Eddy covariance flux towers measure net exchange of land–atmosphere flux. For the flux of carbon dioxide, this net ecosystem exchange (NEE) is governed by two processes, gross primary production ...(GPP) and a sum of autotrophic and heterotrophic respiration components known as ecosystem respiration (RE). A number of statistical flux-partitioning methods, often developed to fill missing NEE data, can also be used to estimate GPP and RE from NEE time series. Here we present results of the first comprehensive, multi-site comparison of these partitioning methods. An initial test was performed with a subset of methods in retrieving GPP and RE from NEE generated by an ecosystem model, which was also degraded with realistic noise. All methods produced GPP and RE estimates that were highly correlated with the synthetic data at the daily and annual timescales, but most were biased low, including a parameter inversion of the original model. We then applied 23 different methods to 10 site years of temperate forest flux data, including 10 different artificial gap scenarios (10% removal of observations), in order to investigate the effects of partitioning method choice, data gaps, and intersite variability on estimated GPP and RE. Most methods differed by less than 10% in estimates of both GPP and RE. Gaps added an additional 6–7% variability, but did not result in additional bias. ANOVA showed that most methods were consistent in identifying differences in GPP and RE across sites, leading to increased confidence in previously published multi-site comparisons and syntheses. Several methods produced outliers at some sites, and some methods were systematically biased against the ensemble mean. Larger model spread was found for Mediterranean sites compared to temperate or boreal sites. For both real and synthetic data, high variability was found in modeling of the diurnal RE cycle, suggesting that additional study of diurnal RE mechanisms could help to improve partitioning algorithms.
This book evaluates current applications of traditional phenology in carbon and H2O cycle research, as well as the potential to identify phenological signals in ecosystem processes themselves. Case ...studies and literature reviews will complement classroom use.
The southeastern United States hosts extensive forested wetlands, providing ecosystem services including carbon sequestration, water quality improvement, groundwater recharge, and wildlife habitat. ...However, these wetland ecosystems are dependent on local climate and hydrology, and are therefore at risk due to climate and land use change. This study develops site-specific empirical hydrologic models for five forested wetlands with different characteristics by analyzing long-term observed meteorological and hydrological data. These wetlands represent typical cypress ponds/swamps, Carolina bays, pine flatwoods, drained pocosins, and natural bottomland hardwood ecosystems. The validated empirical models are then applied at each wetland to predict future water table changes using climate projections from 20 general circulation models (GCMs) participating in Coupled Model Inter-comparison Project 5 (CMIP5) under the Representative Concentration Pathways (RCPs) 4.5 and 8.5 scenarios. We show that combined future changes in precipitation and potential evapotranspiration would significantly alter wetland hydrology including groundwater dynamics by the end of the 21st century. Compared to the historical period, all five wetlands are predicted to become drier over time. The mean water table depth is predicted to drop by 4 to 22 cm in response to the decrease in water availability (i.e., precipitation minus potential evapotranspiration) by the year 2100. Among the five examined wetlands, the depressional wetland in hot and humid Florida appears to be most vulnerable to future climate change. This study provides quantitative information on the potential magnitude of wetland hydrological response to future climate change in typical forested wetlands in the southeastern US.
Changes in species composition and diversity are the inevitable consequences of climate change, as well as land use and land cover change. Predicting species richness at regional spatial scales using ...remotely sensed biophysical variables has emerged as a viable mechanism for monitoring species distribution. In this study, we evaluate the utility of MODIS-based productivity (GPP and EVI) and surface water content (NDSVI and LSWI) in predicting species richness in the semi-arid region of Inner Mongolia, China. We found that these metrics correlated well with plant species richness and could be used in biome- and life form-specific models. The relationships were evaluated on the basis of county-level data recorded from the Flora of Inner Mongolia, stratified by administrative (i.e., counties), biome boundaries (desert, grassland, and forest), and grouped by life forms (trees, grasses, bulbs, annuals and shrubs). The predictor variables included: the annual, mean, maximum, seasonal midpoint (EVImid), standard deviation of MODIS-derived GPP, EVI, LSWI and NDSVI. The regional pattern of species richness correlated with GPPSD (R2=0.27), which was also the best predictor for bulbs, perennial herbs and shrubs (R2=0.36, 0.29 and 0.40, respectively). The predictive power of models improved when counties with >50% of cropland were excluded from the analysis, where the seasonal dynamics of productivity and species richness deviate patterns in natural systems. When stratified by biome, GPPSD remained the best predictor of species richness in grasslands (R2=0.30), whereas the most variability was explained by NDSVImax in forests (R2=0.26), and LSWIavg in deserts (R2=0.61). The results demonstrated that biophysical estimates of productivity and water content can be used to predict plant species richness at the regional and biome levels.
