Forest biomass variation in Southernmost Brazil: the impact of Araucaria trees.

PubMed

Rosenfield, Milena Fermina; Souza, Alexandre F

2014-03-01

A variety of environmental and biotic factors determine vegetation growth and affect plant biomass accumulation. From temperature to species composition, aboveground biomass storage in forest ecosystems is influenced by a number of variables and usually presents a high spatial variability. With this focus, the aim of the study was to evaluate the variables affecting live aboveground forest biomass (AGB) in Subtropical Moist Forests of Southern Brazil, and to analyze the spatial distribution of biomass estimates. Data from a forest inventory performed in the State of Rio Grande do Sul, Southern Brazil, was used in the present study. Thirty-eight 1-ha plots were sampled and all trees with DBH > or = 9.5cm were included for biomass estimation. Values for aboveground biomass were obtained using published allometric equations. Environmental and biotic variables (elevation, rainfall, temperature, soils, stem density and species diversity) were obtained from the literature or calculated from the dataset. For the total dataset, mean AGB was 195.2 Mg/ha. Estimates differed between Broadleaf and Mixed Coniferous-Broadleaf forests: mean AGB was lower in Broadleaf Forests (AGB(BF)=118.9 Mg/ha) when compared to Mixed Forests (AGB(MF)=250.3 Mg/ha). There was a high spatial and local variability in our dataset, even within forest types. This condition is normal in tropical forests and is usually attributed to the presence of large trees. The explanatory multiple regressions were influenced mainly by elevation and explained 50.7% of the variation in AGB. Stem density, diversity and organic matter also influenced biomass variation. The results from our study showed a positive relationship between aboveground biomass and elevation. Therefore, higher values of AGB are located at higher elevations and subjected to cooler temperatures and wetter climate. There seems to be an important contribution of the coniferous species Araucaria angustifolia in Mixed Forest plots, as it presented significantly higher biomass than angiosperm species. In Brazil, this endangered species is part of a high diversity forest (Araucaria Forest) and has the potential for biomass storage. The results of the present study show the spatial and local variability in aboveground biomass in subtropical forests and highlight the importance of these ecosystems in global carbon stock, stimulating the improvement of future biomass estimates.

Quantification of live aboveground forest biomass dynamics with Landsat time-series and field inventory data: A comparison of empirical modeling approaches

Treesearch

Scott L. Powell; Warren B. Cohen; Sean P. Healey; Robert E. Kennedy; Gretchen G. Moisen; Kenneth B. Pierce; Janet L. Ohmann

2010-01-01

Spatially and temporally explicit knowledge of biomass dynamics at broad scales is critical to understanding how forest disturbance and regrowth processes influence carbon dynamics. We modeled live, aboveground tree biomass using Forest Inventory and Analysis (FIA) field data and applied the models to 20+ year time-series of Landsat satellite imagery to...

Impact of logging on aboveground biomass stocks in lowland rain forest, Papua New Guinea.

PubMed

Bryan, Jane; Shearman, Phil; Ash, Julian; Kirkpatrick, J B

2010-12-01

Greenhouse-gas emissions resulting from logging are poorly quantified across the tropics. There is a need for robust measurement of rain forest biomass and the impacts of logging from which carbon losses can be reliably estimated at regional and global scales. We used a modified Bitterlich plotless technique to measure aboveground live biomass at six unlogged and six logged rain forest areas (coupes) across two approximately 3000-ha regions at the Makapa concession in lowland Papua New Guinea. "Reduced-impact logging" is practiced at Makapa. We found the mean unlogged aboveground biomass in the two regions to be 192.96 +/- 4.44 Mg/ha and 252.92 +/- 7.00 Mg/ha (mean +/- SE), which was reduced by logging to 146.92 +/- 4.58 Mg/ha and 158.84 +/- 4.16, respectively. Killed biomass was not a fixed proportion, but varied with unlogged biomass, with 24% killed in the lower-biomass region, and 37% in the higher-biomass region. Across the two regions logging resulted in a mean aboveground carbon loss of 35 +/- 2.8 Mg/ha. The plotless technique proved efficient at estimating mean aboveground biomass and logging damage. We conclude that substantial bias is likely to occur within biomass estimates derived from single unreplicated plots.

Spatial distribution of forest aboveground biomass estimated from remote sensing and forest inventory data in New England, USA

Treesearch

Daolan Zheng; Linda S. Heath; Mark J. Ducey

2008-01-01

We combined satellite (Landsat 7 and Moderate Resolution Imaging Spectrometer) and U.S. Department of Agriculture forest inventory and analysis (FIA) data to estimate forest aboveground biomass (AGB) across New England, USA. This is practical for large-scale carbon studies and may reduce uncertainty of AGB estimates. We estimate that total regional forest AGB was 1,867...

Analysis of biophysical and anthropogenic variables and their relation to the regional spatial variation of aboveground biomass illustrated for North and East Kalimantan, Borneo.

PubMed

Van der Laan, Carina; Verweij, Pita A; Quiñones, Marcela J; Faaij, André Pc

2014-12-01

Land use and land cover change occurring in tropical forest landscapes contributes substantially to carbon emissions. Better insights into the spatial variation of aboveground biomass is therefore needed. By means of multiple statistical tests, including geographically weighted regression, we analysed the effects of eight variables on the regional spatial variation of aboveground biomass. North and East Kalimantan were selected as the case study region; the third largest carbon emitting Indonesian provinces. Strong positive relationships were found between aboveground biomass and the tested variables; altitude, slope, land allocation zoning, soil type, and distance to the nearest fire, road, river and city. Furthermore, the results suggest that the regional spatial variation of aboveground biomass can be largely attributed to altitude, distance to nearest fire and land allocation zoning. Our study showed that in this landscape, aboveground biomass could not be explained by one single variable; the variables were interrelated, with altitude as the dominant variable. Spatial analyses should therefore integrate a variety of biophysical and anthropogenic variables to provide a better understanding of spatial variation in aboveground biomass. Efforts to minimise carbon emissions should incorporate the identified factors, by 1) the maintenance of lands with high AGB or carbon stocks, namely in the identified zones at the higher altitudes; and 2) regeneration or sustainable utilisation of lands with low AGB or carbon stocks, dependent on the regeneration capacity of the vegetation. Low aboveground biomass densities can be found in the lowlands in burned areas, and in non-forest zones and production forests.

Estimation of crown biomass of Pinus pinaster stands and shrubland above-ground biomass using forest inventory data, remotely sensed imagery and spatial prediction models

Treesearch

H. Viana; J. Aranha; D. Lopes; Warren B. Cohen

2012-01-01

Spatially crown biomass of Pinus pinaster stands and shrubland above-ground biomass (AGB) estimation was carried-out in a region located in Centre-North Portugal, by means of different approaches including forest inventory data, remotely sensed imagery and spatial prediction models. Two cover types (pine stands and shrubland) were inventoried and...

Aboveground tree biomass on productive forest land in Alaska.

Treesearch

John Yarie; Delbert Mead

1982-01-01

Total aboveground woody biomass of trees on forest land that can produce 1.4 cubic m eters per hectare per year of industrial wood in Alaska is 1.33 billion metric tons green weight. The estimated energy value of the standing woody biomass is 11.9 x 10'5 Btu's. Statewide tables of biomass and energy values for softwoods, hardwoods, and species groups are...

Does biodiversity make a difference? Relationships between species richness, evolutionary diversity, and aboveground live tree biomass across US forests

Treesearch

Kevin M. Potter; Christopher W. Woodall

2014-01-01

Biodiversity conveys numerous functional benefits to forested ecosystems, including community stability and resilience. In the context of managing forests for climate change mitigation/adaptation, maximizing and/or maintaining aboveground biomass will require understanding the interactions between tree biodiversity, site productivity, and the stocking of live trees....

A Comparison of Two Above-Ground Biomass Estimation Techniques Integrating Satellite-Based Remotely Sensed Data and Ground Data for Tropical and Semiarid Forests in Puerto Rico

EPA Science Inventory

Two above-ground forest biomass estimation techniques were evaluated for the United States Territory of Puerto Rico using predictor variables acquired from satellite based remotely sensed data and ground data from the U.S. Department of Agriculture Forest Inventory Analysis (FIA)...

Patterns of covariance between forest stand and canopy structure in the Pacific Northwest.

Treesearch

Michael A. Lefsky; Andrew T. Hudak; Warren B. Cohen; S.A. Acker

2005-01-01

In the past decade, LIDAR (light detection and ranging) has emerged as a powerful tool for remotely sensing forest canopy and stand structure, including the estimation of aboveground biomass and carbon storage. Numerous papers have documented the use of LIDAR measurements to predict important aspects of forest stand structure, including aboveground biomass. Other...

Aboveground biomass, wood volume, nutrient stocks and leaf litter in novel forests compared to native forests and tree plantations in Puerto Rico

Treesearch

A.E. Lugo; O. Abelleira Martínez; J. Fonseca da Silva

2012-01-01

The article presents comparative data for aboveground biomass, wood volume, nutirent stocks (N, P, K) and leaf litter in different types of forests in Puerto Rico. The aim of the study is to assess how novel forests of Castilla elastica, Panama Rubber Tree, and Spathodea campanulata, African Tulip Tree, compare with tree plantations and native historical forests (both...

Regional applicability of forest height and aboveground biomass models for the Geoscience Laser Altimeter System

Treesearch

Dirk Pflugmacher; Warren B. Cohen; Robert E. Kennedy; Michael. Lefsky

2008-01-01

Accurate estimates of forest aboveground biomass are needed to reduce uncertainties in global and regional terrestrial carbon fluxes. In this study we investigated the utility of the Geoscience Laser Altimeter System (GLAS) onboard the Ice, Cloud and land Elevation Satellite for large-scale biomass inventories. GLAS is the first spaceborne lidar sensor that will...

[Simulation study on the effects of climate change on aboveground biomass of plantation in southern China: Taking Moshao forest farm in Huitong Ecological Station as an example].

PubMed

Dai, Er Fu; Zhou, Heng; Wu, Zhuo; Wang, Xiao-Fan; Xi, Wei Min; Zhu, Jian Jia

2016-10-01

Global climate warming has significant effect on territorial ecosystem, especially on forest ecosystem. The increase in temperature and radiative forcing will significantly alter the structure and function of forest ecosystem. The southern plantation is an important part of forests in China, its response to climate change is getting more and more intense. In order to explore the responses of southern plantation to climate change under future climate scenarios and to reduce the losses that might be caused by climate change, we used climatic estimated data under three new emission scenarios, representative concentration pathways (RCPs) scenarios (RCP2.6 scenario, RCP4.5 scenario, and RCP8.5 scenario). We used the spatially dynamic forest landscape model LANDIS-2, coupled with a forest ecosystem process model PnET-2, to simulate the impact of climate change on aboveground net primary production (ANPP), species' establishment probability (SEP) and aboveground biomass of Moshao forest farm in Huitong Ecological Station, which located in Hunan Province during the period of 2014-2094. The results showed that there were obvious differences in SEP and ANPP among different forest types under changing climate. The degrees of response of SEP to climate change for different forest types were shown as: under RCP2.6 and RCP4.5, artificial coniferous forest>natural broadleaved forest>artificial broadleaved forest. Under RCP8.5, natural broadleaved forest>artificial broadleaved forest>artificial coniferous forest. The degrees of response of ANPP to climate change for different forest types were shown as: under RCP2.6, artificial broadleaved forest> natural broadleaved forest>artificial coniferous forest. Under RCP4.5 and RCP8.5, natural broadleaved forest>artificial broadleaved forest>artificial coniferous forest. The aboveground biomass of the artificial coniferous forest would decline at about 2050, but the natural broadleaved forest and artificial broadleaved forest showed a rising trend in general. During the period of 2014-2094, the total aboveground biomass under RCP2.6, RCP4.5 and RCP8.5 scenarios increased by 68.2%, 79.3% and 72.6%, respectively. The total aboveground biomass under various climatic scenarios sort as: RCP4.5>RCP8.5>RCP2.6. We thought that an appropriate temperature might be beneficial to the biomass accumulation in this study area. However, overextended temperature might hinder the sustainable development of forest production and ecological function.

Soil Moisture Limitations on Monitoring Boreal Forest Regrowth Using Spaceborne L-Band SAR Data

NASA Technical Reports Server (NTRS)

Kasischke, Eric S.; Tanase, Mihai A.; Bourgeau-Chavez, Laura L.; Borr, Matthew

2011-01-01

A study was carried out to investigate the utility of L-band SAR data for estimating aboveground biomass in sites with low levels of vegetation regrowth. Data to estimate biomass were collected from 59 sites located in fire-disturbed black spruce forests in interior Alaska. PALSAR L-band data (HH and HV polarizations) collected on two dates in the summer/fall of 2007 and one date in the summer of 2009 were used. Significant linear correlations were found between the log of aboveground biomass (range of 0.02 to 22.2 t ha-1) and (L-HH) and (L-HV) for the data collected on each of the three dates, with the highest correlation found using the LHV data collected when soil moisture was highest. Soil moisture, however, did change the correlations between L-band and aboveground biomass, and the analyses suggest that the influence of soil moisture is biomass dependent. The results indicate that to use L-band SAR data for mapping aboveground biomass and monitoring forest regrowth will require development of approaches to account for the influence that variations in soil moisture have on L-band microwave backscatter, which can be particularly strong when low levels of aboveground biomass occur

Methods and equations for estimating aboveground volume, biomass, and carbon for trees in the U.S. forest inventory, 2010

Treesearch

Christopher W. Woodall; Linda S. Heath; Grant M. Domke; Michael C. Nichols

2011-01-01

The U.S. Forest Service, Forest Inventory and Analysis (FIA) program uses numerous models and associated coefficients to estimate aboveground volume, biomass, and carbon for live and standing dead trees for most tree species in forests of the United States. The tree attribute models are coupled with FIA's national inventory of sampled trees to produce estimates of...

Identifying aboveground wood fiber potentials in New York State

Treesearch

Eric H. Wharton

1984-01-01

New York forests are made up of more than just the growing stock that is measured during conventional forest inventories. A biomass inventory, completed in 1980, showed that New York commercial forest lands contain nearly 1,164.4 million green tons of aboveground tree biomass, or an average of 75.6 green tons per acre. Conventional growing stock accounted for 57...

Statistical rigor in LiDAR-assisted estimation of aboveground forest biomass

Treesearch

Timothy G. Gregoire; Erik Næsset; Ronald E. McRoberts; Göran Ståhl; Hans Andersen; Terje Gobakken; Liviu Ene; Ross Nelson

2016-01-01

For many decades remotely sensed data have been used as a source of auxiliary information when conducting regional or national surveys of forest resources. In the past decade, airborne scanning LiDAR (Light Detection and Ranging) has emerged as a promising tool for sample surveys aimed at improving estimation of aboveground forest biomass. This technology is now...

Allometric Equations for Aboveground and Belowground Biomass Estimations in an Evergreen Forest in Vietnam.

PubMed

Nam, Vu Thanh; van Kuijk, Marijke; Anten, Niels P R

2016-01-01

Allometric regression models are widely used to estimate tropical forest biomass, but balancing model accuracy with efficiency of implementation remains a major challenge. In addition, while numerous models exist for aboveground mass, very few exist for roots. We developed allometric equations for aboveground biomass (AGB) and root biomass (RB) based on 300 (of 45 species) and 40 (of 25 species) sample trees respectively, in an evergreen forest in Vietnam. The biomass estimations from these local models were compared to regional and pan-tropical models. For AGB we also compared local models that distinguish functional types to an aggregated model, to assess the degree of specificity needed in local models. Besides diameter at breast height (DBH) and tree height (H), wood density (WD) was found to be an important parameter in AGB models. Existing pan-tropical models resulted in up to 27% higher estimates of AGB, and overestimated RB by nearly 150%, indicating the greater accuracy of local models at the plot level. Our functional group aggregated local model which combined data for all species, was as accurate in estimating AGB as functional type specific models, indicating that a local aggregated model is the best choice for predicting plot level AGB in tropical forests. Finally our study presents the first allometric biomass models for aboveground and root biomass in forests in Vietnam.

Allometric Equations for Aboveground and Belowground Biomass Estimations in an Evergreen Forest in Vietnam

PubMed Central

Nam, Vu Thanh; van Kuijk, Marijke; Anten, Niels P. R.

2016-01-01

Allometric regression models are widely used to estimate tropical forest biomass, but balancing model accuracy with efficiency of implementation remains a major challenge. In addition, while numerous models exist for aboveground mass, very few exist for roots. We developed allometric equations for aboveground biomass (AGB) and root biomass (RB) based on 300 (of 45 species) and 40 (of 25 species) sample trees respectively, in an evergreen forest in Vietnam. The biomass estimations from these local models were compared to regional and pan-tropical models. For AGB we also compared local models that distinguish functional types to an aggregated model, to assess the degree of specificity needed in local models. Besides diameter at breast height (DBH) and tree height (H), wood density (WD) was found to be an important parameter in AGB models. Existing pan-tropical models resulted in up to 27% higher estimates of AGB, and overestimated RB by nearly 150%, indicating the greater accuracy of local models at the plot level. Our functional group aggregated local model which combined data for all species, was as accurate in estimating AGB as functional type specific models, indicating that a local aggregated model is the best choice for predicting plot level AGB in tropical forests. Finally our study presents the first allometric biomass models for aboveground and root biomass in forests in Vietnam. PMID:27309718

Modeling loblolly pine aboveground live biomass in a mature pine-hardwood stand: a cautionary tale

Treesearch

D. C. Bragg

2011-01-01

Carbon sequestration in forests is a growing area of interest for researchers and land managers. Calculating the quantity of carbon stored in forest biomass seems to be a straightforward task, but it is highly dependent on the function(s) used to construct the stand. For instance, there are a number of possible equations to predict aboveground live biomass for loblolly...

Developing a Carbon Monitoring System For Pinyon-juniper Forests and Woodlands

NASA Astrophysics Data System (ADS)

Falkowski, M. J.; Hudak, A. T.; Fekety, P.; Filippelli, S.

2017-12-01

Pinyon-juniper (PJ) forests and woodlands are the third largest vegetation type in the United States. They cover over 40 million hectares across the western US, representing 40% of the total forest and woodland area in the Intermountain West. Although the density of carbon stored in these ecosystems is relatively low compared to other forest types, the vast area of short stature forests and woodlands (both nationally and globally) make them critical components of regional, national, and global carbon budgets. The overarching goal of this research is to prototype a carbon monitoring, reporting, and verification (MRV) system for characterizing total aboveground biomass stocks and flux across the PJ vegetation gradient in the western United States. We achieve this by combining in situ forest measurements and novel allometric equations with tree measurements derived from high resolution airborne imagery to map aboveground biomass across 500,000 km2 in the Western US. These high-resolution maps of aboveground biomass are then leveraged as training data to predict biomass flux through time from Landsat time-series data. The results from this research highlight the potential in mapping biomass stocks and flux in open forests and woodlands, and could be easily adopted into an MRV framework.

Estimating aboveground tree biomass on forest land in the Pacific Northwest: a comparison of approaches

Treesearch

Xiaoping Zhou; Miles A. Hemstrom

2009-01-01

Live tree biomass estimates are essential for carbon accounting, bioenergy feasibility studies, and other analyses. Several models are currently used for estimating tree biomass. Each of these incorporates different calculation methods that may significantly impact the estimates of total aboveground tree biomass, merchantable biomass, and carbon pools. Consequently,...

Compatible above-ground biomass equations and carbon stock estimation for small diameter Turkish pine (Pinus brutia Ten.).

PubMed

Sakici, Oytun Emre; Kucuk, Omer; Ashraf, Muhammad Irfan

2018-04-15

Small trees and saplings are important for forest management, carbon stock estimation, ecological modeling, and fire management planning. Turkish pine (Pinus brutia Ten.) is a common coniferous species and comprises 25.1% of total forest area of Turkey. Turkish pine is also important due to its flammable fuel characteristics. In this study, compatible above-ground biomass equations were developed to predict needle, branch, stem wood, and above-ground total biomass, and carbon stock assessment was also described for Turkish pine which is smaller than 8 cm diameter at breast height or shorter than breast height. Compatible biomass equations are useful for biomass prediction of small diameter individuals of Turkish pine. These equations will also be helpful in determining fire behavior characteristics and calculating their carbon stock. Overall, present study will be useful for developing ecological models, forest management plans, silvicultural plans, and fire management plans.

Validation databases for simulation models: aboveground biomass and net primary productive, (NPP) estimation using eastwide FIA data

Treesearch

Jennifer C. Jenkins; Richard A. Birdsey

2000-01-01

As interest grows in the role of forest growth in the carbon cycle, and as simulation models are applied to predict future forest productivity at large spatial scales, the need for reliable and field-based data for evaluation of model estimates is clear. We created estimates of potential forest biomass and annual aboveground production for the Chesapeake Bay watershed...

Evaluating Site-Specific and Generic Spatial Models of Aboveground Forest Biomass Based on Landsat Time-Series and LiDAR Strip Samples in the Eastern USA

Treesearch

Ram Deo; Matthew Russell; Grant Domke; Hans-Erik Andersen; Warren Cohen; Christopher Woodall

2017-01-01

Large-area assessment of aboveground tree biomass (AGB) to inform regional or national forest monitoring programs can be efficiently carried out by combining remotely sensed data and field sample measurements through a generic statistical model, in contrast to site-specific models. We integrated forest inventory plot data with spatial predictors from Landsat time-...

Consequences of long-term severe industrial pollution for aboveground carbon and nitrogen pools in northern taiga forests at local and regional scales.

PubMed

Manninen, Sirkku; Zverev, Vitali; Bergman, Igor; Kozlov, Mikhail V

2015-12-01

Boreal coniferous forests act as an important sink for atmospheric carbon dioxide. The overall tree carbon (C) sink in the forests of Europe has increased during the past decades, especially due to management and elevated nitrogen (N) deposition; however, industrial atmospheric pollution, primarily sulphur dioxide and heavy metals, still negatively affect forest biomass production at different spatial scales. We report local and regional changes in forest aboveground biomass, C and N concentrations in plant tissues, and C and N pools caused by long-term atmospheric emissions from a large point source, the nickel-copper smelter in Monchegorsk, in north-western Russia. An increase in pollution load (assessed as Cu concentration in forest litter) caused C to increase in foliage but C remained unchanged in wood, while N decreased in foliage and increased in wood, demonstrating strong effects of pollution on resource translocation between green and woody tissues. The aboveground C and N pools were primarily governed by plant biomass, which strongly decreased with an increase in pollution load. In our study sites (located 1.6-39.7 km from the smelter) living aboveground plant biomass was 76 to 4888 gm(-2), and C and N pools ranged 35-2333 g C m(-2) and 0.5-35.1 g N m(-2), respectively. We estimate that the aboveground plant biomass is reduced due to chronic exposure to industrial air pollution over an area of about 107,200 km2, and the total (aboveground and belowground) loss of phytomass C stock amounts to 4.24×10(13) g C. Our results emphasize the need to account for the overall impact of industrial polluters on ecosystem C and N pools when assessing the C and N dynamics in northern boreal forests because of the marked long-term negative effects of their emissions on structure and productivity of plant communities. Copyright © 2015 Elsevier B.V. All rights reserved.

Environmental and biotic controls over aboveground biomass throughout a tropical rainforest

Treesearch

G.P. Asner; R.F. Hughes; T.A. Varga; D.E. Knapp; T. Kennedy-Bowdoin

2009-01-01

The environmental and biotic factors affecting spatial variation in canopy three-dimensional (3-D) structure and aboveground tree biomass (AGB) are poorly understood in tropical rain forests. We combined field measurements and airborne light detection and ranging (lidar) to quantify 3-D structure and AGB across a 5,016 ha rain forest reserve on the...

Biomass statistics for Vermont - 1983

Treesearch

Thomas S. Frieswyk; Anne M. Malley

1986-01-01

A new measure of the forest resource has been added to the fourth forest inventory of Vermont. The inventory, which was conducted in 1982-83, included estimates of aboveground tree biomass on timberland. There are approximately 413 million green tons of wood and bark in the aboveground portion of all trees, which equates to an average of 93 green tons per acre...

Satellite detection of land-use change and effects on regional forest aboveground biomass estimates

Treesearch

Daolan Zheng; Linda S. Heath; Mark J. Ducey

2008-01-01

We used remote-sensing-driven models to detect land-cover change effects on forest aboveground biomass (AGB) density (Mg·ha−1, dry weight) and total AGB (Tg) in Minnesota, Wisconsin, and Michigan USA, between the years 1992-2001, and conducted an evaluation of the approach. Inputs included remotely-sensed 1992 reflectance data...

Combining satellite lidar, airborne lidar, and ground plots to estimate the amount and distribution of aboveground biomass in the boreal forest of North America 1

Treesearch

Hank A. Margolis; Ross F. Nelson; Paul M. Montesano; André Beaudoin; Guoqing Sun; Hans-Erik Andersen; Michael A. Wulder

2015-01-01

We report estimates of the amount, distribution, and uncertainty of aboveground biomass (AGB) of the different ecoregions and forest land cover classes within the North American boreal forest, analyze the factors driving the error estimates, and compare our estimates with other reported values. A three-phase sampling strategy was used (i) to tie ground plot AGB to...

Using landsat time-series and lidar to inform aboveground carbon baseline estimation in Minnesota

Treesearch

Ram K. Deo; Grant M. Domke; Matthew B. Russell; Christopher W. Woodall; Michael J. Falkowski

2015-01-01

Landsat data has long been used to support forest monitoring and management decisions despite the limited success of passive optical remote sensing for accurate estimation of structural attributes such as aboveground biomass. The archive of publicly available Landsat images dating back to the 1970s can be used to predict historic forest biomass dynamics. In addition,...

Biomass statistics for New Hampshire - 1983

Treesearch

Thomas S. Frieswyk; Anne M. Malley

1986-01-01

A new measure of the forest resource has been added to the fourth forest inventory of New Hampshire. The inventory, which was conducted in 1982-83, included estimates of aboveground tree biomass on timberland. There are approximately 502 million green tons of wood and bark in the aboveground portion of all trees, or 104 green tons per acre. Fifty-five percent or 275...

Amazon forest carbon dynamics predicted by profiles of canopy leaf area and light environment

Treesearch

S. C. Stark; V. Leitold; J. L. Wu; M. O. Hunter; C. V. de Castilho; F. R. C. Costa; S. M. McMahon; G. G. Parker; M. Takako Shimabukuro; M. A. Lefsky; M. Keller; L. F. Alves; J. Schietti; Y. E. Shimabukuro; D. O. Brandao; T. K. Woodcock; N. Higuchi; P. B de Camargo; R. C. de Oliveira; S. R. Saleska

2012-01-01

Tropical forest structural variation across heterogeneous landscapes may control above-ground carbon dynamics. We tested the hypothesis that canopy structure (leaf area and light availability) – remotely estimated from LiDAR – control variation in above-ground coarse wood production (biomass growth). Using a statistical model, these factors predicted biomass growth...

Forest Aboveground Biomass Estimation in the Greater Mekong, Subregion and Russian Siberia

NASA Astrophysics Data System (ADS)

Pang, Yong; Li, Zengyuan; Sun, Gouqing; Zhang, Zhiyu; Schmullius, Christiane; Meng, Shili; Ma, Zhenyu; Lu, Hao; Li, Shiming; Liu, Qingwang; Bai, Lina; Tian, Xin

2016-08-01

Forests play a vital role in sustainable development and provide a range of economic, social and environmental benefits, including essential ecosystem services such as climate change mitigation and adaptation. We summarized works in forest aboveground biomass estimation in Greater Mekong Subregion (GMS) and Russian Siberia (RuS). Both regions are rich in forest resources. These mapping and estimation works were based on multiple-source remote sensing data and some field measurements. Biomass maps were generated at 500 m and 30 m pixel size for RuS and GMS respectively. With the available of the 2015 PALSAR-2 mosaic at 25 m spacing, Sentinel-2 data at 20 m, we will work on the biomass mapping and dynamic study at higher spatial resolution.

Integration of carbon conservation into sustainable forest management using high resolution satellite imagery: A case study in Sabah, Malaysian Borneo

NASA Astrophysics Data System (ADS)

Langner, Andreas; Samejima, Hiromitsu; Ong, Robert C.; Titin, Jupiri; Kitayama, Kanehiro

2012-08-01

Conservation of tropical forests is of outstanding importance for mitigation of climate change effects and preserving biodiversity. In Borneo most of the forests are classified as permanent forest estates and are selectively logged using conventional logging techniques causing high damage to the forest ecosystems. Incorporation of sustainable forest management into climate change mitigation measures such as Reducing Emissions from Deforestation and Forest Degradation (REDD+) can help to avert further forest degradation by synergizing sustainable timber production with the conservation of biodiversity. In order to evaluate the efficiency of such initiatives, monitoring methods for forest degradation and above-ground biomass in tropical forests are urgently needed. In this study we developed an index using Landsat satellite data to describe the crown cover condition of lowland mixed dipterocarp forests. We showed that this index combined with field data can be used to estimate above-ground biomass using a regression model in two permanent forest estates in Sabah, Malaysian Borneo. Tangkulap represented a conventionally logged forest estate while Deramakot has been managed in accordance with sustainable forestry principles. The results revealed that conventional logging techniques used in Tangkulap during 1991 and 2000 decreased the above-ground biomass by an annual amount of average -6.0 t C/ha (-5.2 to -7.0 t C/ha, 95% confidential interval) whereas the biomass in Deramakot increased by 6.1 t C/ha per year (5.3-7.2 t C/ha, 95% confidential interval) between 2000 and 2007 while under sustainable forest management. This indicates that sustainable forest management with reduced-impact logging helps to protect above-ground biomass. In absolute terms, a conservative amount of 10.5 t C/ha per year, as documented using the methodology developed in this study, can be attributed to the different management systems, which will be of interest when implementing REDD+ that rewards the enhancement of carbon stocks.

Using Landsat Time-Series and LiDAR to Inform Aboveground Forest Biomass Baselines in Northern Minnesota, USA

Treesearch

Ram K. Deo; Matthew B. Russell; Grant M. Domke; Christopher W. Woodall; Michael J. Falkowski; Warren B. Cohen

2017-01-01

The publicly accessible archive of Landsat imagery and increasing regional-scale LiDAR acquisitions offer an opportunity to periodically estimate aboveground forest biomass (AGB) from 1990 to the present to alignwith the reporting needs ofNationalGreenhouseGas Inventories (NGHGIs). This study integrated Landsat time-series data, a state-wide LiDAR dataset, and a recent...

Effects of Model Choice and Forest Structure on Inventory-Based Estimations of Puerto Rican Forest Biomass.

Treesearch

THOMAS J. BRANDEIS; MARIA DEL ROCIO SUAREZ ROZO

2005-01-01

Total aboveground live tree biomass in Puerto Rican lower montane wet, subtropical wet, subtropical moist and subtropical dry forests was estimated using data from two forest inventories and published regression equations. Multiple potentially-applicable published biomass models existed for some forested life zones, and their estimates tended to diverge with increasing...

Effects of model choice and forest structure on inventory-based estimations of Puerto Rican forest biomass

Treesearch

Thomas J. Brandeis; Maria Del Rocio; Suarez Rozo

2005-01-01

Total aboveground live tree biomass in Puerto Rican lower montane wet, subtropical wet, subtropical moist and subtropical dry forests was estimated using data from two forest inventories and published regression equations. Multiple potentially-applicable published biomass models existed for some forested life zones, and their estimates tended to diverge with increasing...

Tropical Soil Carbon Stocks do not Reflect Aboveground Forest Biomass Across Geological and Rainfall Gradients

NASA Astrophysics Data System (ADS)

Cusack, D. F.; Markesteijn, L.; Turner, B. L.

2016-12-01

Soil organic carbon (C) dynamics present a large source of uncertainty in global C cycle models, and inhibit our ability to predict effects of climate change. Tropical wet and seasonal forests exert a disproportionate influence on the global C cycle relative to their land area because they are the most C-rich ecosystems on Earth, containing 25-40% of global terrestrial C stocks. While significant advances have been made to map aboveground C stocks in tropical forests, determining soil C stocks using remote sensing technology is still not possible for closed-canopy forests. It is unclear to what extent aboveground C stocks can be used to predict soil C stocks across tropical forests. Here we present 1-m-deep soil organic C stocks for 42 tropical forest sites across rainfall and geological gradients in Panama. We show that soil C stocks do not correspond to aboveground plant biomass or to litterfall productivity in these humid tropical forests. Rather, soil C stocks were strongly and positively predicted by fine root biomass, soil clay content, and rainfall (R2 = 0.47, p < 0.05). Fine root biomass, in turn, was most strongly predicted by total extractable soil base cations (R2 = 0.24, p < 0.05, negative relationship). Our measures of tropical soil C and its relationships with climatic and soil chemical characteristics form an important basis for improving model estimates of soil C stocks and predictions of climate change effects on tropical C storage.

ROOT BIOMASS ALLOCATION IN THE WORLD'S UPLAND FORESTS

EPA Science Inventory

Because the world's forests play a major role in regulating nutrient and carbon cycles, there is much interest in estimating their biomass. Estimates of aboveground biomass based on well-established methods are relatively abundant; estimates of root biomass based on standard meth...

Estimating Above-Ground Carbon Biomass in a Newly Restored Coastal Plain Wetland Using Remote Sensing

PubMed Central

Riegel, Joseph B.; Bernhardt, Emily; Swenson, Jennifer

2013-01-01

Developing accurate but inexpensive methods for estimating above-ground carbon biomass is an important technical challenge that must be overcome before a carbon offset market can be successfully implemented in the United States. Previous studies have shown that LiDAR (light detection and ranging) is well-suited for modeling above-ground biomass in mature forests; however, there has been little previous research on the ability of LiDAR to model above-ground biomass in areas with young, aggrading vegetation. This study compared the abilities of discrete-return LiDAR and high resolution optical imagery to model above-ground carbon biomass at a young restored forested wetland site in eastern North Carolina. We found that the optical imagery model explained more of the observed variation in carbon biomass than the LiDAR model (adj-R2 values of 0.34 and 0.18 respectively; root mean squared errors of 0.14 Mg C/ha and 0.17 Mg C/ha respectively). Optical imagery was also better able to predict high and low biomass extremes than the LiDAR model. Combining both the optical and LiDAR improved upon the optical model but only marginally (adj-R2 of 0.37). These results suggest that the ability of discrete-return LiDAR to model above-ground biomass may be rather limited in areas with young, small trees and that high spatial resolution optical imagery may be the better tool in such areas. PMID:23840837

Biomass distribution and productivity of Pinus edulis-Juniperus monosperma woodlands of north-central Arizona

Treesearch

Charles C. Grier; Katherine J. Elliott; Deborah G. McCullough

1992-01-01

Above-ground biomass distribution, leaf area, above-ground net primary productivity and foliage characteristics were determined for 90- and 350-year-old Pinus edulis-Juniperus monosperma ecosystems on the Colorado Plateau of northern Arizona. These ecosystems have low biomass, leaf area and primary productivity compared with forests in wetter...

Predicting Biomass of Understory Stems in the Miississipi and Alabama Coastal Plains

Treesearch

B.L. Franchi; I.W. Savelle; W.F. Watson; B.J. Stokes

1984-01-01

Understory forest biomass is becoming an important source of industrial fuelwood. Up to 40 tons per acre of above-ground biomass may be present in the understory of Southern pine stands. The above-ground portion is the only portion of the tree that can be harvested economically for fuel.

A comparison of two above-ground biomass estimation techniques integrating satellite-based remotely sensed data and ground data for tropical and semiarid forests in Puerto Rico

NASA Astrophysics Data System (ADS)

Iiames, J. S.; Riegel, J.; Lunetta, R.

2013-12-01

Two above-ground forest biomass estimation techniques were evaluated for the United States Territory of Puerto Rico using predictor variables acquired from satellite based remotely sensed data and ground data from the U.S. Department of Agriculture Forest Inventory Analysis (FIA) program. The U.S. Environmental Protection Agency (EPA) estimated above-ground forest biomass implementing methodology first posited by the Woods Hole Research Center developed for conterminous United States (National Biomass and Carbon Dataset [NBCD2000]). For EPA's effort, spatial predictor layers for above-ground biomass estimation included derived products from the U.S. Geologic Survey (USGS) National Land Cover Dataset 2001 (NLCD) (landcover and canopy density), the USGS Gap Analysis Program (forest type classification), the USGS National Elevation Dataset, and the NASA Shuttle Radar Topography Mission (tree heights). In contrast, the U.S. Forest Service (USFS) biomass product integrated FIA ground-based data with a suite of geospatial predictor variables including: (1) the Moderate Resolution Imaging Spectrometer (MODIS)-derived image composites and percent tree cover; (2) NLCD land cover proportions; (3) topographic variables; (4) monthly and annual climate parameters; and (5) other ancillary variables. Correlations between both data sets were made at variable watershed scales to test level of agreement. Notice: This work is done in support of EPA's Sustainable Healthy Communities Research Program. The U.S EPA funded and conducted the research described in this paper. Although this work was reviewed by the EPA and has been approved for publication, it may not necessarily reflect official Agency policy. Mention of any trade names or commercial products does not constitute endorsement or recommendation for use.

Allometric Scaling and Resource Limitations Model of Total Aboveground Biomass in Forest Stands: Site-scale Test of Model

NASA Astrophysics Data System (ADS)

CHOI, S.; Shi, Y.; Ni, X.; Simard, M.; Myneni, R. B.

2013-12-01

Sparseness in in-situ observations has precluded the spatially explicit and accurate mapping of forest biomass. The need for large-scale maps has raised various approaches implementing conjugations between forest biomass and geospatial predictors such as climate, forest type, soil property, and topography. Despite the improved modeling techniques (e.g., machine learning and spatial statistics), a common limitation is that biophysical mechanisms governing tree growth are neglected in these black-box type models. The absence of a priori knowledge may lead to false interpretation of modeled results or unexplainable shifts in outputs due to the inconsistent training samples or study sites. Here, we present a gray-box approach combining known biophysical processes and geospatial predictors through parametric optimizations (inversion of reference measures). Total aboveground biomass in forest stands is estimated by incorporating the Forest Inventory and Analysis (FIA) and Parameter-elevation Regressions on Independent Slopes Model (PRISM). Two main premises of this research are: (a) The Allometric Scaling and Resource Limitations (ASRL) theory can provide a relationship between tree geometry and local resource availability constrained by environmental conditions; and (b) The zeroth order theory (size-frequency distribution) can expand individual tree allometry into total aboveground biomass at the forest stand level. In addition to the FIA estimates, two reference maps from the National Biomass and Carbon Dataset (NBCD) and U.S. Forest Service (USFS) were produced to evaluate the model. This research focuses on a site-scale test of the biomass model to explore the robustness of predictors, and to potentially improve models using additional geospatial predictors such as climatic variables, vegetation indices, soil properties, and lidar-/radar-derived altimetry products (or existing forest canopy height maps). As results, the optimized ASRL estimates satisfactorily resemble the FIA aboveground biomass in terms of data distribution, overall agreement, and spatial similarity across scales. Uncertainties are quantified (ranged from 0.2 to 0.4) by taking into account the spatial mismatch (FIA plot vs. PRISM grid), heterogeneity (species composition), and an example bias scenario (= 0.2) in the root system extents.

Stand restoration burning in oak-pine forests in the southern Applachians: effects on aboveground biomass and carbon and nitrogen cycling

Treesearch

Robert M. Hubbard; James M. Vose; Barton D. Clinton; Katherine J. Elliott; Jennifer D. Knoepp

2004-01-01

Understory prescribed burning is being suggested as a viable management tool for restoring degraded oak–pine forest communities in the southern Appalachians yet information is lacking on how this will affect ecosystem processes. Our objectives in this study were to evaluate the watershed scale effects of understory burning on total aboveground biomass, and the carbon...

Lidar-based estimates of aboveground biomass in the continental US and Mexico using ground, airborne, and satellite observations

Treesearch

Ross Nelson; Hank Margolis; Paul Montesano; Guoqing Sun; Bruce Cook; Larry Corp; Hans-Erik Andersen; Ben deJong; Fernando Paz Pellat; Thaddeus Fickel; Jobriath Kauffman; Stephen Prisley

2017-01-01

Existing national forest inventory plots, an airborne lidar scanning (ALS) system, and a space profiling lidar system (ICESat-GLAS) are used to generate circa 2005 estimates of total aboveground dry biomass (AGB) in forest strata, by state, in the continental United States (CONUS) and Mexico. The airborne lidar is used to link ground observations of AGB to space lidar...

Integrating LIDAR and forest inventories to fill the trees outside forests data gap

Treesearch

Kristofer D. Johnson; Richard Birdsey; Jason Cole; Anu Swatantran; Jarlath O' Neil-Dunne; Ralph Dubayah; Andrew Lister

2015-01-01

Forest inventories are commonly used to estimate total tree biomass of forest land even though they are not traditionally designed to measure biomass of trees outside forests (TOF). The consequence may be an inaccurate representation of all of the aboveground biomass, which propagates error to the outputs of spatial and process models that rely on the inventory data....

Measuring carbon in forests: current status and future challenges.

PubMed

Brown, Sandra

2002-01-01

To accurately and precisely measure the carbon in forests is gaining global attention as countries seek to comply with agreements under the UN Framework Convention on Climate Change. Established methods for measuring carbon in forests exist, and are best based on permanent sample plots laid out in a statistically sound design. Measurements on trees in these plots can be readily converted to aboveground biomass using either biomass expansion factors or allometric regression equations. A compilation of existing root biomass data for upland forests of the world generated a significant regression equation that can be used to predict root biomass based on aboveground biomass only. Methods for measuring coarse dead wood have been tested in many forest types, but the methods could be improved if a non-destructive tool for measuring the density of dead wood was developed. Future measurements of carbon storage in forests may rely more on remote sensing data, and new remote data collection technologies are in development.

Above ground biomass and tree species richness estimation with airborne lidar in tropical Ghana forests

NASA Astrophysics Data System (ADS)

Vaglio Laurin, Gaia; Puletti, Nicola; Chen, Qi; Corona, Piermaria; Papale, Dario; Valentini, Riccardo

2016-10-01

Estimates of forest aboveground biomass are fundamental for carbon monitoring and accounting; delivering information at very high spatial resolution is especially valuable for local management, conservation and selective logging purposes. In tropical areas, hosting large biomass and biodiversity resources which are often threatened by unsustainable anthropogenic pressures, frequent forest resources monitoring is needed. Lidar is a powerful tool to estimate aboveground biomass at fine resolution; however its application in tropical forests has been limited, with high variability in the accuracy of results. Lidar pulses scan the forest vertical profile, and can provide structure information which is also linked to biodiversity. In the last decade the remote sensing of biodiversity has received great attention, but few studies focused on the use of lidar for assessing tree species richness in tropical forests. This research aims at estimating aboveground biomass and tree species richness using discrete return airborne lidar in Ghana forests. We tested an advanced statistical technique, Multivariate Adaptive Regression Splines (MARS), which does not require assumptions on data distribution or on the relationships between variables, being suitable for studying ecological variables. We compared the MARS regression results with those obtained by multilinear regression and found that both algorithms were effective, but MARS provided higher accuracy either for biomass (R2 = 0.72) and species richness (R2 = 0.64). We also noted strong correlation between biodiversity and biomass field values. Even if the forest areas under analysis are limited in extent and represent peculiar ecosystems, the preliminary indications produced by our study suggest that instrument such as lidar, specifically useful for pinpointing forest structure, can also be exploited as a support for tree species richness assessment.

Tree allometry and improved estimation of carbon stocks and balance in tropical forests.

PubMed

Chave, J; Andalo, C; Brown, S; Cairns, M A; Chambers, J Q; Eamus, D; Fölster, H; Fromard, F; Higuchi, N; Kira, T; Lescure, J-P; Nelson, B W; Ogawa, H; Puig, H; Riéra, B; Yamakura, T

2005-08-01

Tropical forests hold large stores of carbon, yet uncertainty remains regarding their quantitative contribution to the global carbon cycle. One approach to quantifying carbon biomass stores consists in inferring changes from long-term forest inventory plots. Regression models are used to convert inventory data into an estimate of aboveground biomass (AGB). We provide a critical reassessment of the quality and the robustness of these models across tropical forest types, using a large dataset of 2,410 trees >or= 5 cm diameter, directly harvested in 27 study sites across the tropics. Proportional relationships between aboveground biomass and the product of wood density, trunk cross-sectional area, and total height are constructed. We also develop a regression model involving wood density and stem diameter only. Our models were tested for secondary and old-growth forests, for dry, moist and wet forests, for lowland and montane forests, and for mangrove forests. The most important predictors of AGB of a tree were, in decreasing order of importance, its trunk diameter, wood specific gravity, total height, and forest type (dry, moist, or wet). Overestimates prevailed, giving a bias of 0.5-6.5% when errors were averaged across all stands. Our regression models can be used reliably to predict aboveground tree biomass across a broad range of tropical forests. Because they are based on an unprecedented dataset, these models should improve the quality of tropical biomass estimates, and bring consensus about the contribution of the tropical forest biome and tropical deforestation to the global carbon cycle.

Global-scale impacts of nitrogen deposition on tree carbon sequestration in tropical, temperate, and boreal forests: A meta-analysis.

PubMed

Schulte-Uebbing, Lena; de Vries, Wim

2018-02-01

Elevated nitrogen (N) deposition may increase net primary productivity in N-limited terrestrial ecosystems and thus enhance the terrestrial carbon (C) sink. To assess the magnitude of this N-induced C sink, we performed a meta-analysis on data from forest fertilization experiments to estimate N-induced C sequestration in aboveground tree woody biomass, a stable C pool with long turnover times. Our results show that boreal and temperate forests responded strongly to N addition and sequestered on average an additional 14 and 13 kg C per kg N in aboveground woody biomass, respectively. Tropical forests, however, did not respond significantly to N addition. The common hypothesis that tropical forests do not respond to N because they are phosphorus-limited could not be confirmed, as we found no significant response to phosphorus addition in tropical forests. Across climate zones, we found that young forests responded more strongly to N addition, which is important as many previous meta-analyses of N addition experiments rely heavily on data from experiments on seedlings and young trees. Furthermore, the C-N response (defined as additional mass unit of C sequestered per additional mass unit of N addition) was affected by forest productivity, experimental N addition rate, and rate of ambient N deposition. The estimated C-N responses from our meta-analysis were generally lower that those derived with stoichiometric scaling, dynamic global vegetation models, and forest growth inventories along N deposition gradients. We estimated N-induced global C sequestration in tree aboveground woody biomass by multiplying the C-N responses obtained from the meta-analysis with N deposition estimates per biome. We thus derived an N-induced global C sink of about 177 (112-243) Tg C/year in aboveground and belowground woody biomass, which would account for about 12% of the forest biomass C sink (1,400 Tg C/year). © 2017 John Wiley & Sons Ltd.

Study on forest above-ground biomass synergy inversion from GLAS and HJ-1 data

NASA Astrophysics Data System (ADS)

Fang, Zhou; Cao, Chunxiang; Ji, Wei; Xu, Min; Chen, Wei

2012-10-01

The need exists to develop a systematic approach to inventory and monitor global forests, both for carbon stock evaluation and for land use change analysis. The use of freely available satellite-based data for carbon stock estimation mitigates both the cost and the spatial limitations of field-based techniques. Spaceborne lidar data have been demonstrated as useful for forest aboveground biomass (AGB) estimation over a wide range of biomass values and forest types. However, the application of these data is limited because of their spatially discrete nature. Spaceborne multispectral sensors have been used extensively to estimate AGB, but these methods have been demonstrated as inappropriate for forest structure characterization in high-biomass mature forests. This study uses an integration of ICESat Geospatial Laser Altimeter System (GLAS) lidar and HJ-1 satellites data to develop methods to estimate AGB in an area of Qilian Mountains, Northwest China. Considering the study area belongs to mountainous terrain, the difficulties of this article are how to extract canopy height from GLAS waveform metrics. Combining with HJ-1 data and ground survey data of the study area, we establish forest biomass estimation model for the GLAS data based on BP neural network model. In order to estimate AGB, the training sample data includes the canopy height extracted from GLAS, LAI, vegetation coverage and several kinds of vegetation indices from HJ-1 data. The results of forest aboveground biomass are very close to the fields measured results, and are consistent with land cover data in the spatial distribution.

Predicting small-diameter loblolly pine aboveground biomass in naturally regenerated stands

Treesearch

Kristin M. McElligott; Don C. Bragg; Jamie L. Schuler

2015-01-01

There is growing interest in managing southern pine forests for both carbon sequestration and bioenergy. For instance, thinning otherwise unmerchantable trees in naturally regenerated pine-dominated forests should generate biomass without conflicting with more traditional forest products. However, we lack the tools to accurately quantify the biomass in these...

Quantifying the coarse-root biomass of intensively managed loblolly pine plantations

Treesearch

Ashley T. Miller; H. Lee Allen; Chris A. Maier

2006-01-01

Most of the carbon accumulation during a forest rotation is in plant biomass and the forest floor. Most of the belowground biomass in older loblolly pine (Pinus taeda L.) forests is in coarse roots, and coarse roots persist longer after harvest than aboveground biomass and fine roots. The main objective was to assess the carbon accumulation in coarse...

Quantifying the coarse-root biomass of intensively managed loblolly pine plantations

Treesearch

Ashley T. Miller; H. Lee Allen; Chris A. Maier

2006-01-01

Most of the carbon accumulation during a forest rotation is in plant biomass and the forest floor. Most of the belowground biomass in older loblolly pine (Pinus taeda L.) forests is in coarse roots, and coarse roots ersist longer after harvest than aboveground biomass and fine oots. The main objective was to assess the carbon accumulation in coarse...

Aboveground biomass variability across intact and degraded forests in the Brazilian Amazon

Treesearch

Marcos Longo; Michael Keller; Maiza N. dos-Santos; Veronika Leitold; Ekena R. Pinagé; Alessandro Baccini; Sassan Saatchi; Euler M. Nogueira; Mateus Batistella; Douglas C. Morton

2016-01-01

Deforestation rates have declined in the Brazilian Amazon since 2005, yet degradation from logging, fire, and fragmentation has continued in frontier forests. In this study we quantified the aboveground carbon density (ACD) in intact and degraded forests using the largest data set of integrated forest inventory plots (n = 359) and airborne lidar data (18,000 ha)...

Improving Lidar-based Aboveground Biomass Estimation with Site Productivity for Central Hardwood Forests, USA

NASA Astrophysics Data System (ADS)

Shao, G.; Gallion, J.; Fei, S.

2016-12-01

Sound forest aboveground biomass estimation is required to monitor diverse forest ecosystems and their impacts on the changing climate. Lidar-based regression models provided promised biomass estimations in most forest ecosystems. However, considerable uncertainties of biomass estimations have been reported in the temperate hardwood and hardwood-dominated mixed forests. Varied site productivities in temperate hardwood forests largely diversified height and diameter growth rates, which significantly reduced the correlation between tree height and diameter at breast height (DBH) in mature and complex forests. It is, therefore, difficult to utilize height-based lidar metrics to predict DBH-based field-measured biomass through a simple regression model regardless the variation of site productivity. In this study, we established a multi-dimension nonlinear regression model incorporating lidar metrics and site productivity classes derived from soil features. In the regression model, lidar metrics provided horizontal and vertical structural information and productivity classes differentiated good and poor forest sites. The selection and combination of lidar metrics were discussed. Multiple regression models were employed and compared. Uncertainty analysis was applied to the best fit model. The effects of site productivity on the lidar-based biomass model were addressed.

