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At least 397 records · Page 22

Predicting ecosystem metaphenome from community metagenome: A grand challenge for environmental biology

Abstract Elucidating how an organism's characteristics emerge from its DNA sequence has been one of the great triumphs of biology. This triumph has cumulated in sophisticated computational models that successfully predict how an organism's detailed phenotype emerges from its specific genotype. Inspired by that effort's vision and empowered by its methodologies, a grand challenge is described here that aims to predict the biotic characteristics of an ecosystem, its metaphenome, from nucleic acid sequences of all the species in its community, its metagenome. Meeting this challenge would integrate rapidly advancing abilities of environmental nucleic acids (eDNA and eRNA) to identify organisms, their ecological interactions, and their evolutionary relationships with advances in mechanistic models of complex ecosystems. Addressing the challenge would help integrate ecology and evolutionary biology into a more unified and successfully predictive science that can better help describe and manage ecosystems and the services they provide to humanity.

59 BASIC BIOLOGICAL SCIENCES↗

Aboveground and belowground contributions to ecosystem respiration in a temperate deciduous forest

In this study, we developed a three-way carbon dioxide (CO 2 ) flux-partitioning algorithm that separates net ecosystem exchange (NEE) into aboveground plant respiration (R above ), belowground root and soil respiration (R below ), and gross primary production (GPP). We applied this algorithm to a coupled dataset of continuous chamber-measured soil respiration and eddy covariance (EC)-measured NEE of CO 2 in an oak-hickory (Quercus-Carya) deciduous broadleaf forest from 2006 to 2015. We found that on annual time scale, R below dominated over R above with the former accounting for 66.9–86.4% and the latter 13.6–33.1%, of the total ecosystem respiration (R eco ). The ratio of R below to R above varied seasonally, ranging from 1.77 to 7.25 in growing season, and 1.02 to 4.57 in non-growing season. The temperature sensitivity (E 0 ) of R below was significantly higher than that of R above , and E 0 of R eco responded differently to air and soil temperature. Over the whole study period, annual mean R above , R below , and GPP were 243, 806, and 1170 g C m –2 , respectively, with annual R eco accounting for 89.6% of GPP, of which 68.8% was lost as R below and 20.8% lost as R above , and leaving only 10% of the carbon fixation in ecosystems. Furthermore, these estimates, however, did not consider potential light inhibition of leaf respiration. If we accept the presence of light inhibition, then the daytime three-way partitioning method would underestimate annual R above by 20.4% whereas the nighttime method would overestimate R above by 23.9% and GPP by 4.7%, compared with estimates accounting for light inhibition in leaves.

54 ENVIRONMENTAL SCIENCES↗

Ecosystem service benefits to water users from perennial biomass production

We report although many agree that a transition to renewable energy sources is needed to avoid the climate consequences of continued reliance on fossil sources, price is a barrier. For renewable energy sources, including bioenergy, penetrating energy markets depends on lowering prices to compete with the price of fossil sources, but the tools used in decision making, such as supply curves, exclude non-market benefits from ecosystem services. Here, we extend the economic concept of an economic supply curve to account for ecosystem services co-produced with perennial biomass. We developed three new types of supply curves to visualize the increased supply of biomass (‘sustainable supply’) with sufficient water-quality benefits to offset biomass production costs. Using these tools, we show that the value of water-quality improvements could significantly reduce the break-even price of perennial feedstocks if it were available to farmers. In the most optimistic case, nearly half of potential biomass supply in a large tributary of the Mississippi river basin carried water purification value exceeding the cost of biomass production. Furthermore, adding the value to swimmers and waders offset production cost for over 90% of potential supply. Simulated benefits were context specific. For example, total value for water drinkers peaked at an intermediate level of fertilizer application. Geographically, benefits were highest in the eastern portion of the river basin. This research shows where the sustainable supply is needed and can generate value; the next step is to match this supply with credit buyers. Efforts to internalize the values of ecosystem services into biomass prices could help to meet Biden administration targets to meet 100% of sustainable aviation fuels.

54 ENVIRONMENTAL SCIENCES↗

Can large herbivores enhance ecosystem carbon persistence?

There is growing interest in aligning the wildlife conservation and restoration agenda with climate change mitigation goals. However, the presence of large herbivores tends to reduce aboveground biomass in some open-canopy ecosystems, leading to the possibility that large herbivore restoration may negatively influence ecosystem carbon storage. Furthermore, belowground carbon storage is often ignored in these systems, despite the wide recognition of soils as the largest actively-cycling terrestrial carbon pool. Here, we suggest a shift away from a main focus on vegetation carbon stocks, towards inclusion of whole ecosystem carbon persistence, in future assessments of large herbivore effects on long-term carbon storage. Failure to do so may lead to counterproductive biodiversity and climate impacts of land management actions.

