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DOE OSTI2023

How does Mercury Methylation Respond to Intensive Forest Management and the Creation of Anoxia in Floodplain Soils

This research endeavor, entitled “How does Mercury Methylation Respond to Intensive Forest Management and the Creation of Anoxia in Floodplain Soils?” represents a collaborative effort undertaken by the University of North Carolina at Greensboro, led by Principal Investigator Dr. James S. Coleman, the United States Forest Service Santee Experimental Forest (SEF) Station Director Dr. Carl C. Trettin as Co-Principal Investigator, and The Chinese University of Hong Kong Dr. Martin Tsz-Ki Tsui and Dr. Alex T. Chow serving as Co-Principal Investigators. The overarching objective of this proposed project was to capture and elucidate the immediate and short-term effects of forest disturbances, namely clear-cutting and thinning, on the biogeochemical cycling of mercury (Hg) within the SEF in Huger, South Carolina. To accomplish this objective, a two-year exploratory study was proposed to conduct soil sampling and measurements of Hg and toxic methylmercury (MeHg), and soil physiochemical data within the experimental watershed (WS77) at SEF, following the clear-cutting process initiated for the preparation of the native longleaf pine restoration project by the USFS. Based on our mercury and hydrological data assessment, we concluded that the implementation of forest management practices, particularly mechanical thinning and clear-cutting, appears to enhance the potential for Hg methylation. Furthermore, these forest management practices may disrupt and alter the storage, mobility, and transformations of atmospherically deposited Hg in these lowland forests. We advocate for further research to comprehensively evaluate the impact of forest management on Hg cycling within forest ecosystems.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Biogeochemistry of upland to wetland soils, sediments, and surface waters across Mid-Atlantic and Great Lakes coastal interfaces

Transferable and mechanistic understanding of cross-scale interactions is necessary to predict how coastal systems respond to global change. Cohesive datasets across geographically distributed sites can be used to examine how transferable a mechanistic understanding of coastal ecosystem control points is. To address the above research objectives, data were collected by the EXploration of Coastal Hydrobiogeochemistry Across a Network of Gradients and Experiments (EXCHANGE) Consortium – a regionally distributed network of researchers that collaborated on experimental design, methodology, collection, analysis, and publication. The EXCHANGE Consortium collected samples from 52 coastal terrestrial-aquatic interfaces (TAIs) during Fall of 2021. At each TAI, samples collected include soils from across a transverse elevation gradient (i.e., coastal upland forest, transitional forest, and wetland soils), surface waters, and nearshore sediments across research sites in the Great Lakes and Mid-Atlantic regions (Chesapeake and Delaware Bays) of the continental USA. The first campaign measures surface water quality parameters, bulk geochemical parameters on water, soil, and sediment samples, and physicochemical parameters of sediment and soil.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Soil Carbon Dynamics Following Land Use Changes and Conversion to Oil Palm Plantations in Tropical Lowlands Inferred From Radiocarbon

We measured the 14C and 13C isotopic values of soil organic carbon in mineral soil from lowland tropical forests to provide insight into how quickly carbon is turning over in the soil following conversion of primary forests to oil palm plantations. In addition to areas converted to oil palm plantations in Peru, Indonesia, and Cameroon, we examine pastures and secondary forests in Peru as a comparison to the carbon cycling processes operating in the oil palm plantations.This dataset includes radiocarbon (Δ14C) and stable carbon (δ13C) isotopes of soil organic carbon in mineral soils from natural lowland forests and oil palm plantations in Peru, Indonesia, and Cameroon. We additionally examine plots of secondary forests following agricultural use and pastures on cleared natural forest in Peru. In addition to isotopic data, this dataset includes soil carbon and nitrogen concentrations and stock, soil texture (percent sand, silt, and clay), pH, ECEC (effective cation exchange capacity), base saturation, and bulk density. Soils were sampled in 4 depth increments to 100 cm depth.This dataset supports the publication Finstad et al., 2020. Finstad, K., van Straaten, O., Veldkamp, E., & McFarlane, K. (2020). Soil carbon dynamics following land use changes and conversion to oil palm plantations in tropical lowlands inferred from radiocarbon. Global Biogeochemical Cycles, 34, e2019GB006461. https://doi.org/10.1029/2019GB006461

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

KBase Narrative - Metagenome-assembled genomes from Amazonian soil microbial consortia

We report 17 metagenome-assembled genomes (MAGs) recovered from microbial consortia of forest and pasture soils, in the Brazilian Eastern Amazon. Recovered MAGs constitute novel genomes with the potential to act in important ecological processes, including the degradation of carbohydrate and sulfur and nitrogen cycling.

