scholarly journals MERIS GPP/NPP product for Estonia: I. Algorithm and preliminary results of simulation / MERIS’e GPP/NPP tulem Eesti jaoks: I. Algoritm ja mudelarvutuste esialgsed tulemused

2012 ◽  
Vol 56 (1) ◽  
pp. 56-78
Author(s):  
Tiit Nilson ◽  
Mattias Rennel ◽  
Andres Luhamaa ◽  
Maris Hordo ◽  
Aire Olesk ◽  
...  
Keyword(s):  
Primary Production ◽  
Tree Ring ◽  
Net Primary Production ◽  
Gross Primary Production ◽  
Weather Prediction ◽  
Type Model ◽  
Limited Area ◽  
Area Index ◽  
Tree Ring Data ◽  
Resolution Imaging

Abstract. A light use efficiency (LUE) type model named EST_PP to simulate the yearly gross primary production (GPP) and net primary production (NPP) of Estonian land on a 1 km2 grid is described. The model is based on MERIS (MEdium Resolution Imaging Spectrometer) satellite images to describe the fraction of photosynthetically active radiation (fAPAR) and leaf area index (LAI) as well as meteorological reanalysis datasets on 11 km2 grid produced by Estonian Meteorological Institute (EMHI) and Tartu University (TU) by means of the HIRLAM (High Resolution Limited Area Model) numerical weather prediction model. The land cover map of Estonia needed for the model was derived using DMCii (Disaster Monitoring Constellation International Imaging) SLIM-6-22 (Surrey Linear Imager - 6 channel - 22 m resolution) images and ancillary information. The EST_PP model was run for the period from years 2003 to 2011. The results of GPP and NPP simulation are compared with the available global MODIS (Moderate Resolution Imaging Spectroradiometer) GPP/NPP product and with the Estonian statistical data on yearly volume increment in forests and on yield of agricultural crops. The NPP simulation results on coniferous and deciduous forests are compared with the data from tree ring analyses from different counties. These comparisons show us that the simulated country average yearly NPP values for Estonian forests agree reasonably well with the indirect estimates from other sources, taking into account the rather high uncertainty of the model predictions, uncertainty of forest inventory-based estimates and limited representativity of existing tree ring data. However, problems arise with the ability of present versions of EST_PP and MODIS NPP models to adequately simulate the regional differences of productivity and of variability of productivity in different years. The model needs some modification and the basic LUE principles to be tested in Estonia. Nevertheless, the MODIS NPP and EST_PP models offer additional possibilities to map yearly productivity and carbon sequestration by Estonian vegetation. There is a perspective to add the model-simulated NPP values into the national inventory datasets.

scholarly journals Leaf Area Index identified as a major source of variability in modelled CO<sub>2</sub> fertilization

2018 ◽  
Author(s):  
Qianyu Li ◽  
Xingjie Lu ◽  
Yingping Wang ◽  
Xin Huang ◽  
Peter M. Cox ◽  
...  
Keyword(s):  
Primary Production ◽  
Leaf Area Index ◽  
Leaf Area ◽  
Net Primary Production ◽  
Gross Primary Production ◽  
Vegetation Types ◽  
Cable Model ◽  
Co2 Fertilization ◽  
Area Index ◽  
Leaf Level

