Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “ECOSYSTEMS”

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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
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 OSTI2014

Bridging the Divide: Linking Genomics to Ecosystem Responses to Climate Change: Final Report

Over the project period, we have addressed the following objectives: 1) assess the effects of altered precipitation patterns (i.e., increased variability in growing season precipitation) on genetic diversity of the dominant C4 grass species, Andropogon gerardii, and 2) experimentally assess the impacts of extreme climatic events (heat wave, drought) on responses of the dominant C4 grasses, A. gerardii and Sorghastrum nutans, and the consequences of these response for community and ecosystem structure and function. Below is a summary of how we have addressed these objectives. Objective 1 After ten years of altered precipitation, we found the number of genotypes of A. gerardii was significantly reduced compared to the ambient precipitation treatments (Avolio et al., 2013a). Although genotype number was reduced, the remaining genotypes were less related to one another indicating that the altered precipitation treatment was selecting for increasingly dissimilar genomes (based on mean pairwise Dice distance among individuals). For the four key genotypes that displayed differential abundances depending on the precipitation treatment (G1, G4, and G11 in the altered plots and G2 in the ambient plots), we identified phenotypic differences in the field that could account for ecological sorting (Avolio & Smith, 2013a). The three altered rainfall genotypes also have very different phenotypic traits in the greenhouse in response to different soil moisture availabilities (Avolio and Smith, 2013c). Two of the genotypes that increased in abundance in the altered precipitation plots had greater allocation to root biomass (G4 and G11), while G1 allocated more biomass aboveground. These phenotypic differences among genotypes suggests that changes in genotypic structure between the altered and the ambient treatments has likely occurred via niche differentiation, driven by changes in soil moisture dynamics (reduced mean, increased variability and changes in the depth distribution of soil moisture) under a more variable precipitation regime, rather than reduced population numbers (A. gerardii tiller densities did not differ between altered and ambient treatments; p = 0.505) or a priori differences in genotype richness (Avolio et al.2013a). This ecological sorting of genotypes, which accounts for 40% of all sampled individuals in the altered plots, is an important legacy of the press chronic climate changes in the RaMPs experiment. Objective 2 In May 2010, we established the Climate Extremes Experiment at the Konza Prairie Biological Station. For the experiment, a gradient of temperatures, ranging from ambient to extreme, were imposed in 2010 and 2011 as a mid-season heat wave under well-watered or severe drought conditions. This study allowed us for the first time to examine species-specific thresholds of responses to climate extremes and assess how these phenotypic responses may impact selection of particular genotypes, with the ultimate goal of linking alterations in individual performance and genetic diversity to ecosystem structure and functioning. We found that tallgrass prairie was resistant to heat waves, but it was not resistant to extreme drought, which reduced aboveground net primary productivity (ANPP) below the lowest level measured in this grassland in almost thirty years (Hoover et al. in press(a)). This extreme reduction in ecosystem function was a consequence of reduced productivity of both C4 grasses and C3 forbs. This reduction in biomass of the C4 grasses (Andropogon gerardii and Sorghastrum nutans) was, in part, due to significant reductions in photosynthesis, leaf water potential and productivity with drought in the dominant grasses species, with S. nutans was more sensitive than A. gerardii to drought (Hoover et al. in press(b)). However, the dominant forb was negatively impacted by the drought more than the dominant grasses, and this led to a reordering of species abundances within the plant community. Although this change in community composition persisted post-drought, ANPP recovered completely the year after drought due to rapid demographic responses by the dominant grass, compensating for loss of the dominant forb. Overall, our results show that an extreme reduction in ecosystem function attributable to a climate extreme (e.g., low resistance) does not preclude rapid ecosystem recovery. Given that dominance by a few species is characteristic of most ecosystems, knowledge of the traits of these species and their responses to climate extremes will be key for predicting future ecosystem dynamics and function. In addition, our research suggests that water stress will dominate photosynthetic and productivity responses caused by discrete drought and heat wave events, rather than direct or additive effects of heat stress, with differential sensitivity in these grasses altering future ecosystem function.