Assessment of forest nutrient pools in view of biomass potentials - a case study from Austria oak stands

NASA Astrophysics Data System (ADS)

Yan, S.; Bruckman, V. J.; Glatzel, G.; Hochbichler, E.

2012-04-01

As one of the renewable energy forms, bio-energy could help to relieve the pressure which is caused by growing global energy demand. In Austria, large area of forests, traditional utilization of biomass and people's desire to live in a sound environment have supported the positive development of bio-energy. Soil nutrient status is in principle linked with the productivity of the aboveground biomass. This study focuses on K, Ca and Mg pools in soils and aboveground biomass in order to learn more on the temporal dynamics of plant nutrients as indicators for biomass potentials in Quercus dominated forests in northeastern Austria. Three soil types (according to WRB: eutric cambisol, calcic chernozem and haplic luvisol) were considered representative for the area and sampled. We selected nine Quercus petraea dominated permanent plots for this study. Exchangeable cations K, Ca and Mg in the soils were quantified in our study plots. Macronutrients pools of K, Ca and Mg in aboveground biomass were calculated according to inventory data and literature review. The exchangeable cations pool in the top 50 cm of the soil were 882 - 1,652 kg ha-1 for K, 2,661 to 16,510 kg ha-1 for Ca and 320 - 1,850 kg ha-1 for Mg. The nutrient pool in aboveground biomass ranged from 29 to 181 kg ha-1 for K, from 56 to 426 kg ha-1 for Ca and from 4 to 26 kg ha-1 for Mg. The underground exchangeable pools of K, Ca and Mg are generally 10, 22 and 58 times higher than aboveground biomass nutrient pools. Our results showed that the nutrient pools in the mineral soil are sufficient to support the tree growth. The levels of soil nutrients in particular K, Ca and Mg in our study areas are reasonably high and do not indicate the necessity for additional fertilization under current silvicultural practices and biomass extraction rate. The forest in our study areas is in favorable condition to supply biomass as raw material for energy utilization.

Tree height and tropical forest biomass estimation

Treesearch

M.O. Hunter; M. Keller; D. Vitoria; D.C. Morton

2013-01-01

Tropical forests account for approximately half of above-ground carbon stored in global vegetation. However, uncertainties in tropical forest carbon stocks remain high because it is costly and laborious to quantify standing carbon stocks. Carbon stocks of tropical forests are determined using allometric relations between tree stem diameter and height and biomass....

Efficacy of generic allometric equations for estimating biomass: a test in Japanese natural forests.

PubMed

Ishihara, Masae I; Utsugi, Hajime; Tanouchi, Hiroyuki; Aiba, Masahiro; Kurokawa, Hiroko; Onoda, Yusuke; Nagano, Masahiro; Umehara, Toru; Ando, Makoto; Miyata, Rie; Hiura, Tsutom

2015-07-01

Accurate estimation of tree and forest biomass is key to evaluating forest ecosystem functions and the global carbon cycle. Allometric equations that estimate tree biomass from a set of predictors, such as stem diameter and tree height, are commonly used. Most allometric equations are site specific, usually developed from a small number of trees harvested in a small area, and are either species specific or ignore interspecific differences in allometry. Due to lack of site-specific allometries, local equations are often applied to sites for which they were not originally developed (foreign sites), sometimes leading to large errors in biomass estimates. In this study, we developed generic allometric equations for aboveground biomass and component (stem, branch, leaf, and root) biomass using large, compiled data sets of 1203 harvested trees belonging to 102 species (60 deciduous angiosperm, 32 evergreen angiosperm, and 10 evergreen gymnosperm species) from 70 boreal, temperate, and subtropical natural forests in Japan. The best generic equations provided better biomass estimates than did local equations that were applied to foreign sites. The best generic equations included explanatory variables that represent interspecific differences in allometry in addition to stem diameter, reducing error by 4-12% compared to the generic equations that did not include the interspecific difference. Different explanatory variables were selected for different components. For aboveground and stem biomass, the best generic equations had species-specific wood specific gravity as an explanatory variable. For branch, leaf, and root biomass, the best equations had functional types (deciduous angiosperm, evergreen angiosperm, and evergreen gymnosperm) instead of functional traits (wood specific gravity or leaf mass per area), suggesting importance of other traits in addition to these traits, such as canopy and root architecture. Inclusion of tree height in addition to stem diameter improved the performance of the generic equation only for stem biomass and had no apparent effect on aboveground, branch, leaf, and root biomass at the site level. The development of a generic allometric equation taking account of interspecific differences is an effective approach for accurately estimating aboveground and component biomass in boreal, temperate, and subtropical natural forests.

Estimates of forest canopy height and aboveground biomass using ICESat.

Treesearch

Michael A. Lefsky; David J. Harding; Michael Keller; Warren B. Cohen; Claudia C. Carabajal; Fernando Del Bom Espirito-Santo; Maria O. Hunter; Raimundo de Oliveira Jr.

2005-01-01

Exchange of carbon between forests and the atmosphere is a vital component of the global carbon cycle. Satellite laser altimetry has a unique capability for estimating forest canopy height, which has a direct and increasingly well understood relationship to aboveground carbon storage. While the Geoscience Laser Altimeter System (GLAS) onboard the Ice, Cloud and land...

Monitoring individual tree-based change with airborne lidar.

PubMed

Duncanson, Laura; Dubayah, Ralph

2018-05-01

Understanding the carbon flux of forests is critical for constraining the global carbon cycle and managing forests to mitigate climate change. Monitoring forest growth and mortality rates is critical to this effort, but has been limited in the past, with estimates relying primarily on field surveys. Advances in remote sensing enable the potential to monitor tree growth and mortality across landscapes. This work presents an approach to measure tree growth and loss using multidate lidar campaigns in a high-biomass forest in California, USA. Individual tree crowns were delineated in 2008 and again in 2013 using a 3D crown segmentation algorithm, with derived heights and crown radii extracted and used to estimate individual tree aboveground biomass. Tree growth, loss, and aboveground biomass were analyzed with respect to tree height and crown radius. Both tree growth and loss rates decrease with increasing tree height, following the expectation that trees slow in growth rate as they age. Additionally, our aboveground biomass analysis suggests that, while the system is a net source of aboveground carbon, these carbon dynamics are governed by size class with the largest sources coming from the loss of a relatively small number of large individuals. This study demonstrates that monitoring individual tree-based growth and loss can be conducted with multidate airborne lidar, but these methods remain relatively immature. Disparities between lidar acquisitions were particularly difficult to overcome and decreased the sample of trees analyzed for growth rate in this study to 21% of the full number of delineated crowns. However, this study illuminates the potential of airborne remote sensing for ecologically meaningful forest monitoring at an individual tree level. As methods continue to improve, airborne multidate lidar will enable a richer understanding of the drivers of tree growth, loss, and aboveground carbon flux.

Tropical forest biomass estimation from truncated stand tables.

Treesearch

A. J. R. Gillespie; S. Brown; A. E. Lugo

1992-01-01

Total aboveground forest biomass may be estimated through a variety of techniques based on commercial inventory stand and stock tables. Stand and stock tables from tropical countries commonly omit trees bellow a certain commercial limit.

Biomass statistics for the Northern United States

Treesearch

Eric H. Wharton; Gerhard K. Raile

1984-01-01

The USDA Forest Service now estimates biomass during periodic resource inventories. Such biomass estimates quantify more of the forest resource than do traditional volume inventories that concentrate on tree boles. More than 48 percent of the aboveground tree biomass in the northern United States can be found in woody material outside of the boles. Tree biomass in the...

Airborne Lidar-Based Estimates of Tropical Forest Structure in Complex Terrain: Opportunities and Trade-Offs for REDD+

NASA Technical Reports Server (NTRS)

Leitold, Veronika; Keller, Michael; Morton, Douglas C.; Cook, Bruce D.; Shimabukuro, Yosio E.

2015-01-01

Background: Carbon stocks and fluxes in tropical forests remain large sources of uncertainty in the global carbon budget. Airborne lidar remote sensing is a powerful tool for estimating aboveground biomass, provided that lidar measurements penetrate dense forest vegetation to generate accurate estimates of surface topography and canopy heights. Tropical forest areas with complex topography present a challenge for lidar remote sensing. Results: We compared digital terrain models (DTM) derived from airborne lidar data from a mountainous region of the Atlantic Forest in Brazil to 35 ground control points measured with survey grade GNSS receivers. The terrain model generated from full-density (approx. 20 returns/sq m) data was highly accurate (mean signed error of 0.19 +/-0.97 m), while those derived from reduced-density datasets (8/sq m, 4/sq m, 2/sq m and 1/sq m) were increasingly less accurate. Canopy heights calculated from reduced-density lidar data declined as data density decreased due to the inability to accurately model the terrain surface. For lidar return densities below 4/sq m, the bias in height estimates translated into errors of 80-125 Mg/ha in predicted aboveground biomass. Conclusions: Given the growing emphasis on the use of airborne lidar for forest management, carbon monitoring, and conservation efforts, the results of this study highlight the importance of careful survey planning and consistent sampling for accurate quantification of aboveground biomass stocks and dynamics. Approaches that rely primarily on canopy height to estimate aboveground biomass are sensitive to DTM errors from variability in lidar sampling density.

Airborne lidar-based estimates of tropical forest structure in complex terrain: opportunities and trade-offs for REDD+

PubMed

Leitold, Veronika; Keller, Michael; Morton, Douglas C; Cook, Bruce D; Shimabukuro, Yosio E

2015-12-01

Carbon stocks and fluxes in tropical forests remain large sources of uncertainty in the global carbon budget. Airborne lidar remote sensing is a powerful tool for estimating aboveground biomass, provided that lidar measurements penetrate dense forest vegetation to generate accurate estimates of surface topography and canopy heights. Tropical forest areas with complex topography present a challenge for lidar remote sensing. We compared digital terrain models (DTM) derived from airborne lidar data from a mountainous region of the Atlantic Forest in Brazil to 35 ground control points measured with survey grade GNSS receivers. The terrain model generated from full-density (~20 returns m -2 ) data was highly accurate (mean signed error of 0.19 ± 0.97 m), while those derived from reduced-density datasets (8 m -2 , 4 m -2 , 2 m -2 and 1 m -2 ) were increasingly less accurate. Canopy heights calculated from reduced-density lidar data declined as data density decreased due to the inability to accurately model the terrain surface. For lidar return densities below 4 m -2 , the bias in height estimates translated into errors of 80-125 Mg ha -1 in predicted aboveground biomass. Given the growing emphasis on the use of airborne lidar for forest management, carbon monitoring, and conservation efforts, the results of this study highlight the importance of careful survey planning and consistent sampling for accurate quantification of aboveground biomass stocks and dynamics. Approaches that rely primarily on canopy height to estimate aboveground biomass are sensitive to DTM errors from variability in lidar sampling density.

Quantifying variation in forest disturbance, and its effects on aboveground biomass dynamics, across the eastern United States.

PubMed

Vanderwel, Mark C; Coomes, David A; Purves, Drew W

2013-05-01

The role of tree mortality in the global carbon balance is complicated by strong spatial and temporal heterogeneity that arises from the stochastic nature of carbon loss through disturbance. Characterizing spatio-temporal variation in mortality (including disturbance) and its effects on forest and carbon dynamics is thus essential to understanding the current global forest carbon sink, and to predicting how it will change in future. We analyzed forest inventory data from the eastern United States to estimate plot-level variation in mortality (relative to a long-term background rate for individual trees) for nine distinct forest regions. Disturbances that produced at least a fourfold increase in tree mortality over an approximately 5 year interval were observed in 1-5% of plots in each forest region. The frequency of disturbance was lowest in the northeast, and increased southwards along the Atlantic and Gulf coasts as fire and hurricane disturbances became progressively more common. Across the central and northern parts of the region, natural disturbances appeared to reflect a diffuse combination of wind, insects, disease, and ice storms. By linking estimated covariation in tree growth and mortality over time with a data-constrained forest dynamics model, we simulated the implications of stochastic variation in mortality for long-term aboveground biomass changes across the eastern United States. A geographic gradient in disturbance frequency induced notable differences in biomass dynamics between the least- and most-disturbed regions, with variation in mortality causing the latter to undergo considerably stronger fluctuations in aboveground stand biomass over time. Moreover, regional simulations showed that a given long-term increase in mean mortality rates would support greater aboveground biomass when expressed through disturbance effects compared with background mortality, particularly for early-successional species. The effects of increased tree mortality on carbon stocks and forest composition may thus depend partly on whether future mortality increases are chronic or episodic in nature. © 2013 Blackwell Publishing Ltd.

Quantifying variation in forest disturbance, and its effects on aboveground biomass dynamics, across the eastern United States

PubMed Central

Vanderwel, Mark C; Coomes, David A; Purves, Drew W

2013-01-01

The role of tree mortality in the global carbon balance is complicated by strong spatial and temporal heterogeneity that arises from the stochastic nature of carbon loss through disturbance. Characterizing spatio-temporal variation in mortality (including disturbance) and its effects on forest and carbon dynamics is thus essential to understanding the current global forest carbon sink, and to predicting how it will change in future. We analyzed forest inventory data from the eastern United States to estimate plot-level variation in mortality (relative to a long-term background rate for individual trees) for nine distinct forest regions. Disturbances that produced at least a fourfold increase in tree mortality over an approximately 5 year interval were observed in 1–5% of plots in each forest region. The frequency of disturbance was lowest in the northeast, and increased southwards along the Atlantic and Gulf coasts as fire and hurricane disturbances became progressively more common. Across the central and northern parts of the region, natural disturbances appeared to reflect a diffuse combination of wind, insects, disease, and ice storms. By linking estimated covariation in tree growth and mortality over time with a data-constrained forest dynamics model, we simulated the implications of stochastic variation in mortality for long-term aboveground biomass changes across the eastern United States. A geographic gradient in disturbance frequency induced notable differences in biomass dynamics between the least- and most-disturbed regions, with variation in mortality causing the latter to undergo considerably stronger fluctuations in aboveground stand biomass over time. Moreover, regional simulations showed that a given long-term increase in mean mortality rates would support greater aboveground biomass when expressed through disturbance effects compared with background mortality, particularly for early-successional species. The effects of increased tree mortality on carbon stocks and forest composition may thus depend partly on whether future mortality increases are chronic or episodic in nature. PMID:23505000

The Spatial Distribution of Forest Biomass in the Brazilian Amazon: A Comparison of Estimates

NASA Technical Reports Server (NTRS)

Houghton, R. A.; Lawrence, J. L.; Hackler, J. L.; Brown, S.

2001-01-01

The amount of carbon released to the atmosphere as a result of deforestation is determined, in part, by the amount of carbon held in the biomass of the forests converted to other uses. Uncertainty in forest biomass is responsible for much of the uncertainty in current estimates of the flux of carbon from land-use change. We compared several estimates of forest biomass for the Brazilian Amazon, based on spatial interpolations of direct measurements, relationships to climatic variables, and remote sensing data. We asked three questions. First, do the methods yield similar estimates? Second, do they yield similar spatial patterns of distribution of biomass? And, third, what factors need most attention if we are to predict more accurately the distribution of forest biomass over large areas? Amazonian forests (including dead and below-ground biomass) vary by more than a factor of two, from a low of 39 PgC to a high of 93 PgC. Furthermore, the estimates disagree as to the regions of high and low biomass. The lack of agreement among estimates confirms the need for reliable determination of aboveground biomass over large areas. Potential methods include direct measurement of biomass through forest inventories with improved allometric regression equations, dynamic modeling of forest recovery following observed stand-replacing disturbances (the approach used in this research), and estimation of aboveground biomass from airborne or satellite-based instruments sensitive to the vertical structure plant canopies.

Development of equations for predicting Puerto Rican subtropical dry forest biomass and volume

Treesearch

Thomas J. Brandeis; Matthew Delaney; Bernard R. Parresol; Larry Royer

2006-01-01

Carbon accounting, forest health monitoring and sustainable management of the subtropical dry forests of Puerto Rico and other Caribbean Islands require an accurate assessment of forest aboveground biomass (AGB) and stem volume. One means of improving assessment accuracy is the development of predictive equations derived from locally collected data. Forest inventory...

Development of equations for predicting Puerto Rican subtropical dry forest biomass and volume.

Treesearch

Thomas J. Brandeis; Matthew Delaney; Bernard R. Parresol; Larry Royer

2006-01-01

Carbon accounting, forest health monitoring and sustainable management of the subtropical dry forests of Puerto Rico and other Caribbean Islands require an accurate assessment of forest aboveground biomass (AGB) and stem volume. One means of improving assessment accuracy is the development of predictive equations derived from locally collected data. Forest inventory...

[Estimating individual tree aboveground biomass of the mid-subtropical forest using airborne LiDAR technology].

PubMed

Liu, Feng; Tan, Chang; Lei, Pi-Feng

2014-11-01

Taking Wugang forest farm in Xuefeng Mountain as the research object, using the airborne light detection and ranging (LiDAR) data under leaf-on condition and field data of concomitant plots, this paper assessed the ability of using LiDAR technology to estimate aboveground biomass of the mid-subtropical forest. A semi-automated individual tree LiDAR cloud point segmentation was obtained by using condition random fields and optimization methods. Spatial structure, waveform characteristics and topography were calculated as LiDAR metrics from the segmented objects. Then statistical models between aboveground biomass from field data and these LiDAR metrics were built. The individual tree recognition rates were 93%, 86% and 60% for coniferous, broadleaf and mixed forests, respectively. The adjusted coefficients of determination (R(2)adj) and the root mean squared errors (RMSE) for the three types of forest were 0.83, 0.81 and 0.74, and 28.22, 29.79 and 32.31 t · hm(-2), respectively. The estimation capability of model based on canopy geometric volume, tree percentile height, slope and waveform characteristics was much better than that of traditional regression model based on tree height. Therefore, LiDAR metrics from individual tree could facilitate better performance in biomass estimation.

Quantifying aboveground forest carbon pools and fluxes from repeat LiDAR surveys

Treesearch

Andrew T. Hudak; Eva K. Strand; Lee A. Vierling; John C. Byrne; Jan U. H. Eitel; Sebastian Martinuzzi; Michael J. Falkowski

2012-01-01

Sound forest policy and management decisions to mitigate rising atmospheric CO2 depend upon accurate methodologies to quantify forest carbon pools and fluxes over large tracts of land. LiDAR remote sensing is a rapidly evolving technology for quantifying aboveground biomass and thereby carbon pools; however, little work has evaluated the efficacy of repeat LiDAR...

Estimation and mapping of above-ground biomass of mangrove forests and their replacement land uses in the Philippines using Sentinel imagery

NASA Astrophysics Data System (ADS)

Castillo, Jose Alan A.; Apan, Armando A.; Maraseni, Tek N.; Salmo, Severino G.

2017-12-01

The recent launch of the Sentinel-1 (SAR) and Sentinel-2 (multispectral) missions offers a new opportunity for land-based biomass mapping and monitoring especially in the tropics where deforestation is highest. Yet, unlike in agriculture and inland land uses, the use of Sentinel imagery has not been evaluated for biomass retrieval in mangrove forest and the non-forest land uses that replaced mangroves. In this study, we evaluated the ability of Sentinel imagery for the retrieval and predictive mapping of above-ground biomass of mangroves and their replacement land uses. We used Sentinel SAR and multispectral imagery to develop biomass prediction models through the conventional linear regression and novel Machine Learning algorithms. We developed models each from SAR raw polarisation backscatter data, multispectral bands, vegetation indices, and canopy biophysical variables. The results show that the model based on biophysical variable Leaf Area Index (LAI) derived from Sentinel-2 was more accurate in predicting the overall above-ground biomass. In contrast, the model which utilised optical bands had the lowest accuracy. However, the SAR-based model was more accurate in predicting the biomass in the usually deficient to low vegetation cover non-forest replacement land uses such as abandoned aquaculture pond, cleared mangrove and abandoned salt pond. These models had 0.82-0.83 correlation/agreement of observed and predicted value, and root mean square error of 27.8-28.5 Mg ha-1. Among the Sentinel-2 multispectral bands, the red and red edge bands (bands 4, 5 and 7), combined with elevation data, were the best variable set combination for biomass prediction. The red edge-based Inverted Red-Edge Chlorophyll Index had the highest prediction accuracy among the vegetation indices. Overall, Sentinel-1 SAR and Sentinel-2 multispectral imagery can provide satisfactory results in the retrieval and predictive mapping of the above-ground biomass of mangroves and the replacement non-forest land uses, especially with the inclusion of elevation data. The study demonstrates encouraging results in biomass mapping of mangroves and other coastal land uses in the tropics using the freely accessible and relatively high-resolution Sentinel imagery.

Simulating carbon stocks and fluxes of an African tropical montane forest with an individual-based forest model.

PubMed

Fischer, Rico; Ensslin, Andreas; Rutten, Gemma; Fischer, Markus; Schellenberger Costa, David; Kleyer, Michael; Hemp, Andreas; Paulick, Sebastian; Huth, Andreas

2015-01-01

Tropical forests are carbon-dense and highly productive ecosystems. Consequently, they play an important role in the global carbon cycle. In the present study we used an individual-based forest model (FORMIND) to analyze the carbon balances of a tropical forest. The main processes of this model are tree growth, mortality, regeneration, and competition. Model parameters were calibrated using forest inventory data from a tropical forest at Mt. Kilimanjaro. The simulation results showed that the model successfully reproduces important characteristics of tropical forests (aboveground biomass, stem size distribution and leaf area index). The estimated aboveground biomass (385 t/ha) is comparable to biomass values in the Amazon and other tropical forests in Africa. The simulated forest reveals a gross primary production of 24 tcha(-1) yr(-1). Modeling above- and belowground carbon stocks, we analyzed the carbon balance of the investigated tropical forest. The simulated carbon balance of this old-growth forest is zero on average. This study provides an example of how forest models can be used in combination with forest inventory data to investigate forest structure and local carbon balances.

Structure, production and resource use in some old-growth spruce/fir forests in the front range of the Rocky Mountains, USA

USGS Publications Warehouse

Binkley, Dan; Olsson, U.; Rochelle, R.; Stohlgren, T.; Nikolov, N.

2003-01-01

Old-growth forests of Engelmann spruce (Picea engelmannii Parry ex. Engelm.) and subalpine fir (Abies lasiocarpa (Hook.) Nutt.) dominate much of the landscape of the Rocky Mountains. We characterized the structure, biomass and production of 18 old-growth (200-450-year-old) spruce/fir forests in Rocky Mountain National Park, Colorado, as well as the stand-level supply and use of light and nitrogen. Stands were chosen to span a broad range of elevation, aspect, and topography. Aboveground tree biomass in these old-growth forests averaged 253 Mg/ha (range 130-488 Mg/ha), with aboveground net primary production of 3700 kg ha-1 yr-1 (range from 2700 to 5200 kg ha-1 yr-1). Within stands, trees >35 cm in diameter accounted for 70% of aboveground biomass, but trees <35 cm contributed 70% of the production of woody biomass. Differences in slope and aspect among sites resulted in a range of incoming light from 58 to 74 TJ ha-1 yr-1, and tree canopies intercepted an average of 71% of incoming light (range 50-90%). Aboveground net primary production (ANPP) of trees did not relate to the supply of light or N, but ANPP correlated strongly with the amount of light and N used (r2 = 0.45-0.54, P < 0.01). Uptake of 1 kg of N was associated with about 260 kg of ANPP, and one TJ of intercepted shortwave radiation produced about 78 kg of ANPP. Across these old-growth stands, stands with greater biomass showed higher rates of both ANPP and resource use; variation in aboveground biomass was associated with 24% of the variation in N use (P = 0.04), 44% of the light use (P = 0.003), and 45% of the ANPP (P = 0.002). ?? 2002 Elsevier Science B.V. All rights reserved.

Estimation and Mapping of Coastal Mangrove Biomass Using Both Passive and Active Remote Sensing Method

NASA Astrophysics Data System (ADS)

Yiqiong, L.; Lu, W.; Zhou, J.; Gan, W.; Cui, X.; Lin, G., Sr.

2015-12-01

Mangrove forests play an important role in global carbon cycle, but carbon stocks in different mangrove forests are not easily measured at large scale. In this research, both active and passive remote sensing methods were used to estimate the aboveground biomass of dominant mangrove communities in Zhanjiang National Mangrove Nature Reserve in Guangdong, China. We set up a decision tree including spectral, texture, position and geometry indexes to achieve mangrove inter-species classification among 5 main species named Aegiceras corniculatum, Aricennia marina, Bruguiera gymnorrhiza, Kandelia candel, Sonneratia apetala by using 5.8m multispectral ZY-3 images. In addition, Lidar data were collected and used to obtain the canopy height of different mangrove species. Then, regression equations between the field measured aboveground biomass and the canopy height deduced from Lidar data were established for these mangrove species. By combining these results, we were able to establish a relatively accurate method for differentiating mangrove species and mapping their aboveground biomass distribution at the estuary scale, which could be applied to mangrove forests in other regions.

Uncertainty Analysis in Large Area Aboveground Biomass Mapping

NASA Astrophysics Data System (ADS)

Baccini, A.; Carvalho, L.; Dubayah, R.; Goetz, S. J.; Friedl, M. A.

2011-12-01

Satellite and aircraft-based remote sensing observations are being more frequently used to generate spatially explicit estimates of aboveground carbon stock of forest ecosystems. Because deforestation and forest degradation account for circa 10% of anthropogenic carbon emissions to the atmosphere, policy mechanisms are increasingly recognized as a low-cost mitigation option to reduce carbon emission. They are, however, contingent upon the capacity to accurately measures carbon stored in the forests. Here we examine the sources of uncertainty and error propagation in generating maps of aboveground biomass. We focus on characterizing uncertainties associated with maps at the pixel and spatially aggregated national scales. We pursue three strategies to describe the error and uncertainty properties of aboveground biomass maps, including: (1) model-based assessment using confidence intervals derived from linear regression methods; (2) data-mining algorithms such as regression trees and ensembles of these; (3) empirical assessments using independently collected data sets.. The latter effort explores error propagation using field data acquired within satellite-based lidar (GLAS) acquisitions versus alternative in situ methods that rely upon field measurements that have not been systematically collected for this purpose (e.g. from forest inventory data sets). A key goal of our effort is to provide multi-level characterizations that provide both pixel and biome-level estimates of uncertainties at different scales.

Shifts in biomass and productivity for a subtropical dry forest in response to simulated elevated hurricane disturbances

DOE Office of Scientific and Technical Information (OSTI.GOV)

Holm, Jennifer A.; Van Bloem, Skip J.; Larocque, Guy R.

Caribbean tropical forests are subject to hurricane disturbances of great variability. In addition to natural storm incongruity, climate change can alter storm formation, duration, frequency, and intensity. This model -based investigation assessed the impacts of multiple storms of different intensities and occurrence frequencies on the long-term dynamics of subtropical dry forests in Puerto Rico. Using the previously validated individual-based gap model ZELIG-TROP, we developed a new hurricane damage routine and parameterized it with site- and species-specific hurricane effects. A baseline case with the reconstructed historical hurricane regime represented the control condition. Ten treatment cases, reflecting plausible shifts in hurricane regimes,more » manipulated both hurricane return time (i.e. frequency) and hurricane intensity. The treatment-related change in carbon storage and fluxes were reported as changes in aboveground forest biomass (AGB), net primary productivity (NPP), and in the aboveground carbon partitioning components, or annual carbon accumulation (ACA). Increasing the frequency of hurricanes decreased aboveground biomass by between 5% and 39%, and increased NPP between 32% and 50%. Decadal-scale biomass fluctuations were damped relative to the control. In contrast, increasing hurricane intensity did not create a large shift in the long-term average forest structure, NPP, or ACA from that of historical hurricane regimes, but produced large fluctuations in biomass. Decreasing both the hurricane intensity and frequency by 50% produced the highest values of biomass and NPP. For the control scenario and with increased hurricane intensity, ACA was negative, which indicated that the aboveground forest components acted as a carbon source. However, with an increase in the frequency of storms or decreased storms, the total ACA was positive due to shifts in leaf production, annual litterfall, and coarse woody debris inputs, indicating a carbon sink into the forest over the long-term. The carbon loss from each hurricane event, in all scenarios, always recovered over sufficient time. Our results suggest that subtropical dry forests will remain resilient to hurricane disturbance. However carbon stocks will decrease if future climates increase hurricane frequency by 50% or more.« less

Shifts in biomass and productivity for a subtropical dry forest in response to simulated elevated hurricane disturbances

NASA Astrophysics Data System (ADS)

Holm, Jennifer A.; Van Bloem, Skip J.; Larocque, Guy R.; Shugart, Herman H.

2017-02-01

Caribbean tropical forests are subject to hurricane disturbances of great variability. In addition to natural storm incongruity, climate change can alter storm formation, duration, frequency, and intensity. This model-based investigation assessed the impacts of multiple storms of different intensities and occurrence frequencies on the long-term dynamics of subtropical dry forests in Puerto Rico. Using the previously validated individual-based gap model ZELIG-TROP, we developed a new hurricane damage routine and parameterized it with site- and species-specific hurricane effects. A baseline case with the reconstructed historical hurricane regime represented the control condition. Ten treatment cases, reflecting plausible shifts in hurricane regimes, manipulated both hurricane return time (i.e. frequency) and hurricane intensity. The treatment-related change in carbon storage and fluxes were reported as changes in aboveground forest biomass (AGB), net primary productivity (NPP), and in the aboveground carbon partitioning components, or annual carbon accumulation (ACA). Increasing the frequency of hurricanes decreased aboveground biomass by between 5% and 39%, and increased NPP between 32% and 50%. Decadal-scale biomass fluctuations were damped relative to the control. In contrast, increasing hurricane intensity did not create a large shift in the long-term average forest structure, NPP, or ACA from that of historical hurricane regimes, but produced large fluctuations in biomass. Decreasing both the hurricane intensity and frequency by 50% produced the highest values of biomass and NPP. For the control scenario and with increased hurricane intensity, ACA was negative, which indicated that the aboveground forest components acted as a carbon source. However, with an increase in the frequency of storms or decreased storms, the total ACA was positive due to shifts in leaf production, annual litterfall, and coarse woody debris inputs, indicating a carbon sink into the forest over the long-term. The carbon loss from each hurricane event, in all scenarios, always recovered over sufficient time. Our results suggest that subtropical dry forests will remain resilient to hurricane disturbance. However carbon stocks will decrease if future climates increase hurricane frequency by 50% or more.

Shifts in biomass and productivity for a subtropical dry forest in response to simulated elevated hurricane disturbances

DOE PAGES

Holm, Jennifer A.; Van Bloem, Skip J.; Larocque, Guy R.; ...

2017-02-07

Caribbean tropical forests are subject to hurricane disturbances of great variability. In addition to natural storm incongruity, climate change can alter storm formation, duration, frequency, and intensity. This model -based investigation assessed the impacts of multiple storms of different intensities and occurrence frequencies on the long-term dynamics of subtropical dry forests in Puerto Rico. Using the previously validated individual-based gap model ZELIG-TROP, we developed a new hurricane damage routine and parameterized it with site- and species-specific hurricane effects. A baseline case with the reconstructed historical hurricane regime represented the control condition. Ten treatment cases, reflecting plausible shifts in hurricane regimes,more » manipulated both hurricane return time (i.e. frequency) and hurricane intensity. The treatment-related change in carbon storage and fluxes were reported as changes in aboveground forest biomass (AGB), net primary productivity (NPP), and in the aboveground carbon partitioning components, or annual carbon accumulation (ACA). Increasing the frequency of hurricanes decreased aboveground biomass by between 5% and 39%, and increased NPP between 32% and 50%. Decadal-scale biomass fluctuations were damped relative to the control. In contrast, increasing hurricane intensity did not create a large shift in the long-term average forest structure, NPP, or ACA from that of historical hurricane regimes, but produced large fluctuations in biomass. Decreasing both the hurricane intensity and frequency by 50% produced the highest values of biomass and NPP. For the control scenario and with increased hurricane intensity, ACA was negative, which indicated that the aboveground forest components acted as a carbon source. However, with an increase in the frequency of storms or decreased storms, the total ACA was positive due to shifts in leaf production, annual litterfall, and coarse woody debris inputs, indicating a carbon sink into the forest over the long-term. The carbon loss from each hurricane event, in all scenarios, always recovered over sufficient time. Our results suggest that subtropical dry forests will remain resilient to hurricane disturbance. However carbon stocks will decrease if future climates increase hurricane frequency by 50% or more.« less

Potential aboveground biomass in drought-prone forest used for rangeland pastoralism.

PubMed

Fensham, R J; Fairfax, R J; Dwyer, J M

2012-04-01

The restoration of cleared dry forest represents an important opportunity to sequester atmospheric carbon. In order to account for this potential, the influences of climate, soils, and disturbance need to be deciphered. A data set spanning a region defined the aboveground biomass of mulga (Acacia aneura) dry forest and was analyzed in relation to climate and soil variables using a Bayesian model averaging procedure. Mean annual rainfall had an overwhelmingly strong positive effect, with mean maximum temperature (negative) and soil depth (positive) also important. The data were collected after a recent drought, and the amount of recent tree mortality was weakly positively related to a measure of three-year rainfall deficit, and maximum temperature (positive), soil depth (negative), and coarse sand (negative). A grazing index represented by the distance of sites to watering points was not incorporated by the models. Stark management contrasts, including grazing exclosures, can represent a substantial part of the variance in the model predicting biomass, but the impact of management was unpredictable and was insignificant in the regional data set. There was no evidence of density-dependent effects on tree mortality. Climate change scenarios represented by the coincidence of historical extreme rainfall deficit with extreme temperature suggest mortality of 30.1% of aboveground biomass, compared to 21.6% after the recent (2003-2007) drought. Projections for recovery of forest using a mapping base of cleared areas revealed that the greatest opportunities for restoration of aboveground biomass are in the higher-rainfall areas, where biomass accumulation will be greatest and droughts are less intense. These areas are probably the most productive for rangeland pastoralism, and the trade-off between pastoral production and carbon sequestration will be determined by market forces and carbon-trading rules.

Does Sentinel multi sensor data offer synergy in Improving Accuracy of Aboveground Biomass Estimate of Dense Tropical Forest? - Utility of Decision Tree Based Machine Learning Algorithms

NASA Astrophysics Data System (ADS)

Ghosh, S. M.; Behera, M. D.

2017-12-01

Forest aboveground biomass (AGB) is an important factor for preparation of global policy making decisions to tackle the impact of climate change. Several previous studies has concluded that remote sensing methods are more suitable for estimating forest biomass on regional scale. Among all available remote sensing data and methods, Synthetic Aperture Radar (SAR) data in combination with decision tree based machine learning algorithms has shown better promise in estimating higher biomass values. There aren't many studies done for biomass estimation of dense Indian tropical forests with high biomass density. In this study aboveground biomass was estimated for two major tree species, Sal (Shorea robusta) and Teak (Tectona grandis), of Katerniaghat Wildlife Sanctuary, a tropical forest situated in northern India. Biomass was estimated by combining C-band SAR data from Sentinel-1A satellite, vegetation indices produced using Sentinel-2A data and ground inventory plots. Along with SAR backscatter value, SAR texture images were also used as input as earlier studies had found that image texture has a correlation with vegetation biomass. Decision tree based nonlinear machine learning algorithms were used in place of parametric regression models for establishing relationship between fields measured values and remotely sensed parameters. Using random forest model with a combination of vegetation indices with SAR backscatter as predictor variables shows best result for Sal forest, with a coefficient of determination value of 0.71 and a RMSE value of 105.027 t/ha. In teak forest also best result can be found in the same combination but for stochastic gradient boosted model with a coefficient of determination value of 0.6 and a RMSE value of 79.45 t/ha. These results are mostly better than the results of other studies done for similar kind of forests. This study shows that Sentinel series satellite data has exceptional capabilities in estimating dense forest AGB and machine learning algorithms are better means to do so than parametric regression models.

Ecological Importance of Small-Diameter Trees to the Structure, Diversity and Biomass of a Tropical Evergreen Forest at Rabi, Gabon.

PubMed

Memiaghe, Hervé R; Lutz, James A; Korte, Lisa; Alonso, Alfonso; Kenfack, David

2016-01-01

Tropical forests have long been recognized for their biodiversity and ecosystem services. Despite their importance, tropical forests, and particularly those of central Africa, remain understudied. Until recently, most forest inventories in Central Africa have focused on trees ≥10 cm in diameter, even though several studies have shown that small-diameter tree population may be important to demographic rates and nutrient cycling. To determine the ecological importance of small-diameter trees in central African forests, we used data from a 25-ha permanent plot that we established in the rainforest of Gabon to study the diversity and dynamics of these forests. Within the plot, we censused 175,830 trees ≥1 cm dbh from 54 families, 192 genera, and 345 species. Average tree density was 7,026 trees/ha, basal area 31.64 m2/ha, and above-ground biomass 369.40 Mg/ha. Fabaceae, Ebenaceae and Euphorbiaceae were the most important families by basal area, density and above-ground biomass. Small-diameter trees (1 cm ≥ dbh <10 cm) comprised 93.7% of the total tree population, 16.5% of basal area, and 4.8% of the above-ground biomass. They also had diversity 18% higher at family level, 34% higher at genus level, and 42% higher at species level than trees ≥10 cm dbh. Although the relative contribution of small-diameter trees to biomass was comparable to other forests globally, their contribution to forest density, and diversity was disproportionately higher. The high levels of diversity within small-diameter classes may give these forests high levels of structural resilience to anthropogenic/natural disturbance and a changing climate.

Ecological Importance of Small-Diameter Trees to the Structure, Diversity and Biomass of a Tropical Evergreen Forest at Rabi, Gabon

PubMed Central

Memiaghe, Hervé R.; Lutz, James A.; Korte, Lisa; Alonso, Alfonso; Kenfack, David

2016-01-01

Tropical forests have long been recognized for their biodiversity and ecosystem services. Despite their importance, tropical forests, and particularly those of central Africa, remain understudied. Until recently, most forest inventories in Central Africa have focused on trees ≥10 cm in diameter, even though several studies have shown that small-diameter tree population may be important to demographic rates and nutrient cycling. To determine the ecological importance of small-diameter trees in central African forests, we used data from a 25-ha permanent plot that we established in the rainforest of Gabon to study the diversity and dynamics of these forests. Within the plot, we censused 175,830 trees ≥1 cm dbh from 54 families, 192 genera, and 345 species. Average tree density was 7,026 trees/ha, basal area 31.64 m2/ha, and above-ground biomass 369.40 Mg/ha. Fabaceae, Ebenaceae and Euphorbiaceae were the most important families by basal area, density and above-ground biomass. Small-diameter trees (1 cm ≥ dbh <10 cm) comprised 93.7% of the total tree population, 16.5% of basal area, and 4.8% of the above-ground biomass. They also had diversity 18% higher at family level, 34% higher at genus level, and 42% higher at species level than trees ≥10 cm dbh. Although the relative contribution of small-diameter trees to biomass was comparable to other forests globally, their contribution to forest density, and diversity was disproportionately higher. The high levels of diversity within small-diameter classes may give these forests high levels of structural resilience to anthropogenic/natural disturbance and a changing climate. PMID:27186658

A Model-Data Intercomparison of Carbon Fluxes, Pools, and LAI in the Community Land Model (CLM) and Alternative Carbon Allocation Schemes

NASA Astrophysics Data System (ADS)

Montane, F.; Fox, A. M.; Arellano, A. F.; Alexander, M. R.; Moore, D. J.

2016-12-01

Carbon (C) allocation to different plant tissues (leaves, stem and roots) remains a central challenge for understanding the global C cycle, as it determines C residence time. We used a diverse set of observations (AmeriFlux eddy covariance towers, biomass estimates from tree-ring data, and Leaf Area Index measurements) to compare C fluxes, pools, and Leaf Area Index (LAI) data with the Community Land Model (CLM). We ran CLM for seven temperate forests in North America (including evergreen and deciduous sites) between 1980 and 2013 using different C allocation schemes: i) standard C allocation scheme in CLM, which allocates C to the stem and leaves as a dynamic function of annual net primary productivity (NPP); ii) two fixed C allocation schemes, one representative of evergreen and the other one of deciduous forests, based on Luyssaert et al. 2007; iii) an alternative C allocation scheme, which allocated C to stem and leaves, and to stem and coarse roots, as a dynamic function of annual NPP, based on Litton et al. 2007. At our sites CLM usually overestimated gross primary production and ecosystem respiration, and underestimated net ecosystem exchange. Initial aboveground biomass in 1980 was largely overestimated for deciduous forests, whereas aboveground biomass accumulation between 1980 and 2011 was highly underestimated for both evergreen and deciduous sites due to the lower turnover rate in the sites than the one used in the model. CLM overestimated LAI in both evergreen and deciduous sites because the Leaf C-LAI relationship in the model did not match the observed Leaf C-LAI relationship in our sites. Although the different C allocation schemes gave similar results for aggregated C fluxes, they translated to important differences in long-term aboveground biomass accumulation and aboveground NPP. For deciduous forests, one of the alternative C allocation schemes used (iii) gave more realistic stem C/leaf C ratios, and highly reduced the overestimation of initial aboveground biomass, and accumulated aboveground NPP for deciduous forests by CLM. Our results would suggest using different C allocation schemes for evergreen and deciduous forests. It is crucial to improve CLM in the near future to minimize data-model mismatches, and to address some of the current model structural errors and parameter uncertainties.

Tropical-forest biomass estimation at X-Band from the spaceborne TanDEM-X interferometer

Treesearch

R. Treuhaft; F. Goncalves; J.R. dos Santos; M. Keller; M. Palace; S.N. Madsen; F. Sullivan; P.M.L.A. Graca

2014-01-01

This letter reports the sensitivity of X-band interferometric synthetic aperture radar (InSAR) data from the first dual-spacecraft radar interferometer, TanDEM-X, to variations in tropical-forest aboveground biomass (AGB). It also reports the first tropical-forest AGB estimates fromTanDEM-X data. Tropical forests account for...

Biomass accumulation rates of Amazonian secondary forest and biomass of old-growth forests from Landsat time series and the Geoscience Laser Altimeter System

Treesearch

E. H. Helmer; M. A. Lefsky; D. A. Roberts

2009-01-01

We estimate the age of humid lowland tropical forests in Rondônia, Brazil, from a somewhat densely spaced time series of Landsat images (1975–2003) with an automated procedure, the Threshold Age Mapping Algorithm (TAMA), first described here. We then estimate a landscape-level rate of aboveground woody biomass accumulation of secondary forest by combining forest age...

Distribution of Aboveground Live Biomass in the Amazon Basin

NASA Technical Reports Server (NTRS)

Saatchi, S. S.; Houghton, R. A.; DosSantos Alvala, R. C.; Soares, J. V.; Yu, Y.

2007-01-01

The amount and spatial distribution of forest biomass in the Amazon basin is a major source of uncertainty in estimating the flux of carbon released from land-cover and land-use change. Direct measurements of aboveground live biomass (AGLB) are limited to small areas of forest inventory plots and site-specific allometric equations that cannot be readily generalized for the entire basin. Furthermore, there is no spaceborne remote sensing instrument that can measure tropical forest biomass directly. To determine the spatial distribution of forest biomass of the Amazon basin, we report a method based on remote sensing metrics representing various forest structural parameters and environmental variables, and more than 500 plot measurements of forest biomass distributed over the basin. A decision tree approach was used to develop the spatial distribution of AGLB for seven distinct biomass classes of lowland old-growth forests with more than 80% accuracy. AGLB for other vegetation types, such as the woody and herbaceous savanna and secondary forests, was directly estimated with a regression based on satellite data. Results show that AGLB is highest in Central Amazonia and in regions to the east and north, including the Guyanas. Biomass is generally above 300Mgha(sup 1) here except in areas of intense logging or open floodplains. In Western Amazonia, from the lowlands of Peru, Ecuador, and Colombia to the Andean mountains, biomass ranges from 150 to 300Mgha(sup 1). Most transitional and seasonal forests at the southern and northwestern edges of the basin have biomass ranging from 100 to 200Mgha(sup 1). The AGLB distribution has a significant correlation with the length of the dry season. We estimate that the total carbon in forest biomass of the Amazon basin, including the dead and below ground biomass, is 86 PgC with +/- 20% uncertainty.

Simulating vegetation controls on hurricane-induced shallow landslides with a distributed ecohydrological model

Treesearch

Taehee Hwang; Lawrence E. Band; T. C. Hales; Chelcy F. Miniat; James M. Vose; Paul V. Bolstad; Brian Miles; Katie Price

2015-01-01

The spatial distribution of shallow landslides in steep forested mountains is strongly controlled by aboveground and belowground biomass, including the distribution of root cohesion. While remote sensing of aboveground canopy properties is relatively advanced, estimating the spatial distribution of root cohesion at the forest landscape scale remains challenging. We...

Evaluating the effect of alternative carbon allocation schemes in a land surface model (CLM4.5) on carbon fluxes, pools, and turnover in temperate forests

NASA Astrophysics Data System (ADS)

Montané, Francesc; Fox, Andrew M.; Arellano, Avelino F.; MacBean, Natasha; Alexander, M. Ross; Dye, Alex; Bishop, Daniel A.; Trouet, Valerie; Babst, Flurin; Hessl, Amy E.; Pederson, Neil; Blanken, Peter D.; Bohrer, Gil; Gough, Christopher M.; Litvak, Marcy E.; Novick, Kimberly A.; Phillips, Richard P.; Wood, Jeffrey D.; Moore, David J. P.

2017-09-01

How carbon (C) is allocated to different plant tissues (leaves, stem, and roots) determines how long C remains in plant biomass and thus remains a central challenge for understanding the global C cycle. We used a diverse set of observations (AmeriFlux eddy covariance tower observations, biomass estimates from tree-ring data, and leaf area index (LAI) measurements) to compare C fluxes, pools, and LAI data with those predicted by a land surface model (LSM), the Community Land Model (CLM4.5). We ran CLM4.5 for nine temperate (including evergreen and deciduous) forests in North America between 1980 and 2013 using four different C allocation schemes: i. dynamic C allocation scheme (named "D-CLM4.5") with one dynamic allometric parameter, which allocates C to the stem and leaves to vary in time as a function of annual net primary production (NPP); ii. an alternative dynamic C allocation scheme (named "D-Litton"), where, similar to (i), C allocation is a dynamic function of annual NPP, but unlike (i) includes two dynamic allometric parameters involving allocation to leaves, stem, and coarse roots; iii.-iv. a fixed C allocation scheme with two variants, one representative of observations in evergreen (named "F-Evergreen") and the other of observations in deciduous forests (named "F-Deciduous"). D-CLM4.5 generally overestimated gross primary production (GPP) and ecosystem respiration, and underestimated net ecosystem exchange (NEE). In D-CLM4.5, initial aboveground biomass in 1980 was largely overestimated (between 10 527 and 12 897 g C m-2) for deciduous forests, whereas aboveground biomass accumulation through time (between 1980 and 2011) was highly underestimated (between 1222 and 7557 g C m-2) for both evergreen and deciduous sites due to a lower stem turnover rate in the sites than the one used in the model. D-CLM4.5 overestimated LAI in both evergreen and deciduous sites because the leaf C-LAI relationship in the model did not match the observed leaf C-LAI relationship at our sites. Although the four C allocation schemes gave similar results for aggregated C fluxes, they translated to important differences in long-term aboveground biomass accumulation and aboveground NPP. For deciduous forests, D-Litton gave more realistic Cstem / Cleaf ratios and strongly reduced the overestimation of initial aboveground biomass and aboveground NPP for deciduous forests by D-CLM4.5. We identified key structural and parameterization deficits that need refinement to improve the accuracy of LSMs in the near future. These include changing how C is allocated in fixed and dynamic schemes based on data from current forest syntheses and different parameterization of allocation schemes for different forest types. Our results highlight the utility of using measurements of aboveground biomass to evaluate and constrain the C allocation scheme in LSMs, and suggest that stem turnover is overestimated by CLM4.5 for these AmeriFlux sites. Understanding the controls of turnover will be critical to improving long-term C processes in LSMs.

Evaluating the effect of alternative carbon allocation schemes in a land surface model (CLM4.5) on carbon fluxes, pools, and turnover in temperate forests

DOE PAGES

Montané, Francesc; Fox, Andrew M.; Arellano, Avelino F.; ...

2017-09-22

How carbon (C) is allocated to different plant tissues (leaves, stem, and roots) determines how long C remains in plant biomass and thus remains a central challenge for understanding the global C cycle. We used a diverse set of observations (AmeriFlux eddy covariance tower observations, biomass estimates from tree-ring data, and leaf area index (LAI) measurements) to compare C fluxes, pools, and LAI data with those predicted by a land surface model (LSM), the Community Land Model (CLM4.5). We ran CLM4.5 for nine temperate (including evergreen and deciduous) forests in North America between 1980 and 2013 using four different C allocationmore » schemes: i. dynamic C allocation scheme (named "D-CLM4.5") with one dynamic allometric parameter, which allocates C to the stem and leaves to vary in time as a function of annual net primary production (NPP); ii. an alternative dynamic C allocation scheme (named "D-Litton"), where, similar to (i), C allocation is a dynamic function of annual NPP, but unlike (i) includes two dynamic allometric parameters involving allocation to leaves, stem, and coarse roots; iii.–iv. a fixed C allocation scheme with two variants, one representative of observations in evergreen (named "F-Evergreen") and the other of observations in deciduous forests (named "F-Deciduous"). D-CLM4.5 generally overestimated gross primary production (GPP) and ecosystem respiration, and underestimated net ecosystem exchange (NEE). In D-CLM4.5, initial aboveground biomass in 1980 was largely overestimated (between 10 527 and 12 897 g C m -2) for deciduous forests, whereas aboveground biomass accumulation through time (between 1980 and 2011) was highly underestimated (between 1222 and 7557 g C m -2) for both evergreen and deciduous sites due to a lower stem turnover rate in the sites than the one used in the model. D-CLM4.5 overestimated LAI in both evergreen and deciduous sites because the leaf C–LAI relationship in the model did not match the observed leaf C–LAI relationship at our sites. Although the four C allocation schemes gave similar results for aggregated C fluxes, they translated to important differences in long-term aboveground biomass accumulation and aboveground NPP. For deciduous forests, D-Litton gave more realistic C stem/C leaf ratios and strongly reduced the overestimation of initial aboveground biomass and aboveground NPP for deciduous forests by D-CLM4.5. We identified key structural and parameterization deficits that need refinement to improve the accuracy of LSMs in the near future. These include changing how C is allocated in fixed and dynamic schemes based on data from current forest syntheses and different parameterization of allocation schemes for different forest types. Our results highlight the utility of using measurements of aboveground biomass to evaluate and constrain the C allocation scheme in LSMs, and suggest that stem turnover is overestimated by CLM4.5 for these AmeriFlux sites. Understanding the controls of turnover will be critical to improving long-term C processes in LSMs.« less

Evaluating the effect of alternative carbon allocation schemes in a land surface model (CLM4.5) on carbon fluxes, pools, and turnover in temperate forests

DOE Office of Scientific and Technical Information (OSTI.GOV)

Montané, Francesc; Fox, Andrew M.; Arellano, Avelino F.

