Interannual Variation In Gross Primary Production Research Articles

Interannual variations in GPP in forest ecosystems in Southwest China and regional differences in the climatic contributions

Forest ecosystem plays an important role as carbon sinks in Southwest China. Currently, remote sensing technology has been widely used to substantially model the high temporal and spatial variation in gross primary production (GPP) at a site or regional scale. However, during the growing season, the regional uncertainty of GPP in the forest ecosystem and the relative contributions of climate variations to interannual variation (IAV) of GPP are not well understood across Southwest China. Our research focuses on the joint analysis of the three-cornered hat (TCH) algorithm and uses the contribution index to analyse the model's uncertainties varying with plant functional types (PFTs), climate zones, and the contribution of climate variabilities to GPP IAV. Here, three GPP datasets are used to investigate how climate variabilities contribute to the GPP IAV during the growing season. The uncertainties in GPP vary from 829.33 g C m−2 year−1 to 2031.86 g C m−2 year−1 for different models in different climate zones and different PFTs. Additionally, the results highlight that precipitation dominates the interannual variation in GPP in forest ecosystem during the growing season in Southwest China. It makes the largest contribution (34.46%) to the IAV of GPP in the climate zone of E (cold subtropical highland area) and the largest contribution (80.83%) to PFTs of the MF (mixed forest). Our study suggests the availability and applicability of GPP products can be used to assess GPP uncertainties and analyse the contributions of climate factors to GPP IAV in forest ecosystem or other ecosystems.

Can vegetation index track the interannual variation in gross primary production of temperate deciduous forests?

BackgroundVegetation indices (VIs) by remote sensing are widely used as simple proxies of the gross primary production (GPP) of vegetation, but their performances in capturing the inter-annual variation (IAV) in GPP remain uncertain.MethodsWe evaluated the performances of various VIs in tracking the IAV in GPP estimated by eddy covariance in a temperate deciduous forest of Northeast China. The VIs assessed included the normalized difference vegetation index (NDVI), the enhanced vegetation index (EVI), and the near-infrared reflectance of vegetation (NIRv) obtained from tower-radiometers (broadband) and the Moderate Resolution Imaging Spectroradiometer (MODIS), respectively.ResultsWe found that 25%–35% amplitude of the broadband EVI tracked the start of growing season derived by GPP (R2: 0.56–0.60, bias < 4 d), while 45% (or 50%) amplitudes of broadband (or MODIS) NDVI represented the end of growing season estimated by GPP (R2: 0.58–0.67, bias < 3 d). However, all the VIs failed to characterize the summer peaks of GPP. The growing-season integrals but not averaged values of the broadband NDVI, MODIS NIRv and EVI were robust surrogates of the IAV in GPP (R2: 0.40–0.67).ConclusionThese findings illustrate that specific VIs are effective only to capture the GPP phenology but not the GPP peak, while the integral VIs have the potential to mirror the IAV in GPP.

Quantifying Impacts of Land-Use/Cover Change on Urban Vegetation Gross Primary Production: A Case Study of Wuhan, China

This study quantified the impacts of land-use/cover change (LUCC) on gross primary production (GPP) during 2000–2013 in a typical densely urbanized Chinese city, Wuhan. GPP was estimated at 30-m spatial resolution using annual land cover maps, meteorological data of the baseline year, and the normalized difference vegetation index (NDVI), which was generated with the spatial and temporal adaptive reflectance fusion model (STARFM) based on Landsat and MODIS images. The results showed that approximately 309.95 Gg C was lost over 13 years, which was mainly due to the conversion from cropland to built-up areas. The interannual variation of GPP was affected by the change of vegetation composition, especially the increasing relative fraction of forests. The loss of GPP due to the conversion from forest to cropland fluctuated through the study period, but showed a sharp decrease in 2007 and 2008. The gain of GPP due to the conversion from cropland to forest was low between 2001 and 2009, but increased dramatically between 2009 and 2013. The change rate map showed an increasing trend along the highways, and a decreasing trend around the metropolitan area and lakes. The results indicated that carbon consequences should be considered before land management policies are put forth.

