Aboveground Net Primary Production and Leaf-Area Index in Early Postfire Vegetation in Yellowstone National Park

Ecosystems ◽  
1999 ◽  
Vol 2 (1) ◽  
pp. 88-94 ◽  
Author(s):  
Rebecca A. Reed ◽  
Mary Ellen Finley ◽  
William H. Romme ◽  
Monica G. Turner
Keyword(s):  
Primary Production ◽  
Leaf Area Index ◽  
Leaf Area ◽  
Yellowstone National Park ◽  
National Park ◽  
Net Primary Production ◽  
Aboveground Net Primary Production ◽  
Area Index

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 (

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 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.

Spatial variability of aboveground net primary production for a forested landscape in northern Wisconsin

2003 ◽  
Vol 33 (10) ◽  
pp. 2007-2018 ◽  
Author(s):  
S N Burrows ◽  
S T Gower ◽  
J M Norman ◽  
G Diak ◽  
D S Mackay ◽  
...  
Keyword(s):  
Primary Production ◽  
Leaf Area Index ◽  
Leaf Area ◽  
Spatial Patterns ◽  
Vegetation Cover ◽  
Land Surface ◽  
Net Primary Production ◽  
Mixed Forest ◽  
Forested Wetlands ◽  
Area Index

Quantifying forest net primary production (NPP) is critical to understanding the global carbon cycle because forests are responsible for a large portion of the total terrestrial NPP. The objectives of this study were to measure above ground NPP (NPPA) for a land surface in northern Wisconsin, examine the spatial patterns of NPPA and its components, and correlate NPPA with vegetation cover types and leaf area index. Mean NPPA for aspen, hardwoods, mixed forest, upland conifers, nonforested wetlands, and forested wetlands was 7.8, 7.2, 5.7, 4.9, 5.0, and 4.5 t dry mass·ha–1·year–1, respectively. There were significant (p = 0.01) spatial patterns in wood, foliage, and understory NPP components and NPPA (p = 0.03) when the vegetation cover type was included in the model. The spatial range estimates for the three NPP components and NPPA differed significantly from each other, suggesting that different factors are influencing the components of NPP. NPPA was significantly correlated with leaf area index (p = 0.01) for the major vegetation cover types. The mean NPPA for the 3 km × 2 km site was 5.8 t dry mass·ha–1·year–1.

Aboveground organic matter and production of a montane forest on the eastern slopes of the Washington Cascade Range

1989 ◽  
Vol 19 (4) ◽  
pp. 515-518 ◽  
Author(s):  
Stith T. Gower ◽  
Charles C. Grier
Keyword(s):  
Primary Production ◽  
Leaf Area ◽  
Aboveground Biomass ◽  
Net Primary Production ◽  
Cascade Range ◽  
Conifer Forest ◽  
Mixed Conifer ◽  
Aboveground Net Primary Production ◽  
Area Index ◽  
Mixed Conifer Forest

Aboveground biomass and production were determined for a 70-year-old mixed conifer forest of western larch (Larixoccidentalis Nutt.), lodgepole pine (Pinuscontorta Dougl. var. latifolia Engelm.), and Douglas-fir (Pseudotsugamenziesii (Mirb.) Franco) on the eastern slopes of the Cascade Range in Washington state. Live aboveground biomass, projected leaf area, and aboveground net primary production for the mixed conifer forest were 194 Mg•ha−1, 4.2 m−2•m−2, and 6.1 Mg•ha−1•year−1, respectively. Based on the few studies of montane forests on the eastern slope of the Cascades, aboveground biomass, leaf area index, and aboveground net primary production of these forests are more similar to those of montane coniferous forests in the Rocky Mountains than to those of similar forests located on the western slopes of the Cascades.

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.

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