There is a need to understand the role that wild animals in maintenance and transfer of antibiotic resistance genes (ARGs). Methods: This study used metagenomics to identify and compare the abundance of bacterial species and ARGs detected in the gut microbiomes from sympatric humans and wild mouse lemurs in a forest-dominated, roadless region of Madagascar near Ranomafana National Park. We examined the contribution of human geographic location toward differences in ARG abundance and compared the genomic similarity of ARGs between host source microbiomes. Results: Alpha and beta diversity of species and ARGs between host sources were distinct but maintained a similar number of detectable ARG alleles. Humans were differentially more abundant for four distinct tetracycline resistance-associated genes compared to lemurs. There was no significant difference in human ARG diversity from different locations. Human and lemur microbiomes shared 14 distinct ARGs with highly conserved in nucleotide identity. Synteny of ARG-associated assemblies revealed a distinct multidrug-resistant gene cassette carrying dfrA1 and aadA1 present in human and lemur microbiomes without evidence of geographic overlap, suggesting that these resistance genes could be widespread in this ecosystem. Further investigation into intermediary processes that maintain drug-resistant bacteria in wildlife settings is needed. [ABSTRACT FROM AUTHOR]

AIM: Seasonally dry tropical forest (SDTF) of the Caribbean Islands (primarily West Indies) is floristically distinct from Neotropical SDTF in Central and South America. We evaluate whether tree species composition was associated with climatic gradients or geographical distance. Turnover (dissimilarity) in species composition of different islands or among more distant sites would suggest communities structured by speciation and dispersal limitations. A nested pattern would be consistent with a steep resource gradient. Correlation of species composition with climatic variation would suggest communities structured by broad‐scale environmental filtering. LOCATION: The West Indies (The Bahamas, Cuba, Hispaniola, Jamaica, Puerto Rico, US Virgin Islands, Guadeloupe, Martinique, St. Lucia), Providencia (Colombia), south Florida (USA) and Florida Keys (USA). TAXON: Seed plants—woody taxa (primarily trees). METHODS: We compiled 572 plots from 23 surveys conducted between 1969 and 2016. Hierarchical clustering of species in plots, and indicator species analysis for the resulting groups of sites, identified geographical patterns of turnover in species composition. Nonparametric analysis of variance, applied to principal components of bioclimatic variables, determined the degree of covariation in climate with location. Nestedness versus turnover in species composition was evaluated using beta diversity partitioning. Generalized dissimilarity modelling partitioned the effect of climate versus geographical distance on species composition. RESULTS: Despite a set of commonly occurring species, SDTF tree community composition was distinct among islands and was characterized by spatial turnover on climatic gradients that covaried with geographical gradients. Greater Antillean islands were characterized by endemic indicator species. Northern subtropical areas supported distinct, rather than nested, SDTF communities in spite of low levels of endemism. MAIN CONCLUSIONS: The SDTF species composition was correlated with climatic variation. SDTF on large Greater Antillean islands (Hispaniola, Jamaica and Cuba) was characterized by endemic species, consistent with their geological history and the biogeography of plant lineages. These results suggest that both environmental filtering and speciation shape Caribbean SDTF tree communities.

Knowledge about the biogeographic affinities of the world's tropical forests helps to better understand regional differences in forest structure, diversity, composition, and dynamics. Such understanding will enable anticipation of region-specific responses to global environmental change. Modern phylogenies, in combination with broad coverage of species inventory data, now allow for global biogeographic analyses that take species evolutionary distance into account. Here we present a classification of the world's tropical forests based on their phylogenetic similarity. We identify five principal floristic regions and their floristic relationships: (i) Indo-Pacific, (ii) Subtropical, (iii) African, (iv) American, and (v) Dry forests. Our results do not support the traditional neo- versus paleotropical forest division but instead separate the combined American and African forests from their Indo-Pacific counterparts. We also find indications for the existence of a global dry forest region, with representatives in America, Africa, Madagascar, and India. Additionally, a northern-hemisphere Subtropical forest region was identified with representatives in Asia and America, providing support for a link between Asian and American northern-hemisphere forests.

BackgroundThis data paper provides a description of OpenNahele, the open Hawaiian forest plot database. OpenNahele includes 530 forest plots across the Hawaiian archipelago containing 43,590 individuals of 185 native and alien tree, shrub and tree fern species across six islands. We include estimates of maximum plant size (D950.1 and Dmax3) for 58 woody plant species, a key functional trait associated with dispersal distance and competition for light. OpenNahele can serve as a platform to test key ecological, evolutionary and conservation questions in a hotspot archipelago.New informationOpenNahele is the first database that compiles data from a large number of forest plots across the Hawaiian archipelago to allow broad and high resolution studies of biodiversity patterns.Keywords: Hawaii, forests, islands, biodiversity, community ecology, evolutionary ecology.

