Understanding how plant carbon metabolism responds to environmental variables such as light is central to understanding ecosystem carbon cycling and the production of food, biofuels, and biomaterials. Here, we couple a portable leaf photosynthesis system to an autosampler for volatile organic compounds (VOCs) to enable field observations of net photosynthesis simultaneously with emissions of VOCs as a function of light. Following sample collection, VOCs are analyzed using automated thermal desorption-gas chromatograph-mass spectrometry (TD-GC-MS). An example is presented from a banana plant in the central Amazon with a focus on the response of photosynthesis and the emissions of eight individual monoterpenes to light intensity. Our observations reveal that banana leaf emissions represent a 1.1 +/- 0.1% loss of photosynthesis by carbon. Monoterpene emissions from banana are dominated by trans-β-ocimene, which accounts for up to 57% of total monoterpene emissions at high light. We conclude that the developed system is ideal for the identification and quantification of VOC emissions from leaves in parallel with CO2 and water fluxes.The system therefore permits the analysis of biological and environmental sensitivities of carbon metabolism in leaves in remote field locations, resulting in the emission of hydrocarbons to the atmosphere.•A field-portable system is developed for the identification and quantification of VOCs from leaves in parallel with leaf physiological measurements including photosynthesis and transpiration.•The system will enable the characterization of carbon and energy allocation to the biosynthesis and emission of VOCs linked with photosynthesis (e.g. isoprene and monoterpenes) and their biological and environmental sensitivities (e.g. light, temperature, CO₂).•Allow the development of more accurate mechanistic global VOC emission models linked with photosynthesis, improving our ability to predict how forests will respond to climate change. It is our hope that the presented system will contribute with critical data towards these goals across Earth's diverse tropical forests.

Tropical forests are acknowledged to be the largest global source of isoprene (C₅H₈) and monoterpenes (C₁₀H₁₆) emissions, with current synthesis studies suggesting few tropical species emit isoprenoids (20-38%) and do so with highly variable emission capacities, including within the same genera. This apparent lack of a clear phylogenetic thread has created difficulties both in linking isoprenoid function with evolution and for the development of accurate biosphere-atmosphere models. Here, we present a systematic emission study of "hyperdominant" tree species in the Amazon Basin. Across 162 individuals, distributed among 25 botanical families and 113 species, isoprenoid emissions were widespread among both early and late successional species (isoprene: 61.9% of the species; monoterpenes: 15.0%; both isoprene and monoterpenes: 9.7%). The hyperdominant species (69) across the top five most abundant genera, which make up about 50% of all individuals in the Basin, had a similar abundance of isoprenoid emitters (isoprene: 63.8%; monoterpenes: 17.4%; both 11.6%). Among the abundant genera, only Pouteria had a low frequency of isoprene emitting species (15.8% of 19 species). In contrast, Protium, Licania, Inga, and Eschweilera were rich in isoprene emitting species (83.3% of 12 species, 61.1% of 18 species, 100% of 8 species, and 100% of 12 species, respectively). Light response curves of individuals in each of the five genera showed light-dependent, photosynthesis-linked emission rates of isoprene and monoterpenes. Importantly, in every genus, we observed species with light-dependent isoprene emissions together with monoterpenes including β-ocimene. These observations support the emerging view of the evolution of isoprene synthases from β-ocimene synthases. Our results have important implications for understanding isoprenoid function-evolution relationships and the development of more accurate Earth System Models.

