Ecosystem discovery: Measuring clean energy innovation ecosystems through knowledge discovery and mapping techniques
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Testing complex land surface models has often proceeded by asking the question: does the model prediction agree with the observation? This approach has yet led to high-performance terrestrial models that meet the challenges of climate and ecological studies. Here we test the Community Land Model (CLM) by asking the question: does the model behave like an ecosystem? We pursue its answer by testing CLM in the ecosystem functional space (EFS) at the Missouri Ozark AmeriFlux (MOFLUX) forest site in the Central U.S., focusing on carbon and water flux responses to precipitation regimes and associated stresses. In the observed EFS, precipitation regimes and associated water and heat stresses controlled seasonal and interannual variations of net ecosystem exchange (NEE) of CO 2 and evapotranspiration in this deciduous forest ecosystem. Such controls were exerted more strongly by precipitation variability than by the total precipitation amount per se. A few simply constructed climate variability indices captured these controls, suggesting a high degree of potential predictability. While the interannual fluctuation in NEE was large, a net carbon sink was maintained even during an extreme drought year. Although CLM predicted seasonal and interanual variations in evapotranspiration reasonably well, its predictions of net carbon uptake were too small across the observed range of climate variability. Also, the model systematically underestimated the sensitivities of NEE and evapotranspiration to climate variability and overestimated the coupling strength between carbon and water fluxes. Its suspected that the modeled and observed trajectories of ecosystem fluxes did not overlap in the EFS and the model did not behave like the ecosystem it attempted to simulate. A definitive conclusion will require comprehensive parameter and structural sensitivity tests in a rigorous mathematical framework. We also suggest that future model improvements should focus on better representation and parameterization of process responses to environmental stresses and on more complete and robust representations of carbon-specific processes so that adequate responses to climate variability and a proper degree of coupling between carbon and water exchanges are captured.
The ecosystems of the Tibetan Plateau (TP) provide multiple important ecosystem services that benefit both local populations and those beyond, such as through climate regulation services on precipitation for East Asia and China. However, the precipitation regulation service of the TP ecosystems for supplying moisture and maintaining precipitation is yet to be evaluated. In this study, we used the moisture recycling framework and a moisture tracking model to quantify the precipitation regulation services of TP ecosystems for their contribution to precipitation. We found TP ecosystems contributed substantially to local and downwind precipitation, with a declined contribution from 221 mm/year for the TP and neighboring areas, to <10 mm/year for eastern China and other surrounding countries. Among ecosystem types, grassland contributed most to precipitation, followed by barren and snow lands, forests, and shrublands. In terms of seasonality, precipitation contribution from TP ecosystems was greater in summer months than in non-summer months for western China, while the opposite was true for eastern China – though the magnitude was much smaller. Over the past two decades, the significant evapotranspiration increases in TP translated to a widespread increase in precipitation contribution for TP and downwind beneficiary regions from 2000 to 2020. Our study provides a quantitative way to understand the precipitation regulation services of TP ecosystems through moisture recycling, substantiating their key role to safeguard precipitation and the water cycle for downwind regions– effectively acting as an ecological security shelter that could be perceived by the public.
Synopsis Classic debates in community ecology focused on the complexities of considering an ecosystem as a super-organ or organism. New consideration of such perspectives could clarify mechanisms underlying the dynamics of forest carbon dioxide (CO2) uptake and water vapor loss, important for predicting and managing the future of Earth’s ecosystems and climate system. Here, we provide a rubric for considering ecosystem traits as aggregated, systemic, or emergent, i.e., representing the ecosystem as an aggregate of its individuals or as a metaphorical or literal super-organ or organism. We review recent approaches to scaling-up plant water relations (hydraulics) concepts developed for organs and organisms to enable and interpret measurements at ecosystem-level. We focus on three community-scale versions of water relations traits that have potential to provide mechanistic insight into climate change responses of forest CO2 and H2O gas exchange and productivity: leaf water potential (Ψcanopy), pressure volume curves (eco-PV), and hydraulic conductance (Keco). These analyses can reveal additional ecosystem-scale parameters analogous to those typically quantified for leaves or plants (e.g., wilting point and hydraulic vulnerability) that may act as thresholds in forest responses to drought, including growth cessation, mortality, and flammability. We unite these concepts in a novel framework to predict Ψcanopy and its approaching of critical thresholds during drought, using measurements of Keco and eco-PV curves. We thus delineate how the extension of water relations concepts from organ- and organism-scales can reveal the hydraulic constraints on the interaction of vegetation and climate and provide new mechanistic understanding and prediction of forest water use and productivity.
