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Remote Sensing of Lineage Functional Types for Modeling and Monitoring Biodiversity

Hyperspectral remote sensing has the potential to continuously scale plant function and plant diversity information from landscape to global extents. Numerous studies have indicated that VSWIR (400-2500 nm) reflectance properties of vegetation capture evolutionarily conserved biochemical, structural, and other functional attributes of plant species. Spectral properties conserved in plants provide the opportunity to both 1) aggregate species into lineages with improved classification accuracy and 2) link those lineages directly to plant traits. Full realization of this goal will enable parameterization of Land Surface Models (LSMs) with remotely sensed information, e.g., canopy nitrogen, and better representations of biodiversity and functional diversity in biogeographic studies. In this study, we use hyperspectral AVIRIS data from the 2013 HyspIRI campaign over the Southern Sierra Nevada, California flight box to investigate the potential for incorporating evolutionary thinking into landcover classification. We link the airborne hyperspectral data with vegetation plot data from roughly 1372 surveys and a phylogeny representing 1361 species. We aggregate species into lineages ranging from species level groups down to similar number of Plant Functional Types as often used in LSMs. We assessed the ability of Random Forest and Partial Least Squares Discriminant Analysis to discriminate across these different phylogenetic scales and determine the optimal number of lineages to classify. Although there are some temporal and spatial differences in our training data, our best approaches achieved moderate classification accuracy (Kappa > 0.65). Given an optimal number of lineages, we explored approaches to improve classifications including machine learning and unmixing approaches. This work suggests that lineage-based methods may be a promising way to leverage the huge amounts of data that will come from high resolution and high return interval hyperspectral data planned for the Surface Biology and Geology mission with sparsely sampled existing ground-based ecological data.

Hyperspectral↗

DOE OSTI2021

Targeted DNA insertion in plants

Conventional methods of DNA sequence insertion into plants, using Agrobacterium -mediated transformation or microprojectile bombardment, result in the integration of the DNA at random sites in the genome. These plants may exhibit altered agronomic traits as a consequence of disruption or silencing of genes that serve a critical function. Also, genes of interest inserted at random sites are often not expressed at the desired level. For these reasons, targeted DNA insertion at suitable genomic sites in plants is a desirable alternative. In this paper we review approaches of targeted DNA insertion in plant genomes, discuss current technical challenges, and describe promising applications of targeted DNA insertion for crop genetic improvement.

Dong, Oliver Xiaoou↗

DOE OSTI2025

Rooting for function: community‐level fine‐root traits relate to many ecosystem functions

Humans are driving biodiversity change, which also alters community functional traits. However, how changes in the functional traits of the community alter ecosystem functions—especially belowground—remains an important gap in our understanding of the consequences of biodiversity change. We test hypotheses for how the root traits of the root economics space (composed of the collaboration and conservation gradients) are associated with proxies for ecosystem functioning across grassland and forest ecosystems in both observational and experimental datasets from 810 plant communities. First, we assessed whether community-weighted means of the root economics space traits adhered to the same trade-offs as species-level root traits. Then, we examined the relationships between community-weighted mean root traits and aboveground biomass production, root standing biomass, soil fauna biomass, soil microbial biomass, decomposition of standard and plot-specific material, ammonification, nitrification, phosphatase activity, and drought resistance. We found evidence for a community collaboration gradient but not for a community conservation gradient. Yet, links between community root traits and ecosystem functions were more common than we expected, especially for aboveground biomass, microbial biomass, and decomposition. These findings suggest that changes in species composition, which alter root trait means, will in turn affect critical ecosystem functions.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

The three-dimensional construction of leaves is coordinated with water use efficiency in conifers

Conifers prevail in the canopies of many terrestrial biomes, holding a great ecological and economic importance globally. Current increases in temperature and aridity are imposing high transpirational demands and resulting in conifer mortality. Therefore, identifying leaf structural determinants of water use efficiency is essential for predicting physiological impacts due to environmental variation. Here, using synchrotron-generated microtomography imaging, we extracted leaf volumetric anatomy and stomatal traits in 34 species across conifers with a special focus on Pinus , the richest conifer genus. We show that intrinsic water use efficiency (WUE i ) is positively driven by leaf vein volume. Needle-like leaves of Pinus , as opposed to flat leaves or flattened needles of other genera, showed lower mesophyll porosity, decreasing the relative mesophyll volume. This led to increased ratios of stomatal pore number per mesophyll or intercellular airspace volume, which emerged as powerful explanatory variables, predicting both stomatal conductance and WUE i . Our results clarify how the three-dimensional organisation of tissues within the leaf has a direct impact on plant water use and carbon uptake. By identifying a suite of structural traits that influence important physiological functions, our findings can help to understand how conifers may respond to the pressures exerted by climate change.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Novel Mutant Alleles Reveal a Role of the Extra-Large G Protein in Rice Grain Filling, Panicle Architecture, Plant Growth, and Disease Resistance