Abstract. The concentration-carbon feedback factor (β), also called the CO2 fertilization effect, is a key unknown in climate-carbon cycle projections. A better understanding of model mechanisms that govern terrestrial ecosystem responses to elevated CO2 is urgently needed to enable a more accurate prediction of future terrestrial carbon sink. We calculated CO2 fertilization effects at various hierarchical levels from leaf biochemical reaction, leaf photosynthesis, canopy gross primary production (GPP), net primary production (NPP), to ecosystem carbon storage (cpool), for seven C3 vegetation types in response to increasing CO2 under RCP 8.5 scenario, using the Community Atmosphere Biosphere Land Exchange model (CABLE). Our results show that coefficient of variation (CV) for the CABLE model among the seven vegetation types is 0.15–0.13 for the biochemical level β, 0.13–0.16 for the leaf-level β, 0.48 for the βGPP, 0.45 for the βNPP, and 0.58 for the βcpool. The low variation of the leaf-level β is consistent with a theoretical analysis that leaf photosynthetic sensitivity to increasing CO2 concentration is almost an invariant function. In CABLE, the major jump in CV of β values from leaf- to canopy- and ecosystem-levels results from divergence in modelled leaf area index (LAI) within and among the vegetation types. The correlations of βGPP, βNPP, or βcpool with βLAI are very high in CABLE. Overall, our results indicate that modelled LAI is a key factor causing the divergence in β values in CABLE model. It is therefore urgent to constrain processes that regulate LAI dynamics in order to better represent the response of ecosystem productivity to increasing CO2 in Earth System Models.

scholarly journals Moderate forest disturbance as a stringent test for gap and big-leaf models

2015 ◽  
Vol 12 (2) ◽  
pp. 513-526 ◽  
Author(s):  
B. Bond-Lamberty ◽  
J. P. Fisk ◽  
J. A. Holm ◽  
V. Bailey ◽  
G. Bohrer ◽  
...  
Keyword(s):  
Primary Production ◽  
Tree Mortality ◽  
Net Primary Production ◽  
Forest Disturbance ◽  
Gross Primary Production ◽  
Structural Complexity ◽  
Terrestrial Ecosystem ◽  
Ecosystem Models ◽  
Area Index ◽  
C Cycle

Abstract. Disturbance-induced tree mortality is a key factor regulating the carbon balance of a forest, but tree mortality and its subsequent effects are poorly represented processes in terrestrial ecosystem models. It is thus unclear whether models can robustly simulate moderate (non-catastrophic) disturbances, which tend to increase biological and structural complexity and are increasingly common in aging US forests. We tested whether three forest ecosystem models – Biome-BGC (BioGeochemical Cycles), a classic big-leaf model, and the ZELIG and ED (Ecosystem Demography) gap-oriented models – could reproduce the resilience to moderate disturbance observed in an experimentally manipulated forest (the Forest Accelerated Succession Experiment in northern Michigan, USA, in which 38% of canopy dominants were stem girdled and compared to control plots). Each model was parameterized, spun up, and disturbed following similar protocols and run for 5 years post-disturbance. The models replicated observed declines in aboveground biomass well. Biome-BGC captured the timing and rebound of observed leaf area index (LAI), while ZELIG and ED correctly estimated the magnitude of LAI decline. None of the models fully captured the observed post-disturbance C fluxes, in particular gross primary production or net primary production (NPP). Biome-BGC NPP was correctly resilient but for the wrong reasons, and could not match the absolute observational values. ZELIG and ED, in contrast, exhibited large, unobserved drops in NPP and net ecosystem production. The biological mechanisms proposed to explain the observed rapid resilience of the C cycle are typically not incorporated by these or other models. It is thus an open question whether most ecosystem models will simulate correctly the gradual and less extensive tree mortality characteristic of moderate disturbances.

scholarly journals Importance of succession in estimating biomass loss: Combining remote sensing and individual-based forest models

2020 ◽  
Author(s):  
Ulrike Hiltner ◽  
Andreas Huth ◽  
Rico Fischer
Keyword(s):  
Primary Production ◽  
Leaf Area Index ◽  
Leaf Area ◽  
Tree Mortality ◽  
Net Primary Production ◽  
Gross Primary Production ◽  
Mortality Rates ◽  
Area Index ◽  
Forest Height ◽  
Biomass Loss