Biodiversity-ecosystem functioning (BEF) research rose quickly following concerns that biodiversity loss would negatively affect ecosystem functions and the ecosystem services they underpin. However, despite evidence that biodiversity strongly affects ecosystem functioning, the influence of BEF research upon policy and the management of ‘real-world’ ecosystems, i.e., semi-natural habitats and agroecosystems, has been limited. In this work, we address this concern by classifying BEF research into three clusters based on the degree of human control over species composition and the spatial scale, in terms of grain, of the study, and discussing how the research of each cluster is best suited to inform particular fields of ecosystem management. Research in the first cluster, small-grain highly controlled studies, is best able to provide general insights into mechanisms and to inform the management of species-poor and highly managed systems such as croplands, plantations, and the restoration of heavily degraded ecosystems. Research from the second cluster, small-grain observational studies, and species removal and addition studies, may allow for direct predictions of the impacts of species loss in specific semi-natural ecosystems. Research in the third cluster, large-grain uncontrolled studies, may best inform landscape-scale management and national-scale policy. We discuss barriers to transfer within each cluster and suggest how new research and knowledge exchange mechanisms may overcome these challenges. To meet the potential for BEF research to address global challenges, we recommend transdisciplinary research that goes beyond these current clusters and considers the social-ecological context of the ecosystems in which BEF knowledge is generated. This requires recognizing the social and economic value of biodiversity for ecosystem services at scales, and in units, that matter to land managers and policy makers.
Croplands are extremely productive ecosystems that contribute to land–atmosphere exchange of carbon, energy, and water during their short growing seasons. We evaluated and compared net ecosystem exchange (NEE), latent heat flux (LE), and sensible heat flux (H) simulated by a suite of ecosystem models at five agricultural eddy covariance flux tower sites in the central United States as part of the North American Carbon Program Site Synthesis project. Most of the models overestimated H and underestimated LE during the growing season, leading to overall higher Bowen ratios compared to the observations. Most models systematically under predicted NEE, especially at rain-fed sites. Certain crop-specific models that were developed considering the high productivity and associated physiological changes in specific crops better predicted the NEE and LE at both rain-fed and irrigated sites. Models with specific parameterization for different crops better simulated the inter-annual variability of NEE for maize-soybean rotation compared to those models with a single generic crop type. Stratification according to basic model formulation and phenological methodology did not explain significant variation in model performance across these sites and crops. The under prediction of NEE and LE and over prediction of H by most of the models suggests that models developed and parameterized for natural ecosystems cannot accurately predict the more robust physiology of highly bred and intensively managed crop ecosystems. When coupled in Earth System Models, it is likely that the excessive physiological stress simulated in many land surface component models leads to overestimation of temperature and atmospheric boundary layer depth, and underestimation of humidity and CO 2 seasonal uptake over agricultural regions.
The net ecosystem exchange (NEE) is the difference between ecosystem CO2 assimilation and CO2 losses to the atmosphere. Ecosystem respiration (Reco), the efflux of CO2 from the ecosystem to the atmosphere, includes the soil-to-atmosphere carbon flux (i.e., soil respiration; Rsoil) and aboveground plant respiration. Therefore, Rsoil is a fraction of Reco and by definition has to be smaller than Reco at annual, seasonal and daily scales. However, several studies estimating Reco with the eddy covariance technique and measuring Rsoil within the footprint of the tower have reported higher Rsoil than Reco at different time scales. Here, we compare four different and contrasting ecosystems (from forest to grasslands, and from boreal to semiarid) to study whether, and under what conditions, measurements of Reco are lower than Rsoil. In general, both fluxes showed similar temporal patterns, but Reco was not consistently higher than Rsoil from daily to annual scales across sites. We identified several issues that apply for measuring NEE and measuring/upscaling Rsoil that could result in an underestimation of Reco and/or an overestimation of Rsoil. These issues are discussed based on (a) nighttime measurements of NEE, (b) Rsoil measurements, and (c) the interpretation of the functional relationships of these fluxes with temperature (i.e., Q10). We highlight that there is still a need for better integration of Rsoil with eddy covariance measurements to address challenges related to spatial and temporal variability of Reco and Rsoil.
