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At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Quantifying the drivers of ecosystem fluxes and water potential across the soil-plant-atmosphere continuum in an arid woodland

Dryland ecosystems occupy a vast swath of the terrestrial land surface and exert a sizeable impact on the cycling of carbon and water globally. These biomes are characterized by tightly coupled carbon and water cycles that respond rapidly to transient pulses in water availability. However, there exist many mechanistic uncertainties regarding the environmental drivers of, and linkages between, plant and ecosystem processes. Thus, drylands are often poorly represented in many vegetation and land surface models. An enhanced understanding of dryland ecosystem function is limited by the lack of long-term, co-located, and frequent measurements of plant and ecosystem processes. At a piñon-juniper woodland in southeastern Utah, USA, we collected a continuous dataset of meteorological conditions, soil water potential from surface to bedrock, tree water potential, and ecosystem carbon and water fluxes from eddy covariance. We found that predawn and midday tree water potential and daily ecosystem fluxes were highly sensitive to fluctuations in soil water availability, particularly in shallower layers, and that daytime variability in atmospheric drivers only loosely controlled these processes. The strong connections between shallow soil water potential, tree water potential, and ecosystem fluxes occurred because of the dominant role of precipitation pulses in driving vegetation activity, as even small pulses of moisture stimulated shallow soil water potential, tree water potential, and evapotranspiration for between 1 and 2 weeks. Carbon fluxes (net ecosystem exchange and gross primary productivity) were sensitive to precipitation pulses for longer, up to 3 weeks. Our results highlight that improved monitoring and sensing of shallow soil moisture can greatly enhance our understanding of dryland ecosystem function. Here, a better mechanistic understanding of the impacts of precipitation pulses is also needed to improve vegetation modeling of dryland ecosystems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

The three major axes of terrestrial ecosystem function

The leaf economics spectrum and the global spectrum of plant forms and functions revealed fundamental axes of variation in plant traits, which represent different ecological strategies that are shaped by the evolutionary development of plant species. Ecosystem functions depend on environmental conditions and the traits of species that comprise the ecological communities. However, the axes of variation of ecosystem functions are largely unknown, which limits our understanding of how ecosystems respond as a whole to anthropogenic drivers, climate and environmental variability. Here we derive a set of ecosystem functions from a dataset of surface gas exchange measurements across major terrestrial biomes. We find that most of the variability within ecosystem functions (71.8%) is captured by three key axes. The first axis reflects maximum ecosystem productivity and is mostly explained by vegetation structure. The second axis reflects ecosystem water-use strategies and is jointly explained by variation in vegetation height and climate. The third axis, which represents ecosystem carbon-use efficiency, features a gradient related to aridity, and is explained primarily by variation in vegetation structure. We show that two state-of-the-art land surface models reproduce the first and most important axis of ecosystem functions. However, the models tend to simulate more strongly correlated functions than those observed, which limits their ability to accurately predict the full range of responses to environmental changes in carbon, water and energy cycling in terrestrial ecosystems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Identifying priority ecosystem services in tidal wetland restoration