Abstract. Disturbances can have strong impacts on the dynamics and structure of tropical forests. They often lead to increased tree mortality and affect their behaviour as carbon sinks. In the future, the intensity of disturbances, such as extreme weather events, fires, floods, and biotic agents, will probably even increase, with more serious consequences for tropical forests than we have already observed. However, impacts of altering disturbances on rates of forest biomass loss through tree mortality (hereinafter: biomass mortality) have been little described yet. This complicates progress in quantifying the effects of climate change on forests globally. This study aims to analyse the consequences of elevated tree mortality on forest dynamics and to provide a methodology that can reduce uncertainties in estimating biomass mortality rates at local and country level. We achieved this by linking benefits of individual-based forest model-ling, statistical linear regression, and remote sensing. We applied an individual-based forest model to investigate the impact of varying disturbance regimes on the succession dynamic of a humid Terra Firma forest at the Paracou study site in French Guiana. By simulating increased tree mortality rates, we were able to investigate their influence on several forest attributes, namely biomass, leaf area index, forest height, gross primary production, net primary production, and biomass mortality. Based on simulations of leaf area index and forest height, we developed a linear multivariate regression model to project biomass mortality. Our findings demonstrate that severe disturbances altered the succession pattern of the forests in favour of fast-growing species, which changed gross primary production, but net primary production remained stable. We also observed a strong influence on biomass mortality rates as well as observed complex relationships between these rates and single forest attributes (leaf area index, forest height, and biomass). By combining leaf area index and forest height we obtained relationships that allow an estimation of the biomass mortality. Based on these findings, we mapped the biomass mortality for whole French Guiana. We found a nation-wide biomass mortality of 3 % per year (standard deviation = 1.4 % per year). The approach we describe here, provides a novel methodology for quantifying the spatial-temporal distribution of biomass loss, which has recently been identified as particularly critical for monitoring mortality hot spots. Quantifying biomass mortality rates may help reducing uncertainties in the terrestrial component of the global carbon cycle.

scholarly journals Leaf area index identified as a major source of variability in modeled CO<sub>2</sub> fertilization

2018 ◽  
Vol 15 (22) ◽  
pp. 6909-6925 ◽  
Author(s):  
Qianyu Li ◽  
Xingjie Lu ◽  
Yingping Wang ◽  
Xin Huang ◽  
Peter M. Cox ◽  
...  
Keyword(s):  
Primary Production ◽  
Leaf Area Index ◽  
Leaf Area ◽  
Net Primary Production ◽  
Gross Primary Production ◽  
Leaf Photosynthesis ◽  
Cable Model ◽  
Co2 Fertilization ◽  
C3 Plant ◽  
Area Index

Abstract. The concentration–carbon feedback (β), also called the CO2 fertilization effect, is a key unknown in climate–carbon-cycle projections. A better understanding of model mechanisms that govern terrestrial ecosystem responses to elevated CO2 is urgently needed to enable a more accurate prediction of future terrestrial carbon sink. We conducted C-only, carbon–nitrogen (C–N) and carbon–nitrogen–phosphorus (C–N–P) simulations of the Community Atmosphere Biosphere Land Exchange model (CABLE) from 1901 to 2100 with fixed climate to identify the most critical model process that causes divergence in β. We calculated CO2 fertilization effects at various hierarchical levels from leaf biochemical reaction and leaf photosynthesis to canopy gross primary production (GPP), net primary production (NPP), and ecosystem carbon storage (cpool) for seven C3 plant functional types (PFTs) in response to increasing CO2 under the RCP 8.5 scenario. Our results show that β values at biochemical and leaf photosynthesis levels vary little across the seven PFTs, but greatly diverge at canopy and ecosystem levels in all simulations. The low variation of the leaf-level β is consistent with a theoretical analysis that leaf photosynthetic sensitivity to increasing CO2 concentration is almost an invariant function. In the CABLE model, the major jump in variation of β values from leaf levels to canopy and ecosystem levels results from divergence in modeled leaf area index (LAI) within and among PFTs. The correlation of βGPP, βNPP, or βcpool each with βLAI is very high in all simulations. Overall, our results indicate that modeled LAI is a key factor causing the divergence in β in the CABLE model. It is therefore urgent to constrain processes that regulate LAI dynamics in order to better represent the response of ecosystem productivity to increasing CO2 in Earth system models.

scholarly journals Generation of High Resolution Vegetation Productivity from a Downscaling Method