Plant growth and grain filling are the key agronomical traits for grain weight and yield of rice. The continuous improvement in rice yield is required for a future sustainable global economy and food security. The heterotrimeric G protein complex containing a canonical α subunit (RGA1) couples extracellular signals perceived by receptors to modulate cell function including plant development and grain weight. We hypothesized that, besides RGA1, three atypical, extra-large GTP-binding protein (XLG) subunits also regulate panicle architecture, plant growth, development, grain weight, and disease resistance. Here, we identified a role of XLGs in agronomic traits and stress tolerance by genetically ablating all three rice XLGs individually and in combination using the CRISPR/Cas9 genome editing in rice. For this study, eight (three single, two double, and three triple) null mutants were selected. Three XLG proteins combinatorically regulate seed filling, because loss confers a decrease in grain weight from 14% with loss of one XLG and loss of three to 32% decrease in grain weight. Null mutations in XLG2 and XLG4 increase grain size. The mutants showed significantly reduced panicle length and number per plant including lesser number of grains per panicle compared to the controls. Loss-of-function of all individual XLGs contributed to 9% more aerial biomass compared to wild type (WT). The double mutant showed improved salinity tolerance. Moreover, loss of the XLG gene family confers hypersensitivity to pathogens. Our findings suggest that the non-canonical XLGs play important roles in regulating rice plant growth, grain filling, panicle phenotype, stress tolerance, and disease resistance. Genetic manipulation of XLG s has the potential to improve agronomic properties in rice.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Turbo‐charging crop improvement: harnessing multiplex editing for polygenic trait engineering and beyond

Multiplex CRISPR editing has emerged as a transformative platform for plant genome engineering, enabling the simultaneous targeting of multiple genes, regulatory elements, or chromosomal regions. This approach is effective for dissecting gene family functions, addressing genetic redundancy, engineering polygenic traits, and accelerating trait stacking and de novo domestication. Its applications now extend beyond standard gene knockouts to include epigenetic and transcriptional regulation, chromosomal engineering, and transgene‐free editing. These capabilities are advancing crop improvement not only in annual species but also in more complex systems such as polyploids, undomesticated wild relatives, and species with long generation times. At the same time, multiplex editing presents technical challenges, including complex construct design and the need for robust, scalable mutation detection. We discuss current toolkits and recent innovations in vector architecture, such as promoter and scaffold engineering, that streamline workflows and enhance editing efficiency. High‐throughput sequencing technologies, including long‐read platforms, are improving the resolution of complex editing outcomes such as structural rearrangements—often missed by standard genotyping—when targeting repetitive or tandemly spaced loci. To fully realize the potential of multiplex genome engineering, there is growing demand for user‐friendly, synthetic biology‐compatible, and scalable computational workflows for gRNA design, construct assembly, and mutation analysis. Experimentally validated inducible or tissue‐specific promoters are also highly desirable for achieving spatiotemporal control. As these tools continue to evolve, multiplex CRISPR editing is poised to become a foundational technology of next‐generation crop improvement to address challenges in agriculture, sustainability, and climate resilience.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2026