How carbon (C) is allocated to different plant tissues (leaves, stem, and roots) determines how long C remains in plant biomass and thus remains a central challenge for understanding the global C cycle. We used a diverse set of observations (AmeriFlux eddy covariance tower observations, biomass estimates from tree-ring data, and leaf area index (LAI) measurements) to compare C fluxes, pools, and LAI data with those predicted by a land surface model (LSM), the Community Land Model (CLM4.5). We ran CLM4.5 for nine temperate (including evergreen and deciduous) forests in North America between 1980 and 2013 using four different C allocationmore » schemes: i. dynamic C allocation scheme (named "D-CLM4.5") with one dynamic allometric parameter, which allocates C to the stem and leaves to vary in time as a function of annual net primary production (NPP); ii. an alternative dynamic C allocation scheme (named "D-Litton"), where, similar to (i), C allocation is a dynamic function of annual NPP, but unlike (i) includes two dynamic allometric parameters involving allocation to leaves, stem, and coarse roots; iii.–iv. a fixed C allocation scheme with two variants, one representative of observations in evergreen (named "F-Evergreen") and the other of observations in deciduous forests (named "F-Deciduous"). D-CLM4.5 generally overestimated gross primary production (GPP) and ecosystem respiration, and underestimated net ecosystem exchange (NEE). In D-CLM4.5, initial aboveground biomass in 1980 was largely overestimated (between 10 527 and 12 897 g C m -2) for deciduous forests, whereas aboveground biomass accumulation through time (between 1980 and 2011) was highly underestimated (between 1222 and 7557 g C m -2) for both evergreen and deciduous sites due to a lower stem turnover rate in the sites than the one used in the model. D-CLM4.5 overestimated LAI in both evergreen and deciduous sites because the leaf C–LAI relationship in the model did not match the observed leaf C–LAI relationship at our sites. Although the four C allocation schemes gave similar results for aggregated C fluxes, they translated to important differences in long-term aboveground biomass accumulation and aboveground NPP. For deciduous forests, D-Litton gave more realistic C stem/C leaf ratios and strongly reduced the overestimation of initial aboveground biomass and aboveground NPP for deciduous forests by D-CLM4.5. We identified key structural and parameterization deficits that need refinement to improve the accuracy of LSMs in the near future. These include changing how C is allocated in fixed and dynamic schemes based on data from current forest syntheses and different parameterization of allocation schemes for different forest types. Our results highlight the utility of using measurements of aboveground biomass to evaluate and constrain the C allocation scheme in LSMs, and suggest that stem turnover is overestimated by CLM4.5 for these AmeriFlux sites. Understanding the controls of turnover will be critical to improving long-term C processes in LSMs.« less

Improved accuracy of aboveground biomass and carbon estimates for live trees in forests of the eastern United States

Treesearch

Philip Radtke; David Walker; Jereme Frank; Aaron Weiskittel; Clara DeYoung; David MacFarlane; Grant Domke; Christopher Woodall; John Coulston; James Westfall

2017-01-01

Accurate estimation of forest biomass and carbon stocks at regional to national scales is a key requirement in determining terrestrial carbon sources and sinks on United States (US) forest lands. To that end, comprehensive assessment and testing of alternative volume and biomass models were conducted for individual tree models employed in the component ratio method (...

Comparison of machine-learning methods for above-ground biomass estimation based on Landsat imagery

NASA Astrophysics Data System (ADS)

Wu, Chaofan; Shen, Huanhuan; Shen, Aihua; Deng, Jinsong; Gan, Muye; Zhu, Jinxia; Xu, Hongwei; Wang, Ke

2016-07-01

Biomass is one significant biophysical parameter of a forest ecosystem, and accurate biomass estimation on the regional scale provides important information for carbon-cycle investigation and sustainable forest management. In this study, Landsat satellite imagery data combined with field-based measurements were integrated through comparisons of five regression approaches [stepwise linear regression, K-nearest neighbor, support vector regression, random forest (RF), and stochastic gradient boosting] with two different candidate variable strategies to implement the optimal spatial above-ground biomass (AGB) estimation. The results suggested that RF algorithm exhibited the best performance by 10-fold cross-validation with respect to R2 (0.63) and root-mean-square error (26.44 ton/ha). Consequently, the map of estimated AGB was generated with a mean value of 89.34 ton/ha in northwestern Zhejiang Province, China, with a similar pattern to the distribution mode of local forest species. This research indicates that machine-learning approaches associated with Landsat imagery provide an economical way for biomass estimation. Moreover, ensemble methods using all candidate variables, especially for Landsat images, provide an alternative for regional biomass simulation.

Massive mortality of aspen following severe drought along the southern edge of the Canadian boreal forest

PubMed Central

Michaelian, Michael; Hogg, Edward H; Hall, Ronald J; Arsenault, Eric

2011-01-01

Drought-induced, regional-scale dieback of forests has emerged as a global concern that is expected to escalate under model projections of climate change. Since 2000, drought of unusual severity, extent, and duration has affected large areas of western North America, leading to regional-scale dieback of forests in the southwestern US. We report on drought impacts on forests in a region farther north, encompassing the transition between boreal forest and prairie in western Canada. A central question is the significance of drought as an agent of large-scale tree mortality and its potential future impact on carbon cycling in this cold region. We used a combination of plot-based, meteorological, and remote sensing measures to map and quantify aboveground, dead biomass of trembling aspen (Populus tremuloides Michx.) across an 11.5 Mha survey area where drought was exceptionally severe during 2001–2002. Within this area, a satellite-based land cover map showed that aspen-dominated broadleaf forests occupied 2.3 Mha. Aerial surveys revealed extensive patches of severe mortality (>55%) resembling the impacts of fire. Dead aboveground biomass was estimated at 45 Mt, representing 20% of the total aboveground biomass, based on a spatial interpolation of plot-based measurements. Spatial variation in percentage dead biomass showed a moderately strong correlation with drought severity. In the prairie-like, southern half of the study area where the drought was most severe, 35% of aspen biomass was dead, compared with an estimated 7% dead biomass in the absence of drought. Drought led to an estimated 29 Mt increase in dead biomass across the survey area, corresponding to 14 Mt of potential future carbon emissions following decomposition. Many recent, comparable episodes of drought-induced forest dieback have been reported from around the world, which points to an emerging need for multiscale monitoring approaches to quantify drought effects on woody biomass and carbon cycling across large areas.

Relationship between aboveground biomass and multiple measures of biodiversity in subtropical forest of Puerto Rico

Treesearch

Heather D. Vance-Chalcraft; Michael R. Willig; Stephen B. Cox; Ariel E. Lugo; Frederick N. Scatena

2010-01-01

Anthropogenic activities have accelerated the rate of global loss of biodiversity, making it more important than ever to understand the structure of biodiversity hotspots. One current focus is the relationship between species richness and aboveground biomass (AGB) in a variety of ecosystems. Nonetheless, species diversity, evenness, rarity, or dominance represent other...

Aboveground biomass and nutrient accumulation 20 years after clear-cutting a southern Appalachian watershed

Treesearch

Katherine J. Elliott; Lindsay R. Boring; Wayne T. Swank

2002-01-01

In 1975, we initiated a long-term interdisciplinary study of forest watershed ecosystem response to clear- cutting and cable logging in watershed 7 at the Coweeta Hydrologic Laboratory in the southern Appalachian Mountains of North Carolina. This paper describes ~20 years of change in species composition, aboveground biomass, leaf area index (LAI),...

Effect of thinning on partitioning of aboveground biomass in naturally regenerated shortleaf pine (Pinus echinata mill.)

Treesearch

Charles O. Sabatia; Rodney E. Will; Thomas B. Lynch

2010-01-01

In traditional harvesting systems, yield of forest stands may increase if a greater proportion of net primary production is allocated to bole wood. However, for management related to whole-tree harvesting, carbon sequestration, biofuels, and wildland fire avoidance, assessments of biomass partitioning to all aboveground components is needed. Thinning increases bole...

Final Harvest of Above-Ground Biomass and Allometric Analysis of the Aspen FACE Experiment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mark E. Kubiske

The Aspen FACE experiment, located at the US Forest Service Harshaw Research Facility in Oneida County, Wisconsin, exposes the intact canopies of model trembling aspen forests to increased concentrations of atmospheric CO2 and O3. The first full year of treatments was 1998 and final year of elevated CO2 and O3 treatments is scheduled for 2009. This proposal is to conduct an intensive, analytical harvest of the above-ground parts of 24 trees from each of the 12, 30 m diameter treatment plots (total of 288 trees) during June, July & August 2009. This above-ground harvest will be carefully coordinated with themore » below-ground harvest proposed by D.F. Karnosky et al. (2008 proposal to DOE). We propose to dissect harvested trees according to annual height growth increment and organ (main stem, branch orders, and leaves) for calculation of above-ground biomass production and allometric comparisons among aspen clones, species, and treatments. Additionally, we will collect fine root samples for DNA fingerprinting to quantify biomass production of individual aspen clones. This work will produce a thorough characterization of above-ground tree and stand growth and allocation above ground, and, in conjunction with the below ground harvest, total tree and stand biomass production, allocation, and allometry.« less

[Aboveground biomass of three conifers in Qianyanzhou plantation].

PubMed

Li, Xuanran; Liu, Qijing; Chen, Yongrui; Hu, Lile; Yang, Fengting

2006-08-01

In this paper, the regressive models of the aboveground biomass of Pinus elliottii, P. massoniana and Cunninghamia lanceolata in Qianyanzhou of subtropical China were established, and the regression analysis on the dry weight of leaf biomass and total biomass against branch diameter (d), branch length (L), d3 and d2L was conducted with linear, power and exponent functions. Power equation with single parameter (d) was proved to be better than the rests for P. massoniana and C. lanceolata, and linear equation with parameter (d3) was better for P. elliottii. The canopy biomass was derived by the regression equations for all branches. These equations were also used to fit the relationships of total tree biomass, branch biomass and foliage biomass with tree diameter at breast height (D), tree height (H), D3 and D2H, respectively. D2H was found to be the best parameter for estimating total biomass. For foliage-and branch biomass, both parameters and equation forms showed some differences among species. Correlations were highly significant (P <0.001) for foliage-, branch-and total biomass, with the highest for total biomass. By these equations, the aboveground biomass and its allocation were estimated, with the aboveground biomass of P. massoniana, P. elliottii, and C. lanceolata forests being 83.6, 72. 1 and 59 t x hm(-2), respectively, and more stem biomass than foliage-and branch biomass. According to the previous studies, the underground biomass of these three forests was estimated to be 10.44, 9.42 and 11.48 t x hm(-2), and the amount of fixed carbon was 47.94, 45.14 and 37.52 t x hm(-2), respectively.

The Oldest, Slowest Rainforests in the World? Massive Biomass and Slow Carbon Dynamics of Fitzroya cupressoides Temperate Forests in Southern Chile.

PubMed

Urrutia-Jalabert, Rocio; Malhi, Yadvinder; Lara, Antonio

2015-01-01

Old-growth temperate rainforests are, per unit area, the largest and most long-lived stores of carbon in the terrestrial biosphere, but their carbon dynamics have rarely been described. The endangered Fitzroya cupressoides forests of southern South America include stands that are probably the oldest dense forest stands in the world, with long-lived trees and high standing biomass. We assess and compare aboveground biomass, and provide the first estimates of net primary productivity (NPP), carbon allocation and mean wood residence time in medium-age stands in the Alerce Costero National Park (AC) in the Coastal Range and in old-growth forests in the Alerce Andino National Park (AA) in the Andean Cordillera. Aboveground live biomass was 113-114 Mg C ha(-1) and 448-517 Mg C ha(-1) in AC and AA, respectively. Aboveground productivity was 3.35-3.36 Mg C ha(-1) year(-1) in AC and 2.22-2.54 Mg C ha(-1) year(-1) in AA, values generally lower than others reported for temperate wet forests worldwide, mainly due to the low woody growth of Fitzroya. NPP was 4.21-4.24 and 3.78-4.10 Mg C ha(-1) year(-1) in AC and AA, respectively. Estimated mean wood residence time was a minimum of 539-640 years for the whole forest in the Andes and 1368-1393 years for only Fitzroya in this site. Our biomass estimates for the Andes place these ecosystems among the most massive forests in the world. Differences in biomass production between sites seem mostly apparent as differences in allocation rather than productivity. Residence time estimates for Fitzroya are the highest reported for any species and carbon dynamics in these forests are the slowest reported for wet forests worldwide. Although primary productivity is low in Fitzroya forests, they probably act as ongoing biomass carbon sinks on long-term timescales due to their low mortality rates and exceptionally long residence times that allow biomass to be accumulated for millennia.

The Oldest, Slowest Rainforests in the World? Massive Biomass and Slow Carbon Dynamics of Fitzroya cupressoides Temperate Forests in Southern Chile

PubMed Central

Urrutia-Jalabert, Rocio; Malhi, Yadvinder; Lara, Antonio

2015-01-01

Old-growth temperate rainforests are, per unit area, the largest and most long-lived stores of carbon in the terrestrial biosphere, but their carbon dynamics have rarely been described. The endangered Fitzroya cupressoides forests of southern South America include stands that are probably the oldest dense forest stands in the world, with long-lived trees and high standing biomass. We assess and compare aboveground biomass, and provide the first estimates of net primary productivity (NPP), carbon allocation and mean wood residence time in medium-age stands in the Alerce Costero National Park (AC) in the Coastal Range and in old-growth forests in the Alerce Andino National Park (AA) in the Andean Cordillera. Aboveground live biomass was 113–114 Mg C ha-1 and 448–517 Mg C ha-1 in AC and AA, respectively. Aboveground productivity was 3.35–3.36 Mg C ha-1 year-1 in AC and 2.22–2.54 Mg C ha-1 year-1 in AA, values generally lower than others reported for temperate wet forests worldwide, mainly due to the low woody growth of Fitzroya. NPP was 4.21–4.24 and 3.78–4.10 Mg C ha-1 year-1 in AC and AA, respectively. Estimated mean wood residence time was a minimum of 539–640 years for the whole forest in the Andes and 1368–1393 years for only Fitzroya in this site. Our biomass estimates for the Andes place these ecosystems among the most massive forests in the world. Differences in biomass production between sites seem mostly apparent as differences in allocation rather than productivity. Residence time estimates for Fitzroya are the highest reported for any species and carbon dynamics in these forests are the slowest reported for wet forests worldwide. Although primary productivity is low in Fitzroya forests, they probably act as ongoing biomass carbon sinks on long-term timescales due to their low mortality rates and exceptionally long residence times that allow biomass to be accumulated for millennia. PMID:26353111

Landscape-level effects on aboveground biomass of tropical forests: A conceptual framework.

PubMed

Melito, Melina; Metzger, Jean Paul; de Oliveira, Alexandre A

2018-02-01

Despite the general recognition that fragmentation can reduce forest biomass through edge effects, a systematic review of the literature does not reveal a clear role of edges in modulating biomass loss. Additionally, the edge effects appear to be constrained by matrix type, suggesting that landscape composition has an influence on biomass stocks. The lack of empirical evidence of pervasive edge-related biomass losses across tropical forests highlights the necessity for a general framework linking landscape structure with aboveground biomass. Here, we propose a conceptual model in which landscape composition and configuration mediate the magnitude of edge effects and seed-flux among forest patches, which ultimately has an influence on biomass. Our model hypothesizes that a rapid reduction of biomass can occur below a threshold of forest cover loss. Just below this threshold, we predict that changes in landscape configuration can strongly influence the patch's isolation, thus enhancing biomass loss. Moreover, we expect a synergism between landscape composition and patch attributes, where matrix type mediates the effects of edges on species decline, particularly for shade-tolerant species. To test our conceptual framework, we propose a sampling protocol where the effects of edges, forest amount, forest isolation, fragment size, and matrix type on biomass stocks can be assessed both collectively and individually. The proposed model unifies the combined effects of landscape and patch structure on biomass into a single framework, providing a new set of main drivers of biomass loss in human-modified landscapes. We argue that carbon trading agendas (e.g., REDD+) and carbon-conservation initiatives must go beyond the effects of forest loss and edges on biomass, considering the whole set of effects on biomass related to changes in landscape composition and configuration. © 2017 John Wiley & Sons Ltd.

Model Effects on GLAS-Based Regional Estimates of Forest Biomass and Carbon

NASA Technical Reports Server (NTRS)

Nelson, Ross

2008-01-01

ICESat/GLAS waveform data are used to estimate biomass and carbon on a 1.27 million sq km study area. the Province of Quebec, Canada, below treeline. The same input data sets and sampling design are used in conjunction with four different predictive models to estimate total aboveground dry forest biomass and forest carbon. The four models include nonstratified and stratified versions of a multiple linear model where either biomass or (square root of) biomass serves as the dependent variable. The use of different models in Quebec introduces differences in Provincial biomass estimates of up to 0.35 Gt (range 4.942+/-0.28 Gt to 5.29+/-0.36 Gt). The results suggest that if different predictive models are used to estimate regional carbon stocks in different epochs, e.g., y2005, y2015, one might mistakenly infer an apparent aboveground carbon "change" of, in this case, 0.18 Gt, or approximately 7% of the aboveground carbon in Quebec, due solely to the use of different predictive models. These findings argue for model consistency in future, LiDAR-based carbon monitoring programs. Regional biomass estimates from the four GLAS models are compared to ground estimates derived from an extensive network of 16,814 ground plots located in southern Quebec. Stratified models proved to be more accurate and precise than either of the two nonstratified models tested.

Mapping U.S. forest biomass using nationwide forest inventory data and moderate resolution information

Treesearch

J. A. Blackard; M. V. Finco; E. H. Helmer; G. R. Holden; M. L. Hoppus; D.M. Jacobs; A. J. Lister; G. G. Moisen; M. D. Nelson; R. Riemann; B. Ruefenacht; D. Salajanu; D. L. Weyermann; K. C. Winterberger; T. J. Brandeis; R. L. Czaplewski; R. E. McRoberts; P. L. Patterson; R. P. Tymcio

2008-01-01

A spatially explicit dataset of aboveground live forest biomass was made from ground measured inventory plots for the conterminous U.S., Alaska and Puerto Rico. The plot data are from the USDA Forest Service Forest Inventory and Analysis (FIA) program. To scale these plot data to maps, we developed models relating field-measured response variables to plot attributes...

A Study on PolInSAR Coherence Based Regression Analysis of Forest Biomass (BARKOT Reserve Forest India), Using RADARSAT-2 Datasets

NASA Astrophysics Data System (ADS)

Singh, J.; Kumar, S.; Kushwaha, S. P. S.

2015-04-01

Forests cover 30% of the world's land surface, and are home to around 90% of the world's flora and fauna. They serve as one of the world's largest carbon sinks, absorbing 2.4 million tons of CO2 each year and storing billions more in form of biomass. Around 6 million hectares of forest is lost or changed each year and as much as a fifth of global emissions are estimated to come from deforestation. Hence accurate estimation of forest biophysical variables is necessary as it is a key parameter in determination of forest inventories, vegetation modeling and global carbon cycle. SAR Remote sensing technique is capable of providing accurate and reliable information about forest parameters. The present work aims to explore the potential of C-band Radarsat-2 Polarimetric Interferometric Synthetic Aperture Radar (PolinSAR) technique for developing a relationship between complex coherence and forest aboveground biomass (t/ha). In order to attain our objective Radarsat-2 satellite interferometric pair of 4th March 2013(master image) and 28th March 2013(slave image) were acquired for Barkot Reserve Forest, Dehradun, India. Field inventory was done for 30 plots (31.62m x 31.62m) and tree height and stem diameter were procured for each plot which were later utilized in calculation of aboveground biomass(AGB).Work emphasizes on the application of PolinSAR coherence instead of using SAR backscatter which saturates after a certain value of biomass content. Complex coherence values for different polarization channels were computed with the help of polarimetric interferometric coherence matrix. Retrieved complex coherences were investigated individually and then regression analysis was carried with the field estimated aboveground biomass. R2 value of HV+VH complex coherence component was found to be relatively higher than other polarization channel components

Deriving biomass models for small-diameter loblolly pine on the Crossett Experimental Forest

Treesearch

K.M. McElligott; D.C. Bragg

2013-01-01

Foresters and landowners have a growing interest in carbon sequestration and cellulosic biofuels in southern pine forests, and hence need to be able to accurately predict them. To this end, we derived a set of aboveground biomass models using data from 62 small-diameter loblolly pines (Pinus taeda) sampled on the Crossett Experimental Forest in...

Amazonian landscapes and the bias in field studies of forest structure and biomass.

PubMed

Marvin, David C; Asner, Gregory P; Knapp, David E; Anderson, Christopher B; Martin, Roberta E; Sinca, Felipe; Tupayachi, Raul

2014-12-02

Tropical forests convert more atmospheric carbon into biomass each year than any terrestrial ecosystem on Earth, underscoring the importance of accurate tropical forest structure and biomass maps for the understanding and management of the global carbon cycle. Ecologists have long used field inventory plots as the main tool for understanding forest structure and biomass at landscape-to-regional scales, under the implicit assumption that these plots accurately represent their surrounding landscape. However, no study has used continuous, high-spatial-resolution data to test whether field plots meet this assumption in tropical forests. Using airborne LiDAR (light detection and ranging) acquired over three regions in Peru, we assessed how representative a typical set of field plots are relative to their surrounding host landscapes. We uncovered substantial mean biases (9-98%) in forest canopy structure (height, gaps, and layers) and aboveground biomass in both lowland Amazonian and montane Andean landscapes. Moreover, simulations reveal that an impractical number of 1-ha field plots (from 10 to more than 100 per landscape) are needed to develop accurate estimates of aboveground biomass at landscape scales. These biases should temper the use of plots for extrapolations of forest dynamics to larger scales, and they demonstrate the need for a fundamental shift to high-resolution active remote sensing techniques as a primary sampling tool in tropical forest biomass studies. The potential decrease in the bias and uncertainty of remotely sensed estimates of forest structure and biomass is a vital step toward successful tropical forest conservation and climate-change mitigation policy.

Diversity and aboveground biomass of lianas in the tropical seasonal rain forests of Xishuangbanna, SW China.

PubMed

Lü, Xiao-Tao; Tang, Jian-Wei; Feng, Zhi-Li; Li, Mai-He

2009-01-01

Lianas are important components of tropical forests and have significant impacts on the diversity, structure and dynamics of tropical forests. The present study documented the liana flora in a Chinese tropical region. Species richness, abundance, size-class distribution and spatial patterns of lianas were investigated in three 1-ha plots in tropical seasonal rain forests in Xishuangbanna, SW China. All lianas with > or = 2 cm diameter at breast height (dbh) were measured, tagged and identified. A total of 458 liana stems belonging to 95 species (ranging from 38 to 50 species/ha), 59 genera and 32 families were recorded in the three plots. The most well-represented families were Loganiaceae, Annonceae, Papilionaceae, Apocynaceae and Rhamnaceae. Papilionaceae (14 species recorded) was the most important family in the study forests. The population density, basal area and importance value index (IVI) varied greatly across the three plots. Strychnos cathayensis, Byttneria grandifolia and Bousigonia mekongensis were the dominant species in terms of IVI across the three plots. The mean aboveground biomass of lianas (3 396 kg/ha) accounted for 1.4% of the total community above-ground biomass. The abundance, diversity and biomass of lianas in Xishuangbanna tropical seasonal rain forests are lower than those in tropical moist and wet forests, but higher than those in tropical dry forests. This study provides new data on lianas from a geographical region that has been little-studied. Our findings emphasize that other factors beyond the amount and seasonality of precipitation should be included when considering the liana abundance patterns across scales.

Simulating Carbon Stocks and Fluxes of an African Tropical Montane Forest with an Individual-Based Forest Model

PubMed Central

Fischer, Rico; Ensslin, Andreas; Rutten, Gemma; Fischer, Markus; Schellenberger Costa, David; Kleyer, Michael; Hemp, Andreas; Paulick, Sebastian; Huth, Andreas

2015-01-01

Tropical forests are carbon-dense and highly productive ecosystems. Consequently, they play an important role in the global carbon cycle. In the present study we used an individual-based forest model (FORMIND) to analyze the carbon balances of a tropical forest. The main processes of this model are tree growth, mortality, regeneration, and competition. Model parameters were calibrated using forest inventory data from a tropical forest at Mt. Kilimanjaro. The simulation results showed that the model successfully reproduces important characteristics of tropical forests (aboveground biomass, stem size distribution and leaf area index). The estimated aboveground biomass (385 t/ha) is comparable to biomass values in the Amazon and other tropical forests in Africa. The simulated forest reveals a gross primary production of 24 tcha-1yr-1. Modeling above- and belowground carbon stocks, we analyzed the carbon balance of the investigated tropical forest. The simulated carbon balance of this old-growth forest is zero on average. This study provides an example of how forest models can be used in combination with forest inventory data to investigate forest structure and local carbon balances. PMID:25915854

Assessing biomass accumulation in second growth forests of Puerto Rico using airborne lidar

NASA Astrophysics Data System (ADS)

Martinuzzi, S.; Cook, B.; Corp, L. A.; Morton, D. C.; Helmer, E.; Keller, M.

2017-12-01

Degraded and second growth tropical forests provide important ecosystem services, such as carbon sequestration and soil stabilization. Lidar data measure the three-dimensional structure of forest canopies and are commonly used to quantify aboveground biomass in temperate forest landscapes. However, the ability of lidar data to quantify second growth forest biomass in complex, tropical landscapes is less understood. Our goal was to evaluate the use of airborne lidar data to quantify aboveground biomass in a complex tropical landscape, the Caribbean island of Puerto Rico. Puerto Rico provides an ideal place for studying biomass accumulation because of the abundance of second growth forests in different stages of recovery, and the high ecological heterogeneity. Puerto Rico was almost entirely deforested for agriculture until the 1930s. Thereafter, agricultural abandonment resulted in a mosaic of second growth forests that have recovered naturally under different types of climate, land use, topography, and soil fertility. We integrated forest plot data from the US Forest Service, Forest Inventory and Analysis (FIA) Program with recent lidar data from NASA Goddard's Lidar, Hyperspectral, and Thermal (G-LiHT) airborne imager to quantify forest biomass across the island's landscape. The G-LiHT data consisted on targeted acquisitions over the FIA plots and other forested areas representing the environmental heterogeneity of the island. To fully assess the potential of the lidar data, we compared the ability of lidar-derived canopy metrics to quantify biomass alone, and in combination with intensity and topographic metrics. The results presented here are a key step for improving our understanding of the patterns and drivers of biomass accumulation in tropical forests.

Detrital carbon pools in temperate forests: magnitude and potential for landscape-scale assessment

Treesearch

John B. Bradford; Peter Weishampel; Marie-Louise Smith; Randall Kolka; Richard A. Birdsey; Scott V. Ollinger; Michael G. Ryan

2009-01-01

Reliably estimating carbon storage and cycling in detrital biomass is an obstacle to carbon accounting. We examined carbon pools and fluxes in three small temperate forest landscapes to assess the magnitude of carbon stored in detrital biomass and determine whether detrital carbon storage is related to stand structural properties (leaf area, aboveground biomass,...

Net aboveground biomass declines of four major forest types with forest ageing and climate change in western Canada's boreal forests.

PubMed

Chen, Han Y H; Luo, Yong

2015-10-01

Biomass change of the world's forests is critical to the global carbon cycle. Despite storing nearly half of global forest carbon, the boreal biome of diverse forest types and ages is a poorly understood component of the carbon cycle. Using data from 871 permanent plots in the western boreal forest of Canada, we examined net annual aboveground biomass change (ΔAGB) of four major forest types between 1958 and 2011. We found that ΔAGB was higher for deciduous broadleaf (DEC) (1.44 Mg ha(-1)  year(-1) , 95% Bayesian confidence interval (CI), 1.22-1.68) and early-successional coniferous forests (ESC) (1.42, CI, 1.30-1.56) than mixed forests (MIX) (0.80, CI, 0.50-1.11) and late-successional coniferous (LSC) forests (0.62, CI, 0.39-0.88). ΔAGB declined with forest age as well as calendar year. After accounting for the effects of forest age, ΔAGB declined by 0.035, 0.021, 0.032 and 0.069 Mg ha(-1)  year(-1) per calendar year in DEC, ESC, MIX and LSC forests, respectively. The ΔAGB declines resulted from increased tree mortality and reduced growth in all forest types except DEC, in which a large biomass loss from mortality was accompanied with a small increase in growth. With every degree of annual temperature increase, ΔAGB decreased by 1.00, 0.20, 0.55 and 1.07 Mg ha(-1)  year(-1) in DEC, ESC, MIX and LSC forests, respectively. With every cm decrease of annual climatic moisture availability, ΔAGB decreased 0.030, 0.045 and 0.17 Mg ha(-1)  year(-1) in ESC, MIX and LSC forests, but changed little in DEC forests. Our results suggest that persistent warming and decreasing water availability have profound negative effects on forest biomass in the boreal forests of western Canada. Furthermore, our results indicate that forest responses to climate change are strongly dependent on forest composition with late-successional coniferous forests being most vulnerable to climate changes in terms of aboveground biomass. © 2015 John Wiley & Sons Ltd.

Aboveground carbon in Quebec forests: stock quantification at the provincial scale and assessment of temperature, precipitation and edaphic properties effects on the potential stand-level stocking.

PubMed

Duchesne, Louis; Houle, Daniel; Ouimet, Rock; Lambert, Marie-Claude; Logan, Travis

2016-01-01

Biological carbon sequestration by forest ecosystems plays an important role in the net balance of greenhouse gases, acting as a carbon sink for anthropogenic CO2 emissions. Nevertheless, relatively little is known about the abiotic environmental factors (including climate) that control carbon storage in temperate and boreal forests and consequently, about their potential response to climate changes. From a set of more than 94,000 forest inventory plots and a large set of spatial data on forest attributes interpreted from aerial photographs, we constructed a fine-resolution map (∼375 m) of the current carbon stock in aboveground live biomass in the 435,000 km(2) of managed forests in Quebec, Canada. Our analysis resulted in an area-weighted average aboveground carbon stock for productive forestland of 37.6 Mg ha(-1), which is lower than commonly reported values for similar environment. Models capable of predicting the influence of mean annual temperature, annual precipitation, and soil physical environment on maximum stand-level aboveground carbon stock (MSAC) were developed. These models were then used to project the future MSAC in response to climate change. Our results indicate that the MSAC was significantly related to both mean annual temperature and precipitation, or to the interaction of these variables, and suggest that Quebec's managed forests MSAC may increase by 20% by 2041-2070 in response to climate change. Along with changes in climate, the natural disturbance regime and forest management practices will nevertheless largely drive future carbon stock at the landscape scale. Overall, our results allow accurate accounting of carbon stock in aboveground live tree biomass of Quebec's forests, and provide a better understanding of possible feedbacks between climate change and carbon storage in temperate and boreal forests.

Changes in forest biomass and tree species distribution under climate change in the northeastern United States

Treesearch

Wen J. Wang; Hong S. He; Frank R. Thompson; Jacob S. Fraser; William D. Dijak

2016-01-01

Context. Forests in the northeastern United States are currently in early- and mid-successional stages recovering from historical land use. Climate change will affect forest distribution and structure and have important implications for biodiversity, carbon dynamics, and human well-being. Objective. We addressed how aboveground biomass (AGB) and...

Litterfall in the hardwood forest of a minor alluvial-floodplain

Treesearch

Calvin E. Meier; John A. Stanturf; Emile S. Gardiner

2006-01-01

within mature deciduous forests, annual development of foliar biomass is a major component of aboveground net primary production and nutrient demand. As litterfall, this same foliage becomes a dominant annual transfer of biomass and nutrients to the detritus pathway. We report litterfall transfers of a mature bottomland hardwood forest in a minor alluvial-floodplain...

Evaluating land use and aboveground biomass dynamics in an oil palm-dominated landscape in Borneo using optical remote sensing

NASA Astrophysics Data System (ADS)

Singh, Minerva; Malhi, Yadvinder; Bhagwat, Shonil

2014-01-01

The focus of this study is to assess the efficacy of using optical remote sensing (RS) in evaluating disparities in forest composition and aboveground biomass (AGB). The research was carried out in the East Sabah region, Malaysia, which constitutes a disturbance gradient ranging from pristine old growth forests to forests that have experienced varying levels of disturbances. Additionally, a significant proportion of the area consists of oil palm plantations. In accordance with local laws, riparian forest (RF) zones have been retained within oil palm plantations and other forest types. The RS imagery was used to assess forest stand structure and AGB. Band reflectance, vegetation indicators, and gray-level co-occurrence matrix (GLCM) consistency features were used as predictor variables in regression analysis. Results indicate that the spectral variables were limited in their effectiveness in differentiating between forest types and in calculating biomass. However, GLCM based variables illustrated strong correlations with the forest stand structures as well as with the biomass of the various forest types in the study area. The present study provides new insights into the efficacy of texture examination methods in differentiating between various land-use types (including small, isolated forest zones such as RFs) as well as their AGB stocks.

The role of gap phase processes in the biomass dynamics of tropical forests

PubMed Central

Feeley, Kenneth J; Davies, Stuart J; Ashton, Peter S; Bunyavejchewin, Sarayudh; Nur Supardi, M.N; Kassim, Abd Rahman; Tan, Sylvester; Chave, Jérôme

2007-01-01

The responses of tropical forests to global anthropogenic disturbances remain poorly understood. Above-ground woody biomass in some tropical forest plots has increased over the past several decades, potentially reflecting a widespread response to increased resource availability, for example, due to elevated atmospheric CO2 and/or nutrient deposition. However, previous studies of biomass dynamics have not accounted for natural patterns of disturbance and gap phase regeneration, making it difficult to quantify the importance of environmental changes. Using spatially explicit census data from large (50 ha) inventory plots, we investigated the influence of gap phase processes on the biomass dynamics of four ‘old-growth’ tropical forests (Barro Colorado Island (BCI), Panama; Pasoh and Lambir, Malaysia; and Huai Kha Khaeng (HKK), Thailand). We show that biomass increases were gradual and concentrated in earlier-phase forest patches, while biomass losses were generally of greater magnitude but concentrated in rarer later-phase patches. We then estimate the rate of biomass change at each site independent of gap phase dynamics using reduced major axis regressions and ANCOVA tests. Above-ground woody biomass increased significantly at Pasoh (+0.72% yr−1) and decreased at HKK (−0.56% yr−1) independent of changes in gap phase but remained stable at both BCI and Lambir. We conclude that gap phase processes play an important role in the biomass dynamics of tropical forests, and that quantifying the role of gap phase processes will help improve our understanding of the factors driving changes in forest biomass as well as their place in the global carbon budget. PMID:17785266

The role of gap phase processes in the biomass dynamics of tropical forests.

PubMed

Feeley, Kenneth J; Davies, Stuart J; Ashton, Peter S; Bunyavejchewin, Sarayudh; Nur Supardi, M N; Kassim, Abd Rahman; Tan, Sylvester; Chave, Jérôme

2007-11-22

The responses of tropical forests to global anthropogenic disturbances remain poorly understood. Above-ground woody biomass in some tropical forest plots has increased over the past several decades, potentially reflecting a widespread response to increased resource availability, for example, due to elevated atmospheric CO2 and/or nutrient deposition. However, previous studies of biomass dynamics have not accounted for natural patterns of disturbance and gap phase regeneration, making it difficult to quantify the importance of environmental changes. Using spatially explicit census data from large (50 ha) inventory plots, we investigated the influence of gap phase processes on the biomass dynamics of four 'old-growth' tropical forests (Barro Colorado Island (BCI), Panama; Pasoh and Lambir, Malaysia; and Huai Kha Khaeng (HKK), Thailand). We show that biomass increases were gradual and concentrated in earlier-phase forest patches, while biomass losses were generally of greater magnitude but concentrated in rarer later-phase patches. We then estimate the rate of biomass change at each site independent of gap phase dynamics using reduced major axis regressions and ANCOVA tests. Above-ground woody biomass increased significantly at Pasoh (+0.72% yr(-1)) and decreased at HKK (-0.56% yr(-1)) independent of changes in gap phase but remained stable at both BCI and Lambir. We conclude that gap phase processes play an important role in the biomass dynamics of tropical forests, and that quantifying the role of gap phase processes will help improve our understanding of the factors driving changes in forest biomass as well as their place in the global carbon budget.

Forest biomass change estimated from height change in interferometric SAR height models.

PubMed

Solberg, Svein; Næsset, Erik; Gobakken, Terje; Bollandsås, Ole-Martin

2014-12-01

There is a need for new satellite remote sensing methods for monitoring tropical forest carbon stocks. Advanced RADAR instruments on board satellites can contribute with novel methods. RADARs can see through clouds, and furthermore, by applying stereo RADAR imaging we can measure forest height and its changes. Such height changes are related to carbon stock changes in the biomass. We here apply data from the current Tandem-X satellite mission, where two RADAR equipped satellites go in close formation providing stereo imaging. We combine that with similar data acquired with one of the space shuttles in the year 2000, i.e. the so-called SRTM mission. We derive height information from a RADAR image pair using a method called interferometry. We demonstrate an approach for REDD based on interferometry data from a boreal forest in Norway. We fitted a model to the data where above-ground biomass in the forest increases with 15 t/ha for every m increase of the height of the RADAR echo. When the RADAR echo is at the ground the estimated biomass is zero, and when it is 20 m above the ground the estimated above-ground biomass is 300 t/ha. Using this model we obtained fairly accurate estimates of biomass changes from 2000 to 2011. For 200 m 2 plots we obtained an accuracy of 65 t/ha, which corresponds to 50% of the mean above-ground biomass value. We also demonstrate that this method can be applied without having accurate terrain heights and without having former in-situ biomass data, both of which are generally lacking in tropical countries. The gain in accuracy was marginal when we included such data in the estimation. Finally, we demonstrate that logging and other biomass changes can be accurately mapped. A biomass change map based on interferometry corresponded well to a very accurate map derived from repeated scanning with airborne laser. Satellite based, stereo imaging with advanced RADAR instruments appears to be a promising method for REDD. Interferometric processing of the RADAR data provides maps of forest height changes from which we can estimate temporal changes in biomass and carbon.

Combining LIDAR estimates of aboveground biomass and Landsat estimates of stand age for spatially extensive validation of modeled forest productivity.

Treesearch

M.A. Lefsky; D.P. Turner; M. Guzy; W.B. Cohen

2005-01-01

Extensive estimates of forest productivity are required to understand the relationships between shifting land use, changing climate and carbon storage and fluxes. Aboveground net primary production of wood (NPPAw) is a major component of total NPP and of net ecosystem production (NEP). Remote sensing of NPP and NPPAw is...

Individual tree size inequality enhances aboveground biomass in homegarden agroforestry systems in the dry zone of Sri Lanka.

PubMed

Ali, Arshad; Mattsson, Eskil

2017-01-01

Individual tree size variation, which is generally quantified by variances in tree diameter at breast height (DBH) and height in isolation or conjunction, plays a central role in ecosystem functioning in both controlled and natural environments, including forests. However, none of the studies have been conducted in homegarden agroforestry systems. In this study, aboveground biomass, stand quality, cation exchange capacity (CEC), DBH variation, and species diversity were determined across 45 homegardens in the dry zone of Sri Lanka. We employed structural equation modeling (SEM) to test for the direct and indirect effects of stand quality and CEC, via tree size inequality and species diversity, on aboveground biomass. The SEM accounted for 26, 8, and 1% of the variation in aboveground biomass, species diversity and DBH variation, respectively. DBH variation had the strongest positive direct effect on aboveground biomass (β=0.49), followed by the non-significant direct effect of species diversity (β=0.17), stand quality (β=0.17) and CEC (β=-0.05). There were non-significant direct effects of CEC and stand quality on DBH variation and species diversity. Stand quality and CEC had also non-significant indirect effects, via DBH variation and species diversity, on aboveground biomass. Our study revealed that aboveground biomass substantially increased with individual tree size variation only, which supports the niche complementarity mechanism. However, aboveground biomass was not considerably increased with species diversity, stand quality and soil fertility, which might be attributable to the adaptation of certain productive species to the local site conditions. Stand structure shaped by few productive species or independent of species diversity is a main determinant for the variation in aboveground biomass in the studied homegardens. Maintaining stand structure through management practices could be an effective approach for enhancing aboveground biomass in these dry zone homegarden agroforestry systems. Copyright © 2016 Elsevier B.V. All rights reserved.

Comparing aboveground biomass predictions for an uneven-aged pine-dominated stand using local, regional, and national models

Treesearch

D.C. Bragg; K.M. McElligott

2013-01-01

Sequestration by Arkansas forests removes carbon dioxide from the atmosphere, storing this carbon in biomass that fills a number of critical ecological and socioeconomic functions. We need a better understanding of the contribution of forests to the carbon cycle, including the accurate quantification of tree biomass. Models have long been developed to predict...

Aboveground tree biomass for Pinus ponderosa in northeastern California

Treesearch

Martin W. Ritchie; Jianwei Zhang; Todd A. Hamilton

2013-01-01

Forest managers need accurate biomass equations to plan thinning for fuel reduction or energy production. Estimates of carbon sequestration also rely upon such equations. The current allometric equations for ponderosa pine (Pinus ponderosa) commonly employed for California forests were developed elsewhere, and are often applied without consideration potential for...

Aboveground Tree Growth Varies with Belowground Carbon Allocation in a Tropical Rainforest Environment

PubMed Central

Raich, James W.; Clark, Deborah A.; Schwendenmann, Luitgard; Wood, Tana E.

2014-01-01

Young secondary forests and plantations in the moist tropics often have rapid rates of biomass accumulation and thus sequester large amounts of carbon. Here, we compare results from mature forest and nearby 15–20 year old tree plantations in lowland Costa Rica to evaluate differences in allocation of carbon to aboveground production and root systems. We found that the tree plantations, which had fully developed, closed canopies, allocated more carbon belowground - to their root systems - than did mature forest. This increase in belowground carbon allocation correlated significantly with aboveground tree growth but not with canopy production (i.e., leaf fall or fine litter production). In contrast, there were no correlations between canopy production and either tree growth or belowground carbon allocation. Enhanced allocation of carbon to root systems can enhance plant nutrient uptake, providing nutrients beyond those required for the production of short-lived tissues such as leaves and fine roots, and thus enabling biomass accumulation. Our analyses support this deduction at our site, showing that enhanced allocation of carbon to root systems can be an important mechanism promoting biomass accumulation during forest growth in the moist tropics. Identifying factors that control when, where and for how long this occurs would help us to improve models of forest growth and nutrient cycling, and to ascertain the role that young forests play in mitigating increased atmospheric carbon dioxide. PMID:24945351

Forest biomass estimated from MODIS and FIA data in the Lake States: MN, WI and MI, USA

Treesearch

Daolan Zheng; Linda S. Heath; Mark J. Ducey

2007-01-01

This study linked the Moderate Resolution Imaging Spectrometer and USDA Forest Service, Forest Inventory and Analysis (FIA) data through empirical models established using high-resolution Landsat Enhanced Thematic Mapper Plus observations to estimate aboveground biomass (AGB) in three Lake States in the north-central USA. While means obtained from larger sample sizes...

Spatially-explicit modeling of multi-scale drivers of aboveground forest biomass and water yield in watersheds of the Southeastern United States.

PubMed

Ajaz Ahmed, Mukhtar Ahmed; Abd-Elrahman, Amr; Escobedo, Francisco J; Cropper, Wendell P; Martin, Timothy A; Timilsina, Nilesh

2017-09-01

Understanding ecosystem processes and the influence of regional scale drivers can provide useful information for managing forest ecosystems. Examining more local scale drivers of forest biomass and water yield can also provide insights for identifying and better understanding the effects of climate change and management on forests. We used diverse multi-scale datasets, functional models and Geographically Weighted Regression (GWR) to model ecosystem processes at the watershed scale and to interpret the influence of ecological drivers across the Southeastern United States (SE US). Aboveground forest biomass (AGB) was determined from available geospatial datasets and water yield was estimated using the Water Supply and Stress Index (WaSSI) model at the watershed level. Our geostatistical model examined the spatial variation in these relationships between ecosystem processes, climate, biophysical, and forest management variables at the watershed level across the SE US. Ecological and management drivers at the watershed level were analyzed locally to identify whether drivers contribute positively or negatively to aboveground forest biomass and water yield ecosystem processes and thus identifying potential synergies and tradeoffs across the SE US region. Although AGB and water yield drivers varied geographically across the study area, they were generally significantly influenced by climate (rainfall and temperature), land-cover factor1 (Water and barren), land-cover factor2 (wetland and forest), organic matter content high, rock depth, available water content, stand age, elevation, and LAI drivers. These drivers were positively or negatively associated with biomass or water yield which significantly contributes to ecosystem interactions or tradeoff/synergies. Our study introduced a spatially-explicit modelling framework to analyze the effect of ecosystem drivers on forest ecosystem structure, function and provision of services. This integrated model approach facilitates multi-scale analyses of drivers and interactions at the local to regional scale. Copyright © 2017 Elsevier Ltd. All rights reserved.

Aboveground tree growth varies with belowground carbon allocation in a tropical rainforest environment

Treesearch

J.W. Raich; D.A. Clark; L. Schwendenmann; Tana Wood

2014-01-01

Young secondary forests and plantations in the moist tropics often have rapid rates of biomass accumulation and thus sequester large amounts of carbon. Here, we compare results from mature forest and nearby 15–20 year old tree plantations in lowland Costa Rica to evaluate differences in allocation of carbon to aboveground production and root systems. We found that the...

Fine Root Dynamics and Forest Production Across a Calcium Gradient in Northern Hardwood and Conifer Ecosystems

Treesearch

Byung Bae Park; Ruth D. Yanai; Timothy J. Fahey; Scott W. Bailey; Thomas G. Siccama; James B. Shanley; Natalie L. Cleavitt

2008-01-01

Losses of soil base cations due to acid rain have been implicated in declines of red spruce and sugar maple in the northeastern USA. We studied fine root and aboveground biomass and production in five northern hardwood and three conifer stands differing in soil Ca status at Sleepers River, VT; Hubbard Brook, NH; and Cone Pond, NH. Neither aboveground biomass and...

Non-pulp utilization of above-ground biomass of mixed-species forests of small trees

Treesearch

P. Koch

1982-01-01

This soulution propose to rehabilitate annually- by clear felling, site preparation, and planting- 25,000 acres of level to rolling land averaging about490 cubic feet per acre of stemwood in small hardwood trees 5 inches in diameter at breast height (dbh) and larger, and of many species, plus all equal volume of above-ground biomass in stembark and tops, and in trees...

Disentangling the effects of species diversity, and intraspecific and interspecific tree size variation on aboveground biomass in dry zone homegarden agroforestry systems.

PubMed

Ali, Arshad; Mattsson, Eskil

2017-11-15

The biodiversity - aboveground biomass relationship has been intensively studied in recent decades. However, no consensus has been arrived to consider the interplay of species diversity, and intraspecific and interspecific tree size variation in driving aboveground biomass, after accounting for the effects of plot size heterogeneity, soil fertility and stand quality in natural forest including agroforests. We tested the full, partial and no mediations effects of species diversity, and intraspecific and interspecific tree size variation on aboveground biomass by employing structural equation models (SEMs) using data from 45 homegarden agroforestry systems in Sri Lanka. The full mediation effect of either species diversity or intraspecific and interspecific tree size variation was rejected, while the partial and no mediation effects were accepted. In the no mediation SEM, homegarden size had the strongest negative direct effect (β=-0.49) on aboveground biomass (R 2 =0.65), followed by strong positive direct effect of intraspecific tree size variation (β=0.32), species diversity (β=0.29) and interspecific tree size variation (β=0.28). Soil fertility had a negative direct effect on interspecific tree size variation (β=-0.31). Stand quality had a significant positive total effect on aboveground biomass (β=0.28), but homegarden size had a significant negative total effect (β=-0.62), while soil fertility had a non-significant total effect on aboveground biomass. Similar to the no mediation SEM, the partial mediation SEMs had explained almost similar variation in aboveground biomass because species diversity, and intraspecific and interspecific tree size variation had non-significant indirect effects on aboveground biomass via each other. Our results strongly suggest that a multilayered tree canopy structure, due to high intraspecific and interspecific tree size variation, increases light capture and efficient utilization of resources among component species, and hence, support the niche complementarity mechanism via plant-plant interactions. Copyright © 2017 Elsevier B.V. All rights reserved.

Elevated CO2 enrichment induces a differential biomass response in a mixed species temperate forest plantation.

PubMed

Smith, Andrew R; Lukac, Martin; Hood, Robin; Healey, John R; Miglietta, Franco; Godbold, Douglas L

2013-04-01

In a free-air carbon dioxide (CO(2)) enrichment study (BangorFACE), Alnus glutinosa, Betula pendula and Fagus sylvatica were planted in areas of one-, two- and three-species mixtures (n = 4). The trees were exposed to ambient or elevated CO(2) (580 μmol mol(-1)) for 4 yr, and aboveground growth characteristics were measured. In monoculture, the mean effect of CO(2) enrichment on aboveground woody biomass was + 29, + 22 and + 16% for A. glutinosa, F. sylvatica and B. pendula, respectively. When the same species were grown in polyculture, the response to CO(2) switched to + 10, + 7 and 0% for A. glutinosa, B. pendula and F. sylvatica, respectively. In ambient atmosphere, our species grown in polyculture increased aboveground woody biomass from 12.9 ± 1.4 to 18.9 ± 1.0 kg m(-2), whereas, in an elevated CO(2) atmosphere, aboveground woody biomass increased from 15.2 ± 0.6 to 20.2 ± 0.6 kg m(-2). The overyielding effect of polyculture was smaller (+ 7%) in elevated CO(2) than in an ambient atmosphere (+ 18%). Our results show that the aboveground response to elevated CO(2) is affected significantly by intra- and interspecific competition, and that the elevated CO(2) response may be reduced in forest communities comprising tree species with contrasting functional traits. © 2013 The Authors. New Phytologist © 2013 New Phytologist Trust.

Monitoring grass nutrients and biomass as indicators of rangeland quality and quantity using random forest modelling and WorldView-2 data

NASA Astrophysics Data System (ADS)

Ramoelo, Abel; Cho, M. A.; Mathieu, R.; Madonsela, S.; van de Kerchove, R.; Kaszta, Z.; Wolff, E.

