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DOE OSTI2024

Metagenomic clustering links specific metabolic functions to globally relevant ecosystems

ABSTRACT Metagenomic sequencing has advanced our understanding of biogeochemical processes by providing an unprecedented view into the microbial composition of different ecosystems. While the amount of metagenomic data has grown rapidly, simple-to-use methods to analyze and compare across studies have lagged behind. Thus, tools expressing the metabolic traits of a community are needed to broaden the utility of existing data. Gene abundance profiles are a relatively low-dimensional embedding of a metagenome’s functional potential and are, thus, tractable for comparison across many samples. Here, we compare the abundance of KEGG Ortholog Groups (KOs) from 6,539 metagenomes from the Joint Genome Institute’s Integrated Microbial Genomes and Metagenomes (JGI IMG/M) database. We find that samples cluster into terrestrial, aquatic, and anaerobic ecosystems with marker KOs reflecting adaptations to these environments. For instance, functional clusters were differentiated by the metabolism of antibiotics, photosynthesis, methanogenesis, and surprisingly GC content. Using this functional gene approach, we reveal the broad-scale patterns shaping microbial communities and demonstrate the utility of ortholog abundance profiles for representing a rapidly expanding body of metagenomic data. IMPORTANCE Metagenomics, or the sequencing of DNA from complex microbiomes, provides a view into the microbial composition of different environments. Metagenome databases were created to compile sequencing data across studies, but it remains challenging to compare and gain insight from these large data sets. Consequently, there is a need to develop accessible approaches to extract knowledge across metagenomes. The abundance of different orthologs (i.e., genes that perform a similar function across species) provides a simplified representation of a metagenome’s metabolic potential that can easily be compared with others. In this study, we cluster the ortholog abundance profiles of thousands of metagenomes from diverse environments and uncover the traits that distinguish them. This work provides a simple to use framework for functional comparison and advances our understanding of how the environment shapes microbial communities.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Building Intelligent Cyberinfrastructure to Learn Iteratively from both Observations and Models for Understanding Watershed Dynamics

Focal Area(s): Predictive modeling through the use of AI techniques and AI-derived model components; the use of AI and other tools to design a prediction system comprising of a hierarchy of models (e.g., AI-driven model/component/parameterization selection). Science Challenge: Watershed processes, such as the fate and transport of sediment, carbon and nutrients across landscapes and their fluxes to water bodies (e.g., streams, rivers and lakes), have important implications for global and regional carbon and nutrient dynamics, biogeochemical functioning of terrestrial ecosystems, and soil functions. The magnitude of lateral surface/subsurface transport and fluxes of sediment, carbon and nutrients are key factors controlling the vulnerability of watersheds to climate extremes such as droughts, wildfires, and floods. Recent field observations and other scientific evidence suggest that the magnitudes of lateral transport and fluxes of sediment, carbon and nutrients are governed primarily by the spatial and vertical heterogeneity of landscape and soil properties and by pedogenic processes. However, the current generation of land surface and watershed models do not mechanistically couple the terrestrial and hydrologic systems, nor do they represent sufficiently the spatial and vertical heterogeneity of land surface and subsurface properties. On the other hand, increasing complexity of coupled watershed and land surface models requires more data to parameterize, calibrate and validate. Remote sensing (RS) provides a means to acquire spatial data and characterize their heterogeneity at the watershed scale, overcoming a major limitation associated with conventional point measurements. To improve the representation of land-surface and surface/subsurface process coupling and sub-grid heterogeneity in watershed models, it is essential to build our predictive understanding by learning from both the multi-scale multi-process modeling and diverse multi-scale data while leveraging powerful artificial intelligence (AI) techniques.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

The Global Spectra-Trait Initiative: A database of paired leaf spectroscopy and functional traits associated with leaf photosynthetic capacity (v1.0.0)

The Global Spectra-Trait Initiative (GSTI) aims to generate generalizable spectra trait models using reflectance data to predict leaf traits associated with the photosynthesis capacity of leaves. It comprises a synthesized dataset of leaf trait data, input datasets and code. Leaf traits include the maximum carboxylation rate of rubisco (Vcmax), the maximum electron transport rate (Jmax), the dark respiration, as well as the prediction of leaf nitrogen, leaf mass per area (LMA), and leaf water content (LWC). The dataset comprises >7500 paired observations from around 400 species from a broad range of biomes. This dataset comprises a zip file of the GSTI GitHub repository (https://github.com/plantphys/gsti), the synthesized database (.csv) and database metadata files. This dataset was updated on 2025-12-12 with minor edits to mirror the accepted manuscript version and GitHub release (Version 1.0.0 (ESSD accepted version)). Edits included minor changes to the project documentation on GitHub and removal of 12 duplicate entries from the database.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Shower thoughts: why scientists should spend more time in the rain

