Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “ECOSYSTEM”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,747 records · Page 97

Final Technical Report to DOE for the Award DE-SC0004601

Understanding the responses, adaptations and feedback mechanisms of biological communities to climate change is critical to project future state of earth and climate systems. Although significant amount of knowledge is available on the feedback responses of aboveground communities to climate change, little is known about the responses of belowground microbial communities due to the challenges in analyzing soil microbial community structure. Thus the goal overall goal of this study is to provide system-level, predictive mechanistic understanding of the temperature sensitivity of soil carbon (C) decomposition to climate warming by using cutting-edge integrated metagenomic technologies. Towards this goal, the following four objectives will be pursued: (i) To determine phylogenetic composition and metabolic diversity of microbial communities in the temperate grassland and tundra ecosystems; (ii) To delineate the responses of microbial community structure, functions and activities to climate change in the temperate grassland and tundra ecosystems; (iii) To determine the temperature sensitivity of microbial respiration in soils with different mixtures of labile versus recalcitrant C, and the underlying microbiological basis for temperature sensitivity of these pools; and (iv) To synthesize all experimental data for revealing microbial control of ecosystem carbon processes in responses to climate change. We have achieved our goals for all four proposed objectives. First, we determined the phylogenetic composition and metabolic diversity of microbial communities in the temperate grassland and tundra ecosystems. For this objective, we have developed a novel phasing amplicon sequencing (PAS) approach for MiSeq sequencing of amplicons. This approach has been used for sequencing various phylogenetic and functional genes related to ecosystem functioning. A comprehensive functional gene array (e.g., GeoChip 5.0) has also been developed and used for soil microbial community analysis in this study. In addition, shot-gun metagenome sequencing along with the above approaches have been used to understand the phylogenetic and functional diversity, composition, and structure of soil microbial communities in both temperature grassland and tundra ecosystems. Second, we determined the response of soil microbial communities to climate warming in both temperate grassland and tundra ecosystems using various methods. Our major findings are: (i) Microorganisms are very rapid to respond to climate warming in the tundra ecosystem, AK, which is vulnerable, too. (ii) Climate warming also significantly shifted the metabolic diversity, composition and structure of microbial communities, and key metabolic pathways related to carbon turnover, such as cellulose degradation (~13%) and CO2 production (~10%), and to nitrogen cycling, including denitrification (~12%) were enriched by warming. (iii) Warming also altered the expression patterns of microbial functional genes important to ecosystem functioning and stability through GeoChip and metatranscriptomic analysis of soil microbial communities at the OK site. Third, we analyzed temperature sensitivity of C decomposition to climate warming for both AK and OK soils through laboratory incubations. Key results include: (i) Alaska tundra soils showed that after one year of incubation, CT in the top 15 cm could be as high as 25% and 15% of the initial soil C content at 25°C and 15°C incubations, respectively. (ii) analysis of 456 incubated soil samples with 16S rRNA gene, ITS and GeoChip hybridization showed that warming shifted the phylogenretic and functional diversity, composition, structure and metabolic potential of soil microbial communities, and at different stages of incubation, key populations and functional genes significantly changed along with soil substrate changes. Functional gene diversity and functional genes for degrading labile C components decrease along incubation when labile C components are exhausting, but the genes related to degrading recalcitrant C increase. These molecular data will be directly used for modeling. Fourth, we have developed novel approaches to integrate and model experimental data to understand microbial control of ecosystem C processes in response to climate change. We compared different methods to calculate Q10 for estimating temperature sensitivity, and new approaches for Q10 calculation and molecular ecological network analysis were also developed. Using those newly developed approaches, our result indicated that Q10s increased with the recalcitrance of C pools, suggesting that longer incubation studies are needed in order to assess the temperature sensitivity of slower C pools, especially at low temperature regimes. This project has been very productive, resulting in 42 papers published or in press, 4 submitted, and 13 in preparation.

