scholarly journals The allocation of ecosystem net primary productivity in tropical forests

2011 ◽  
Vol 366 (1582) ◽  
pp. 3225-3245 ◽  
Author(s):  
Yadvinder Malhi ◽  
Christopher Doughty ◽  
David Galbraith
Keyword(s):  
Primary Productivity ◽  
Fine Roots ◽  
Net Primary Productivity ◽  
Fine Root ◽  
Terrestrial Ecosystem ◽  
Ecosystem Models ◽  
Woody Tissue ◽  
Trade Off ◽  
The Mean ◽  
Main Components

The allocation of the net primary productivity (NPP) of an ecosystem between canopy, woody tissue and fine roots is an important descriptor of the functioning of that ecosystem, and an important feature to correctly represent in terrestrial ecosystem models. Here, we collate and analyse a global dataset of NPP allocation in tropical forests, and compare this with the representation of NPP allocation in 13 terrestrial ecosystem models. On average, the data suggest an equal partitioning of allocation between all three main components (mean 34 ± 6% canopy, 39 ± 10% wood, 27 ± 11% fine roots), but there is substantial site-to-site variation in allocation to woody tissue versus allocation to fine roots. Allocation to canopy (leaves, flowers and fruit) shows much less variance. The mean allocation of the ecosystem models is close to the mean of the data, but the spread is much greater, with several models reporting allocation partitioning outside of the spread of the data. Where all main components of NPP cannot be measured, litterfall is a good predictor of overall NPP ( r 2 = 0.83 for linear fit forced through origin), stem growth is a moderate predictor and fine root production a poor predictor. Across sites the major component of variation of allocation is a shifting allocation between wood and fine roots, with allocation to the canopy being a relatively invariant component of total NPP. This suggests the dominant allocation trade-off is a ‘fine root versus wood’ trade-off, as opposed to the expected ‘root–shoot’ trade-off; such a trade-off has recently been posited on theoretical grounds for old-growth forest stands. We conclude by discussing the systematic biases in estimates of allocation introduced by missing NPP components, including herbivory, large leaf litter and root exudates production. These biases have a moderate effect on overall carbon allocation estimates, but are smaller than the observed range in allocation values across sites.

scholarly journals Asymmetric responses of primary productivity to altered precipitation simulated by ecosystem models across three long-term grassland sites

2018 ◽  
Vol 15 (11) ◽  
pp. 3421-3437 ◽  
Author(s):  
Donghai Wu ◽  
Philippe Ciais ◽  
Nicolas Viovy ◽  
Alan K. Knapp ◽  
Kevin Wilcox ◽  
...  
Keyword(s):  
Primary Productivity ◽  
Net Primary Productivity ◽  
Precipitation Variability ◽  
Aboveground Net Primary Productivity ◽  
Ecosystem Models ◽  
Rainfall Gradient ◽  
Positive Effects ◽  
Altered Precipitation ◽  
The Mean ◽  
Asymmetric Responses

Abstract. Field measurements of aboveground net primary productivity (ANPP) in temperate grasslands suggest that both positive and negative asymmetric responses to changes in precipitation (P) may occur. Under normal range of precipitation variability, wet years typically result in ANPP gains being larger than ANPP declines in dry years (positive asymmetry), whereas increases in ANPP are lower in magnitude in extreme wet years compared to reductions during extreme drought (negative asymmetry). Whether the current generation of ecosystem models with a coupled carbon–water system in grasslands are capable of simulating these asymmetric ANPP responses is an unresolved question. In this study, we evaluated the simulated responses of temperate grassland primary productivity to scenarios of altered precipitation with 14 ecosystem models at three sites: Shortgrass steppe (SGS), Konza Prairie (KNZ) and Stubai Valley meadow (STU), spanning a rainfall gradient from dry to moist. We found that (1) the spatial slopes derived from modeled primary productivity and precipitation across sites were steeper than the temporal slopes obtained from inter-annual variations, which was consistent with empirical data; (2) the asymmetry of the responses of modeled primary productivity under normal inter-annual precipitation variability differed among models, and the mean of the model ensemble suggested a negative asymmetry across the three sites, which was contrary to empirical evidence based on filed observations; (3) the mean sensitivity of modeled productivity to rainfall suggested greater negative response with reduced precipitation than positive response to an increased precipitation under extreme conditions at the three sites; and (4) gross primary productivity (GPP), net primary productivity (NPP), aboveground NPP (ANPP) and belowground NPP (BNPP) all showed concave-down nonlinear responses to altered precipitation in all the models, but with different curvatures and mean values. Our results indicated that most models overestimate the negative drought effects and/or underestimate the positive effects of increased precipitation on primary productivity under normal climate conditions, highlighting the need for improving eco-hydrological processes in those models in the future.

