Seasonal Variation In Gross Primary Production Research Articles

Gross primary productivity of Brazilian Savanna (Cerrado) estimated by different remote sensing-based models

Gross primary production (GPP) is the total amount of fixed carbon and depends on vegetation health and water and energy availability. GPP has been monitored worldwide by flux towers and models that are coupled with remotely sensed data, such as by Moderate Resolution Imaging Spectroradiometer (MODIS). However, models have not been evaluated for tropical savanna, which presumably represent a challenge because of large spatial and seasonal variation in GPP. Thus, our goal was to evaluate the Vegetation Photosynthesis Model (VPM), Temperature and Greenness Model (TG), Vegetation Index Model (VI), and the MOD17A2 product of MODIS in a tropical mixed woodland-grassland. The Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Land Surface Water Index (LSWI), Land Surface Temperature (LST) and Photosynthetically Active Radiation Fraction (fPAR) derived from the MODIS sensor were used as model inputs and integrated with ground-based micrometeorological variables. GPP varied significantly between the wet and dry seasons and was positively correlated with seasonal variations in soil volumetric water content (VSWC) and precipitation, and negatively correlated with the vapor pressure deficit (VPD). Satellite vegetation indices (NDVI, LSWI, and to a lesser extent, the EVI) and derived quantities (fPAR and LUE) also exhibited similar correlations with VSWC and precipitation. Thus, there were strong positive correlations between the SVIs and GPP. All of the models were able to simulate the seasonal variations in GPP; however, VPM had the best performance with the highest correlation and smallest errors. TG, VI, and MOD17A2 models performed similarly, except for the VI model based only on the EVI. Given their ability to capture seasonal dynamics, remote-sensing based models, such as those tested here, will likely be an important tool for assessing how climate variability alters C cycling dynamics in these spatially and temporally heterogeneous landscapes.

SIFSpec: Measuring Solar-Induced Chlorophyll Fluorescence Observations for Remote Sensing of Photosynthesis.

Solar-induced chlorophyll fluorescence (SIF) is regarded as a proxy for photosynthesis in terrestrial vegetation. Tower-based long-term observations of SIF are very important for gaining further insight into the ecosystem-specific seasonal dynamics of photosynthetic activity, including gross primary production (GPP). Here, we present the design and operation of the tower-based automated SIF measurement (SIFSpec) system. This system was developed with the aim of obtaining synchronous SIF observations and flux measurements across different terrestrial ecosystems, as well as to validate the increasing number of satellite SIF products using in situ measurements. Details of the system components, instrument installation, calibration, data collection, and processing are introduced. Atmospheric correction is also included in the data processing chain, which is important, but usually ignored for tower-based SIF measurements. Continuous measurements made across two growing cycles over maize at a Daman (DM) flux site (in Gansu province, China) demonstrate the reliable performance of SIF as an indicator for tracking the diurnal variations in photosynthetically active radiation (PAR) and seasonal variations in GPP. For the O2–A band in particular, a high correlation coefficient value of 0.81 is found between the SIF and seasonal variations of GPP. It is thus concluded that, in coordination with continuous eddy covariance (EC) flux measurements, automated and continuous SIF observations can provide a reliable approach for understanding the photosynthetic activity of the terrestrial ecosystem, and are also able to bridge the link between ground-based optical measurements and airborne or satellite remote sensing data.

MODELLING GROSS PRIMARY PRODUCTION OF TROPICAL FOREST BY REMOTE SENSING

The application of remote sensing has provided an opportunity to improve the estimation of gross primary production (GPP) on a regional scale. Several models to estimate GPP of homogeneous ecosystems, such as agricultural areas, entirely based on remote sensing data exist, but models to describe more heterogeneous areas are less common. Thus, the aim of the study was to evaluate the GPP estimated by different remote sensing methods in an Amazon-Cerrado transition forest in Mato Grosso, using MODIS spectral data. Two models, known as the temperature and greenness model (TG) and the vegetation index (VI) model, were used to estimate seasonal and interannual variations in GPP. Our results indicated that the TG and VI models were incapable of reproducing the seasonal variation in GPP, because the lack of correlation between vegetation indices and the GPP measured from tower-based eddy covariance (GPP EC ). Furthermore, the time series of the enhanced vegetation index (EVI) was delayed by 2 months with GPP EC . The results presented in this paper highlight some of the complexities in validating satellite products. Further study over a variety of Brazilian forests is needed to quantitatively assess the TG and VI and other methods to improve their accuracy.