54 ENVIRONMENTAL SCIENCES↗

University of Utah, Energy Commercialization Center

During the Energy Commercialization Center’s (ECC) three years in operation, the only thing constant was change. The world of commercialization and cleantech evolved significantly during the time the ECC was formed and operating, including: the availability of cleantech funding lessoned, the growth of incubators and accelerators skyrocketed, the State of Utah created an office dedicated to energy development, the University of Utah was both praised and criticized for its success in commercialization, and the Federal government temporarily shut down. During the three-year grant there were three principle investigators on the grant, as well as three directors for the University’s Commercialization Office. Change can be hard for an organization,but as we instruct the companies we support, “Fail fast and fail often, because it is the fastest path to success.” Although there were some unanticipated challenges along the way, the local ecosystem is stronger because of the ECC’s efforts. Perhaps the greatest lesson learned was the importance of aligned incentives between key stakeholders in the commercialization process and the need for resources at the company and individual entrepreneur levels. The universities have systems and incentives to commercialize technologies, but creating value and companies generally rest with the individuals and entrepreneurs. Unfortunately the ECC was unable to create a viable mechanism to transfer the commercialization process that successfully aligned incentives and achieve a more effective ecosystem within the Rocky Mountain West. However, the ECC was successful in adding value to the individual ecosystems, and connecting national resources to regional and local needs. Regarding the ECC’s effectiveness in developing a cleantech commercialization ecosystem, initial inroads and relationships were established with key stakeholders. However, incentives, perceived or real competition, differences in commercialization processes, and culture all played a role in inhibiting the development and distribution of a regional ecosystem and commercialization process. Had the University and the ECC been able to develop a software platform, some of these challenges may have been overcome, but without the final development and release of the Western Innovation Network, the ECC realistically could not scale and distribute a commercialization platform. Further, cleantech startups need to engage in a more intensive customer validation process, and establish strong community connections if they are to succeed in commercializing their products. The university system incentivizes research and access to research funding and risk capital is competitive, so by nature collaboration on commercialization was difficult. Each of the local ecosystems within the Rocky Mountain West was unique. Utah did not, and does not, have a system outside of the universities to support entrepreneurs and cleantech commercialization. Through the ECC’s efforts developing a regional ecosystem, it became clear that successful ecosystems had a community and associated mechanisms that supported local entrepreneurs and startups. Most importantly the ECC aided in the creation of Utah’s cleantech ecosystem, one that supports entrepreneurs and startup companies that need help and support in their efforts to commercialize clean technologies. The absence of support for clean tech from state government and local organizations was a significant impediment to cleantech commercialization. To overcome this challenge, the ECC has formed Sustainable Startups. Sustainable Startups is a new non-profit organization designed to build a culture and community in Utah that supports and understands the importance of cleantech and sustainable development. While the ECC generated mixed success in building a regional commercialization ecosystem for cleantech, the organization did provide tremendous benefit to startups and the broader public. Over 60 companies were given direct business development support by the ECC, many of whom then generated direct economic development impacts. In addition, the ECC served an important role as community convener, educator and relationship builder through hosting numerous public and private events including: Energize 2013; Millennial Train whistle stop; business plan competition supporter; Clean Tech Open Accelerator organizer; Sustainable Startups Series developer, and much more. While the ECC did not fully apply, develop, and transmit the University of Utah’s TCO commercialization model to cleantech, it nevertheless assisted numerous inventors, entrepreneurs and institutions in furthering the growth of clean energy and energy efficiency technologies. The TCO’s commercialization model was not applied to regional clean tech initiatives for several main reasons. First, flaws with the commercialization model were realized after the ECC’s formation. Second, leadership changes within the TCO and ECC hampered early organizational development and implementation initiatives. Third, misaligned incentives between the ECC, regional universities, institutions, and the State of Utah resulted in a lack of collaboration and knowledge transfer regarding commercialization. In principle, everyone was aligned and willing to collaborate, but reality was much different and challenging.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Responses of tundra plant community carbon flux to experimental warming, dominant species removal and elevation

1. Rising temperatures can influence ecosystem processes both directly and indirectly, through effects on plant species and communities. An improved understanding of direct versus indirect effects of warming on ecosystem processes is needed for robust predictions of the impacts of climate change on terrestrial ecosystem carbon (C) dynamics. 2. To explore potential direct and indirect effects of warming on C dynamics in arctic tundra heath, we established a warming (open top chambers) and dominant plant species (Empetrum hermaphroditum Hagerup) removal experiment at a high and low elevation site. We measured the individual and interactive effects of warming, dominant species removal and elevation on plant species cover, the normalized difference vegetation index (NDVI), leaf area index (LAI), temperature, soil moisture and instantaneous net ecosystem CO 2 exchange. 3. We hypothesized that ecosystems would be stronger CO 2 sinks at the low elevation site, and that warming and species removal would weaken the CO 2 sink because warming should increase ecosystem respiration (ER) and species removal should reduce gross primary productivity (GPP). Furthermore, we hypothesized that warming and species removal would have the greatest impact on processes at the high elevation where site temperature should be most limiting and dominant species may buffer the overall community to environmental stress more compared to the low elevation site where plants are more likely to compete with the dominant species. 4. The instantaneous CO 2 flux, which reflected a weak CO 2 sink, was similar at both elevations. Neither experimental warming nor dominant species removal significantly changed GPP or instantaneous net ecosystem CO 2 exchange even though species removal significantly reduced ER, NDVI and LAI. 5. Our results show that even the loss of dominant plant species may not result in significant landscape-scale responses of net ecosystem CO 2 exchange to warming. They also show that NDVI and LAI may be limited in their ability to predict changes in GPP in these tundra heaths systems. Our study highlights the need for more detailed vegetation analyses and ground-truthed measurements in order to accurately predict direct and indirect impacts of climatic change on ecosystem C dynamics.