Abstract Stormwater is a vital resource and dynamic driver of terrestrial ecosystem processes. However, processes controlling interactions during and shortly after storms are often poorly seen and poorly sensed when direct observations are substituted with technological ones. We discuss how human observations complement technological ones and the benefits of scientists spending more time in the storm. Human observation can reveal ephemeral storm-related phenomena such as biogeochemical hot moments, organismal responses, and sedimentary processes that can then be explored in greater resolution using sensors and virtual experiments. Storm-related phenomena trigger lasting, oversized impacts on hydrologic and biogeochemical processes, organismal traits or functions, and ecosystem services at all scales. We provide examples of phenomena in forests, across disciplines and scales, that have been overlooked in past research to inspire mindful, holistic observation of ecosystems during storms. We conclude that technological observations alone are insufficient to trace the process complexity and unpredictability of fleeting biogeochemical or ecological events without the shower thoughts produced by scientists’ human sensory and cognitive systems during storms.

ecosystem functioning↗

DOE OSTI2022

A framework for soil microbial ecology in urban ecosystems

Nearly all ecosystems host diverse microbiomes that support vital ecosystem processes. At the same time, these ecosystems and their microbiomes are increasingly altered by human activities, particularly in highly managed urban environments. While microbial ecologists are beginning to understand the drivers of microbial assembly and the link between community structure and function in many ecosystems, few of these advances have been applied to urban ecosystems. In this synthesis, we review research on the urban soil microbiome and develop a framework to integrate soil microbial communities with urban ecosystem function. We identify disturbance, altered resources, and heterogeneity as key drivers through which human activities including urban development affect soils and their resident microorganisms. Steep environmental gradients in many urban systems present a unique opportunity to address fundamental questions in microbial ecology, such as how microbes respond to stress and how biogeochemical rates relate to microbial diversity and composition. Soil microbiomes in cities also provide ecosystem services and harms, making it crucial to understand how human activity drives those functions and the consequences for environmental and human health. We argue that much-needed integration across disturbance ecology, urban ecology, and microbial ecology will help generate practical and equitable strategies for managing ecosystem benefits in cities where most humans now live.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Climate-driven tradeoffs between landscape connectivity and the maintenance of the coastal carbon sink

Abstract Ecosystem connectivity tends to increase the resilience and function of ecosystems responding to stressors. Coastal ecosystems sequester disproportionately large amounts of carbon, but rapid exchange of water, nutrients, and sediment makes them vulnerable to sea level rise and coastal erosion. Individual components of the coastal landscape (i.e., marsh, forest, bay) have contrasting responses to sea level rise, making it difficult to forecast the response of the integrated coastal carbon sink. Here we couple a spatially-explicit geomorphic model with a point-based carbon accumulation model, and show that landscape connectivity, in-situ carbon accumulation rates, and the size of the landscape-scale coastal carbon stock all peak at intermediate sea level rise rates despite divergent responses of individual components. Progressive loss of forest biomass under increasing sea level rise leads to a shift from a system dominated by forest biomass carbon towards one dominated by marsh soil carbon that is maintained by substantial recycling of organic carbon between marshes and bays. These results suggest that climate change strengthens connectivity between adjacent coastal ecosystems, but with tradeoffs that include a shift towards more labile carbon, smaller marsh and forest extents, and the accumulation of carbon in portions of the landscape more vulnerable to sea level rise and erosion.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

NASA's surface biology and geology designated observable: A perspective on surface imaging algorithms