2015-12-01

Land use and climate change could have huge impacts on food security and the health of various ecosystems. Leaf nitrogen (N) and above-ground biomass are some of the key factors limiting agricultural production and ecosystem functioning. Leaf N and biomass can be used as indicators of rangeland quality and quantity. Conventional methods for assessing these vegetation parameters at landscape scale level are time consuming and tedious. Remote sensing provides a bird-eye view of the landscape, which creates an opportunity to assess these vegetation parameters over wider rangeland areas. Estimation of leaf N has been successful during peak productivity or high biomass and limited studies estimated leaf N in dry season. The estimation of above-ground biomass has been hindered by the signal saturation problems using conventional vegetation indices. The objective of this study is to monitor leaf N and above-ground biomass as an indicator of rangeland quality and quantity using WorldView-2 satellite images and random forest technique in the north-eastern part of South Africa. Series of field work to collect samples for leaf N and biomass were undertaken in March 2013, April or May 2012 (end of wet season) and July 2012 (dry season). Several conventional and red edge based vegetation indices were computed. Overall results indicate that random forest and vegetation indices explained over 89% of leaf N concentrations for grass and trees, and less than 89% for all the years of assessment. The red edge based vegetation indices were among the important variables for predicting leaf N. For the biomass, random forest model explained over 84% of biomass variation in all years, and visible bands including red edge based vegetation indices were found to be important. The study demonstrated that leaf N could be monitored using high spatial resolution with the red edge band capability, and is important for rangeland assessment and monitoring.

Above-ground biomass and carbon estimates of Shorea robusta and Tectona grandis forests using QuadPOL ALOS PALSAR data

NASA Astrophysics Data System (ADS)

Behera, M. D.; Tripathi, P.; Mishra, B.; Kumar, Shashi; Chitale, V. S.; Behera, Soumit K.

2016-01-01

Mechanisms to mitigate climate change in tropical countries such as India require information on forest structural components i.e., biomass and carbon for conservation steps to be implemented successfully. The present study focuses on investigating the potential use of a one time, QuadPOL ALOS PALSAR L-band 25 m data to estimate above-ground biomass (AGB) using a water cloud model (WCM) in a wildlife sanctuary in India. A significant correlation was obtained between the SAR-derived backscatter coefficient (σ°) and the field measured AGB, with the maximum coefficient of determination for cross-polarized (HV) σ° for Shorea robusta, and the weakest correlation was observed with co-polarized (HH) σ° for Tectona grandis forests. The biomass of S. robusta and that of T. grandis were estimated on the basis of field-measured data at 444.7 ± 170.4 Mg/ha and 451 ± 179.4 Mg/ha respectively. The mean biomass values estimated using the WCM varied between 562 and 660 Mg/ha for S. robusta; between 590 and 710 Mg/ha for T. grandis using various polarized data. Our results highlighted the efficacy of one time, fully polarized PALSAR data for biomass and carbon estimate in a dense forest.

Aboveground carbon in Quebec forests: stock quantification at the provincial scale and assessment of temperature, precipitation and edaphic properties effects on the potential stand-level stocking

PubMed Central

Houle, Daniel; Ouimet, Rock; Lambert, Marie-Claude; Logan, Travis

2016-01-01

Biological carbon sequestration by forest ecosystems plays an important role in the net balance of greenhouse gases, acting as a carbon sink for anthropogenic CO2 emissions. Nevertheless, relatively little is known about the abiotic environmental factors (including climate) that control carbon storage in temperate and boreal forests and consequently, about their potential response to climate changes. From a set of more than 94,000 forest inventory plots and a large set of spatial data on forest attributes interpreted from aerial photographs, we constructed a fine-resolution map (∼375 m) of the current carbon stock in aboveground live biomass in the 435,000 km2 of managed forests in Quebec, Canada. Our analysis resulted in an area-weighted average aboveground carbon stock for productive forestland of 37.6 Mg ha−1, which is lower than commonly reported values for similar environment. Models capable of predicting the influence of mean annual temperature, annual precipitation, and soil physical environment on maximum stand-level aboveground carbon stock (MSAC) were developed. These models were then used to project the future MSAC in response to climate change. Our results indicate that the MSAC was significantly related to both mean annual temperature and precipitation, or to the interaction of these variables, and suggest that Quebec’s managed forests MSAC may increase by 20% by 2041–2070 in response to climate change. Along with changes in climate, the natural disturbance regime and forest management practices will nevertheless largely drive future carbon stock at the landscape scale. Overall, our results allow accurate accounting of carbon stock in aboveground live tree biomass of Quebec’s forests, and provide a better understanding of possible feedbacks between climate change and carbon storage in temperate and boreal forests. PMID:26966680

The impact of integrating WorldView-2 sensor and environmental variables in estimating plantation forest species aboveground biomass and carbon stocks in uMgeni Catchment, South Africa

NASA Astrophysics Data System (ADS)

Dube, Timothy; Mutanga, Onisimo

2016-09-01

Reliable and accurate mapping and extraction of key forest indicators of ecosystem development and health, such as aboveground biomass (AGB) and aboveground carbon stocks (AGCS) is critical in understanding forests contribution to the local, regional and global carbon cycle. This information is critical in assessing forest contribution towards ecosystem functioning and services, as well as their conservation status. This work aimed at assessing the applicability of the high resolution 8-band WorldView-2 multispectral dataset together with environmental variables in quantifying AGB and aboveground carbon stocks for three forest plantation species i.e. Eucalyptus dunii (ED), Eucalyptus grandis (EG) and Pinus taeda (PT) in uMgeni Catchment, South Africa. Specifically, the strength of the Worldview-2 sensor in terms of its improved imaging agilities is examined as an independent dataset and in conjunction with selected environmental variables. The results have demonstrated that the integration of high resolution 8-band Worldview-2 multispectral data with environmental variables provide improved AGB and AGCS estimates, when compared to the use of spectral data as an independent dataset. The use of integrated datasets yielded a high R2 value of 0.88 and RMSEs of 10.05 t ha-1 and 5.03 t C ha-1 for E. dunii AGB and carbon stocks; whereas the use of spectral data as an independent dataset yielded slightly weaker results, producing an R2 value of 0.73 and an RMSE of 18.57 t ha-1 and 09.29 t C ha-1. Similarly, high accurate results (R2 value of 0.73 and RMSE values of 27.30 t ha-1 and 13.65 t C ha-1) were observed from the estimation of inter-species AGB and carbon stocks. Overall, the findings of this work have shown that the integration of new generation multispectral datasets with environmental variables provide a robust toolset required for the accurate and reliable retrieval of forest aboveground biomass and carbon stocks in densely forested terrestrial ecosystems.

Lidar remote sensing of above-ground biomass in three biomes.

Treesearch

Michael A. Lefsky; Warren B. Cohen; David J. Harding; Geoffrey G. Parkers; Steven A. Acker; S. Thomas Gower

2002-01-01

Estimation of the amount of carbon stored in forests is a key challenge for understanding the global carbon cycle, one which remote sensing is expected to help address. However, estimation of carbon storage in moderate to high biomass forests is difficult for conventional optical and radar sensors. Lidar (light detection and ranging) instruments measure the vertical...

Bringing Together Users and Developers of Forest Biomass Maps

NASA Technical Reports Server (NTRS)

Brown, Molly E.; Macauley, Molly

2011-01-01

Forests store carbon and thus represent important sinks for atmospheric carbon dioxide. Reducing uncertainty in current estimates of the amount of carbon in standing forests will improve precision of estimates of anthropogenic contributions to carbon dioxide in the atmosphere due to deforestation. Although satellite remote sensing has long been an important tool for mapping land cover, until recently aboveground forest biomass estimates have relied mostly on systematic ground sampling of forests. In alignment with fiscal year 2010 congressional direction, NASA has initiated work toward a carbon monitoring system (CMS) that includes both maps of forest biomass and total carbon flux estimates. A goal of the project is to ensure that the products are useful to a wide community of scientists, managers, and policy makers, as well as to carbon cycle scientists. Understanding the needs and requirements of these data users is helpful not just to the NASA CMS program but also to the entire community working on carbon-related activities. To that end, this meeting brought together a small group of natural resource managers and policy makers who use information on forests in their work with NASA scientists who are working to create aboveground forest biomass maps. These maps, derived from combining remote sensing and ground plots, aim to be more accurate than current inventory approaches when applied at local and regional scales.

Evaluation of sampling strategies to estimate crown biomass

Treesearch

Krishna P Poudel; Hailemariam Temesgen; Andrew N Gray

2015-01-01

Depending on tree and site characteristics crown biomass accounts for a significant portion of the total aboveground biomass in the tree. Crown biomass estimation is useful for different purposes including evaluating the economic feasibility of crown utilization for energy production or forest products, fuel load assessments and fire management strategies, and wildfire...

Carbon allocation to young loblolly pine roots and stems

Treesearch

Paul P. Kormanik; Shi-Jean S. Sung; Clanton C. Black; Stanley J. Zarnoch

1995-01-01

This study of root biomass with loblolly pine was designed with the following objectives: (1) to measure the root biomass for a range of individual trees between the ages of 3 and 10 years on different artificial and natural forest sites and (2) to relate the root biomass to aboveground biomass components.

VT0005 In Action: National Forest Biomass Inventory Using Airborne Lidar Sampling

NASA Astrophysics Data System (ADS)

Saatchi, S. S.; Xu, L.; Meyer, V.; Ferraz, A.; Yang, Y.; Shapiro, A.; Bastin, J. F.

2016-12-01

Tropical countries are required to produce robust and verifiable estimates of forest carbon stocks for successful implementation of climate change mitigation. Lack of systematic national inventory data due to access, cost, and infrastructure, has impacted the capacity of most tropical countries to accurately report the GHG emissions to the international community. Here, we report on the development of the aboveground forest carbon (AGC) map of Democratic Republic of Congo (DRC) by using the VCS (Verified Carbon Standard) methodology developed by Sassan Saatchi (VT0005) using high-resolution airborne LiDAR samples. The methodology provides the distribution of the carbon stocks in aboveground live trees of more than 150 million ha of forests at 1-ha spatial resolution in DRC using more than 430, 000 ha of systematic random airborne Lidar inventory samples of forest structure. We developed a LIDAR aboveground biomass allometry using more than 100 1-ha plots across forest types and power-law model with LIDAR height metrics and average landscape scale wood density. The methodology provided estimates of forest biomass over the entire country using two approaches: 1) mean, variance, and total carbon estimates for each forest type present in DRC using inventory statistical techniques, and 2) a wall-to-wall map of the forest biomass extrapolated using satellite radar (ALOS PALSAR), surface topography from SRTM, and spectral information from Landsat (TM) and machine learning algorithms. We present the methodology, the estimates of carbon stocks and the spatial uncertainty over the entire country. AcknowledgementsThe theoretical research was carried out partially at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration, and the design and implementation in the Democratic Republic of Congo was carried out at the Institute of Environment and Sustainability at University of California Los Angeles through the support of the International Climate Initiative of the German Ministry of Environment, Conservation and Nuclear Security, and the KFW Development Bank.

Aboveground Biomass Variability Across Intact and Degraded Forests in the Brazilian Amazon

NASA Technical Reports Server (NTRS)

Longo, Marcos; Keller, Michael; Dos-Santos, Maiza N.; Leitold, Veronika; Pinage, Ekena R.; Baccini, Alessandro; Saatchi, Sassan; Nogueira, Euler M.; Batistella, Mateus; Morton, Douglas C.

2016-01-01

Deforestation rates have declined in the Brazilian Amazon since 2005, yet degradation from logging, re, and fragmentation has continued in frontier forests. In this study we quantified the aboveground carbon density (ACD) in intact and degraded forests using the largest data set of integrated forest inventory plots (n 359) and airborne lidar data (18,000 ha) assembled to date for the Brazilian Amazon. We developed statistical models relating inventory ACD estimates to lidar metrics that explained70 of the variance across forest types. Airborne lidar-ACD estimates for intact forests ranged between 5.0 +/- 2.5 and 31.9 +/- 10.8 kg C m(exp -2). Degradation carbon losses were large and persistent. Sites that burned multiple times within a decade lost up to 15.0 +/- 0.7 kg C m(-2)(94%) of ACD. Forests that burned nearly15 years ago had between 4.1 +/- 0.5 and 6.8 +/- 0.3 kg C m(exp -2) (22-40%) less ACD than intact forests. Even for low-impact logging disturbances, ACD was between 0.7 +/- 0.3 and 4.4 +/- 0.4 kg C m(exp -2)(4-21%) lower than unlogged forests. Comparing biomass estimates from airborne lidar to existing biomass maps, we found that regional and pan-tropical products consistently overestimated ACD in degraded forests, under-estimated ACD in intact forests, and showed little sensitivity to res and logging. Fine-scale heterogeneity in ACD across intact and degraded forests highlights the benefits of airborne lidar for carbon mapping. Differences between airborne lidar and regional biomass maps underscore the need to improve and update biomass estimates for dynamic land use frontiers, to better characterize deforestation and degradation carbon emissions for regional carbon budgets and Reduce Emissions from Deforestation and forest Degradation(REDD+).

Regional mapping of forest canopy water content and biomass using AIRSAR images over BOREAS study area

NASA Technical Reports Server (NTRS)

Saatchi, Sasan; Rignot, Eric; Vanzyl, Jakob

1995-01-01

In recent years, monitoring vegetation biomass over various climate zones has become the primary focus of several studies interested in assessing the role of the ecosystem responses to climate change and human activities. Airborne and spaceborne Synthetic Aperture Radar (SAR) systems provide a useful tool to directly estimate biomass due to its sensitivity to structural and moisture characteristics of vegetation canopies. Even though the sensitivity of SAR data to total aboveground biomass has been successfully demonstrated in many controlled experiments over boreal forests and forest plantations, so far, no biomass estimation algorithm has been developed. This is mainly due to the fact that the SAR data, even at lowest frequency (P-band) saturates at biomass levels of about 200 tons/ha, and the structure and moisture information in the SAR signal forces the estimation algorithm to be forest type dependent. In this paper, we discuss the development of a hybrid forest biomass algorithm which uses a SAR derived land cover map in conjunction with a forest backscatter model and an inversion algorithm to estimate forest canopy water content. It is shown that unlike the direct biomass estimation from SAR data, the estimation of water content does not depend on the seasonal and/or environmental conditions. The total aboveground biomass can then be derived from canopy water content for each type of forest by incorporating other ecological information. Preliminary results from this technique over several boreal forest stands indicate that (1) the forest biomass can be estimated with reasonable accuracy, and (2) the saturation level of the SAR signal can be enhanced by separating the crown and trunk biomass in the inversion algorithm. We have used the JPL AIRSAR data over BOREAS southern study area to test the algorithm and to generate regional scale water content and biomass maps. The results are compared with ground data and the sources of errors are discussed. Several SAR images in synoptic modes are used to generate the parameter maps. The maps are then combined to generate mosaic maps over the BOREAS modeling grid.

Carbon sequestration potential of second-growth forest regeneration in the Latin American tropics

PubMed Central

Chazdon, Robin L.; Broadbent, Eben N.; Rozendaal, Danaë M. A.; Bongers, Frans; Zambrano, Angélica María Almeyda; Aide, T. Mitchell; Balvanera, Patricia; Becknell, Justin M.; Boukili, Vanessa; Brancalion, Pedro H. S.; Craven, Dylan; Almeida-Cortez, Jarcilene S.; Cabral, George A. L.; de Jong, Ben; Denslow, Julie S.; Dent, Daisy H.; DeWalt, Saara J.; Dupuy, Juan M.; Durán, Sandra M.; Espírito-Santo, Mario M.; Fandino, María C.; César, Ricardo G.; Hall, Jefferson S.; Hernández-Stefanoni, José Luis; Jakovac, Catarina C.; Junqueira, André B.; Kennard, Deborah; Letcher, Susan G.; Lohbeck, Madelon; Martínez-Ramos, Miguel; Massoca, Paulo; Meave, Jorge A.; Mesquita, Rita; Mora, Francisco; Muñoz, Rodrigo; Muscarella, Robert; Nunes, Yule R. F.; Ochoa-Gaona, Susana; Orihuela-Belmonte, Edith; Peña-Claros, Marielos; Pérez-García, Eduardo A.; Piotto, Daniel; Powers, Jennifer S.; Rodríguez-Velazquez, Jorge; Romero-Pérez, Isabel Eunice; Ruíz, Jorge; Saldarriaga, Juan G.; Sanchez-Azofeifa, Arturo; Schwartz, Naomi B.; Steininger, Marc K.; Swenson, Nathan G.; Uriarte, Maria; van Breugel, Michiel; van der Wal, Hans; Veloso, Maria D. M.; Vester, Hans; Vieira, Ima Celia G.; Bentos, Tony Vizcarra; Williamson, G. Bruce; Poorter, Lourens

2016-01-01

Regrowth of tropical secondary forests following complete or nearly complete removal of forest vegetation actively stores carbon in aboveground biomass, partially counterbalancing carbon emissions from deforestation, forest degradation, burning of fossil fuels, and other anthropogenic sources. We estimate the age and spatial extent of lowland second-growth forests in the Latin American tropics and model their potential aboveground carbon accumulation over four decades. Our model shows that, in 2008, second-growth forests (1 to 60 years old) covered 2.4 million km2 of land (28.1% of the total study area). Over 40 years, these lands can potentially accumulate a total aboveground carbon stock of 8.48 Pg C (petagrams of carbon) in aboveground biomass via low-cost natural regeneration or assisted regeneration, corresponding to a total CO2 sequestration of 31.09 Pg CO2. This total is equivalent to carbon emissions from fossil fuel use and industrial processes in all of Latin America and the Caribbean from 1993 to 2014. Ten countries account for 95% of this carbon storage potential, led by Brazil, Colombia, Mexico, and Venezuela. We model future land-use scenarios to guide national carbon mitigation policies. Permitting natural regeneration on 40% of lowland pastures potentially stores an additional 2.0 Pg C over 40 years. Our study provides information and maps to guide national-level forest-based carbon mitigation plans on the basis of estimated rates of natural regeneration and pasture abandonment. Coupled with avoided deforestation and sustainable forest management, natural regeneration of second-growth forests provides a low-cost mechanism that yields a high carbon sequestration potential with multiple benefits for biodiversity and ecosystem services. PMID:27386528

Carbon sequestration potential of second-growth forest regeneration in the Latin American tropics.

PubMed

Chazdon, Robin L; Broadbent, Eben N; Rozendaal, Danaë M A; Bongers, Frans; Zambrano, Angélica María Almeyda; Aide, T Mitchell; Balvanera, Patricia; Becknell, Justin M; Boukili, Vanessa; Brancalion, Pedro H S; Craven, Dylan; Almeida-Cortez, Jarcilene S; Cabral, George A L; de Jong, Ben; Denslow, Julie S; Dent, Daisy H; DeWalt, Saara J; Dupuy, Juan M; Durán, Sandra M; Espírito-Santo, Mario M; Fandino, María C; César, Ricardo G; Hall, Jefferson S; Hernández-Stefanoni, José Luis; Jakovac, Catarina C; Junqueira, André B; Kennard, Deborah; Letcher, Susan G; Lohbeck, Madelon; Martínez-Ramos, Miguel; Massoca, Paulo; Meave, Jorge A; Mesquita, Rita; Mora, Francisco; Muñoz, Rodrigo; Muscarella, Robert; Nunes, Yule R F; Ochoa-Gaona, Susana; Orihuela-Belmonte, Edith; Peña-Claros, Marielos; Pérez-García, Eduardo A; Piotto, Daniel; Powers, Jennifer S; Rodríguez-Velazquez, Jorge; Romero-Pérez, Isabel Eunice; Ruíz, Jorge; Saldarriaga, Juan G; Sanchez-Azofeifa, Arturo; Schwartz, Naomi B; Steininger, Marc K; Swenson, Nathan G; Uriarte, Maria; van Breugel, Michiel; van der Wal, Hans; Veloso, Maria D M; Vester, Hans; Vieira, Ima Celia G; Bentos, Tony Vizcarra; Williamson, G Bruce; Poorter, Lourens

2016-05-01

Regrowth of tropical secondary forests following complete or nearly complete removal of forest vegetation actively stores carbon in aboveground biomass, partially counterbalancing carbon emissions from deforestation, forest degradation, burning of fossil fuels, and other anthropogenic sources. We estimate the age and spatial extent of lowland second-growth forests in the Latin American tropics and model their potential aboveground carbon accumulation over four decades. Our model shows that, in 2008, second-growth forests (1 to 60 years old) covered 2.4 million km(2) of land (28.1% of the total study area). Over 40 years, these lands can potentially accumulate a total aboveground carbon stock of 8.48 Pg C (petagrams of carbon) in aboveground biomass via low-cost natural regeneration or assisted regeneration, corresponding to a total CO2 sequestration of 31.09 Pg CO2. This total is equivalent to carbon emissions from fossil fuel use and industrial processes in all of Latin America and the Caribbean from 1993 to 2014. Ten countries account for 95% of this carbon storage potential, led by Brazil, Colombia, Mexico, and Venezuela. We model future land-use scenarios to guide national carbon mitigation policies. Permitting natural regeneration on 40% of lowland pastures potentially stores an additional 2.0 Pg C over 40 years. Our study provides information and maps to guide national-level forest-based carbon mitigation plans on the basis of estimated rates of natural regeneration and pasture abandonment. Coupled with avoided deforestation and sustainable forest management, natural regeneration of second-growth forests provides a low-cost mechanism that yields a high carbon sequestration potential with multiple benefits for biodiversity and ecosystem services.

Below and above-ground carbon distribution along a rainfall gradient. A case of the Zambezi teak forests, Zambia

NASA Astrophysics Data System (ADS)

Ngoma, Justine; Moors, Eddy; Kruijt, Bart; Speer, James H.; Vinya, Royd; Chidumayo, Emmanuel N.; Leemans, Rik

2018-02-01

Understanding carbon (C) stocks or biomass in forests is important to examine how forests mitigate climate change. To estimate biomass in stems, branches and roots takes intensive fieldwork to uproot, cut and weigh the mass of each component. Different models or equations are also required. Our research focussed on the dry tropical Zambezi teak forests and we studied their structure at three sites following a rainfall gradient in Zambia. We sampled 3558 trees at 42 plots covering a combined area of 15ha. Using data from destructive tree samples, we developed mixed-species biomass models to estimate above ground biomass for small (<5 cm diameter at breast height (DBH, 1.3 m above-ground)) and large (≥5 cm DBH) trees involving 90 and 104 trees respectively, that belonged to 12 species. A below-ground biomass model was developed from seven trees of three species (16-44 cm DBH) whose complete root systems were excavated. Three stump models were also derived from these uprooted trees. Finally, we determined the C fractions from 194 trees that belonged to 12 species. The analysis revealed that DBH was the only predictor that significantly correlated to both above-ground and below-ground biomass. We found a mean root-to-shoot ratio of 0.38:0.62. The C fraction in leaves ranged from 39% to 42%, while it varied between 41% and 46% in wood. The C fraction was highest at the Kabompo site that received the highest rainfall, and lowest at the intermediate Namwala site. The C stocks varied between 15 and 36 ton C ha-1 and these stocks where highest at the wetter Kabompo site and lowest at the drier Sesheke site. Our results indicate that the projected future rainfall decrease for southern Africa, will likely reduce the C storage potential of the Zambezi teak forests, thereby adversely affecting their mitigating role in climate change.

Abiotic and biotic determinants of coarse woody productivity in temperate mixed forests.

PubMed

Yuan, Zuoqiang; Ali, Arshad; Wang, Shaopeng; Gazol, Antonio; Freckleton, Robert; Wang, Xugao; Lin, Fei; Ye, Ji; Zhou, Li; Hao, Zhanqing; Loreau, Michel

2018-07-15

Forests play an important role in regulating the global carbon cycle. Yet, how abiotic (i.e. soil nutrients) and biotic (i.e. tree diversity, stand structure and initial biomass) factors simultaneously contribute to aboveground biomass (coarse woody) productivity, and how the relative importance of these factors changes over succession remain poorly studied. Coarse woody productivity (CWP) was estimated as the annual aboveground biomass gain of stems using 10-year census data in old growth and secondary forests (25-ha and 4.8-ha, respectively) in northeast China. Boosted regression tree (BRT) model was used to evaluate the relative contribution of multiple metrics of tree diversity (taxonomic, functional and phylogenetic diversity and trait composition as well as stand structure attributes), stand initial biomass and soil nutrients on productivity in the studied forests. Our results showed that community-weighted mean of leaf phosphorus content, initial stand biomass and soil nutrients were the three most important individual predictors for CWP in secondary forest. Instead, initial stand biomass, rather than diversity and functional trait composition (vegetation quality) was the most parsimonious predictor of CWP in old growth forest. By comparing the results from secondary and old growth forest, the summed relative contribution of trait composition and soil nutrients on productivity decreased as those of diversity indices and initial biomass increased, suggesting the stronger effect of diversity and vegetation quantity over time. Vegetation quantity, rather than diversity and soil nutrients, is the main driver of forest productivity in temperate mixed forest. Our results imply that diversity effect for productivity in natural forests may not be so important as often suggested, at least not during the later stage of forest succession. This finding suggests that as a change of the importance of different divers of productivity, the environmentally driven filtering decreases and competitively driven niche differentiation increases with forest succession. Copyright © 2018 Elsevier B.V. All rights reserved.

Biomass and nutrient dynamics associated with slash fires in neotropical dry forests

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kauffman, J.B.; Cummings, D.L.; Sanford, R.L. Jr.

1993-01-01

Unprecedented rates of deforestation and biomass burning in tropical dry forests are dramatically influencing biogeochemical cycles, resulting in resource depletion, declines in biodiversity, and atmospheric pollution. We quantified the effects of deforestation and varying levels of slash-fire severity on nutrient losses and redistribution in a second-growth tropical dry forest ([open quotes]Caatinga[close quotes]) near Serra Talhada, Pernambuco, Brazil. Total aboveground biomass prior to burning was [approx]74 Mg/ha. Nitrogen and phosphorus concentrations were highest in litter, leaves attached to slash, and fine wood debris (

Modeling forest biomass and growth: Coupling long-term inventory and LiDAR data

Treesearch

Chad Babcock; Andrew O. Finley; Bruce D. Cook; Aaron Weiskittel; Christopher W. Woodall

2016-01-01

Combining spatially-explicit long-term forest inventory and remotely sensed information from Light Detection and Ranging (LiDAR) datasets through statistical models can be a powerful tool for predicting and mapping above-ground biomass (AGB) at a range of geographic scales. We present and examine a novel modeling approach to improve prediction of AGB and estimate AGB...

Local discrepancies in continental scale biomass maps: a case study over forested and non-forested landscapes in Maryland, USA

Treesearch

Wenli Huang; Anu Swatantran; Kristofer Johnson; Laura Duncanson; Hao Tang; Jarlath O' Neil Dunne; George Hurtt; Ralph Dubayah

2015-01-01

Continental-scale aboveground biomass maps are increasingly available, but their estimates vary widely, particularly at high resolution. A comprehensive understanding of map discrepancies is required to improve their effectiveness in carbon accounting and local decision-making. To this end, we compare four continental-scale maps with a recent high-resolution lidar-...

Tropical-Forest Structure and Biomass Dynamics from TanDEM-X Radar Interferometry

Treesearch

Robert Treuhaft; Yang Lei; Fabio Gonçalves; Michael Keller; João Santos; Maxim Neumann; André Almeida

2017-01-01

Changes in tropical-forest structure and aboveground biomass (AGB) contribute directly to atmospheric changes in CO2, which, in turn, bear on global climate. This paper demonstrates the capability of radar-interferometric phase-height time series at X-band (wavelength = 3 cm) to monitor changes in vertical structure and AGB, with sub-hectare and monthly spatial and...

Regional distribution of forest height and biomass from multisensor data fusion

Treesearch

Yifan Yu; Sassan Saatch; Linda S. Heath; Elizabeth LaPoint; Ranga Myneni; Yuri Knyazikhin

2010-01-01

Elevation data acquired from radar interferometry at C-band from SRTM are used in data fusion techniques to estimate regional scale forest height and aboveground live biomass (AGLB) over the state of Maine. Two fusion techniques have been developed to perform post-processing and parameter estimations from four data sets: 1 arc sec National Elevation Data (NED), SRTM...

Estimating Forest Canopy Heights and Aboveground Biomass with Simulated ICESat-2 Data

NASA Astrophysics Data System (ADS)

Malambo, L.; Narine, L.; Popescu, S. C.; Neuenschwander, A. L.; Sheridan, R.

2016-12-01

The Ice, Cloud and Land Elevation Satellite (ICESat) 2 is scheduled for launch in 2017 and one of its overall science objectives will be to measure vegetation heights, which can be used to estimate and monitor aboveground biomass (AGB) over large spatial scales. This study serves to develop a methodology for utilizing vegetation data collected by ICESat-2 that will be on a five-year mission from 2017, for mapping forest canopy heights and estimating aboveground forest biomass (AGB). The specific objectives are to, (1) simulate ICESat-2 photon-counting lidar (PCL) data, (2) utilize simulated PCL data to estimate forest canopy heights and propose a methodology for upscaling PCL height measurements to obtain spatially contiguous coverage and, (3) estimate and map AGB using simulated PCL data. The laser pulse from ICESat-2 will be divided into three pairs of beams spaced approximately 3 km apart, with footprints measuring approximately 14 m in diameter and with 70 cm along-track intervals. Using existing airborne lidar data (ALS) for Sam Houston National Forest (SHNF) and known ICESat-2 beam locations, footprints are generated along beam locations and PCL data are then simulated from discrete return lidar points within each footprint. By applying data processing algorithms, photons are classified into top of canopy points and ground surface elevation points to yield tree canopy height values within each ICESat-2 footprint. AGB is then estimated using simple linear regression that utilizes AGB from a biomass map generated with ALS data for SHNF and simulated PCL height metrics for 100 m segments along ICESat-2 tracks. Two approaches also investigated for upscaling AGB estimates to provide wall-to-wall coverage of AGB are (1) co-kriging and (2) Random Forest. Height and AGB maps, which are the outcomes of this study, will demonstrate how data acquired by ICESat-2 can be used to measure forest parameters and in extension, estimate forest carbon for climate change initiatives.

Assimilating satellite-based canopy height within an ecosystem model to estimate aboveground forest biomass

NASA Astrophysics Data System (ADS)

Joetzjer, E.; Pillet, M.; Ciais, P.; Barbier, N.; Chave, J.; Schlund, M.; Maignan, F.; Barichivich, J.; Luyssaert, S.; Hérault, B.; von Poncet, F.; Poulter, B.

2017-07-01

Despite advances in Earth observation and modeling, estimating tropical biomass remains a challenge. Recent work suggests that integrating satellite measurements of canopy height within ecosystem models is a promising approach to infer biomass. We tested the feasibility of this approach to retrieve aboveground biomass (AGB) at three tropical forest sites by assimilating remotely sensed canopy height derived from a texture analysis algorithm applied to the high-resolution Pleiades imager in the Organizing Carbon and Hydrology in Dynamic Ecosystems Canopy (ORCHIDEE-CAN) ecosystem model. While mean AGB could be estimated within 10% of AGB derived from census data in average across sites, canopy height derived from Pleiades product was spatially too smooth, thus unable to accurately resolve large height (and biomass) variations within the site considered. The error budget was evaluated in details, and systematic errors related to the ORCHIDEE-CAN structure contribute as a secondary source of error and could be overcome by using improved allometric equations.

Predicting of biomass in Brazilian tropical dry forest: a statistical evaluation of generic equations.

PubMed

Lima, Robson B DE; Alves, Francisco T; Oliveira, Cinthia P DE; Silva, José A A DA; Ferreira, Rinaldo L C

2017-01-01

Dry tropical forests are a key component in the global carbon cycle and their biomass estimates depend almost exclusively of fitted equations for multi-species or individual species data. Therefore, a systematic evaluation of statistical models through validation of estimates of aboveground biomass stocks is justifiable. In this study was analyzed the capacity of generic and specific equations obtained from different locations in Mexico and Brazil, to estimate aboveground biomass at multi-species levels and for four different species. Generic equations developed in Mexico and Brazil performed better in estimating tree biomass for multi-species data. For Poincianella bracteosa and Mimosa ophthalmocentra, only the Sampaio and Silva (2005) generic equation was the most recommended. These equations indicate lower tendency and lower bias, and biomass estimates for these equations are similar. For the species Mimosa tenuiflora, Aspidosperma pyrifolium and for the genus Croton the specific regional equations are more recommended, although the generic equation of Sampaio and Silva (2005) is not discarded for biomass estimates. Models considering gender, families, successional groups, climatic variables and wood specific gravity should be adjusted, tested and the resulting equations should be validated at both local and regional levels as well as on the scales of tropics with dry forest dominance.

Dispersal limitation induces long-term biomass collapse in overhunted Amazonian forests.

PubMed

Peres, Carlos A; Emilio, Thaise; Schietti, Juliana; Desmoulière, Sylvain J M; Levi, Taal

2016-01-26

Tropical forests are the global cornerstone of biological diversity, and store 55% of the forest carbon stock globally, yet sustained provisioning of these forest ecosystem services may be threatened by hunting-induced extinctions of plant-animal mutualisms that maintain long-term forest dynamics. Large-bodied Atelinae primates and tapirs in particular offer nonredundant seed-dispersal services for many large-seeded Neotropical tree species, which on average have higher wood density than smaller-seeded and wind-dispersed trees. We used field data and models to project the spatial impact of hunting on large primates by ∼ 1 million rural households throughout the Brazilian Amazon. We then used a unique baseline dataset on 2,345 1-ha tree plots arrayed across the Brazilian Amazon to model changes in aboveground forest biomass under different scenarios of hunting-induced large-bodied frugivore extirpation. We project that defaunation of the most harvest-sensitive species will lead to losses in aboveground biomass of between 2.5-5.8% on average, with some losses as high as 26.5-37.8%. These findings highlight an urgent need to manage the sustainability of game hunting in both protected and unprotected tropical forests, and place full biodiversity integrity, including populations of large frugivorous vertebrates, firmly in the agenda of reducing emissions from deforestation and forest degradation (REDD+) programs.

Biomass is the main driver of changes in ecosystem process rates during tropical forest succession.

PubMed

Lohbeck, Madelon; Poorter, Lourens; Martínez-Ramos, Miguel; Bongers, Frans

2015-05-01

Over half of the world's forests are disturbed, and the rate at which ecosystem processes recover after disturbance is important for the services these forests can provide. We analyze the drivers' underlying changes in rates of key ecosystem processes (biomass productivity, litter productivity, actual litter decomposition, and potential litter decomposition) during secondary succession after shifting cultivation in wet tropical forest of Mexico. We test the importance of three alternative drivers of ecosystem processes: vegetation biomass (vegetation quantity hypothesis), community-weighted trait mean (mass ratio hypothesis), and functional diversity (niche complementarity hypothesis) using structural equation modeling. This allows us to infer the relative importance of different mechanisms underlying ecosystem process recovery. Ecosystem process rates changed during succession, and the strongest driver was aboveground biomass for each of the processes. Productivity of aboveground stem biomass and leaf litter as well as actual litter decomposition increased with initial standing vegetation biomass, whereas potential litter decomposition decreased with standing biomass. Additionally, biomass productivity was positively affected by community-weighted mean of specific leaf area, and potential decomposition was positively affected by functional divergence, and negatively by community-weighted mean of leaf dry matter content. Our empirical results show that functional diversity and community-weighted means are of secondary importance for explaining changes in ecosystem process rates during tropical forest succession. Instead, simply, the amount of vegetation in a site is the major driver of changes, perhaps because there is a steep biomass buildup during succession that overrides more subtle effects of community functional properties on ecosystem processes. We recommend future studies in the field of biodiversity and ecosystem functioning to separate the effects of vegetation quality (community-weighted mean trait values and functional diversity) from those of vegetation quantity (biomass) on ecosystem processes and services.

Tree seedlings respond to both light and soil nutrients in a Patagonian evergreen-deciduous forest.

PubMed

Promis, Alvaro; Allen, Robert B

2017-01-01

Seedlings of co-occurring species vary in their response to resource availability and this has implications for the conservation and management of forests. Differential shade-tolerance is thought to influence seedling performance in mixed Nothofagus betuloides-Nothofagus pumilio forests of Patagonia. However, these species also vary in their soil nutrient requirements. To determine the effects of light and soil nutrient resources on small seedlings we examined responses to an experimental reduction in canopy tree root competition through root trenching and restricting soil nutrient depletion through the addition of fertilizer. To understand the effect of light these treatments were undertaken in small canopy gaps and nearby beneath undisturbed canopy with lower light levels. Seedling diameter growth was greater for N. pumilio and height growth was greater for N. betuloides. Overall, diameter and height growth were greater in canopy gaps than beneath undisturbed canopy. Such growths were also greater with fertilizer and root trenching treatments, even beneath undisturbed canopy. Seedling survival was lower under such treatments, potentially reflecting thinning facilitated by resource induced growth. Finally, above-ground biomass did not vary among species although the less shade tolerant N. pumilio had higher below-ground biomass and root to shoot biomass ratio than the more shade tolerant N. betuloides. Above- and below-ground biomass were higher in canopy gaps so that the root to shoot biomass ratio was similar to that beneath undisturbed canopy. Above-ground biomass was also higher with fertilizer and root trenching treatments and that lowered the root to shoot biomass ratio. Restricting soil nutrient depletion allowed seedlings of both species to focus their responses above-ground. Our results support a view that soil nutrient resources, as well as the more commonly studied light resources, are important to seedlings of Nothofagus species occurring on infertile soils.

Using aerial photography to estimate wood suitable for charcoal in managed oak forests

NASA Astrophysics Data System (ADS)

Ramírez-Mejía, D.; Gómez-Tagle, A.; Ghilardi, A.

2018-02-01

Mexican oak forests (genus Quercus) are frequently used for traditional charcoal production. Appropriate management programs are needed to ensure their long-term use, while conserving the biodiversity and ecosystem services, and associated benefits. A key variable needed to design these programs is the spatial distribution of standing woody biomass. A state-of-the-art methodology using small format aerial photographs was developed to estimate the total aboveground biomass (AGB) and aboveground woody biomass suitable for charcoal making (WSC) in intensively managed oak forests. We used tree crown area (CAap) measurements from very high-resolution (30 cm) orthorectified small format digital aerial photographs as the predictive variable. The CAap accuracy was validated using field measurements of the crown area (CAf). Allometric relationships between: (a) CAap versus AGB, and (b) CAap versus WSC had a high significance level (R 2 > 0.91, p < 0.0001). This approach shows that it is possible to obtain sound biomass estimates as a function of the crown area derived from digital small format aerial photographs.

Stand structural diversity rather than species diversity enhances aboveground carbon storage in secondary subtropical forests in Eastern China

NASA Astrophysics Data System (ADS)

Ali, Arshad; Yan, En-Rong; Chen, Han Y. H.; Chang, Scott X.; Zhao, Yan-Tao; Yang, Xiao-Dong; Xu, Ming-Shan

2016-08-01

Stand structural diversity, typically characterized by variances in tree diameter at breast height (DBH) and total height, plays a critical role in influencing aboveground carbon (C) storage. However, few studies have considered the multivariate relationships of aboveground C storage with stand age, stand structural diversity, and species diversity in natural forests. In this study, aboveground C storage, stand age, tree species, DBH and height diversity indices, were determined across 80 subtropical forest plots in Eastern China. We employed structural equation modelling (SEM) to test for the direct and indirect effects of stand structural diversity, species diversity, and stand age on aboveground C storage. The three final SEMs with different directions for the path between species diversity and stand structural diversity had a similar goodness of fit to the data. They accounted for 82 % of the variation in aboveground C storage, 55-59 % of the variation in stand structural diversity, and 0.1 to 9 % of the variation in species diversity. Stand age demonstrated strong positive total effects, including a positive direct effect (β = 0.41), and a positive indirect effect via stand structural diversity (β = 0.41) on aboveground C storage. Stand structural diversity had a positive direct effect on aboveground C storage (β = 0.56), whereas there was little total effect of species diversity as it had a negative direct association with, but had a positive indirect effect, via stand structural diversity, on aboveground C storage. The negligible total effect of species diversity on aboveground C storage in the forests under study may have been attributable to competitive exclusion with high aboveground biomass, or a historical logging preference for productive species. Our analyses suggested that stand structural diversity was a major determinant for variations in aboveground C storage in the secondary subtropical forests in Eastern China. Hence, maintaining tree DBH and height diversity through silvicultural operations might constitute an effective approach for enhancing aboveground C storage in these forests.

Biomass and nutrient distributions in central Oregon second-growth ponderosa pine ecosystems.

Treesearch

Susan N. Little; Lauri J. Shainsky

1995-01-01

We investigated the distribution of biomass and nutrients in second-growth ponderosa pine (Pinus ponderosa Dougl. ex Laws.) ecosystems in central Oregon. Destructive sampling of aboveground and belowground tree biomass was carried out at six sites in the Deschutes National Forest; three of these sites also were intensively sampled for biomass and...

Dissecting variation in biomass conversion factors across China's forests: implications for biomass and carbon accounting.

PubMed

Luo, Yunjian; Zhang, Xiaoquan; Wang, Xiaoke; Ren, Yin

2014-01-01

Biomass conversion factors (BCFs, defined as the ratios of tree components (i.e. stem, branch, foliage and root), as well as aboveground and whole biomass of trees to growing stock volume, Mg m-3) are considered as important parameters in large-scale forest biomass carbon estimation. To date, knowledge of possible sources of the variation in BCFs is still limited at large scales. Using our compiled forest biomass dataset of China, we presented forest type-specific values of BCFs, and examined the variation in BCFs in relation to forest type, stand development and environmental factors (climate and soil fertility). BCFs exhibited remarkable variation across forest types, and also were significantly related to stand development (especially growing stock volume). BCFs (except Stem BCF) had significant relationships with mean annual temperature (MAT) and mean annual precipitation (MAP) (P<0.001). Climatic data (MAT and MAP) collectively explained 10.0-25.0% of the variation in BCFs (except Stem BCFs). Moreover, stronger climatic effects were found on BCFs for functional components (i.e. branch, foliage and root) than BCFs for combined components (i.e. aboveground section and whole trees). A general trend for BCFs was observed to decrease and then increase from low to high soil fertility. When qualitative soil fertility and climatic data (MAT and MAP) were combined, they explained 14.1-29.7% of the variation in in BCFs (except Stem BCFs), adding only 4.1-4.9% than climatic data used. Therefore, to reduce the uncertainty induced by BCFs in forest carbon estimates, we should apply values of BCFs for a specified forest type, and also consider climatic and edaphic effects, especially climatic effect, in developing predictive models of BCFs (except Stem BCF).

Dissecting Variation in Biomass Conversion Factors across China’s Forests: Implications for Biomass and Carbon Accounting

PubMed Central

Wang, Xiaoke; Ren, Yin

2014-01-01

Biomass conversion factors (BCFs, defined as the ratios of tree components (i.e. stem, branch, foliage and root), as well as aboveground and whole biomass of trees to growing stock volume, Mg m−3) are considered as important parameters in large-scale forest biomass carbon estimation. To date, knowledge of possible sources of the variation in BCFs is still limited at large scales. Using our compiled forest biomass dataset of China, we presented forest type-specific values of BCFs, and examined the variation in BCFs in relation to forest type, stand development and environmental factors (climate and soil fertility). BCFs exhibited remarkable variation across forest types, and also were significantly related to stand development (especially growing stock volume). BCFs (except Stem BCF) had significant relationships with mean annual temperature (MAT) and mean annual precipitation (MAP) (P<0.001). Climatic data (MAT and MAP) collectively explained 10.0–25.0% of the variation in BCFs (except Stem BCFs). Moreover, stronger climatic effects were found on BCFs for functional components (i.e. branch, foliage and root) than BCFs for combined components (i.e. aboveground section and whole trees). A general trend for BCFs was observed to decrease and then increase from low to high soil fertility. When qualitative soil fertility and climatic data (MAT and MAP) were combined, they explained 14.1–29.7% of the variation in in BCFs (except Stem BCFs), adding only 4.1–4.9% than climatic data used. Therefore, to reduce the uncertainty induced by BCFs in forest carbon estimates, we should apply values of BCFs for a specified forest type, and also consider climatic and edaphic effects, especially climatic effect, in developing predictive models of BCFs (except Stem BCF). PMID:24728222

ABOVEGROUND BIOMASS DISTRIBUTION OF US EASTERN HARDWOOD FORESTS AND THE USE OF LARGE TREES AS AN INDICATOR OF FOREST DEVELOPMENT

EPA Science Inventory

Past clearing and harvesting of the deciduous hardwood forests of eastern USA released large amount of carbon dioxide into the atmosphere, but through recovery and regrowth these forests are now accumulating atmospheric carbon (C). This study examined quantities and distribution ...

Seeing the Forest through the Trees: Citizen Scientists Provide Critical Data to Refine Aboveground Carbon Estimates in Restored Riparian Forests

NASA Astrophysics Data System (ADS)

Viers, J. H.

2013-12-01

Integrating citizen scientists into ecological informatics research can be difficult due to limited opportunities for meaningful engagement given vast data streams. This is particularly true for analysis of remotely sensed data, which are increasingly being used to quantify ecosystem services over space and time, and to understand how land uses deliver differing values to humans and thus inform choices about future human actions. Carbon storage and sequestration are such ecosystem services, and recent environmental policy advances in California (i.e., AB 32) have resulted in a nascent carbon market that is helping fuel the restoration of riparian forests in agricultural landscapes. Methods to inventory and monitor aboveground carbon for market accounting are increasingly relying on hyperspatial remotely sensed data, particularly the use of light detection and ranging (LiDAR) technologies, to estimate biomass. Because airborne discrete return LiDAR can inexpensively capture vegetation structural differences at high spatial resolution (< 1 m) over large areas (> 1000 ha), its use is rapidly increasing, resulting in vast stores of point cloud and derived surface raster data. While established algorithms can quantify forest canopy structure efficiently, the highly complex nature of native riparian forests can result in highly uncertain estimates of biomass due to differences in composition (e.g., species richness, age class) and structure (e.g., stem density). This study presents the comparative results of standing carbon estimates refined with field data collected by citizen scientists at three different sites, each capturing a range of agricultural, remnant forest, and restored forest cover types. These citizen science data resolve uncertainty in composition and structure, and improve allometric scaling models of biomass and thus estimates of aboveground carbon. Results indicate that agricultural land and horticulturally restored riparian forests store similar amounts of aboveground carbon (< 50 Mg/ha), but significantly less than naturally recruiting riparian forests (50 - 200 Mg/ha). Monitoring and assessment of dynamic ecosystem processes and functions will increasingly use data intensive methodologies; however, this research shows the utility of engaging citizen scientists in developing more robust data streams that not only reduces uncertainty, but also provide invaluable opportunities for improved education and outreach.

Does nitrogen and sulfur deposition affect forest productivity?

Treesearch

Brittany A. Johnson; Kathryn B. Piatek; Mary Beth Adams; John R. Brooks

2010-01-01

We studied the effects of atmospheric nitrogen and sulfur deposition on forest productivity in a 10-year-old, aggrading forest stand at the Fernow Experimental Forest in Tucker County, WV. Forest productivity was expressed as total aboveground wood biomass, which included stem and branch weight of standing live trees. Ten years after stand regeneration and treatment...

Estimating forest characteristics using NAIP imagery and ArcObjects

Treesearch

John S Hogland; Nathaniel M. Anderson; Woodam Chung; Lucas Wells

2014-01-01

Detailed, accurate, efficient, and inexpensive methods of estimating basal area, trees, and aboveground biomass per acre across broad extents are needed to effectively manage forests. In this study we present such a methodology using readily available National Agriculture Imagery Program imagery, Forest Inventory Analysis samples, a two stage classification and...

A sample design for globally consistent biomass estimation using lidar data from the Geoscience Laser Altimeter System (GLAS)

Treesearch

Sean P. Healey; Paul L. Patterson; Sassan S. Saatchi; Michael A. Lefsky; Andrew J. Lister; Elizabeth A. Freeman

2012-01-01

Lidar height data collected by the Geosciences Laser Altimeter System (GLAS) from 2002 to 2008 has the potential to form the basis of a globally consistent sample-based inventory of forest biomass. GLAS lidar return data were collected globally in spatially discrete full waveform "shots," which have been shown to be strongly correlated with aboveground forest...

Applying inventory methods to estimate aboveground biomass from satellite light detection and ranging (LiDAR) forest height data

Treesearch

Sean P. Healey; Paul L. Patterson; Sassan Saatchi; Michael A. Lefsky; Andrew J. Lister; Elizabeth A. Freeman; Gretchen G. Moisen

2012-01-01

Light Detection and Ranging (LiDAR) returns from the spaceborne Geoscience Laser Altimeter (GLAS) sensor may offer an alternative to solely field-based forest biomass sampling. Such an approach would rely upon model-based inference, which can account for the uncertainty associated with using modeled, instead of field-collected, measurements. Model-based methods have...

Large area mapping of southwestern forest crown cover, canopy height, and biomass using the NASA Multiangle Imaging Spectro-Radiometer

Treesearch

Mark Chopping; Gretchen G. Moisen; Lihong Su; Andrea Laliberte; Albert Rango; John V. Martonchik; Debra P. C. Peters

2008-01-01

A rapid canopy reflectance model inversion experiment was performed using multi-angle reflectance data from the NASA Multi-angle Imaging Spectro-Radiometer (MISR) on the Earth Observing System Terra satellite, with the goal of obtaining measures of forest fractional crown cover, mean canopy height, and aboveground woody biomass for large parts of south-eastern Arizona...

Mapping aboveground woody biomass using forest inventory, remote sensing and geostatistical techniques.

PubMed

Yadav, Bechu K V; Nandy, S

2015-05-01

Mapping forest biomass is fundamental for estimating CO₂ emissions, and planning and monitoring of forests and ecosystem productivity. The present study attempted to map aboveground woody biomass (AGWB) integrating forest inventory, remote sensing and geostatistical techniques, viz., direct radiometric relationships (DRR), k-nearest neighbours (k-NN) and cokriging (CoK) and to evaluate their accuracy. A part of the Timli Forest Range of Kalsi Soil and Water Conservation Division, Uttarakhand, India was selected for the present study. Stratified random sampling was used to collect biophysical data from 36 sample plots of 0.1 ha (31.62 m × 31.62 m) size. Species-specific volumetric equations were used for calculating volume and multiplied by specific gravity to get biomass. Three forest-type density classes, viz. 10-40, 40-70 and >70% of Shorea robusta forest and four non-forest classes were delineated using on-screen visual interpretation of IRS P6 LISS-III data of December 2012. The volume in different strata of forest-type density ranged from 189.84 to 484.36 m(3) ha(-1). The total growing stock of the forest was found to be 2,024,652.88 m(3). The AGWB ranged from 143 to 421 Mgha(-1). Spectral bands and vegetation indices were used as independent variables and biomass as dependent variable for DRR, k-NN and CoK. After validation and comparison, k-NN method of Mahalanobis distance (root mean square error (RMSE) = 42.25 Mgha(-1)) was found to be the best method followed by fuzzy distance and Euclidean distance with RMSE of 44.23 and 45.13 Mgha(-1) respectively. DRR was found to be the least accurate method with RMSE of 67.17 Mgha(-1). The study highlighted the potential of integrating of forest inventory, remote sensing and geostatistical techniques for forest biomass mapping.