Global patterns of extreme drought-induced loss in land primary production: Identifying ecological extremes from rain-use efficiency

Quantifying the ecological patterns of loss of ecosystem function in extreme drought is important to understand the carbon exchange between the land and atmosphere. Rain-use efficiency [RUE; gross primary production (GPP)/precipitation] acts as a typical indicator of ecosystem function. In this study, a novel method based on maximum rain-use efficiency (RUEmax) was developed to detect losses of ecosystem function globally. Three global GPP datasets from the MODIS remote sensing data (MOD17), ground upscaling FLUXNET observations (MPI-BGC), and process-based model simulations (BESS), and a global gridded precipitation product (CRU) were used to develop annual global RUE datasets for 2001–2011. Large, well-known extreme drought events were detected, e.g. 2003 drought in Europe, 2002 and 2011 drought in the U.S., and 2010 drought in Russia. Our results show that extreme drought-induced loss of ecosystem function could impact 0.9% ± 0.1% of earth's vegetated land per year and was mainly distributed in semi-arid regions. The reduced carbon uptake caused by functional loss (0.14 ± 0.03 PgC/yr) could explain >70% of the interannual variation in GPP in drought-affected areas (p ≤ 0.001). Our results highlight the impact of ecosystem function loss in semi-arid regions with increasing precipitation variability and dry land expansion expected in the future.

Seasonal and interannual variations of carbon exchange over a rice-wheat rotation system on the North China Plain

Rice–wheat (R–W) rotation systems are ubiquitous in South and East Asia, and play an important role in modulating the carbon cycle and climate. Long-term, continuous flux measurements help in better understanding the seasonal and interannual variation of the carbon budget over R–W rotation systems. In this study, measurements of CO2 fluxes and meteorological variables over an R–W rotation system on the North China Plain from 2007 to 2010 were analyzed. To analyze the abiotic factors regulating Net Ecosystem Exchange (NEE), NEE was partitioned into gross primary production (GPP) and ecosystem respiration. Nighttime NEE or ecosystem respiration was controlled primarily by soil temperature, while daytime NEE was mainly determined by photosythetically active radiation (PAR). The responses of nighttime NEE to soil temperature and daytime NEE to light were closely associated with crop development and photosynthetic activity, respectively. Moreover, the interannual variation in GPP and NEE mainly depended on precipitation and PAR. Overall, NEE was negative on the annual scale and the rotation system behaved as a carbon sink of 982 g C m-2 per year over the three years. The winter wheat field took up more CO2 than the rice paddy during the longer growing season, while the daily NEE for wheat and rice were -2.35 and -3.96 g C m-2, respectively. After the grain harvest was subtracted from the NEE, the winter wheat field became a moderately strong carbon sink of 251–334 g C m-2 per season, whereas the rice paddy switched to a weak carbon sink of 107–132 per season.

Retrieval and assessment of CO2 uptake by mediterranean ecosystems using remote sensing and

Retrieval and assessment of CO2 uptake by mediterranean ecosystems using remote sensing and

Modeling Carbon Fluxes Using Multi-Temporal MODIS Imagery and CO2 Eddy Flux Tower Data in Zoige Alpine Wetland, South-West China

An accurate and synoptic quantification of gross primary production (GPP) in wetland ecosystems is essential for assessing carbon budgets at regional or global scales. In this study, a satellite-based Vegetation Photosynthesis Model (VPM) integrated with observed eddy tower and remote sens- ing data was employed and adapted to evaluate the feasibility and dependability of the model for estimating GPP in an alpine wetland, located in Zoige, Southwestern China. Eddy flux data from 2-year observations showed that temperature explained mostof theseasonal variability incarbonfluxesand that warming increased GPP and ecosystem respiration, and hence affected the carbon balance of alpine wetlands. The comparison between modeled and observed GPP fluxes indi- cated that simulated values were largely in agreement with tower-based values (P<0.0001). 12-year long-term simula- tions (2000-2011) found that (1) there was significantly in- creasing trends at rate of 17.01 gCm �2 year �1 for annual GPP (R 2 =0.62, P=0.002); (2) the inter-annual variation in GPP was highly sensitive to climate warming; and (3) a warmer climate can prolong the plant growing season and, by that, increase wetland productivity. Our results demonstrated that the satellite-driven VPM model has the potential to be applied at large spatial and temporal scales for scaling-up carbon fluxes of alpine wetlands.

A few extreme events dominate global interannual variability in gross primary production

Understanding the impacts of climate extremes on the carbon cycle is important for quantifying the carbon-cycle climate feedback and highly relevant to climate change assessments. Climate extremes and fires can have severe regional effects, but a spatially explicit global impact assessment is still lacking. Here, we directly quantify spatiotemporal contiguous extreme anomalies in four global data sets of gross primary production (GPP) over the last 30 years. We find that positive and negative GPP extremes occurring on 7% of the spatiotemporal domain explain 78% of the global interannual variation in GPP and a significant fraction of variation in the net carbon flux. The largest thousand negative GPP extremes during 1982–2011 (4.3% of the data) account for a decrease in photosynthetic carbon uptake of about 3.5 Pg C yr−1, with most events being attributable to water scarcity. The results imply that it is essential to understand the nature and causes of extremes to understand current and future GPP variability.

