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Synthesizing trait observations and knowledge across the Tree of Life remains a grand challenge for biodiversity science. Species traits are widely used in ecological and evolutionary science, and new data and methods have proliferated rapidly. Yet accessing and integrating disparate data sources remains a considerable challenge, slowing progress toward a global synthesis to integrate trait data across organisms. Trait science needs a vision for achieving global integration across all organisms. Here, we outline how the adoption of key Open Science principles—open data, open source and open methods—is transforming trait science, increasing transparency, democratizing access and accelerating global synthesis. To enhance widespread adoption of these principles, we introduce the Open Traits Network (OTN), a global, decentralized community welcoming all researchers and institutions pursuing the collaborative goal of standardizing and integrating trait data across organisms. We demonstrate how adherence to Open Science principles is key to the OTN community and outline five activities that can accelerate the synthesis of trait data across the Tree of Life, thereby facilitating rapid advances to address scientific inquiries and environmental issues. Lessons learned along the path to a global synthesis of trait data will provide a framework for addressing similarly complex data science and informatics challenges.

In natural grasslands, C-4 plant dominance increases with growing season temperatures and reflects distinct differences in plant growth rates and water use efficiencies of C-3 vs. C-4 photosynthetic pathways. However, in lawns, management decisions influence interactions between planted turfgrass and weed species, leading to some uncertainty about the degree of human vs. climatic controls on lawn species distributions. We measured herbaceous plant carbon isotope ratios (delta C-13, index of C-3/C-4 relative abundance) and C-4 cover in residential lawns across seven U.S. cities to determine how climate, lawn plant management, or interactions between climate and plant management influenced C-4 lawn cover. We also calculated theoretical C-4 carbon gain predicted by a plant physiological model as an index of expected C-4 cover due to growing season climatic conditions in each city. Contrary to theoretical predictions, plant delta C-13 and C-4 cover in urban lawns were more strongly related to mean annual temperature than to growing season temperature. Wintertime temperatures influenced the distribution of C-4 lawn turf plants, contrary to natural ecosystems where growing season temperatures primarily drive C-4 distributions. C-4 cover in lawns was greatest in the three warmest cities, due to an interaction between climate and homeowner plant management (e.g., planting C-4 turf species) in these cities. The proportion of C-4 lawn species was similar to the proportion of C-4 species in the regional grass flora. However, the majority of C-4 species were nonnative turf grasses, and not of regional origin. While temperature was a strong control on lawn species composition across the United States, cities differed as to whether these patterns were driven by cultivated lawn grasses vs. weedy species. In some cities, biotic interactions with weedy plants appeared to dominate, while in other cities, C-4 plants were predominantly imported and cultivated. Elevated CO2 and temperature in cities can influence C-3/C-4 competitive outcomes; however, this study provides evidence that climate and plant management dynamics influence biogeography and ecology of C-3/C-4 plants in lawns. Their differing water and nutrient use efficiency may have substantial impacts on carbon, water, energy, and nutrient budgets across cities. ; U.S. National Science Foundation Macrosystems Biology Program [EF-1065548, 1065737, 1065740, 1065741, 1065772, 1065785, 1065831, 121238320] ; This research was funded by a series of collaborative grants from the U.S. National Science Foundation Macrosystems Biology Program (EF-1065548, 1065737, 1065740, 1065741, 1065772, 1065785, 1065831, 121238320). The authors thank La'Shaye Ervin, William Borrowman, Moumita Kundu, and Barbara Uhl for field and laboratory assistance. ; Public domain authored by a U.S. government employee