Evaluating lidar point densities for effective estimation of aboveground biomass

USGS Publications Warehouse

Wu, Zhuoting; Dye, Dennis G.; Stoker, Jason M.; Vogel, John M.; Velasco, Miguel G.; Middleton, Barry R.

2016-01-01

The U.S. Geological Survey (USGS) 3D Elevation Program (3DEP) was recently established to provide airborne lidar data coverage on a national scale. As part of a broader research effort of the USGS to develop an effective remote sensing-based methodology for the creation of an operational biomass Essential Climate Variable (Biomass ECV) data product, we evaluated the performance of airborne lidar data at various pulse densities against Landsat 8 satellite imagery in estimating above ground biomass for forests and woodlands in a study area in east-central Arizona, U.S. High point density airborne lidar data, were randomly sampled to produce five lidar datasets with reduced densities ranging from 0.5 to 8 point(s)/m2, corresponding to the point density range of 3DEP to provide national lidar coverage over time. Lidar-derived aboveground biomass estimate errors showed an overall decreasing trend as lidar point density increased from 0.5 to 8 points/m2. Landsat 8-based aboveground biomass estimates produced errors larger than the lowest lidar point density of 0.5 point/m2, and therefore Landsat 8 observations alone were ineffective relative to airborne lidar for generating a Biomass ECV product, at least for the forest and woodland vegetation types of the Southwestern U.S. While a national Biomass ECV product with optimal accuracy could potentially be achieved with 3DEP data at 8 points/m2, our results indicate that even lower density lidar data could be sufficient to provide a national Biomass ECV product with accuracies significantly higher than that from Landsat observations alone.

Verification of the Jenkins and FIA sapling biomass equations for hardwood species in Maine

Treesearch

Andrew S. Nelson; Aaron R. Weiskittel; Robert G. Wagner; Michael R. Saunders

2012-01-01

In 2009, the Forest Inventory and Analysis Program (FIA) updated its biomass estimation protocols by switching to the component ratio method to estimate biomass of medium and large trees. Additionally, FIA switched from using regional equations to the current FIA aboveground sapling biomass equations that predict woody sapling (2.5 to 12.4 cm d.b.h.) biomass using the...

Estimating Forest Aboveground Biomass by Combining Optical and SAR Data: A Case Study in Genhe, Inner Mongolia, China

PubMed Central

Shao, Zhenfeng; Zhang, Linjing

2016-01-01

Estimation of forest aboveground biomass is critical for regional carbon policies and sustainable forest management. Passive optical remote sensing and active microwave remote sensing both play an important role in the monitoring of forest biomass. However, optical spectral reflectance is saturated in relatively dense vegetation areas, and microwave backscattering is significantly influenced by the underlying soil when the vegetation coverage is low. Both of these conditions decrease the estimation accuracy of forest biomass. A new optical and microwave integrated vegetation index (VI) was proposed based on observations from both field experiments and satellite (Landsat 8 Operational Land Imager (OLI) and RADARSAT-2) data. According to the difference in interaction between the multispectral reflectance and microwave backscattering signatures with biomass, the combined VI (COVI) was designed using the weighted optical optimized soil-adjusted vegetation index (OSAVI) and microwave horizontally transmitted and vertically received signal (HV) to overcome the disadvantages of both data types. The performance of the COVI was evaluated by comparison with those of the sole optical data, Synthetic Aperture Radar (SAR) data, and the simple combination of independent optical and SAR variables. The most accurate performance was obtained by the models based on the COVI and optical and microwave optimal variables excluding OSAVI and HV, in combination with a random forest algorithm and the largest number of reference samples. The results also revealed that the predictive accuracy depended highly on the statistical method and the number of sample units. The validation indicated that this integrated method of determining the new VI is a good synergistic way to combine both optical and microwave information for the accurate estimation of forest biomass. PMID:27338378

Implications of allometric model selection for county-level biomass mapping.

PubMed

Duncanson, Laura; Huang, Wenli; Johnson, Kristofer; Swatantran, Anu; McRoberts, Ronald E; Dubayah, Ralph

2017-10-18

Carbon accounting in forests remains a large area of uncertainty in the global carbon cycle. Forest aboveground biomass is therefore an attribute of great interest for the forest management community, but the accuracy of aboveground biomass maps depends on the accuracy of the underlying field estimates used to calibrate models. These field estimates depend on the application of allometric models, which often have unknown and unreported uncertainties outside of the size class or environment in which they were developed. Here, we test three popular allometric approaches to field biomass estimation, and explore the implications of allometric model selection for county-level biomass mapping in Sonoma County, California. We test three allometric models: Jenkins et al. (For Sci 49(1): 12-35, 2003), Chojnacky et al. (Forestry 87(1): 129-151, 2014) and the US Forest Service's Component Ratio Method (CRM). We found that Jenkins and Chojnacky models perform comparably, but that at both a field plot level and a total county level there was a ~ 20% difference between these estimates and the CRM estimates. Further, we show that discrepancies are greater in high biomass areas with high canopy covers and relatively moderate heights (25-45 m). The CRM models, although on average ~ 20% lower than Jenkins and Chojnacky, produce higher estimates in the tallest forests samples (> 60 m), while Jenkins generally produces higher estimates of biomass in forests < 50 m tall. Discrepancies do not continually increase with increasing forest height, suggesting that inclusion of height in allometric models is not primarily driving discrepancies. Models developed using all three allometric models underestimate high biomass and overestimate low biomass, as expected with random forest biomass modeling. However, these deviations were generally larger using the Jenkins and Chojnacky allometries, suggesting that the CRM approach may be more appropriate for biomass mapping with lidar. These results confirm that allometric model selection considerably impacts biomass maps and estimates, and that allometric model errors remain poorly understood. Our findings that allometric model discrepancies are not explained by lidar heights suggests that allometric model form does not drive these discrepancies. A better understanding of the sources of allometric model errors, particularly in high biomass systems, is essential for improved forest biomass mapping.

Wisconsin's forest resources in 2001.

Treesearch

John S. Vissage; Gery J. Brand; Manfred E. Mielke

2003-01-01

Results of the 2001 annual inventory of Wisconsin show about 15.8 million acres of forest land, more than 21.6 billion cubic feet of live volume on forest land, and nearly 584 million dry tons of all live aboveground tree biomass on timberland. Gypsy moth, forest tent caterpillar, twolined chestnut borer, bronze birch borer, ash yellows, and white pine blister rust...

Wisconsin's forest resources in 2002.

Treesearch

John S. Vissage; Gary J. Brand; Manfred E. Mielke

2004-01-01

Results of the 2002 annual inventory of Wisconsin show about 16.0 million acres of forest land, over 22.2 billion cubic feet of live volume on forest land, and nearly 598 million dry tons of all live aboveground tree biomass on timberland. Gypsy moth, forest tent caterpillar, twolined chestnut borer, bronze birch borer, ash yellows, and white pine blister rust were...

Minnesota Forest Resources in 2000.

Treesearch

David E. Haugen; Manfred E. Mielke

2002-01-01

Results of the 2000 annual inventory of Minnesota show over 16.5 million acres of forest land, over 17.6 billion cubic feet of all live volume on timberland, and an estimated 429 million dry tons of all live aboveground tree biomass on timberland. Known pests in Minnesota forests include the forest tent caterpillar, spruce budworm, large aspen tortrix, and introduced...

Forest Restoration Carbon Analysis of Baseline Carbon Emissions and Removal in Tropical Rainforest at La Selva Central, Peru

DOE Office of Scientific and Technical Information (OSTI.GOV)

Patrick Gonzalez; Benjamin Kroll; Carlos R. Vargas

Conversion of tropical forest to agricultural land and pasture has reduced forest extent and the provision of ecosystem services, including watershed protection, biodiversity conservation, and carbon sequestration. Forest conservation and reforestation can restore those ecosystem services. We have assessed forest species patterns, quantified deforestation and reforestation rates, and projected future baseline carbon emissions and removal in Amazon tropical rainforest at La Selva Central, Peru. The research area is a 4800 km{sup 2} buffer zone around the Parque Nacional Yanachaga-Chemillen, Bosque de Proteccion San Matias-San Carlos, and the Reserva Comunal Yanesha. A planned project for the period 2006-2035 would conserve 4000more » ha of forest in a proposed 7000 ha Area de Conservacion Municipale de Chontabamba and establish 5600 ha of natural regeneration and 1400 ha of native species plantations, laid out in fajas de enriquecimiento (contour plantings), to reforest 7000 ha of agricultural land. Forest inventories of seven sites covering 22.6 ha in primary forest and 17 sites covering 16.5 ha in secondary forest measured 17,073 trees of diameter {ge} 10 cm. The 24 sites host trees of 512 species, 267 genera, and 69 families. We could not identify the family of 7% of the trees or the scientific species of 21% of the trees. Species richness is 346 in primary forest and 257 in the secondary forest. In primary forest, 90% of aboveground biomass resides in old-growth species. Conversely, in secondary forest, 66% of aboveground biomass rests in successional species. The density of trees of diameter {ge} 10 cm is 366 trees ha{sup -1} in primary forest and 533 trees ha{sup -1} in secondary forest, although the average diameter is 24 {+-} 15 cm in primary forest and 17 {+-} 8 cm in secondary forest. Using Amazon forest biomass equations and wood densities for 117 species, aboveground biomass is 240 {+-} 30 t ha{sup -1} in the primary sites and 90 {+-} 10 t ha{sup -1} in the secondary sites. Aboveground carbon density is 120 {+-} 15 t ha{sup -1} in primary forest and 40 {+-} 5 t ha{sup -1} in secondary forest. Forest stands in the secondary forest sites range in age from 10 to 42 y. Growth in biomass (t ha{sup -1}) as a function of time (y) follows the relation: biomass = 4.09-0.017 age{sup 2} (p < 0.001). Aboveground biomass and forest species richness are positively correlated (r{sup 2} = 0.59, p < 0.001). Analyses of Landsat data show that the land cover of the 3700 km{sup 2} of non-cloud areas in 1999 was: closed forest 78%; open forest 12%, low vegetation cover 4%, sparse vegetation cover 6%. Deforestation from 1987 to 1999 claimed a net 200 km{sup 2} of forest, proceeding at a rate of 0.005 y{sup -1}. Of those areas of closed forest in 1987, only 89% remained closed forest in 1999. Consequently, closed forests experienced disruption in the time period at double the rate of net deforestation. The three protected areas experienced negligible deforestation or slight reforestation. Based on 1987 forest cover, 26,000 ha are eligible for forest carbon trading under the Clean Development Mechanism, established by the Kyoto Protocol to the United Nations Framework Convention on Climate Change. Principal components analysis showed that distance to nonforest was the factor that best explained observed patterns of deforestation while distance to forest best explained observed patterns of reforestation, more significant than elevation, distance to rivers, distance to roads, slope, and distance to towns of population > 400. Aboveground carbon in live vegetation in the project area decreased from 35 million {+-} 4 million t in 1987 to 34 million {+-} 4 million t in 1999. Projected aboveground carbon in live vegetation would fall to 33 million {+-} 4 million t in 2006, 32 million {+-} 4 million t in 2011, and 29 million {+-} 3 million t in 2035. Projected net deforestation in the research area would total 13,000 {+-} 3000 ha in the period 1999-2011, proceeding at a rate of 0.003 {+-} 0.0007 y{sup -1}, and would total 33,000 {+-} 7000 ha in the period 2006-2035. The proposed 7000 ha of forest conservation could prevent gross baseline deforestation of 100 ha (min. 70 ha, max 150 ha) in the period 2006-2035, averting baseline carbon emissions of 10,000 t (min. 6 000 t, max. 18 000 t). Projected gross reforestation in the research area would total 8500 {+-} 1500 ha in the period 1999-2011, proceeding at a rate of 0.0012 y{sup -1} (min. 0.01 y{sup -1}, max. 0.014 y{sup -1}), and would total 24,000 {+-} 4000 ha in the period 2006-2035. Gross baseline reforestation for the proposed 7000 ha of reforestation would total 2600 {+-} 400 ha in the period 2006-2035, representing a baseline removal from the atmosphere of 73,000 t carbon (min. 30,000 t, max. 120,000 t). The proposed reforestation project could sequester 230,000 t carbon (min. 140,000 t, max. 310,000 t) above baseline removal in the period 2006-2035.« less

Terrestrial Carbon Fluxes from Deforestation in the Brazilian Amazon and Cerrado Regions Predicted from MODIS Satellite Data and Ecosystem Modeling

NASA Astrophysics Data System (ADS)

Klooster, S.; Potter, C.; Genovese, V.

2008-12-01

The NASA-CASA (Carnegie Ames Stanford Approach) simulation model based on satellite observations of monthly vegetation cover from the Moderate Resolution Imaging Spectroradiometer (MODIS) was used to estimate tropical forest and savanna (Cerrado) carbon pools for the Brazilian Amazon region over the period 2000-2004. Adjustments for mean age of forest stands were carried out across the region, resulting in a new mapping of aboveground biomass pools based on MODIS satellite data. Yearly maps of newly deforested lands from the Brazilian PRODES (Programa de calculo do desflorestamento da Amazonia ) project were combined with these NASA-CASA biomass predictions to generate seasonal budgets of potential carbon and nitrogen trace gas losses from biomass burning events. Simulations of plant residue and soil carbon decomposition were conducted in the NASA-CASA model during and following deforestation events to track the fate of aboveground biomass pools that were cut and burned each year across the region.

Spaceborne Applications of P Band Imaging Radars for Measuring Forest Biomass

NASA Technical Reports Server (NTRS)

Rignot, Eric J.; Zimmermann, Reiner; vanZyl, Jakob J.

1995-01-01

In three sites of boreal and temperate forests, P band HH, HV, and VV polarization data combined estimate total aboveground dry woody biomass within 12 to 27% of the values derived from allometric equations, depending on forest complexity. Biomass estimates derived from HV-polarization data only are 2 to 14% less accurate. When the radar operates at circular polarization, the errors exceed 100% over flooded forests, wet or damaged trees and sparse open tall forests because double-bounce reflections of the radar signals yield radar signatures similar to that of tall and massive forests. Circular polarizations, which minimize the effect of Faraday rotation in spaceborne applications, are therefore of limited use for measuring forest biomass. In the tropical rain forest of Manu, in Peru, where forest biomass ranges from 4 kg/sq m in young forest succession up to 50 kg/sq m in old, undisturbed floodplain stands, the P band horizontal and vertical polarization data combined separate biomass classes in good agreement with forest inventory estimates. The worldwide need for large scale, updated, biomass estimates, achieved with a uniformly applied method, justifies a more in-depth exploration of multi-polarization long wavelength imaging radar applications for tropical forests inventories.

Soil moisture limitations on monitoring boreal forest regrowth using spaceborne L-band SAR data

Treesearch

Eric S. Kasischke; Mihai A. Tanase; Laura L. Bourgeau-Chavez; Matthew Borr

2011-01-01

A study was carried out to investigate the utility of L-band SAR data for estimating aboveground biomass in sites with low levels of vegetation regrowth. Data to estimate biomass were collected from 59 sites located in fire-disturbed black spruce forests in interior Alaska. PALSAR L-band data (HH and HV polarizations) collected on two dates in the summer/fall of 2007...

Impacts of airborne lidar pulse density on estimating biomass stocks and changes in a selectively logged tropical forest

Treesearch

Carlos Alberto Silva; Andrew Thomas Hudak; Lee Alexander Vierling; Carine Klauberg; Mariano Garcia; Antonio Ferraz; Michael Keller; Jan Eitel; Sassan Saatchi

2017-01-01

Airborne lidar has become a well-suited technology for predicting and mapping many tropical forest attributes, including aboveground biomass (AGB). However, trade-offs exist between lidar pulse density and acquisition cost. The aim of this study was to evaluate the influence of lidar pulse density on AGB change predictions using airborne lidar and field plot data in a...

Dispersal limitation induces long-term biomass collapse in overhunted Amazonian forests

PubMed Central

Peres, Carlos A.; Emilio, Thaise; Schietti, Juliana; Desmoulière, Sylvain J. M.; Levi, Taal

2016-01-01

Tropical forests are the global cornerstone of biological diversity, and store 55% of the forest carbon stock globally, yet sustained provisioning of these forest ecosystem services may be threatened by hunting-induced extinctions of plant–animal mutualisms that maintain long-term forest dynamics. Large-bodied Atelinae primates and tapirs in particular offer nonredundant seed-dispersal services for many large-seeded Neotropical tree species, which on average have higher wood density than smaller-seeded and wind-dispersed trees. We used field data and models to project the spatial impact of hunting on large primates by ∼1 million rural households throughout the Brazilian Amazon. We then used a unique baseline dataset on 2,345 1-ha tree plots arrayed across the Brazilian Amazon to model changes in aboveground forest biomass under different scenarios of hunting-induced large-bodied frugivore extirpation. We project that defaunation of the most harvest-sensitive species will lead to losses in aboveground biomass of between 2.5–5.8% on average, with some losses as high as 26.5–37.8%. These findings highlight an urgent need to manage the sustainability of game hunting in both protected and unprotected tropical forests, and place full biodiversity integrity, including populations of large frugivorous vertebrates, firmly in the agenda of reducing emissions from deforestation and forest degradation (REDD+) programs. PMID:26811455

Assessing the potential for biomass energy development in South Carolina

Treesearch

Roger C. Conner; Tim O. Adams; Tony G. Johnson

2009-01-01

An assessment of the potential for developing a sustainable biomass energy industry in South Carolina was conducted. Biomass as defined by Forest Inventory and Analysis is the aboveground dry weight of wood in the bole and limbs of live trees ≥1-inch diameter at breast height, and excludes tree foliage, seedlings, and understory...

Liana infestation impacts tree growth in a lowland tropical moist forest

NASA Astrophysics Data System (ADS)

van der Heijden, G. M. F.; Phillips, O. L.

2009-03-01

Stand-level estimates of the effect of lianas on tree growth in mature tropical forests are needed to evaluate the functional impact of lianas and their potential to affect the ability of tropical forests to sequester carbon, but these are currently lacking. Using data collected on tree growth rates, local growing conditions and liana competition in five permanent sampling plots in Amazonian Peru, we present the first such estimates of the effect of lianas on above-ground productivity of trees. By constructing a multi-level linear mixed effect model to predict individual tree diameter growth model using individual tree growth conditions, we were able to estimate stand-level above-ground biomass (AGB) increment in the absence of lianas. We show that lianas, mainly by competing above-ground with trees, reduce tree annual above-ground stand-level biomass by ~10%, equivalent to 0.51 Mg dry weight ha-1 yr-1 or 0.25 Mg C ha-1 yr-1. AGB increment of lianas themselves was estimated to be 0.15 Mg dry weight ha-1 yr-1 or 0.07 Mg C ha-1 yr-1, thus only compensating ~29% of the liana-induced reduction in stand-level AGB increment. Increasing liana pressure on tropical forests may therefore not only reduce their carbon storage capacity, by indirectly promoting tree species with low-density wood, but also their rate of carbon uptake, with potential consequences for the rate of increase in atmospheric carbon dioxide.

Liana infestation impacts tree growth in a lowland tropical moist forest

NASA Astrophysics Data System (ADS)

van der Heijden, G. M. F.; Phillips, O. L.

2009-10-01

Ecosystem-level estimates of the effect of lianas on tree growth in mature tropical forests are needed to evaluate the functional impact of lianas and their potential to affect the ability of tropical forests to sequester carbon, but these are currently lacking. Using data collected on tree growth rates, local growing conditions and liana competition in five permanent sampling plots in Amazonian Peru, we present the first ecosystem-level estimates of the effect of lianas on above-ground productivity of trees. By first constructing a multi-level linear mixed effect model to predict individual-tree diameter growth model using individual-tree growth conditions, we were able to then estimate stand-level above-ground biomass (AGB) increment in the absence of lianas. We show that lianas, mainly by competing above-ground with trees, reduce tree annual above-ground stand-level biomass increment by ~10%, equivalent to 0.51 Mg dry weight ha-1 yr-1 or 0.25 Mg C ha-1 yr-1. AGB increment of lianas themselves was estimated to be 0.15 Mg dry weight ha-1 yr-1 or 0.07 Mg C ha-1 yr-1, thus only compensating ~29% of the liana-induced reduction in ecosystem AGB increment. Increasing liana pressure on tropical forests will therefore not only tend to reduce their carbon storage capacity, by indirectly promoting tree species with low-density wood, but also their rate of carbon uptake, with potential consequences for the rate of increase in atmospheric carbon dioxide.

Surface Fire Influence on Carbon Balance Components in Scots Pine Forest of Siberia, Russia

NASA Astrophysics Data System (ADS)

Kukavskaya, E.; Ivanova, G. A.; Conard, S. G.; Soja, A. J.

2008-12-01

Wildfire is one of the most important disturbances in boreal forests, and it can have a profound effect on forest-atmosphere carbon exchange. Pinus sylvestris (Scots pine) stands of Siberia are strongly impacted by fires of low to high severity. Biomass distribution in mature lichen/feathermoss Scots pine stands indicates that they are carbon sinks before fire. Fires contribute significantly to the carbon budget resulting in a considerable carbon efflux, initially through direct consumption of forest fuels and later as a result of tree mortality and decomposition of dead material accumulated on the forest floor. In initial postfire years these processes dominate over photosynthetic carbon assimilation, and the ecosystems become a carbon source. Over several postfire years, above-ground carbon in dead biomass tends to increase, with the increase depending significantly on fire severity. High-severity fire enhances dead biomass carbon, while moderate- and low-severity fires have minimal effect on above-ground carbon distribution in Scots pine ecosystems. Dead stand biomass carbon increases, primarily during the first two years following fires, due to tree mortality. This increase can account for up to 12.4% of the total stand biomass after low- and moderate- intensity fires. We found tree dieback following a high-intensity fire is an order of magnitude higher, and thus the dead biomass increases up to 88.1% of total above-ground biomass. Photosynthetic CO2 uptake decreases with increasing tree mortality, and needle foliage and bark are incorporated into the upper layer of the forest floor in the course of years. Ground vegetation and duff carbon were >90, 71-83, and 82% of prefire levels after fires of low, moderate, and high severity, respectively for the first 4 to 5 years after fire. Fires of low and moderate severity caused down woody fuel carbon to increase by 2.1 and 3.6 t ha-1 respectively by four years after burning as compared to the pre-fire values. Climate change and increasing drought length observed in recent decades have increased the probability of high-intensity fire occurrence. Areas burned have increased in extent and severity across Siberia, resulting in increased carbon emissions to the atmosphere from fuel combustion and post fire decomposition.

Using Lidar and Radar measurements to constrain predictions of forest ecosystem structure and function.

PubMed

Antonarakis, Alexander S; Saatchi, Sassan S; Chazdon, Robin L; Moorcroft, Paul R

2011-06-01

Insights into vegetation and aboveground biomass dynamics within terrestrial ecosystems have come almost exclusively from ground-based forest inventories that are limited in their spatial extent. Lidar and synthetic-aperture Radar are promising remote-sensing-based techniques for obtaining comprehensive measurements of forest structure at regional to global scales. In this study we investigate how Lidar-derived forest heights and Radar-derived aboveground biomass can be used to constrain the dynamics of the ED2 terrestrial biosphere model. Four-year simulations initialized with Lidar and Radar structure variables were compared against simulations initialized from forest-inventory data and output from a long-term potential-vegtation simulation. Both height and biomass initializations from Lidar and Radar measurements significantly improved the representation of forest structure within the model, eliminating the bias of too many large trees that arose in the potential-vegtation-initialized simulation. The Lidar and Radar initializations decreased the proportion of larger trees estimated by the potential vegetation by approximately 20-30%, matching the forest inventory. This resulted in improved predictions of ecosystem-scale carbon fluxes and structural dynamics compared to predictions from the potential-vegtation simulation. The Radar initialization produced biomass values that were 75% closer to the forest inventory, with Lidar initializations producing canopy height values closest to the forest inventory. Net primary production values for the Radar and Lidar initializations were around 6-8% closer to the forest inventory. Correcting the Lidar and Radar initializations for forest composition resulted in improved biomass and basal-area dynamics as well as leaf-area index. Correcting the Lidar and Radar initializations for forest composition and fine-scale structure by combining the remote-sensing measurements with ground-based inventory data further improved predictions, suggesting that further improvements of structural and carbon-flux metrics will also depend on obtaining reliable estimates of forest composition and accurate representation of the fine-scale vertical and horizontal structure of plant canopies.

Improving North American forest biomass estimates from literature synthesis and meta-analysis of existing biomass equations

Treesearch

David C. Chojnacky; Jennifer C. Jenkins; Amanda K. Holland

2009-01-01

Thousands of published equations purport to estimate biomass of individual trees. These equations are often based on very small samples, however, and can provide widely different estimates for trees of the same species. We addressed this issue in a previous study by devising 10 new equations that estimated total aboveground biomass for all species in North America (...

Biomass Allocation Patterns across China’s Terrestrial Biomes

PubMed Central

Wang, Limei; Li, Longhui; Chen, Xi; Tian, Xin; Wang, Xiaoke; Luo, Geping

2014-01-01

Root to shoot ratio (RS) is commonly used to describe the biomass allocation between below- and aboveground parts of plants. Determining the key factors influencing RS and interpreting the relationship between RS and environmental factors is important for biological and ecological research. In this study, we compiled 2088 pairs of root and shoot biomass data across China’s terrestrial biomes to examine variations in the RS and its responses to biotic and abiotic factors including vegetation type, soil texture, climatic variables, and stand age. The median value of RS (RSm) for grasslands, shrublands, and forests was 6.0, 0.73, and 0.23, respectively. The range of RS was considerably wide for each vegetation type. RS values for all three major vegetation types were found to be significantly correlated to mean annual precipitation (MAP) and potential water deficit index (PWDI). Mean annual temperature (MAT) also significantly affect the RS for forests and grasslands. Soil texture and forest origin altered the response of RS to climatic factors as well. An allometric formula could be used to well quantify the relationship between aboveground and belowground biomass, although each vegetation type had its own inherent allometric relationship. PMID:24710503

Demographic controls of aboveground forest biomass across North America.

PubMed

Vanderwel, Mark C; Zeng, Hongcheng; Caspersen, John P; Kunstler, Georges; Lichstein, Jeremy W

2016-04-01

Ecologists have limited understanding of how geographic variation in forest biomass arises from differences in growth and mortality at continental to global scales. Using forest inventories from across North America, we partitioned continental-scale variation in biomass growth and mortality rates of 49 tree species groups into (1) species-independent spatial effects and (2) inherent differences in demographic performance among species. Spatial factors that were separable from species composition explained 83% and 51% of the respective variation in growth and mortality. Moderate additional variation in mortality (26%) was attributable to differences in species composition. Age-dependent biomass models showed that variation in forest biomass can be explained primarily by spatial gradients in growth that were unrelated to species composition. Species-dependent patterns of mortality explained additional variation in biomass, with forests supporting less biomass when dominated by species that are highly susceptible to competition (e.g. Populus spp.) or to biotic disturbances (e.g. Abies balsamea). © 2016 John Wiley & Sons Ltd/CNRS.

Wisconsin's forest resources in 2004

Treesearch

Charles H. Perry

2006-01-01

Results of the 2000-2004 annual inventory of Wisconsin show about 16.0 million acres of forest land, more than 22.1 billion cubic feet of live volume on forest land, and nearly 593 million dry tons of all live aboveground tree biomass on timberland. Populations of jack pine budworm are increasing, and it remains a significant pest in Wisconsin forests. A complete...

Minnesota's forest resources in 2005

Treesearch

Patrick D. Miles; Gary J. Brand

2007-01-01

Reports forest statistics for Minnesota based on five annual inventories from 2001 through 2005. Minnesota's total forest area is estimated at 16.3 million acres or 32 percent of the total land area of the State. The estmated total live-tree volume on forest land is 17.7 billion cubic feet or 1,085 cubic feet per acre. The estimated aboveground live-tree biomass...

Wisconsin's forest resources in 2003

Treesearch

John S. Vissage; Gary J. Brand; J.E. Cummings-Carlson,

2005-01-01

Results of the 2003 annual inventory of Wisconsin show about 15.9 million acres of forest land, over 21.9 billion cubic feet of live volume on forest land, and nearly 591 million dry tons of all live aboveground tree biomass on timberland. Gypsy moth, forest tent caterpillar, twolined chestnut borer, bronze birch borer, ash yellows, and oak wilt were among the pests of...

Airborne lidar-based estimates of tropical forest structure in complex terrain: opportunities and trade-offs for REDD+

Treesearch

Veronika Leitold; Michael Keller; Douglas C Morton; Bruce D Cook; Yosio E Shimabukuro

2015-01-01

Background: Carbon stocks and fluxes in tropical forests remain large sources of uncertainty in the global carbon budget. Airborne lidar remote sensing is a powerful tool for estimating aboveground biomass, provided that lidar measurements penetrate dense forest vegetation to generate accurate estimates of surface topography and canopy heights. Tropical forest areas...

Harvesting intensity affects forest structure and composition in an upland Amazonian forest

Treesearch

John A. Parrotta; John K. Francis; Oliver H. Knowles; NO-VALUE

2002-01-01

Forest structure and floristic composition were studied in a series of 0.5 ha natural forest plots at four sites near Porto Trombetas in Pará State, Brazil, 11–12 years after being subjected to differing levels of above-ground biomass harvest and removal. In addition to undisturbed control plots, experimental treatments included: removal of...

Regional Distribution of Forest Height and Biomass from Multisensor Data Fusion

NASA Technical Reports Server (NTRS)

Yu, Yifan; Saatchi, Sassan; Heath, Linda S.; LaPoint, Elizabeth; Myneni, Ranga; Knyazikhin, Yuri

2010-01-01

Elevation data acquired from radar interferometry at C-band from SRTM are used in data fusion techniques to estimate regional scale forest height and aboveground live biomass (AGLB) over the state of Maine. Two fusion techniques have been developed to perform post-processing and parameter estimations from four data sets: 1 arc sec National Elevation Data (NED), SRTM derived elevation (30 m), Landsat Enhanced Thematic Mapper (ETM) bands (30 m), derived vegetation index (VI) and NLCD2001 land cover map. The first fusion algorithm corrects for missing or erroneous NED data using an iterative interpolation approach and produces distribution of scattering phase centers from SRTM-NED in three dominant forest types of evergreen conifers, deciduous, and mixed stands. The second fusion technique integrates the USDA Forest Service, Forest Inventory and Analysis (FIA) ground-based plot data to develop an algorithm to transform the scattering phase centers into mean forest height and aboveground biomass. Height estimates over evergreen (R2 = 0.86, P < 0.001; RMSE = 1.1 m) and mixed forests (R2 = 0.93, P < 0.001, RMSE = 0.8 m) produced the best results. Estimates over deciduous forests were less accurate because of the winter acquisition of SRTM data and loss of scattering phase center from tree ]surface interaction. We used two methods to estimate AGLB; algorithms based on direct estimation from the scattering phase center produced higher precision (R2 = 0.79, RMSE = 25 Mg/ha) than those estimated from forest height (R2 = 0.25, RMSE = 66 Mg/ha). We discuss sources of uncertainty and implications of the results in the context of mapping regional and continental scale forest biomass distribution.

Quantifying the Spatio-temporal Impacts of Sea Level Rise on Carbon Storage Using Repeat Lidar Surveys and Multispectral Satellite Imagery

NASA Astrophysics Data System (ADS)

Smart, L.; Taillie, P. J.; Smith, J. W.; Meentemeyer, R. K.

2017-12-01

Sound coastal land-use policy and management decisions to mitigate or adapt to sea level rise impacts depend on understanding vegetation responses to sea level rise over large extents. Accurate methodologies to quantify these changes are necessary to understand the continued production of the ecosystem services upon which human health and well-being depend. This research quantifies spatio-temporal changes in aboveground biomass altered by sea level rise across North Carolina's coastal plain using a combination of repeat-acquisition lidar data and multi-temporal satellite imagery. Using field data from across the study area, we evaluated the reliability of multi-temporal lidar data with disparate densities and accuracies to detect changes along a coastal vegetation gradient from marsh to forested wetland. Despite an 18 fold increase in lidar point density between survey years (2001, 2014), the relationships between lidar-derived heights and field-measured heights were similar (adjusted r2; 0.6 -0.7). Random Forest, a machine learning algorithm, was used to separately predict above-ground biomass pools at the landscape-scale for the two time periods using the 98 field plots as reference data. Models performed well for both years (adjusted r2; 0.67-0.85). The 2001 model required the addition of Landsat spectral indices to meet the same adjusted r2 values as the 2014 model, which utilized lidar-derived metrics alone. Of the many potential lidar-derived predictor metrics, median and mean vegetation height were the best predictors in both time periods. To measure the spatial patterns of biomass change across the landscape, we subtracted the 2001 biomass model from the 2014 model and found significant spatial heterogeneity in biomass change across both the vegetation gradient and across the peninsula over the 12-year time period. In forested areas, we found a mean increase in aboveground biomass whereas in transition zones, marshes and freshwater emergent wetlands we found overall decreases in aboveground biomass. These changes were correlated with distance to estuarine shoreline - areas closest to the shoreline exhibiting the strongest biomass declines. Results from this study have allowed us to better understand climate change-related vegetation dynamics in a sensitive coastal region.

Large-scale carbon stock assessment of woody vegetation in tropical dry deciduous forest of Sathanur reserve forest, Eastern Ghats, India.

PubMed

Gandhi, Durai Sanjay; Sundarapandian, Somaiah

2017-04-01

Tropical dry forests are one of the most widely distributed ecosystems in tropics, which remain neglected in research, especially in the Eastern Ghats. Therefore, the present study was aimed to quantify the carbon storage in woody vegetation (trees and lianas) on large scale (30, 1 ha plots) in the dry deciduous forest of Sathanur reserve forest of Eastern Ghats. Biomass of adult (≥10 cm DBH) trees was estimated by species-specific allometric equations using diameter and wood density of species whereas in juvenile tree population and lianas, their respective general allometric equations were used to estimate the biomass. The fractional value 0.4453 was used to convert dry biomass into carbon in woody vegetation of tropical dry forest. The mean aboveground biomass value of juvenile tree population was 1.86 Mg/ha. The aboveground biomass of adult trees ranged from 64.81 to 624.96 Mg/ha with a mean of 245.90 Mg/ha. The mean aboveground biomass value of lianas was 7.98 Mg/ha. The total biomass of woody vegetation (adult trees + juvenile population of trees + lianas) ranged from 85.02 to 723.46 Mg/ha, with a mean value of 295.04 Mg/ha. Total carbon accumulated in woody vegetation in tropical dry deciduous forest ranged from 37.86 to 322.16 Mg/ha with a mean value of 131.38 Mg/ha. Adult trees accumulated 94.81% of woody biomass carbon followed by lianas (3.99%) and juvenile population of trees (1.20%). Albizia amara has the greatest biomass and carbon stock (58.31%) among trees except for two plots (24 and 25) where Chloroxylon swietenia contributed more to biomass and carbon stock. Similarly, Albizia amara (52.4%) showed greater carbon storage in juvenile population of trees followed by Chloroxylon swietenia (21.9%). Pterolobium hexapetalum (38.86%) showed a greater accumulation of carbon in liana species followed by Combretum albidum (33.04%). Even though, all the study plots are located within 10 km radius, they show a significant spatial variation among them in terms of biomass and carbon stocks which could be attributed to variation in anthropogenic pressures among the plots as well as to changes in tree density across landscapes. Total basal area of woody vegetation showed a significant positive (R 2  = 0.978; P = 0.000) relationship with carbon storage while juvenile tree basal area showed the negative relationship (R 2  = 0.4804; P = 0.000) with woody carbon storage. The present study generates a large-scale baseline data of dry deciduous forest carbon stock, which would facilitate carbon stock assessment at a national level as well as to understand its contribution on a global scale.

A SPATIAL ANALYSIS OF FINE-ROOT BIOMASS FROM STAND DATA IN OREGON AND WASHINGTON

EPA Science Inventory

Because of the high spatial variability of fine roots in natural forest stands, accurate estimates of stand-level fine root biomass are difficult and expensive to obtain by standard coring methods. This study compares two different approaches that employ aboveground tree metrics...

A SPATIAL ANALYSIS OF THE FINE ROOT BIOMASS FROM STAND DATA IN THE PACIFIC NORTHWEST

EPA Science Inventory

High spatial variability of fine roots in natural forest stands makes accurate estimates of stand-level fine root biomass difficult and expensive to obtain by standard coring methods. This study uses aboveground tree metrics and spatial relationships to improve core-based estima...

Uncertainty in the spatial distribution of tropical forest biomass: a comparison of pan-tropical maps.

PubMed

Mitchard, Edward Ta; Saatchi, Sassan S; Baccini, Alessandro; Asner, Gregory P; Goetz, Scott J; Harris, Nancy L; Brown, Sandra

2013-10-26

Mapping the aboveground biomass of tropical forests is essential both for implementing conservation policy and reducing uncertainties in the global carbon cycle. Two medium resolution (500 m - 1000 m) pantropical maps of vegetation biomass have been recently published, and have been widely used by sub-national and national-level activities in relation to Reducing Emissions from Deforestation and forest Degradation (REDD+). Both maps use similar input data layers, and are driven by the same spaceborne LiDAR dataset providing systematic forest height and canopy structure estimates, but use different ground datasets for calibration and different spatial modelling methodologies. Here, we compare these two maps to each other, to the FAO's Forest Resource Assessment (FRA) 2010 country-level data, and to a high resolution (100 m) biomass map generated for a portion of the Colombian Amazon. We find substantial differences between the two maps, in particular in central Amazonia, the Congo basin, the south of Papua New Guinea, the Miombo woodlands of Africa, and the dry forests and savannas of South America. There is little consistency in the direction of the difference. However, when the maps are aggregated to the country or biome scale there is greater agreement, with differences cancelling out to a certain extent. When comparing country level biomass stocks, the two maps agree with each other to a much greater extent than to the FRA 2010 estimates. In the Colombian Amazon, both pantropical maps estimate higher biomass than the independent high resolution map, but show a similar spatial distribution of this biomass. Biomass mapping has progressed enormously over the past decade, to the stage where we can produce globally consistent maps of aboveground biomass. We show that there are still large uncertainties in these maps, in particular in areas with little field data. However, when used at a regional scale, different maps appear to converge, suggesting we can provide reasonable stock estimates when aggregated over large regions. Therefore we believe the largest uncertainties for REDD+ activities relate to the spatial distribution of biomass and to the spatial pattern of forest cover change, rather than to total globally or nationally summed carbon density.

GAP SIZE AND SUCCESSIONAL PROCESSES IN SOUTHERN APPALACHIAN FORESTS

EPA Science Inventory

We used clearcut logging in establishing four replicated sizes of canopy openings (0.016, 0.08, 0.4, and 2.0 ha) in a southern Appalachian hardwood forest in 1981 to examine the long-term effects of disturbance size on plant community structure, biomass accumulation, aboveground ...

Estimating aboveground tree biomass for beetle-killed lodgepole pine in the Rocky Mountains of northern Colorado

Treesearch

Woodam Chung; Paul Evangelista; Nathaniel Anderson; Anthony Vorster; Hee Han; Krishna Poudel; Robert Sturtevant

2017-01-01

The recent mountain pine beetle (Dendroctonus ponderosae Hopkins) epidemic has affected millions of hectares of conifer forests in the Rocky Mountains. Land managers are interested in using biomass from beetle-killed trees for bioenergy and biobased products, but they lack adequate information to accurately estimate biomass in stands with heavy mortality. We...

Height-diameter allometry of tropical forest trees

Treesearch

T.R. Feldpausch; L. Banin; O.L. Phillips; T.R. Baker; S.L. Lewis; C.A. Quesada; K. Affum-Baffoe; E.J.M.M. Arets; N.J. Berry; M. Bird; E.S. Brondizio; P de Camargo; J. Chave; G. Djagbletey; T.F. Domingues; M. Drescher; P.M. Fearnside; M.B. Franca; N.M. Fyllas; G. Lopez-Gonzalez; A. Hladik; N. Higuchi; M.O. Hunter; Y. Iida; K.A. Salim; A.R. Kassim; M. Keller; J. Kemp; D.A. King; J.C. Lovett; B.S. Marimon; B.H. Marimon-Junior; E. Lenza; A.R. Marshall; D.J. Metcalfe; E.T.A. Mitchard; E.F. Moran; B.W. Nelson; R. Nilus; E.M. Nogueira; M. Palace; S. Patiño; K.S.-H. Peh; M.T. Raventos; J.M. Reitsma; G. Saiz; F. Schrodt; B. Sonke; H.E. Taedoumg; S. Tan; L. White; H. Woll; J. Lloyd

2011-01-01

Tropical tree height-diameter (H:D) relationships may vary by forest type and region making large-scale estimates of above-ground biomass subject to bias if they ignore these differences in stem allometry. We have therefore developed a new global tropical forest database consisting of 39 955 concurrent H and D measurements encompassing 283 sites in 22 tropical...

Fire in the Brazilian Amazon : 3. Dynamics of biomass, C, and nutrient pools in regenerating forests.

PubMed

Hughes, R F; Kauffman, J B; Cummings, D L

2000-09-01

Regenerating forests have become a common land-cover type throughout the Brazilian Amazon. However, the potential for these systems to accumulate and store C and nutrients, and the fluxes resulting from them when they are cut, burned, and converted back to croplands and pastures have not been well quantified. In this study, we quantified pre- and post-fire pools of biomass, C, and nutrients, as well as the emissions of those elements, at a series of second- and third-growth forests located in the states of Pará and Rondônia, Brazil. Total aboveground biomass (TAGB) of second- and third-growth forests averaged 134 and 91 Mg ha -1 , respectively. Rates of aboveground biomass accumulation were rapid in these systems, but were not significantly different between second- and third-growth forests, ranging from 9 to 16 Mg ha -1 year -1 . Residual pools of biomass originating from primary forest vegetation accounted for large portions of TAGB in both forest types and were primarily responsible for TAGB differences between the two forest types. In second-growth forests this pool (82 Mg ha -1 ) represented 58% of TAGB, and in third-growth forests (40 Mg ha -1 ) it represented 40% of TAGB. Amounts of TAGB consumed by burning of second- and third-growth forests averaged 70 and 53 Mg ha -1 , respectively. Aboveground pre-fire pools in second- and third-growth forests averaged 67 and 45 Mg C ha -1 , 821 and 707 kg N ha -1 , 441 and 341 kg P ha -1 , and 46 and 27 kg Ca ha -1 , respectively. While pre-fire pools of C, N, S and K were not significantly different between second- and third-growth forests, pools of both P and Ca were significantly higher in second-growth forests. This suggests that increasing land use has a negative impact on these elemental pools. Site losses of elements resulting from slashing and burning these sites were highly variable: losses of C ranged from 20 to 47 Mg ha -1 ; N losses ranged from 306 to 709 kg ha -1 ; Ca losses ranged from 10 to 145 kg ha -1 ; and P losses ranged from 2 to 20 kg ha -1 . Elemental losses were controlled to a large extent by the relative distribution of elemental mass within biomass components of varying susceptibilities to combustion and the temperatures of volatilization of each element. Due to a relatively low temperature of volatilization and its concentration in highly combustible biomass pools, site losses of N averaged 70% of total pre-fire pools. In contrast, site losses of P and Ca resulting from burning were 33 and 20% of total pre-fire pools, respectively, as much of the mass of those elements was deposited on site as ash. Pre- and post-fire biomass and elemental pools of second- and third-growth forests, as well as the emissions from those systems, were intermediate between those of primary forests and pastures in the Brazilian Amazon. Overall, regenerating forests have the capacity to act as either large terrestrial sinks or sources of C and nutrients, depending on the course of land-use patterns within the Brazilian Amazon. Combining remote sensing techniques with field measures of aboveground C accumulation in regenerating forests and C fluxes from those forests when they are cut and burned, we estimate that during 1990-1991 roughly 104 Tg of C was accumulated by regenerating forests across the Brazilian Amazon. Further, we estimate that approximately 103 Tg of C was lost via the cutting and burning of regenerating forests across the Brazilian Amazon during this same period. Since average C accumulations (5.5 Mg ha -1 year -1 ) in regenerating forests were 19% of the C lost when such forests are cut and burned (29.3 Mg ha -1 ), our results suggest that when less than 19% of the total area accounted for by secondary forests is cut and burned in a given year, those forests will be net accumulators of C during that year. Conversely, when more than 19% of regenerating forests are burned, those forests will be a net source of C to the atmosphere.

Iowa's forest resources in 2002.

Treesearch

Earl C Leatherberry; Gary J. Brand

2004-01-01

Results of the 2002 annual inventory of Iowa show an estimated 2.7 million acres of forest land. The estimate of total all live tree volume on forest land is 3.9 billion cubic feet. Nearly 2.6 million acres of forest land in Iowa are classified as timberland. The estimate of growing-stock volume on timberland is 3.0 billion cubic feet. All live aboveground tree biomass...

Changes in carbon storage and net carbon exchange one year after an initial shelterwood harvest at Howland Forest, ME

Treesearch

Neal A. Scott; Charles A. Rodrigues; Holly Hughes; John T. Lee; Eric A. Davidson; D Bryan Dail; Phil Malerba; David Y. Hollinger

2004-01-01

Although many forests are actively sequestering carbon, little research has examined the direct effects of forest management practices on carbon sequestration. At the Howland Forest in Maine, USA, we are using eddy covariance and biometric techniques to evaluate changes in carbon storage following a shelterwood cut that removed just under 30% of aboveground biomass....

Measuring and modeling carbon stock change estimates for US forests and uncertainties from apparent inter-annual variability

Treesearch

James E. Smith; Linda S. Heath

2015-01-01

Our approach is based on a collection of models that convert or augment the USDA Forest Inventory and Analysis program survey data to estimate all forest carbon component stocks, including live and standing dead tree aboveground and belowground biomass, forest floor (litter), down deadwood, and soil organic carbon, for each inventory plot. The data, which include...

Variability in oak forest herb layer communities

Treesearch

J. R. McClenahen; R. P. Long

1995-01-01

This study evaluates forest herb-layer sensitivity to annual-scale environmental fluctuation. Specific objectives were to determine the between-year variation in herb-layer community biomass, and to contrast and evaluate the temporal stability of spatial relationships in herb-layer community structure and composition between successive years. Aboveground dry weights of...

Fine root dynamics and forest production across a calcium gradient in northern hardwood and conifer ecosystems

USGS Publications Warehouse

Park, B.B.; Yanai, R.D.; Fahey, T.J.; Bailey, S.W.; Siccama, T.G.; Shanley, J.B.; Cleavitt, N.L.

2008-01-01

Losses of soil base cations due to acid rain have been implicated in declines of red spruce and sugar maple in the northeastern USA. We studied fine root and aboveground biomass and production in five northern hardwood and three conifer stands differing in soil Ca status at Sleepers River, VT; Hubbard Brook, NH; and Cone Pond, NH. Neither aboveground biomass and production nor belowground biomass were related to soil Ca or Ca:Al ratios across this gradient. Hardwood stands had 37% higher aboveground biomass (P = 0.03) and 44% higher leaf litter production (P < 0.01) than the conifer stands, on average. Fine root biomass (<2 mm in diameter) in the upper 35 cm of the soil, including the forest floor, was very similar in hardwoods and conifers (5.92 and 5.93 Mg ha-1). The turnover coefficient (TC) of fine roots smaller than 1 mm ranged from 0.62 to 1.86 y-1 and increased significantly with soil exchangeable Ca (P = 0.03). As a result, calculated fine root production was clearly higher in sites with higher soil Ca (P = 0.02). Fine root production (biomass times turnover) ranged from 1.2 to 3.7 Mg ha-1 y-1 for hardwood stands and from 0.9 to 2.3 Mg ha-1 y -1 for conifer stands. The relationship we observed between soil Ca availability and root production suggests that cation depletion might lead to reduced carbon allocation to roots in these ecosystems. ?? 2008 Springer Science+Business Media, LLC.

Soil carbon stocks across tropical forests of Panama regulated by base cation effects on fine roots

DOE PAGES

Cusack, Daniela F.; Markesteijn, Lars; Condit, Richard; ...

2018-01-02

We report that tropical forests are the most carbon (C)- rich ecosystems on Earth, containing 25–40% of global terrestrial C stocks. While large-scale quantifi- cation of aboveground biomass in tropical forests has improved recently, soil C dynamics remain one of the largest sources of uncertainty in Earth system models, which inhibits our ability to predict future climate. Globally, soil texture and climate predict B 30% of the variation in soil C stocks, so ecosystem models often predict soil C using measures of aboveground plant growth. However, this approach can underestimate tropical soil C stocks, and has proven inaccurate when comparedmore » with data for soil C in data-rich northern ecosystems. By quantifying soil organic C stocks to 1 m depth for 48 humid tropical forest plots across gradients of rainfall and soil fertility in Panama, we show that soil C does not correlate with common predictors used in models, such as plant biomass or litter production. Instead, a structural equation model including base cations, soil clay content, and rainfall as exogenous factors and root biomass as an endogenous factor predicted nearly 50% of the variation in tropical soil C stocks, indicating a strong indirect effect of base cation availability on tropical soil C storage. Including soil base cations in C cycle models, and thus emphasizing mechanistic links among nutrients, root biomass, and soil C stocks, will improve prediction of climate-soil feedbacks in tropical forests.« less

Soil carbon stocks across tropical forests of Panama regulated by base cation effects on fine roots

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cusack, Daniela F.; Markesteijn, Lars; Condit, Richard

We report that tropical forests are the most carbon (C)- rich ecosystems on Earth, containing 25–40% of global terrestrial C stocks. While large-scale quantifi- cation of aboveground biomass in tropical forests has improved recently, soil C dynamics remain one of the largest sources of uncertainty in Earth system models, which inhibits our ability to predict future climate. Globally, soil texture and climate predict B 30% of the variation in soil C stocks, so ecosystem models often predict soil C using measures of aboveground plant growth. However, this approach can underestimate tropical soil C stocks, and has proven inaccurate when comparedmore » with data for soil C in data-rich northern ecosystems. By quantifying soil organic C stocks to 1 m depth for 48 humid tropical forest plots across gradients of rainfall and soil fertility in Panama, we show that soil C does not correlate with common predictors used in models, such as plant biomass or litter production. Instead, a structural equation model including base cations, soil clay content, and rainfall as exogenous factors and root biomass as an endogenous factor predicted nearly 50% of the variation in tropical soil C stocks, indicating a strong indirect effect of base cation availability on tropical soil C storage. Including soil base cations in C cycle models, and thus emphasizing mechanistic links among nutrients, root biomass, and soil C stocks, will improve prediction of climate-soil feedbacks in tropical forests.« less

Shifts in Aboveground Biomass Allocation Patterns of Dominant Shrub Species across a Strong Environmental Gradient

PubMed Central

Kumordzi, Bright B.; Gundale, Michael J.; Nilsson, Marie-Charlotte; Wardle, David A.