The 2017-2027 National Academies' Decadal Survey, Thriving on Our Changing Planet, recommended Surface Biology and Geology (SBG) as a "Designated Targeted Observable" (DO). The SBG DO is based on the need for capabilities to acquire global, high spatial resolution, visible to shortwave infrared (VSWIR; 380 - 2500 nm; ~30 m pixel resolution) hyperspectral (imaging spectroscopy) and multispectral midwave and thermal infrared (MWIR: 3-5 µm; TIR: 8-12 µm; ~60 m pixel resolution) measurements with sub-monthly temporal revisits over terrestrial, freshwater, and coastal marine habitats. To address the various mission design needs, an SBG Algorithms Working Group of multidisciplinary researchers has been formed to review and evaluate the algorithms applicable to the SBG DO across a wide range of Earth science disciplines, including terrestrial and aquatic ecology, atmospheric science, geology, and hydrology. Here, we summarize current state-of-the-practice VSWIR and TIR algorithms that use airborne or orbital spectral imaging observations to address the SBG DO priorities identified by the Decadal Survey: (i) terrestrial vegetation physiology, functional traits, and health; (ii) inland and coastal aquatic ecosystems physiology, functional traits, and health; (iii) snow and ice accumulation, melting, and albedo; (iv) active surface composition (eruptions, landslides, evolving landscapes, hazard risks); (v) effects of changing land use on surface energy, water, momentum, and carbon fluxes; and (vi) managing agriculture, natural habitats, water use/quality, and urban development. We review existing algorithms in the following categories: snow/ice, aquatic environments, geology, and terrestrial vegetation, and summarize the community-state-of-practice in each category. Finally, this effort synthesizes the findings of more than 130 scientists.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Degradation Reduces Microbial Richness and Alters Microbial Functions in an Australian Peatland

Abstract Peatland ecosystems cover only 3% of the world’s land area; however, they store one-third of the global soil carbon (C). Microbial communities are the main drivers of C decomposition in peatlands, yet we have limited knowledge of their structure and function. While the microbial communities in the Northern Hemisphere peatlands are well documented, we have limited understanding of microbial community composition and function in the Southern Hemisphere peatlands, especially in Australia. We investigated the vertical stratification of prokaryote and fungal communities from Wellington Plains peatland in the Australian Alps. Within the peatland complex, bog peat was sampled from the intact peatland and dried peat from the degraded peatland along a vertical soil depth gradient (i.e., acrotelm, mesotelm, and catotelm). We analyzed the prokaryote and fungal community structure, predicted functional profiles of prokaryotes using PICRUSt, and assigned soil fungal guilds using FUNGuild. We found that the structure and function of prokaryotes were vertically stratified in the intact bog. Soil carbon, manganese, nitrogen, lead, and sodium content best explained the prokaryote composition. Prokaryote richness was significantly higher in the intact bog acrotelm compared to degraded bog acrotelm. Fungal composition remained similar across the soil depth gradient; however, there was a considerable increase in saprotroph abundance and decrease in endophyte abundance along the vertical soil depth gradient. The abundance of saprotrophs and plant pathogens was two-fold higher in the degraded bog acrotelm. Soil manganese and nitrogen content, electrical conductivity, and water table level (cm) best explained the fungal composition. Our results demonstrate that both fungal and prokaryote communities are shaped by soil abiotic factors and that peatland degradation reduces microbial richness and alters microbial functions. Thus, current and future changes to the environmental conditions in these peatlands may lead to altered microbial community structures and associated functions which may have implications for broader ecosystem function changes in peatlands.

Environmental Sciences & Ecology↗

DOE OSTI2025

Assessing the cumulative effects of nearshore habitat restoration actions for multiple populations of juvenile salmon in Whidbey Basin, Washington: foundation and approach for synthesis and evaluation