Modeling gross primary production of irrigated and rain-fed maize using MODIS imagery and CO2 flux tower data

Information on gross primary production (GPP) of maize croplands is needed for assessing and monitoring maize crop conditions and the carbon cycle. A number of studies have used the eddy covariance technique to measure net ecosystem exchange (NEE) of CO2 between maize cropland fields and the atmosphere and partitioned NEE data to estimate seasonal dynamics and interannual variation of GPP in maize fields having various crop rotation systems and different water management practices. How to scale up in situ observations from flux tower sites to regional and global scales is a challenging task. In this study, the Vegetation Photosynthesis Model (VPM) and satellite images from the Moderate Resolution Imaging Spectroradiometer (MODIS) are used to estimate seasonal dynamics and interannual variation of GPP during 2001–2005 at five maize cropland sites located in Nebraska and Minnesota of the U.S.A. These sites have different crop rotation systems (continuously maize vs. maize and soybean rotated annually) and different water management practices (irrigation vs. rain-fed). The VPM is based on the concept of light absorption by chlorophyll and is driven by the Enhanced Vegetation Index (EVI) and the Land Surface Water Index (LSWI), photosynthetically active radiation (PAR), and air temperature. The seasonal dynamics of GPP predicted by the VPM agreed well with GPP estimates from eddy covariance flux tower data over the period of 2001–2005. These simulation results clearly demonstrate the potential of the VPM to scale-up GPP estimation of maize cropland, which is relevant to food, biofuel, and feedstock production, as well as food and energy security.

Multi-year model analysis of GPP in a temperate beech forest in France

In this paper gross primary production (GPP) predicted by FORUG is compared with GPP calculated from eddy covariance measurements for a beech forest in France (Hesse). Two photosynthesis formulations at leaf level are compared: the biochemically supported approach described by Farquhar et al. [Farquhar, G.D., Von Caemmerer, S., Berry, J.A., 1980. A biochemical model of photosynthetic CO 2 assimilation in leaves of C3 species. Planta 12B, 549–587] (BCF) and an empirical light response curve (LRC). Five consecutive years (1996–2000) of measured GPP are compared with FORUG model predictions. Results did not discriminate between both model formulations, but good agreement between modelled and measured GPP support the reliability of FORUG for both photosynthesis approaches. Although some discrepancies appeared, the parameterization combining literature and fitted parameters can be considered as a useful strategy. Residuals were analysed to find explanations for discrepancies between model predictions and data. The increase in residuals over the years, indicate that interannual variability of GPP is not only determined by direct climatic effects. Due to interfering long-term effects, a combination of several climatic factors (drought, temperature), acclimation, environmental and management impacts account for the interannual variation in GPP. However, the long-term effect of drought appeared to be the most important driver of the interannual variability in GPP. Taking into account these long-term climate effects will be an essential step in development of better performing ecosystem models.

Climatic versus biotic constraints on carbon and water fluxes in seasonally drought‐affected ponderosa pine ecosystems

We investigated the relative importance of climatic versus biotic controls on gross primary production (GPP) and water vapor fluxes in seasonally drought‐affected ponderosa pine forests. The study was conducted in young (YS), mature (MS), and old stands (OS) over 4 years at the AmeriFlux Metolius sites. Model simulations showed that interannual variation of GPP did not follow the same trends as precipitation, and effects of climatic variation were smallest at the OS (&lt;10%), largest at the MS (&gt;50%), and intermediate at the YS (&lt;20%). In the young, developing stand, interannual variation in leaf area has larger effects on fluxes than climate, although leaf area is a function of climate in that climate can interact with age‐related shifts in carbon allocation and affect whole‐tree hydraulic conductance. Older forests, with well‐established root systems, appear to be better buffered from effects of seasonal drought and interannual climatic variation. Interannual variation of net ecosystem exchange (NEE) was also lowest at the OS, where NEE is controlled more by interannual variation of ecosystem respiration, 70% of which is from soil, than by the variation of GPP, whereas variation in GPP is the primary reason for interannual changes in NEE at the YS and MS. Across spatially heterogeneous landscapes with high frequency of younger stands resulting from natural and anthropogenic disturbances, interannual climatic variation and change in leaf area are likely to result in large interannual variation in GPP and NEE.