2016-01-01

Most plant biomass allocation studies have focused on allocation to shoots versus roots, and little is known about drivers of allocation for aboveground plant organs. We explored the drivers of within-and between-species variation of aboveground biomass allocation across a strong environmental resource gradient, i.e., a long-term chronosequence of 30 forested islands in northern Sweden across which soil fertility and plant productivity declines while light availability increases. For each of the three coexisting dominant understory dwarf shrub species on each island, we estimated the fraction of the total aboveground biomass produced year of sampling that was allocated to sexual reproduction (i.e., fruits), leaves and stems for each of two growing seasons, to determine how biomass allocation responded to the chronosequence at both the within-species and whole community levels. Against expectations, within-species allocation to fruits was least on less fertile islands, and allocation to leaves at the whole community level was greatest on intermediate islands. Consistent with expectations, different coexisting species showed contrasting allocation patterns, with the species that was best adapted for more fertile conditions allocating the most to vegetative organs, and with its allocation pattern showing the strongest response to the gradient. Our study suggests that co-existing dominant plant species can display highly contrasting biomass allocations to different aboveground organs within and across species in response to limiting environmental resources within the same plant community. Such knowledge is important for understanding how community assembly, trait spectra, and ecological processes driven by the plant community vary across environmental gradients and among contrasting ecosystems. PMID:27270445

Conversion of tropical lowland forest reduces nutrient return through litterfall, and alters nutrient use efficiency and seasonality of net primary production.

PubMed

Kotowska, Martyna M; Leuschner, Christoph; Triadiati, Triadiati; Hertel, Dietrich

2016-02-01

Tropical landscapes are not only rapidly transformed by ongoing land-use change, but are additionally confronted by increasing seasonal climate variation. There is an increasing demand for studies analyzing the effects and feedbacks on ecosystem functioning of large-scale conversions of tropical natural forest into intensively managed cash crop agriculture. We analyzed the seasonality of aboveground litterfall, fine root litter production, and aboveground woody biomass production (ANPP(woody)) in natural lowland forests, rubber agroforests under natural tree cover ("jungle rubber"), rubber and oil palm monocultures along a forest-to-agriculture transformation gradient in Sumatra. We hypothesized that the temporal fluctuation of litter production increases with increasing land-use intensity, while the associated nutrient fluxes and nutrient use efficiency (NUE) decrease. Indeed, the seasonal variation of aboveground litter production and ANPP(woody) increased from the natural forest to the plantations, while aboveground litterfall generally decreased. Nutrient return through aboveground litter was mostly highest in the natural forest; however, it was significantly lower only in rubber plantations. NUE of N, P and K was lowest in the oil palm plantations, with natural forest and the rubber systems showing comparably high values. Root litter production was generally lower than leaf litter production in all systems, while the root-to-leaf ratio of litter C flux increased along the land-use intensity gradient. Our results suggest that nutrient and C cycles are more directly affected by climate seasonality in species-poor agricultural systems than in species-rich forests, and therefore might be more susceptible to inter-annual climate fluctuation and climate change.

Degraded tropical rain forests possess valuable carbon storage opportunities in a complex, forested landscape.

PubMed

Alamgir, Mohammed; Campbell, Mason J; Turton, Stephen M; Pert, Petina L; Edwards, Will; Laurance, William F

2016-07-20

Tropical forests are major contributors to the terrestrial global carbon pool, but this pool is being reduced via deforestation and forest degradation. Relatively few studies have assessed carbon storage in degraded tropical forests. We sampled 37,000 m(2) of intact rainforest, degraded rainforest and sclerophyll forest across the greater Wet Tropics bioregion of northeast Australia. We compared aboveground biomass and carbon storage of the three forest types, and the effects of forest structural attributes and environmental factors that influence carbon storage. Some degraded forests were found to store much less aboveground carbon than intact rainforests, whereas others sites had similar carbon storage to primary forest. Sclerophyll forests had lower carbon storage, comparable to the most heavily degraded rainforests. Our findings indicate that under certain situations, degraded forest may store as much carbon as intact rainforests. Strategic rehabilitation of degraded forests could enhance regional carbon storage and have positive benefits for tropical biodiversity.

Degraded tropical rain forests possess valuable carbon storage opportunities in a complex, forested landscape

PubMed Central

Alamgir, Mohammed; Campbell, Mason J.; Turton, Stephen M.; Pert, Petina L.; Edwards, Will; Laurance, William F.

2016-01-01

Tropical forests are major contributors to the terrestrial global carbon pool, but this pool is being reduced via deforestation and forest degradation. Relatively few studies have assessed carbon storage in degraded tropical forests. We sampled 37,000 m2 of intact rainforest, degraded rainforest and sclerophyll forest across the greater Wet Tropics bioregion of northeast Australia. We compared aboveground biomass and carbon storage of the three forest types, and the effects of forest structural attributes and environmental factors that influence carbon storage. Some degraded forests were found to store much less aboveground carbon than intact rainforests, whereas others sites had similar carbon storage to primary forest. Sclerophyll forests had lower carbon storage, comparable to the most heavily degraded rainforests. Our findings indicate that under certain situations, degraded forest may store as much carbon as intact rainforests. Strategic rehabilitation of degraded forests could enhance regional carbon storage and have positive benefits for tropical biodiversity. PMID:27435389

Degraded tropical rain forests possess valuable carbon storage opportunities in a complex, forested landscape

NASA Astrophysics Data System (ADS)

Alamgir, Mohammed; Campbell, Mason J.; Turton, Stephen M.; Pert, Petina L.; Edwards, Will; Laurance, William F.

2016-07-01

Tropical forests are major contributors to the terrestrial global carbon pool, but this pool is being reduced via deforestation and forest degradation. Relatively few studies have assessed carbon storage in degraded tropical forests. We sampled 37,000 m2 of intact rainforest, degraded rainforest and sclerophyll forest across the greater Wet Tropics bioregion of northeast Australia. We compared aboveground biomass and carbon storage of the three forest types, and the effects of forest structural attributes and environmental factors that influence carbon storage. Some degraded forests were found to store much less aboveground carbon than intact rainforests, whereas others sites had similar carbon storage to primary forest. Sclerophyll forests had lower carbon storage, comparable to the most heavily degraded rainforests. Our findings indicate that under certain situations, degraded forest may store as much carbon as intact rainforests. Strategic rehabilitation of degraded forests could enhance regional carbon storage and have positive benefits for tropical biodiversity.

Above-ground biomass prediction by Sentinel-1 multitemporal data in central Italy with integration of ALOS2 and Sentinel-2 data

NASA Astrophysics Data System (ADS)

Laurin, Gaia Vaglio; Balling, Johannes; Corona, Piermaria; Mattioli, Walter; Papale, Dario; Puletti, Nicola; Rizzo, Maria; Truckenbrodt, John; Urban, Marcel

2018-01-01

The objective of this research is to test Sentinel-1 SAR multitemporal data, supported by multispectral and SAR data at other wavelengths, for fine-scale mapping of above-ground biomass (AGB) at the provincial level in a Mediterranean forested landscape. The regression results indicate good accuracy of prediction (R2=0.7) using integrated sensors when an upper bound of 400 Mg ha-1 is used in modeling. Multitemporal SAR information was relevant, allowing the selection of optimal Sentinel-1 data, as broadleaf forests showed a different response in backscatter throughout the year. Similar accuracy in predictions was obtained when using SAR multifrequency data or joint SAR and optical data. Predictions based on SAR data were more conservative, and in line with those from an independent sample from the National Forest Inventory, than those based on joint data types. The potential of S1 data in predicting AGB can possibly be improved if models are developed per specific groups (deciduous or evergreen species) or forest types and using a larger range of ground data. Overall, this research shows the usefulness of Sentinel-1 data to map biomass at very high resolution for local study and at considerable carbon density.

Inference for lidar-assisted estimation of forest growing stock volume

Treesearch

Ronald E. McRoberts; Erik Næsset; Terje Gobakken

2013-01-01

Estimates of growing stock volume are reported by the national forest inventories (NFI) of most countries and may serve as the basis for aboveground biomass and carbon estimates as required by an increasing number of international agreements. The probability-based (design-based) statistical estimators traditionally used by NFIs to calculate estimates are generally...

Iowa's forest resources in 2000

Treesearch

Joseph T. II Boykin

2003-01-01

Results of the 2000 annual inventory of Iowa show that there are as estimated 2.5 million acres of forest land; 3.2 billion cubic feet of all live volume on timberland; and 87 million dry tons of all live aboveground tree biomass on timberland. Known pathogens and pests in Iowa's forets include oak wilt and gypsy moth.

Estimating leaf area and above-ground biomass of forest regeneration areas using a corrected normalized difference vegetation index

Treesearch

Tommy L. Coleman; James H. Miller; Bruce R. Zutter

1992-01-01

The objective of this study was to investigate the regression relations between vegetation indices derived from remotely-sensed data of single and mixed forest regeneration plots. Loblolly pine (Pinus taeda L.) seedlings, sweelgum (Liquidambar styraciflua L.) seedlings and broomsedge (Andropogon virginicus L.)...

Canopy carbon net assimilation of an urban, naturally assembled brownfield forest

NASA Astrophysics Data System (ADS)

Schafer, K. V.; Wadhwa, S.; Tripathee, R.; Gallagher, F. J.

2010-12-01

In this study, we have been investigating an urban brownfield at Liberty State Park that has been abandoned approximately for 40 years. Natural colonization has taken place that allowed a pioneer forest to grow with primarily Betula populifera and Populus spec. Despite soil metal contamination this urban forest exhibits moderate annual productivity and serves as a carbon sink. Diameters at breast height (DBH, 1.35 m above ground) of all trees in a study plot were measured. Aboveground biomass equations were determined for both species through destructive sampling. Aboveground net primary production was about 770 gC m-2 a-1 in 2009. Canopy net assimilation (AnC) was modeled with the canopy conductance constrained assimilation (4CA) model using measured sapflux derived conductance and photosynthetic parameters measured with a LICOR 6400. Annual AnC in 2009 was approximately 1500 gC m-2 a-1 thus with a partitioning of biomass and respiration in the same range of most natural forest with less anthropogenic induced stress. Urban brownfields thus can serve as C sinks and provide phytostabilization of contaminants.

Forest structure in low-diversity tropical forests: a study of Hawaiian wet and dry forests.

PubMed

Ostertag, Rebecca; Inman-Narahari, Faith; Cordell, Susan; Giardina, Christian P; Sack, Lawren

2014-01-01

The potential influence of diversity on ecosystem structure and function remains a topic of significant debate, especially for tropical forests where diversity can range widely. We used Center for Tropical Forest Science (CTFS) methodology to establish forest dynamics plots in montane wet forest and lowland dry forest on Hawai'i Island. We compared the species diversity, tree density, basal area, biomass, and size class distributions between the two forest types. We then examined these variables across tropical forests within the CTFS network. Consistent with other island forests, the Hawai'i forests were characterized by low species richness and very high relative dominance. The two Hawai'i forests were floristically distinct, yet similar in species richness (15 vs. 21 species) and stem density (3078 vs. 3486/ha). While these forests were selected for their low invasive species cover relative to surrounding forests, both forests averaged 5->50% invasive species cover; ongoing removal will be necessary to reduce or prevent competitive impacts, especially from woody species. The montane wet forest had much larger trees, resulting in eightfold higher basal area and above-ground biomass. Across the CTFS network, the Hawaiian montane wet forest was similar to other tropical forests with respect to diameter distributions, density, and aboveground biomass, while the Hawai'i lowland dry forest was similar in density to tropical forests with much higher diversity. These findings suggest that forest structural variables can be similar across tropical forests independently of species richness. The inclusion of low-diversity Pacific Island forests in the CTFS network provides an ∼80-fold range in species richness (15-1182 species), six-fold variation in mean annual rainfall (835-5272 mm yr(-1)) and 1.8-fold variation in mean annual temperature (16.0-28.4°C). Thus, the Hawaiian forest plots expand the global forest plot network to enable testing of ecological theory for links among species diversity, environmental variation and ecosystem function.

Forest Structure in Low-Diversity Tropical Forests: A Study of Hawaiian Wet and Dry Forests

PubMed Central

Ostertag, Rebecca; Inman-Narahari, Faith; Cordell, Susan; Giardina, Christian P.; Sack, Lawren

2014-01-01

The potential influence of diversity on ecosystem structure and function remains a topic of significant debate, especially for tropical forests where diversity can range widely. We used Center for Tropical Forest Science (CTFS) methodology to establish forest dynamics plots in montane wet forest and lowland dry forest on Hawai‘i Island. We compared the species diversity, tree density, basal area, biomass, and size class distributions between the two forest types. We then examined these variables across tropical forests within the CTFS network. Consistent with other island forests, the Hawai‘i forests were characterized by low species richness and very high relative dominance. The two Hawai‘i forests were floristically distinct, yet similar in species richness (15 vs. 21 species) and stem density (3078 vs. 3486/ha). While these forests were selected for their low invasive species cover relative to surrounding forests, both forests averaged 5–>50% invasive species cover; ongoing removal will be necessary to reduce or prevent competitive impacts, especially from woody species. The montane wet forest had much larger trees, resulting in eightfold higher basal area and above-ground biomass. Across the CTFS network, the Hawaiian montane wet forest was similar to other tropical forests with respect to diameter distributions, density, and aboveground biomass, while the Hawai‘i lowland dry forest was similar in density to tropical forests with much higher diversity. These findings suggest that forest structural variables can be similar across tropical forests independently of species richness. The inclusion of low-diversity Pacific Island forests in the CTFS network provides an ∼80-fold range in species richness (15–1182 species), six-fold variation in mean annual rainfall (835–5272 mm yr−1) and 1.8-fold variation in mean annual temperature (16.0–28.4°C). Thus, the Hawaiian forest plots expand the global forest plot network to enable testing of ecological theory for links among species diversity, environmental variation and ecosystem function. PMID:25162731

Mapping above- and below-ground carbon pools in boreal forests: The case for airborne lidar

Treesearch

Terje Kristensen; Erik Naesset; Mikael Ohlson; Paul V. Bolstad; Randall Kolka

2015-01-01

A large and growing body of evidence has demonstrated that airborne scanning light detection and ranging (lidar) systems can be an effective tool in measuring and monitoring above-ground forest tree biomass. However, the potential of lidar as an all-round tool for assisting in assessment of carbon (C) stocks in soil and non-tree vegetation components of the forest...

Simulating ungulate herbivory across forest landscapes: A browsing extension for LANDIS-II

USGS Publications Warehouse

DeJager, Nathan R.; Drohan, Patrick J.; Miranda, Brian M.; Sturtevant, Brian R.; Stout, Susan L.; Royo, Alejandro; Gustafson, Eric J.; Romanski, Mark C.

2017-01-01

Browsing ungulates alter forest productivity and vegetation succession through selective foraging on species that often dominate early succession. However, the long-term and large-scale effects of browsing on forest succession are not possible to project without the use of simulation models. To explore the effects of ungulates on succession in a spatially explicit manner, we developed a Browse Extension that simulates the effects of browsing ungulates on the growth and survival of plant species cohorts within the LANDIS-II spatially dynamic forest landscape simulation model framework. We demonstrate the capabilities of the new extension and explore the spatial effects of ungulates on forest composition and dynamics using two case studies. The first case study examined the long-term effects of persistently high white-tailed deer browsing rates in the northern hardwood forests of the Allegheny National Forest, USA. In the second case study, we incorporated a dynamic ungulate population model to simulate interactions between the moose population and boreal forest landscape of Isle Royale National Park, USA. In both model applications, browsing reduced total aboveground live biomass and caused shifts in forest composition. Simulations that included effects of browsing resulted in successional patterns that were more similar to those observed in the study regions compared to simulations that did not incorporate browsing effects. Further, model estimates of moose population density and available forage biomass were similar to previously published field estimates at Isle Royale and in other moose-boreal forest systems. Our simulations suggest that neglecting effects of browsing when modeling forest succession in ecosystems known to be influenced by ungulates may result in flawed predictions of aboveground biomass and tree species composition.

Spatially explicit estimation of aboveground boreal forest biomass in the Yukon River Basin, Alaska

USGS Publications Warehouse

Ji, Lei; Wylie, Bruce K.; Brown, Dana R. N.; Peterson, Birgit E.; Alexander, Heather D.; Mack, Michelle C.; Rover, Jennifer R.; Waldrop, Mark P.; McFarland, Jack W.; Chen, Xuexia; Pastick, Neal J.

2015-01-01

Quantification of aboveground biomass (AGB) in Alaska’s boreal forest is essential to the accurate evaluation of terrestrial carbon stocks and dynamics in northern high-latitude ecosystems. Our goal was to map AGB at 30 m resolution for the boreal forest in the Yukon River Basin of Alaska using Landsat data and ground measurements. We acquired Landsat images to generate a 3-year (2008–2010) composite of top-of-atmosphere reflectance for six bands as well as the brightness temperature (BT). We constructed a multiple regression model using field-observed AGB and Landsat-derived reflectance, BT, and vegetation indices. A basin-wide boreal forest AGB map at 30 m resolution was generated by applying the regression model to the Landsat composite. The fivefold cross-validation with field measurements had a mean absolute error (MAE) of 25.7 Mg ha−1 (relative MAE 47.5%) and a mean bias error (MBE) of 4.3 Mg ha−1(relative MBE 7.9%). The boreal forest AGB product was compared with lidar-based vegetation height data; the comparison indicated that there was a significant correlation between the two data sets.

Implication of Forest-Savanna Dynamics on Biomass and Carbon Stock: Effectiveness of an Amazonian Ecological Station

NASA Astrophysics Data System (ADS)

Couto-Santos, F. R.; Luizao, F. J.

2014-12-01

The forests-savanna advancement/retraction process seems to play an important role in the global carbon cycle and in the climate-vegetation balance maintenance in the Amazon. To contribute with long term carbon dynamics and assess effectiveness of a protected area in reduce carbon emissions in Brazilian Amazon transitional areas, variations in forest-savanna mosaics biomass and carbon stock within Maraca Ecological Station (MES), Roraima/Brazil, and its outskirts non-protected areas were compared. Composite surface soil samples and indirect methods based on regression models were used to estimate aboveground tree biomass accumulation and assess vegetation and soil carbon stock along eleven 0.6 ha transects perpendicular to the forest-savanna limits. Aboveground biomass and carbon accumulation were influenced by vegetation structure, showing higher values within protected area, with great contribution of trees above 40 cm in diameter. In the savanna environments of protected areas, a higher tree density and carbon stock up to 30 m from the border confirmed a forest encroachment. This pointed that MES acts as carbon sink, even under variations in soil fertility gradient, with a potential increase of the total carbon stock from 9 to 150 Mg C ha-1. Under 20 years of fire and disturbance management, the results indicated the effectiveness of this protected area to reduce carbon emissions and mitigate greenhouse and climate change effects in a forest-savanna transitional area in Brazilian Northern Amazon. The contribution of this study in understanding rates and reasons for biomass and carbon variation, under different management strategies, should be considered the first approximation to assist policies of reducing emissions from deforestation and forest degradation (REDD) from underresearched Amazonian ecotone; despite further efforts in this direction are still needed. FINANCIAL SUPPORT: Boticário Group Foundation (Fundação Grupo Boticário); National Council for Scientific and Technological Development (CNPq); Minas Gerais State Research Foundation (FAPEMIG).

Effects of harvest management practices on forest biomass and soil carbon in eucalypt forests in New South Wales, Australia: Simulations with the forest succession model LINKAGES

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ranatunga, Kemachandra; Keenan, Rodney J.; Wullschleger, Stan D

2008-01-01

Understanding long-term changes in forest ecosystem carbon stocks under forest management practices such as timber harvesting is important for assessing the contribution of forests to the global carbon cycle. Harvesting effects are complicated by the amount, type, and condition of residue left on-site, the decomposition rate of this residue, the incorporation of residue into soil organic matter and the rate of new detritus input to the forest floor from regrowing vegetation. In an attempt to address these complexities, the forest succession model LINKAGES was used to assess the production of aboveground biomass, detritus, and soil carbon stocks in native Eucalyptusmore » forests as influenced by five harvest management practices in New South Wales, Australia. The original decomposition sub-routines of LINKAGES were modified by adding components of the Rothamsted (RothC) soil organic matter turnover model. Simulation results using the new model were compared to data from long-term forest inventory plots. Good agreement was observed between simulated and measured above-ground biomass, but mixed results were obtained for basal area. Harvesting operations examined included removing trees for quota sawlogs (QSL, DBH >80 cm), integrated sawlogs (ISL, DBH >20 cm) and whole-tree harvesting in integrated sawlogs (WTH). We also examined the impact of different cutting cycles (20, 50 or 80 years) and intensities (removing 20, 50 or 80 m{sup 3}). Generally medium and high intensities of shorter cutting cycles in sawlog harvesting systems produced considerably higher soil carbon values compared to no harvesting. On average, soil carbon was 2-9% lower in whole-tree harvest simulations whereas in sawlog harvest simulations soil carbon was 5-17% higher than in no harvesting.« less

Estimates of grassland biomass and turnover time on the Tibetan Plateau

NASA Astrophysics Data System (ADS)

Xia, Jiangzhou; Ma, Minna; Liang, Tiangang; Wu, Chaoyang; Yang, Yuanhe; Zhang, Li; Zhang, Yangjian; Yuan, Wenping

2018-01-01

The grassland of the Tibetan Plateau forms a globally significant biome, which represents 6% of the world’s grasslands and 44% of China’s grasslands. However, large uncertainties remain concerning the vegetation carbon storage and turnover time in this biome. In this study, we quantified the pool size of both the aboveground and belowground biomass and turnover time of belowground biomass across the Tibetan Plateau by combining systematic measurements taken from a substantial number of surveys (i.e. 1689 sites for aboveground biomass, 174 sites for belowground biomass) with a machine learning technique (i.e. random forest, RF). Our study demonstrated that the RF model is effective tool for upscaling local biomass observations to the regional scale, and for producing continuous biomass estimates of the Tibetan Plateau. On average, the models estimated 46.57 Tg (1 Tg = 1012g) C of aboveground biomass and 363.71 Tg C of belowground biomass in the Tibetan grasslands covering an area of 1.32 × 106 km2. The turnover time of belowground biomass demonstrated large spatial heterogeneity, with a median turnover time of 4.25 years. Our results also demonstrated large differences in the biomass simulations among the major ecosystem models used for the Tibetan Plateau, largely because of inadequate model parameterization and validation. This study provides a spatially continuous measure of vegetation carbon storage and turnover time, and provides useful information for advancing ecosystem models and improving their performance.

Above-ground biomass and structure of 260 African tropical forests

PubMed Central

Lewis, Simon L.; Sonké, Bonaventure; Sunderland, Terry; Begne, Serge K.; Lopez-Gonzalez, Gabriela; van der Heijden, Geertje M. F.; Phillips, Oliver L.; Affum-Baffoe, Kofi; Baker, Timothy R.; Banin, Lindsay; Bastin, Jean-François; Beeckman, Hans; Boeckx, Pascal; Bogaert, Jan; De Cannière, Charles; Chezeaux, Eric; Clark, Connie J.; Collins, Murray; Djagbletey, Gloria; Djuikouo, Marie Noël K.; Droissart, Vincent; Doucet, Jean-Louis; Ewango, Cornielle E. N.; Fauset, Sophie; Feldpausch, Ted R.; Foli, Ernest G.; Gillet, Jean-François; Hamilton, Alan C.; Harris, David J.; Hart, Terese B.; de Haulleville, Thales; Hladik, Annette; Hufkens, Koen; Huygens, Dries; Jeanmart, Philippe; Jeffery, Kathryn J.; Kearsley, Elizabeth; Leal, Miguel E.; Lloyd, Jon; Lovett, Jon C.; Makana, Jean-Remy; Malhi, Yadvinder; Marshall, Andrew R.; Ojo, Lucas; Peh, Kelvin S.-H.; Pickavance, Georgia; Poulsen, John R.; Reitsma, Jan M.; Sheil, Douglas; Simo, Murielle; Steppe, Kathy; Taedoumg, Hermann E.; Talbot, Joey; Taplin, James R. D.; Taylor, David; Thomas, Sean C.; Toirambe, Benjamin; Verbeeck, Hans; Vleminckx, Jason; White, Lee J. T.; Willcock, Simon; Woell, Hannsjorg; Zemagho, Lise

2013-01-01

We report above-ground biomass (AGB), basal area, stem density and wood mass density estimates from 260 sample plots (mean size: 1.2 ha) in intact closed-canopy tropical forests across 12 African countries. Mean AGB is 395.7 Mg dry mass ha−1 (95% CI: 14.3), substantially higher than Amazonian values, with the Congo Basin and contiguous forest region attaining AGB values (429 Mg ha−1) similar to those of Bornean forests, and significantly greater than East or West African forests. AGB therefore appears generally higher in palaeo- compared with neotropical forests. However, mean stem density is low (426 ± 11 stems ha−1 greater than or equal to 100 mm diameter) compared with both Amazonian and Bornean forests (cf. approx. 600) and is the signature structural feature of African tropical forests. While spatial autocorrelation complicates analyses, AGB shows a positive relationship with rainfall in the driest nine months of the year, and an opposite association with the wettest three months of the year; a negative relationship with temperature; positive relationship with clay-rich soils; and negative relationships with C : N ratio (suggesting a positive soil phosphorus–AGB relationship), and soil fertility computed as the sum of base cations. The results indicate that AGB is mediated by both climate and soils, and suggest that the AGB of African closed-canopy tropical forests may be particularly sensitive to future precipitation and temperature changes. PMID:23878327

Introduction to the invited issue on carbon allocation of trees and forests

Treesearch

Daniel Epron; Yann Nouvellon; Michael G. Ryan

2012-01-01

Carbon (C) allocation is a major issue in plant ecology, controlling the flows of C fixed in photosynthesis between respiration and biomass production, and between short- and long-lived and aboveground and belowground tissues. Incomplete knowledge of C allocation currently hinders accurate modelling of tree growth and forest ecosystem metabolism (Friedlingstein et al....

COMBINING LIDAR ESTIMATES OF BIOMASS AND LANDSAT ESTIMATES OF STAND AGE FOR SPATIALLY EXTENSIVE VALIDATION OF MODELED FOREST PRODUCTIVITY. (R828309)

EPA Science Inventory

Extensive estimates of forest productivity are required to understand the
relationships between shifting land use, changing climate and carbon storage
and fluxes. Aboveground net primary production of wood (NPP_Aw) is a major component
of total NPP and...

Where did the US forest biomass/carbon go?

Treesearch

Christopher William Woodall

2012-01-01

In Apr. 2012, with the submission of the 1990-2010 US Greenhouse Gas (GHG) Inventory to the United Nations Framework Convention on Climate Change (UNFCCC), the official estimates of aboveground live tree carbon stocks within managed forests of the United States will drop by approximately 14%, compared with last year's inventory. It does not stop there, dead wood...

Secondary Forest Age and Tropical Forest Biomass Estimation Using TM

NASA Technical Reports Server (NTRS)

Nelson, R. F.; Kimes, D. S.; Salas, W. A.; Routhier, M.

1999-01-01

The age of secondary forests in the Amazon will become more critical with respect to the estimation of biomass and carbon budgets as tropical forest conversion continues. Multitemporal Thematic Mapper data were used to develop land cover histories for a 33,000 Square kM area near Ariquemes, Rondonia over a 7 year period from 1989-1995. The age of the secondary forest, a surrogate for the amount of biomass (or carbon) stored above-ground, was found to be unimportant in terms of biomass budget error rates in a forested TM scene which had undergone a 20% conversion to nonforest/agricultural cover types. In such a situation, the 80% of the scene still covered by primary forest accounted for over 98% of the scene biomass. The difference between secondary forest biomass estimates developed with and without age information were inconsequential relative to the estimate of biomass for the entire scene. However, in futuristic scenarios where all of the primary forest has been converted to agriculture and secondary forest (55% and 42% respectively), the ability to age secondary forest becomes critical. Depending on biomass accumulation rate assumptions, scene biomass budget errors on the order of -10% to +30% are likely if the age of the secondary forests are not taken into account. Single-date TM imagery cannot be used to accurately age secondary forests into single-year classes. A neural network utilizing TM band 2 and three TM spectral-texture measures (bands 3 and 5) predicted secondary forest age over a range of 0-7 years with an RMSE of 1.59 years and an R(Squared) (sub actual vs predicted) = 0.37. A proposal is made, based on a literature review, to use satellite imagery to identify general secondary forest age groups which, within group, exhibit relatively constant biomass accumulation rates.

Multiple metrics of diversity have different effects on temperate forest functioning over succession.

PubMed

Yuan, Zuoqiang; Wang, Shaopeng; Gazol, Antonio; Mellard, Jarad; Lin, Fei; Ye, Ji; Hao, Zhanqing; Wang, Xugao; Loreau, Michel

2016-12-01

Biodiversity can be measured by taxonomic, phylogenetic, and functional diversity. How ecosystem functioning depends on these measures of diversity can vary from site to site and depends on successional stage. Here, we measured taxonomic, phylogenetic, and functional diversity, and examined their relationship with biomass in two successional stages of the broad-leaved Korean pine forest in northeastern China. Functional diversity was calculated from six plant traits, and aboveground biomass (AGB) and coarse woody productivity (CWP) were estimated using data from three forest censuses (10 years) in two large fully mapped forest plots (25 and 5 ha). 11 of the 12 regressions between biomass variables (AGB and CWP) and indices of diversity showed significant positive relationships, especially those with phylogenetic diversity. The mean tree diversity-biomass regressions increased from 0.11 in secondary forest to 0.31 in old-growth forest, implying a stronger biodiversity effect in more mature forest. Multi-model selection results showed that models including species richness, phylogenetic diversity, and single functional traits explained more variation in forest biomass than other candidate models. The models with a single functional trait, i.e., leaf area in secondary forest and wood density in mature forest, provided better explanations for forest biomass than models that combined all six functional traits. This finding may reflect different strategies in growth and resource acquisition in secondary and old-growth forests.

Converting wood volume to biomass for pinyon and juniper. Forest Service research note

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chojnacky, D.C.; Moisen, G.G.

1993-03-01

A technique was developed to convert pinyon-juniper volume equation predictions to weights. The method uses specific gravity and biomass conversion equations to obtain foliage weight and total wood weight of all stems, branches, and bark. Specific gravity data are given for several Arizona pinyon-juniper species. Biomass conversion equations are constructed from pinyon-juniper data collected in Nevada. Results provide an interim means of estimating pinyon-juniper aboveground biomass from available volume inventory data.

Effects of Light Regimes on the Biomass and Morphological Characteristics of 2-Year-Old Cherrybark Oak Seedlings

Treesearch

Yanfei Guo; Michael G. Shelton

2004-01-01

We used modified shadehouses to simulate the complex light conditions within forest openings and tested the effects of time of direct light exposure, the ratio of direct light to day length, and daily photosynthetically active radiation on aboveground biomass and morphological characteristics of 2-year-old cherrybark oak (Quercus pagoda Raf.)...

Combining Multi-Source Remotely Sensed Data and a Process-Based Model for Forest Aboveground Biomass Updating.

PubMed

Lu, Xiaoman; Zheng, Guang; Miller, Colton; Alvarado, Ernesto

2017-09-08

Monitoring and understanding the spatio-temporal variations of forest aboveground biomass (AGB) is a key basis to quantitatively assess the carbon sequestration capacity of a forest ecosystem. To map and update forest AGB in the Greater Khingan Mountains (GKM) of China, this work proposes a physical-based approach. Based on the baseline forest AGB from Landsat Enhanced Thematic Mapper Plus (ETM+) images in 2008, we dynamically updated the annual forest AGB from 2009 to 2012 by adding the annual AGB increment (ABI) obtained from the simulated daily and annual net primary productivity (NPP) using the Boreal Ecosystem Productivity Simulator (BEPS) model. The 2012 result was validated by both field- and aerial laser scanning (ALS)-based AGBs. The predicted forest AGB for 2012 estimated from the process-based model can explain 31% ( n = 35, p < 0.05, RMSE = 2.20 kg/m²) and 85% ( n = 100, p < 0.01, RMSE = 1.71 kg/m²) of variation in field- and ALS-based forest AGBs, respectively. However, due to the saturation of optical remote sensing-based spectral signals and contribution of understory vegetation, the BEPS-based AGB tended to underestimate/overestimate the AGB for dense/sparse forests. Generally, our results showed that the remotely sensed forest AGB estimates could serve as the initial carbon pool to parameterize the process-based model for NPP simulation, and the combination of the baseline forest AGB and BEPS model could effectively update the spatiotemporal distribution of forest AGB.

Combining Multi-Source Remotely Sensed Data and a Process-Based Model for Forest Aboveground Biomass Updating

PubMed Central

Lu, Xiaoman; Zheng, Guang; Miller, Colton

2017-01-01

Monitoring and understanding the spatio-temporal variations of forest aboveground biomass (AGB) is a key basis to quantitatively assess the carbon sequestration capacity of a forest ecosystem. To map and update forest AGB in the Greater Khingan Mountains (GKM) of China, this work proposes a physical-based approach. Based on the baseline forest AGB from Landsat Enhanced Thematic Mapper Plus (ETM+) images in 2008, we dynamically updated the annual forest AGB from 2009 to 2012 by adding the annual AGB increment (ABI) obtained from the simulated daily and annual net primary productivity (NPP) using the Boreal Ecosystem Productivity Simulator (BEPS) model. The 2012 result was validated by both field- and aerial laser scanning (ALS)-based AGBs. The predicted forest AGB for 2012 estimated from the process-based model can explain 31% (n = 35, p < 0.05, RMSE = 2.20 kg/m2) and 85% (n = 100, p < 0.01, RMSE = 1.71 kg/m2) of variation in field- and ALS-based forest AGBs, respectively. However, due to the saturation of optical remote sensing-based spectral signals and contribution of understory vegetation, the BEPS-based AGB tended to underestimate/overestimate the AGB for dense/sparse forests. Generally, our results showed that the remotely sensed forest AGB estimates could serve as the initial carbon pool to parameterize the process-based model for NPP simulation, and the combination of the baseline forest AGB and BEPS model could effectively update the spatiotemporal distribution of forest AGB. PMID:28885556

Changes in composition, structure and aboveground biomass over seventy-six years (1930-2006) in the Black Rock Forest, Hudson Highlands, southeastern New York State.

PubMed

Schuster, W S F; Griffin, K L; Roth, H; Turnbull, M H; Whitehead, D; Tissue, D T

2008-04-01

We sought to quantify changes in tree species composition, forest structure and aboveground forest biomass (AGB) over 76 years (1930-2006) in the deciduous Black Rock Forest in southeastern New York, USA. We used data from periodic forest inventories, published floras and a set of eight long-term plots, along with species-specific allometric equations to estimate AGB and carbon content. Between the early 1930s and 2000, three species were extirpated from the forest (American elm (Ulmus americana L.), paper birch (Betula papyrifera Marsh.) and black spruce (Picea mariana (nigra) (Mill.) BSP)) and seven species invaded the forest (non-natives tree-of-heaven (Ailanthus altissima (Mill.) Swingle) and white poplar (Populus alba L.) and native, generally southerly distributed, southern catalpa (Catalpa bignonioides Walt.), cockspur hawthorn (Crataegus crus-galli L.), red mulberry (Morus rubra L.), eastern cottonwood (Populus deltoides Bartr.) and slippery elm (Ulmus rubra Muhl.)). Forest canopy was dominated by red oak and chestnut oak, but the understory tree community changed substantially from mixed oak-maple to red maple-black birch. Density decreased from an average of 1500 to 735 trees ha(-1), whereas basal area doubled from less than 15 m(2) ha(-1) to almost 30 m(2) ha(-1) by 2000. Forest-wide mean AGB from inventory data increased from about 71 Mg ha(-1) in 1930 to about 145 Mg ha(-1) in 1985, and mean AGB on the long-term plots increased from 75 Mg ha(-1) in 1936 to 218 Mg ha(-1) in 1998. Over 76 years, red oak (Quercus rubra L.) canopy trees stored carbon at about twice the rate of similar-sized canopy trees of other species. However, there has been a significant loss of live tree biomass as a result of canopy tree mortality since 1999. Important constraints on long-term biomass increment have included insect outbreaks and droughts.

Drought sensitivity of the Amazon rainforest.

PubMed

Phillips, Oliver L; Aragão, Luiz E O C; Lewis, Simon L; Fisher, Joshua B; Lloyd, Jon; López-González, Gabriela; Malhi, Yadvinder; Monteagudo, Abel; Peacock, Julie; Quesada, Carlos A; van der Heijden, Geertje; Almeida, Samuel; Amaral, Iêda; Arroyo, Luzmila; Aymard, Gerardo; Baker, Tim R; Bánki, Olaf; Blanc, Lilian; Bonal, Damien; Brando, Paulo; Chave, Jerome; de Oliveira, Atila Cristina Alves; Cardozo, Nallaret Dávila; Czimczik, Claudia I; Feldpausch, Ted R; Freitas, Maria Aparecida; Gloor, Emanuel; Higuchi, Niro; Jiménez, Eliana; Lloyd, Gareth; Meir, Patrick; Mendoza, Casimiro; Morel, Alexandra; Neill, David A; Nepstad, Daniel; Patiño, Sandra; Peñuela, Maria Cristina; Prieto, Adriana; Ramírez, Fredy; Schwarz, Michael; Silva, Javier; Silveira, Marcos; Thomas, Anne Sota; Steege, Hans Ter; Stropp, Juliana; Vásquez, Rodolfo; Zelazowski, Przemyslaw; Alvarez Dávila, Esteban; Andelman, Sandy; Andrade, Ana; Chao, Kuo-Jung; Erwin, Terry; Di Fiore, Anthony; Honorio C, Eurídice; Keeling, Helen; Killeen, Tim J; Laurance, William F; Peña Cruz, Antonio; Pitman, Nigel C A; Núñez Vargas, Percy; Ramírez-Angulo, Hirma; Rudas, Agustín; Salamão, Rafael; Silva, Natalino; Terborgh, John; Torres-Lezama, Armando

2009-03-06

Amazon forests are a key but poorly understood component of the global carbon cycle. If, as anticipated, they dry this century, they might accelerate climate change through carbon losses and changed surface energy balances. We used records from multiple long-term monitoring plots across Amazonia to assess forest responses to the intense 2005 drought, a possible analog of future events. Affected forest lost biomass, reversing a large long-term carbon sink, with the greatest impacts observed where the dry season was unusually intense. Relative to pre-2005 conditions, forest subjected to a 100-millimeter increase in water deficit lost 5.3 megagrams of aboveground biomass of carbon per hectare. The drought had a total biomass carbon impact of 1.2 to 1.6 petagrams (1.2 x 10(15) to 1.6 x 10(15) grams). Amazon forests therefore appear vulnerable to increasing moisture stress, with the potential for large carbon losses to exert feedback on climate change.

Biomass, production and woody detritus in an old coast redwood (Sequoia sempervirens) forest

USGS Publications Warehouse

Busing, R.T.; Fujimori, T.

2005-01-01

We examined aboveground biomass dynamics, aboveground net primary production (ANPP), and woody detritus input in an old Sequoia sempervirens stand over a three-decade period. Our estimates of aboveground biomass ranged from 3300 to 5800 Mg ha-1. Stem biomass estimates ranged from 3000 to 5200 Mg ha-1. Stem biomass declined 7% over the study interval. Biomass dynamics were patchy, with marked declines in recent tree-fall patches <0.05 ha in size. Larger tree-fall patches approaching 0.2 ha in size were observed outside the study plot. Our estimates of ANPP ranged from 6 to 14 Mg ha -1yr-1. Estimates of 7 to 10 Mg ha-1yr -1 were considered to be relatively accurate. Thus, our estimates based on long-term data corroborated the findings of earlier short-term studies. ANPP of old, pure stands of Sequoia was not above average for temperate forests. Even though production was potentially high on a per stem basis, it was moderate at the stand level. We obtained values of 797 m3 ha -1 and 262 Mg ha-1 for coarse woody detritus volume and mass, respectively. Fine woody detritus volume and mass were estimated at 16 m3 ha-1 and 5 Mg ha-1, respectively. Standing dead trees (or snags) comprised 7% of the total coarse detritus volume and 8% of the total mass. Coarse detritus input averaged 5.7 to 6.9 Mg ha -1yr-1. Assuming steady-state input and pool of coarse detritus, we obtained a decay rate constant of 0.022 to 0.026. The old-growth stand of Sequoia studied had extremely high biomass, but ANPP was moderate and the amount of woody detritus was not exceptionally large. Biomass accretion and loss were not rapid in this stand partly because of the slow population dynamics and low canopy turnover rate of Sequoia at the old-growth stage. Nomenclature: Hickman (1993). ?? Springer 2005.

Contribution of aboveground plant respiration to carbon cycling in a Bornean tropical rainforet

NASA Astrophysics Data System (ADS)

Katayama, Ayumi; Tanaka, Kenzo; Ichie, Tomoaki; Kume, Tomonori; Matsumoto, Kazuho; Ohashi, Mizue; Kumagai, Tomo'omi

2014-05-01

Bornean tropical rainforests have a different characteristic from Amazonian tropical rainforests, that is, larger aboveground biomass caused by higher stand density of large trees. Larger biomass may cause different carbon cycling and allocation pattern. However, there are fewer studies on carbon allocation and each component in Bornean tropical rainforests, especially for aboveground plant respiration, compared to Amazonian forests. In this study, we measured woody tissue respiration and leaf respiration, and estimated those in ecosystem scale in a Bornean tropical rainforest. Then, we examined carbon allocation using the data of soil respiration and aboveground net primary production obtained from our previous studies. Woody tissue respiration rate was positively correlated with diameter at breast height (dbh) and stem growth rate. Using the relationships and biomass data, we estimated woody tissue respiration in ecosystem scale though methods of scaling resulted in different estimates values (4.52 - 9.33 MgC ha-1 yr-1). Woody tissue respiration based on surface area (8.88 MgC ha-1 yr-1) was larger than those in Amazon because of large aboveground biomass (563.0 Mg ha-1). Leaf respiration rate was positively correlated with height. Using the relationship and leaf area density data at each 5-m height, leaf respiration in ecosystem scale was estimated (9.46 MgC ha-1 yr-1), which was similar to those in Amazon because of comparable LAI (5.8 m2 m-2). Gross primary production estimated from biometric measurements (44.81 MgC ha-1 yr-1) was much higher than those in Amazon, and more carbon was allocated to woody tissue respiration and total belowground carbon flux. Large tree with dbh > 60cm accounted for about half of aboveground biomass and aboveground biomass increment. Soil respiration was also related to position of large trees, resulting in high soil respiration rate in this study site. Photosynthesis ability of top canopy for large trees was high and leaves for the large trees accounted for 30% of total, which can lead high GPP. These results suggest that large trees play considerable role in carbon cycling and make a distinctive carbon allocation in the Bornean tropical rainforest.

Model Effects on GLAS-Based Regional Estimates of Forest Biomass and Carbon

NASA Technical Reports Server (NTRS)

Nelson, Ross F.

2010-01-01

Ice, Cloud, and land Elevation Satellite (ICESat) / Geosciences Laser Altimeter System (GLAS) waveform data are used to estimate biomass and carbon on a 1.27 X 10(exp 6) square km study area in the Province of Quebec, Canada, below the tree line. The same input datasets and sampling design are used in conjunction with four different predictive models to estimate total aboveground dry forest biomass and forest carbon. The four models include non-stratified and stratified versions of a multiple linear model where either biomass or (biomass)(exp 0.5) serves as the dependent variable. The use of different models in Quebec introduces differences in Provincial dry biomass estimates of up to 0.35 G, with a range of 4.94 +/- 0.28 Gt to 5.29 +/-0.36 Gt. The differences among model estimates are statistically non-significant, however, and the results demonstrate the degree to which carbon estimates vary strictly as a function of the model used to estimate regional biomass. Results also indicate that GLAS measurements become problematic with respect to height and biomass retrievals in the boreal forest when biomass values fall below 20 t/ha and when GLAS 75th percentile heights fall below 7 m.

Waveform LiDAR across forest biomass gradients

NASA Astrophysics Data System (ADS)

Montesano, P. M.; Nelson, R. F.; Dubayah, R.; Sun, G.; Ranson, J.

2011-12-01

Detailed information on the quantity and distribution of aboveground biomass (AGB) is needed to understand how it varies across space and changes over time. Waveform LiDAR data is routinely used to derive the heights of scattering elements in each illuminated footprint, and the vertical structure of vegetation is related to AGB. Changes in LiDAR waveforms across vegetation structure gradients can demonstrate instrument sensitivity to land cover transitions. A close examination of LiDAR waveforms in footprints across a forest gradient can provide new insight into the relationship of vegetation structure and forest AGB. In this study we use field measurements of individual trees within Laser Vegetation Imaging Sensor (LVIS) footprints along transects crossing forest to non-forest gradients to examine changes in LVIS waveform characteristics at sites with low (< 50Mg/ha) AGB. We relate field AGB measurements to original and adjusted LVIS waveforms to detect the forest AGB interval along a forest - non-forest transition in which the LVIS waveform lose the ability to discern differences in AGB. Our results help identify the lower end the forest biomass range that a ~20m footprint waveform LiDAR can detect, which can help infer accumulation of biomass after disturbances and during forest expansion, and which can guide the use of LiDAR within a multi-sensor fusion biomass mapping approach.

Integrating LIDAR and forest inventories to fill the trees outside forests data gap.

PubMed

Johnson, Kristofer D; Birdsey, Richard; Cole, Jason; Swatantran, Anu; O'Neil-Dunne, Jarlath; Dubayah, Ralph; Lister, Andrew

2015-10-01

Forest inventories are commonly used to estimate total tree biomass of forest land even though they are not traditionally designed to measure biomass of trees outside forests (TOF). The consequence may be an inaccurate representation of all of the aboveground biomass, which propagates error to the outputs of spatial and process models that rely on the inventory data. An ideal approach to fill this data gap would be to integrate TOF measurements within a traditional forest inventory for a parsimonious estimate of total tree biomass. In this study, Light Detection and Ranging (LIDAR) data were used to predict biomass of TOF in all "nonforest" Forest Inventory and Analysis (FIA) plots in the state of Maryland. To validate the LIDAR-based biomass predictions, a field crew was sent to measure TOF on nonforest plots in three Maryland counties, revealing close agreement at both the plot and county scales between the two estimates. Total tree biomass in Maryland increased by 25.5 Tg, or 15.6%, when biomass of TOF were included. In two counties (Carroll and Howard), there was a 47% increase. In contrast, counties located further away from the interstate highway corridor showed only a modest increase in biomass when TOF were added because nonforest conditions were less common in those areas. The advantage of this approach for estimating biomass of TOF is that it is compatible with, and explicitly separates TOF biomass from, forest biomass already measured by FIA crews. By predicting biomass of TOF at actual FIA plots, this approach is directly compatible with traditionally reported FIA forest biomass, providing a framework for other states to follow, and should improve carbon reporting and modeling activities in Maryland.

Forest biomass mapping from fusion of GEDI Lidar data and TanDEM-X InSAR data

NASA Astrophysics Data System (ADS)

Qi, W.; Hancock, S.; Armston, J.; Marselis, S.; Dubayah, R.

2017-12-01

Mapping forest above-ground biomass (hereafter biomass) can significantly improve our ability to assess the role of forest in terrestrial carbon budget and to analyze the ecosystem productivity. Global Ecosystem Dynamic Investigation (GEDI) mission will provide the most complete lidar observations of forest vertical structure and has the potential to provide global-scale forest biomass data at 1-km resolution. However, GEDI is intrinsically a sampling mission and will have a between-track spacing of 600 m. An increase in adjacent-swath distance and the presence of cloud cover may also lead to larger gaps between GEDI tracks. In order to provide wall-to-wall forest biomass maps, fusion algorithms of GEDI lidar data and TanDEM-X InSAR data were explored in this study. Relationship between biomass and lidar RH metrics was firstly developed and used to derive biomass values over GEDI tracks which were simulated using airborne lidar data. These GEDI biomass values were then averaged in each 1-km cell to represent the biomass density within that cell. Whereas for cells without any GEDI observations, regression models developed between GEDI-derived biomass and TDX InSAR variables were applied to predict biomass over those places. Based on these procedures, contiguous biomass maps were finally generated at 1-km resolution over three representative forest types. Uncertainties for these biomass maps were also estimated at 1 km following methods developed in Saarela et al. (2016). Our results indicated great potential of GEDI/TDX fusion for large-scale biomass mapping. Saarela, S., Holm, S., Grafstrom, A., Schnell, S., Naesset, E., Gregoire, T.G., Nelson, R.F., & Stahl, G. (2016). Hierarchical model-based inference for forest inventory utilizing three sources of information. Annals of Forest Science, 73, 895-910

Salinity influences on aboveground and belowground net primary productivity in tidal wetlands

USGS Publications Warehouse

Pierfelice, Kathryn N.; Graeme Lockaby, B.; Krauss, Ken W.; Conner, William H.; Noe, Gregory; Ricker, Matthew C.

2017-01-01

Tidal freshwater wetlands are one of the most vulnerable ecosystems to climate change and rising sea levels. However salinification within these systems is poorly understood, therefore, productivity (litterfall, woody biomass, and fine roots) were investigated on three forested tidal wetlands [(1) freshwater, (2) moderately saline, and (3) heavily salt-impacted] and a marsh along the Waccamaw and Turkey Creek in South Carolina. Mean aboveground (litterfall and woody biomass) production on the freshwater, moderately saline, heavily salt-impacted, and marsh, respectively, was 1,061, 492, 79, and 0  g m−2 year−1 versus belowground (fine roots) 860, 490, 620, and 2,128  g m−2 year−1. Litterfall and woody biomass displayed an inverse relationship with salinity. Shifts in productivity across saline sites is of concern because sea level is predicted to continue rising. Results from the research reported in this paper provide baseline data upon which coupled hydrologic/wetland models can be created to quantify future changes in tidal forest functions.

Climate-suitable planting as a strategy for maintaining forest productivity and functional diversity.

PubMed

Duveneck, Matthew J; Scheller, Robert M

2015-09-01

Within the time frame of the longevity of tree species, climate change will change faster than the ability of natural tree migration. Migration lags may result in reduced productivity and reduced diversity in forests under current management and climate change. We evaluated the efficacy of planting climate-suitable tree species (CSP), those tree species with current or historic distributions immediately south of a focal landscape, to maintain or increase aboveground biomass productivity, and species and functional diversity. We modeled forest change with the LANDIS-II forest simulation model for 100 years (2000-2100) at a 2-ha cell resolution and five-year time steps within two landscapes in the Great Lakes region (northeastern Minnesota and northern lower Michigan, USA). We compared current climate to low- and high-emission futures. We simulated a low-emission climate future with the Intergovernmental Panel on Climate Change (IPCC) 2007 B1 emission scenario and the Parallel Climate Model Global Circulation Model (GCM). We simulated a high-emission climate future with the IPCC A1FI emission scenario and the Geophysical Fluid Dynamics Laboratory (GFDL) GCM. We compared current forest management practices (business-as-usual) to CSP management. In the CSP scenario, we simulated a target planting of 5.28% and 4.97% of forested area per five-year time step in the Minnesota and Michigan landscapes, respectively. We found that simulated CSP species successfully established in both landscapes under all climate scenarios. The presence of CSP species generally increased simulated aboveground biomass. Species diversity increased due to CSP; however, the effect on functional diversity was variable. Because the planted species were functionally similar to many native species, CSP did not result in a consistent increase nor decrease in functional diversity. These results provide an assessment of the potential efficacy and limitations of CSP management. These results have management implications for sites where diversity and productivity are expected to decline. Future efforts to restore a specific species or forest type may not be possible, but CSP may sustain a more general ecosystem service (e.g., aboveground biomass).