scholarly journals Research Advances in Net Primary Productivity of Terrestrial Ecosystem

2020 ◽  
Vol 08 (08) ◽  
pp. 48-54
Author(s):  
Yixin Xu ◽  
Xiaoling Hu ◽  
Zhao Liu ◽  
Huayong Zhang
Keyword(s):  
Primary Productivity ◽  
Net Primary Productivity ◽  
Terrestrial Ecosystem

Modeling net primary productivity of the terrestrial ecosystem in China from 1961 to 2005

2013 ◽  
Vol 24 (1) ◽  
pp. 3-17 ◽  
Author(s):  
Quanzhi Yuan ◽  
Shaohong Wu ◽  
Dongsheng Zhao ◽  
Erfu Dai ◽  
Li Chen ◽  
...  
Keyword(s):  
Primary Productivity ◽  
Net Primary Productivity ◽  
Terrestrial Ecosystem

scholarly journals North Sea Ecosystem-Scale Model-Based Quantification of Net Primary Productivity Changes by the Benthic Filter Feeder Mytilus edulis

Water ◽  
2018 ◽  
Vol 10 (11) ◽  
pp. 1527 ◽  
Author(s):  
Carsten Lemmen
Keyword(s):  
Shallow Water ◽  
North Sea ◽  
Primary Productivity ◽  
Net Primary Productivity ◽  
Water Filtration ◽  
Scale Model ◽  
Ecosystem Models ◽  
Blue Mussels ◽  
Filtration Effect ◽  
Filter Feeders

Blue mussels are among the most abundant bivalves in shallow water along the German coasts. As filter feeders, a major ecosystem service they provide is water filtration and the vertical transfer of suspended organic and attached inorganic material to the sea floor. Laboratory and field studies previously demonstrated that blue mussels can remove large quantities of plankton from the surrounding water. I here perform numerical experiments that investigate the effect of filtration at the scale of an entire coastal sea—the southern North Sea. These experiments were performed with a state-of-the-art bentho-pelagic coupled hydrodynamic and ecosystem model and used a novel reconstruction of the benthic biomass distribution of blue mussels. The filtration effect was assessed as the simulated change in net primary productivity caused by blue mussels. In shallow water, filtration takes out up to half of the entire annual primary productivity; it is negligible in offshore waters. For the entire basin, the filtration effect is 10%. While many ecosystem models have a global parameterization for filter feeders, the coastal gradient in the filtration effect is usually not considered; our research demonstrates the importance of including spatially heterogeneous filtration in coupled bentho-pelagic ecosystem models if we want to better understand the spatial patterns in shallow water coastal systems.

scholarly journals Roles of Climate Change and Increasing CO2 in Driving Changes of Net Primary Productivity in China Simulated Using a Dynamic Global Vegetation Model

2019 ◽  
Vol 11 (15) ◽  
pp. 4176 ◽  
Author(s):  
Qing Huang ◽  
Weimin Ju ◽  
Fangyi Zhang ◽  
Qian Zhang
Keyword(s):  
Climate Change ◽  
Interannual Variability ◽  
Primary Productivity ◽  
Southwest China ◽  
Net Primary Productivity ◽  
Terrestrial Ecosystem ◽  
Co2 Concentration ◽  
Series Data ◽  
Geographical Regions ◽  
The Future

Net primary productivity (NPP) is the key component of the terrestrial carbon cycle, and terrestrial NPP trends under increasing CO2 and climate change in the past and future are of great significance in the study of the global carbon budget. Here, the LPJ-DGVM was employed to simulate the magnitude and pattern of China’s terrestrial NPP using long-term series data to understand the response of terrestrial NPP to increasing CO2 concentration and climate change. The results showed that total NPP of China’s terrestrial ecosystem increased from 2.8 to 3.6 Pg C yr−1 over the period of 1961–2016, with an annual average of 3.1 Pg C yr−1. The average NPP showed a gradient decrease from the southeast to northwest. Southwest China and Northwest China, comprising mostly arid and semi-arid regions, exhibited the largest increase rate in total NPP among the six geographical regions of China. Additionally, large interannual variability around the NPP trends was presented, and NPP anomalies in China’s terrestrial ecosystem are strongly associated with the El Niño-Southern Oscillation (ENSO). Southwest China made the largest contribution to the interannual variability of national total NPP. The total NPP of China’s terrestrial ecosystem continuously increased with the concurrent increase in the CO2 concentration and climate change under different scenarios in the future. During the period from 2091 to 2100, the average total NPP under the A2 and RCP85 scenarios would reach 4.9 and 5.1 Pg C yr−1 respectively, higher than 4.2 and 3.9 Pg C yr−1 under the B1 and RCP45 scenarios. Forests, especially temperate forests, make the largest contribution to the future increase in NPP. The increase in CO2 concentration would play a dominant role in driving further NPP increase in China’s terrestrial ecosystems, and climate change may slightly attenuate the fertilization effect of CO2 on NPP.