Classification systems can be an important tool for identifying and quantifying the importance of relationships, assessing spatial patterns in a standardized way, and forecasting alternative decision scenarios to characterize the potential benefits (e.g., ecosystem services) from ecosystem restoration that improve human health and well-being. We present a top-down approach that systematically leverages ecosystem services classification systems to identify potential services relevant for ecosystem restoration decisions. We demonstrate this approach using the U.S. Environmental Protection Agency’s National Ecosystem Service Classification System Plus (NESCS Plus) to identify those ecosystem services that are relevant to restoration of tidal wetlands. We selected tidal wetland management documents from federal agencies, state agencies, wetland conservation organizations, and land stewards across three regions of the continental United States (northern Gulf of Mexico, Mid-Atlantic, and Pacific Northwest) to examine regional and organizational differences in identified potential benefits of tidal wetland restoration activities and the potential user groups who may benefit. We used an automated document analysis to quantify the frequencies at which different wetland types were mentioned in the management documents along with their associated beneficiary groups and the ecological end products (EEPs) those beneficiaries care about, as defined by NESCS Plus. Results showed that a top combination across all three regions, all four organizations, and all four tidal wetland types was the EEP naturalness paired with the beneficiary people who care (existence). Overall, the Mid-Atlantic region and the land steward organizations mentioned ecosystem services more than the others, and EEPs were mentioned in combination with tidal wetlands as a high-level, more general category than the other more specific tidal wetland types. Certain regional and organizations differences were statistically significant. Those results may be useful in identifying ecosystem services-related goals for tidal wetland restoration. This approach for identifying and comparing ecosystem service priorities is broadly transferrable to other ecosystems or decision-making contexts.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Microbial carbon limitation: The need for integrating microorganisms into our understanding of ecosystem carbon cycling

Abstract Numerous studies have demonstrated that fertilization with nutrients such as nitrogen, phosphorus, and potassium increases plant productivity in both natural and managed ecosystems, demonstrating that primary productivity is nutrient limited in most terrestrial ecosystems. In contrast, it has been demonstrated that heterotrophic microbial communities in soil are primarily limited by organic carbon or energy. While this concept of contrasting limitations, that is, microbial carbon and plant nutrient limitation, is based on strong evidence that we review in this paper, it is often ignored in discussions of ecosystem response to global environment changes. The plant‐centric perspective has equated plant nutrient limitations with those of whole ecosystems, thereby ignoring the important role of the heterotrophs responsible for soil decomposition in driving ecosystem carbon storage. To truly integrate carbon and nutrient cycles in ecosystem science, we must account for the fact that while plant productivity may be nutrient limited, the secondary productivity by heterotrophic communities is inherently carbon limited. Ecosystem carbon cycling integrates the independent physiological responses of its individual components, as well as tightly coupled exchanges between autotrophs and heterotrophs. To the extent that the interacting autotrophic and heterotrophic processes are controlled by organisms that are limited by nutrient versus carbon accessibility, respectively, we propose that ecosystems by definition cannot be ‘limited’ by nutrients or carbon alone. Here, we outline how models aimed at predicting non‐steady state ecosystem responses over time can benefit from dissecting ecosystems into the organismal components and their inherent limitations to better represent plant–microbe interactions in coupled carbon and nutrient models.

Soong, Jennifer L.↗
DOE OSTI2022

Impact of Shifts in Vegetation Phenology on the Carbon Balance of a Semiarid Sagebrush Ecosystem

Dryland ecosystems are critical in regulating the interannual variability of the global terrestrial carbon cycle. The responses of such ecosystems to weather and environmental conditions remain important factors that limit the accurate projections of carbon balance under future climate change. Here, we investigated how shifts in vegetation phenology resulting from changes in weather and environmental conditions influenced ecosystem carbon cycling in one semiarid ecosystem in the Hanford area of central Washington, United States. We examined two years of measurements of the phenology camera, eddy covariance, and soil chamber from an upland semiarid sagebrush ecosystem. Both years had contrasting diel and seasonal patterns of CO 2 fluxes, primarily driven by differences in vegetation phenology. The net ecosystem exchange of CO 2 (NEE) and evapotranspiration (ET) in 2019 were enlarged by shifted vegetation phenology, as a cold and snow-covered winter and warm and dry winter in 2020 resulted in constrained magnitudes of NEE and ET during the summer months. The annual gross primary productivity (GPP) was much higher in 2019 than in 2020 (-211 vs. -112 gC m -2 ), whereas ecosystem respiration was comparable in these two years (164 vs. 144 gC m -2 ). Thus, the annual NEE in 2019 was negative (-47 gC m -2 ) with the sagebrush ecosystem functioning as a carbon sink, while the positive annual NEE in 2020 indicated that the sagebrush ecosystem functioned as a carbon source. Our results demonstrate that winter snowpack can be a critical driver of annual carbon uptake in semiarid sagebrush ecosystems.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Integration of ecosystem science into radioecology: A consensus perspective