Genomic signatures in Variovorax enabling colonization of the Populus endosphere

Microbial colonization of plant roots involves strong selective pressures that shape the structure and function of root-associated communities. In particular, the endosphere represents a highly selective environment requiring host entry and in planta persistence. However, strain-specific microbial traits that enable endosphere colonization remain poorly understood. Here, we use a defined, genome-resolved community of 28 Variovorax strains isolated from the roots of Populus deltoides and Populus trichocarpa (poplar trees) to determine which strains partition between rhizosphere and endosphere compartments and to identify the genomic traits associated with endosphere specialization. By combining strain-resolved metagenomic profiling, comparative genomics, and functional assays, we demonstrate that dominant endosphere colonizers are enriched in genes related to nutrient metabolism, redox balance, transcriptional regulation, and a conserved L-fucose utilization pathway experimentally shown to enhance root colonization. Not all strains succeed through the same strategy. Community-wide functional profiling revealed a distinct and reduced set of traits in the endosphere, including orthogroups associated with low-abundance strains that were overlooked in strain-level analyses. These findings reveal that multiple ecological strategies, such as metabolic competition, regulatory adaptation, and niche specialization, can support endosphere colonization. Our results advance the understanding of how bacterial colonization traits are distributed and deployed within a plant microbiome and suggest that host filtering selects for distinct, and sometimes complementary, microbial strategies. This work supports a shift toward mechanistic, genome-resolved models of microbiome assembly and offers a framework for linking microbial function to host colonization success.

comparative genomics↗

DOE OSTI2022

High–throughput measurement of plant fitness traits with an object detection method using Faster R–CNN

Revealing the contributions of genes to plant phenotype is frequently challenging because loss-of-function effects may be subtle or masked by varying degrees of genetic redundancy. Such effects can potentially be detected by measuring plant fitness, which reflects the cumulative effects of genetic changes over the lifetime of a plant. However, fitness is challenging to measure accurately, particularly in species with high fecundity and relatively small propagule sizes such as Arabidopsis thaliana. An image segmentation-based method using the software ImageJ and an object detection-based method using the Faster Region-based Convolutional Neural Network (R-CNN) algorithm were used for measuring two Arabidopsis fitness traits: seed and fruit counts. The segmentation-based method was error-prone (correlation between true and predicted seed counts, r 2 = 0.849) because seeds touching each other were undercounted. By contrast, the object detection-based algorithm yielded near perfect seed counts (r 2 = 0.9996) and highly accurate fruit counts (r 2 = 0.980). Comparing seed counts for wild-type and 12 mutant lines revealed fitness effects for three genes; fruit counts revealed the same effects for two genes. Our study provides analysis pipelines and models to facilitate the investigation of Arabidopsis fitness traits and demonstrates the importance of examining fitness traits when studying gene functions.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Dynamic ecosystem assembly and escaping the “fire trap” in the tropics: insights from FATES_15.0.0

Abstract. Fire is a fundamental part of the Earth system, with impacts on vegetation structure, biomass, and community composition, the latter mediated in part via key fire-tolerance traits, such as bark thickness. Due to anthropogenic climate change and land use pressure, fire regimes are changing across the world, and fire risk has already increased across much of the tropics. Projecting the impacts of these changes at global scales requires that we capture the selective force of fire on vegetation distribution through vegetation functional traits and size structure. We have adapted the fire behavior and effects module, SPITFIRE (SPread and InTensity of FIRE), for use with the Functionally Assembled Terrestrial Ecosystem Simulator (FATES), a size-structured vegetation demographic model. We test how climate, fire regime, and fire-tolerance plant traits interact to determine the biogeography of tropical forests and grasslands. We assign different fire-tolerance strategies based on crown, leaf, and bark characteristics, which are key observed fire-tolerance traits across woody plants. For these simulations, three types of vegetation compete for resources: a fire-vulnerable tree with thin bark, a vulnerable deep crown, and fire-intolerant foliage; a fire-tolerant tree with thick bark, a thin crown, and fire-tolerant foliage; and a fire-promoting C4 grass. We explore the model sensitivity to a critical parameter governing fuel moisture and show that drier fuels promote increased burning, an expansion of area for grass and fire-tolerant trees, and a reduction of area for fire-vulnerable trees. This conversion to lower biomass or grass areas with increased fuel drying results in increased fire-burned area and its effects, which could feed back to local climate variables. Simulated size-based fire mortality for trees less than 20 cm in diameter and those with fire-vulnerable traits is higher than that for larger and/or fire-tolerant trees, in agreement with observations. Fire-disturbed forests demonstrate reasonable productivity and capture observed patterns of aboveground biomass in areas dominated by natural vegetation for the recent historical period but have a large bias in less disturbed areas. Though the model predicts a greater extent of burned fraction than observed in areas with grass dominance, the resulting biogeography of fire-tolerant, thick-bark trees and fire-vulnerable, thin-bark trees corresponds to observations across the tropics. In areas with more than 2500 mm of precipitation, simulated fire frequency and burned area are low, with fire intensities below 150 kW m−1, consistent with observed understory fire behavior across the Amazon. Areas drier than this demonstrate fire intensities consistent with those measured in savannas and grasslands, with high values up to 4000 kW m−1. The results support a positive grass–fire feedback across the region and suggest that forests which have existed without frequent burning may be vulnerable at higher fire intensities, which is of greater concern under intensifying climate and land use pressures. The ability of FATES to capture the connection between fire disturbance and plant fire-tolerance strategies in determining biogeography provides a useful tool for assessing the vulnerability and resilience of these critical carbon storage areas under changing conditions across the tropics.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Identifying ecological and evolutionary research targets and risks in climate change studies to break barriers to broad inference