54 ENVIRONMENTAL SCIENCES↗

Data Synthesis and Data Assimilation at Global Change Experiments and Fluxnet Toward Improving Land Process Models

The project was conducted during the period from 7/1/2012 to 6/30/2017 with three major tasks: (1) data synthesis and development of data assimilation (DA) techniques to constrain modeled ecosystem feedback to climate change; (2) applications of DA techniques to improve process models at different scales from ecosystem to regions and the globe; and 3) improvements of modeling soil carbon (C) dynamics by land surface models. During this period, we have synthesized published data from soil incubation experiments (e.g., Chen et al., 2016; Xu et al., 2016; Feng et al., 2016), global change experiments (e.g., Li et al., 2013; Shi et al., 2015, 2016; Liang et al., 2016) and fluxnet (e.g., Niu et al., 2012., Xia et al., 2015; Li et al., 2016). These data have been organized into multiple data products and have been used to identify general mechanisms and estimate parameters for model improvement. We used the data sets that we collected and the DA techniques to improve model performance of both ecosystem models and global land models. The objectives are: 1) to improve model simulations of litter and soil carbon storage (e.g., Schädel et al., 2013; Hararuk and Luo, 2014; Hararuk et al., 2014; Liang et al., 2015); 2) to explore the effects of CO 2 , warming and precipitation on ecosystem processes (e.g., van Groenigen et al., 2014; Shi et al., 2015, 2016; Feng et al., 2017); and 3) to estimate parameters variability in different ecosystems (e.g., Li et al., 2016). We developed a traceability framework, which was based on matrix approaches and decomposed the modeled steady-state terrestrial ecosystem carbon storage capacity into four can trace the difference in ecosystem carbon storage capacity among different biomes to four traceable components: net primary productivity (NPP), baseline C residence times, environmental scalars and climate forcing (Xia et al., 2013). With this framework, we can diagnose the differences in modeled carbon storage across ecosystems, biomes, and models. This framework has been successfully implemented by several global land models, such as CABLE (Xia et al., 2013), LPJ-GUESS (Ahlström et al., 2015), CLM (Hararuk et al., 2014; Huang et al., 2017, submitted; Shi et al., 2017, submitted), and ORCHIDEE (Huang et al., 2017, unpublished). Moreover, we have identified the theoretical foundation of the determinants of transient C storage dynamics by adding another term, C storage potential, to the steady-state traceability framework (Luo et al., 2017). The theoretical foundation of transient C storage dynamics has been applied to develop a transient traceability framework to explore the traceable components of transient C storage dynamics responded to the rising CO 2 and climate change in the two contrasting ecosystem types Duke needleleaved forest and Harvard deciduous broadleaved forest (Jiang et al., 2017, in revision). Overall, with the data synthesis, data assimilation techniques, and the steady-state and transient traceability frameworks, we have greatly improved land process models for predicting responses and feedback of terrestrial C dynamics to global change. The matrix approaches has the potential to be applied in theoretical research on nitrogen and phosphorus cycle, and therefore, the coupling of carbon-nitrogen-phosphorus.

58 GEOSCIENCES↗

Resilience: Concepts and Measures

Inertia, the resistance of an ecosystem property to change under stress, is distinguished from resilience, which refers to the degree, manner. and pace of change or recovery in ecosystem properties following disturbance. In turn, these two terms are differentiated from 'stability'. which is used here to refer to the pattern of natural fluctuation in ecosystem properties in the absence of major exogenous disturbance. Four component attributes of resilience are reviewed in the context of Mediterranean-climate examples. The elasticity component concerns the rate of recovery of an ecosystem property following disturbance; amplitude, the threshold of stress beyond which recovery to the initial state does not occur; hysteresis, the degree to which the pattern of recovery after stress differs from that of deterioration under chronic stress, and malleability the ease with which the ecosystem can become permanently altered. Each ecosystem property will typically reveal a different level of resilience to a given stress and stressor. The degree of recovery should not be expected to be complete in any event, due to sample variability and stochastic events. In cyclicallystable ecosystems, the pattern of recovery should be measured in light of this periodicity, and short-term (within-cycle) recovery distinguished from long-term (between-cycle) recovery. The prediction of resilience properties of ecosystems can be approached through a knowledge of the modular structure of foodwebs, through knowledge of the autecological adaptations of key species to the stressor, or through cumulative experience of the response to disturbance at the community level. At present there is much room for investigation of each of these approaches in Mediterranean-climate ecosystems.

Westman, Walter E.↗

Predicting Chronic Climate-Driven Disturbances and Their Mitigation

Society increasingly demands the stable provision of ecosystem resources to support our population. Resource risks from climate-driven disturbances--including drought, heat, insect outbreaks, and wildfire--are rising as a chronic state of disequilibrium results from increasing temperatures and a greater frequency of extreme events. This confluence of increased demand and risk may soon reach critical thresholds. We explain here why extreme chronic disequilibrium of ecosystem function is likely to increase dramatically across the globe, creating no-analog conditions that challenge adaptation. We also present novel mechanistic theory that combines models for disturbance mortality and metabolic scaling to link size-dependent plant mortality to changes in ecosystem stocks and fluxes. Efforts must anticipate and model chronic ecosystem disequilibrium to properly prepare for resilience planning.