In the Fall of 2016 a workshop was held which brought together over 50 scientists from the ecological and radiological fields to discuss feasibility and challenges of reintegrating ecosystem science into radioecology. There is a growing desire to incorporate attributes of ecosystem science into radiological risk assessment and radioecological research more generally, fueled by recent advances in quantification of emergent ecosystem attributes and the desire to accurately reflect impacts of radiological stressors upon ecosystem function. This work is a synthesis of the discussions and consensus of the workshop participant's responses to three primary questions, which were: 1) How can ecosystem science support radiological risk assessment? 2) What ecosystem level endpoints potentially could be used for radiological risk assessment? and 3) What inference strategies and associated methods would be most appropriate to assess the effects of radionuclides on ecosystem structure and function? The consensus of the participants was that ecosystem science can and should support radiological risk assessment through the incorporation of quantitative metrics that reflect ecosystem functions which are sensitive to radiological contaminants. The participants also agreed that many such endpoints exit or are thought to exit and while many are used in ecological risk assessment currently, additional data need to be collected that link the causal mechanisms of radiological exposure to these endpoints. Finally, the participants agreed that radiological risk assessments must be designed and informed by rigorous statistical frameworks capable of revealing the causal inference tying radiological exposure to the endpoints selected for measurement.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Warming and Increased Respiration Have Transformed an Alpine Steppe Ecosystem on the Tibetan Plateau From a Carbon Dioxide Sink Into a Source

Cold region ecosystems store vast amounts of soil organic carbon (C), which upon warming and decomposition can affect the C balance and potentially change these ecosystems from C sinks to carbon dioxide (CO 2 ) sources. We quantified the decadal year-round CO 2 flux from an alpine steppe-ecosystem on the Tibetan Plateau using eddy covariance and automatic chamber approaches during a period of significant warming (0.13°C per 10 years; and 0.18°C in the non-growing season alone: 1st October to next 30th April). The results showed that ongoing climate change, mainly warming within the topsoil layers, is the main reason for the site’s change from a sink for to a source of CO 2 in the atmosphere. Non-growing-season ecosystem respiration accounted for 51% of the annual ecosystem respiration and has increased significantly. The growing seasons (1st May to 30th September) were consistent CO 2 sink periods without significant changes over the study period. Observations revealed high-emission events from the end of the non-growing season to early in the growing season (1st March to fifteenth May), which significantly (p < 0.01) increased at a rate of 22.6 g C m -2 decade -1 , ranging from 14.6 ± 10.7 g C m -2 yr -1 in 2012 to 35.3 ± 12.1 g C m -2 yr -1 in 2017. Further, structural equation modeling suggested that active layer warming was the key factor in explaining changes in ecosystem respiration, leading to significant changes in net ecosystem exchange over the period 2011–2020 and indicated that these changes have already transformed the ecosystem from a CO 2 sink into a source. These results can be used to improve our understanding of the sensitivity of ecosystem respiration to increased warming during the non-growing period.

58 GEOSCIENCES↗
DOE OSTI2020

Mountain biodiversity and ecosystem functions: interplay between geology and contemporary environments

