A global network of long‐term carbon and water flux measurements has existed since the late 1990s. With its representative sampling of the terrestrial biosphere's climate and ecological spaces, this ...network is providing background information and direct measurements on how ecosystem metabolism responds to environmental and biological forcings and how they may be changing in a warmer world with more carbon dioxide. In this review, I explore how carbon and water fluxes of the world's ecosystem are responding to a suite of covarying environmental factors, like sunlight, temperature, soil moisture, and carbon dioxide. I also report on how coupled carbon and water fluxes are modulated by biological and ecological factors such as phenology and a suite of structural and functional properties. And, I investigate whether long‐term trends in carbon and water fluxes are emerging in various ecological and climate spaces and the degree to which they may be driven by physical and biological forcings. As a growing number of time series extend up to 20 years in duration, we are at the verge of capturing ecosystem scale trends in the breathing of a changing biosphere. Consequently, flux measurements need to continue to report on future conditions and responses and assess the efficacy of natural climate solutions.
I explore how carbon and water fluxes of the world's ecosystem are responding to a suite of covarying environmental factors, like sunlight, temperature, soil moisture, and carbon dioxide. I also report on how coupled carbon and water fluxes are modulated by biological and ecological factors such as phenology and a suite of structural and functional properties. And, I investigate whether long‐term trends in carbon and water fluxes are emerging in various ecological and climate spaces and the degree to which they may be driven by physical and biological forcings.
Quantifying global terrestrial photosynthesis is essential to understanding the global carbon cycle and the climate system. Remote sensing has played a pivotal role in advancing our understanding of ...photosynthesis from leaf to global scale; however, substantial uncertainties still exist. In this review, we provide a historical overview of theory, modeling, and observations of photosynthesis across space and time for decadal intervals beginning in the 1950s. Then we identify the key uncertainties in global photosynthesis estimates, including evaluating light intercepted by canopies, biophysical forcings, the structure of light use efficiency models and their parameters, like photosynthetic capacity, and relationships between sun-induced chlorophyll fluorescence and canopy photosynthesis. Finally, we review new opportunities with big data and recently launched or planned satellite missions.
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•Reviewed history of global photosynthesis since 1950s•Reviewed uncertainties in remote sensing of global photosynthesis•Reviewed emerging opportunities with recent and new satellite missions
•Interannual variability in net carbon exchange is large relative to its mean.•Many biophysical variables explain this variability, and differ by region.•Ecosystem photosynthesis modulated net carbon ...exchange more than respiration.•A few ecosystems are on the verge of switching from a carbon sink to sources.
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 (162gCm−2y−1) is large relative to its population mean (−200gCm−2 y−1). Broad-leaved evergreen forests and crops experienced the greatest absolute variability in interannual net carbon exchange (greater than ±300gCm−2y−1) and boreal evergreen forests and maritime wetlands were among the least variable (less than ±40 gCm−2y−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. Future 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.
A common approach for estimating fluxes of CO2 and water in canopy models is to couple a model of photosynthesis (An) to a semi‐empirical model of stomatal conductance (gs) such as the widely ...validated and utilized Ball–Berry (BB) model. This coupling provides an effective way of predicting transpiration at multiple scales. However, the designated value of the slope parameter (m) in the BB model impacts transpiration estimates. There is a lack of consensus regarding how m varies among species or plant functional types (PFTs) or in response to growth conditions. Literature values are highly variable, with inter‐species and intra‐species variations of >100%, and comparisons are made more difficult because of differences in collection techniques. This paper reviews the various methods used to estimate m and highlights how variations in measurement techniques or the data utilized can influence the resultant m. Additionally, this review summarizes the reported responses of m to CO2 and water stress, collates literature values by PFT and compiles nearly three decades of values into a useful compendium.
A common approach for estimating fluxes of CO2 and water in leaf and canopy models is to couple a biochemical model of photosynthesis to a semi‐empirical model of stomatal conductance, such as the widely validated Ball–Berry model (e.g. Ball et al. 1987). The designated value of the slope parameter (m) in the Ball–Berry model influences transpiration estimates, but there is a lack of consensus regarding how m varies among species or plant functional types (PFTs) or in response to growth conditions, and literature values are highly variable. This review explores the techniques utilized to collect m, discusses factors that can influence estimates and compiles and synthesizes the reported values of m by species, PFT and growth conditions for the Ball–Berry, Ball–Berry–Leuning and unified stomatal optimization models.
Linking plant and ecosystem functional biogeography Reichstein, Markus; Bahn, Michael; Mahecha, Miguel D. ...