disequilibrium↗

Arctic Shrub Expansion, Plant Functional Trait Variation, and Effects on Belowground Carbon Cycling (Final Technical Report)

Terrestrial ecosystems are undergoing dramatic changes in response to climate warming, and these changes are expected to feedback to the atmosphere, potentially altering the trajectory of future climate change. Feedbacks from Arctic ecosystems are a major concern because the Arctic is projected to warm significantly in the 21 st century and because >50% of global belowground organic carbon is stored in permafrost and overlying soils. Warming-driven release of this carbon could drastically increase atmospheric greenhouse gas concentrations and accelerate climate warming. Plant communities are also responding to warming, as evidenced by the widely documented increase in woody-shrub growth and “greening” across much of the Arctic tundra biome. This vegetation shift may offset or amplify warming by altering carbon cycling. The direction and magnitude of shrub effects remain highly uncertain, however, due to limited understanding of the consequences of shrub expansion for belowground carbon cycling and simplification of these relationships in models. The major shrubs expanding in the Arctic (Betula, Salix, and Alnus) vary widely with respect to aboveground and belowground traits (e.g., tissue production and chemistry, rooting depth, microbial symbionts), and may also exhibit substantial intraspecific variation in these traits in response to environmental conditions. Such variation is likely to have profound implications for soil carbon cycling. The overarching goal of this project was to improve process-based understanding of the influence of shrub expansion on carbon cycling to enable improved representation of carbon dynamics in ecosystem and Earth system models. We investigated how plant functional traits vary among shrub genera, respond to environmental conditions, and affect belowground carbon and nutrient cycling by quantifying relationships among functional traits and biogeochemical cycling along edaphic gradients nested within a climate gradient in the Alaskan tundra. We found consistent differences in leaf and root traits among shrub genera and between shrubs and a widespread sedge species, indicating diverse nutrient acquisition strategies and belowground impacts among different arctic shrubs. We also found striking differences in trait values among individuals within the same species or genera within sites. Soil parameters were more important than climate parameters for predicting size and leaf trait variation, and root trait responses were less dependent on climate overall. For all but one root trait, including parameters representing aboveground traits improved the predictive ability of models. These results demonstrate that tundra shrub traits vary considerably at local scales and soil factors drive this variation, especially belowground. Furthermore, leveraging information about aboveground traits and soil conditions can improve predictions of how belowground traits will respond to climate change. Despite these differences, soil carbon and nitrogen pools in the active layer did not vary among plots dominated by different shrub or sedge genera. Instead, pool sizes generally decreased from warmer to colder sites, consistent with a productivity gradient. Patterns of isotopic N composition indicate that shrubs tighten nitrogen cycling via nitrogen resorption or immobilization of shrub litter. Overall, these results suggest that further identifying the specific shrub genera in the tundra landscape will ultimately provide better predictions of belowground dynamics across the changing arctic. We also performed simulation experiments with the Terrestrial Ecosystem Model (TEM) incorporated in the Predictive Ecosystem Analyzer (PEcAn) framework, treats model parameters as probability distributions, estimates parameters based on a synthesis of available field data, and then quantifies both model sensitivity and uncertainty to a given parameter or suite of parameters. We performed simulations across different types of tundra, including shrub tundra. One key finding was that both model sensitivity and uncertainty to a given parameter could vary within the same type of tundra, but in a different geographical location, such as over the climate gradient of shrub tundra described above. We organized a special session at the annual meeting of the Ecological Society of America in August 2019 to disseminate our results, refine recommendations for model improvement, and initiate collaborations to implement these recommendations in existing models of tundra carbon dynamics at ecosystem to Earth system scales. Our results support DOE near-term priorities by providing mechanistic insights into the role of vegetation change in the terrestrial carbon cycle in a region that is inadequately represented in Earth system models. Current models reduce the complexity of Arctic vegetation to a small number of plant functional types (PFTs). This approach implicitly assumes that each PFT represents the average ecological function of its constituent species, thus ignoring the effects of trait variation on biogeochemical cycling and potentially leading to large uncertainty in the sign and magnitude of ecosystem feedbacks to climate. By quantifying variation of plant functional traits across broad gradients of climatic and edaphic conditions and elucidating the linkages of such variation with carbon and nutrient cycling, our results illustrate the need and create a foundation for further developing trait-based modeling approaches that allow the traits of PFTs to vary as a function of environmental conditions. These approaches should improve the capacity of simulation models to offer insights into ecosystem carbon dynamics associated with novel plant communities in a rapidly changing Arctic.