Although biodiversity and ecosystem functions are strongly shaped by contemporary environments, such as climate and local biotic and abiotic attributes, relatively little is known about how they depend on long-term geological processes. Here, along a 3000-m elevational gradient with tectonic faults on the Tibetan Plateau (that is, Galongla Mountain in Medog County, China), we study the joint effects of geological and contemporary environments on biological communities, such as the diversity and community composition of plants and soil bacteria, and ecosystem functions. We find that these biological communities and ecosystem functions generally show consistent elevational breakpoints at 2000–2800 m, which coincide with Indus-Yalu suture zone fault and are similar to the elevational breakpoints of soil bacteria on another mountain range 1000 km away. Mean annual temperature, soil pH and moisture are the primary contemporary determinants of biodiversity and ecosystem functions, which support previous findings. However, compared with the models excluding geological processes, inclusion of geological effects, such as parent rock and weathering, increases 67.9 and 35.9% of the explained variations in plant and bacterial communities, respectively. Such inclusion increases 27.6% of the explained variations in ecosystem functions. The geological processes thus provide additional links to ecosystem properties, which are prominent but show divergent effects on biodiversity and ecosystem functions: parent rock and weathering exert considerable direct effects on biodiversity, whereas indirectly influence ecosystem functions via interactions with biodiversity and contemporary environments. Thus, the integration of geological processes with environmental gradients could enhance our understanding of biodiversity and, ultimately, ecosystem functioning across different climatic zones.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

The ecosystem wilting point defines drought response and recovery of a Quercus‐Carya forest

Abstract Soil and atmospheric droughts increasingly threaten plant survival and productivity around the world. Yet, conceptual gaps constrain our ability to predict ecosystem‐scale drought impacts under climate change. Here, we introduce the ecosystem wilting point (Ψ EWP ), a property that integrates the drought response of an ecosystem's plant community across the soil–plant–atmosphere continuum. Specifically, Ψ EWP defines a threshold below which the capacity of the root system to extract soil water and the ability of the leaves to maintain stomatal function are strongly diminished. We combined ecosystem flux and leaf water potential measurements to derive the Ψ EWP of a Quercus‐Carya forest from an “ecosystem pressure–volume (PV) curve,” which is analogous to the tissue‐level technique. When community predawn leaf water potential (Ψ pd ) was above Ψ EWP (=−2.0 MPa), the forest was highly responsive to environmental dynamics. When Ψ pd fell below Ψ EWP , the forest became insensitive to environmental variation and was a net source of carbon dioxide for nearly 2 months. Thus, Ψ EWP is a threshold defining marked shifts in ecosystem functional state. Though there was rainfall‐induced recovery of ecosystem gas exchange following soaking rains, a legacy of structural and physiological damage inhibited canopy photosynthetic capacity. Although over 16 growing seasons, only 10% of Ψ pd observations fell below Ψ EWP , the forest is commonly only 2–4 weeks of intense drought away from reaching Ψ EWP , and thus highly reliant on frequent rainfall to replenish the soil water supply. We propose, based on a bottom‐up analysis of root density profiles and soil moisture characteristic curves, that soil water acquisition capacity is the major determinant of Ψ EWP , and species in an ecosystem require compatible leaf‐level traits such as turgor loss point so that leaf wilting is coordinated with the inability to extract further water from the soil.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

A framework for soil microbial ecology in urban ecosystems

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

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Design methodologies and engineering applications for ecosystem biomimicry: an interdisciplinary review spanning cyber, physical, and cyber-physical systems

Abstract Ecosystem biomimicry is a promising pathway for sustainable development. However, while typical form- and process-level biomimicry is prevalent, system-level ecosystem biomimicry remains a nascent practice in numerous engineering fields. This critical review takes an interdisciplinary approach to synthesize trends across case studies, evaluate design methodologies, and identify future opportunities when applying ecosystem biomimicry to engineering practices, including cyber systems (CS), physical systems (PS), and cyber-physical systems (CPS). After systematically sourcing publications from major databases, the papers were first analyzed at a meta level for their bibliographic context and for statistical correlations among categorical variables. Then, we investigated deeper into the engineering applications and design methodologies. Results indicate that CPS most frequently mimic organisms and ecosystems, while CS and PS frequently mimic populations-communities and molecules-tissues-organ systems, respectively (statistically highly significant). An indirect approach is most often used for mimicry at organizational levels from populations to ecosystems, while a direct approach frequently suits levels from molecules to organisms (highly significant). Dominant themes across engineering applications include symbiotic organism search algorithms for CS and ecological network analysis for CPS, while PS are highly diverse. For design methodologies, this work summarizes and details ten well-documented biomimetic process models among literature, which addresses an outdated concern for a lack of systematic methods for ecosystem biomimicry. In addition to the Biomimetics Standard ISO 18458, these methods include the Natural Step and Techno-Ecological Synergy framework, among others. Further, the analyses revealed future opportunities from less utilized design methods (e.g. interdisciplinary teams tackling indirect, ecosystem-level projects) to well-established engineering concepts ready for technological advancement (e.g. implementing membrane computing for physical applications). For future studies, this review provides a comprehensive reference for ecosystem biomimetic design practices and application opportunities across multiple engineering domains.