Proceedings of the National Academy of Sciences - PNAS,
09/2014, Letnik:
111, Številka:
38
Journal Article
Recenzirano
Odprti dostop
Significance This article defines ecosystem functional properties, which can be derived from long-term observations of gas and energy exchange between ecosystems and the atmosphere, and shows that ...variations of those cannot be easily explained by classical climatological or biogeographical approaches such as plant functional types. Instead, we argue that plant traits have the potential to explain this variation, and we call for a stronger integration of research communities dedicated to plant traits and to ecosystem–atmosphere exchange.
Classical biogeographical observations suggest that ecosystems are strongly shaped by climatic constraints in terms of their structure and function. On the other hand, vegetation function feeds back on the climate system via biosphere–atmosphere exchange of matter and energy. Ecosystem-level observations of this exchange reveal very large functional biogeographical variation of climate-relevant ecosystem functional properties related to carbon and water cycles. This variation is explained insufficiently by climate control and a classical plant functional type classification approach. For example, correlations between seasonal carbon-use efficiency and climate or environmental variables remain below 0.6, leaving almost 70% of variance unexplained. We suggest that a substantial part of this unexplained variation of ecosystem functional properties is related to variations in plant and microbial traits. Therefore, to progress with global functional biogeography, we should seek to understand the link between organismic traits and flux-derived ecosystem properties at ecosystem observation sites and the spatial variation of vegetation traits given geoecological covariates. This understanding can be fostered by synergistic use of both data-driven and theory-driven ecological as well as biophysical approaches.
Accurate estimation of gross primary production (GPP), the amount of carbon absorbed by plants via photosynthesis, is of great importance for understanding ecosystem functions, carbon cycling, and ...climate-carbon feedbacks. Remote sensing has been widely used to quantify GPP at regional to global scales. However, polar-orbiting satellites (e.g., Landsat, Sentinel, Terra, Aqua, Suomi NPP, JPSS, OCO-2) lack the capability to examine the diurnal cycles of GPP because they observe the Earth's surface at the same time of day. The Ecosystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS), launched in June 2018, observes the land surface temperature (LST) at different times of day with high spatial resolution (70 m × 70 m) from the International Space Station (ISS). Here, we made use of ECOSTRESS data to predict instantaneous GPP with high spatial resolution for different times of day using a data-driven approach based on machine learning. The predictive GPP model used instantaneous ECOSTRESS LST observations along with the daily enhanced vegetation index (EVI) from the Moderate Resolution Imaging Spectroradiometer (MODIS), land cover type from the National Land Cover Database (NCLD), and instantaneous meteorological data from the ERA5 reanalysis dataset. Our model estimated instantaneous GPP across 56 flux tower sites fairly well (R2 = 0.88, Root Mean Squared Error (RMSE) = 2.42 μmol CO2 m−2 s−1). The instantaneous GPP estimates driven by ECOSTRESS LST captured the diurnal variations of tower GPP for different biomes. We then produced multiple high resolution ECOSTRESS GPP maps for the central and northern California. We found distinct changes in GPP at different times of day (e.g., higher in late morning, peak around noon, approaching zero at dusk), and clear differences in productivity across landscapes (e.g., savannas, croplands, grasslands, and forests) for different times of day. ECOSTRESS GPP also captured the seasonal variations in the diurnal cycling of photosynthesis. This study demonstrates the feasibility of using ECOSTRESS data for producing instantaneous GPP (i.e., GPP for the acquisition time of the ECOSTRESS data) for different times of day. The ECOSTRESS GPP can shed light on how plant photosynthesis and water use vary over the course of the diurnal cycle and inform agricultural management and future improvement of terrestrial biosphere/land surface models.
•We estimate instantaneous GPP based on ECOSTRESS land surface temperature data.•Our instantaneous ECOSTRESS GPP estimates also have fine spatial resolution (70 m).•ECOSTRESS GPP captures the diurnal variations of tower GPP for different biomes.•Our GPP depicts diurnal variations and spatial patterns of GPP at the regional scale.•ECOSTRESS GPP can help us better understand how plants absorb carbon and use water.
Numerous models of evapotranspiration have been published that range in data-driven complexity, but global estimates require a model that does not depend on intensive field measurements. The ...Priestley–Taylor model is relatively simple, and has proven to be remarkably accurate and theoretically robust for estimates of potential evapotranspiration. Building on recent advances in ecophysiological theory that allow detection of multiple stresses on plant function using biophysical remote sensing metrics, we developed a bio-meteorological approach for translating Priestley–Taylor estimates of potential evapotranspiration into rates of actual evapotranspiration. Five model inputs are required: net radiation (
R
n), normalized difference vegetation index (NDVI), soil adjusted vegetation index (SAVI), maximum air temperature (
T
max), and water vapor pressure (ea). Our model requires no calibration, tuning or spin-ups. The model is tested and validated against eddy covariance measurements (FLUXNET) from a wide range of climates and plant functional types—grassland, crop, and deciduous broadleaf, evergreen broadleaf, and evergreen needleleaf forests. The model-to-measurement
r
2 was 0.90 (RMS
=
16 mm/month or 28%) for all 16 FLUXNET sites across 2 years (most recent data release). Global estimates of evapotranspiration at a temporal resolution of monthly and a spatial resolution of 1° during the years 1986–1993 were determined using globally consistent datasets from the International Satellite Land-Surface Climatology Project, Initiative II (ISLSCP-II) and the Advanced Very High Resolution Spectroradiometer (AVHRR). Our model resulted in improved prediction of evapotranspiration across water-limited sites, and showed spatial and temporal differences in evapotranspiration globally, regionally and latitudinally.