Ecosystem restoration is a common tool for re-establishing ecosystem processes, structures, and functions to improve biodiversity and services in coastal and estuarine ecosystems. In the Salish Sea, salmon habitats have been fragmented, reduced in size, and diminished in quality, and the ecosystem processes that form and sustain these habitats have been degraded and disrupted as well. This loss is especially prevalent in estuaries, where up to 90% of former salmon habitat has been lost or compromised. Salmon species are integral to the identities and cultures of people in the Pacific Northwest, yet salmon abundances remain at historic lows, especially in urbanized areas. Recent investments in restoration are creating rearing habitat and repairing lost ecosystem function. However, restoration efforts in this region have largely proceeded at the site scale, with less attention to big-picture thinking regarding how restoration will effectively recover degraded or lost habitats for target species. As a result, no landscape-scale evaluation program exists, and the cumulative benefits of multiple interventions are unknown. We describe innovative methods for science synthesis related to the evaluation of cumulative effects of ecosystem restoration for Pacific salmon, using years of existing, but disparate data. Building from previous work on cumulative effects evaluation and incorporating a hierarchy of hypotheses approach, we propose using causal inference across numerous hypotheses in a framework to assess the cumulative benefits to Pacific salmon from multiple estuarine restoration projects. We present the framework as a method that can be used to address many complex questions and provide examples from the Salish Sea where the approach is being implemented. The framework draws on science synthesis from numerous fields and uses a hierarchy of hypotheses, causal analysis at multiple scales, and a new hierarchy of synthesis for assessing multiple lines of evidence documenting restoration effects on Pacific salmon. We propose causal inference to synthesize dissimilar data streams, in our case, to identify various manifestations of cumulative effects of restoration and benefits to salmon, and to further inform restoration and recovery planning. A unifying framework would allow for the detection of thresholds at which restoration provides measurable improvement and would greatly advance understanding of the effects of restoration on ecosystems.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Data from Raczka et al., Interactions between microbial diversity and substrate chemistry determine the fate of carbon in soil, from Elizabeth Woods in Morgantown, West Virginia, USA

File types include: Soil respiration as 13C cumulative respiration from soil incubation experiment, qSIP (quantitative stable isotope probing) data that is "18S apes wide" which is the fungal atom percent excess or how much the fungi took up of the labeled litter and "16S apes wide" which is the bacterial atom percent excess or how much the bacteria took up of the labeled litter, metabolomic data from the incubated soil samples called "Metab Soil Unique Filtered", which is the metabolomic data that had an initial filter from the raw data, and lipidomic data from the incubated soil samples called "All lipids soil". These files were used according to methods in Raczka et al. 2021 Scientific Reports. Headers show soil type (Oak, Poplar) and litter type (also called substrate here, which is labeled as no litter (control), poplar, and oak). This research was done to understand interactions between ecosystem-level processes and microbial diversity that impacts the composition of decomposition products that can form stable soil organic matter.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Data for “Fast-decaying plant litter enhances soil carbon in temperate forests, but not through microbial physiological traits”

This data package contains data and code used in the paper “Fast-decaying plant litter enhances soil carbon in temperate forests, but not through microbial physiological traits”. This paper details results from two studies: 1) a laboratory leaf litter incubation experiment (lab experiment) and 2) a multi-site observational field study (field study). Both studies were designed to test the relationships among litter quality, microbial physiological traits, and mineral-associated soil carbon (C). In the lab experiment, we incubated 16 temperate tree litters of differing chemical quality with isotopically distinct soil, measuring microbial physiological traits and the flow of litter-derived C into the mineral-associated soil C pool. In the field study, we sampled soils (0-5 cm) across six eastern US temperate forests, measuring microbial physiological traits, soil abiotic properties, and leaf litter chemistry. The analysis data are provided in two .csv files corresponding to either the lab experiment or field study. Both files contain data on litter chemistry, microbial physiological traits (growth and turnover rates, and carbon use efficiency [CUE]), and the mineral-associated soil C pool. The lab experiment dataset additionally contains litter-derived versus soil-derived soil C, respiration, and litter decomposition parameters. The field study dataset additionally contains site-level climatic information, ectomycorrhizal dominance of plots, and plot-level soil properties. Also provided is the R code and output reproducing the results in the related publication. Analyses were originally performed using R version 3.6.1 using the package "lavaan" and the packages listed on lines 5-7 in the file "data.R".

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Arctic shrub and Eriophorum leaf and root decomposition, northern Alaska, 2017-2018

This data package contains litter decomposition data collected from 170 plots of rapidly expanding shrub genera (Alnus, Betula, and Salix) and a widespread sedge (Eriophorum vaginatum) along a latitudinal and temperature gradient in northern Alaska. These data were produced from a litter bag experiment that took place from July 2017 to July 2018 and include mass loss and nitrogen loss decomposition metrics for both leaf and root litters. These raw data support a submitted manuscript that examines the variability in decomposition between shrub and graminoid leaf and root litters across a 1-year experiment across the graminoid-dominated Arctic tundra and reveals how deciduous shrub expansion affects litter decomposition in tundra ecosystems. Data are presented by site (n=5) and patch (shrub or sedge plot) in csv files. The site and plot location data and environmental measurement data are provided in Fraterrigo and Chen (2020). Additional methods regarding plot distribution and environmental measurements are in Chen et al. (2020) and Fraterrigo et al. (2024).