Understanding the responses of plants, microbes, and their interactions to long-term climate change is essential to identifying the traits, genes, and functions of organisms that maintain ecosystem stability and function of the biosphere. However, many studies investigating organismal responses to climate change are limited in their scope along several key ecological, evolutionary, and environmental axes, creating barriers to broader inference. Broad inference, or the ability to apply and validate findings across these axes, is a vital component of achieving climate preparedness in the future. Breaking barriers to broad inference requires accurate cross-ecosystem interpretability and the identification of reliable frameworks for how these responses will manifest. Current approaches have generated a valuable, yet sometimes contradictory or context dependent, understanding of responses to climate change factors from the organismal- to ecosystem-level. In this synthesis, we use plants, soil microbial communities, and their interactions as examples to identify five major barriers to broad inference and resultant target research areas. We also explain risks associated with disregarding these barriers to broad inference and potential approaches to overcoming them. Developing and funding experimental frameworks that integrate basic ecological and evolutionary principles and are designed to capture broad inference across levels of organization is necessary to further our understanding of climate change on large scales.

Love, Sarah J. (ORCID:0000000180787373)↗

DOE OSTI2024

Phosphoribosylpyrophosphate synthetase as a metabolic valve advances Methylobacterium/Methylorubrum phyllosphere colonization and plant growth

The proficiency of phyllosphere microbiomes in efficiently utilizing plant-provided nutrients is pivotal for their successful colonization of plants. The methylotrophic capabilities of Methylobacterium/Methylorubrum play a crucial role in this process. However, the precise mechanisms facilitating efficient colonization remain elusive. In the present study, we investigate the significance of methanol assimilation in shaping the success of mutualistic relationships between methylotrophs and plants. A set of strains originating from Methylorubrum extorquens AM1 are subjected to evolutionary pressures to thrive under low methanol conditions. A mutation in the phosphoribosylpyrophosphate synthetase gene is identified, which converts it into a metabolic valve. This valve redirects limited C1-carbon resources towards the synthesis of biomass by up-regulating a non-essential phosphoketolase pathway. These newly acquired bacterial traits demonstrate superior colonization capabilities, even at low abundance, leading to increased growth of inoculated plants. This function is prevalent in Methylobacterium/Methylorubrum strains. In summary, our findings offer insights that could guide the selection of Methylobacterium/Methylorubrum strains for advantageous agricultural applications.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Assessing climate change impacts on live fuel moisture and wildfire risk using a hydrodynamic vegetation model

Abstract. Live fuel moisture content (LFMC) plays a critical role in wildfire dynamics, but little is known about responses of LFMC to multivariate climate change, e.g., warming temperature, CO2 fertilization, and altered precipitation patterns, leading to a limited prediction ability of future wildfire risks. Here, we use a hydrodynamic demographic vegetation model to estimate LFMC dynamics of chaparral shrubs, a dominant vegetation type in fire-prone southern California. We parameterize the model based on observed shrub allometry and hydraulic traits and evaluate the model's accuracy through comparisons between observed and simulated LFMC of three plant functional types (PFTs) under current climate conditions. Moreover, we estimate the number of days per year of LFMC below 79 % (which is a critical threshold for wildfire danger rating of southern California chaparral shrubs) from 1960 to 2099 for each PFT and compare the number of days below the threshold for medium and high greenhouse gas emission scenarios (RCP4.5 and 8.5). We find that climate change could lead to more days per year (5.2 %–14.8 % increase) with LFMC below 79 % between the historical (1960–1999) and future (2080–2099) periods, implying an increase in wildfire danger for chaparral shrubs in southern California. Under the high greenhouse gas emission scenario during the dry season, we find that the future LFMC reductions mainly result from a warming temperature, which leads to 9.1 %–18.6 % reduction in LFMC. Lower precipitation in the spring leads to a 6.3 %–8.1 % reduction in LFMC. The combined impacts of warming and precipitation change on fire season length are equal to the additive impacts of warming and precipitation change individually. Our results show that the CO2 fertilization will mitigate fire risk by causing a 3.5 %–4.8 % increase in LFMC. Our results suggest that multivariate climate change could cause a significant net reduction in LFMC and thus exacerbate future wildfire danger in chaparral shrub systems.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