Over the years, a series of trembling aspen (Populus tremuloides Michx.) clones differing in O sub(3) sensitivity have been identified from OTC studies. Three clones (216 and 271(O sub(3) tolerant ...and 259 O sub(3) sensitive) have been characterized for O sub(3) sensitivity by growth and biomass responses, foliar symptoms, gas exchange, chlorophyll content, epicuticular wax characteristics, and antioxidant production. In this study we compared the responses of these same clones exposed to O sub(3) under field conditions along a natural O sub(3) gradient and in a Free-Air CO sub(2) and O sub(3) Enrichment (FACE) facility. In addition, we examined how elevated CO sub(2) affected O sub(3) symptom development. Visible O sub(3) symptoms were consistently seen (5 out of 6 years) at two of the three sites along the O sub(3) gradient and where daily one-hour maximum concentrations were in the range of 96 to 125 ppb. Clonal differences in O sub(3) sensitivity were consistent with our OTC rankings. Elevated CO sub(2) (200 ppm over ambient and applied during daylight hours during the growing season) reduced visible foliar symptoms for all three clones from 31 to 96% as determined by symptom development in elevated O sub(3) versus elevated O sub(3) + CO sub(2) treatments. Degradation of the epicuticular wax surface of all three clones was found at the two elevated O sub(3) gradient sites. This degradation was quantified by a coefficient of occlusion which was a measure of stomatal occlusion by epicuticular waxes. Statistically significant increases in stomatal occlusion compared to controls were found for all three clones and for all treatments including elevated CO sub(2), elevated O sub(3), and elevated CO sub(2) + O sub(3). Our results provide additional evidence that current ambient O sub(3) levels in the Great Lakes region are causing adverse effects on trembling aspen. Whether or not elevated CO sub(2) in the future will alleviate some of these adverse effects, as occurred with visible symptoms but not with epicuticular wax degradation, is unknown.
One year of continuous data from two eddy-flux towers established along an elevation gradient in coastal Shanghai was analyzed to evaluate the tidal effect on carbon flux (
F
c) over an estuarine ...wetland. The measured wavelet spectra and cospectra of
F
c and other environmental factors demonstrated that the dynamics of
F
c at both sites exhibited a tidal-driven pattern with obvious characteristics at scales between 10 and 20 days (256–512-h). Environmental factors exerted major controls on the carbon balance at finer temporal scales.
F
c was more sensitive to tides at the low-elevation site than at the high-elevation site. Overall, the mean nighttime
F
c during spring tides was lower than that during neap tides, indicating suppressed ecosystem respiration under inundation. Larger differences were observed at the low-elevation site due to longer inundation durations. In contrast, daytime
F
c was more variable since plants reacted differently in different growth periods and under different tidal elevations. The amplitudes of diurnal
F
c during tidal periods were larger than those reported for other wetland types, implying a great potential for future carbon sequestration. Whilst tides would also transport organic matter to nearby estuaries and hence may incur carbon emission in the receiving ecosystems. Thus, further study on lateral carbon transport is required to investigate the tidal effect on the carbon sink/source role of the wetland.
Predicting how forest carbon cycling will change in response to climate change and management depends on the collective knowledge from measurements across environmental gradients, ecosystem ...manipulations of global change factors, and mathematical models. Formally integrating these sources of knowledge through data assimilation, or model–data fusion, allows the use of past observations to constrain model parameters and estimate prediction uncertainty. Data assimilation (DA) focused on the regional scale has the opportunity to integrate data from both environmental gradients and experimental studies to constrain model parameters. Here, we introduce a hierarchical Bayesian DA approach (Data Assimilation to Predict Productivity for Ecosystems and Regions, DAPPER) that uses observations of carbon stocks, carbon fluxes, water fluxes, and vegetation dynamics from loblolly pine plantation ecosystems across the southeastern US to constrain parameters in a modified version of the Physiological Principles Predicting Growth (3-PG) forest growth model. The observations included major experiments that manipulated atmospheric carbon dioxide (CO2) concentration, water, and nutrients, along with nonexperimental surveys that spanned environmental gradients across an 8.6 × 105 km2 region. We optimized regionally representative posterior distributions for model parameters, which dependably predicted data from plots withheld from the data assimilation. While the mean bias in predictions of nutrient fertilization experiments, irrigation experiments, and CO2 enrichment experiments was low, future work needs to focus modifications to model structures that decrease the bias in predictions of drought experiments. Predictions of how growth responded to elevated CO2 strongly depended on whether ecosystem experiments were assimilated and whether the assimilated field plots in the CO2 study were allowed to have different mortality parameters than the other field plots in the region. We present predictions of stem biomass productivity under elevated CO2, decreased precipitation, and increased nutrient availability that include estimates of uncertainty for the southeastern US. Overall, we (1) demonstrated how three decades of research in southeastern US planted pine forests can be used to develop DA techniques that use multiple locations, multiple data streams, and multiple ecosystem experiment types to optimize parameters and (2) developed a tool for the development of future predictions of forest productivity for natural resource managers that leverage a rich dataset of integrated ecosystem observations across a region.