Key message: Annual stem CO2 efflux increases with stem wood production rates and are inhibited by daily moisture stress. Abstract: Tropical forests cycle a large amount of CO2 between the land and atmosphere, with a substantial portion of the return flux due tree respiratory processes. However, in situ estimates of woody tissue respiratory fluxes and carbon use efficiencies (CUEW) and their dependencies on physiological processes including stem wood production (Pw) and transpiration in tropical forests remain scarce. Here, we synthesize monthly Pw and daytime stem CO2 efflux (ES) measurements over 1 year from 80 trees with variable biomass accumulation rates in the central Amazon. On average, carbon flux to woody tissues, expressed in the same stem area normalized units as ES, averaged 0.90 ± 1.2 µmol m−2 s−1 for Pw, and 0.55 ± 0.33 µmol m−2 s−1 for daytime ES. A positive linear correlation was found between stem growth rates and stem CO2 efflux, with respiratory carbon loss equivalent to 15 ± 3% of stem carbon accrual. CUEW of stems was non-linearly correlated with growth and was as high as 77–87% for a fast-growing tree. Diurnal measurements of stem CO2 efflux for three individuals showed a daytime reduction of ES by 15–50% during periods of high sap flow and transpiration. The results demonstrate that high daytime ES fluxes are associated with high CUEW during fast tree growth, reaching higher values than previously observed in the Amazon Basin (e.g., maximum CUEW up to 77–87%, versus 30–56%). The observations are consistent with the emerging view that diurnal dynamics of stem water status influences growth processes and associated respiratory metabolism.

Physical samples are foundational entities for research across biological, Earth, and environmental sciences. Data generated from sample-based analyses are not only the basis of individual studies, but can also be integrated with other data to answer new and broader-scale questions. Ecosystem studies increasingly rely on multidisciplinary team-science to study climate and environmental changes. While there are widely adopted conventions within certain domains to describe sample data, these have gaps when applied in a multidisciplinary context. In this study, we reviewed existing practices for identifying, characterizing, and linking related environmental samples. We then tested practicalities of assigning persistent identifiers to samples, with standardized metadata, in a pilot field test involving eight United States Department of Energy projects. Participants collected a variety of sample types, with analyses conducted across multiple facilities. We address terminology gaps for multidisciplinary research and make recommendations for assigning identifiers and metadata that supports sample tracking, integration, and reuse. Our goal is to provide a practical approach to sample management, geared towards ecosystem scientists who contribute and reuse sample data. (IGSN); physical samples; soil; water; plant; leaf; microbial communities; related identifiers; persistent identifiers.

Research can be more transparent and collaborative by using Findable, Accessible, Interoperable, and Reusable (FAIR) principles to publish Earth and environmental science data. Reporting formats-instructions, templates, and tools for consistently formatting data within a discipline-can help make data more accessible and reusable. However, the immense diversity of data types across Earth science disciplines makes development and adoption challenging. Here, we describe 11 community reporting formats for a diverse set of Earth science (meta)data including cross-domain metadata (dataset metadata, location metadata, sample metadata), file-formatting guidelines (file-level metadata, CSV files, terrestrial model data archiving), and domain-specific reporting formats for some biological, geochemical, and hydrological data (amplicon abundance tables, leaf-level gas exchange, soil respiration, water and sediment chemistry, sensor-based hydrologic measurements). More broadly, we provide guidelines that communities can use to create new (meta)data formats that integrate with their scientific workflows. Such reporting formats have the potential to accelerate scientific discovery and predictions by making it easier for data contributors to provide (meta)data that are more interoperable and reusable.

Data standardization combined with descriptive metadata facilitate data reuse, which is the ultimate goal of the Findable, Accessible, Interoperable, and Reusable (FAIR) principles. Community data or metadata standards are increasingly created through an approach that emphasizes collaboration between various stakeholders. Such an approach requires platforms for collaboration on the development process that centers on sharing information and receiving feedback. Our objective in this study was to conduct a systematic review to identify data standards and reporting formats that use version control for developing data standards and to summarize common practices, particularly in earth and environmental sciences. Out of 108 data standards and reporting formats identified in our review, 32 used GitHub as the version control platform, and no other platforms were used. We found no universally accepted methodology for developing and publishing data standards. Many GitHub repositories did not use key features that could help developers to gather user feedback, or to create and revise standards that build on previous work. We provide guidance for community-driven standard development and associated documentation on GitHub based on a systematic review of existing practices.