54 ENVIRONMENTAL SCIENCES↗
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↗
NASA NTRS1992

Linkages between terrestrial ecosystems and the atmosphere

The primary research issue in understanding the role of terrestrial ecosystems in global change is analyzing the coupling between processes with vastly differing rates of change, from photosynthesis to community change. Representing this coupling in models is the central challenge to modeling the terrestrial biosphere as part of the earth system. Terrestrial ecosystems participate in climate and in the biogeochemical cycles on several temporal scales. Some of the carbon fixed by photosynthesis is incorporated into plant tissue and is delayed from returning to the atmosphere until it is oxidized by decomposition or fire. This slower (i.e., days to months) carbon loop through the terrestrial component of the carbon cycle, which is matched by cycles of nutrients required by plants and decomposers, affects the increasing trend in atmospheric CO2 concentration and imposes a seasonal cycle on that trend. Moreover, this cycle includes key controls over biogenic trace gas production. The structure of terrestrial ecosystems, which responds on even longer time scales (annual to century), is the integrated response to the biogeochemical and environmental constraints that develop over the intermediate time scale. The loop is closed back to the climate system since it is the structure of ecosystems, including species composition, that sets the terrestrial boundary condition in the climate system through modification of surface roughness, albedo, and, to a great extent, latent heat exchange. These separate temporal scales contain explicit feedback loops which may modify ecosystem dynamics and linkages between ecosystems and the atmosphere. The long-term change in climate, resulting from increased atmospheric concentrations of greenhouse gases (e.g., CO2, CH4, and nitrous oxide (N2O)) will further modify the global environment and potentially induce further ecosystem change. Modeling these interactions requires coupling successional models to biogeochemical models to physiological models that describe the exchange of water, energy, and biogenic trace gases between the vegetation and the atmosphere at fine time scales. There does not appear to be any obvious way to allow direct reciprocal coupling of atmospheric general circulation models (GCM's), which inherently run with fine time steps, to ecosystem or successional models, which have coarse temporal resolution, without the interposition of physiological canopy models. This is equally true for biogeochemical models of the exchange of carbon dioxide and trace gases. This coupling across time scales is nontrivial and sets the focus for the modeling strategy.

Bretherton, Francis↗
DOE OSTI2019

Predicting impacts of chemicals from organisms to ecosystem service delivery: A case study of insecticide impacts on a freshwater lake

Assessing and managing risks of anthropogenic activities to ecological systems is necessary to ensure sustained delivery of ecosystem services for future generations. Ecological models provide a means of quantitatively linking measured risk assessment endpoints with protection goals, by integrating potential chemical effects with species life history, ecological interactions, environmental drivers and other potential stressors. In this work we demonstrate how an ecosystem modeling approach can be used to quantify insecticide-induced impacts on ecosystem services provided by a lake from toxicity data for organism-level endpoints. We used a publicly available aquatic ecosystem model AQUATOX that integrates environmental fate of chemicals and their impacts on food webs in aquatic environments. By simulating a range of exposure patterns, we illustrated how exposure to a hypothetical insecticide could affect aquatic species populations (e.g., recreational fish abundance) and environmental properties (e.g., water clarity) that would in turn affect delivery of ecosystem services. Different results were observed for different species of fish, thus the decision to manage the use of the insecticide for ecosystem services derived by anglers depends upon the favored species of fish. In our hypothetical shallow reservoir, water clarity was mostly driven by changes in food web dynamics, specifically the presence of zooplankton. In contrast to the complex response by fishing value, water clarity increased with reduced insecticide use, which produced a monotonic increase in value by waders and swimmers. Our research clearly showed the importance of considering nonlinear ecosystem feedbacks where the presence of insecticide changed the modeled food-web dynamics in unexpected ways. Our study introduces one of the main advantages of using ecological models for risk assessment, namely the ability to generalize to meaningful levels of organization and to facilitate quantitative comparisons among alternative scenarios and associated trade-offs among them while explicitly accounting for different groups of beneficiaries.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2012

Ecosystem carbon storage capacity as affected by disturbance regimes: A general theoretical model