Understanding ecosystem responses to compound disturbance regimes and the influence of specific sequences of events in determining ecosystem shifts remains a challenge. We use a modelling framework for Mediterranean-type ecosystems to assess the effects of fire–drought interactions on long-term vegetation dynamics and to identify disturbance-driven changes in trait composition (tree seeder vs. tree resprouter prevalence) and ecosystem state (forest vs. non-forest). Changes in tree seeder and the tree resprouter dominance show nonlinear, threshold-type trends over gradients of increasing compound disturbance frequency. Vegetation composition thresholds mostly occur in a narrow range of the compound fire–drought disturbance space. Additionally, trait compositional switches and the likelihood of sudden changes in ecosystem state are promoted by fire-drought interactions. Distinct sequences of disturbance events cause vegetation transitions, disrupting ecosystem resilience, even under moderate recurrence of individual disturbances. An extreme drought year followed by one or two large fire events promotes shifts from resprouter- to seeder dominance. Contrastingly, a large crown fire followed by an extreme drought promotes changes from seeder to resprouter dominance. This disturbance sequence is also a mechanism strong enough to trigger sudden shifts in ecosystem state (from forest to non-forest). Synthesis. Thresholds of change in vegetation composition occur over a narrow range of the modelled gradients of compound fire-drought recurrence, and the loss of ecosystem resilience is contingent on particular sequences of disturbance events. Overall, our findings highlight that disturbance interactions define the relative location of tipping points in ecosystem state, and that effects and feedbacks of compound disturbance regimes increase the long-term likelihood of sudden ecosystem shifts and, therefore, uncertainty in predicting vegetation state.
Century-old forests in the U.S. upper Midwest and Northeast power much of North Amer- ica’s terrestrial carbon (C) sink, but these forests’ production and C sequestration capacity are expected to soon decline as fast-growing early successional species die and are replaced by slower growing late successional species. But will this really happen? Here we marshal empirical data and ecological theory to argue that substantial declines in net ecosystem production (NEP) owing to reduced forest growth, or net primary production (NPP), are not imminent in regrown temperate deciduous forests over the next several decades. Forest age and production data for temperate deciduous forests, synthesized from published literature, suggest slight declines in NEP and increasing or stable NPP during middle successional stages. We revisit long-held hypotheses by EP Odum and others that suggest low-severity, high-frequency disturbances occurring in the region’s aging forests will, against intuition, maintain NEP at higher-than- expected rates by increasing ecosystem complexity, sustaining or enhancing NPP to a level that largely o sets rising C losses as heterotrophic respiration increases. This theoretical model is also supported by biological evidence and observations from the Forest Accelerated Succession Experiment in Michigan, USA. Ecosystems that experience high-severity disturbances that simplify ecosystem complexity can exhibit substantial declines in production during middle stages of succession. However, observations from these ecosystems have exerted a disproportionate in uence on assumptions regarding the trajectory and magnitude of age-related declines in forest production. We conclude that there is a wide ecological space for forests to maintain NPP and, in doing so, lessens the declines in NEP, with signi cant implications for the future of the North American carbon sink. Our intellectual frameworks for understanding forest C cycle dynamics and resilience need to catch up to our more complex and nuanced understanding of ecological succession.