Mandro, Jessica Adriele↗

DOE OSTI2026

Untargeted, tandem mass spectrometry (LC/MS-MS) metaproteomes from soil samples in control and warming plots in Blodgett Forest, CA (2014-2021)

The pathways of carbon transport and loss through and from soils—soil organic matter (SOM) depolymerization to dissolved organic carbon and mineralization to carbon dioxide (CO2)—are fundamentally driven by microbial activity, which is strongly regulated by environmental conditions. As part of Lawrence Berkeley National Laboratory (LBNL) Terrestrial Ecosystem Science (TES) Belowground Biogeochemistry Science Focus Area (SFA), we have established a novel whole-soil long-term warming experiment at the University of California (UC) Blodgett Forest Research Station (Sierra Nevada) in 2014, where we study the role of biogeochemical, microbial and geochemical process interactions in SOM decomposition and stabilization. This package contains soil metaproteomics data in the context of site specific metagenomes from soil depth profiles in three paired control and warming plots from a temperate mixed forest in Northern California. Each paired plot had been subjected to experimental warming since June 2014 to simulate a predicted climate change scenario for northern California. These metaproteomes were collected in 2018 after 4.5 years of warming from five depth intervals (0-10 cm, 10-30 cm, 30-45 cm, 45-60 cm, 60-80 cm). For protein identification, the collected spectra were searched following a target-decoy search strategy against a database of metagenome predicted proteins (covering 96 samples from 2014 to 2021) representing the complete sequence diversity at the site. Data was searched with mass spectrometry database search tool (MS-GF+) using Pacific Northwest National Laboratory (PNNL)'s Data Management System (DMS) Processing pipeline. The metagenomes are published as part of another data package. Raw metaproteomic data and the data products from MS-GF+ are deposited in the Mass Spectrometry Interactive Virtual Environment (MassIVE) database under accession no. MSV000097826. Here we present a dataset that includes spectral counts for the detected proteins across samples (EMSL50964_BrodieAllMAGs_Globals_SC.txt), the sequences of the detected proteins, and sample metadata file that contains site information for the soil metaproteome samples.

Belowground Biogeochemistry Science Focus Area↗

DOE OSTI2020

A Causal Inference Model Based on Random Forests to Identify the Effect of Soil Moisture on Precipitation

Soil moisture influences precipitation mainly through its impact on land–atmosphere interactions. Understanding and correctly modeling soil moisture–precipitation (SM–P) coupling is crucial for improving weather forecasting and subseasonal to seasonal climate predictions, especially when predicting the persistence and magnitude of drought. However, the sign and spatial structure of SM–P feedback are still being debated in the climate research community, mainly due to the difficulty in establishing causal relationships and the high degree of nonlinearity in land–atmosphere processes. To this end, we developed a causal inference model based on the Granger causality analysis and a nonlinear machine learning model. This model includes three steps: nonlinear anomaly decomposition, nonlinear Granger causality analysis, and evaluation of the quality of SM–P feedback, which eliminates the nonlinear response of interannual and seasonal variability and the memory effects of climatic factors and isolates the causal relationship of local SM–P feedback. We applied this model by using National Climate Assessment–Land Data Assimilation System (NCA-LDAS) datasets over the United States. Here, the results highlight the importance of nonlinear atmosphere responses in land–atmosphere interactions. In addition, the strong feedback over the southwestern United States and the Great Plains both highlight the impacts of topographic factors rather than only the sensitivity of evapotranspiration to soil moisture. Furthermore, the SM–P index defined by our framework is used to benchmark Earth system models (ESMs), which provides a new metric for efficiently identifying potential model biases in modeling local land–atmosphere interactions and may help the development of ESMs in improving simulations of water cycle variability and extremes.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Differences in soil organic matter between EcM- and AM-dominated forests depend on tree and fungal identity