2018 ◽  
Vol 10 (11) ◽  
pp. 1748 ◽  
Author(s):  
Tao Yu ◽  
Rui Sun ◽  
Zhiqiang Xiao ◽  
Qiang Zhang ◽  
Juanmin Wang ◽  
...  
Keyword(s):  
High Resolution ◽  
Primary Production ◽  
Land Surface ◽  
Net Primary Production ◽  
Gross Primary Production ◽  
Terrestrial Ecosystems ◽  
Vegetation Productivity ◽  
Area Index ◽  
Multi Scale ◽  
Downscaling Method

Accurately estimating vegetation productivity is important in the research of terrestrial ecosystems, carbon cycles and climate change. Although several gross primary production (GPP) and net primary production (NPP) products have been generated and many algorithms developed, advances are still needed to exploit multi-scale data streams for producing GPP and NPP with higher spatial and temporal resolution. In this paper, a method to generate high spatial resolution (30 m) GPP and NPP products was developed based on multi-scale remote sensing data and a downscaling method. First, high resolution fraction photosynthetically active radiation (FPAR) and leaf area index (LAI) were obtained by using a regression tree approach and the spatial and temporal adaptive reflectance fusion model (STARFM). Second, the GPP and NPP were estimated from a multi-source data synergized quantitative algorithm. Finally, the vegetation productivity estimates were validated with the ground-based field data, and were compared with MODerate Resolution Imaging Spectroradiometer (MODIS) and estimated Global LAnd Surface Satellite (GLASS) products. Results of this paper indicated that downscaling methods have great potential in generating high resolution GPP and NPP.

Estimation of forest Leaf Area Index using remote sensing and GIS data for modelling net primary production

1997 ◽  
Vol 18 (16) ◽  
pp. 3459-3471 ◽  
Author(s):  
S. E. Franklin ◽  
M. B. Lavigne ◽  
M. J. Deuling ◽  
M. A. Wulder ◽  
E. R. Hunt
Keyword(s):  
Remote Sensing ◽  
Primary Production ◽  
Leaf Area Index ◽  
Leaf Area ◽  
Net Primary Production ◽  
Remote Sensing And Gis ◽  
Area Index ◽  
Gis Data

scholarly journals Above-Ground Net Primary Production, Leaf Area Index, and Nitrogen Dynamics in Early Post-Fire Vegetation, Yellowstone National Park

1997 ◽  
Vol 21 ◽  
pp. 130-134
Author(s):  
Monica Turner ◽  
Rebecca Reed ◽  
William Romme ◽  
Mary Finley ◽  
Dennis Knight
Keyword(s):  
Primary Production ◽  
Leaf Area Index ◽  
Leaf Area ◽  
Yellowstone National Park ◽  
National Park ◽  
Net Primary Production ◽  
Lodgepole Pine ◽  
Fire Severity ◽  
Ecosystem Processes ◽  
Area Index

The 1988 fires in Yellowstone National Park (YNP), Wyoming, affected >250,000 ha, creating a striking mosaic of burn severities across the landscape which is likely to influence ecological processes for decades to come (Christensen et al. 1989, Knight and Wallace 1989, Turner et al.1994). Substantial spatial heterogeneity in early post-fire succession has been observed in the decade since the fires, resulting largely from spatial variation in fire severity and in the availability of lodgepole pine (Pinus contorta var. latifolia) seeds in or near the burned area (Anderson and Romme 1991, Tinker et al. 1994, Turner et al. 1997). Post­fire vegetation now includes pine stands ranging from relatively low to extremely high pine sapling density (ca 10,000 to nearly 100,000 stems ha-1) as well as non-forest or marginally forested vegetation across the Yellowstone landscape may influence ecosystem processes related to energy flow and biogeochemisty. We also are interested in how quickly these processes may return to their pre­ disturbance characteristics. In this pilot study, we began to address these general questions by examining the variation in above-ground net primary production (ANPP), leaf area index (LAI) of tree (lodgepole pine) and herbaceous components, and rates of nitrogen mineralization and loss in successional stands 9 years after the fires. ANPP measures the cumulative new biomass generated over a given period of time, and is a fundamental ecosystem property often used to compare ecosystems (Carpenter 1998). Leaf area (typically expressed as leaf area index [LAI], i.e., leaf area per unit ground surface area) influences rates of two fundamental ecosystem processes -­ primary productivity and transpiration -- and is communities (