Growth responses of trees and understory plants to nitrogen fertilization in a subtropical forest in China

NASA Astrophysics Data System (ADS)

Tian, Di; Li, Peng; Fang, Wenjing; Xu, Jun; Luo, Yongkai; Yan, Zhengbing; Zhu, Biao; Wang, Jingjing; Xu, Xiaoniu; Fang, Jingyun

2017-07-01

Reactive nitrogen (N) increase in the biosphere has been a noteworthy aspect of global change, producing considerable ecological effects on the functioning and dynamics of the terrestrial ecosystems. A number of observational studies have explored responses of plants to experimentally simulated N enrichment in boreal and temperate forests. Here we investigate how the dominant trees and different understory plants respond to experimental N enrichment in a subtropical forest in China. We conducted a 3.4-year N fertilization experiment in an old-aged subtropical evergreen broad-leaved forest in eastern China with three treatment levels applied to nine 20 m × 20 m plots and replicated in three blocks. We divided the plants into trees, saplings, shrubs (including tree seedlings), and ground-cover plants (ferns) according to the growth forms, and then measured the absolute and relative basal area increments of trees and saplings and the aboveground biomass of understory shrubs and ferns. We further grouped individuals of the dominant tree species, Castanopsis eyrei, into three size classes to investigate their respective growth responses to the N fertilization. Our results showed that the plot-averaged absolute and relative growth rates of basal area and aboveground biomass of trees were not affected by N fertilization. Across the individuals of C. eyrei, the small trees with a DBH (diameter at breast height) of 5-10 cm declined by 66.4 and 59.5 %, respectively, in N50 (50 kg N ha-1 yr-1) and N100 fertilized plots (100 kg N ha-1 yr-1), while the growth of median and large trees with a DBH of > 10 cm did not significantly change with the N fertilization. The growth rate of small trees, saplings, and the aboveground biomass of understory shrubs and ground-cover ferns decreased significantly in the N-fertilized plots. Our findings suggested that N might not be a limiting nutrient in this mature subtropical forest, and that the limitation of other nutrients in the forest ecosystem might be aggravated by the enhanced N availability, potentially resulting in an adverse effect on the development of natural subtropical forest.

Long-term patterns in tropical reforestation: plant community composition and aboveground biomass accumulation.

Treesearch

E. Mar¡n-Spiotta; R. Ostertag; Silver W. L.

2007-01-01

Primary tropical forests are renowned for their high biodiversity and carbon storage, and considerable research has documented both species and carbon losses with deforestation and agricultural land uses. Economic drivers are now leading to the abandonment of agricultural lands, and the area in secondary forests is increasing. We know little about how long it takes for...

Long-term, patterns in tropical reforestation: plant community composition and aboveground biomass accumulation.

Treesearch

E. MARIN-SPIOTTA; R. OSTERTAG; SILVER W. L.

2007-01-01

Primary tropical forests are renowned for their high biodiversity and carbon storage, and considerable research has documented both species and carbon losses with deforestation and agricultural land uses. Economic drivers are now leading to the abandonment of agricultural lands, and the area in secondary forests is increasing. We know little about how long it takes for...

Acidic deposition and sustainable forest management in the central Appalachians, USA

Treesearch

Mary Beth Adams

1999-01-01

Long-term productivity of mixed-species forests in the central Appalachian region of the United States may be threatened by changes in base cation availability of the soil. These changes may be due to increased intensity of harvest removals and a shift toward shorter rotations that result in increased removal of calcium and magnesium in aboveground biomass, and through...

Modeling water yield response to forest cover changes in northern Minnesota

Treesearch

S.C. Bernath; E.S. Verry; K.N. Brooks; P.F. Ffolliott

1982-01-01

A water yield model (TIMWAT) has been developed to predict changes in water yield following changes in forest cover in northern Minnesota. Two versions of the model exist; one predicts changes in water yield as a function of gross precipitation and time after clearcutting. The second version predicts changes in water yield due to changes in above-ground biomass...

Estimates of biomass in logging residue and standing residual inventory following tree-harvest activity on timberland acres in the southern region

Treesearch

Roger C. Conner; Tony G. Johnson

2011-01-01

This report provides estimates of biomass (green tons) in logging residue and standing residual inventory on timberland acres with evidence of tree cutting. Biomass as defined by Forest Inventory and Analysis is the aboveground dry weight of wood in the bole and limbs of live trees ≥ 1-inch diameter at breast height (d.b.h.), and excludes tree foliage, seedlings, and...

Allometric biomass equations for 12 tree species in coniferous and broadleaved mixed forests, Northeastern China.

PubMed

He, Huaijiang; Zhang, Chunyu; Zhao, Xiuhai; Fousseni, Folega; Wang, Jinsong; Dai, Haijun; Yang, Song; Zuo, Qiang

2018-01-01

Understanding forest carbon budget and dynamics for sustainable resource management and ecosystem functions requires quantification of above- and below-ground biomass at individual tree species and stand levels. In this study, a total of 122 trees (9-12 per species) were destructively sampled to determine above- and below-ground biomass of 12 tree species (Acer mandshuricum, Acer mono, Betula platyphylla, Carpinus cordata, Fraxinus mandshurica, Juglans mandshurica, Maackia amurensis, P. koraiensis, Populus ussuriensis, Quercus mongolica, Tilia amurensis and Ulmus japonica) in coniferous and broadleaved mixed forests of Northeastern China, an area of the largest natural forest in the country. Biomass allocation was examined and biomass models were developed using diameter as independent variable for individual tree species and all species combined. The results showed that the largest biomass allocation of all species combined was on stems (57.1%), followed by coarse root (21.3%), branch (18.7%), and foliage (2.9%). The log-transformed model was statistically significant for all biomass components, although predicting power was higher for species-specific models than for all species combined, general biomass models, and higher for stems, roots, above-ground biomass, and total tree biomass than for branch and foliage biomass. These findings supplement the previous studies on this forest type by additional sample trees, species and locations, and support biomass research on forest carbon budget and dynamics by management activities such as thinning and harvesting in the northeastern part of China.

Allometric biomass equations for 12 tree species in coniferous and broadleaved mixed forests, Northeastern China

PubMed Central

He, Huaijiang; Zhao, Xiuhai; Fousseni, Folega; Wang, Jinsong; Dai, Haijun; Yang, Song; Zuo, Qiang

2018-01-01

Understanding forest carbon budget and dynamics for sustainable resource management and ecosystem functions requires quantification of above- and below-ground biomass at individual tree species and stand levels. In this study, a total of 122 trees (9–12 per species) were destructively sampled to determine above- and below-ground biomass of 12 tree species (Acer mandshuricum, Acer mono, Betula platyphylla, Carpinus cordata, Fraxinus mandshurica, Juglans mandshurica, Maackia amurensis, P. koraiensis, Populus ussuriensis, Quercus mongolica, Tilia amurensis and Ulmus japonica) in coniferous and broadleaved mixed forests of Northeastern China, an area of the largest natural forest in the country. Biomass allocation was examined and biomass models were developed using diameter as independent variable for individual tree species and all species combined. The results showed that the largest biomass allocation of all species combined was on stems (57.1%), followed by coarse root (21.3%), branch (18.7%), and foliage (2.9%). The log-transformed model was statistically significant for all biomass components, although predicting power was higher for species-specific models than for all species combined, general biomass models, and higher for stems, roots, above-ground biomass, and total tree biomass than for branch and foliage biomass. These findings supplement the previous studies on this forest type by additional sample trees, species and locations, and support biomass research on forest carbon budget and dynamics by management activities such as thinning and harvesting in the northeastern part of China. PMID:29351291

Hyperspectral sensing of forests

NASA Astrophysics Data System (ADS)

Goodenough, David G.; Dyk, Andrew; Chen, Hao; Hobart, Geordie; Niemann, K. Olaf; Richardson, Ash

2007-11-01

Canada contains 10% of the world's forests covering an area of 418 million hectares. The sustainable management of these forest resources has become increasingly complex. Hyperspectral remote sensing can provide a wealth of new and improved information products to resource managers to make more informed decisions. Research in this area has demonstrated that hyperspectral remote sensing can be used to create more accurate products for forest inventory, forest health, foliar biochemistry, biomass, and aboveground carbon than are currently available. This paper surveys recent methods and results in hyperspectral sensing of forests and describes space initiatives for hyperspectral sensing.

Testing the sensitivity of terrestrial carbon models using remotely sensed biomass estimates

NASA Astrophysics Data System (ADS)

Hashimoto, H.; Saatchi, S. S.; Meyer, V.; Milesi, C.; Wang, W.; Ganguly, S.; Zhang, G.; Nemani, R. R.

2010-12-01

There is a large uncertainty in carbon allocation and biomass accumulation in forest ecosystems. With the recent availability of remotely sensed biomass estimates, we now can test some of the hypotheses commonly implemented in various ecosystem models. We used biomass estimates derived by integrating MODIS, GLAS and PALSAR data to verify above-ground biomass estimates simulated by a number of ecosystem models (CASA, BIOME-BGC, BEAMS, LPJ). This study extends the hierarchical framework (Wang et al., 2010) for diagnosing ecosystem models by incorporating independent estimates of biomass for testing and calibrating respiration, carbon allocation, turn-over algorithms or parameters.

Spaceborne SAR Data for Aboveground-Biomass Retrieval of Indian Tropical Forests

NASA Astrophysics Data System (ADS)

Khati, U.; Singh, G.; Musthafa, M.

2017-12-01

Forests are important and indispensable part of the terrestrial ecosystems, and have a direct impact on the global carbon cycle. Forest biophysical parameters such as forest stand height and forest above-ground biomass (AGB) are forest health indicators. Measuring the forest biomass using traditional ground survey techniques are man-power consuming and have very low spatial coverage. Satellite based remote sensing techniques provide synoptic view of the earth with continuous measurements over large, inaccessible forest regions. Satellite Synthetic Aperture Radar (SAR) data has been shown to be sensitive to these forest bio-physical parameters and have been extensively utilized over boreal and tropical forests. However, there are limited studies over Indian tropical forests due to lack of auxiliary airborne data and difficulties in manual in situ data collection. In this research work we utilize spaceborne data from TerraSAR-X/TanDEM-X and ALOS-2/PALSAR-2 and implement both Polarimetric SAR and PolInSAR techniques for retrieval of AGB of a managed tropical forest in India. The TerraSAR-X/TanDEM-X provide a single-baseline PolInSAR data robust to temporal decorrelation. This would be used to accurately estimate the forest stand height. The retrieved height would be an input parameter for modelling AGB using the L-band ALOS-2/PALSAR-2 data. The IWCM model is extensively utilized to estimate AGB from SAR observations. In this research we utilize the six component scattering power decomposition (6SD) parameters and modify the IWCM based technique for a better retrieval of forest AGB. PolInSAR data shows a high estimation accuracy with r2 of 0.8 and a RMSE of 2 m. With this accurate height provided as input to the modified model along with 6SD parameters shows promising results. The results are validated with extensive field based measurements, and are further analysed in detail.

The influence of fire on the radiocarbon signature and character of soil organic matter in the Siskiyou national forest, Oregon, USA

Treesearch

Katherine Heckman; John L. Campbell; Heath Powers; Beverly E. Law; Chris Swanston

2013-01-01

Forest fires contribute a significant amount of CO2 to the atmosphere each year, and CO2 emissions from fires are likely to increase under projected conditions of global climate change. In addition to volatilizing aboveground biomass and litter layers, forest fires have a profound effect on belowground carbon (C) pools and the cycling of soil organic matter as a whole...

Forest Aboveground Biomass Mapping and Canopy Cover Estimation from Simulated ICESat-2 Data

NASA Astrophysics Data System (ADS)

Narine, L.; Popescu, S. C.; Neuenschwander, A. L.

2017-12-01

The assessment of forest aboveground biomass (AGB) can contribute to reducing uncertainties associated with the amount and distribution of terrestrial carbon. With a planned launch date of July 2018, the Ice, Cloud and Land Elevation Satellite-2 (ICESat-2) will provide data which will offer the possibility of mapping AGB at global scales. In this study, we develop approaches for utilizing vegetation data that will be delivered in ICESat-2's land-vegetation along track product (ATL08). The specific objectives are to: (1) simulate ICESat-2 photon-counting lidar (PCL) data using airborne lidar data, (2) utilize simulated PCL data to estimate forest canopy cover and AGB and, (3) upscale AGB predictions to create a wall-to-wall AGB map at 30-m spatial resolution. Using existing airborne lidar data for Sam Houston National Forest (SHNF) located in southeastern Texas and known ICESat-2 beam locations, PCL data are simulated from discrete return lidar points. We use multiple linear regression models to relate simulated PCL metrics for 100 m segments along the ICESat-2 ground tracks to AGB from a biomass map developed using airborne lidar data and canopy cover calculated from the same. Random Forest is then used to create an AGB map from predicted estimates and explanatory data consisting of spectral metrics derived from Landsat TM imagery and land cover data from the National Land Cover Database (NLCD). Findings from this study will demonstrate how data that will be acquired by ICESat-2 can be used to estimate forest structure and characterize the spatial distribution of AGB.

Five-year vegetation control effects on aboveground biomass and nitrogen content and allocation in Douglas-fir plantations on three contrasting sites

Treesearch

Warren D. Devine; Timothy B. Harrington; Thomas A. Terry; Robert B. Harrison; Robert A. Slesak; David H. Peter; Constance A. Harrington; Carol J. Shilling; Stephen H. Schoenholtz

2011-01-01

Despite widespread use of intensive vegetation control (VC) in forest management, the effects of VC on allocation of biomass and nutrients between young trees and competing vegetation are not well understood. On three Pacific Northwest sites differing in productivity, soil parent material, and understory vegetation community, we evaluated year-5 effects of presence/...

Examining effective use of data sources and modeling algorithms for improving biomass estimation in a moist tropical forest of the Brazilian Amazon

Treesearch

Yunyun Feng; Dengsheng Lu; Qi Chen; Michael Keller; Emilio Moran; Maiza Nara dos-Santos; Edson Luis Bolfe; Mateus Batistella

2017-01-01

Previous research has explored the potential to integrate lidar and optical data in aboveground biomass (AGB) estimation, but how different data sources, vegetation types, and modeling algorithms influence AGB estimation is poorly understood. This research conducts a comparative analysis of different data sources and modeling approaches in improving AGB estimation....

Ability of LANDSAT-8 Oli Derived Texture Metrics in Estimating Aboveground Carbon Stocks of Coppice Oak Forests

NASA Astrophysics Data System (ADS)

Safari, A.; Sohrabi, H.

2016-06-01

The role of forests as a reservoir for carbon has prompted the need for timely and reliable estimation of aboveground carbon stocks. Since measurement of aboveground carbon stocks of forests is a destructive, costly and time-consuming activity, aerial and satellite remote sensing techniques have gained many attentions in this field. Despite the fact that using aerial data for predicting aboveground carbon stocks has been proved as a highly accurate method, there are challenges related to high acquisition costs, small area coverage, and limited availability of these data. These challenges are more critical for non-commercial forests located in low-income countries. Landsat program provides repetitive acquisition of high-resolution multispectral data, which are freely available. The aim of this study was to assess the potential of multispectral Landsat 8 Operational Land Imager (OLI) derived texture metrics in quantifying aboveground carbon stocks of coppice Oak forests in Zagros Mountains, Iran. We used four different window sizes (3×3, 5×5, 7×7, and 9×9), and four different offsets ([0,1], [1,1], [1,0], and [1,-1]) to derive nine texture metrics (angular second moment, contrast, correlation, dissimilar, entropy, homogeneity, inverse difference, mean, and variance) from four bands (blue, green, red, and infrared). Totally, 124 sample plots in two different forests were measured and carbon was calculated using species-specific allometric models. Stepwise regression analysis was applied to estimate biomass from derived metrics. Results showed that, in general, larger size of window for deriving texture metrics resulted models with better fitting parameters. In addition, the correlation of the spectral bands for deriving texture metrics in regression models was ranked as b4>b3>b2>b5. The best offset was [1,-1]. Amongst the different metrics, mean and entropy were entered in most of the regression models. Overall, different models based on derived texture metrics were able to explain about half of the variation in aboveground carbon stocks. These results demonstrated that Landsat 8 derived texture metrics can be applied for mapping aboveground carbon stocks of coppice Oak Forests in large areas.

A simple method for estimating gross carbon budgets for vegetation in forest ecosystems.

PubMed

Ryan, Michael G.

1991-01-01

Gross carbon budgets for vegetation in forest ecosystems are difficult to construct because of problems in scaling flux measurements made on small samples over short periods of time and in determining belowground carbon allocation. Recently, empirical relationships have been developed to estimate total belowground carbon allocation from litterfall, and maintenance respiration from tissue nitrogen content. I outline a method for estimating gross carbon budgets using these empirical relationships together with data readily available from ecosystem studies (aboveground wood and canopy production, aboveground wood and canopy biomass, litterfall, and tissue nitrogen contents). Estimates generated with this method are compared with annual carbon fixation estimates from the Forest-BGC model for a lodgepole pine (Pinus contorta Dougl.) and a Pacific silver fir (Abies amabilis Dougl.) chronosequence.

The importance of forest structure for carbon fluxes of the Amazon rainforest

NASA Astrophysics Data System (ADS)

Rödig, Edna; Cuntz, Matthias; Rammig, Anja; Fischer, Rico; Taubert, Franziska; Huth, Andreas

2018-05-01

Precise descriptions of forest productivity, biomass, and structure are essential for understanding ecosystem responses to climatic and anthropogenic changes. However, relations between these components are complex, in particular for tropical forests. We developed an approach to simulate carbon dynamics in the Amazon rainforest including around 410 billion individual trees within 7.8 million km2. We integrated canopy height observations from space-borne LIDAR in order to quantify spatial variations in forest state and structure reflecting small-scale to large-scale natural and anthropogenic disturbances. Under current conditions, we identified the Amazon rainforest as a carbon sink, gaining 0.56 GtC per year. This carbon sink is driven by an estimated mean gross primary productivity (GPP) of 25.1 tC ha‑1 a‑1, and a mean woody aboveground net primary productivity (wANPP) of 4.2 tC ha‑1 a‑1. We found that successional states play an important role for the relations between productivity and biomass. Forests in early to intermediate successional states are the most productive, and woody above-ground carbon use efficiencies are non-linear. Simulated values can be compared to observed carbon fluxes at various spatial resolutions (>40 m). Notably, we found that our GPP corresponds to the values derived from MODIS. For NPP, spatial differences can be observed due to the consideration of forest successional states in our approach. We conclude that forest structure has a substantial impact on productivity and biomass. It is an essential factor that should be taken into account when estimating current carbon budgets or analyzing climate change scenarios for the Amazon rainforest.

Quantifying Fire's Impacts on Total and Pyrogenic Carbon Stocks in Mixed-Conifer Forests: Results from Pre- and Post-Fire Measurements in Active Wildfire Incidents

NASA Astrophysics Data System (ADS)

Miesel, J. R.; Reiner, A. L.; Ewell, C. M.; Sanderman, J.; Maestrini, B.; Adkins, J.

2016-12-01

Widespread US fire suppression policy has contributed to an accumulation of vegetation in many western forests relative to historic conditions, and these changes can exacerbate wildfire severity and carbon (C) emissions. Serious concern exists about positive feedbacks between wildfire emissions and global climate; however, fires not only release C from terrestrial to atmospheric pools, they also create "black" or pyrogenic C (PyC) which contributes to longer-term C stability. Our objective was to quantify wildfire impacts on aboveground and belowground total C and PyC stocks in California mixed-conifer forests. We worked with incident management teams to access five active wildfires to establish and measure plots within days before and after fire. We measured pre- and post-fire aboveground forest structure and woody fuels to calculate aboveground biomass, biomass C, and PyC, and we collected pre- and post-fire forest floor and 0-5 cm mineral soil samples to measure belowground C and PyC stocks. Our preliminary results show that fire had minimal impact on the number of trees per hectare, whereas C losses from the tree layer occurred via consumption of foliage, and PyC gain occurred in tree bark. Fire released 54% to 100% of surface fuel C. In the forest floor layer, we observed 33 to 100% C loss, whereas changes in PyC stocks ranged from 100% loss to 186% gain relative to pre-fire samples. In general, fire had minimal to no impact on 0-5 cm mineral soil C. We will present relationships between total C, PyC and post-fire C and N dynamics in one of the five wildfire sites. Our data are unique because they represent nearly immediate pre- and post-fire measurements in major wildfires in a widespread western U.S. forest type. This research advances understanding of the role of fire on forest C fluxes and C sequestration potential as PyC.

Towards Linking 3D SAR and Lidar Models with a Spatially Explicit Individual Based Forest Model

NASA Astrophysics Data System (ADS)

Osmanoglu, B.; Ranson, J.; Sun, G.; Armstrong, A. H.; Fischer, R.; Huth, A.

2017-12-01

In this study, we present a parameterization of the FORMIND individual-based gap model (IBGM)for old growth Atlantic lowland rainforest in La Selva, Costa Rica for the purpose of informing multisensor remote sensing techniques for above ground biomass techniques. The model was successfully parameterized and calibrated for the study site; results show that the simulated forest reproduces the structural complexity of Costa Rican rainforest based on comparisons with CARBONO inventory plot data. Though the simulated stem numbers (378) slightly underestimated the plot data (418), particularly for canopy dominant intermediate shade tolerant trees and shade tolerant understory trees, overall there was a 9.7% difference. Aboveground biomass (kg/ha) showed a 0.1% difference between the simulated forest and inventory plot dataset. The Costa Rica FORMIND simulation was then used to parameterize a spatially explicit (3D) SAR and lidar backscatter models. The simulated forest stands were used to generate a Look Up Table as a tractable means to estimate aboveground forest biomass for these complex forests. Various combinations of lidar and radar variables were evaluated in the LUT inversion. To test the capability of future data for estimation of forest height and biomass, we considered data of 1) L- (or P-) band polarimetric data (backscattering coefficients of HH, HV and VV); 2) L-band dual-pol repeat-pass InSAR data (HH/HV backscattering coefficients and coherences, height of scattering phase center at HH and HV using DEM or surface height from lidar data as reference); 3) P-band polarimetric InSAR data (canopy height from inversion of PolInSAR data or use the coherences and height of scattering phase center at HH, HV and VV); 4) various height indices from waveform lidar data); and 5) surface and canopy top height from photon-counting lidar data. The methods for parameterizing the remote sensing models with the IBGM and developing Look Up Tables will be discussed. Results from various remote sensing scenarios will also be presented.

Evaluating the utility of the medium-spatial resolution Landsat 8 multispectral sensor in quantifying aboveground biomass in uMgeni catchment, South Africa

NASA Astrophysics Data System (ADS)

Dube, Timothy; Mutanga, Onisimo

2015-03-01

Aboveground biomass estimation is critical in understanding forest contribution to regional carbon cycles. Despite the successful application of high spatial and spectral resolution sensors in aboveground biomass (AGB) estimation, there are challenges related to high acquisition costs, small area coverage, multicollinearity and limited availability. These challenges hamper the successful regional scale AGB quantification. The aim of this study was to assess the utility of the newly-launched medium-resolution multispectral Landsat 8 Operational Land Imager (OLI) dataset with a large swath width, in quantifying AGB in a forest plantation. We applied different sets of spectral analysis (test I: spectral bands; test II: spectral vegetation indices and test III: spectral bands + spectral vegetation indices) in testing the utility of Landsat 8 OLI using two non-parametric algorithms: stochastic gradient boosting and the random forest ensembles. The results of the study show that the medium-resolution multispectral Landsat 8 OLI dataset provides better AGB estimates for Eucalyptus dunii, Eucalyptus grandis and Pinus taeda especially when using the extracted spectral information together with the derived spectral vegetation indices. We also noted that incorporating the optimal subset of the most important selected medium-resolution multispectral Landsat 8 OLI bands improved AGB accuracies. We compared medium-resolution multispectral Landsat 8 OLI AGB estimates with Landsat 7 ETM + estimates and the latter yielded lower estimation accuracies. Overall, this study demonstrates the invaluable potential and strength of applying the relatively affordable and readily available newly-launched medium-resolution Landsat 8 OLI dataset, with a large swath width (185-km) in precisely estimating AGB. This strength of the Landsat OLI dataset is crucial especially in sub-Saharan Africa where high-resolution remote sensing data availability remains a challenge.

Forest dynamics in the temperate rainforests of Alaska: from individual tree to regional scales

Treesearch

Tara M. Barrett

2015-01-01

Analysis of remeasurement data from 1079 Forest Inventory and Analysis (FIA) plots revealed multi-scale change occurring in the temperate rainforests of southeast Alaska. In the western half of the region, including Prince William Sound, aboveground live tree biomass and carbon are increasing at a rate of 8 ( ± 2 ) percent per decade, driven by an increase in Sitka...

Extensive Sampling of Forest Carbon using High Density Power Line Lidar

NASA Astrophysics Data System (ADS)

Hampton, H. M.; Chen, Q.; Dye, D. G.; Hungate, B. A.

2013-12-01

Estimating carbon sequestration and greenhouse gas emissions from forest management, natural processes, and disturbance is of growing interest for mitigating global warming. Ponderosa pine is common at mid-elevations throughout the western United States and is a dominant tree species in southwestern forests. Existing unmanaged "relict" sites and stand reconstructions of southwestern ponderosa pine forests from before European settlement (late 1800s) provide evidence of forests of larger trees of lower density and less vulnerability to severe fires than today's typical conditions of high densities of small trees that have resulted from a century of fire suppression. Forest treatments to improve forest health in the region include tree cutting focused on small-diameter trees (thinning), low-intensity prescribed burning, and monitoring rather than suppressing wildfires. Stimulated by several uncharacteristically-intense fires in the last decade, a collaborative process found strong stakeholder agreement to accelerate forest treatments to reduce fire risk and restore ecological conditions. Land use planning to ramp up management is underway and could benefit from quick and inexpensive techniques to inventory tree-level carbon because existing inventory data are not adequate to capture the range of forest structural conditions. Our approach overcomes these shortcomings by employing recent breakthroughs in estimating aboveground biomass from high resolution light detection and ranging (lidar) remote sensing. Lidar is an active remote sensing technique, analogous to radar, which measures the time required for a transmitted pulse of laser light to return to the sensor after reflection from a target. Lidar data can capture 3-dimensional forest structure with greater detail and broader spatial coverage than is feasible with conventional field measurements. We developed a novel methodology for extensive sampling and field validation of forest carbon, applicable to managed and unmanaged areas, using high point density lidar collected over transmission line corridors. The lidar metric of quadratic mean height guided our selection of field plots spanning the full range from low to high levels of aboveground biomass across the study region. Before model selection, we minimized two of the major sources of errors in lidar calibration: variance in tree allometry across landscapes and plot edge effects (spatial mismatch between field measurements and lidar points). We tested an assortment of model selection techniques and goodness of fit measures for deriving forest structural metrics of interest. For example, we obtained an R-squared value for aboveground biomass (Mg/ha) of 0.9 using stepwise regression. The forest metrics obtained are being used in the next stage of the project to parameterize biogeochemical models linking terrestrial carbon pools and atmospheric greenhouse gas exchanges.

[Structural recovering in Andean successional forests from Porce (Antioquia, Colombia)].

PubMed

Yepes, Adriana P; del Valle, Jorge I; Jaramillo, Sandra L; Orrego, Sergio A

2010-03-01

Places subjected to natural or human disturbance can recover forest through an ecological process called secondary succession. Tropical succession is affected by factors such as disturbances, distance from original forest, surface configuration and local climate. These factors determine the composition of species and the time trend of the succession itself. We studied succession in soils used for cattle ranching over various decades in the Porce Region of Colombia (Andean Colombian forests). A set of twenty five permanent plots was measured, including nine plots (20 x 50 m) in primary forests and sixteen (20 x 25 m) in secondary forests. All trees with diameter > or =1.0 cm were measured. We analyzed stem density, basal area, above-ground biomass and species richness, in a successional process of ca. 43 years, and in primary forests. The secondary forests' age was estimated in previous studies, using radiocarbon dating, aerial photographs and a high-resolution satellite image analysis (7 to >43 years). In total, 1,143 and 1,766 stems were measured in primary and secondary forests, respectively. Basal area (5.7 to 85.4 m2 ha(-1)), above-ground biomass (19.1 to 1,011.5 t ha(-1)) and species richness (4 to 69) directly increased with site age, while steam density decreased (3,180 to 590). Diametric distributions were "J-inverted" for primary forests and even-aged size-class structures for secondary forests. Three species of palms were abundant and exclusive in old secondary forests and primary forests: Oenocarpus mapora, Euterpe precatoria and Oenocarpus bataua. These palms happened in cohorts after forest disturbances. Secondary forest structure was 40% in more than 43 years of forest succession and indicate that many factors are interacting and affecting the forests succession in the area (e.g. agriculture, cattle ranching, mining, etc.).

Wildfires in bamboo-dominated Amazonian forest: impacts on above-ground biomass and biodiversity.

PubMed

Barlow, Jos; Silveira, Juliana M; Mestre, Luiz A M; Andrade, Rafael B; Camacho D'Andrea, Gabriela; Louzada, Julio; Vaz-de-Mello, Fernando Z; Numata, Izaya; Lacau, Sébastien; Cochrane, Mark A

2012-01-01

Fire has become an increasingly important disturbance event in south-western Amazonia. We conducted the first assessment of the ecological impacts of these wildfires in 2008, sampling forest structure and biodiversity along twelve 500 m transects in the Chico Mendes Extractive Reserve, Acre, Brazil. Six transects were placed in unburned forests and six were in forests that burned during a series of forest fires that occurred from August to October 2005. Normalized Burn Ratio (NBR) calculations, based on Landsat reflectance data, indicate that all transects were similar prior to the fires. We sampled understorey and canopy vegetation, birds using both mist nets and point counts, coprophagous dung beetles and the leaf-litter ant fauna. Fire had limited influence upon either faunal or floral species richness or community structure responses, and stems <10 cm DBH were the only group to show highly significant (p = 0.001) community turnover in burned forests. Mean aboveground live biomass was statistically indistinguishable in the unburned and burned plots, although there was a significant increase in the total abundance of dead stems in burned plots. Comparisons with previous studies suggest that wildfires had much less effect upon forest structure and biodiversity in these south-western Amazonian forests than in central and eastern Amazonia, where most fire research has been undertaken to date. We discuss potential reasons for the apparent greater resilience of our study plots to wildfire, examining the role of fire intensity, bamboo dominance, background rates of disturbance, landscape and soil conditions.

Wildfires in Bamboo-Dominated Amazonian Forest: Impacts on Above-Ground Biomass and Biodiversity

PubMed Central

Barlow, Jos; Silveira, Juliana M.; Mestre, Luiz A. M.; Andrade, Rafael B.; Camacho D'Andrea, Gabriela; Louzada, Julio; Vaz-de-Mello, Fernando Z.; Numata, Izaya; Lacau, Sébastien; Cochrane, Mark A.

2012-01-01

Fire has become an increasingly important disturbance event in south-western Amazonia. We conducted the first assessment of the ecological impacts of these wildfires in 2008, sampling forest structure and biodiversity along twelve 500 m transects in the Chico Mendes Extractive Reserve, Acre, Brazil. Six transects were placed in unburned forests and six were in forests that burned during a series of forest fires that occurred from August to October 2005. Normalized Burn Ratio (NBR) calculations, based on Landsat reflectance data, indicate that all transects were similar prior to the fires. We sampled understorey and canopy vegetation, birds using both mist nets and point counts, coprophagous dung beetles and the leaf-litter ant fauna. Fire had limited influence upon either faunal or floral species richness or community structure responses, and stems <10 cm DBH were the only group to show highly significant (p = 0.001) community turnover in burned forests. Mean aboveground live biomass was statistically indistinguishable in the unburned and burned plots, although there was a significant increase in the total abundance of dead stems in burned plots. Comparisons with previous studies suggest that wildfires had much less effect upon forest structure and biodiversity in these south-western Amazonian forests than in central and eastern Amazonia, where most fire research has been undertaken to date. We discuss potential reasons for the apparent greater resilience of our study plots to wildfire, examining the role of fire intensity, bamboo dominance, background rates of disturbance, landscape and soil conditions. PMID:22428035

Timber volume and aboveground live tree biomass estimations for landscape analyses in the Pacific Northwest

Treesearch

Xiaoping Zhou; Miles A. Hemstrom

2010-01-01

Timber availability, aboveground tree biomass, and changes in aboveground carbon pools are important consequences of landscape management. There are several models available for calculating tree volume and aboveground tree biomass pools. This paper documents species-specific regional equations for tree volume and aboveground live tree biomass estimation that might be...

Deadwood stocks increase with selective logging and large tree frequency in Gabon.

PubMed

Carlson, Ben S; Koerner, Sally E; Medjibe, Vincent P; White, Lee J T; Poulsen, John R

2017-04-01

Deadwood is a major component of aboveground biomass (AGB) in tropical forests and is important as habitat and for nutrient cycling and carbon storage. With deforestation and degradation taking place throughout the tropics, improved understanding of the magnitude and spatial variation in deadwood is vital for the development of regional and global carbon budgets. However, this potentially important carbon pool is poorly quantified in Afrotropical forests and the regional drivers of deadwood stocks are unknown. In the first large-scale study of deadwood in Central Africa, we quantified stocks in 47 forest sites across Gabon and evaluated the effects of disturbance (logging), forest structure variables (live AGB, wood density, abundance of large trees), and abiotic variables (temperature, precipitation, seasonality). Average deadwood stocks (measured as necromass, the biomass of deadwood) were 65 Mg ha -1 or 23% of live AGB. Deadwood stocks varied spatially with disturbance and forest structure, but not abiotic variables. Deadwood stocks increased significantly with logging (+38 Mg ha -1 ) and the abundance of large trees (+2.4 Mg ha -1 for every tree >60 cm dbh). Gabon holds 0.74 Pg C, or 21% of total aboveground carbon in deadwood, a threefold increase over previous estimates. Importantly, deadwood densities in Gabon are comparable to those in the Neotropics and respond similarly to logging, but represent a lower proportion of live AGB (median of 18% in Gabon compared to 26% in the Neotropics). In forest carbon accounting, necromass is often assumed to be a constant proportion (9%) of biomass, but in humid tropical forests this ratio varies from 2% in undisturbed forest to 300% in logged forest. Because logging significantly increases the deadwood carbon pool, estimates of tropical forest carbon should at a minimum use different ratios for logged (mean of 30%) and unlogged forests (mean of 18%). © 2016 John Wiley & Sons Ltd.

Assessing evidence for a pervasive alteration in tropical tree communities.

PubMed

Chave, Jérôme; Condit, Richard; Muller-Landau, Helene C; Thomas, Sean C; Ashton, Peter S; Bunyavejchewin, Sarayudh; Co, Leonardo L; Dattaraja, Handanakere S; Davies, Stuart J; Esufali, Shameema; Ewango, Corneille E N; Feeley, Kenneth J; Foster, Robin B; Gunatilleke, Nimal; Gunatilleke, Savitri; Hall, Pamela; Hart, Terese B; Hernández, Consuelo; Hubbell, Stephen P; Itoh, Akira; Kiratiprayoon, Somboon; Lafrankie, James V; Loo de Lao, Suzanne; Makana, Jean-Rémy; Noor, Md Nur Supardi; Kassim, Abdul Rahman; Samper, Cristián; Sukumar, Raman; Suresh, Hebbalalu S; Tan, Sylvester; Thompson, Jill; Tongco, Ma Dolores C; Valencia, Renato; Vallejo, Martha; Villa, Gorky; Yamakura, Takuo; Zimmerman, Jess K; Losos, Elizabeth C

2008-03-04

In Amazonian tropical forests, recent studies have reported increases in aboveground biomass and in primary productivity, as well as shifts in plant species composition favouring fast-growing species over slow-growing ones. This pervasive alteration of mature tropical forests was attributed to global environmental change, such as an increase in atmospheric CO2 concentration, nutrient deposition, temperature, drought frequency, and/or irradiance. We used standardized, repeated measurements of over 2 million trees in ten large (16-52 ha each) forest plots on three continents to evaluate the generality of these findings across tropical forests. Aboveground biomass increased at seven of our ten plots, significantly so at four plots, and showed a large decrease at a single plot. Carbon accumulation pooled across sites was significant (+0.24 MgC ha(-1) y(-1), 95% confidence intervals [0.07, 0.39] MgC ha(-1) y(-1)), but lower than reported previously for Amazonia. At three sites for which we had data for multiple census intervals, we found no concerted increase in biomass gain, in conflict with the increased productivity hypothesis. Over all ten plots, the fastest-growing quartile of species gained biomass (+0.33 [0.09, 0.55] % y(-1)) compared with the tree community as a whole (+0.15 % y(-1)); however, this significant trend was due to a single plot. Biomass of slow-growing species increased significantly when calculated over all plots (+0.21 [0.02, 0.37] % y(-1)), and in half of our plots when calculated individually. Our results do not support the hypothesis that fast-growing species are consistently increasing in dominance in tropical tree communities. Instead, they suggest that our plots may be simultaneously recovering from past disturbances and affected by changes in resource availability. More long-term studies are necessary to clarify the contribution of global change to the functioning of tropical forests.

Estimating aboveground live understory vegetation carbon in the United States

NASA Astrophysics Data System (ADS)

Johnson, Kristofer D.; Domke, Grant M.; Russell, Matthew B.; Walters, Brian; Hom, John; Peduzzi, Alicia; Birdsey, Richard; Dolan, Katelyn; Huang, Wenli

2017-12-01

Despite the key role that understory vegetation plays in ecosystems and the terrestrial carbon cycle, it is often overlooked and has few quantitative measurements, especially at national scales. To understand the contribution of understory carbon to the United States (US) carbon budget, we developed an approach that relies on field measurements of understory vegetation cover and height on US Department of Agriculture Forest Service, Forest Inventory and Analysis (FIA) subplots. Allometric models were developed to estimate aboveground understory carbon. A spatial model based on stand characteristics and remotely sensed data was also applied to estimate understory carbon on all FIA plots. We found that most understory carbon was comprised of woody shrub species (64%), followed by nonwoody forbs and graminoid species (35%) and seedlings (1%). The largest estimates were found in temperate or warm humid locations such as the Pacific Northwest and southeastern US, thus following the same broad trend as aboveground tree biomass. The average understory aboveground carbon density was estimated to be 0.977 Mg ha-1, for a total estimate of 272 Tg carbon across all managed forest land in the US (approximately 2% of the total aboveground live tree carbon pool). This estimate is more than twice as low as previous FIA modeled estimates that did not rely on understory measurements, suggesting that this pool may currently be overestimated in US National Greenhouse Gas reporting.

Forest succession in the Upper Rio Negro of Colombia and Venezuela

DOE Office of Scientific and Technical Information (OSTI.GOV)

Saldarriaga, J.G.; West, D.C.; Tharp, M.L.

1986-11-01

Woody vegetation from 23 forest stands along the Upper Rio Negro of Venezuela and Colombia was sampled in 1982 to examine the hypothesis that the Amazon forest has been largely undisturbed since the Pleistocene, to quantify vegetation development during different stages of succession following agricultural development, and to determine the time required for a successional stand to become a mature forest. The ubiquitousness of charcoal in the tierra firme forest indicated the presence of fire associated with extreme dry periods and human disturbances. Changes in species composition, vegetation structure, and woody biomass were studied on 19 abandoned farms and fourmore » mature forest stands. Living and dead biomass for the tress and their components was determined by regression equations developed from measurements of harvested trees. The rate of recovery of floristic composition, structure, and biomass following disturbance is relatively slow. Aboveground dead biomass remained high 14 years after the forest was disturbed by the agricultural practices. The lowest dead biomass is reached 20 years after abandonment, and the largest values are found in mature forests. Data analysis of 80-year-old stands showed that the species composition approached that of a mature forest. Approximately 140 to 200 years was required for an abandoned farm to attain the basal area and biomass values comparable to those of a mature forest. The results of this study indicate that recovery is five to seven times longer in the Upper Rio Negro than it is in other tropical areas in South America.« less

Effects of LiDAR point density and landscape context on estimates of urban forest biomass

NASA Astrophysics Data System (ADS)

Singh, Kunwar K.; Chen, Gang; McCarter, James B.; Meentemeyer, Ross K.

2015-03-01

Light Detection and Ranging (LiDAR) data is being increasingly used as an effective alternative to conventional optical remote sensing to accurately estimate aboveground forest biomass ranging from individual tree to stand levels. Recent advancements in LiDAR technology have resulted in higher point densities and improved data accuracies accompanied by challenges for procuring and processing voluminous LiDAR data for large-area assessments. Reducing point density lowers data acquisition costs and overcomes computational challenges for large-area forest assessments. However, how does lower point density impact the accuracy of biomass estimation in forests containing a great level of anthropogenic disturbance? We evaluate the effects of LiDAR point density on the biomass estimation of remnant forests in the rapidly urbanizing region of Charlotte, North Carolina, USA. We used multiple linear regression to establish a statistical relationship between field-measured biomass and predictor variables derived from LiDAR data with varying densities. We compared the estimation accuracies between a general Urban Forest type and three Forest Type models (evergreen, deciduous, and mixed) and quantified the degree to which landscape context influenced biomass estimation. The explained biomass variance of the Urban Forest model, using adjusted R2, was consistent across the reduced point densities, with the highest difference of 11.5% between the 100% and 1% point densities. The combined estimates of Forest Type biomass models outperformed the Urban Forest models at the representative point densities (100% and 40%). The Urban Forest biomass model with development density of 125 m radius produced the highest adjusted R2 (0.83 and 0.82 at 100% and 40% LiDAR point densities, respectively) and the lowest RMSE values, highlighting a distance impact of development on biomass estimation. Our evaluation suggests that reducing LiDAR point density is a viable solution to regional-scale forest assessment without compromising the accuracy of biomass estimates, and these estimates can be further improved using development density.

Lidar-based biomass assessment for the Yukon River Basin

NASA Astrophysics Data System (ADS)

Peterson, B.; Wylie, B. K.; Stoker, J.; Nossov, D.

2010-12-01

Climate change is expected to have a significant impact on high-latitude forests in terms of their ability to sequester carbon as expressed as pools of standing total biomass and soil organic matter. Above ground biomass is an important driver in ecosystem process models used to assess, predict, and understand climate change impacts. Therefore, it is of compelling interest to acquire accurate assessments of current biomass levels for these high-latitude forests, a particular challenge because of their vastness and remoteness. At this time, remote sensing is the only feasible method through which to acquire such assessments. In this study, the use of lidar data for estimating shrub and tree biomass for the Yukon Flats region of Alaska’s Yukon River Basin (YRB) is demonstrated. The lidar data were acquired in the late summer and fall of 2009 as were an initial set of field sampling data collected for training and validation purposes. The 2009 field campaigns were located near Canvasback Lake and Boot Lake in the YRB. Various tallies of biomass were calculated from the field data using allometric equations (Bond-Lamberty et al. 2002, Yarie et al. 2007, Mack et al. 2008). Additional field data were also collected during two 2010 field campaigns at different locations in the Yukon Flats. Linear regressions have been developed based on field-based shrub and tree biomass and various lidar metrics of canopy height calculated for the plots (900 m^2). A multiple linear regression performed at the plot level resulted in a strong relationship (R^2=0.88) between observed and predicted biomass at the plot level. The coefficients for this regression were used to generate a shrub and tree biomass map for the entire Yukon Flats study area covered by lidar. This biomass map will be evaluated using additional field data collected in 2010 as well as other remote sensing data sources. Furthermore, additional lidar metrics (e.g. height of median energy) are being derived from the raw lidar data set and are expected to result in improved biomass products for the YRB as they have been shown to be highly predictive of biomass in other biomes. The results of this project represent the first step in a larger effort to collect lidar and field data for various study sites across the YRB for biomass estimations to train large-scale mapping efforts using Landsat imagery and radar data. Bond-Lamberty, B., C. Wang, and S.T. Gower. 2002. Aboveground and belowground biomass and sapwood area allometric equations for six boreal tree species of northern Manitoba. Canadian Journal of Forest Research 32: 1441-1450. Mack, M., K. Treseder, K. Manies, J. Harden, E. Schuur, J. Vogel, J. Randerson, and F.S. Chapin III. 2008. Recovery of Aboveground Plant Biomass and Productivity After Fire in Mesic and Dry Black Spruce Forests of Interior Alaska, Ecosystems v.11:209-225. Yarie, J., E. Kane, and M. Mack. 2007. Aboveground Biomass Equations for the Trees of Interior Alaska. AFES Bulletin 115.

Canopy area of large trees explains aboveground biomass variations across neotropical forest landscapes

NASA Astrophysics Data System (ADS)

Meyer, Victoria; Saatchi, Sassan; Clark, David B.; Keller, Michael; Vincent, Grégoire; Ferraz, António; Espírito-Santo, Fernando; d'Oliveira, Marcus V. N.; Kaki, Dahlia; Chave, Jérôme

2018-06-01

Large tropical trees store significant amounts of carbon in woody components and their distribution plays an important role in forest carbon stocks and dynamics. Here, we explore the properties of a new lidar-derived index, the large tree canopy area (LCA) defined as the area occupied by canopy above a reference height. We hypothesize that this simple measure of forest structure representing the crown area of large canopy trees could consistently explain the landscape variations in forest volume and aboveground biomass (AGB) across a range of climate and edaphic conditions. To test this hypothesis, we assembled a unique dataset of high-resolution airborne light detection and ranging (lidar) and ground inventory data in nine undisturbed old-growth Neotropical forests, of which four had plots large enough (1 ha) to calibrate our model. We found that the LCA for trees greater than 27 m (˜ 25-30 m) in height and at least 100 m2 crown size in a unit area (1 ha), explains more than 75 % of total forest volume variations, irrespective of the forest biogeographic conditions. When weighted by average wood density of the stand, LCA can be used as an unbiased estimator of AGB across sites (R2 = 0.78, RMSE = 46.02 Mg ha-1, bias = -0.63 Mg ha-1). Unlike other lidar-derived metrics with complex nonlinear relations to biomass, the relationship between LCA and AGB is linear and remains unique across forest types. A comparison with tree inventories across the study sites indicates that LCA correlates best with the crown area (or basal area) of trees with diameter greater than 50 cm. The spatial invariance of the LCA-AGB relationship across the Neotropics suggests a remarkable regularity of forest structure across the landscape and a new technique for systematic monitoring of large trees for their contribution to AGB and changes associated with selective logging, tree mortality and other types of tropical forest disturbance and dynamics.

Deadwood biomass: an underestimated carbon stock in degraded tropical forests?

NASA Astrophysics Data System (ADS)

Pfeifer, Marion; Lefebvre, Veronique; Turner, Edgar; Cusack, Jeremy; Khoo, MinSheng; Chey, Vun K.; Peni, Maria; Ewers, Robert M.

2015-04-01

Despite a large increase in the area of selectively logged tropical forest worldwide, the carbon stored in deadwood across a tropical forest degradation gradient at the landscape scale remains poorly documented. Many carbon stock studies have either focused exclusively on live standing biomass or have been carried out in primary forests that are unaffected by logging, despite the fact that coarse woody debris (deadwood with ≥10 cm diameter) can contain significant portions of a forest’s carbon stock. We used a field-based assessment to quantify how the relative contribution of deadwood to total above-ground carbon stock changes across a disturbance gradient, from unlogged old-growth forest to severely degraded twice-logged forest, to oil palm plantation. We measured in 193 vegetation plots (25 × 25 m), equating to a survey area of >12 ha of tropical humid forest located within the Stability of Altered Forest Ecosystems Project area, in Sabah, Malaysia. Our results indicate that significant amounts of carbon are stored in deadwood across forest stands. Live tree carbon storage decreased exponentially with increasing forest degradation 7-10 years after logging while deadwood accounted for >50% of above-ground carbon stocks in salvage-logged forest stands, more than twice the proportion commonly assumed in the literature. This carbon will be released as decomposition proceeds. Given the high rates of deforestation and degradation presently occurring in Southeast Asia, our findings have important implications for the calculation of current carbon stocks and sources as a result of human-modification of tropical forests. Assuming similar patterns are prevalent throughout the tropics, our data may indicate a significant global challenge to calculating global carbon fluxes, as selectively-logged forests now represent more than one third of all standing tropical humid forests worldwide.

Does species richness affect fine root biomass and production in young forest plantations?

PubMed

Domisch, Timo; Finér, Leena; Dawud, Seid Muhie; Vesterdal, Lars; Raulund-Rasmussen, Karsten

2015-02-01

Tree species diversity has been reported to increase forest ecosystem above-ground biomass and productivity, but little is known about below-ground biomass and production in diverse mixed forests compared to single-species forests. For testing whether species richness increases below-ground biomass and production and thus complementarity between forest tree species in young stands, we determined fine root biomass and production of trees and ground vegetation in two experimental plantations representing gradients in tree species richness. Additionally, we measured tree fine root length and determined species composition from fine root biomass samples with the near-infrared reflectance spectroscopy method. We did not observe higher biomass or production in mixed stands compared to monocultures. Neither did we observe any differences in tree root length or fine root turnover. One reason for this could be that these stands were still young, and canopy closure had not always taken place, i.e. a situation where above- or below-ground competition did not yet exist. Another reason could be that the rooting traits of the tree species did not differ sufficiently to support niche differentiation. Our results suggested that functional group identity (i.e. conifers vs. broadleaved species) can be more important for below-ground biomass and production than the species richness itself, as conifers seemed to be more competitive in colonising the soil volume, compared to broadleaved species.

Impact of deforestation and climate on the Amazon Basin's above-ground biomass during 1993-2012.

PubMed

Exbrayat, Jean-François; Liu, Yi Y; Williams, Mathew

2017-11-15

Since the 1960s, large-scale deforestation in the Amazon Basin has contributed to rising global CO 2 concentrations and to climate change. Recent advances in satellite observations enable estimates of gross losses of above-ground biomass (AGB) stocks due to deforestation. However, because of simultaneous regrowth, the net contribution of deforestation emissions to rising atmospheric CO 2 concentrations is poorly quantified. Climate change may also reduce the potential for forest regeneration in previously disturbed regions. Here, we address these points of uncertainty with a machine-learning approach that combines satellite observations of AGB with climate data across the Amazon Basin to reconstruct annual maps of potential AGB during 1993-2012, the above-ground C storage potential of the undisturbed landscape. We derive a 2.2 Pg C loss of AGB over the study period, and, for the regions where these losses occur, we estimate a 0.7 Pg C reduction in potential AGB. Thus, climate change has led to a decline of ~1/3 in the capacity of these disturbed forests to recover and recapture the C lost in disturbances during 1993-2012. Our approach further shows that annual variations in land use change mask the natural relationship between the El Niño/Southern Oscillation and AGB stocks in disturbed regions.