54 ENVIRONMENTAL SCIENCES↗

How to improve scaling from traits to ecosystem processes

Scaling approaches in ecology assume that traits are the main attributes by which organisms influence ecosystem functioning. However, several recent empirical papers have found only weak links between traits and ecosystem functioning, questioning the usefulness of trait-based ecology (TBE). Here, we argue that these studies often suffer from one or more widespread misconceptions. Specifically, these studies often (i) conflict with the conceptual foundations of TBE, (ii) lack theory- or hypothesis-driven selection and use of traits, (iii) tend to ignore intraspecific variation, and (iv) use experimental or study designs that are not well suited to make strong tests of TBE assumptions. Addressing these aspects could significantly improve our ability to scale from traits to ecosystem functioning.

54 ENVIRONMENTAL SCIENCES↗

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↗

Simulating Marine Ecosystem Dynamics and Biogeochemical Cycling With Multiple Plankton Functional Types

Current representations of marine ecosystems in Earth System Models are greatly simplified, neglecting key interactions between dynamic food webs, biogeochemistry, and climate change. We use the Marine Biogeochemistry Library code base within the Community Earth System Model 2.2.2 to create an expanded ecosystem model with eight phytoplankton groups and four zooplankton size classes (MARBL-8P4Z). Incorporating more specific plankton types and size classes has the potential to capture a wider range of possible behaviors of the ecosystem, its complex interactions with biogeochemistry, and its feedback to climate change. It also permits stronger observational constraints, including in situ group-specific biomass and various observational estimates of plankton community composition. MARBL-8P4Z broadly captures observed global-scale patterns in biomass and community composition for both phytoplankton and zooplankton, with a good performance in simulating broad biogeochemistry fields. The model shows comparable spatial patterns and magnitudes to the observed picophytoplankton biomass (Prochlorococcus, Synechococcus, picoeukaryotes), and captures the seasonal cycle of mesozooplankton biomass. Picophytoplankton groups and microzooplankton dominate biomass and production in oligotrophic, subtropical regions, while nano-phytoplankton, diatoms and the larger zooplankton groups prevail at higher latitudes and within upwelling zones. The model simulates reasonable energy transfer efficiency through the food web, with tight linkages between the phytoplankton community composition, zooplankton grazing, and carbon export, with the potential to link to fisheries models. Thus, MARBL-8P4Z has the potential to account for key climate-driven ecological shifts in the plankton that will modify ocean biogeochemistry in the future.

54 ENVIRONMENTAL SCIENCES↗

Widespread spring phenology effects on drought recovery of Northern Hemisphere ecosystems

The time required for an ecosystem to recover from severe drought is a key component of ecological resilience. The phenology effects on drought recovery are, however, poorly understood. These effects centre on how phenology variations impact biophysical feedbacks, vegetation growth and, ultimately, recovery itself. Using multiple remotely sensed datasets, we found that more than half of ecosystems in mid- and high-latitudinal Northern Hemisphere failed to recover from extreme droughts within a single growing season. Earlier spring phenology in the drought year slowed drought recovery when extreme droughts occurred in mid-growing season. Delayed spring phenology in the subsequent year slowed drought recovery for all vegetation types (with importance of spring phenology ranging from 46% to 58%). The phenology effects on drought recovery were comparable to or larger than other well-known postdrought climatic factors. These results strongly suggest that the interactions between vegetation phenology and drought must be incorporated into Earth system models to accurately quantify ecosystem resilience.

54 ENVIRONMENTAL SCIENCES↗

Multiple elements of soil biodiversity drive ecosystem functions across biomes

The role of soil biodiversity in regulating multiple ecosystem functions is poorly understood, limiting our ability to predict how soil biodiversity loss might affect human wellbeing and ecosystem sustainability. Furthermore, combining a global observational study with an experimental microcosm study, we provide evidence that soil biodiversity (bacteria, fungi, protists and invertebrates) is significantly and positively associated with multiple ecosystem functions. These functions include nutrient cycling, decomposition, plant production, and reduced potential for pathogenicity and belowground biological warfare. Our findings also reveal the context dependency of such relationships and the importance of the connectedness, biodiversity and nature of the globally distributed dominant phylotypes within the soil network in maintaining multiple functions. Moreover, our results suggest that the positive association between plant diversity and multifunctionality across biomes is indirectly driven by soil biodiversity. Together, our results provide insights into the importance of soil biodiversity for maintaining soil functionality locally and across biomes, as well as providing strong support for the inclusion of soil biodiversity in conservation and management programmes.