California annual grass phenology and allometry influence ecosystem dynamics and fire regime in a vegetation demography model

Grass-dominated ecosystems cover wide areas of the land surface yet have received far less attention from the Earth System Model (ESM) community. This limits model projections of ecosystem dynamics in response to global change and coupled vegetation–climate dynamics. We used the Functionally Assembled Terrestrial Ecosystem Simulator (FATES), a dynamic vegetation demography model, to determine ecosystem sensitivity to alternate, observed grass allometries and biophysical traits, and evaluated model performance in capturing California C 3 annual grasslands structure and fire regimes. Grass allometry, leaf physiology, plant phenology, and plant mortality all drove the seasonal variation in matter and energy exchange and fire dynamics in California annual grasslands. Allometry influenced grassland structure and function mainly through canopy architecture-mediated space and light competition instead of through carbon partitioning strategy. Regional variation in grassland annual burned area was driven by variation in ecosystem productivity. Our study advances the modeling of grassy ecosystems in ESMs by establishing the importance of grass allometry and plant phenology and mortality in driving C 3 annual grassland seasonal dynamics and fire regime. The calibrated annual grass allometry and biophysical traits presented can be applied in future studies to project climate–vegetation–fire feedbacks in annual grass-dominant ecosystems under global change.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

TARP Identifying Critical Thresholds for Acute Response of Plants and Ecosystems to Water Stress at Walker Branch Watershed, 2002-2005

This dataset contains data from a manipulative field study aimed at identifying critical thresholds for acute response of plants and ecosystems to water stress (TARP) that took place at Walker Branch Watershed in Oak Ridge, Tennessee from 2002-2005 (2002-06-20 to 2005-12-16). The study used understory tents for the removal of 100% of the growing-season throughfall and stem flow, to provide data on the impact of acute drought on mechanisms responsible for growth and mortality of deciduous forest canopy trees representative of common plant functional types (Liriodendron and Quercus). Through three years of manipulation (2003, 2004 and 2005; pretreatment measurements in 2002) various measures of tree response to surface moisture deficits were recorded including root and leaf traits, plant nonstructural carbohydrates status, hourly sapflow, basal area, and periodic observations of foliar photosynthesis and conductance. Additionally, environmental data such as air and soil temperature, soil water content, and soil matric potential were recorded. This dataset contains data 16 files in comma-separate (*.csv) format. Additional metadata are provided: 16 data dictionaries and a file-level metadata file in comma separate (*.csv) format and a user guide in PDF (*.pdf) format.

basal area↗

DOE OSTI2021

The genetic basis of the root economics spectrum in a perennial grass

Significance Plants have evolved diverse root form and function across the Earth’s environment, yet only certain types of trait combinations have proved evolutionarily viable. Using a genetic mapping population of the native perennial switchgrass, our study demonstrates multiple genetic linkages among root morphology, growth, and turnover. Switching alleles derived from southern-origin ecotypes to alleles from northern-origin ecotypes increases root turnover but reduces tissue investment in root length construction. The genetic trade-off between construction and turnover likely facilitates the local adaptation of root strategy along the warm to cold climatic gradients of the species range. In practice, our study provides the genetic evidence that increasing switchgrass yield for bioenergy does not directly conflict with enhancing its root-derived carbon sequestration.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Phylogenetic conservatism of mycoparasitism and its contribution to pathogen antagonism