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Stomatal response of three Arctic plant species, Seward Peninsula, Alaska, 2022

Stomatal response to changing irradiance measurements on three common tussock tundra shrub species. Data were collected in 2022 from two sites on the Seward Peninsula, Kougarok Mile 64 and Teller Mile 27. Measurements were made with LI-COR LI-6800 gas exchange systems using a slow curve light response method. Light curve observations enable the estimation of stomatal slope and intercept parameters, g1 and g0. The data package files include a data file, metadata files and the complete instrument output for all measurements in .csv format, and a pdf describing the experimental protocol. See the related data package NGA315 for foliar trait data (leaf mass per area, leaf nitrogen concentration) and NGA209 for co-located thaw depth and soil moisture. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Vegetation browning: global drivers, impacts, and feedbacks

As global climate conditions continue to change, disturbance regimes and environmental drivers will continue to shift, impacting global vegetation dynamics. Following a period of vegetation greening, there has been a progressive increase in remotely sensed vegetation browning globally. Further, given the many societal benefits that forests provide, it is critical that we understand vegetation dynamic alterations. Here, we review associative drivers, impacts, and feedbacks, revealing the complexity of browning. Concomitant increases in browning include the weakening of ecosystem services and functions and alterations to vegetation structure and species composition as well as the development of potential positive climate change feedbacks. Also discussed are the current challenges in browning detection and understanding associated impacts and feedbacks. Finally, we outline recommended strategies.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Experimental warming differentially affects vegetative and reproductive phenology of tundra plants

Rapid climate warming is altering Arctic and alpine tundra ecosystem structure and function, including shifts in plant phenology. While the advancement of green up and flowering are well-documented, it remains unclear whether all phenophases, particularly those later in the season, will shift in unison or respond divergently to warming. Here, we present the largest synthesis to our knowledge of experimental warming effects on tundra plant phenology from the International Tundra Experiment. We examine the effect of warming on a suite of season-wide plant phenophases. Results challenge the expectation that all phenophases will advance in unison to warming. Instead, we find that experimental warming caused: (1) larger phenological shifts in reproductive versus vegetative phenophases and (2) advanced reproductive phenophases and green up but delayed leaf senescence which translated to a lengthening of the growing season by approximately 3%. Patterns were consistent across sites, plant species and over time. The advancement of reproductive seasons and lengthening of growing seasons may have significant consequences for trophic interactions and ecosystem function across the tundra.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Duke Forest FACE (FACTS-I): Plant and Soil Response Data

This dataset describing the responses of plant and soil pools and fluxes to elevated atmospheric CO2 concentration and increased nitrogen supply was collected from Duke Forest Free Air CO2 Enrichment (FACE) – Forest-Atmosphere Carbon Transfer and Storage (FACTS-I) experiment from 1996 to 2012. The dataset includes data files for allometry (diameter at breast height, tree height, and height to live crown base), leaf area index, biomass (stem, branch, foliage, and root biomass, tree density, and basal area), net primary productivity (stem, branch, foliage, reproductive, and coarse root NPP), sap flux density, soil CO2 efflux, and stem temperature. Data files were formatted as .csv (Microsoft Excel or other spreadsheet programs can be used to read the format) and file descriptions, including variable name, unit, and data range, can be found in ‘FileDescription_[data_name].txt’ files. The Duke FACE experiment was in a loblolly pine (Pinus taeda L.) plantation established in 1983. Naturally regenerated broadleaved species including sweetgum (Liquidambar styraciflua L.) and tulip poplar (Liriodendron tulipifera L.), mostly in the overstory, and winged elm (Ulmus alata Michx.) and red maple (Acer rubrum L.) were common in the understory. The FACE experiment commenced with two plots (plots 7-8) in 1994 (Oren et al. 2001), with six additional plots (plots 1-6) coming online on 27 August 1996. CO2 enrichment was terminated on 31 October 2010 and post-enrichment data collection continued through 2012. Complete fertilization was applied annually to half of plots 7-8 from 1998 to 2004. The nutrient addition experiment expanded to half of plots 1-6 with a common protocol of N-fertilization in 2005 and continued until 2012. The levels of treatment in this dataset were expressed as ambient CO2 (AMB) or elevated CO2 (ELE) for CO2 treatment and control soil (CONT) or fertilized soil (FERT) for N treatment, respectively.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Data for: A Synoptic System for Capturing Ecosystem Control Points Across Terrestrial-Aquatic Interfaces