42 ENGINEERING↗
DOE OSTI2022

Hourly water-carbon interactions modulate decadal water-use efficiency trends inferred from ecosystem-scale measurements

Plant stomatal conductance regulates photosynthesis and transpiration. This physiological link affects ecosystem responses to microclimate and harmonizes carbon, energy, and water exchanges between the biosphere and atmosphere. The relationship between water losses via transpiration and carbon gains via photosynthesis can be quantified by plant water-use efficiency (WUE). While leaf- and ecosystem-scale observations both suggest rising WUE in recent decades, WUE trends inferred from the ecosystem scale are much larger than those inferred from the leaf scale or implied by theory. The unexpectedly large ecosystem-scale WUE trends complicate interpretation of ecophysiological responses to changing environmental conditions. Here, we analyze ecosystem-scale WUE inferred from 40 FLUXNET sites, each with at least 10 years of measurements. Furthermore, our results demonstrate that observed ecosystem-scale WUE trends are more sensitive to hourly weather conditions than longer-term changes in atmospheric carbon dioxide or vapor pressure deficit. Our analysis shows that Earth System Models participating in CMIP6 did not capture the observed WUE sensitivity to inter-site variability and microclimatic conditions. Collectively, our findings suggest that ecosystem-scale WUE trends reflect water-carbon interactions across multiple temporal scales, and disentangling factors contributing to emergent ecosystem responses is needed to infer ecophysiological relationships and model structures from observations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Spatiotemporal dynamics of ecosystem fires and biomass burning-induced carbon emissions in China over the past two decades

Fire is a major type of disturbance that has important influences on ecosystem dynamics and carbon cycles. Yet our understanding of ecosystem fires and their carbon cycle consequences is still limited, largely due to the difficulty of large-scale fire monitoring and the complex interactions between fire, vegetation, climate, and anthropogenic factors. Here, using data from satellite-derived fire observations and ecosystem model simulations, we performed a comprehensive investigation of the spatial and temporal dynamics of China's ecosystem fire disturbances and their carbon emissions over the past two decades (1997–2016). Satellite-derived results showed that on average about 3.47 - 4.53 x 10 4 km 2 of the land was burned annually during the past two decades, among which annual burned forest area was about 0.81 - 1.25 × 10 4 km 2 , accounting for 0.33-0.51% of the forest area in China. Biomass burning emitted about 23.02 TgC per year. Compared to satellite products, simulations from the Energy Exascale Earth System Land Model (ELM) strongly overestimated China's burned area and fire-induced carbon emissions. Annual burned area and fire-induced carbon emissions were high for boreal forest in Northeast China's Daxing'anling region and subtropical dry forest in South Yunnan, as revealed by both the satellite product and the model simulations. Our results suggest that climate and anthropogenic factors play critical roles in controlling the spatial and seasonal distribution of China's ecosystem fire disturbances. Our findings highlight the importance of multiple complementary approaches in assessing ecosystem fire disturbance and its carbon consequences. Further studies are required to improve the methods of observing and modelling China's ecosystem fire disturbances, which will provide valuable information for fire management and ecosystem sustainability in an era when both human activities and the natural environment are rapidly changing.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Improving collaborations between empiricists and modelers to advance grassland community dynamics in ecosystem models