54 ENVIRONMENTAL SCIENCES↗

Discerning the thermodynamic feasibility of the spontaneous coexistence of multiple functional vegetation groups

Can the Second Law of Thermodynamics explain why ecosystems naturally organize into a complex structure composed of multiple vegetation species and functional groups? Ecosystem structure, which refers to the number and type of plant functional groups, is the result of self-organization, or the spontaneous emergence of order from random fluctuations. By considering ecosystems as open thermodynamic systems, we model and study these fluctuations of throughput signatures on short timescales to determine the drivers and characteristics of ecosystem structure. This diagnostic approach allows us to use fluxes of energy and entropy to calculate an ecosystem’s estimated work and understand the thermodynamic behavior of the system. We use a multi-layer canopy-root-soil model to calculate the energy and entropy fluxes of different scenarios for field sites across various climates. At each site, scenarios comprised of native individual plant functional groups and a coexisting multi-group composition scenario including all functional groups observed at the site are compared. Ecosystem-scale calculations demonstrate that entropy fluxes and work efficiency—the work performed for the amount of radiation entering the ecosystem—are greatest in the multi-group scenario when its leaf area is significantly larger than each of its individual functional groups. Thus, we conclude that ecosystems self-organize towards the vegetation structure with the greatest outgoing entropy flux and work efficiency, resulting in the coexistence of multiple functional groups and performing the maximum amount of work within the constraints of locally available energy, water, and nutrients.

54 ENVIRONMENTAL SCIENCES↗

Using Science Skills to Understand Ecophysiology and Manage Resources

Presentation will be for a general audience and focus on plant science and ecosystem science in NASA. Examples from the projects involving the presenter will be used to illustrate. Specifically, the California Sacramento-San Joaquin River Delta project. This collaboration supports the goals of the Delta Plan in developing science-based, adaptive-management strategies. The mission is to improve reliability of water supply and restore a healthy Delta ecosystem while enhancing agriculture and recreation. NASA can contribute gap-filling science understanding of overall functions in the Delta ecosystem and assess and help develop management plans for specific issues. Airborne and satellite remote-sensing, ecosystem modeling, and biological studies provide underlying data needed by Delta stakeholders to assess and address water, ecosystem restoration, and environmental and economic impacts of potential actions in the Delta. The California Sacramento-San Joaquin River Delta, the hub for California's water supply, supports important ecosystem services for fisheries, supplies drinking water for millions, and distributes water from Northern California to agriculture and urban communities to the south; millions of people and businesses depend on Delta water. Decades of competing demands for Delta resources and year-to-year variability in precipitation has resulted in diminished overall health of the Delta. Declines in fish populations, threatened ecosystems, endangered species, invasive plants and animals, cuts in agricultural exports, and increased water conservation is the result. NASA and the USDA, building on previous collaborations, aide local Delta stakeholders in assessing and developing an invasive weed management approach. Aquatic, terrestrial, and riparian invasive weeds threaten aquatic and terrestrial ecosystem restoration efforts. Aquatic weeds are currently detrimental economically, environmentally, and sociologically in the Delta. They negatively impact the redistribution of water and disrupt the ecology of the Bay Delta food web. Filling current science gaps in the Delta Plan and improving management practices within the Delta are important to achieving the mission of improved Delta health. Methods developed can become routine land and water management tools. New high-resolution NASA sensor systems could be used to provide data packages specifically designed for water system The presenter will also speak about his personal experience and the role Delaware Valley College played in preparation for a professional career science.

Water↗

Decoupling of greenness and gross primary productivity as aridity decreases

Ecosystem primary productivity is a key ecological process influencing many ecosystem services, including carbon storage. Thus, clarifying how primary productivity in terrestrial ecosystems responds to climatic variability can reveal key mechanisms that will drive future changes in the global carbon budget. Satellite products of canopy greenness are widely used as proxies for vegetation productivity to evaluate how ecosystems respond to climate variability. However, to what degree inter-annual variations in productivity are consistent with greenness and how this relationship varies spatially remains unclear. Here we investigated the strength of the coupling between inter-annual variations in leaf area index (LAI, a measure of greenness) and ecosystem gross primary productivity (GPP) derived from eddy covariance towers, i.e., the r2 of the LAI-GPP relationship. Overall, inter-annual GPP and LAI were highly coupled (i.e., high r2) in arid grasslands, but were fully decoupled in mesic evergreen broadleaf forests, indicating that this relationship varies strongly along aridity gradients. A possible mechanism of the spatial variation in the LAI-GPP relationship is that the tradeoff between ecosystem structure (LAI) and physiology (photosynthesis per unit leaf area) becomes stronger in more humid climates. Land models overestimated the r2 of LAI-GPP correlation for most ecosystem types and failed to capture the spatial pattern along aridity gradients. We conclude that relying on greenness products for evaluating inter-annual changes in vegetation productivity may bias assessments, especially in tropical rainforest ecosystems. Our findings may also reconcile observed disparities between responses in greenness and GPP during drought in Amazon forests.