Abstract Closely related species are expected to have similar functional traits due to shared ancestry and phylogenetic inertia. However, few tests of this hypothesis are available for plant‐associated fungal symbionts. Fungal leaf endophytes occur in all land plants and can protect their host plant from disease by a variety of mechanisms, including by parasitizing pathogens (e.g., mycoparasitism). Here, we tested whether phylogenetic relatedness among species of Cladosporium , a widespread genus that includes mycoparasitic species, predicts the effect of this endophyte on the severity of leaf rust disease. First, we used congruence among different marker sequences (i.e., genealogical concordance phylogenetic species recognition criterion) to delimit species of Cladosporium . Next, in a controlled experiment, we quantified both mycoparasitism and disease modification for the selected Cladosporium species. We identified 17 species of Cladosporium ; all the species reduced rust disease severity in our experiment. Cladosporium phylogeny was a significant predictor of mycoparasitism. However, we did not observe a phylogenetic effect on disease severity overall, indicating that other mechanism/s operating independently of shared ancestry also contributed to endophyte effects on disease severity. Indeed, a second experiment showed that Cladosporium endophyte exudates (no live organism) from divergent species groups equally reduced disease severity. Our results reveal that multiple mechanisms contribute to the protective effects of an endophyte against a plant pathogen, but not all traits underlying these mechanisms are phylogenetically conserved.

Barge, Edward G.↗

DOE OSTI2020

Assessing Impacts of Plant Stoichiometric Traits on Terrestrial Ecosystem Carbon Accumulation Using the E3SM Land Model

Carbon (C) enters into the terrestrial ecosystems via photosynthesis and cycles through the system together with other essential nutrients (i.e., nitrogen [N] and phosphorus [P]). Such a strong coupling of C, N, and P leads to the theoretical prediction that limited nutrient availability will limit photosynthesis rate, plant growth, and future terrestrial C dynamics. However, the lack of reliable information about plant tissue stoichiometric constraints remains a challenge for quantifying nutrient limitations on projected global C cycling. In this study, we harmonized observed plant tissue C:N:P stoichiometry from more than 6,000 plant species with the commonly used plant functional type framework in global land models. Using observed C:N:P stoichiometry and the flexibility of these ratios as emergent plant traits, we show that observationally constrained fixed plant stoichiometry does not improve model estimates of present-day C dynamics compared with unconstrained stoichiometry. However, adopting stoichiometric flexibility significantly improves model predictions of C fluxes and stocks. The 21st century simulations with RCP8.5 CO 2 concentrations show that stoichiometric flexibility, rather than baseline stoichiometric ratios, is the dominant controller of plant productivity and ecosystem C accumulation in modeled responses to CO 2 fertilization. The enhanced nutrient limitations and plant P use efficiency mainly explain this result. This study is consistent with the previous consensus that nutrient availability will limit xfuture land carbon sequestration but challenges the idea that imbalances between C and nutrient supplies and fixed stoichiometry limit future land C sinks. We show here that it is necessary to represent nutrient stoichiometric flexibility in models to accurately project future terrestrial ecosystem carbon sequestration.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Tradeoffs and Synergies in Tropical Forest Root Traits and Dynamics for Nutrient and Water Acquisition: Field and Modeling Advances

Vegetation processes are fundamentally limited by nutrient and water availability, the uptake of which is mediated by plant roots in terrestrial ecosystems. While tropical forests play a central role in global water, carbon, and nutrient cycling, we know very little about tradeoffs and synergies in root traits that respond to resource scarcity. Tropical trees face a unique set of resource limitations, with rock-derived nutrients and moisture seasonality governing many ecosystem functions, and nutrient versus water availability often separated spatially and temporally. Root traits that characterize biomass, depth distributions, production and phenology, morphology, physiology, chemistry, and symbiotic relationships can be predictive of plants’ capacities to access and acquire nutrients and water, with links to aboveground processes like transpiration, wood productivity, and leaf phenology. In this review, we identify an emerging trend in the literature that tropical fine root biomass and production in surface soils are greatest in infertile or sufficiently moist soils. We also identify interesting paradoxes in tropical forest root responses to changing resources that merit further exploration. For example, specific root length, which typically increases under resource scarcity to expand the volume of soil explored, instead can increase with greater base cation availability, both across natural tropical forest gradients and in fertilization experiments. Also, nutrient additions, rather than reducing mycorrhizal colonization of fine roots as might be expected, increased colonization rates under scenarios of water scarcity in some forests. Efforts to include fine root traits and functions in vegetation models have grown more sophisticated over time, yet there is a disconnect between the emphasis in models characterizing nutrient and water uptake rates and carbon costs versus the emphasis in field experiments on measuring root biomass, production, and morphology in response to changes in resource availability. Closer integration of field and modeling efforts could connect mechanistic investigation of fine-root dynamics to ecosystem-scale understanding of nutrient and water cycling, allowing us to better predict tropical forest-climate feedbacks.

54 ENVIRONMENTAL SCIENCES↗