There has been an increasing interest in urban forests and the levels of biodiversity they contain. Currently there are no spatially explicit maps of tree species richness in urban areas. This research tests and identifies GIS and remote sensing metrics (climate, area, productivity, three-dimensional structure) hypothesized to be associated with species richness in native forests and identifies methods that can be applied to predict and map tree species richness in cities. We quantified tree species richness, floristic composition, and structure in 28 1-ha plots in the city of Los Angeles. Climate and remote sensing metrics from high-resolution aerial imagery (10 cm), QuickBird (60 cm), Landsat (30 m), MODIS (250 m), and airborne lidar (2 m) were collected for each plot. There were 1208 individual stems and 108 trees identified to species. Species richness ranged from 2 to 31 species per ha and averaged 17 species per ha. Tree canopy cover from QuickBird explained the highest portion of variance (54%) in tree species richness followed by NDVI from Landsat (42%). Tree species richness can be higher in residential urban forests than native forests in the United States. Spatially explicit species richness maps at 1 ha can be created and tested for cities in order to identify both hotspots and coldspots of tree species richness and changes in species richness over time.

The original version of this article unfortunately contained a mistake. One of the authors name was incorrectly listed as “Darrell E. Jenerette” and should be corrected as “G. Darrel Jenerette”. The original article was corrected.

Aim: We propose and test a climate tolerance and trait choice hypothesis of urban macroecological variation in which strong filtering associated with low winter temperatures restricts urban biodiversity while weak filtering associated with warmer temperatures and irrigation allows dispersal of species from a global source pool, thereby increasing urban biodiversity. Location: Twenty cities across the USA and Canada. Methods: We examined variation in tree community taxonomic diversity, origins and production of an aesthetic ecosystem service trait in a cross-section of urban field surveys. We correlated urban tree community composition indicators with a key climate restriction, namely mean minimum winter temperature, and evaluated alternative possible drivers: precipitation, summer maximum temperature, population size and the percentage of adults with a college education. Results: Species accumulation curves differed substantially among cities, with observed richness varying from 22 to 122 species. Similarities in tree communities decreased exponentially with increases in climatic differences. Ordination of tree communities showed strong separation among cities with component axes correlated with minimum winter temperature and annual precipitation. Variation among urban tree communities in richness, origins and the provisioning of an aesthetic ecosystem service were all correlated with minimum winter temperature. Main conclusions: The urban climate tolerance and trait choice hypothesis provides a coherent mechanism to explain the large variation among urban tree communities resulting from an interacting environment, species and human decisions. Reconciling the feedbacks between human decision making and biophysical limitations provides a foundation for an urban ecological theory that can better understand and predict the dynamics of other linked biotic communities, associated ecosystem dynamics and resulting services provided to urban residents.

UnlabelledIt has long been hypothesized that polyomaviruses (PyV; family Polyomaviridae) codiverged with their animal hosts. In contrast, recent analyses suggested that codivergence may only marginally influence the evolution of PyV. We reassess this question by focusing on a single lineage of PyV infecting hominine hosts, the Merkel cell polyomavirus (MCPyV) lineage. By characterizing the genetic diversity of these viruses in seven African great ape taxa, we show that they exhibit very strong host specificity. Reconciliation analyses identify more codivergence than noncodivergence events. In addition, we find that a number of host and PyV divergence events are synchronous. Collectively, our results support codivergence as the dominant process at play during the evolution of the MCPyV lineage. More generally, our results add to the growing body of evidence suggesting an ancient and stable association of PyV and their animal hosts.ImportanceThe processes involved in viral evolution and the interaction of viruses with their hosts are of great scientific interest and public health relevance. It has long been thought that the genetic diversity of double-stranded DNA viruses was generated over long periods of time, similar to typical host evolutionary timescales. This was also hypothesized for polyomaviruses (family Polyomaviridae), a group comprising several human pathogens, but this remains a point of controversy. Here, we investigate this question by focusing on a single lineage of polyomaviruses that infect both humans and their closest relatives, the African great apes. We show that these viruses exhibit considerable host specificity and that their evolution largely mirrors that of their hosts, suggesting that codivergence with their hosts played a major role in their diversification. Our results provide statistical evidence in favor of an association of polyomaviruses and their hosts over millions of years.