Spatial and temporal variability in the net primary production of grassland in China and its relation to climate factors

Plant Ecology ◽  
2017 ◽  
Vol 218 (9) ◽  
pp. 1117-1133 ◽  
Author(s):  
Meiling Zhang ◽  
Rattan Lal ◽  
Youyi Zhao ◽  
Wenlan Jiang ◽  
Quangong Chen
Keyword(s):  
Primary Production ◽  
Temporal Variability ◽  
Net Primary Production ◽  
Spatial And Temporal Variability ◽  
Climate Factors

scholarly journals Spatio-Temporal Variability of Phytoplankton Primary Production in Baltic Lakes Using Sentinel-3 OLCI Data

2020 ◽  
Vol 12 (15) ◽  
pp. 2415
Author(s):  
Tuuli Soomets ◽  
Kristi Uudeberg ◽  
Kersti Kangro ◽  
Dainis Jakovels ◽  
Agris Brauns ◽  
...  
Keyword(s):  
Primary Production ◽  
Temporal Variability ◽  
Carbon Fixation ◽  
Remote Sensing Data ◽  
Spatial And Temporal Variation ◽  
Spatial And Temporal Variability ◽  
Phytoplankton Primary Production ◽  
Spatio Temporal ◽  
Lake Size

Phytoplankton primary production (PP) in lakes play an important role in the global carbon cycle. However, monitoring the PP in lakes with traditional complicated and costly in situ sampling methods are impossible due to the large number of lakes worldwide (estimated to be 117 million lakes). In this study, bio-optical modelling and remote sensing data (Sentinel-3 Ocean and Land Colour Instrument) was combined to investigate the spatial and temporal variation of PP in four Baltic lakes during 2018. The model used has three input parameters: concentration of chlorophyll-a, the diffuse attenuation coefficient, and incident downwelling irradiance. The largest of our studied lakes, Võrtsjärv (270 km2), had the highest total yearly estimated production (61 Gg C y−1) compared to the smaller lakes Lubans (18 Gg C y−1) and Razna (7 Gg C y−1). However, the most productive was the smallest studied, Lake Burtnieks (40.2 km2); although the total yearly production was 13 Gg C y−1, the daily average areal production was 910 mg C m−2 d−1 in 2018. Even if lake size plays a significant role in the total PP of the lake, the abundance of small and medium-sized lakes would sum up to a significant contribution of carbon fixation. Our method is applicable to larger regions to monitor the spatial and temporal variability of lake PP.

scholarly journals Net Primary Production Changes over Korea and Climate Factors

2011 ◽  
Vol 27 (4) ◽  
pp. 467-480 ◽  
Author(s):  
Ji-Youn Hong ◽  
Chang-Sub Shim ◽  
Moung-Jin Lee ◽  
Gyoung-Hye Baek ◽  
Won-Kyong Song ◽  
...  
Keyword(s):  
Primary Production ◽  
Net Primary Production ◽  
Climate Factors

scholarly journals Monitoring Spatial and Temporal Variabilities of Gross Primary Production Using MAIAC MODIS Data

2019 ◽  
Vol 11 (7) ◽  
pp. 874 ◽  
Author(s):  
Marcos Fernández-Martínez ◽  
Rong Yu ◽  
John Gamon ◽  
Gabriel Hmimina ◽  
Iolanda Filella ◽  
...  
Keyword(s):  
Time Series ◽  
Primary Production ◽  
Interannual Variability ◽  
Temporal Variability ◽  
Gross Primary Production ◽  
Vegetation Indices ◽  
Spatial And Temporal Variability ◽  
Data Set ◽  
Broad Leaved Forest ◽  
Leaved Forest