Disturbances have been recognized as a key factor shaping terrestrial ecosystem states and dynamics. A general model that quantitatively describes the relationship between carbon storage and disturbance regime is critical for better understanding large scale terrestrial ecosystem carbon dynamics. We developed a model (REGIME) to quantify ecosystem carbon storage capacities (E[x]) under varying disturbance regimes with an analytical solution E[x] = U {center_dot} {tau}{sub E} {center_dot} {lambda}{lambda} + s {tau} 1, where U is ecosystem carbon influx, {tau}{sub E} is ecosystem carbon residence time, and {tau}{sub 1} is the residence time of the carbon pool affected by disturbances (biomass pool in this study). The disturbance regime is characterized by the mean disturbance interval ({lambda}) and the mean disturbance severity (s). It is a Michaelis-Menten-type equation illustrating the saturation of carbon content with mean disturbance interval. This model analytically integrates the deterministic ecosystem carbon processes with stochastic disturbance events to reveal a general pattern of terrestrial carbon dynamics at large scales. The model allows us to get a sense of the sensitivity of ecosystems to future environmental changes just by a few calculations. According to the REGIME model, for example, approximately 1.8 Pg C will be lost in the high-latitude regions of North America (>45{sup o} N) if fire disturbance intensity increases around 5.7 time the current intensity to the end of the twenty-first century, which will require around 12% increases in net primary productivity (NPP) to maintain stable carbon stocks. If the residence time decreased 10% at the same time additional 12.5% increases in NPP are required to keep current C stocks. The REGIME model also lays the foundation for analytically modeling the interactions between deterministic biogeochemical processes and stochastic disturbance events.

09 BIOMASS FUELS↗
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 OSTI2019

Reimagining the potential of Earth observations for ecosystem service assessments

The benefits nature provides to people, called ecosystem services, are increasingly recognized and accounted for in assessments of infrastructure development, agricultural management, conservation prioritization, and sustainable sourcing. These assessments are often limited by data, however, a gap with tremendous potential to be filled through Earth observations (EO), which produce a variety of data across spatial and temporal extents and resolutions. Despite widespread recognition of this potential, in practice few ecosystem service studies use EO. Here, we identify challenges and opportunities to using EO in ecosystem service modeling and assessment. Some challenges are technical, related to data awareness, processing, and access. These challenges require systematic investment in model platforms and data management. Other challenges are more conceptual but still systemic; they are byproducts of the structure of existing ecosystem service models and addressing them requires scientific investment in solutions and tools applicable to a wide range of models and approaches. We also highlight new ways in which EO can be leveraged for ecosystem service assessments, identifying promising new areas of research. More widespread use of EO for ecosystem service assessment will only be achieved if all of these types of challenges are addressed. Furthermore, this will require non-traditional funding and partnering opportunities from private and public agencies to promote data exploration, sharing, and archiving. Investing in this integration will be reflected in better and more accurate ecosystem service assessments worldwide.

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↗
DOE OSTI2024

Decadal increases in carbon uptake offset by respiratory losses across northern permafrost ecosystems

Tundra and boreal ecosystems encompass the northern circumpolar permafrost region and are experiencing rapid environmental change with important implications for the global carbon (C) budget. We analysed multi-decadal time series containing 302 annual estimates of carbon dioxide (CO 2 ) flux across 70 permafrost and non-permafrost ecosystems, and 672 estimates of summer CO 2 flux across 181 ecosystems. We find an increase in the annual CO 2 sink across non-permafrost ecosystems but not permafrost ecosystems, despite similar increases in summer uptake. Thus, recent non-growing-season CO 2 losses have substantially impacted the CO 2 balance of permafrost ecosystems. Furthermore, analysis of interannual variability reveals warmer summers amplify the C cycle (increase productivity and respiration) at putatively nitrogen-limited sites and at sites less reliant on summer precipitation for water use. Our findings suggest that water and nutrient availability will be important predictors of the C-cycle response of these ecosystems to future warming.

58 GEOSCIENCES↗
DOE OSTI2023

Viral infections likely mediate microbial controls on ecosystem responses to global warming