The investigation of how climate change and water level fluctuations impact variable and interconnected ecosystems, like the interfaces between terrestrial and aquatic environments, requires the collection and integration of many data types. We describe an integrative and autonomous environmental monitoring approach that uses environmental sensors and data loggers to monitor surface water, groundwater, soil, and vegetation changes and generate essential data for predictive models. We established the network at seven sites along the Chesapeake Bay and Lake Erie coastlines, including a large-scale flood manipulation experiment, collectively generating over three million observations per month. Such sensor networks hold great promise for tracking and comprehending environmental changes where land and water intersect. The sensor system and overall approach to sensor management that we have designed is intended to be widely accessible for research teams spanning in size from an individual investigator to large multi-institution projects. This dataset shows example data generated by the sensor network described above. Data output for data loggers connected to groundwater water quality sondes measuring dissolved oxygen, pH, oxidative redox potential (ORP), groundwater elevation, groundwater salinity and temperature, and groundwater elevation; replicate soil moisture and conductivity probes installed at 10 and 30 cm below the ground surface; rainfall and solar radiation; and mean sap flow from 8 replicate probes. Sensors are installed at upland forest (UP), wetlands (W), and transitional locations between these ecosystems (TR). Example datasets are from Goodwin Islands in the Chesapeake Bay and Portage River along the Lake Erie coastline.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Reproductive and leaf litterfall fluxes in forest ecosystem sites globally (1950-2022)

Forest allocation of net primary productivity (NPP) to reproduction is poorly quantified globally, despite its critical role in forest regeneration and a well-supported trade-off with allocation to growth. Although field measurements of total NPP are rare, our work finds that a proxy for reproductive carbon allocation constructed from leaf (L) and reproductive (R) litterfall fluxes, R/(R+L), is strongly correlated with R/NPP, facilitating analysis across a wide range of sites where biometric estimates of NPP are not available (R² = 0.85; Hanbury-Brown et al., 2022, Ward et al., in prep). To investigate relationships between ecosystem-scale reproductive allocation (RA) and climate, soil fertility, and stand age gradients, we conducted a literature search and synthesized 824 observations of annual average leaf and reproductive litterfall fluxes across forest sites globally. The zip file includes 1) a folder Data/ containing the litterfall data ("GlobalForestRA_data.csv") and metadata ("GlobalForestRA_metadata.doc") files. The data file includes geographic coordinates, long-term mean annual temperature and precipitation (1970-2000, extracted from WorldClim2.1), leaf and reproductive litterfall fluxes, sampling interval and protocols, forest characteristics (dominant leaf morphology, information pertaining to forest age and successional stage, and disturbance history) and soil properties (% sand, %silt, %clay, total phosphorus (P), nitrogen (N), cation exchange capacity (CEC) and pH) extracted from SoilGrids250 and from on-site measurements, where available. The metadata file contains information about each variable reported in the data file, including data sources, processing methods, and all references. The Data folder contains two additional files used to create Figure 1; these are described in greater detail in the README.2) R scripts GloalForestRA_analysis.r and GlobalForestRA_SI.r and a folder /Functions used to produce results, figures, and tables in the manuscript Ward et al. (in press)3) a README file describing how the data and R scripts can be used to reproduce statistical results, figures, and tables found in the manuscript. Ward et al. (in press)This repository can also be found at: https://github.com/r-ward/Global_Analysis_ForestRA.Ward, R.E., Zhang-Zheng, H. Aernethy, K., Adu-Bredu, S., Arroyo, L., Bailey, A. et al. (in press). Forest age rivals climate to explain reproductive allocation patterns in forest ecosystems globally. Ecology Letters. Hanbury-Brown, A.R., Ward, R.E. & Kueppers, L.M. (2022). Forest regeneration within Earth system models: current process representations and ways forward. New Phytol., 235, 20–40.Ward et al. (2025), Forest age rivals climate to explain reproductive allocation patterns in forest ecosystems globally, in prep.

54 ENVIRONMENTAL SCIENCES↗