A comparison of the fine root component of a pure and a mixed coniferous stand

1988 ◽  
Vol 18 (11) ◽  
pp. 1416-1426 ◽  
Author(s):  
H. M. McKay ◽  
D. C. Malcolm
Keyword(s):  
Fine Roots ◽  
Standing Crop ◽  
Fine Root ◽  
Sitka Spruce ◽  
Nitrogen And Phosphorus ◽  
Mixed Stands ◽  
Method Of Calculation ◽  
The Mean ◽  
Phosphorus And Potassium ◽  
Nitrogen Phosphorus

Fine roots were sampled at monthly intervals during 1984–1985 in pure plots of Sitka spruce (Piceasitchensis (Bong.) Carr.) and mixed plots of Scots pine (Pinussylvestris L.) and Sitka spruce established on an upland heath in 1969. Both types of planting had received phosphorus and potassium fertiliser but no nitrogen. The mean standing crop of live roots (<2 mm diameter) in the top 5 cm of pure spruce plots was 112 g • m−2, almost double that of mixed stands (37 g • m−2 of spruce plus 20 g • m−2 of pine). Necromass was 80% of total mass in both stand types. Concentrations of nitrogen and phosphorus were greater in pure plots than in mixed plots, but fine root capital of nitrogen, phosphorus, and potassium was greater in pure spruce than in mixed plots (biomass and necromass contained 11, 2, and 5 and 45, 4, and 7 kg • ha−1 of nitrogen, phosphorus, and potassium, in pure plots, and 7, 1, and 3 and 30, 3, and 3 kg • ha−1 of nitrogen, phosphorus, and potassium in mixed plots, respectively). Production of fine roots in pure and mixed stands was estimated at 181 and 97 g • m−2•year−1 or 715 and 367 g • m−2•year−1, respectively, depending on the method of calculation. Fine roots of pure plots were highly concentrated in the top 3 cm. In mixture, spruce roots had a less extreme vertical distribution and pine roots were more evenly distributed down to 9 cm.

scholarly journals Partitioning of canopy and soil CO<sub>2</sub> fluxes in a pine forests at the dry timberline

2019 ◽  
Author(s):  
Rafat Qubaja ◽  
Feyodor Tatarinov ◽  
Eyal Rotenberg ◽  
Dan Yakir
Keyword(s):  
Soil Respiration ◽  
Primary Productivity ◽  
Net Primary Productivity ◽  
Carbon Allocation ◽  
Ecosystem Respiration ◽  
Pine Forest ◽  
Carbon Accumulation ◽  
Dry Forest ◽  
Co2 Uptake ◽  
The Mean

Abstract. Partitioning carbon fluxes is key to understanding the process underlying ecosystem response to change. This study used soil and canopy fluxes with stable isotopes (13C) and radiocarbon (14C) measurements of a 50-year-old dry (i.e., 287 mm of annual precipitation) pine forest to partition the ecosystem’s CO2 flux into gross primary productivity (GPP) and ecosystem respiration (Re) and soil respiration flux into autotrophic (Rsa), heterotrophic (Rh), and inorganic (Ri) components. On an annual scale, GPP and Re were 655 and 488 g C m−2, respectively, with a net primary productivity (NPP) of 276 g C m−2 and carbon-use efficiency (CUE = NPP / GPP) of 0.42. Soil respiration (Rs) made up 60 % of the total ecosystem respiration and was comprised of 24 ± 4 %, 23 ± 4 %, and 13 ± 1 % Rsa, Rh, and Ri, respectively. The contribution of root and microbial respiration to Re increased during high productivity periods, and inorganic sources were more significant components when soil water content was low. Compared to the mean values for 2001–2006 at the same site; (Grünzweig et al., 2009), annual Rs decreased by 27 % to the mean 2016 rates of 0.8 ± 0.1 µmol m−2 s−1). This was associated with decrease in the respiration Q10 values across the same observation by 36 % and 9 % in the wet and dry periods, respectively. Low rates of soil carbon loss combined with relatively high below ground carbon allocation (i.e., 40 % of canopy CO2 uptake) help explain the high soil organic carbon accumulation and the relatively high ecosystem CUE of the dry forest. This was indicative of the higher resilience of the pine forest to climate change and the significant potential for carbon sequestration in these regions.