54 ENVIRONMENTAL SCIENCES↗

Observing terrestrial ecosystems and the carbon cycle from space

Modeled terrestrial ecosystem and carbon cycle feedbacks contribute substantial uncertainty to projections of future climate. The limitations of current observing networks contribute to this uncertainty. Here we present a current climatology of global model predictions and observations for photosynthesis, biomass, plant diversity and plant functional diversity. Carbon cycle tipping points occur in terrestrial regions where fluxes or stocks are largest, and where biological variability is highest, the tropics and Arctic/Boreal zones. Global observations are predominately in the mid-latitudes and are sparse in high and low latitude ecosystems. Observing and forecasting ecosystem change requires sustained observations of sufficient density in time and space in critical regions. Using data and theory available now, we can develop a strategy to detect and forecast terrestrial carbon cycle-climate interactions, by combining in situ and remote techniques.

carbon cycle↗

Reduced ecosystem resilience quantifies fine-scale heterogeneity in tropical forest mortality responses to drought

Sensitivity of forest mortality to drought in carbon-dense tropical forests remains fraught with uncertainty, while extreme droughts are predicted to be more frequent and intense. Here, in this study, the potential of temporal autocorrelation of high-frequency variability in Landsat Enhanced Vegetation Index (EVI), an indicator of ecosystem resilience, to predict spatial and temporal variations of forest biomass mortality is evaluated against in situ census observations for 64 site-year combinations in Costa Rican tropical dry forests during the 2015 ENSO drought. Temporal autocorrelation, within the optimal moving window of 24 months, demonstrated robust predictive power for in situ mortality (leave-one- out cross-validation R 2 = 0.54), which allows for estimates of annual biomass mortality patterns at 30 m resolution. Subsequent spatial analysis showed substantial fine-scale heterogeneity of forest mortality patterns, largely driven by drought intensity and ecosystem properties related to plant water use such as forest deciduousness and topography. Highly deciduous forest patches demonstrated much lower mortality sensitivity to drought stress than less deciduous forest patches after elevation was controlled. Our results highlight the potential of high-resolution remote sensing to “fingerprint” forest mortality and the significant role of ecosystem heterogeneity in forest biomass resistance to drought.

59 BASIC BIOLOGICAL SCIENCES↗

Embracing fine-root system complexity in terrestrial ecosystem modeling

Projecting the dynamics and functioning of the biosphere requires a holistic consideration of whole-ecosystem processes. However, biases toward leaf, canopy, and soil modeling since the 1970s have constantly left fine-root systems being rudimentarily treated. As accelerated empirical advances in the last two decades establish clearly functional differentiation conferred by the hierarchical structure of fine-root orders and associations with mycorrhizal fungi, a need emerges to embrace this complexity to bridge the data-model gap in still extremely uncertain models. In this work, we propose a three-pool structure comprising transport and absorptive fine roots with mycorrhizal fungi (TAM) to model vertically resolved fine-root systems across organizational and spatial–temporal scales. Emerging from a conceptual shift away from arbitrary homogenization, TAM builds upon theoretical and empirical foundations as an effective and efficient approximation that balances realism and simplicity. A proof-of-concept demonstration of TAM in a big-leaf model both conservatively and radically shows robust impacts of differentiation within fine-root systems on simulating carbon cycling in temperate forests. Theoretical and quantitative support warrants exploiting its rich potentials across ecosystems and models to confront uncertainties and challenges for a predictive understanding of the biosphere. Echoing a broad trend of embracing ecological complexity in integrative ecosystem modeling, TAM may offer a consistent framework where modelers and empiricists can work together toward this grand goal.