The urban heat island (UHI) is a well-documented pattern of warming in cities relative to rural areas. Most UHI research utilizes remote sensing methods at large scales, or climate sensors in single cities surrounded by standardized land cover. Relatively few studies have explored continental-scale climatic patterns within common urban microenvironments such as residential landscapes that may affect human comfort. We tested the urban homogenization hypothesis which states that structure and function in cities exhibit ecological "sameness" across diverse regions relative to the native ecosystems they replaced. We deployed portable micrometeorological sensors to compare air temperature and humidity in residential yards and native landscapes across six U.S. cities that span a range of climates (Phoenix, AZ; Los Angeles, CA; Minneapolis-St. Paul, MN; Boston, MA; Baltimore, MD; and Miami, FL). Microclimate in residential ecosystems was more similar among cities than among native ecosystems, particularly during the calm morning hours. Maximum regional actual evapotranspiration (AET) was related to the morning residential microclimate effect. Residential yards in cities with maximum AET < 50-65 cm/year (Phoenix and Los Angeles) were generally cooler and more humid than nearby native shrublands during summer mornings, while yards in cities above this threshold were generally warmer (Baltimore and Miami) and drier (Miami) than native forests. On average, temperature and absolute humidity were similar to 6 % less variable among residential ecosystems than among native ecosystems from diverse regions. These data suggest that common residential land cover and structural characteristics lead to microclimatic convergence across diverse regions at the continental scale. ; Macrosystems Biology Program at NSF [EF-1065548, 1065737, 1065740, 1065741, 1065772, 1065785, 1065831, 1241960, 121238320]; Earth Systems Modeling program at NSF [EF-1049251]; NSF Long-term Ecological Research Program in Baltimore (BES LTER) [DEB-0423476]; NSF Long-term Ecological Research Program in Phoenix (CAP LTER) [BCS-1026865]; NSF Long-term Ecological Research Program in Plum Island (PIE LTER Boston) [OCE-1058747, 1238212]; NSF Long-term Ecological Research Program in Cedar Creek (CDR LTER, Minneapolis-St Paul) [DEB-1234162]; NSF Long-term Ecological Research Program in Florida Coastal Everglades (FCE LTER, Miami) [DBI-0620409] ; We are grateful to numerous technical staff, students, and volunteers who assisted with microclimate data collection, including Erin Barton, Matthew Camba, Emma Dixon, La'Shaye Ervin, Caitlin Holmes, Richard McHorney, Miguel Morgan, Joseph Rittenhouse, Anna Royar, Jehane Samaha, Sydney Schiffner, Julea Shaw, Anissa Vega, Elisabeth Ward, and Megan Wheeler. We also thank Darrel Jenerette for reviewing an earlier draft of this manuscript. This project was supported by several collaborative grants from the Macrosystems Biology Program at NSF (EF-1065548, 1065737, 1065740, 1065741, 1065772, 1065785, 1065831, 1241960, and 121238320), and by the Earth Systems Modeling program at NSF (EF-1049251). This work was also supported in part by the NSF Long-term Ecological Research Program in Baltimore (BES LTER, DEB-0423476), Phoenix (CAP LTER, BCS-1026865), Plum Island (PIE LTER Boston; OCE-1058747 and 1238212), Cedar Creek (CDR LTER, Minneapolis-St Paul; DEB-1234162), and Florida Coastal Everglades (FCE LTER, Miami; DBI-0620409). ; Public domain authored by a U.S. government employee

Synthesizing trait observations and knowledge across the Tree of Life remains a grand challenge for biodiversity science. Species traits are widely used in ecological and evolutionary science, and new data and methods have proliferated rapidly. Yet accessing and integrating disparate data sources remains a considerable challenge, slowing progress toward a global synthesis to integrate trait data across organisms. Trait science needs a vision for achieving global integration across all organisms. Here, we outline how the adoption of key Open Science principles—open data, open source and open methods—is transforming trait science, increasing transparency, democratizing access and accelerating global synthesis. To enhance widespread adoption of these principles, we introduce the Open Traits Network (OTN), a global, decentralized community welcoming all researchers and institutions pursuing the collaborative goal of standardizing and integrating trait data across organisms. We demonstrate how adherence to Open Science principles is key to the OTN community and outline five activities that can accelerate the synthesis of trait data across the Tree of Life, thereby facilitating rapid advances to address scientific inquiries and environmental issues. Lessons learned along the path to a global synthesis of trait data will provide a framework for addressing similarly complex data science and informatics challenges.

Synthesizing trait observations and knowledge across the Tree of Life remains a grand challenge for biodiversity science. Species traits are widely used in ecological and evolutionary science, and new data and methods have proliferated rapidly. Yet accessing and integrating disparate data sources remains a considerable challenge, slowing progress toward a global synthesis to integrate trait data across organisms. Trait science needs a vision for achieving global integration across all organisms. Here, we outline how the adoption of key Open Science principles-open data, open source and open methods-is transforming trait science, increasing transparency, democratizing access and accelerating global synthesis. To enhance widespread adoption of these principles, we introduce the Open Traits Network (OTN), a global, decentralized community welcoming all researchers and institutions pursuing the collaborative goal of standardizing and integrating trait data across organisms. We demonstrate how adherence to Open Science principles is key to the OTN community and outline five activities that can accelerate the synthesis of trait data across the Tree of Life, thereby facilitating rapid advances to address scientific inquiries and environmental issues. Lessons learned along the path to a global synthesis of trait data will provide a framework for addressing similarly complex data science and informatics challenges.

Synthesizing trait observations and knowledge across the Tree of Life remains a grand challenge for biodiversity science. Species traits are widely used in ecological and evolutionary science, and new data and methods have proliferated rapidly. Yet accessing and integrating disparate data sources remains a considerable challenge, slowing progress toward a global synthesis to integrate trait data across organisms. Trait science needs a vision for achieving global integration across all organisms. Here, we outline how the adoption of key Open Science principles—open data, open source and open methods—is transforming trait science, increasing transparency, democratizing access and accelerating global synthesis. To enhance widespread adoption of these principles, we introduce the Open Traits Network (OTN), a global, decentralized community welcoming all researchers and institutions pursuing the collaborative goal of standardizing and integrating trait data across organisms. We demonstrate how adherence to Open Science principles is key to the OTN community and outline five activities that can accelerate the synthesis of trait data across the Tree of Life, thereby facilitating rapid advances to address scientific inquiries and environmental issues. Lessons learned along the path to a global synthesis of trait data will provide a framework for addressing similarly complex data science and informatics challenges.