Climate change, increasing atmospheric CO 2 , and land use change have altered biogeochemical and hydrologic cycles world-wide, with grassland systems being particularly vulnerable to resulting vegetation shifts (Komatsu et al., 2019). Therefore, incorporating plant community dynamics into ecosystem models is critical for accurate forecasting of ecosystem responses to global change (Levine, 2016). Process-based ecosystem models, which simulate the biogeochemical transfers of mass and energy among biota, the subsurface, and atmosphere, require representation of dynamic composition of organisms within ecosystems. For example, these models simulate leaf and plant-level characteristics, such as electron transport rate and allometry of carbon (C) allocation, to predict how net primary productivity and other ecosystem processes respond to abiotic drivers. These models are particularly useful in scaling from organismal to ecosystem levels but are still underdeveloped in their ability to capture community change, especially in grassland ecosystems. To represent compositional changes, these models must simulate competition, mortality, establishment, and reproduction of plant populations within communities. Yet, current ecosystem modeling approaches to forecast plant community change have derived from studies of forested systems and are either too coarse to capture fine-scale community dynamics (e.g. dynamic global vegetation models (DGVMs)) or too complex to be used at large spatial scales (e.g. forest gap models).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

A bacterial sensor taxonomy across earth ecosystems for machine learning applications

Microbial communities have evolved to colonize all ecosystems of the planet, from the deep sea to the human gut. Microbes survive by sensing, responding, and adapting to immediate environmental cues. This process is driven by signal transduction proteins such as histidine kinases, which use their sensing domains to bind or otherwise detect environmental cues and “transduce” signals to adjust internal processes. We hypothesized that an ecosystem’s unique stimuli leave a sensor “fingerprint,” able to identify and shed insight on ecosystem conditions. To test this, we collected 20,712 publicly available metagenomes from Host-associated, Environmental, and Engineered ecosystems across the globe. We extracted and clustered the collection’s nearly 18M unique sensory domains into 113,712 similar groupings with MMseqs2. We built gradient-boosted decision tree machine learning models and found we could classify the ecosystem type (accuracy: 87%) and predict the levels of different physical parameters (R2 score: 83%) using the sensor cluster abundance as features. Feature importance enables identification of the most predictive sensors to differentiate between ecosystems which can lead to mechanistic interpretations if the sensor domains are well annotated. To demonstrate this, a machine learning model was trained to predict patient’s disease state and used to identify domains related to oxygen sensing present in a healthy gut but missing in patients with abnormal conditions. Moreover, since 98.7% of identified sensor domains are uncharacterized, importance ranking can be used to prioritize sensors to determine what ecosystem function they may be sensing. Furthermore, these new predictive sensors can function as targets for novel sensor engineering with applications in biotechnology, ecosystem maintenance, and medicine.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Ectomycorrhizal Plant-Fungal Co-invasions as Natural Experiments for Connecting Plant and Fungal Traits to Their Ecosystem Consequences