As global change shifts the species composition of forests, we need to understand which species characteristics affect soil organic matter (SOM) cycling to predict future soil carbon (C) storage. Recently, whether a tree species forms a symbiosis with arbuscular (AM) versus ectomycorrhizal (EcM) fungi has been suggested as a strong predictor of soil C storage, but there is wide variability within EcM systems. In this study, we investigated how mycorrhizal associations and the species composition of canopy trees and mycorrhizal fungi related to the proportion of soil C and nitrogen (N) in mineral associations and soil C:N across four sites representing distinct climates and tree communities in the eastern US broadleaf forest biome. In two of our sites, we found the expected relationship of declining mineral-associated C and N and increasing soil C:N ratios as the basal area of EcM-associating trees increased. However, across all sites these soil properties strongly correlated with canopy tree and fungal species composition. Sites where the expected pattern with EcM basal area was observed were (1) dominated by trees with lower quality litter in the Pinaceae and Fagaceae families and (2) dominated by EcM fungi with medium-distance exploration type hyphae, melanized tissues, and the potential to produce peroxidases. Here, this observational study demonstrates that differences in SOM between AM and EcM systems are dependent on the taxa of trees and EcM fungi involved. Important information is lost when the rich mycorrhizal symbiosis is reduced to two categories.

mineral-associated organic matter↗

DOE OSTI2025

Metagenome-assembled genomes from soil samples in control and warming plots in Blodgett Forest, CA (2014-2021)

The pathways of carbon transport and loss through and from soils—soil organic matter (SOM) depolymerization to dissolved organic carbon and mineralization to carbon dioxide (CO2)—are fundamentally driven by microbial activity, which is strongly regulated by environmental conditions. As part of LBNL (Lawrence Berkeley National Laboratory) TES (Terrestrial Ecosystem Science) Belowground Biogeochemistry Science Focus Area (SFA), we have established a novel whole-soil long-term warming experiment at the University of California (UC) Blodgett Forest Research Station (Sierra Nevada) in 2014, where we study the role of biogeochemical, microbial and geochemical process interactions in SOM decomposition and stabilization.Here, we present metagenome-assembled genomes (MAGs) for the bacterial and archaeal community from soil depth profiles collected from 2014 to 2021 from three paired control and warming plots. We collected soil samples across a range of depth profiles (spanning surface to 90 cm deep) from three paired control and warming plots from a temperate mixed forest in Northern California. Each paired plot had been subjected to experimental warming since June 2014 to simulate a predicted climate change scenario for northern California. 101 soil metagenomes were sequenced at JGI (Joint Genome Institute) and UCSF (University of California San Francisco) Center for Advanced Technology and can be found under the JGI (Joint Genome Institute) GOLD (Genomes Online Database) Sequencing project Gs0151586 and NCBI (National Center for Biotechnology Information) Projects PRJNA1225762 and PRJEB39497. Metagenomes were assembled using JGI (Joint Genome Institute) Metagenome Workflow (10.1128/mSystems.00804-20). For each metagenome, the assembled contigs were binned into genomes using 3 binning algorithms (cocacola, metabat, and maxbin) and the resulting bins were consolidated using dastool. The consolidated bins from all metagenomes were pooled, filtered by completeness (>50%) and contamination (<25%), and dereplicated at 99% ANI (average nucleotide identity) using dRep (https://github.com/MrOlm/drep).The dataset includes a zip file of 2321 MAG (Metagenome Assembled Genome) fasta files, the accession numbers for the underlying metagenomes, and a csv file with MAG (Metagenome Assembled Genome) quality metrics and taxonomic classification (GTDB -Genome Taxonomy Database-RS220). This dataset also includes a file-level metadata (flmd.csv) file that lists each file contained in the dataset with associated metadata and a data dictionary (dd.csv) file that contains column/row headers used throughout the files along with a definition, units, and data type. A sample metadata file (samples.csv) that contains site information has also been included.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Dissection of Carbon and Nitrogen Cycling in Post-Fire Soil Environments using a Genome- Informed Experimental Community (Final Technical Report)