Eddy covariance flux towers provide continuous measurements of net ecosystem carbon exchange (NEE) for a wide range of climate and biome types. However, these measurements only represent the carbon ...fluxes at the scale of the tower footprint. To quantify the net exchange of carbon dioxide between the terrestrial biosphere and the atmosphere for regions or continents, flux tower measurements need to be extrapolated to these large areas. Here we used remotely sensed data from the Moderate Resolution Imaging Spectrometer (MODIS) instrument on board the National Aeronautics and Space Administration's (NASA) Terra satellite to scale up AmeriFlux NEE measurements to the continental scale. We first combined MODIS and AmeriFlux data for representative U.S. ecosystems to develop a predictive NEE model using a modified regression tree approach. The predictive model was trained and validated using eddy flux NEE data over the periods 2000–2004 and 2005–2006, respectively. We found that the model predicted NEE well (
r
=
0.73,
p
<
0.001). We then applied the model to the continental scale and estimated NEE for each 1
km
×
1
km cell across the conterminous U.S. for each 8-day interval in 2005 using spatially explicit MODIS data. The model generally captured the expected spatial and seasonal patterns of NEE as determined from measurements and the literature. Our study demonstrated that our empirical approach is effective for scaling up eddy flux NEE measurements to the continental scale and producing wall-to-wall NEE estimates across multiple biomes. Our estimates may provide an independent dataset from simulations with biogeochemical models and inverse modeling approaches for examining the spatiotemporal patterns of NEE and constraining terrestrial carbon budgets over large areas.
Leaf nitrogen distribution pattern was studied four times during the growing season in a 2-year-old Salix viminalis L. and Salix dasyclados Wimm. plantation in Estonia. We measured the vertical ...distributions of leaf nitrogen concentration, dry mass, leaf area and light environment (as fractional transmission of diffuse irradiance, a(d)) in the canopy. The light-independent nitrogen pool was evaluated as the intercept of the leaf nitrogen concentration versus a(d) relationship, and the nondegradable nitrogen pool was evaluated as the nitrogen remaining in abscised leaves. A strong vertical gradient of mass-based leaf nitrogen concentration was detected at the beginning of the growing season, and decreased steadily during canopy development. This decline had at least three causes: (1) the amount of nitrogen in the foliage was larger at the beginning of the growing season than at the end of the growing season, probably because of pre-existing root systems; (2) with increasing leaf area index (LAI) during the growing season, the proportion of leaf nitrogen in total canopy nitrogen that could be redistributed (light-dependent nitrogen pool) decreased; and (3) the photosynthetic photon flux density gradient inside the canopy changed during the season, most probably because of changes in leaf area and leaf angle distributions. Total canopy nitrogen increased almost proportionally to LAI, whereas the light-dependent nitrogen pool had a maximum in August. Also, the proportion of the light-dependent nitrogen pool in the total canopy nitrogen decreased steadily from 65.2% in June to 17.2% in September in S. dasyclados and from 63.3 to 15.1% in S. viminalis. The degradable nitrogen pool was always bigger than the light-dependent nitrogen pool.
Poplar plantation is the most dominant broadleaf forest type in northern China. Since the mid-1990s plantation was intensified to combat desertification along China's northwestern border, i.e., ...within Inner Mongolia (IM). This evoked much concern regarding the ecological and environmental effects on areas that naturally grow grass or shrub vegetation. To highlight potential consequences of large-scale poplar plantations on the water budget within semiarid IM, we compared the growing season water balance (evapotranspiration (ET) and precipitation (PPT)) of a 3-yr old poplar plantation (Kp
3) and a natural shrubland (Ks) in the Kubuqi Desert in western IM, and a 6-yr old poplar plantation (Bp
6) growing under sub-humid climate near Beijing. The results showed that, despite 33% lower PPT at Kp
3, ET was 2% higher at Kp
3 (228
mm) as compared with Ks (223
mm) in May–September 2006. The difference derived mainly from higher ET at the plantation during drier periods of the growing season, which also indicated that the poplars must have partly transpired groundwater. Estimated growing season ET at Bp
6 was about 550
mm and more than 100% higher than at Kp
3. It is estimated that increases in leaf area index and net radiation at Kp
3 provide future potential for the poplars in Kubuqi to exceed the present ET and ET of the natural shrubland by 100–200%. These increases in ET are only possible through the permanent use of groundwater either directly by the trees or through increased irrigation. This may significantly change the water balance in the area (e.g., high ET at the cost of a reduction in the water table), which renders large-scale plantations a questionable tool in sustainable arid-land management.
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