Remotely sensed vegetation indices (RSVIs) can be used to efficiently estimate terrestrial primary productivity across space and time. Terrestrial productivity, however, has many facets (e.g., spatial and temporal variability, including seasonality, interannual variability, and trends), and different vegetation indices may not be equally good at predicting them. Their accuracy in monitoring productivity has been mostly tested in single-ecosystem studies, but their performance in different ecosystems distributed over large areas still needs to be fully explored. To fill this gap, we identified the facets of terrestrial gross primary production (GPP) that could be monitored using RSVIs. We compared the temporal and spatial patterns of four vegetation indices (NDVI, EVI, NIRV, and CCI), derived from the MODIS MAIAC data set and of GPP derived from data from 58 eddy-flux towers in eight ecosystems with different plant functional types (evergreen needle-leaved forest, evergreen broad-leaved forest, deciduous broad-leaved forest, mixed forest, open shrubland, grassland, cropland, and wetland) distributed throughout Europe, covering Mediterranean, temperate, and boreal regions. The RSVIs monitored temporal variability well in most of the ecosystem types, with grasslands and evergreen broad-leaved forests most strongly and weakly correlated with weekly and monthly RSVI data, respectively. The performance of the RSVIs monitoring temporal variability decreased sharply, however, when the seasonal component of the time series was removed, suggesting that the seasonal cycles of both the GPP and RSVI time series were the dominant drivers of their relationships. Removing winter values from the analyses did not affect the results. NDVI and CCI identified the spatial variability of average annual GPP, and all RSVIs identified GPP seasonality well. The RSVI estimates, however, could not estimate the interannual variability of GPP across sites or monitor the trends of GPP. Overall, our results indicate that RSVIs are suitable to track different facets of GPP variability at the local scale, therefore they are reliable sources of GPP monitoring at larger geographical scales.

scholarly journals Temporal variability of the NPP-GPP ratio at seasonal and interannual time scales in a temperate beech forest

2011 ◽  
Vol 8 (9) ◽  
pp. 2481-2492 ◽  
Author(s):  
M. Campioli ◽  
B. Gielen ◽  
M. Göckede ◽  
D. Papale ◽  
O. Bouriaud ◽  
...  
Keyword(s):  
Primary Production ◽  
Interannual Variability ◽  
Temporal Variability ◽  
Current Knowledge ◽  
Net Primary Production ◽  
Gross Primary Production ◽  
Tree Canopy ◽  
Data Uncertainty ◽  
Severe Drought ◽  
Beech Stand

Abstract. The allocation of carbon (C) taken up by the tree canopy for respiration and production of tree organs with different construction and maintenance costs, life span and decomposition rate, crucially affects the residence time of C in forests and their C cycling rate. The carbon-use efficiency, or ratio between net primary production (NPP) and gross primary production (GPP), represents a convenient way to analyse the C allocation at the stand level. In this study, we extend the current knowledge on the NPP-GPP ratio in forests by assessing the temporal variability of the NPP-GPP ratio at interannual (for 8 years) and seasonal (for 1 year) scales for a young temperate beech stand, reporting dynamics for both leaves and woody organs, in particular stems. NPP was determined with biometric methods/litter traps, whereas the GPP was estimated via the eddy covariance micrometeorological technique. The interannual variability of the proportion of C allocated to leaf NPP, wood NPP and leaf plus wood NPP (on average 11% yr−1, 29% yr−1 and 39% yr−1, respectively) was significant among years with up to 12% yr−1 variation in NPP-GPP ratio. Studies focusing on the comparison of NPP-GPP ratio among forests and models using fixed allocation schemes should take into account the possibility of such relevant interannual variability. Multiple linear regressions indicated that the NPP-GPP ratio of leaves and wood significantly correlated with environmental conditions. Previous year drought and air temperature explained about half of the NPP-GPP variability of leaves and wood, respectively, whereas the NPP-GPP ratio was not decreased by severe drought, with large NPP-GPP ratio on 2003 due mainly to low GPP. During the period between early May and mid June, the majority of GPP was allocated to leaf and stem NPP, whereas these sinks were of little importance later on. Improved estimation of seasonal GPP and of the contribution of previous-year reserves to stem growth, as well as reduction of data uncertainty, will be of relevance to increase the accuracy of the seasonal assessment of the NPP-GPP ratio in forests.

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