As the lifetime of regional flux networks approach twenty years, there is a growing number of papers that have published long term records (5 years or more) of net carbon fluxes between ecosystems and the atmosphere. Unanswered questions from this body of work are: 1) how variable are carbon fluxes on a year to year basis?; 2) what are the biophysical factors that may cause interannual variability and/or temporal trends in carbon fluxes?; and 3) how does the biophysical control on this carbon flux variability differ by climate and ecological spaces? To address these questions, we surveyed published data from 59 sites that reported on five or more years of continuous measurements, yielding 544 site-years of data. We found that the standard deviation of the interannual variability in net ecosystem carbon exchange (162 gC m -2 y -1 ) is large relative to its population mean (-200 gC m -2 y -1 ). Broad-leaved evergreen forests and crops experienced the greatest absolute variability in interannual net carbon exchange (greater than ±300 gC m -2 y -1 ) and boreal evergreen forests and maritime wetlands were among the least variable (less than ±40 gC m -2 y -1 ). A disproportionate fraction of the yearly variability in net ecosystem exchange was associated with biophysical factors that modulated ecosystem photosynthesis rather than ecosystem respiration. Yet, there was appreciable and statistically significant covariance between ecosystem photosynthesis and respiration. Consequently, biophysical conditions that conspired to increase ecosystem photosynthesis to from one year to the next were associated with an increase in ecosystem respiration, and vice versa; on average, the year to year change in respiration was 40% as large as the year to year change in photosynthesis. The analysis also identified sets of ecosystems that are on the verge of switching from being carbon sinks to carbon sources. These include sites in the Arctic tundra, the evergreen forests in the Pacific northwest and some grasslands, where year to year changes in respiration are outpacing those in photosynthesis. While a select set of climatic and ecological factors (e.g. light, rainfall, temperature, phenology) played direct and indirect roles on this variability, their impact differed conditionally, as well as by climate and ecological spaces. For example, rainfall had both positive and negative effects. Deficient rainfall caused a physiological decline in photosynthesis in temperate and semi-arid regions. Too much rain, in the humid tropics, limited photosynthesis by limiting light. In peatlands and tundra, excess precipitation limited ecosystem respiration when it raised the water table to the surface. For deciduous forests, warmer temperatures lengthened the growing season, increasing photosynthesis, but this effect also increased soil respiration. Finally, statistical analysis was performed to evaluate the detection limit of trends; we computed the confidence intervals of trends in multi-year carbon fluxes that need to be resolved to conclude whether the differences are to be attributed to randomness or biophysical forcings. Ongoing studies and reports on interannual variations need to consider the role of the duration of the time series on random errors when quantifying potential trends and extreme events.
1. Precipitation regimes are changing in response to climate change, yet understanding of how forest ecosystems respond to extreme droughts and pluvials remains incomplete. As future precipitation extremes will likely fall outside the range of historical variability, precipitation manipulation experiments (PMEs) are critical to advancing knowledge about potential ecosystem responses. However, few PMEs have been conducted in forests compared to short-statured ecosystems, and forest PMEs have unique design requirements and constraints. Moreover, past forest PMEs have lacked coordination, limiting cross-site comparisons. Here, we review and synthesize approaches, challenges, and opportunities for conducting PMEs in forests, with the goal of guiding design decisions, while maximizing the potential for coordination. 2. We reviewed 63 forest PMEs at 70 sites world-wide. Workshops, meetings, and communications with experimentalists were used to generate and build consensus around approaches for addressing the key challenges and enhancing coordination. 3. Past forest PMEs employed a variety of study designs related to treatment level, replication, plot and infrastructure characteristics, and measurement approaches.Important considerations for establishing new forest PMEs include: selecting appropriate treatment levels to reach ecological thresholds; balancing cost, logistical complexity, and effectiveness in infrastructure design; and preventing unintended water subsidies. Response variables in forest PMEs were organized into three broad tiers reflecting increasing complexity and resource intensiveness, with the first tier representing a recommended core set of common measurements. 4. Differences in site conditions combined with unique research questions of experimentalists necessitate careful adaptation of guidelines for forest PMEs to balance local objectives with coordination among experiments. We advocate adoption of a common framework for coordinating forest PME design to enhance cross-site comparability and advance fundamental knowledge about the response and sensitivity of diverse forest ecosystems to precipitation extremes.