Wildfires are a natural part of many forest ecosystems, with globally important carbon (C) storage and nutrient cycling consequences, and they are increasing in frequency and severity in Western North America. Forest fires affect soil C stocks in complex ways; some C is released into the atmosphere through combustion, while a large percentage of the C is added to the soil in the form of pyrogenic organic matter. Worldwide, it is estimated that 16% of soil organic matter is pyrogenic, while locally, this number may be as high as 80%. Understanding how wildfires affect soil organic matter cycling requires understanding how microbes respond to pyrogenic organic matter and other post-fire soil conditions. However, our understanding of microbial interactions within post-fire soil was in its infancy at the time of our proposal. Outstanding questions included: Which microbes are capable of degrading pyrogenic organic matter? What are the relevant genes and metabolites associated with this degradation? What are the key interactions among post-fire microbes? Key highlights of outcomes supported by this grant included training eleven early-career scientists and two early-career PIs, publication of twelve peer-reviewed papers, cross-lab collaborations that empowered complex scientific approaches, the development of an open-source automated gas sampler to drive novel insights in C cycling, enhanced understanding of post-fire microbial community dynamics, and novel genetic and molecular insights into microbial responses to fire.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Short-term warming increased soil heterotrophic respiration due to enhanced active microbial community

Soil microbes, particularly active microbes, play a crucial role in conserving soil carbon under climate change, especially in forest ecosystems, constituting over 50% of global soil organic carbon. Nevertheless, the response mechanisms of active microbial community to climate warming and their subsequent impacts on soil heterotrophic respiration (Rh) remain insufficiently understood. To resolve this mechanistic uncertainty, we implemented a 3-year soil translocation experiment to investigate soil warming effects on active microbial community and Rh. We used 16S rRNA gene amplicon sequencing, Metatranscriptomics sequencing, coupled with correlation analyses to explore the linkages between warming-induced shifts in Rh and the active microbial community. Our results demonstrated that warming of soil induced a 55% enhancement in Rh. Concurrently, the Shannon index and Richness of active microbial community increased by 20% and 117%, respectively. Warming significantly altered active microbial community composition, inducing a compositional shift characterized by 0.5-to 2-fold increases in the abundances of Proteobacteria, Chloroflexi, and Actinobacteria. Our study also revealed 92–100% increases in the abundance of C-degradation functional genes encoding starch, cellulose, and lignin decomposition pathways within active microbial community under warming. Statistical analyses identified significant positive correlations between Rh and the abundance of Proteobacteria and Actinobacteria, as well as expression levels of functional genes associated with lignin and cellulose decomposition pathways. Furthermore, our results suggested that short-term warming increased Rh through altering diversity, species composition, and C degradation functional genes of active microbial community providing insights into the influence of microbial communities on soil C-climate feedbacks under climate warming.

Active microbial community↗

DOE OSTI2025

Soil Particulate Organic Matter is Related to Ericoid Mycorrhizal Shrubs, not Ectomycorrhizal Trees, in a Temperate Forest

Mycorrhizal associations are key drivers of soil biogeochemistry, but previous studies have focused almost exclusively on ectomycorrhizal (EcM) and arbuscular mycorrhizal (AM) associations. Ericoid mycorrhizal (ErM) shrubs frequently occur in forest understories and are expanding in response to disturbance, but are rarely considered in biogeochemical frameworks. We investigated the relationships of understory ErM shrubs and overstory trees on carbon (C) and nitrogen (N) in soil organic matter fractions in a southern Appalachian temperate forest. We sampled the 0–10 cm mineral soil layer from 43 plots at the Coweeta Hydrologic Laboratory, across gradients in overstory EcM dominance and understory ErM shrub biomass. Soil C:N ratios increased with both increasing EcM dominance and increasing ErM shrub biomass. However, total particulate organic matter (POM) C, and the proportion of C and N held in POM increased with increasing ErM shrub biomass, but not with increasing EcM dominance. In contrast, mineral-associated organic matter (MAOM) C and N were negatively associated with EcM dominance, but were not related to ErM shrubs. Our findings suggest that ErM shrubs facilitate POM formation while AM trees promote MAOM formation. Because ErM shrub biomass represents a small fraction of total forest biomass, our work provides evidence that ErM shrubs have an outsized effect on soil organic matter, which advocates for their inclusion in mechanistic studies and biogeochemical frameworks.