Forest ecosystems across the globe show an increase in ecosystem carbon uptake efficiency under conditions with high fraction of diffuse radiation. Here, we combine eddy covariance flux measurements ...at a deciduous temperate forest in central Germany with canopy‐scale modeling using the biophysical multilayer model CANVEG to investigate the impact of diffuse radiation on various canopy gas exchange processes and to elucidate the underlying mechanisms. Increasing diffuse radiation enhances canopy photosynthesis by redistributing the solar radiation load from light saturated sunlit leaves to nonsaturated shade leaves. Interactions with atmospheric vapor pressure deficit and reduced leaf respiration are only of minor importance to canopy photosynthesis. The response strength of carbon uptake to diffuse radiation depends on canopy characteristics such as leaf area index and leaf optical properties. Our model computations shows that both canopy photosynthesis and transpiration increase initially with diffuse fraction, but decrease after an optimum at a diffuse fraction of 0.45 due to reduction in global radiation. The initial increase in canopy photosynthesis exceeds the increase in transpiration, leading to a rise in water‐use‐efficiency. Our model predicts an increase in carbon isotope discrimination with water‐use‐efficiency resulting from differences in the leaf‐to‐air vapor pressure gradient and atmospheric vapor pressure deficit. This finding is in contrast to those predicted with simple big‐leaf models that do not explicitly calculate leaf energy balance. At an annual scale, we estimate a decrease in annual carbon uptake for a potential increase in diffuse fraction, since diffuse fraction was beyond the optimum for 61% of the data.
The application of the eddy covariance flux method to measure fluxes of trace gas and energy between ecosystems and the atmosphere has exploded over the past 25 years. This opinion paper provides a ...perspective on the contributions and future opportunities of the eddy covariance method. First, the paper discusses the pros and cons of this method relative to other methods used to measure the exchange of trace gases between ecosystems and the atmosphere. Second, it discusses how the use of eddy covariance method has grown and evolved. Today, more than 400 flux measurement sites are operating world‐wide and the duration of the time series exceed a decade at dozens of sites. Networks of tower sites now enable scientists to ask scientific questions related to climatic and ecological gradients, disturbance, changes in land use, and management. The paper ends with discussions on where the field of flux measurement is heading. Topics discussed include role of open access data sharing and data mining, in this new era of big data, and opportunities new sensors that measure a variety of trace gases, like volatile organic carbon compounds, methane and nitrous oxide, and aerosols, may yield.
Agricultural drainage of organic soils has resulted in vast soil subsidence and contributed to increased atmospheric carbon dioxide (CO₂) concentrations. The Sacramento‐San Joaquin Delta in ...California was drained over a century ago for agriculture and human settlement and has since experienced subsidence rates that are among the highest in the world. It is recognized that drained agriculture in the Delta is unsustainable in the long‐term, and to help reverse subsidence and capture carbon (C) there is an interest in restoring drained agricultural land‐use types to flooded conditions. However, flooding may increase methane (CH₄) emissions. We conducted a full year of simultaneous eddy covariance measurements at two conventional drained agricultural peatlands (a pasture and a corn field) and three flooded land‐use types (a rice paddy and two restored wetlands) to assess the impact of drained to flooded land‐use change on CO₂and CH₄fluxes in the Delta. We found that the drained sites were net C and greenhouse gas (GHG) sources, releasing up to 341 g C m⁻² yr⁻¹as CO₂and 11.4 g C m⁻² yr⁻¹as CH₄. Conversely, the restored wetlands were net sinks of atmospheric CO₂, sequestering up to 397 g C m⁻² yr⁻¹. However, they were large sources of CH₄, with emissions ranging from 39 to 53 g C m⁻² yr⁻¹. In terms of the full GHG budget, the restored wetlands could be either GHG sources or sinks. Although the rice paddy was a small atmospheric CO₂sink, when considering harvest and CH₄emissions, it acted as both a C and GHG source. Annual photosynthesis was similar between sites, but flooding at the restored sites inhibited ecosystem respiration, making them net CO₂sinks. This study suggests that converting drained agricultural peat soils to flooded land‐use types can help reduce or reverse soil subsidence and reduce GHG emissions.
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