59 BASIC BIOLOGICAL SCIENCES↗

Valuation of ecosystem services in alternative bioenergy landscape scenarios

Abstract Agricultural land in the Midwest is a source of food and fuel, as well as biodiversity. It is also a cause of excess nutrients that make their way to the Mississippi River and the Gulf of Mexico. To address unsustainable changes to biogeochemical cycles and ecosystem functions, a multidisciplinary approach involving social science, natural science, and engineering is often effective. Given the potential of second‐generation biofuels, and capitalizing on the deep‐rooted perennial bioenergy crops capable of thriving in poor soils, we demonstrated an integrated socio‐environmental analysis of the impacts of growing switchgrass within row‐crop landscapes in Illinois. In this study, we model land use scenarios that incorporate switchgrass as a biofuel crop in a Midwest corn‐belt watershed using the Soil Water Assessment Tool coupled with an economic analysis for the Vermilion Basin in Illinois. We estimated the values of ecosystem services under an alternative bioenergy landscape, including commodity and bioenergy crops, changes in biogeochemistry, and recreational services. The estimated annual values of nitrate and sediment reduction attributed to bioenergy crops range from $38 million to $97 million and $16,000 to $197,000, respectively. The annual value of carbon dioxide emission reduction ranges from $1.8 million to $6.1 million based on the initial crop rotation pattern. Estimated average annual values for wildlife viewing, water‐based recreation, and pheasant hunting are $1.24 million, $0.17 million, and $0.3 million, respectively. To our knowledge, this study represents the first effort to comprehensively quantify ecosystem services using a process‐based model, and estimate their value in an alternative bioenergy landscape. The information we generate could aid in understanding the potential for biomass production from marginal land and the total economic value of the landscape at various spatial scales. The framework is useful in fostering alternative bioenergy landscapes with synergies in a food, energy, and conservation nexus.

54 ENVIRONMENTAL SCIENCES↗

Need for Laboratory Ecosystems To Unravel the Structures and Functions of Soil Microbial Communities Mediated by Chemistry

The chemistry underpinning microbial interactions provides an integrative framework for linking the activities of individual microbes, microbial communities, plants, and their environments. Currently, we know very little about the functions of genes and metabolites within these communities because genome annotations and functions are derived from the minority of microbes that have been propagated in the laboratory. Yet the diversity, complexity, inaccessibility, and irreproducibility of native microbial consortia limit our ability to interpret chemical signaling and map metabolic networks. In this perspective, we contend that standardized laboratory ecosystems are needed to dissect the chemistry of soil microbiomes. We argue that dissemination and application of standardized laboratory ecosystems will be transformative for the field, much like how model organisms have played critical roles in advancing biochemistry and molecular and cellular biology. Community consensus on fabricated ecosystems (“EcoFABs”) along with protocols and data standards will integrate efforts and enable rapid improvements in our understanding of the biochemical ecology of microbial communities.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Spatial Study 2022: Water Column, Sediment, and Total Ecosystem Respiration Rates across the Yakima River Basin, Washington, USA (v2)

This dataset supports a broader study examining the drivers of spatial variability in sediment respiration rates in the Yakima River Basin and is associated with the manuscript “Sediment-associated processes account for most of the spatial variation in ecosystem respiration in the Yakima River basin” submitted to Nature Communications Earth & Environment (Garayburu-Caruso et al., in review). The dataset provides ecosystem metabolism estimates generated from streamMetabolizer (Appling et al.; 2018) using data collected during the same five-week period at 48 sites within multiple rivers throughout the Yakima River Basin in Washington, USA. Additionally, it includes the scripts used for the analysis and producing the figures in the manuscript. The contents include streamMetabolizer inputs and outputs and additional relevant data needed to generate the main manuscript results. The data included are: total ecosystem respiration, water respiration, calculated sediment-associated respiration, gross primary production outputs from the river corridor model for the Yakima River Basin, median grain size (d50), depth, dissolved oxygen, water temperature, pressure, and annual oxygen consumption. The associated GitHub repository can be found at https://github.com/river-corridors-sfa/SSS_metabolism. Samples collected during this study were labeled as “Second Spatial Study” or “SSS.” Raw time series sensor data, total suspended solids, and depth data from SSS were published at https://data.ess-dive.lbl.gov/datasets/doi:10.15485/1969566. A subset of data from the SSS samples were published in the contiguous United States (CONUS)-Scale Model-Sample (CM) study data package available at https://data.ess-dive.lbl.gov/view/doi:10.15485/1923689 that presents data from across the CONUS. They include dissolved organic carbon (DOC, measured as non-purgeable organic carbon, NPOC), total nitrogen (TN), grain size, aerobic sediment respiration, dissolved oxygen (DO), and temperature. Parent IDs and Site IDs are consistent between the SSS and CM data packages, and they can be mapped directly so data across packages can be used together. Field metadata for the samples in this da This dataset is comprised of one main data folder with four subfolders. The main data folder contains of (1) file-level metadata; (2) data dictionary; (3) total/water column/sediment respiration; (4) gross primary production (GPP); (5) median grain size (d50); and (6) annual oxygen consumption. The “Figures” subfolder contains the figures used in the paper and all intermediate files (including geospatial files). The “Published_Data” contains a readme directing the user to download the public data to reproduce analyses and figures. The “Scripts” folder contains all scripts used in the analyses that were not part of running StreamMetabolizer. Lastly, the “Stream_Metabolizer” folder contains all files associated with running StreamMetabolizer including (1) model input files, (2) model output files, (3) processing scripts, (4) histogram plots of the outputs, and (5) an R project. All files are .csv, .pdf, .R, .Rmd, .Rproj, .html, .png, .txt, .qgz, .cpg, .dbf, .prj, .shp, .shp.ea.iso.xml, .shp.iso.xml, .shx, .sbn. ta package can be found at either link. We acknowledge the Yakama Nation as owners and caretakers of the lands where we collected these data. We thank the Confederated Tribes and Bands of the Yakama Nation Tribal Council and Yakama Nation Fisheries for working with us to facilitate sample collection and optimization of data usage according to their values and worldview.