54 ENVIRONMENTAL SCIENCES↗

A meta-analysis of 1,119 manipulative experiments on terrestrial carbon-cycling responses to global change

Direct quantification of terrestrial biosphere responses to global change is crucial for projections of future climate change in Earth system models. Here, we synthesized ecosystem carbon-cycling data from 1,119 experiments performed over the past four decades concerning changes in temperature, precipitation, CO2 and nitrogen across major terrestrial vegetation types of the world. Most experiments manipulated single rather than multiple global change drivers in temperate ecosystems of the USA, Europe and China. The magnitudes of warming and elevated CO2 treatments were consistent with the ranges of future projections, whereas those of precipitation changes and nitrogen inputs often exceeded the projected ranges. Increases in global change drivers consistently accelerated, but decreased precipitation slowed down carbon-cycle processes. Nonlinear (including synergistic and antagonistic) effects among global change drivers were rare. Belowground carbon allocation responded negatively to increased precipitation and nitrogen addition and positively to decreased precipitation and elevated CO2. The sensitivities of carbon variables to multiple global change drivers depended on the background climate and ecosystem condition, suggesting that Earth system models should be evaluated using site-specific conditions for best uses of this large dataset. Together, this synthesis underscores an urgent need to explore the interactions among multiple global change drivers in underrepresented regions such as semi-arid ecosystems, forests in the tropics and subtropics, and Arctic tundra when forecasting future terrestrial carbon-climate feedback.

Song, Jian↗

The predictive power of phylogeny on growth rates in soil bacterial communities

Abstract Predicting ecosystem function is critical to assess and mitigate the impacts of climate change. Quantitative predictions of microbially mediated ecosystem processes are typically uninformed by microbial biodiversity. Yet new tools allow the measurement of taxon-specific traits within natural microbial communities. There is mounting evidence of a phylogenetic signal in these traits, which may support prediction and microbiome management frameworks. We investigated phylogeny-based trait prediction using bacterial growth rates from soil communities in Arctic, boreal, temperate, and tropical ecosystems. Here we show that phylogeny predicts growth rates of soil bacteria, explaining an average of 31%, and up to 58%, of the variation within ecosystems. Despite limited overlap in community composition across these ecosystems, shared nodes in the phylogeny enabled ancestral trait reconstruction and cross-ecosystem predictions. Phylogenetic relationships could explain up to 38% (averaging 14%) of the variation in growth rates across the highly disparate ecosystems studied. Our results suggest that shared evolutionary history contributes to similarity in the relative growth rates of related bacteria in the wild, allowing phylogeny-based predictions to explain a substantial amount of the variation in taxon-specific functional traits, within and across ecosystems.

Walkup, Jeth (ORCID:0000000279082963)↗

S4PST: Sustainability for Programming Systems and Tools: May Workshop Report

The US Department of Energy (DOE) Exascale Computing Project (ECP) has fostered and strengthened the use of modern software engineering practices for developing applications and libraries, and this effort has resulted in the coordinated and interoperable E4S1 and xSDK2 ecosystems. Although this approach is cost-effective, it relies on robust programming systems and tools (PST) as the underlying foundation for our HPC software. At present, our primary PST stack consists of traditional high-performance computing (HPC) languages, namely Fortran, C, C++, and the popular Python language for data analysis and AI workflows. These languages support various programming frameworks and run-time abstractions that enable parallelism and concurrency across multiple node architectures and thousands of nodes through a variety of interconnect systems. However, to accommodate users’ diverse needs, certain aspects of the HPC ecosystem are delegated to vendor-specific or third-party implementations that extend beyond a particular scientific domain. This broader scope results in a multitude of specifications and variations, which leads to a complex orchestration of many-ecosystems. Unfortunately, this complexity in the ecosystem imposes additional overhead costs on consumers during the latter stages of the development cycle. In addition to the software ecosystem challenge, the upcoming conclusion of the ECP by December 2023 has raised significant concerns within the HPC programming systems community, from both the economic and social perspectives. The ECP has implemented a management structure for software development and funding decisions across all ECP participants by following a conventional hierarchical and centralized approach. However, this structure has prompted certain considerations within the community, particularly in anticipation of the Software Sustainability initiative by the DOE’s Advanced Scientific Computing Research Program (ASCR). For the success of this new initiative, it is of utmost importance to secure consistent funding and foster close engagement with researchers and core developers of existing programming-system products. This collaboration is vital to maintaining the critical capabilities of the current software during the transition phase while proactively adapting to future technology and workforce trends. The community recognizes the significance of adapting to emerging trends and is aware of the inherent fragility of the HPC software ecosystem, particularly in relation to programming systems that cater to all users. The ability to adapt and evolve is essential to staying relevant and effectively addressing these technical, economic, and social challenges. The S4PST team, which represents one of the six ASCR Software Sustainability seedling projects, is dedicated to tackling these challenges through community-based approaches that go beyond the scope of the DOE. This involves collaboration between national laboratories with academia, non-DOE institutions, hardware and system vendors, and international partners. By fostering these partnerships, we aim to create a robust and sustainable HPC software ecosystem that can effectively meet the needs of the community. This new community effort, driven by the eight DOE labs, will take on the responsibility of guiding funding decisions for programming-systems development and maintenance with transparency and consistency across all decisions. Additionally, the team will offer common technical services to the programming systems community, irrespective of their funding situations, and facilitate community-wide incubation to proactively nurture the software ecosystem. By actively engaging with stakeholders and employing a collaborative approach, we can collectively shape the future of programming systems and ensure a robust and thriving HPC software landscape. On May 11–12, 2023, the S4PST team conducted its inaugural kick-off workshop at the Innovative Computing Laboratory (ICL) in the University of Tennessee, Knoxville, hosted by Hartwig Anzt. The workshop encompassed various sessions dedicated to presentations and discussions, with the aim of comprehending the team members’ perspectives on the vision of software sustainability. Additionally, the workshop aimed to identify the technical, economic, and social requirements for sustaining the programming-systems community in the field of HPC. This report provides a summary of the S4PST effort by highlighting five major thrust areas discussed during the workshop: (i) community, (ii) technical support, (iii) training and diversity, (iv) verification, validation and correctness, and (v) emerging technologies. It also encompasses an overview of the presentations and discussions held throughout the event, our views and potential synergies with other seedling efforts, along with the outcomes and key takeaways from our initial discussions.