Multiple effects of a Gracilaria vermiculophylla invasion on estuarine mudflat functioning and diversity

The invasive Japanese seaweed Gracilaria vermiculophylla has become established over the past several years in numerous European estuaries, from Portugal to Norway. In the Faou estuary (48.295°N-4.179°W, Brittany, France), it forms a dense population at the mud's surface. The effects of G. vermiculophylla on metabolism, diversity, and the food web were studied. Community gross primary production (GPP) and respiration (CR) during emersion, chlorophyll-a content, macrofaunal and meiofaunal diversity and abundance, and stable isotopes (δ13C and δ15N) of representative macrofaunal species and main food sources were measured at low tide in winter, spring, summer 2014, and winter 2015. Results show significant seasonal variation in GPP and CR. Moreover, GPP was significantly higher in areas where G. vermiculophylla was present than in the control area (bare mud). However, this high GPP appeared to be linked to the increase in biomass in primary producers, with their efficiency (primary productivity, i.e. assimilation number) remaining relatively stable compared with the control area. Significant variation in abundance of meiofauna and macrofauna was also detected and new epifaunal species were collected, mainly in Gracilaria-colonized areas. Isotopic food-web Bayesian mixing models strongly suggested that G. vermiculophylla plays a major role in the diet of some dominant species. Mechanisms interacting with the functioning and diversity of the mudflat are discussed. Finally, the invasive seaweed G. vermiculophylla affected the mudflat ecosystem in three ways: as a new primary producer (increase in metabolism), as a habitat-forming species (changes in diversity and abundance of macrofauna and meiofauna), and as a new abundant food source, likely through the detrital pathway.

Simulating the net ecosystem CO2 exchange and its components over winter wheat cultivation sites across a large climate gradient in Europe using the ORCHIDEE-STICS generic model

Over the last decade, efforts have been carried on to develop and evaluate versions of global terrestrial ecosystem models (GTEM) in which crop specificities are represented. The goal of this study is to evaluate the ability of the ORCHIDEE-STICS (Organising Carbon and Hydrology In Dynamic EcosystEms—Simulateur mulTIdisciplinaire pour les Cultures Standard) GTEM in simulating the observed seasonal variations and annual budgets of net ecosystem exchange (NEE), gross primary production (GPP) and total ecosystem respiration (TER) fluxes over seven wheat sites spanning a large climate gradient in Europe. Overall, the seasonal variations of GPP are well represented by the model, with 5 sites out of 7 exhibiting a correlation coefficient (R) value higher than 0.9 and a normalized standard deviation (NSTD) between 0.8 and 1.2. In comparison, the model performances for catching the seasonal variations of TER are lower, especially in terms of NSTD. Regarding the annual budgets, mean simulated deviations averaged over all sites do not exceed 10% and 15% of the observed annual mean budget, for GPP and TER, respectively. For NEE, the model capacity at estimating annual budgets is low, its mean deviation corresponding to ∼35% of the observed mean value. This clearly shows that more accurate model estimates of GPP and especially TER are required for estimating NEE annual budgets. In this respect, past land-use and land-management changes are probably the most crucial processes to add, for getting soil carbon disequilibrium and more accurate NEE annual budgets.From a sensitivity analysis of the modelled fluxes to three management practices (plant variety, sowing date and fertilization intensity), we found that the fertilization is the most sensitive practice impacting the model performances of any flux, both in terms of seasonal variations and annual budgets.

The influence of riparian vegetation and season on stream metabolism of Valley Creek, Minnesota

Climate change will undoubtedly influence stream ecosystems by affecting water temperature, discharge, and riparian vegetation phenology. It has been suggested that increasing the extent of riparian buffers may help to mitigate these impacts and contribute to ecosystem resilience. Measures of stream metabolism are one way to examine the changes in ecosystem function as they respond to climate change and management strategies used to respond to these impacts. In this study we examine the influence of riparian vegetation (open vs. forest) and season on ecosystem metabolism in a small stream in MN, USA. The stream was heterotrophic regardless of the type of riparian vegetation but the presence of a forested buffer depressed gross primary production (GPP) and also resulted in lower (less negative) ecosystem respiration (ER) and net ecosystem production (NEP). We also found significant daily and seasonal variation in GPP, ER, and NEP. Stream metabolism was more variable in the fall than in the summer. The study design was complicated by the fact that there were differences in groundwater dynamics between the two locations; the forested location was a losing stream while the open location was a gaining stream. Despite the fact that groundwater input likely influenced the oxygen dynamics of the open location, the impact of the forest buffer outweighed the impact of groundwater. The presence of a forested riparian corridor resulted in decreased GPP likely through the attenuation of light. The low O2 groundwater input at the open location likely biased measures of ER and NEP. Modifying stream corridors with increased forest vegetation to offset the impacts of climate change will likely result in less in-stream primary production and a shift to a more heterotrophic system. This shift will undoubtedly influence many ecosystem functions in-stream systems.