Introductions and invasions by fungi, especially pathogens and mycorrhizal fungi, are widespread and potentially highly consequential for native ecosystems, but may also offer opportunities for linking microbial traits to their ecosystem functions. In particular, treating ectomycorrhizal (EM) invasions, i.e., co-invasions by EM fungi and their EM host plants, as natural experiments may offer a powerful approach for testing how microbial traits influence ecosystem functions. Forests dominated by EM symbiosis have unique biogeochemistry whereby the secretions of EM plants and fungi affect carbon (C) and nutrient cycling; moreover, particular lineages of EM fungi have unique functional traits. EM invasions may therefore alter the biogeochemistry of the native ecosystems they invade, especially nitrogen (N) and C cycling. By identifying “response traits” that favor the success of fungi in introductions and invasions (e.g., spore dispersal and germination) and their correlations with “effect traits” (e.g., nutrient-cycling enzymes) that can alter N and C cycling (and affect other coupled elemental cycles), one may be able to predict the functional consequences for ecosystems of fungal invasions using biogeochemistry models that incorporate fungal traits. Here, we review what is already known about how EM fungal community composition, traits, and ecosystem functions differ between native and exotic populations, focusing on the example of EM fungi associated with species of Pinus introduced from the Northern into the Southern Hemisphere. We develop hypotheses on how effects of introduced and invasive EM fungi may depend on interactions between soil N availability in the exotic range and EM fungal traits. We discuss how such hypotheses could be tested by utilizing Pinus introductions and invasions as a model system, especially when combined with controlled laboratory experiments. Finally, we illustrate how ecosystem modeling can be used to link fungal traits to their consequences for ecosystem N and C cycling in the context of biological invasions, and we highlight exciting avenues for future directions in understanding EM invasion.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Vulnerability and resilience of urban energy ecosystems to extreme climate events: A systematic review and perspectives

We reviewed the present studies on the vulnerability and resilience of the energy ecosystem (most parts of the energy ecosystem), considering extreme climate events. This study revealed that the increased interactions formed during the transformation of the energy landscape into an ecosystem could notably increase the vulnerability of the energy infrastructure. Such complex ecosystem cannot be assessed using the present state of the art models used by the energy system modelers. Therefore, this study introduces a novel analogy known as the COVID analogy to understand the propagation of disruption within and beyond the energy ecosystem and organized the present state of the art based on the COVID analogy. The analogy helps to categorize the vulnerability of the energy infrastructure into three stages. The study revealed that although there are many publications covering the vulnerability and resilience of the energy infrastructure, considering extreme climate events, the majority are focused on the direct impact of extreme climate on the energy ecosystem. In addition, most of the studies do not consider the impact of future climate variations during this assessment. The propagation of disruptions was assessed mainly for wildfires and hurricanes. Further, there is a clear research gap in considering vulnerability assessment for interconnected energy infrastructure. Here, the transformation of energy systems into a complex ecosystem notably increases the complexity, making it difficult to assess vulnerability and resilience. A shift from a centralized to decentralized modeling architecture could be beneficial when considering the complexities brought by that transformation. Hybrid models consisting of both physical and data-driven machine learning techniques could also be beneficial in this context.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Root Foraging Alters Global Patterns of Ecosystem Legacy From Climate Perturbations

The response of terrestrial ecosystems to climate perturbations typically persist longer than the timescale of the forcing, a phenomenon broadly referred to as legacy. Understanding the strength of legacy is critical for predicting ecosystem sensitivity to climate extremes and the extent that persistent changes in surface-atmosphere exchange might feedback onto climate. The cause of ecosystem legacy has been associated with myriad factors such as changes in aboveground biomass, however, few studies have tested how changes in the depth distribution of fine roots in response to perturbation might alter an ecosystem's recovery time. We explore this question using an Earth System Model that includes a dynamic root module where vegetation can forage for water and nutrients by altering their root profiles. The global simulations presented here show that in response to water stress events most ecosystems deepen their root profiles. In semi-arid ecosystems, this response expedites recovery (i.e., less legacy) relative to simulations without dynamics roots because access to deeper water pools after the initial event remains favorable. In wetter ecosystems, the development of deeper root profiles slows down the recovery timescale (i.e., more legacy) because the deeper root profile reduces access to nutrients and is thus unfavorable. Here, the simulations show that while the inclusion of dynamic roots might only minimally affect global patterns of Gross Primary Productivity and Evapotranspiration, the shift in root profile alters the timescale of recovery. Studies interested in the sustained response of land surfaces fluxes to climate disturbances should consider models that include dynamic root capability.

54 ENVIRONMENTAL SCIENCES↗