54 ENVIRONMENTAL SCIENCES↗

Remote Sensing and GIS data at 1km-grid over Chesapeake Bay used in “He et al. 2024, Effects of spatial variability in vegetation phenology, climate, landcover, biodiversity, topography, and soil property on soil respiration across a coastal ecosystem”

The package contains the data layers used in “He et al. 2024, Effects of spatial variability in vegetation phenology, climate, landcover, biodiversity, topography, and soil property on soil respiration across a coastal ecosystem”. The study aims to use multi-source remote sensing and GIS datasets to investigate the spatial heterogeneity and identify spatial zones with similar environmental characteristics and understand the primary driving factors affecting soil respiration within sub-ecosystems of the coastal ecosystem. We employed unsupervised hierarchical clustering analysis to identify spatial regions with distinct environmental characteristics, then determined the main driving factors using Random Forest regression and SHapley Additive exPlanations (SHAP). Spatial data layers include soil respiration, kernel Normalized Difference Vegetation Index (kNDVI) computed from Harmonized Landsat 8 and Sentinel-2 time series, climate variables from the Daymet dataset, land cover, biodiversity, topographical metrics, soil property, and tidal elevation.

54 ENVIRONMENTAL SCIENCES↗

Gap-filled methane and carbon dioxide fluxes across two ecosystem states at the US-OWC AmeriFlux site (2015−2016, 2020−2022)

This dataset contains gap-filled measurements of methane flux (FCH4), net ecosystem CO2 exchange (NEE) partitioned into gross primary productivity (GPP) and ecosystem respiration (RE), as well as latent heat flux (LE) from a Great Lakes coastal freshwater wetland at the US-OWC AmeriFlux site. The dataset covers the peak growing seasons (June−September) of 2015−2016, dominated by Typha spp., and 2020−2022, characterized by floating-leaved species (lotus and water lily). These data were generated to investigate how rising water levels and vegetation shifts influence CH4 and CO2 fluxes across two distinct ecosystem states in this wetland. The dataset, provided in CSV format, includes half-hourly gap-filled flux data from June to September for 2015, 2016, 2020, 2021, and 2022. The gap-filled data refers to measurements where missing values due to instrument issues or quality control were filled using artificial neural networks (ANNs).

54 ENVIRONMENTAL SCIENCES↗

COMPASS-FME Terrestrial Ecosystem Manipulation to Probe the Effects of Storm Treatments (TEMPEST) Experiment Tree Inventory

This is the tree inventory (diameter, species, and live/dead status) data from the Terrestrial Ecosystem Manipulation to Probe the Effects of Storm Treatments (TEMPEST) experimental site. This manipulative, ecosystem-scale TEMPEST experiment is part of the COMPASS-FME (Coastal Observations, Mechanisms, and Predictions Across Systems and Scales: Field Measurements and Experiments; see https://compass.pnnl.gov/FME/COMPASSFME) project. It addresses the potential for freshwater and estuarine-water disturbance events to alter tree function, species composition, and ecosystem processes in a deciduous coastal forest in eastern Maryland, USA. The experiment uses a large-unit (2000 m2), un-replicated experimental design, with three 50 m × 40 m plots serving as control, freshwater, and estuarine-water treatments.This dataset includes:- An overall dataset README file.- The tree inventory data in both "wide" and "long" forms. These contain the same information but are structured differently, with the former more useful for human viewers and the latter more amenable for programmatic analyses.- A key to the species/genus codes used, which follow the U.S. Department of Agriculture's PLANTS schema (https://plants.usda.gov/).- A copy of the R code used to generate the wide- and long-form data files.All files are comma-separated value (CSV) and no special software is required to read them.

54 ENVIRONMENTAL SCIENCES↗