scholarly journals Mean age of carbon in fine roots from temperate forests and grasslands with different management

2013 ◽  
Vol 10 (3) ◽  
pp. 5671-5700 ◽  
Author(s):  
E. Solly ◽  
I. Schöning ◽  
S. Boch ◽  
J. Müller ◽  
S. A. Socher ◽  
...  
Keyword(s):  
Species Diversity ◽  
Plant Species ◽  
Fine Roots ◽  
Fine Root ◽  
Plant Species Diversity ◽  
Soil Conditions ◽  
Perennial Species ◽  
Temperate Grasslands ◽  
Organic C ◽  
The Mean

Abstract. Fine roots are the most dynamic portion of a plant's root system and a major source of soil organic matter. By altering plant species diversity and composition, soil conditions and nutrient availability, and consequently belowground allocation and dynamics of root carbon (C) inputs, land-use and management changes may influence organic C storage in terrestrial ecosystems. In three German regions we measured fine root radiocarbon (14C) content to estimate the mean time since C in root tissues was fixed from the atmosphere in 54 grassland and forest plots with different management and soil conditions. Although root biomass was on average greater in grasslands 5.1 ± 0.8 g (mean ± SE, n = 27) than in forests 3.1 ± 0.5 g (n = 27), the mean age of C in fine roots in forests averaged 11.3 ± 1.8 yr and was significantly older and more variable compared to grasslands 1.7 ± 0.4 yr. We further found that management affects the mean age of fine root C in temperate grasslands mediated by changes in plant species diversity and composition. Fine root mean C age is positively correlated to plant diversity (r = 0.65) and to the number of perennial species (r = 0.77). In temperate grasslands the mean age of fine root C is also influenced by the study region mainly driven by differences in soil characteristics and climate which reflect in plant composition variations, with averages of 0.7 ± 0.1 yr (n = 9) on mostly organic sandy soils in northern Germany and of 1.8 ± 0.3 yr (n = 9) and 2.6 ± 0.3 (n = 9) in more silty and clayey soils respectively in central and southern Germany. Our results indicate an internal redistribution of C in perennial species and suggest linkages between fine root C age and management in grasslands. These findings improve our ability to predict and model belowground C fluxes across broader spatial scales.

scholarly journals GRASSLAND NPP MONITORING BASED ON MULTI-SOURCE REMOTE SENSING DATA FUSION

2018 ◽  
Vol XLII-3 ◽  
pp. 113-118
Author(s):  
Y. R. Cai ◽  
J. H. Zheng ◽  
M. J. Du ◽  
C. Mu ◽  
J. Peng
Keyword(s):  
Carbon Cycle ◽  
Primary Productivity ◽  
Vegetation Index ◽  
Net Primary Productivity ◽  
Terrestrial Ecosystem ◽  
Remote Sensing Data ◽  
Terrestrial Ecosystems ◽  
The United States ◽  
Estimation Accuracy ◽  
Modis Ndvi

Vegetation is an important part of the terrestrial ecosystem. It plays an important role in the energy and material exchange of the ground-atmosphere system and is a key part of the global carbon cycle process.Climate change has an important influence on the carbon cycle of terrestrial ecosystems. Net Primary Productivity (Net Primary Productivity)is an important parameter for evaluating global terrestrial ecosystems. For the Xinjiang region, the study of grassland NPP has gradually become a hot issue in the ecological environment.Increasing the estimation accuracy of NPP is of great significance to the development of the ecosystem in Xinjiang. Based on the third-generation GIMMS AVHRR NDVI global vegetation dataset and the MODIS NDVI (MOD13A3) collected each month by the United States Atmospheric and Oceanic Administration (NOAA),combining the advantages of different remotely sensed datasets, this paper obtained the maximum synthesis fusion for New normalized vegetation index (NDVI) time series in 2006&amp;ndash;2015.Analysis of Net Primary Productivity of Grassland Vegetation in Xinjiang Using Improved CASA Model The method described in this article proves the feasibility of applying data processing, and the accuracy of the NPP calculation using the fusion processed NDVI has been greatly improved. The results show that: (1) The NPP calculated from the new normalized vegetation index (NDVI) obtained from the fusion of GIMMS AVHRR NDVI and MODIS NDVI is significantly higher than the NPP calculated from these two raw data; (2) The grassland NPP in Xinjiang Interannual changes show an overall increase trend; interannual changes in NPP have a certain relationship with precipitation.

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