Abstract Climate change is affecting how energy and matter flow through ecosystems, thereby altering global carbon and nutrient cycles. Microorganisms play a fundamental role in carbon and nutrient cycling and are thus an integral link between ecosystems and climate. Here, we highlight a major black box hindering our ability to anticipate ecosystem climate responses: viral infections within complex microbial food webs. We show how understanding and predicting ecosystem responses to warming could be challenging—if not impossible—without accounting for the direct and indirect effects of viral infections on different microbes (bacteria, archaea, fungi, protists) that together perform diverse ecosystem functions. Importantly, understanding how rising temperatures associated with climate change influence viruses and virus-host dynamics is crucial to this task, yet is severely understudied. In this perspective, we (i) synthesize existing knowledge about virus-microbe-temperature interactions and (ii) identify important gaps to guide future investigations regarding how climate change might alter microbial food web effects on ecosystem functioning. To provide real-world context, we consider how these processes may operate in peatlands—globally significant carbon sinks that are threatened by climate change. We stress that understanding how warming affects biogeochemical cycles in any ecosystem hinges on disentangling complex interactions and temperature responses within microbial food webs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Interannual variability of ecosystem carbon exchange: From observation to prediction

Here, terrestrial ecosystems have sequestered, on average, the equivalent of 30% of anthropogenic carbon (C) emissions during the past decades, but annual sequestration varies from year to year. For effective C management, it is imperative to develop a predictive understanding of the interannual variability (IAV) of terrestrial net ecosystem C exchange (NEE). Location: Global terrestrial ecosystems. Furthermore, we conducted a comprehensive review to examine the IAV of NEE at global, regional and ecosystem scales. Then we outlined a conceptual framework for understanding how anomalies in climate factors impact ecological processes of C cycling and thus influence the IAV of NEE through biogeochemical regulation. As a result, the phenomenon of IAV in land NEE has been ubiquitously observed at global, regional and ecosystem scales. Global IAV is often attributable to either tropical or semi-arid regions, or to some combination thereof, which is still under debate. Previous studies focus on identifying climate factors as driving forces of IAV, whereas biological mechanisms underlying the IAV of ecosystem NEE are less clear. We found that climate anomalies affect the IAV of NEE primarily through their differential impacts on ecosystem C uptake and respiration. Moreover, recent studies suggest that the carbon uptake period makes less contribution than the carbon uptake amplitude to IAV in NEE. Although land models incorporate most processes underlying IAV, their efficacy to predict the IAV in NEE remains low. In conclusion, to improve our ability to predict future IAV of the terrestrial C cycle, we have to understand biological mechanisms through which anomalies in climate factors cause the IAV of NEE. Future research needs to pay more attention not only to the differential effects of climate anomalies on photosynthesis and respiration but also to the relative importance of the C uptake period and amplitude in causing the IAV of NEE. Ultimately, we need multiple independent approaches, such as benchmark analysis, data assimilation and time-series statistics, to integrate data, modelling frameworks and theory to improve our ability to predict future IAV in the terrestrial C cycle.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Biotic and climatic controls on interannual variability in carbon fluxes across terrestrial ecosystems

Interannual variability (IAV, represented by standard deviation) in net ecosystem exchange of CO 2 (NEE) is mainly driven by climatic drivers and biotic variations (i.e., the changes in photosynthetic and respiratory responses to climate), the effects of which are referred to as climatic (CE) and biotic effects (BE), respectively. Evaluating the relative contributions of CE and BE to the IAV in carbon (C) fluxes and understanding their controlling mechanisms are critical in projecting ecosystem changes in the future climate. In this study, we applied statistical methods with flux data from 65 sites located in the Northern Hemisphere to address this issue. Our results showed that the relative contribution of BE (CnBE) and CE (CnCE) to the IAV in NEE was 57% ± 14% and 43% ± 14%, respectively. The discrepancy in the CnBE among sites could be largely explained by water balance index (WBI). Across water-stressed ecosystems, the CnBE decreased with increasing aridity (slope = 0.18% mm –1 ). In addition, the CnBE tended to increase and the uncertainty reduced as timespan of available data increased from 5 to 15 years. Inter-site variation of the IAV in NEE mainly resulted from the IAV in BE (72%) compared to that in CE (37%). Interestingly, positive correlations between BE and CE occurred in grasslands and dry ecosystems (r > 0.45, P < 0.05) but not in other ecosystems. Furthermore, these results highlighted the importance of BE in determining the IAV in NEE and the ability of ecosystems to regulate C fluxes under climate change might decline when the ecosystems experience more severe water stress in the future.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Analyzing urban ecosystem variation in the City of Dongguan: A stepwise cluster modeling approach