Seasonal and inter-annual variations in carbon fluxes and evapotranspiration over cotton field under drip irrigation with plastic mulch in an arid region of Northwest China

Xinjiang is the largest semi-arid and arid region in China, and drip irrigation under plastic mulch is widely used in this water-limited area. Quantifying carbon and water fluxes as well as investigating their environmental drivers over cotton fields is critical for understanding regional carbon and water budgets in Xinjiang, the largest cotton production basin of China. In this study, an eddy covariance (EC) technique was used to measure the carbon and water fluxes of cotton field under drip irrigation with plastic mulch in the growing seasons of 2009, 2010, 2012 and 2013 at Wulanwusu Agrometeorological Experiment Station, a representative oasis cropland in northern Xinjiang. The diurnal patterns of gross primary production (GPP), net ecosystem exchange (NEE) and evapotranspiration (ET) showed obviously sinusoidal variations from June to September, while the diurnal ecosystem respiration (Res) was stable between daytime and nighttime. The daytime hourly GPP and ET displayed asymptotic relationships with net solar radiation (Rnet), while showed concave patterns with raising vapor pressure deficit (VPD) and air temperature (Ta). The increases in hourly GPP and ET towards the maximum occurred over half ranges of VPD and Ta. The seasonal variations of GPP, NEE and ET were close to the cotton phenology, which almost reached the peak value in July. The cumulative GPP averaged 816.2±55.0 g C/m2 in the growing season (from April to October), and more than half of GPP was partitioned into NEE (mean value of −478.6±41.4 g C/m2). The mean seasonal ET was 501.3±13.9 mm, and the mean water use efficiency (WUE) was 1.0±0.1 (mg C/g H2O)/d. The agro-ecosystem behaved as a carbon sink from squaring to harvest period, while it acted as a carbon source before the squaring time as well as after the harvest time.

Modelling gross primary production of a tropical semi-deciduous forest in the southern Amazon Basin

Semi-deciduous forest in the Amazon Basin is sensitive to temporal variation in surface water availability that can limit seasonal rates of leaf and canopy gas exchange. We estimated the seasonal dynamics of gross primary production (GPP) over 3 years (2005–2008) using eddy covariance and assessed canopy spectral reflectance using MODIS imagery for a mature tropical semi-deciduous forest located near Sinop, Mato Grosso, Brazil. A light-use efficiency model, known as the Vegetation Photosynthesis Model (VPM), was used to estimate seasonal and inter-annual variations in GPP as a function of the enhanced vegetation index (EVI), the land surface water index (LSWI), and local meteorology. Our results indicate that the standard VPM was incapable of reproducing the seasonal variation in GPP, primarily because the model overestimated dry-season GPP. In the standard model, the scalar function that alters light-use efficiency (εg) as a function of water availability (Wscalar) is calculated as a linear function of the LSWI derived from MODIS; however, the LSWI is negatively correlated with several measures of water availability including precipitation, soil water content, and relative humidity (RH). Thus, during the dry season, when rainfall, soil water content, and RH are low, LSWI, and therefore, Wscalar, are at a seasonal maximum. Using previous research, we derived new functions for Wscalar based on time series of RH and photosynthetic photon flux density (PPFD) that significantly improved the performance of the VPM. Whether these new functions perform equally well in water stressed and unstressed tropical forests needs to be determined, but presumably unstressed ecosystems would have high cloud cover and humidity, which would minimize variations in Wscalar and GPP to spatial and/or temporal variation in water availability.

Seasonal and interannual variation in net ecosystem production of an evergreen needleleaf forest in Japan

Carbon dioxide (CO2) flux was measured above the forest at the Fujiyoshida site on the northern slope of Mount Fuji in Japan in 2000–2008 using an eddy covariance technique. The forest mainly consists of Japanese red pine (Pinus densiflora) and Japanese holly (Ilex pedunculosa). The 9-year average of monthly mean net ecosystem production (NEP) ranged from −0.1…−2 day−1 in January to 2.5…−2 day−1 in May. The maximum net uptake was observed in May, although gross primary production (GPP) was highest in July. Variation in the leaf amount did not notably affect seasonal variation in GPP. This site was characterized by carbon uptake even in winter, if the meteorological conditions were conducive for photosynthesis and a resulting long period of carbon uptake. The 9-year averages of annual NEP, GPP, and ecosystem respiration (RE) were 388, 1,802, and 1,413…−2 year−1, respectively. The annual NEP was lowest in 2003 and highest in 2004 over the 9 years. Year-to-year variability of NEP mainly depended on air temperature and photosynthetically active radiation in summer, and the dependence of the deviation of annual NEP on that of GPP was greater than that of RE. Long-term observational data indicated that the carbon uptake ability at the study site was at a moderate level in comparison with other temperate humid evergreen forests around the world. These data also indicated that the site had a high carbon uptake ability compared with other deciduous forests in Japan because of the duration of carbon uptake.