This data archive is in support of the Next-Generation Ecosystem Experiments in the Arctic (NGEE Arctic) publication "Integrating Characteristic Arctic Vegetation in a Land Surface Model Improves Representation of Carbon Dynamics Across a Tundra Landscape", by Murphy et al. (2025a). Murphy et al. (2025a) evaluated whether incorporating observed Arctic vegetation heterogeneity into ELM, the land model of the Department of Energy’s Energy Exascale Earth System Model (E3SM), improved simulations of tundra carbon cycling. The associated model archive can be found at Murphy et al. (2025b). The study focused on the spatial patterns and net landscape-level growing season productivity and carbon uptake. As part of this evaluation, observationally derived maps of average growing season (June–August) net ecosystem exchange (NEE) and gross primary production (GPP) were developed for the same domain. These maps, which form the dataset described here, integrate eddy covariance flux tower, remote sensing, and vegetation community data to provide spatially explicit benchmarks for model evaluation. The maps provide spatially explicit estimates of average growing season NEE and GPP across 13 tundra vegetation communities within the study domain. By combining flux tower observations with Airborne Visible-Infrared Imaging Spectrometer-Next Generation (AVIRIS-NG) hyperspectral imagery and drone-based normalized difference vegetation index (NDVI), these maps capture the heterogeneity of carbon fluxes associated with different Arctic vegetation types. While they represent average seasonal conditions rather than interannual variability, the maps provide a unique dataset for evaluating model performance, comparing vegetation community contributions to landscape-scale carbon cycling, and supporting regional analyses of Arctic carbon dynamics. This data archive contains 5 m resolution maps of vegetation communities, vegetation community average growing season GPP, and vegetation community average growing season NEE (three *.tif files), a User’s Guide (*pdf file), and Table 1 of the User’s Guide displaying vegetation community coverage and average growing season NEE and GPP values (*.csv file).
Abstract Wetlands are critical terrestrial ecosystems in Alaska, covering ~177,000 km 2 , an area greater than all the wetlands in the remainder of the United States. To assess the relative influence of changing climate, atmospheric carbon dioxide (CO 2 ) concentration, and fire regime on carbon balance in wetland ecosystems of Alaska, a modeling framework that incorporates a fire disturbance model and two biogeochemical models was used. Spatially explicit simulations were conducted at 1‐km resolution for the historical period (1950–2009) and future projection period (2010–2099). Simulations estimated that wetland ecosystems of Alaska lost 175 Tg carbon (C) in the historical period. Ecosystem C storage in 2009 was 5,556 Tg, with 89% of the C stored in soils. The estimated loss of C as CO 2 and biogenic methane (CH 4 ) emissions resulted in wetlands of Alaska increasing the greenhouse gas forcing of climate warming. Simulations for the projection period were conducted for six climate change scenarios constructed from two climate models forced under three CO 2 emission scenarios. Ecosystem C storage averaged among climate scenarios increased 3.94 Tg C/yr by 2099, with variability among the simulations ranging from 2.02 to 4.42 Tg C/yr. These increases were driven primarily by increases in net primary production (NPP) that were greater than losses from increased decomposition and fire. The NPP increase was driven by CO 2 fertilization (~5% per 100 parts per million by volume increase) and by increases in air temperature (~1% per °C increase). Increases in air temperature were estimated to be the primary cause for a projected 47.7% mean increase in biogenic CH 4 emissions among the simulations (~15% per °C increase). Ecosystem CO 2 sequestration offset the increase in CH 4 emissions during the 21st century to decrease the greenhouse gas forcing of climate warming. However, beyond 2100, we expect that this forcing will ultimately increase as wetland ecosystems transition from being a sink to a source of atmospheric CO 2 because of (1) decreasing sensitivity of NPP to increasing atmospheric CO 2 , (2) increasing availability of soil C for decomposition as permafrost thaws, and (3) continued positive sensitivity of biogenic CH 4 emissions to increases in soil temperature.