Bonilla, Kayla A. [University of Georgia, Athens, ↗

DOE OSTI2021

Mycorrhizal associations of tree species influence soil nitrogen dynamics via effects on soil acid–base chemistry

Across all spatial scales, ECM-dominated forests were associated with greater soil acidity. In particular, ECM-dominated soils exhibited lower soil pH and base cations, although the magnitude of mycorrhizal-associated differences in soil acid–base chemistry depended on the biomes, with differences being more pronounced in temperate than in sub/tropical forests. Higher lignin and lower base cations in ECM tree leaf litter were related to greater soil acidity in ECM-dominated forests. Moreover, the lower inorganic N concentrations and slower N transformation rates in ECM-dominated forests were associated with their greater soil acidity. Our results indicate that the scale-invariant feedbacks between plant nutrient-use strategies and soil properties have the potential to impact forest community assembly and ecosystem processes, particularly in the context of global change.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Using respiration quotients to track changing sources of soil respiration seasonally and with experimental warming

Developing a more mechanistic understanding of soil respiration is hampered by the difficulty in determining the contribution of different organic substrates to respiration and in disentangling autotrophic-versus-heterotrophic and aerobic-versus-anaerobic processes. Here, we use a relatively novel tool for better understanding soil respiration: the apparent respiration quotient (ARQ). The ARQ is the amount of CO 2 produced in the soil divided by the amount of O 2 consumed, and it changes according to which organic substrates are being consumed and whether oxygen is being used as an electron acceptor. We investigated how the ARQ of soil gas varied seasonally, by soil depth, and by in situ experimental warming ( +4 ° C) in a coniferous-forest whole-soil-profile warming experiment over 2 years. We then compared the patterns in ARQ to those of soil δ 13 CO 2 . Our measurements showed strong seasonal variations in ARQ, from ≈0.9 during the late spring and summer to ≈0.7 during the winter. This pattern likely reflected a shift from respiration being fueled by oxidized substrates like sugars and organic acids derived from root and root respiration during the growing season to more reduced substrates such as lipids and proteins derived from microbial necromass during the winter. This interpretation was supported by δ 13 CO 2 values, which were lower, like lipids, in the winter and higher, like sugars, in the summer. Furthermore, experimental warming significantly changed how both ARQ and δ 13 CO 2 responded to soil temperature. Wintertime ARQ and δ 13 CO 2 values were higher in heated than in control plots, probably due to the warming-driven increase in microbial activity that may have utilized oxidized carbon substrates, while growing-season values were lower in heated plots. Experimental warming and phenology change the sources of soil respiration throughout the soil profile. The sensitivity of ARQ to these changes demonstrates its potential as a tool for disentangling the biological sources contributing to soil respiration.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2026

1H-NMR characterization of soil dissolved organic matter from soil samples in control and warming plots in Blodgett Forest, CA (2014 and 2018)

1H-NMR (nucleic magnetic resonance) spectroscopy↗

DOE OSTI2025

High resolution characterization of soil dissolved organic matter with FTICR-MS (Fourier-transform ion cyclotron resonance mass spectrometry) from soil samples in control and warming plots in Blodgett Forest, CA (2014 and 2018)

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Litter production and foliar nutrient resorption in fast- and slow-growing tree species in the Central Amazon

Litterfall is crucial for forest maintenance, serving as a primary mechanism for nutrient return to the nutrient-poor soils of tropical forests. Foliar nutrient resorption likewise represents an important nutrient-conservation mechanism. Yet, little is known about how these processes vary between fast- and slow-growing species in post-logging areas of the Amazon forest. Here, the objective of this study was to quantify litterfall production and the resorption of foliar nutrients in fast-growing and slow-growing tree species of the Central Amazon, in a forest that was experimentally logged in 1987. The study was conducted from May 2022 to April 2023. Litterfall was collected biweekly using four collectors that were systematically distributed beneath the canopy of each monitored tree, totaling 72 collectors. Three fast-growing and three slow-growing species were selected, each with three replicates, totaling 18 monitored individuals. Species-specific samples of fresh (green) and senesced (litter) leaves were collected and analyzed for their nutrient content and resorption efficiency. Fast-growing species had a monthly leaf litter deposition of 13.53 ± 1.6 g m −2 month −1 , compared to 2.59 ± 0.4 g m −2 month −1 for slow-growing species. The average annual litter production across both functional types was 8.6 ± 2.6 Mg ha −1 year −1 . Nutrient inputs through litterfall were higher in fast-growing species for all elements, particularly nitrogen (N), with 21.92 ± 4.9 kg ha −1 year −1 . Phosphorus (P) and potassium (K) exhibited the highest foliar resorption. P resorption efficiency was 68.3 % in fast-growing species and 57.8 % in slow-growing species. For K, efficiencies were 59.0 % and 41.7 %, respectively. These results highlight the substantial role that fast-growing species play in restoring forest productivity in managed Amazon forests, both through higher litter deposition and nutrient fluxes, and through nutrient conserving-mechanisms such as foliar nutrient resorption.