Carbon sequestration potential of tropical pasture compared with afforestation in Panama

AbstractTropical forest ecosystems play an important role in regulating the global climate, yet deforestation and land‐use change mean that the tropical carbon sink is increasingly influenced by agroecosystems and pastures. Despite this, it is not yet fully understood how carbon cycling in the tropics responds to land‐use change, particularly for pasture and afforestation. Thus, the objectives of our study were: (1) to elucidate the environmental controls and the impact of management on gross primary production (GPP), total ecosystem respiration (TER) and net ecosystem CO2 exchange (NEE); (2) to estimate the carbon sequestration potential of tropical pasture compared with afforestation; and (3) to compare eddy covariance‐derived carbon budgets with biomass and soil inventory data. We performed comparative measurements of NEE in a tropical C4 pasture and an adjacent afforestation with native tree species in Sardinilla (Panama) from 2007 to 2009. Pronounced seasonal variation in GPP, TER and NEE were closely related to radiation, soil moisture, and C3 vs. C4 plant physiology. The shallow rooting depth of grasses compared with trees resulted in a higher sensitivity of the pasture ecosystem to water limitation and seasonal drought. During 2008, substantial amounts of carbon were sequestered by the afforestation (–442 g C m–2, negative values denote ecosystem carbon uptake), which was in agreement with biometric observations (–450 g C m–2). In contrast, the pasture ecosystem was a strong carbon source in 2008 and 2009 (261 g C m–2), associated with seasonal drought and overgrazing. In addition, soil carbon isotope data indicated rapid carbon turnover after conversion from C4 pasture to C3 afforestation. Our results clearly show the potential for considerable carbon sequestration of tropical afforestation and highlight the risk of carbon losses from pasture ecosystems in a seasonal tropical climate.

Comparison of multiple models for estimating gross primary production using MODIS and eddy covariance data in Harvard Forest

Gross primary production (GPP) defined as the overall rate of fixation of carbon through the process of vegetation photosynthesis is important for carbon cycle and climate change research. Three models, the Vegetation Photosynthesis Model (VPM), the Temperature and Greenness (TG) model and the Vegetation Index (VI) model have been compared for the estimation of GPP in Harvard Forest from 2003 to 2006 using climate variables acquired by eddy covariance (EC) measurements and Moderate Resolution Imaging Spectroradiometer (MODIS) satellite images. All these models provide more reliable estimates of GPP than that of MODIS GPP product. High Pearsons correlation coefficients r equal to 0.94, 0.92 and 0.90 are observed for the VPM, the TG and the VI model, respectively. Relationships between GPP and land surface temperature (LST, R 2 = 0.72), and vapor pressure deficit (VPD, R 2 = 0.45) indicate that climate variables are important for GPP estimation. Due to proper characterization of temperature, water stress and leaf age by three scalars, VPM best follows the seasonal variations of GPP. By incorporation of the MODIS surface reflectance and LST product, the TG model is the most suitable choice for areas without prior knowledge as it is based entirely on remote sensing observations. Results from the VI model demonstrate the possibility of using a single vegetation index for light use efficiency (LUE) estimation in deciduous forest that is of high spatial heterogeneity. The validation and comparison of models will be helpful in development of future GPP models using combinations of climate variables and/or remote sensing observations.

CO 2 fluxes in adjacent new and permanent temperate grasslands

Carbon dioxide (CO 2) fluxes and grass production were measured in adjacent new and permanent intensively managed, Lolium perenne grasslands. Cumulative grass production during 2004 was 0.38 and 0.70 kg C m −2 year −1 in the new and permanent sites, respectively. Chamber measurements were used to create site-specific statistical response functions of gross primary production (GPP) and total respiration ( R TOT) at the two sites. A 1-year time series of GPP and R TOT was reconstructed by combining these functions with measurements of leaf area index (LAI) and continuous meteorological data. Net ecosystem exchange (NEE) was estimated by subtracting R TOT from GPP. Seasonal variation in GPP closely followed the changes in grass production and LAI. R TOT increased in summertime due to increased soil temperature and optimal soil moisture conditions. Both sites were net CO 2 sinks during the grass growing season. Cumulative values of GPP, R TOT and NEE in the new grassland were 2.14, −1.98 and 0.15 kg C m −2 year −1, respectively. In the permanent grassland cumulative values of GPP, R TOT and NEE were 2.90, −2.52 and 0.38 kg C m −2 year −1, respectively.