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One of the largest sources of uncertainty in the projected global mean temperature response to anthropogenic carbon (C) emissions is the role of the land surface in contributing to or mediating the rise in atmospheric CO2 [IPCC, 2007]. Development of ecosystem processes in global land surface models (LSMs) is far from complete, with major components such as the nitrogen (N) cycle only recently being implemented in some LSMs [Thornton et al., 2007; Sokolov et al., 2008; Xu-Ri and Prentice, 2008; Fisher et al., 2010]. Inclusion of the N cycle can reduce terrestrial C uptake by up to ~50 Pg C·y-1 globally [Figure 1: Fisher et al., 2010]. However, even these early representations of the N cycle in LSMs are missing critical plant–soil interactions that have been shown empirically to exert a major influence over ecosystem C fluxes. Here we propose to use a newly developed plant N model by PI Fisher as a theoretical and analytical framework for integrating novel field-based methods and long-term flux observations to quantify the impacts of belowground processes on fluxes of C, water and energy, from ecosystem to regional scales. Although the model (Fixation & Uptake of Nitrogen: FUN) is one of the more advanced global plant N models available, the model is dependent on theoretical C flux curves optimizing plant C allocation to root exudates, symbiotic bacteria and fungi, and retranslocation enzymes that have not been confirmed or validated with measurements—primarily because the measurement techniques had not been available, until recently. Parallel to the model developments by Fisher et al. were developments in in situ direct measurement techniques by Phillips et al. [2008; 2011], who were able to measure C fluxes from roots to soil. Not only do these techniques have the capacity to confirm and/or modify the modeling components in the Fisher et al. plant N model, but they also provide insight into how belowground C supply from roots couples the C–N cycles at the micro-site and ecosystem scales. Collectively, the integration of measurements and modeling provides empirical grounding for theoretical process behavior. Three critical components will enable us to successfully carry out this research: I) new methodological approaches developed by co-I Phillips for in situ measurement of root exudates, and belowground C fluxes that allow for testing and refinement of FUN [Phillips et al., 2008; Phillips et al., 2011]; II) an innovative research design that involves data integration across an ecological gradient, including a DOE-supported AmeriFlux tower operated by co-I Dragoni, which is essential to determining the ecosystem flux impacts [Dragoni et al., 2011]; and, III) new results from co-I Evans showing unique spectral signatures of trees in association with ectomycorrhizae (ECM) and arbuscular mycorrhizae (AM) fungi from Landsat data using spectral mixture analysis (SMA), which is key to scaling up belowground processes to regional scales [Andersson et al., 2009]. Each component provides feedback to and is intimately linked with all other components; no part operates in isolation. Our team and approach combines expertise in modeling, remote sensing, ecosystem ecology, plant physiology, soil biogeochemistry, and micrometeorology to address these inherently interdisciplinary problems and questions. This proposal directly responds to the focused Science Area of the FOA: “The role of belowground processes and mechanisms across scales (e.g., soil carbon transformation, root dynamics, mycorrhizal interactions, and plant mediated (e.g., root exudates) biogeochemical transformations) associated with a changing climate.
Extreme climatic events, such as droughts and heat stress, induce anomalies in ecosystem–atmosphere CO 2 fluxes, such as gross primary production (GPP) and ecosystem respiration (R eco ), and, hence, can change the net ecosystem carbon balance. However, despite our increasing understanding of the underlying mechanisms, the magnitudes of the impacts of different types of extremes on GPP and R eco within and between ecosystems remain poorly predicted. Here we aim to identify the major factors controlling the amplitude of extreme-event impacts on GPP, R eco , and the resulting net ecosystem production (NEP). We focus on the impacts of heat and drought and their combination. We identified hydrometeorological extreme events in consistently downscaled water availability and temperature measurements over a 30-year time period. We then used FLUXNET eddy covariance flux measurements to estimate the CO 2 flux anomalies during these extreme events across dominant vegetation types and climate zones. Overall, our results indicate that short-term heat extremes increased respiration more strongly than they downregulated GPP, resulting in a moderate reduction in the ecosystem's carbon sink potential. In the absence of heat stress, droughts tended to have smaller and similarly dampening effects on both GPP and R eco and, hence, often resulted in neutral NEP responses. The combination of drought and heat typically led to a strong decrease in GPP, whereas heat and drought impacts on respiration partially offset each other. Taken together, compound heat and drought events led to the strongest C sink reduction compared to any single-factor extreme. A key insight of this paper, however, is that duration matters most: for heat stress during droughts, the magnitude of impacts systematically increased with duration, whereas under heat stress without drought, the response of R eco over time turned from an initial increase to a downregulation after about 2 weeks. This confirms earlier theories that not only the magnitude but also the duration of an extreme event determines its impact. Our study corroborates the results of several local site-level case studies but as a novelty generalizes these findings on the global scale. Specifically, we find that the different response functions of the two antipodal land–atmosphere fluxes GPP and R eco can also result in increasing NEP during certain extreme conditions. Apparently counterintuitive findings of this kind bear great potential for scrutinizing the mechanisms implemented in state-of-the-art terrestrial biosphere models and provide a benchmark for future model development and testing.