Amazon forest↗

DOE OSTI2024

NIST: Soil Respiration, Moisture, Temperature, Chemistry; and Fine Root Measurements from a Transect Through a Forest Edge, Gaithersburg, Maryland, 2017-2021

This dataset contains soil respiration, moisture, temperature, and chemistry, as well as fine root measurements from the National Institute of Standards and Technology (NIST) Forested Optical Reference for Evaluating Sensor Technology (FOREST) research facility at Gaithersburg, Maryland. Measurements were taken at an existing transect array that begins in a grassy meadow, crosses a sharp forest edge, then a small stream, and finally extends upwards in the interior of the forest at the top of a ridge. There are 6 different landscape positions replicated across three transects in the array. Soil respiration was measured during growing seasons in 2017-2019 (2017-06-02 to 2020-02-27). Pedons (1 m3) were isolated from surrounding tree roots using trenching and a fabric to inhibit root ingrowth. Flux measurements inside the pedons were thus assumed to represent heterotrophic only respiration in 2019, and these fluxes were paired with nearby fluxes assumed to represent total respiration. Deep vertical probes measured volumetric moisture content and temperature at the same points in the array every 10 cm in depth to either 90 cm or 120 cm total depth, at 15 minute intervals, from 2019-2021 (2019-07-09 to 2021-09-10). Soil core samples were collected from each of the array points for three different months in early- to mid-2019 (2019-03-19 to 2019-07-10), at three depths each. Soils were analyzed for gravimetric moisture content; pH; total carbon, nitrogen, and phosphorus; texture; microbial biomass carbon, nitrogen, and phosphorus; extractable dissolved organic carbon, nitrogen, and phosphorus; extractable nitrate and ammonia; and extracellular hydrolytic enzyme activities. The fine roots were separated from the cores and segregated by plant functional type (grass or tree species) and if they were dead or alive. Fine roots were then measured for length, surface area, diameter, and dry mass. This dataset contains four data files in comma separated (*.csv) format. These data serve to deepen our understanding of root and soil processes at forest edges and in transitional zones.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Patterns and controls on island‐wide aboveground biomass accumulation in second‐growth forests of Puerto Rico

Abstract Understanding the heterogeneity of biomass accumulation in second‐growth tropical forests following land use abandonment is important for informing ecosystem carbon models and forest restoration efforts. There is an urgent need for a broad sample of second‐growth forests to enhance our knowledge of carbon accumulation in human‐dominated landscapes, especially for older forests. Puerto Rico has predominantly second‐growth forests, ranging in age from approximately 25 to more than 80 years. We used an island‐wide sample of airborne lidar from the NASA Goddard Lidar, Hyperspectral, and Thermal (G‐LiHT) Airborne Imager collected on March 2017, forest inventory data, and data on forest age, precipitation, soils, and land use to estimate aboveground biomass stocks in moist and wet, second‐growth tropical forests. Biomass accumulation rates in Puerto Rico were lower, on average, than in other Neotropical forests. Median biomass across >16,700 ha of older second‐growth forests was 105 Mg ha −1 , and sampled biomass rarely surpassed 250 Mg ha −1 . Differences in biomass by age were large and persistent across different substrates and land uses, with a plateau in the pattern of island‐wide biomass accumulation after about 33 years. A spatial regression model showed that multiple factors were related to biomass accumulation, including time since abandonment, geologic substrate, past land use as coffee or pasture, precipitation, topographic wetness index, and slope. Our findings have important consequences for the total carbon storage and expected climate mitigation benefits of large‐scale reforestation efforts, and highlight the value of airborne lidar for quantifying biomass variability in complex tropical landscapes. Abstract in Spanish is available with online material.

54 ENVIRONMENTAL SCIENCES↗