Estimating total forest biomass in New York, 1993

Wharton, Eric H.; Alerich, Carol A.; Drake, David

doi:10.2737/ne-rb-139

Cited by 3 publications

(2 citation statements)

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“…Aboveground wood NPP was calculated as the difference between the two inventories, on a tree‐by‐tree basis, using species‐specific allometric equations based on diameter at breast height (dbh), crown depth and height, and aggregated to the plot level. Coarse root production was calculated using ratios of root biomass to above‐stump biomass (Wharton et al ., 1997; Wharton & Griffith, 1998) for species lacking such equations. TNPP was calculated using .…”

Section: Methodsmentioning

confidence: 99%

Terrestrial net primary production estimates for 0.5° grid cells from field observations—a contribution to global biogeochemical modeling

Zheng

Prince

Wright

2002

Global Change Biology

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Net Primary Production (NPP) is an important component of the carbon cycle and, among the pools and fluxes that make up the cycle, it is one of the steps that are most accessible to field measurement. While easier than some other steps to measure, direct measurement of NPP is tedious and not practical for large areas and so models are generally used to study the carbon cycle at a global scale. Nevertheless these models require field measurements of NPP for parameterization, calibration and validation. Most NPP data are for relatively small field plots that cannot represent the 0.5° × 0.5° grid cells that are commonly used in global scale models. Furthermore, technical difficulties generally restrict NPP measurements to aboveground parts and sometimes do not even include all components of aboveground NPP. Thus direct inter‐comparison between field data obtained in different studies or comparison of these results with coarse resolution model outputs can be misleading. We summarize and present a series of methods that were used by original authors to estimate NPP and how and what we have done to prepare a consistent data set of NPP for 0.5 °grid cells for a range of biomes from these studies. The methods used for estimation of NPP include: (i) aggregation of fine‐scale (plot or stand‐level) vegetation inventory data to larger grid cells, (ii) mapping of grid cells and area weighting of field NPP observations in each mapped class, (iii) direct correlation of extensive data sets of ground measurements with remotely sensed spectral vegetation indices, (iv) local modeling of NPP using key independent variables, for which maps are available at the scale of the grid cell, and (v) regression analysis to link productivity with controlling environmental variables. For a few grid cells whose NPP were obtained for multiple years, temporal analysis was conducted. The grid cells are grouped to the biome level and are compared with existing compilations of field NPP and the results of the Miami potential NPP model. Mean NPP was similar to the well‐known compilation of Whittaker and Likens, except for temperate evergreen needle‐leaved forest, woodland, and shrubland. The grid cell datasets are a contribution to the International Geosphere‐Biosphere Programme (IGBP) Data and Information System (DIS) Global Primary Production Data Initiative (GPPDI). The full dataset currently contains 3654 cells (including replicate measurements) developed from 15 studies representing NPP in croplands, sparse vegetation, shrub lands, grasslands, and forests worldwide. An edited subset consists of 2335 cells in which outliers were removed and all replicate measurements were averaged for each unique geographical location. Most of the data incorporated into GPPDI were wholly or partly developed by participants in the GPPDI, in addition to the present authors. These studies are gathered together here to provide a consistent account of the grid cell component of GPPDI and an analysis of the entire data set. The datasets have been deposited in a...

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Section: Methodsmentioning

confidence: 99%

Terrestrial net primary production estimates for 0.5° grid cells from field observations—a contribution to global biogeochemical modeling

Zheng

Prince

Wright

2002

Global Change Biology

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“…The subplots occupy 0.07 ha (0.17 ac), and the subplot array can be subtended by a circle of 0.4 ha (1.0 ac) in area. The value of the total aboveground dry biomass was calculated from live tree data collected on each plot using equations found inWharton et al (1997).The predictor data used were contained in a multilayered ERDAS IMAGINE image and consisted of 271 250-m resolution layers, including multidate and monthly composites and derived indexes of imagery from the Moderate Resolution Imaging Spectroradiometer (MODIS)-satellite-borne sensor (Justice and Townsend 2002), several rasterized summaries of the State Soil Geographic soils database compiled by the USDA Natural Resources Conservation Service (1994), summaries of the land cover classes found in the National Land Cover Data (NLCD)…”

mentioning

confidence: 99%

Proceedings of the sixth annual forest inventory and analysis symposium

Duesen¹,

McRoberts²,

Reams³

et al. 2006

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The Forest Inventory and Analysis (FIA) program of the U.S. Department of Agriculture Forest Service has made significant progress implementing the annualized inventory in 46 States in 2004. Major increases in program performance included the availability of plot data and the plots' corresponding approximate coordinates. A mill site study and biomass models were used to compare actual versus approximate coordinates. The protocols used to protect the privacy of private forest landowners did not meaningfully alter the results. A new strategic plan for FIA will be developed for 2007-12. Through meetings with partners and customers, FIA will evaluate opportunities to broaden the information collected and analyses of this data.

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