Energy and nutrients

2019 ◽  
pp. 161-176
Author(s):  
Richard T. Corlett
Keyword(s):  
Primary Production ◽  
Forest Ecology ◽  
Net Primary Production ◽  
Ecosystem Respiration ◽  
Gross Primary Production ◽  
Nitrogen And Phosphorus ◽  
New Information ◽  
Tropical Forest Ecology ◽  
Toxic Concentrations

This chapter deals with the ecology of Tropical East Asia from the perspective of water, energy, and matter flows through ecosystems, particularly forests. Data from the network of eddy flux covariance towers is revealing general patterns in gross primary production, ecosystem respiration, and net ecosystem production, and exchange. There is also new information on the patterns of net primary production and biomass within the region. In contrast, our understanding of the role of soil nutrients in tropical forest ecology still relies mostly on work done in the Neotropics, with just enough data from Asia to suggest that the major patterns may be pantropical. Nitrogen and phosphorus have received most attention regionally, followed by calcium, potassium, and magnesium, and there has been very little study of the role of micronutrients and potentially toxic concentrations of aluminium, manganese, and hydrogen ions. Animal nutrition has also been neglected.

scholarly journals How drought severity constrains gross primary production(GPP) and its partitioning among carbon pools in a <i>Quercus ilex</i> coppice?

2014 ◽  
Vol 11 (23) ◽  
pp. 6855-6869 ◽  
Author(s):  
S. Rambal ◽  
M. Lempereur ◽  
J. M. Limousin ◽  
N. K. Martin-StPaul ◽  
J. M. Ourcival ◽  
...  
Keyword(s):  
Primary Production ◽  
Water Deficit ◽  
Eddy Covariance ◽  
Quercus Ilex ◽  
Net Primary Production ◽  
Gross Primary Production ◽  
Carbon Fluxes ◽  
Stem Growth ◽  
Drought Severity ◽  
Mediterranean Ecosystem

Abstract. The partitioning of photosynthates toward biomass compartments plays a crucial role in the carbon (C) sink function of forests. Few studies have examined how carbon is allocated toward plant compartments in drought-prone forests. We analyzed the fate of gross primary production (GPP) in relation to yearly water deficit in an old evergreen Mediterranean Quercus ilex coppice severely affected by water limitations. Carbon fluxes between the ecosystem and the atmosphere were measured with an eddy covariance flux tower running continuously since 2001. Discrete measurements of litterfall, stem growth and fAPAR allowed us to derive annual productions of leaves, wood, flowers and acorns, and an isometric relationship between stem and belowground biomass has been used to estimate perennial belowground growth. By combining eddy covariance fluxes with annual net primary productions (NPP), we managed to close a C budget and derive values of autotrophic, heterotrophic respirations and carbon-use efficiency (CUE; the ratio between NPP and GPP). Average values of yearly net ecosystem production (NEP), GPP and Reco were 282, 1259 and 977 g C m−2. The corresponding aboveground net primary production (ANPP) components were 142.5, 26.4 and 69.6 g C m−2 for leaves, reproductive effort (flowers and fruits) and stems, respectively. NEP, GPP and Reco were affected by annual water deficit. Partitioning to the different plant compartments was also impacted by drought, with a hierarchy of responses going from the most affected – the stem growth – to the least affected – the leaf production. The average CUE was 0.40, which is well in the range for Mediterranean-type forest ecosystems. CUE tended to decrease less drastically in response to drought than GPP and NPP did, probably due to drought acclimation of autotrophic respiration. Overall, our results provide a baseline for modeling the inter-annual variations of carbon fluxes and allocation in this widespread Mediterranean ecosystem, and they highlight the value of maintaining continuous experimental measurements over the long term.

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