Highlights: • A stepwise cluster modeling approach is proposed for urban ecosystem simulation. • Nonlinear relationship is established among NDVI and multiple drivers. • Vegetation conditions get better gradually from the north to the south of Dongguan. • Ecosystem in the east of Dongguan is sensitive to growth of economy and population. In this study, a stepwise cluster modeling approach (SCMA) is developed for analyzing urban ecosystem variation via Normalized Difference Vegetation Index (NDVI). NDVI is an indicator of vegetation growth and coverage and useful in reflecting urban ecosystem. SCMA is established on a cluster tree that can characterize the complex relationship between independent and dependent variables. SCMA is applied to the City of Dongguan for simulating the urban NDVI and identifying associated drivers of human activity, topography and meteorology without specific functions. Results show that SCMA performances better than conventional statistical methods, illustrating the ability of SCMA in capturing the complex and nonlinear features of urban ecosystem. Results disclose that human activities play negative effects on NDVI due to the destruction of green space for pursuing more space for buildings. NDVI reduces gradually from the south part to the north part of Dongguan due to increased gross domestic product and population density, indicating that the ecosystem in Dongguan is better in the south part. NDVI in the northeast part (dominated by agriculture) is sensitive to the growth of economy and population. More attention should be paid to this part for sustainable development, such as increasing afforestation, planting grass and constructing parks. Precipitation has a positive effect on NDVI due to the promotion of soil moisture that is beneficial to plants’ growth. Awareness of these complexities is helpful for sustainable development of urban ecosystem.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Effect of climate warming on the annual terrestrial net ecosystem CO 2 exchange globally in the boreal and temperate regions

The net ecosystem CO 2 exchange is the result of the imbalance between the assimilation process (gross primary production, GPP) and ecosystem respiration (RE). The aim of this study was to investigate temperature sensitivities of these processes and the effect of climate warming on the annual terrestrial net ecosystem CO 2 exchange globally in the boreal and temperate regions. A database of 403 site-years of ecosystem flux data at 101 sites in the world was collected and analyzed. Temperature sensitivities of rates of RE and GPP were quantified with Q 10 , defined as the increase of RE (or GPP) rates with a temperature rise of 10 °C. Results showed that on the annual time scale, the intrinsic temperature sensitivity of GPP (Q 10sG ) was higher than or equivalent to the intrinsic temperature sensitivity of RE (Q 10sR ). Q 10sG was negatively correlated to the mean annual temperature (MAT), whereas Q 10sR was independent of MAT. The analysis of the current temperature sensitivities and net ecosystem production suggested that temperature rise might enhance the CO 2 sink of terrestrial ecosystems both in the boreal and temperate regions. Additionally, ecosystems in these regions with different plant functional types should sequester more CO 2 with climate warming.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Decomposition decreases molecular diversity and ecosystem similarity of soil organic matter

Soil organic matter (SOM) is comprised of a diverse array of reactive carbon molecules, including hydrophilic and hydrophobic compounds, that impact rates of SOM formation and persistence. Despite clear importance to ecosystem science, little is known about broad-scale controls on SOM diversity and variability in soil. Here, we show that microbial decomposition drives significant variability in the molecular richness and diversity of SOM between soil horizons and across a continental-scale gradient in climate and ecosystem type (arid shrubs, coniferous, deciduous, and mixed forests, grasslands, and tundra sedges). The molecular dissimilarity of SOM was strongly influenced by ecosystem type (hydrophilic compounds: 17%, P < 0.001; hydrophobic compounds: 10% P < 0.001) and soil horizon (hydrophilic compounds: 17%, P < 0.001; hydrophobic compounds: 21%, P < 0.001), as assessed using metabolomic analysis of hydrophilic and hydrophobic metabolites. While the proportion of shared molecular features was significantly higher in the litter layer than subsoil C horizons across ecosystems (12 times and 4 times higher for hydrophilic and hydrophobic compounds, respectively), the proportion of site-specific molecular features nearly doubled from the litter layer to the subsoil horizon, suggesting greater differentiation of compounds after microbial decomposition within each ecosystem. Together, these results suggest that microbial decomposition of plant litter leads to a decrease in SOM α-molecular diversity, yet an increase in β-molecular diversity across ecosystems. The degree of microbial degradation, determined by the position in the soil profile, exerts a greater control on SOM molecular diversity than environmental factors, such as soil texture, moisture, and ecosystem type.

59 BASIC BIOLOGICAL SCIENCES↗