97 MATHEMATICS AND COMPUTING↗

Integrating the Social, Hydrological and Ecological Dimensions of Freshwater Health: The Freshwater Health Index

Degradation of freshwater ecosystems and the services they provide is a primary cause of increasing water insecurity, raising the need for integrated solutions to freshwater management. While methods for characterizing the multi-faceted challenges of managing freshwater ecosystems abound, they tend to emphasize either social or ecological dimensions and fall short of being truly integrative. This paper suggests that management for sustainability of freshwater systems needs to consider the linkages between human water uses, freshwater ecosystems and governance. We present a conceptualization of freshwater resources as part of an integrated social-ecological system and propose a set of corresponding indicators to monitor freshwater ecosystem health and to highlight priorities for management. We demonstrate an application of this new framework -the Freshwater Health Index (FHI) - in the Dongjiang River Basin in southern China, where stakeholders are addressing multiple and conflicting freshwater demands. By combining empirical and modeled datasets with surveys to gauge stakeholders' preferences and elicit expert information about governance mechanisms, the FHI helps stakeholders understand the status of freshwater ecosystems in their basin, how ecosystems are being manipulated to enhance or decrease water-related services, and how well the existing water re-source management regime is equipped to govern these dynamics over time. This framework helps to operationalize a truly integrated approach to water resource management by recognizing the interplay between governance, stakeholders, freshwater ecosystems and the services they provide

ecosystem services↗

The role of reforestation in carbon sequestration

In the United States (U.S.), the maintenance of forest cover is a legal mandate for federally managed forest lands. More broadly, reforestation following harvesting, recent or historic disturbances can enhance numerous carbon (C)-based ecosystem services and functions. These include production of woody biomass for forest products, and mitigation of atmospheric CO 2 pollution and climate change by sequestering C into ecosystem pools where it can be stored for long timescales. Nonetheless, a range of assessments and analyses indicate that reforestation in the U.S. lags behind its potential, with the continuation of ecosystem services and functions at risk if reforestation is not increased. In this context, there is need for multiple independent analyses that quantify the role of reforestation in C sequestration, from ecosystems up to regional and national levels. Here, we describe the methods and report the findings of a large-scale data synthesis aimed at four objectives: (1) estimate C storage in major ecosystem pools in forest and other land cover types; (2) quantify sources of variation in ecosystem C pools; (3) compare the impacts of reforestation and afforestation on C pools; (4) assess whether these results hold or diverge across ecoregions. The results of our synthesis support four overarching inferences regarding reforestation and other land use impacts on C sequestration. First, in the bigger picture, soils are the dominant C pool in all ecosystems and land cover types in the U.S., and soil C pool sizes vary less by land cover than by other factors, such as spatial variation or soil wetness. Second, where historically cultivated lands are being reforested, topsoils are sequestering significant amounts of C, with the majority of reforested lands yet to reach their capacity relative to the potential indicated by natural forest soils. Third, the establishment of woody vegetation delivers immediate to multi-decadal C sequestration benefits in aboveground woody biomass and coarse woody debris pools, with two- to three-fold C sequestration benefits in biomass during the first several decades following planting. Fourth, opportunities to enhance C sequestration through reforestation vary among the ecoregions, according to current levels of planting, typical forest growth rates, and past land uses (especially cultivation). Furthermore, our results suggest that an immediate, but phased and spatially targeted approach to reforestation can enhance C sequestration in forest biomass and soils in the U.S. for decades to centuries to come.

54 ENVIRONMENTAL SCIENCES↗

Green spaces are not all the same for the provision of air purification and climate regulation services: The case of urban parks

Highlights: • Air purification and climate regulation were quantified in an urban green space. • Different vegetation types shown different capacities to provide these services. • Original woodland presented the higher ecosystem services provision. • Vegetation structure, composition and management matter to services provision. • Nature-based solutions in urban areas can optimize local climate and air quality. The growing human population concentrated in urban areas lead to the increase of road traffic and artificial areas, consequently enhancing air pollution and urban heat island effects, among others. These environmental changes affect citizen's health, causing a high number of premature deaths, with considerable social and economic costs. Nature-based solutions are essential to ameliorate those impacts in urban areas. While the mere presence of urban green spaces is pointed as an overarching solution, the relative importance of specific vegetation structure, composition and management to improve the ecosystem services of air purification and climate regulation are overlooked. This avoids the establishment of optimized planning and management procedures for urban green spaces with high spatial resolution and detail. Our aim was to understand the relative contribution of vegetation structure, composition and management for the provision of ecosystem services of air purification and climate regulation in urban green spaces, in particular the case of urban parks. This work was done in a large urban park with different types of vegetation surrounded by urban areas. As indicators of microclimatic effects and of air pollution levels we selected different metrics: lichen diversity and pollutants accumulation in lichens. Among lichen diversity, functional traits related to nutrient and water requirements were used as surrogates of the capacity of vegetation to filter air pollution and to regulate climate, and provide air purification and climate regulation ecosystem services, respectively. This was also obtained with very high spatial resolution which allows detailed spatial planning for optimization of ecosystem services. We found that vegetation type characterized by a more complex structure (trees, shrubs and herbaceous layers) and by the absence of management (pruning, irrigation and fertilization) had a higher capacity to provide the ecosystems services of air purification and climate regulation. By contrast, lawns, which have a less complex structure and are highly managed, were associated to a lower capacity to provide these services. Tree plantations showed an intermediate effect between the other two types of vegetation. Thus, vegetation structure, composition and management are important to optimize green spaces capacity to purify air and regulate climate. Taking this into account green spaces can be managed at high spatial resolutions to optimize these ecosystem services in urban areas and contribute to improve human well-being.

54 ENVIRONMENTAL SCIENCES↗

Climate adaptation and sustainability in switchgrass: exploring plant-microbe-soil interactions across continental scale environmental gradients

Less carbon-intensive energy sources are needed to reduce greenhouse gas emissions and their predicted role in climate change. There is growing interest in the potential of biofuels for meeting this need. A critical question is whether large-scale biofuel production can be sustainable over the time scales needed to mitigate our carbon debt from fossil fuel consumption. The carbon balance and ultimately the sustainability of biofuel feedstock production is the result of complex climate-coupled interactions between carbon fixation, sequestration, and release through combustion. Similarly, the long-term productivity of biofuels depends on the environmental factors limiting plant growth. These factors are often related to soil resources which involve complex interactions at the plant-microbe-soil interface impacting their availability and cycling. Our collaborative project addressed sustainable switchgrass (Panicum virgatum) production by exploring Plant Systems, Plant-Microbiome Interactions, and Ecosystem Processes through the integrating lens of Multi-Scale Modeling. Our research was based on detailed characterization of genetically diverse switchgrass genotypes planted in common gardens across a continental latitudinal gradient. The underlying theme of our Plant Systems research was the use of locally adapted plant material to explore plant function, to understand the mechanistic basis of environmental interactions, and to discover the plant genes important for adaptation and sustainability in the face of climate change. Our Plant-Microbiome Interaction project characterized the microbial communities associated with switchgrass using genomic tools. Our Ecosystem Processes research focused on carbon cycle responses at the ecosystem level using stand level plantings. Finally, our Multi-Scale Modeling helped to define conditions of a sustainable biofuel system and identify key tradeoffs between genetic diversity, productivity, and ecosystem services. Genome-wide association analyses were used to identify alleles that contribute to successful establishment and biomass production across North America. Together, our work provided a baseline analyses of the potential of switchgrass as a biofuel feedstock. Our project resulted in a number of successful outcomes. First, we were successful in collecting switchgrass germplasm across the species range, propagating the material, and establishing common garden experiments across the species range. In collaboration with DOE JGI, we successfully assembled the first tetraploid switchgrass genome and published this resource with an analyses of the genetic basis local adaptation from our gardens (Lowry et al. 2019, Lovell et al. 2021). The gardens were used to characterize the genetic architecture for a number of important plant phenotypes. Our project also conducted extensive sampling and sequencing to characterize the bacterial and fungal associates of switchgrass roots and leaves. We showed that host genotype, location, and harvesting practices can play a role in microbiome assembly (Singer et al. 2019 & 2022, Van Wallendael et al. 2020 & 2022, Edwards et al. 2023). Our ecosystem processes work created baseline dataset of carbon and nutrient cycling in realistic stand plantings of switchgrass. Data from this experiment provided new insight into the role of plant traits, phenology, and local environments in ecosystem processes like soil respiration, net-ecosystem exchange, and dynamics of soil and plant nutrients (Ricketts et al. 2023). Finally, our crop modelling experiments help to characterize the sensitivity of common modeling frameworks to parameters, identify key limiters of productivity across large geographic scales, and leverage patterns of local adaptation in prediction. Ultimately, these studies help to identify critical plant-microbe-soil traits that may be manipulated, through breeding or agronomic management, to improve the sustainability of biofuel feedstocks.

09 BIOMASS FUELS↗

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

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

59 BASIC BIOLOGICAL SCIENCES↗