Assessing the influence of return density on estimation of lidar-based aboveground biomass in tropical peat swamp forests of Kalimantan, Indonesia

Treesearch

Solichin Manuri; Hans-Erik Andersen; Robert J. McGaughey; Cris Brack

2017-01-01

The airborne lidar system (ALS) provides a means to efficiently monitor the status of remote tropical forests and continues to be the subject of intense evaluation. However, the cost of ALS acquisition canvary significantly depending on the acquisition parameters, particularly the return density (i.e., spatial resolution) of the lidar point cloud. This study assessed...

Height-related trends in leaf xylem anatomy and shoot hydraulic characteristics in a tall conifer: safety versus efficiency in water transport

Treesearch

D.R. Woodruff; F.C. Meinzer; B. Lachenbruch

2008-01-01

Growth and aboveground biomass accumulation follow a common pattern as tree size increases, with productivity peaking when leaf area reaches its maximum and then declining as tree age and size increase. Age- and size-related declines in forest productivity are major considerations in setting the rotational age of commercial forests, and relate to issues of carbon...

Novel and lost forests in the Upper Midwestern United States, from new estimates of settlement-era composition, stem density, and biomass

USGS Publications Warehouse

Goring, Simon; Mladenoff, David J.; Cogbill, Charles; Record, Sydne; Paciorek, Christopher J.; Dietze, Michael C.; Dawson, Andria; Matthes, Jaclyn; McLachlan, Jason S.; Williams, John W.

2016-01-01

EuroAmerican land-use and its legacies have transformed forest structure and composition across the United States (US). More accurate reconstructions of historical states are critical to understanding the processes governing past, current, and future forest dynamics. Here we present new gridded (8x8km) reconstructions of pre-settlement (1800s) forest composition and structure from the upper Midwestern US (Minnesota, Wisconsin, and most of Michigan), using 19th Century Public Land Survey System (PLSS), with estimates of relative composition, above-ground biomass, stem density, and basal area for 28 tree types. This mapping is more robust than past efforts, using spatially varying correction factors to accommodate sampling design, azimuthal censoring, and biases in tree selection.

Ecological Importance of Large-Diameter Trees in a Temperate Mixed-Conifer Forest

PubMed Central

Lutz, James A.; Larson, Andrew J.; Swanson, Mark E.; Freund, James A.

2012-01-01

Large-diameter trees dominate the structure, dynamics and function of many temperate and tropical forests. Although both scaling theory and competition theory make predictions about the relative composition and spatial patterns of large-diameter trees compared to smaller diameter trees, these predictions are rarely tested. We established a 25.6 ha permanent plot within which we tagged and mapped all trees ≥1 cm dbh, all snags ≥10 cm dbh, and all shrub patches ≥2 m2. We sampled downed woody debris, litter, and duff with line intercept transects. Aboveground live biomass of the 23 woody species was 507.9 Mg/ha, of which 503.8 Mg/ha was trees (SD = 114.3 Mg/ha) and 4.1 Mg/ha was shrubs. Aboveground live and dead biomass was 652.0 Mg/ha. Large-diameter trees comprised 1.4% of individuals but 49.4% of biomass, with biomass dominated by Abies concolor and Pinus lambertiana (93.0% of tree biomass). The large-diameter component dominated the biomass of snags (59.5%) and contributed significantly to that of woody debris (36.6%). Traditional scaling theory was not a good model for either the relationship between tree radii and tree abundance or tree biomass. Spatial patterning of large-diameter trees of the three most abundant species differed from that of small-diameter conspecifics. For A. concolor and P. lambertiana, as well as all trees pooled, large-diameter and small-diameter trees were spatially segregated through inter-tree distances <10 m. Competition alone was insufficient to explain the spatial patterns of large-diameter trees and spatial relationships between large-diameter and small-diameter trees. Long-term observations may reveal regulation of forest biomass and spatial structure by fire, wind, pathogens, and insects in Sierra Nevada mixed-conifer forests. Sustaining ecosystem functions such as carbon storage or provision of specialist species habitat will likely require different management strategies when the functions are performed primarily by a few large trees as opposed to many smaller trees. PMID:22567132

Assimilation of repeated woody biomass observations constrains decadal ecosystem carbon cycle uncertainty in aggrading forests

NASA Astrophysics Data System (ADS)

Smallman, T. L.; Exbrayat, J.-F.; Mencuccini, M.; Bloom, A. A.; Williams, M.

2017-03-01

Forest carbon sink strengths are governed by plant growth, mineralization of dead organic matter, and disturbance. Across landscapes, remote sensing can provide information about aboveground states of forests and this information can be linked to models to estimate carbon cycling in forests close to steady state. For aggrading forests this approach is more challenging and has not been demonstrated. Here we apply a Bayesian approach, linking a simple model to a range of data, to evaluate their information content, for two aggrading forests. We compare high information content analyses using local observations with retrievals using progressively sparser remotely sensed information (repeated, single, and no woody biomass observations). The net biome productivity of both forests is constrained to be a net sink with <2 Mg C ha-1 yr-1 variation across the range of inputs. However, the sequestration of particular carbon pool(s) varies with assimilated biomass information. Assimilation of repeated biomass observations reduces uncertainty and/or bias in all ecosystem C pools not just wood, compared to analyses using single or no stock information. As verification, our repeated biomass analysis explains 78-86% of variation in litter dynamics at one forest, while at the second forest total dead organic matter estimates are within observational uncertainty. The uncertainty of retrieved ecosystem traits in the repeated biomass analysis is reduced by up to 50% compared to analyses with less biomass information. This study quantifies the importance of repeated woody observations in constraining the dynamics of both wood and dead organic matter, highlighting the benefit of proposed remote sensing missions.

Quantitative retrieving forest ecological parameters based on remote sensing in Liping County of China

NASA Astrophysics Data System (ADS)

Tian, Qingjiu; Chen, Jing M.; Zheng, Guang; Xia, Xueqi; Chen, Junying

2006-09-01

Forest ecosystem is an important component of terrestrial ecosystem and plays an important role in global changes. Aboveground biomass (AGB) of forest ecosystem is an important factor in global carbon cycle studies. The purpose of this study was to retrieve the yearly Net Primary Productivity (NPP) of forest from the 8-days-interval MODIS-LAI images of a year and produce a yearly NPP distribution map. The LAI, DBH (diameter at breast height), tree height, and tree age field were measured in different 80 plots for Chinese fir, Masson pine, bamboo, broadleaf, mix forest in Liping County. Based on the DEM image and Landsat TM images acquired on May 14th, 2000, the geometric correction and terrain correction were taken. In addition, the "6S"model was used to gain the surface reflectance image. Then the correlation between Leaf Area Index (LAI) and Reduced Simple Ratio (RSR) was built. Combined with the Landcover map, forest stand map, the LAI, aboveground biomass, tree age map were produced respectively. After that, the 8-days- interval LAI images of a year, meteorology data, soil data, forest stand image and Landcover image were inputted into the BEPS model to get the NPP spatial distribution. At last, the yearly NPP spatial distribution map with 30m spatial resolution was produced. The values in those forest ecological parameters distribution maps were quite consistent with those of field measurements. So it's possible, feasible and time-saving to estimate forest ecological parameters at a large scale by using remote sensing.

Lidar-Based Estimates of Above-Ground Biomass in the Continental US and Mexico Using Ground, Airborne, and Satellite Observations

NASA Technical Reports Server (NTRS)

Nelson, Ross; Margolis, Hank; Montesano, Paul; Sun, Guoqing; Cook, Bruce; Corp, Larry; Andersen, Hans-Erik; DeJong, Ben; Pellat, Fernando Paz; Fickel, Thaddeus;

The Biomass mission: a step forward in quantifying forest biomass and structure

NASA Astrophysics Data System (ADS)

LE Toan, T.

2015-12-01

The primary aim of the ESA BIOMASS mission is to determine, for the first time and in a consistent manner, the global distribution of above-ground forest biomass (AGB) in order to provide greatly improved quantification of the size and distribution of the terrestrial carbon pool, and improved estimates of terrestrial carbon fluxes. Specifically, BIOMASS will measure forest carbon stock, as well as forest height, from data provided by a single satellite giving a biomass map covering tropical, temperate and boreal forests at a resolution of around 200 m every 6 months throughout the five years of the mission. BIOMASS will use a long wavelength SAR (P-band) providing three mutually supporting measurement techniques, namely polarimetric SAR (PolSAR), polarimetric interferometric SAR (PolInSAR) and tomographic SAR (TomoSAR). The combination of these techniques will significantly reduce the uncertainties in biomass retrievals by yielding complementary information on biomass properties. Horizontal mapping: For a forest canopy, the P-band radar waves penetrate deep into the canopy, and their interaction with the structure of the forest will be exploited to map above ground biomass (AGB), as demonstrated from airborne data for temperate, boreal forests and tropical forest. Height mapping: By repeat revisits to the same location, the PolInSAR measurements will be used to estimate the height of scattering in the forest canopy. The long wavelength used by BIOMASS is crucial for the temporal coherence to be preserved over much longer timescales than at L-band, for example. 3D mapping: The P-band frequency used by BIOMASS is low enough to ensure penetration through the entire canopy, even in dense tropical forests. As a consequence, resolution of the vertical structure of the forest will be possible using tomographic methods from the multi-baseline acquisitions. This is the concept of SAR tomography, which will be implemented in the BIOMASS mission. The improvement in the quantification of the vegetation structure, will have an important impact in many aspects of ecosystem function, such as carbon cycling and biodiversity. For example, areas of forest loss or degradation and areas of growth or recovery, can be determined by the vegetation structure and its temporal change.

Annual measurements of gain and loss in aboveground carbon density

NASA Astrophysics Data System (ADS)

Baccini, A.; Walker, W. S.; Carvalho, L.; Farina, M.; Sulla-menashe, D. J.; Houghton, R. A.

2017-12-01

Tropical forests hold large stores of carbon, but their net carbon balance is uncertain. Land use and land-cover change (LULCC) are believed to release between 0.81 and 1.14 PgC yr-1, while intact native forests are thought to be a net carbon sink of approximately the same magnitude. Reducing the uncertainty of these estimates is not only fundamental to the advancement of carbon cycle science but is also of increasing relevance to national and international policies designed to reduce emissions from deforestation and forest degradation (e.g., REDD+). Contemporary approaches to estimating the net carbon balance of tropical forests rely on changes in forest area between two periods, typically derived from satellite data, together with information on average biomass density. These approaches tend to capture losses in biomass due to deforestation (i.e., wholesale stand removals) but are limited in their sensitivity to forest degradation (e.g., selective logging or single-tree removals), which can account for additional biomass losses on the order of 47-75% of deforestation. Furthermore, while satellite-based estimates of forest area loss have been used successfully to estimate associated carbon losses, few such analyses have endeavored to determine the rate of carbon sequestration in growing forests. Here we use 12 years (2003-2014) of pantropical satellite data to quantify net annual changes in the aboveground carbon density of woody vegetation (MgC ha-1yr-1), providing direct, measurement-based evidence that the world's tropical forests are a net carbon source of 425.2 ± 92.0 Tg C yr-1. This net release of carbon consists of losses of 861.7 ± 80.2 Tg C yr-1 and gains of -436.5 ± 31.0 Tg C yr-1 . Gains result from forest growth; losses result from reductions in forest area due to deforestation and from reductions in biomass density within standing forests (degradation), with the latter accounting for 68.9% of overall losses. Our findings advance previous research by providing novel, annual measurements of carbon losses and gains, from forest loss, degradation, and growth, with reduced uncertainty that stems from an unconventional shift in emphasis away from classifications of land area change toward direct estimation of carbon density dynamics.

Bringing Together Users and Developers of Forest Biomass Maps

NASA Technical Reports Server (NTRS)

Brown, Molly Elizabeth; Macauley, Molly K.

2012-01-01

Forests store carbon and thus represent important sinks for atmospheric carbon dioxide. Reducing uncertainty in current estimates of the amount of carbon in standing forests will improve precision of estimates of anthropogenic contributions to carbon dioxide in the atmosphere due to deforestation. Although satellite remote sensing has long been an important tool for mapping land cover, until recently aboveground forest biomass estimates have relied mostly on systematic ground sampling of forests. In alignment with fiscal year 2010 congressional direction, NASA has initiated work toward a carbon monitoring system (CMS) that includes both maps of forest biomass and total carbon flux estimates. A goal of the project is to ensure that the products are useful to a wide community of scientists, managers, and policy makers, as well as to carbon cycle scientists. Understanding the needs and requirements of these data users is helpful not just to the NASA CMS program but also to the entire community working on carbon-related activities. To that end, this meeting brought together a small group of natural resource managers and policy makers who use information on forests in their work with NASA scientists who are working to create aboveground forest biomass maps. These maps, derived from combining remote sensing and ground plots, aim to be more accurate than current inventory approaches when applied at local and regional scales. Meeting participants agreed that users of biomass information will look to the CMS effort not only to provide basic data for carbon or biomass measurements but also to provide data to help serve a broad range of goals, such as forest watershed management for water quality, habitat management for biodiversity and ecosystem services, and potential use for developing payments for ecosystem service projects. Participants also reminded the CMS group that potential users include not only public sector agencies and nongovernmental organizations but also the private sector because much forest acreage in the United States is privately held and needs data for forest management. Additional key outcomes identified by meeting participants include the following: (1) Priority should be given to building into the biomass product ease of use and low costs (including costs of hardware, software, and analysis requirements), (2) CMS products should also be relevant to other biomass measures for forest watershed management, habitat protection for biodiversity, and assessment of markets for ecosystem services, (3) CMS leadership should engage with the Subsidiary Body for Scientific and Technological Advice of the United Nations Framework Convention on Climate Change as they establish measuring, reporting, and verification standards, and (4) CMS leadership should continue to keep sister agencies and other organizations informed as CMS develops, particularly via the agencies active in the U.S. Global Change Research Program Carbon Cycle Interagency Working Group (U.S. Geological Survey, U.S. Department of Agriculture, and National Oceanic and Atmospheric Administration) and nongovernmental organizations.

Recent Progress in Measuring and Modeling Patterns of Biomass and Soil Carbon Pools Across the Amazon Basin

NASA Technical Reports Server (NTRS)

Potter, Christopher; Malhi, Yadvinder

2004-01-01

Ever more detailed representations of above-ground biomass and soil carbon pools have been developed during the LBA project. Environmental controls such as regional climate, land cover history, secondary forest regrowth, and soil fertility are now being taken into account in regional inventory studies. This paper will review the evolution of measurement-extrapolation approaches, remote sensing, and simulation modeling techniques for biomass and soil carbon pools, which together help constrain regional carbon budgets and enhance in our understanding of uncertainty at the regional level.

Carbon pool and biomass dynamics associated with deforestation, land use, and agricultural abandonment in the neotropics.

PubMed

Kauffman, J Boone; Hughes, R Flint; Heider, Chris

2009-07-01

Current rates of deforestation and the resulting C emissions in the tropics exceed those of secondary forest regrowth and C sequestration. Changing land-use strategies that would maintain standing forests may be among the least expensive of climate change mitigation options. Further, secondary tropical forests have been suggested to have great value for their potential to sequester atmospheric C. These options require an understanding of and capability to quantify C dynamics at landscape scales. Because of the diversity of physical and biotic features of tropical forests as well as approaches and intensities of land uses within the neotropics, there are tremendous differences in the capacity of different landscapes to store and sequester C. Major gaps in our current knowledge include quantification of C pools, rates and patterns of biomass loss following land-cover change, and quantification of the C storage potential of secondary forests following abandonment. In this paper we present a synthesis and further analyses from recent studies that describe C pools, patterns of C decline associated with land use, and rates of C accumulation following secondary-forest establishment--all information necessary for climate-change mitigation options. Ecosystem C pools of Neotropical primary forests minimally range from approximately 141 to 571 Mg/ha, demonstrating tremendous differences in the capacity of different forests to store C. Most of the losses in C and nutrient pools associated with conversion occur when fires are set to remove the slashed forest to prepare sites for crop or pasture establishment. Fires burning slashed primary forests have been found to result in C losses of 62-80% of prefire aboveground pools in dry (deciduous) forest landscapes and 29-57% in wet (evergreen) forest landscapes. Carbon emissions equivalent to the aboveground primary-forest pool arise from repeated fires occurring in the first 4 to 10 years following conversion. Feedbacks of climate change, land-cover change, and increasing habitat fragmentation may result in increases of both the area burned and the total quantity of biomass consumed per unit area by fire. These effects may well limit the capacity for future tropical forests to sequester C and nutrients.

Unearthing the hidden world of roots: Root biomass and architecture differ among species within the same guild

PubMed Central

2017-01-01

The potential benefits of planting trees have generated significant interest with respect to sequestering carbon and restoring other forest based ecosystem services. Reliable estimates of carbon stocks are pivotal for understanding the global carbon balance and for promoting initiatives to mitigate CO2 emissions through forest management. There are numerous studies employing allometric regression models that convert inventory into aboveground biomass (AGB) and carbon (C). Yet the majority of allometric regression models do not consider the root system nor do these equations provide detail on the architecture and shape of different species. The root system is a vital piece toward understanding the hidden form and function roots play in carbon accumulation, nutrient and plant water uptake, and groundwater infiltration. Work that estimates C in forests as well as models that are used to better understand the hydrologic function of trees need better characterization of tree roots. We harvested 40 trees of six different species, including their roots down to 2 mm in diameter and created species-specific and multi-species models to calculate aboveground (AGB), coarse root belowground biomass (BGB), and total biomass (TB). We also explore the relationship between crown structure and root structure. We found that BGB contributes ~27.6% of a tree’s TB, lateral roots extend over 1.25 times the distance of crown extent, root allocation patterns varied among species, and that AGB is a strong predictor of TB. These findings highlight the potential importance of including the root system in C estimates and lend important insights into the function roots play in water cycling. PMID:29023553

Estimation of biophysical properties of upland Sitka spruce (Picea sitchensis) plantations

NASA Technical Reports Server (NTRS)

Green, Robert M.

1993-01-01

It is widely accepted that estimates of forest above-ground biomass are required as inputs to forest ecosystem models, and that SAR data have the potential to provide such information. This study describes relationships between polarimetric radar backscatter and key biophysical properties of a coniferous plantation in upland central Wales, U.K. Over the test site, topography was relatively complex and was expected to influence the amount of radar backscatter.

Estimating stand structure using discrete-return lidar: an example from low density, fire prone ponderosa pine forests

USGS Publications Warehouse

Hall, S. A.; Burke, I.C.; Box, D. O.; Kaufmann, M. R.; Stoker, Jason M.

2005-01-01

The ponderosa pine forests of the Colorado Front Range, USA, have historically been subjected to wildfires. Recent large burns have increased public interest in fire behavior and effects, and scientific interest in the carbon consequences of wildfires. Remote sensing techniques can provide spatially explicit estimates of stand structural characteristics. Some of these characteristics can be used as inputs to fire behavior models, increasing our understanding of the effect of fuels on fire behavior. Others provide estimates of carbon stocks, allowing us to quantify the carbon consequences of fire. Our objective was to use discrete-return lidar to estimate such variables, including stand height, total aboveground biomass, foliage biomass, basal area, tree density, canopy base height and canopy bulk density. We developed 39 metrics from the lidar data, and used them in limited combinations in regression models, which we fit to field estimates of the stand structural variables. We used an information–theoretic approach to select the best model for each variable, and to select the subset of lidar metrics with most predictive potential. Observed versus predicted values of stand structure variables were highly correlated, with r2 ranging from 57% to 87%. The most parsimonious linear models for the biomass structure variables, based on a restricted dataset, explained between 35% and 58% of the observed variability. Our results provide us with useful estimates of stand height, total aboveground biomass, foliage biomass and basal area. There is promise for using this sensor to estimate tree density, canopy base height and canopy bulk density, though more research is needed to generate robust relationships. We selected 14 lidar metrics that showed the most potential as predictors of stand structure. We suggest that the focus of future lidar studies should broaden to include low density forests, particularly systems where the vertical structure of the canopy is important, such as fire prone forests.

Patterns of biomass and carbon distribution across a chronosequence of Chinese pine (Pinus tabulaeformis) forests.

PubMed

Zhao, Jinlong; Kang, Fengfeng; Wang, Luoxin; Yu, Xiaowen; Zhao, Weihong; Song, Xiaoshuai; Zhang, Yanlei; Chen, Feng; Sun, Yu; He, Tengfei; Han, Hairong

2014-01-01

Patterns of biomass and carbon (C) storage distribution across Chinese pine (Pinus tabulaeformis) natural secondary forests are poorly documented. The objectives of this study were to examine the biomass and C pools of the major ecosystem components in a replicated age sequence of P. tabulaeformis secondary forest stands in Northern China. Within each stand, biomass of above- and belowground tree, understory (shrub and herb), and forest floor were determined from plot-level investigation and destructive sampling. Allometric equations using the diameter at breast height (DBH) were developed to quantify plant biomass. C stocks in the tree and understory biomass, forest floor, and mineral soil (0-100 cm) were estimated by analyzing the C concentration of each component. The results showed that the tree biomass of P. tabulaeformis stands was ranged from 123.8 Mg·ha-1 for the young stand to 344.8 Mg·ha-1 for the mature stand. The understory biomass ranged from 1.8 Mg·ha-1 in the middle-aged stand to 3.5 Mg·ha-1 in the young stand. Forest floor biomass increased steady with stand age, ranging from 14.9 to 23.0 Mg·ha-1. The highest mean C concentration across the chronosequence was found in tree branch while the lowest mean C concentration was found in forest floor. The observed C stock of the aboveground tree, shrub, forest floor, and mineral soil increased with increasing stand age, whereas the herb C stock showed a decreasing trend with a sigmoid pattern. The C stock of forest ecosystem in young, middle-aged, immature, and mature stands were 178.1, 236.3, 297.7, and 359.8 Mg C ha-1, respectively, greater than those under similar aged P. tabulaeformis forests in China. These results are likely to be integrated into further forest management plans and generalized in other contexts to evaluate C stocks at the regional scale.

Patterns of Biomass and Carbon Distribution across a Chronosequence of Chinese Pine (Pinus tabulaeformis) Forests

PubMed Central

Wang, Luoxin; Yu, Xiaowen; Zhao, Weihong; Song, Xiaoshuai; Zhang, Yanlei; Chen, Feng; Sun, Yu; He, Tengfei; Han, Hairong

2014-01-01

Patterns of biomass and carbon (C) storage distribution across Chinese pine (Pinus tabulaeformis) natural secondary forests are poorly documented. The objectives of this study were to examine the biomass and C pools of the major ecosystem components in a replicated age sequence of P. tabulaeformis secondary forest stands in Northern China. Within each stand, biomass of above- and belowground tree, understory (shrub and herb), and forest floor were determined from plot-level investigation and destructive sampling. Allometric equations using the diameter at breast height (DBH) were developed to quantify plant biomass. C stocks in the tree and understory biomass, forest floor, and mineral soil (0–100 cm) were estimated by analyzing the C concentration of each component. The results showed that the tree biomass of P. tabulaeformis stands was ranged from 123.8 Mg·ha–1 for the young stand to 344.8 Mg·ha–1 for the mature stand. The understory biomass ranged from 1.8 Mg·ha–1 in the middle-aged stand to 3.5 Mg·ha–1 in the young stand. Forest floor biomass increased steady with stand age, ranging from 14.9 to 23.0 Mg·ha–1. The highest mean C concentration across the chronosequence was found in tree branch while the lowest mean C concentration was found in forest floor. The observed C stock of the aboveground tree, shrub, forest floor, and mineral soil increased with increasing stand age, whereas the herb C stock showed a decreasing trend with a sigmoid pattern. The C stock of forest ecosystem in young, middle-aged, immature, and mature stands were 178.1, 236.3, 297.7, and 359.8 Mg C ha–1, respectively, greater than those under similar aged P. tabulaeformis forests in China. These results are likely to be integrated into further forest management plans and generalized in other contexts to evaluate C stocks at the regional scale. PMID:24736660

Towards ground-truthing of spaceborne estimates of above-ground biomass and leaf area index in tropical rain forests

NASA Astrophysics Data System (ADS)

Köhler, P.; Huth, A.

2010-05-01

The canopy height of forests is a key variable which can be obtained using air- or spaceborne remote sensing techniques such as radar interferometry or lidar. If new allometric relationships between canopy height and the biomass stored in the vegetation can be established this would offer the possibility for a global monitoring of the above-ground carbon content on land. In the absence of adequate field data we use simulation results of a tropical rain forest growth model to propose what degree of information might be generated from canopy height and thus to enable ground-truthing of potential future satellite observations. We here analyse the correlation between canopy height in a tropical rain forest with other structural characteristics, such as above-ground biomass (AGB) (and thus carbon content of vegetation) and leaf area index (LAI). The process-based forest growth model FORMIND2.0 was applied to simulate (a) undisturbed forest growth and (b) a wide range of possible disturbance regimes typically for local tree logging conditions for a tropical rain forest site on Borneo (Sabah, Malaysia) in South-East Asia. It is found that for undisturbed forest and a variety of disturbed forests situations AGB can be expressed as a power-law function of canopy height h (AGB=a·hb) with an r2~60% for a spatial resolution of 20 m×20 m (0.04 ha, also called plot size). The regression is becoming significant better for the hectare wide analysis of the disturbed forest sites (r2=91%). There seems to exist no functional dependency between LAI and canopy height, but there is also a linear correlation (r2~60%) between AGB and the area fraction in which the canopy is highly disturbed. A reasonable agreement of our results with observations is obtained from a comparison of the simulations with permanent sampling plot data from the same region and with the large-scale forest inventory in Lambir. We conclude that the spaceborne remote sensing techniques have the potential to quantify the carbon contained in the vegetation, although this calculation contains due to the heterogeneity of the forest landscape structural uncertainties which restrict future applications to spatial averages of about one hectare in size. The uncertainties in AGB for a given canopy height are here 20-40% (95% confidence level) corresponding to a standard deviation of less than ±10%. This uncertainty on the 1 ha-scale is much smaller than in the analysis of 0.04 ha-scale data. At this small scale (0.04 ha) AGB can only be calculated out of canopy height with an uncertainty which is at least of the magnitude of the signal itself due to the natural spatial heterogeneity of these forests.

Polarimetric SAR Interferometry based modeling for tree height and aboveground biomass retrieval in a tropical deciduous forest

NASA Astrophysics Data System (ADS)

Kumar, Shashi; Khati, Unmesh G.; Chandola, Shreya; Agrawal, Shefali; Kushwaha, Satya P. S.

2017-08-01

The regulation of the carbon cycle is a critical ecosystem service provided by forests globally. It is, therefore, necessary to have robust techniques for speedy assessment of forest biophysical parameters at the landscape level. It is arduous and time taking to monitor the status of vast forest landscapes using traditional field methods. Remote sensing and GIS techniques are efficient tools that can monitor the health of forests regularly. Biomass estimation is a key parameter in the assessment of forest health. Polarimetric SAR (PolSAR) remote sensing has already shown its potential for forest biophysical parameter retrieval. The current research work focuses on the retrieval of forest biophysical parameters of tropical deciduous forest, using fully polarimetric spaceborne C-band data with Polarimetric SAR Interferometry (PolInSAR) techniques. PolSAR based Interferometric Water Cloud Model (IWCM) has been used to estimate aboveground biomass (AGB). Input parameters to the IWCM have been extracted from the decomposition modeling of SAR data as well as PolInSAR coherence estimation. The technique of forest tree height retrieval utilized PolInSAR coherence based modeling approach. Two techniques - Coherence Amplitude Inversion (CAI) and Three Stage Inversion (TSI) - for forest height estimation are discussed, compared and validated. These techniques allow estimation of forest stand height and true ground topography. The accuracy of the forest height estimated is assessed using ground-based measurements. PolInSAR based forest height models showed enervation in the identification of forest vegetation and as a result height values were obtained in river channels and plain areas. Overestimation in forest height was also noticed at several patches of the forest. To overcome this problem, coherence and backscatter based threshold technique is introduced for forest area identification and accurate height estimation in non-forested regions. IWCM based modeling for forest AGB retrieval showed R2 value of 0.5, RMSE of 62.73 (t ha-1) and a percent accuracy of 51%. TSI based PolInSAR inversion modeling showed the most accurate result for forest height estimation. The correlation between the field measured forest height and the estimated tree height using TSI technique is 62% with an average accuracy of 91.56% and RMSE of 2.28 m. The study suggested that PolInSAR coherence based modeling approach has significant potential for retrieval of forest biophysical parameters.

Evaluation of forest management practices through application of a biogeochemical model, PnET-BGC

NASA Astrophysics Data System (ADS)

Valipour, M.; Driscoll, C. T.; Johnson, C. E.; Campbell, J. L.; Fahey, T.; Zeng, T.

2017-12-01

Forest ecosystem response to logging disturbance varies significantly, depending on site conditions, species composition, land use history, and the method and frequency of harvesting. The long-term effects of forest cuttings are less clear due to limited information on land use history and long-term time series observations. The hydrochemical model, PnET-BGC was modified and verified using field data from multiple experimentally harvested northern hardwood watersheds at the Hubbard Brook Experimental Forest (HBEF), New Hampshire, USA, including a commercial whole-tree harvest (Watershed 5), a devegetation experiment (Watershed 2; devegetation and herbicide treatment), a commercial strip-cut (Watershed 4) to simulate the hydrology, biomass accumulation, and soil solution and stream water chemistry responses to clear-cutting. The confirmed model was used to investigate temporal changes in aboveground biomass accumulation and nutrient dynamics under three different harvesting intensities (40%, 60%, 80%) over four varied rotation lengths (20, 40, 60, 80 years) with results compared with a scenario of no forest harvesting. The total ecosystem carbon pool (biomass, soil and litter) was reduced over harvesting events. The greatest decline occurred in litter by 40%-70%, while the pool of carbon stored in aboveground biomass decreased by 30%-60% for 80% cutting levels at 40 and 20 year rotation lengths, respectively. The large pool of soil organic carbon remained relatively stable, with only minor declines over logging regimes. Stream water simulations demonstrated increased loss of major elements over cutting events. Ca+2 and NO3- were the most sensitive elements to leaching over frequent intensive logging. Accumulated leaching of Ca+2 and NO3- varied between 90-520 t Ca/ha and 40-420 t N/ha from conservative (80-year period and 40% cutting) to aggressive (20-year period and 80% cutting) cutting regimes, respectively. Moreover, a reduction in nutrient plant uptake over logging scenarios was estimated. Model simulations indicated nutrient losses were more sensitive to harvesting rotation length than intensity.

Aboveground biomass mapping of African forest mosaics using canopy texture analysis: toward a regional approach.

PubMed

Bastin, Jean-François; Barbier, Nicolas; Couteron, Pierre; Adams, Benoît; Shapiro, Aurélie; Bogaert, Jan; De Cannière, Charles

In the context of the reduction of greenhouse gas emissions caused by deforestation and forest degradation (the REDD+ program), optical very high resolution (VHR) satellite images provide an opportunity to characterize forest canopy structure and to quantify aboveground biomass (AGB) at less expense than methods based on airborne remote sensing data. Among the methods for processing these VHR images, Fourier textural ordination (FOTO) presents a good method to detect forest canopy structural heterogeneity and therefore to predict AGB variations. Notably, the method does not saturate at intermediate AGB values as do pixelwise processing of available space borne optical and radar signals. However, a regional-scale application requires overcoming two difficulties: (1) instrumental effects due to variations in sun–scene–sensor geometry or sensor-specific responses that preclude the use of wide arrays of images acquired under heterogeneous conditions and (2) forest structural diversity including monodominant or open canopy forests, which are of particular importance in Central Africa. In this study, we demonstrate the feasibility of a rigorous regional study of canopy texture by harmonizing FOTO indices of images acquired from two different sensors (Geoeye-1 and QuickBird-2) and different sun–scene–sensor geometries and by calibrating a piecewise biomass inversion model using 26 inventory plots (1 ha) sampled across very heterogeneous forest types. A good agreement was found between observed and predicted AGB (residual standard error [RSE] = 15%; R2 = 0.85; P < 0.001) across a wide range of AGB levels from 26 Mg/ha to 460 Mg/ha, and was confirmed by cross validation. A high-resolution biomass map (100-m pixels) was produced for a 400-km2 area, and predictions obtained from both imagery sources were consistent with each other (r = 0.86; slope = 1.03; intercept = 12.01 Mg/ha). These results highlight the horizontal structure of forest canopy as a powerful descriptor of the entire forest stand structure and heterogeneity. In particular, we show that quantitative metrics resulting from such textural analysis offer new opportunities to characterize the spatial and temporal variation of the structure of dense forests and may complement the toolbox used by tropical forest ecologists, managers or REDD+ national monitoring, reporting and verification bodies.

Long-term structural and biomass dynamics of virgin Tsuga canadensis-Pinus strobus forests after hurricane disturbance.

PubMed

D'Amato, Anthony W; Orwig, David A; Foster, David R; Barker Plotkin, Audrey; Schoonmaker, Peter K; Wagner, Maggie R

2017-03-01

The development of old-growth forests in northeastern North America has largely been within the context of gap-scale disturbances given the rarity of stand-replacing disturbances. Using the 10-ha old-growth Harvard Tract and its associated 90-year history of measurements, including detailed surveys in 1989 and 2009, we document the long-term structural and biomass development of an old-growth Tsuga canadensis-Pinus strobus forest in southern New Hampshire, USA following a stand-replacing hurricane in 1938. Measurements of aboveground biomass pools were integrated with data from second- and old-growth T. canadensis forests to evaluate long-term patterns in biomass development following this disturbance. Ecosystem structure across the Tract prior to the hurricane exhibited a high degree of spatial heterogeneity with the greatest levels of live tree basal area (70-129 m 2 /ha) on upper west-facing slopes where P. strobus was dominant and intermixed with T. canadensis. Live-tree biomass estimates for these stratified mixtures ranged from 159 to 503 Mg/ha at the localized, plot scale (100 m 2 ) and averaged 367 Mg/ha across these portions of the landscape approaching the upper bounds for eastern forests. Live-tree biomass 71 years after the hurricane is more uniform and lower in magnitude, with T. canadensis currently the dominant overstory tree species throughout much of the landscape. Despite only one living P. strobus stem in the 2009 plots (and fewer than five stems known across the entire 10-ha area), the detrital legacy of this species is pronounced with localized accumulations of coarse woody debris exceeding 237.7-404.2 m 3 /ha where this species once dominated the canopy. These patterns underscore the great sizes P. strobus attained in pre-European landscapes and its great decay resistance relative to its forest associates. Total aboveground biomass pools in this 71-year-old forest (255 Mg/ha) are comparable to those in modern old-growth ecosystems in the region that also lack abundant white pine. Results highlight the importance of disturbance legacies in affecting forest structural conditions over extended periods following stand-replacing events and underscore that post-disturbance salvage logging can alter ecosystem development for decades. Moreover, the dominant role of old-growth P. strobus in live and detrital biomass pools before and after the hurricane, respectively, demonstrate the disproportionate influence this species likely had on carbon storage at localized scales prior to the widespread, selective harvesting of large P. strobus across the region in the 18th and 19th centuries. © 2017 by the Ecological Society of America.

Aboveground vs. Belowground Carbon Stocks in African Tropical Lowland Rainforest: Drivers and Implications.

PubMed

Doetterl, Sebastian; Kearsley, Elizabeth; Bauters, Marijn; Hufkens, Koen; Lisingo, Janvier; Baert, Geert; Verbeeck, Hans; Boeckx, Pascal

2015-01-01

African tropical rainforests are one of the most important hotspots to look for changes in the upcoming decades when it comes to C storage and release. The focus of studying C dynamics in these systems lies traditionally on living aboveground biomass. Belowground soil organic carbon stocks have received little attention and estimates of the size, controls and distribution of soil organic carbon stocks are highly uncertain. In our study on lowland rainforest in the central Congo basin, we combine both an assessment of the aboveground C stock with an assessment of the belowground C stock and analyze the latter in terms of functional pools and controlling factors. Our study shows that despite similar vegetation, soil and climatic conditions, soil organic carbon stocks in an area with greater tree height (= larger aboveground carbon stock) were only half compared to an area with lower tree height (= smaller aboveground carbon stock). This suggests that substantial variability in the aboveground vs. belowground C allocation strategy and/or C turnover in two similar tropical forest systems can lead to significant differences in total soil organic C content and C fractions with important consequences for the assessment of the total C stock of the system. We suggest nutrient limitation, especially potassium, as the driver for aboveground versus belowground C allocation. However, other drivers such as C turnover, tree functional traits or demographic considerations cannot be excluded. We argue that large and unaccounted variability in C stocks is to be expected in African tropical rain-forests. Currently, these differences in aboveground and belowground C stocks are not adequately verified and implemented mechanistically into Earth System Models. This will, hence, introduce additional uncertainty to models and predictions of the response of C storage of the Congo basin forest to climate change and its contribution to the terrestrial C budget.

Aboveground vs. Belowground Carbon Stocks in African Tropical Lowland Rainforest: Drivers and Implications

PubMed Central

Bauters, Marijn; Hufkens, Koen; Lisingo, Janvier; Baert, Geert; Verbeeck, Hans; Boeckx, Pascal

2015-01-01

Background African tropical rainforests are one of the most important hotspots to look for changes in the upcoming decades when it comes to C storage and release. The focus of studying C dynamics in these systems lies traditionally on living aboveground biomass. Belowground soil organic carbon stocks have received little attention and estimates of the size, controls and distribution of soil organic carbon stocks are highly uncertain. In our study on lowland rainforest in the central Congo basin, we combine both an assessment of the aboveground C stock with an assessment of the belowground C stock and analyze the latter in terms of functional pools and controlling factors. Principal Findings Our study shows that despite similar vegetation, soil and climatic conditions, soil organic carbon stocks in an area with greater tree height (= larger aboveground carbon stock) were only half compared to an area with lower tree height (= smaller aboveground carbon stock). This suggests that substantial variability in the aboveground vs. belowground C allocation strategy and/or C turnover in two similar tropical forest systems can lead to significant differences in total soil organic C content and C fractions with important consequences for the assessment of the total C stock of the system. Conclusions/Significance We suggest nutrient limitation, especially potassium, as the driver for aboveground versus belowground C allocation. However, other drivers such as C turnover, tree functional traits or demographic considerations cannot be excluded. We argue that large and unaccounted variability in C stocks is to be expected in African tropical rain-forests. Currently, these differences in aboveground and belowground C stocks are not adequately verified and implemented mechanistically into Earth System Models. This will, hence, introduce additional uncertainty to models and predictions of the response of C storage of the Congo basin forest to climate change and its contribution to the terrestrial C budget. PMID:26599231

Influence of tree size, taxonomy, and edaphic conditions on heart rot in mixed-dipterocarp Bornean rainforests: implications for aboveground biomass estimates

NASA Astrophysics Data System (ADS)

Heineman, K. D.; Russo, S. E.; Baillie, I. C.; Mamit, J. D.; Chai, P. P.-K.; Chai, L.; Hindley, E. W.; Lau, B.-T.; Tan, S.; Ashton, P. S.

2015-05-01

Fungal decay of heartwood creates hollows and areas of reduced wood density within the stems of living trees known as heart rot. Although heart rot is acknowledged as a source of error in forest aboveground biomass estimates, there are few datasets available to evaluate the environmental controls over heart rot infection and severity in tropical forests. Using legacy and recent data from drilled, felled, and cored stems in mixed dipterocarp forests in Sarawak, Malaysian Borneo, we quantified the frequency and severity of heart rot, and used generalized linear mixed effect models to characterize the association of heart rot with tree size, wood density, taxonomy, and edaphic conditions. Heart rot was detected in 55% of felled stems > 30 cm DBH, while the detection frequency was lower for stems of the same size evaluated by non-destructive drilling (45%) and coring (23%) methods. Heart rot severity, defined as the percent stem volume lost in infected stems, ranged widely from 0.1-82.8%. Tree taxonomy explained the greatest proportion of variance in heart rot frequency and severity among the fixed and random effects evaluated in our models. Heart rot frequency, but not severity, increased sharply with tree diameter, ranging from 56% infection across all datasets in stems > 50 cm DBH to 11% in trees 10-30 cm DBH. The frequency and severity of heart rot increased significantly in soils with low pH and cation concentrations in topsoil, and heart rot was more common in tree species associated with dystrophic sandy soils than with nutrient-rich clays. When scaled to forest stands, the percent of stem biomass lost to heart rot varied significantly with soil properties, and we estimate that 7% of the forest biomass is in some stage of heart rot decay. This study demonstrates not only that heart rot is a significant source of error in forest carbon estimates, but also that it strongly covaries with soil resources, underscoring the need to account for edaphic variation in estimating carbon storage in tropical forests.

A wood density and aboveground biomass variability assessment using pre-felling inventory data in Costa Rica.

PubMed

Svob, Sienna; Arroyo-Mora, J Pablo; Kalacska, Margaret

2014-12-01

The high spatio-temporal variability of aboveground biomass (AGB) in tropical forests is a large source of uncertainty in forest carbon stock estimation. Due to their spatial distribution and sampling intensity, pre-felling inventories are a potential source of ground level data that could help reduce this uncertainty at larger spatial scales. Further, exploring the factors known to influence tropical forest biomass, such as wood density and large tree density, will improve our knowledge of biomass distribution across tropical regions. Here, we evaluate (1) the variability of wood density and (2) the variability of AGB across five ecosystems of Costa Rica. Using forest management (pre-felling) inventories we found that, of the regions studied, Huetar Norte had the highest mean wood density of trees with a diameter at breast height (DBH) greater than or equal to 30 cm, 0.623 ± 0.182 g cm -3 (mean ± standard deviation). Although the greatest wood density was observed in Huetar Norte, the highest mean estimated AGB (EAGB) of trees with a DBH greater than or equal to 30 cm was observed in Osa peninsula (173.47 ± 60.23 Mg ha -1 ). The density of large trees explained approximately 50% of EAGB variability across the five ecosystems studied. Comparing our study's EAGB to published estimates reveals that, in the regions of Costa Rica where AGB has been previously sampled, our forest management data produced similar values. This study presents the most spatially rich analysis of ground level AGB data in Costa Rica to date. Using forest management data, we found that EAGB within and among five Costa Rican ecosystems is highly variable. Combining commercial logging inventories with ecological plots will provide a more representative ground level dataset for the calibration of the models and remotely sensed data used to EAGB at regional and national scales. Additionally, because the non-protected areas of the tropics offer the greatest opportunity to reduce rates of deforestation and forest degradation, logging inventories offer a promising source of data to support mechanisms such as the United Nations REDD + (Reducing Emissions from Tropical Deforestation and Degradation) program.

A forward-looking, national-scale remote sensing-based model of tidal marsh aboveground carbon stocks

NASA Astrophysics Data System (ADS)

Holmquist, J. R.; Byrd, K. B.; Ballanti, L.; Nguyen, D.; Simard, M.; Windham-Myers, L.; Thomas, N.

2017-12-01

Remote sensing based maps of tidal marshes, both of their extents and carbon stocks, have the potential to play a key role in conducting greenhouse gas inventories and implementing climate mitigation policies. Our goal was to generate a single remote sensing model of tidal marsh aboveground biomass and carbon that represents nationally diverse tidal marshes within the conterminous United States (CONUS). To meet this objective we developed the first national-scale dataset of aboveground tidal marsh biomass, species composition, and aboveground plant carbon content (%C) from six CONUS regions: Cape Cod, MA, Chesapeake Bay, MD, Everglades, FL, Mississippi Delta, LA, San Francisco Bay, CA, and Puget Sound, WA. Using the random forest algorithm we tested Sentinel-1 radar backscatter metrics and Landsat vegetation indices as predictors of biomass. The final model, driven by six Landsat vegetation indices and with the soil adjusted vegetation index as the most important (n=409, RMSE=310 g/m2, 10.3% normalized RMSE), successfully predicted biomass and carbon for a range of marsh plant functional types defined by height, leaf angle and growth form. Model error was reduced by scaling field measured biomass by Landsat fraction green vegetation derived from object-based classification of National Agriculture Imagery Program imagery. We generated 30m resolution biomass maps for estuarine and palustrine emergent tidal marshes as indicated by a modified NOAA Coastal Change Analysis Program map for each region. With a mean plant %C of 44.1% (n=1384, 95% C.I.=43.99% - 44.37%) we estimated mean aboveground carbon densities (Mg/ha) and total carbon stocks for each wetland type for each region. Louisiana palustrine emergent marshes had the highest C density (2.67 ±0.08 Mg/ha) of all regions, while San Francisco Bay brackish/saline marshes had the highest C density of all estuarine emergent marshes (2.03 ±0.06 Mg/ha). This modeling and data synthesis effort will allow for aboveground C stocks in tidal marshes to be included for the first time in the 2018 U.S. EPA Greenhouse Gas Inventory for coastal wetlands. As technical barriers have been reduced through the availability of free post-processed satellite data, cloud computing platforms and open source software, this approach can potentially be applied globally as well.

Changing Amazon biomass and the role of atmospheric CO2 concentration, climate, and land use

NASA Astrophysics Data System (ADS)

Almeida Castanho, Andrea D.; Galbraith, David; Zhang, Ke; Coe, Michael T.; Costa, Marcos H.; Moorcroft, Paul

2016-01-01

The Amazon tropical evergreen forest is an important component of the global carbon budget. Its forest floristic composition, structure, and function are sensitive to changes in climate, atmospheric composition, and land use. In this study biomass and productivity simulated by three dynamic global vegetation models (Integrated Biosphere Simulator, Ecosystem Demography Biosphere Model, and Joint UK Land Environment Simulator) for the period 1970-2008 are compared with observations from forest plots (Rede Amazónica de Inventarios Forestales). The spatial variability in biomass and productivity simulated by the DGVMs is low in comparison to the field observations in part because of poor representation of the heterogeneity of vegetation traits within the models. We find that over the last four decades the CO2 fertilization effect dominates a long-term increase in simulated biomass in undisturbed Amazonian forests, while land use change in the south and southeastern Amazonia dominates a reduction in Amazon aboveground biomass, of similar magnitude to the CO2 biomass gain. Climate extremes exert a strong effect on the observed biomass on short time scales, but the models are incapable of reproducing the observed impacts of extreme drought on forest biomass. We find that future improvements in the accuracy of DGVM predictions will require improved representation of four key elements: (1) spatially variable plant traits, (2) soil and nutrients mediated processes, (3) extreme event mortality, and (4) sensitivity to climatic variability. Finally, continued long-term observations and ecosystem-scale experiments (e.g. Free-Air CO2 Enrichment experiments) are essential for a better understanding of the changing dynamics of tropical forests.

Plant community variability on a small area in southeastern Montana

Treesearch

James G. MacCracken; Daniel W. Uresk; Richard M. Hansen

1984-01-01

Plant communities are inherently variable due to a number of environmental and biological forces. Canopy cover and aboveground biomass were determined for understory vegetation in plant communities of a prairie grassland-forest ecotone in southeastern Montana. Vegetation units were described using polar ordination and stepwise discriminant analysis. Nine of a total of...

Effects of LiDAR point density and landscape context on the retrieval of urban forest biomass

NASA Astrophysics Data System (ADS)

Singh, K. K.; Chen, G.; McCarter, J. B.; Meentemeyer, R. K.

2014-12-01

Light Detection and Ranging (LiDAR), as an alternative to conventional optical remote sensing, is being increasingly used to accurately estimate aboveground forest biomass ranging from individual tree to stand levels. Recent advancements in LiDAR technology have resulted in higher point densities and better data accuracies, which however pose challenges to the procurement and processing of LiDAR data for large-area assessments. Reducing point density cuts data acquisition costs and overcome computational challenges for broad-scale forest management. However, how does that impact the accuracy of biomass estimation in an urban environment containing a great level of anthropogenic disturbances? The main goal of this study is to evaluate the effects of LiDAR point density on the biomass estimation of remnant forests in the rapidly urbanizing regions of Charlotte, North Carolina, USA. We used multiple linear regression to establish the statistical relationship between field-measured biomass and predictor variables (PVs) derived from LiDAR point clouds with varying densities. We compared the estimation accuracies between the general Urban Forest models (no discrimination of forest type) and the Forest Type models (evergreen, deciduous, and mixed), which was followed by quantifying the degree to which landscape context influenced biomass estimation. The explained biomass variance of Urban Forest models, adjusted R2, was fairly consistent across the reduced point densities with the highest difference of 11.5% between the 100% and 1% point densities. The combined estimates of Forest Type biomass models outperformed the Urban Forest models using two representative point densities (100% and 40%). The Urban Forest biomass model with development density of 125 m radius produced the highest adjusted R2 (0.83 and 0.82 at 100% and 40% LiDAR point densities, respectively) and the lowest RMSE values, signifying the distance impact of development on biomass estimation. Our evaluation suggests that reducing LiDAR point density is a viable solution to regional-scale forest biomass assessment without compromising the accuracy of estimation, which may further be improved using development density.

Specific gravity of woody tissue from lowland Neotropical plants: differences among forest types.

PubMed

Casas, Luisa Fernanda; Aldana, Ana María; Henao-Diaz, Francisco; Villanueva, Boris; Stevenson, Pablo R

2017-05-01

Wood density, or more precisely, wood specific gravity, is an important parameter when estimating aboveground biomass, which has become a central tool for the management and conservation of forests around the world. When using biomass allometric equations for tropical forests, researchers are often required to assume phylogenetic trait conservatism, which allows us to assign genus- and family-level wood specific gravity mean values, to many woody species. The lack of information on this trait for many Neotropical plant species has led to an imprecise estimation of the biomass stored in Neotropical forests. The data presented here has information of woody tissue specific gravity from 2,602 individual stems for 386 species, including trees, lianas, and hemi-epiphytes of lowland tropical forests in Colombia. This data set was produced by us collecting wood cores from woody species in five localities in the Orinoco and Magdalena Basins in Colombia. We found lower mean specific gravity values in várzea than in terra firme and igapó. © 2017 The Authors. Ecology, published by Wiley Periodicals, Inc., on behalf of the Ecological Society of America.

A remote sensing-based model of tidal marsh aboveground carbon stocks for the conterminous United States

NASA Astrophysics Data System (ADS)

Byrd, Kristin B.; Ballanti, Laurel; Thomas, Nathan; Nguyen, Dung; Holmquist, James R.; Simard, Marc; Windham-Myers, Lisamarie

2018-05-01

Remote sensing based maps of tidal marshes, both of their extents and carbon stocks, have the potential to play a key role in conducting greenhouse gas inventories and implementing climate mitigation policies. Our objective was to generate a single remote sensing model of tidal marsh aboveground biomass and carbon that represents nationally diverse tidal marshes within the conterminous United States (CONUS). We developed the first calibration-grade, national-scale dataset of aboveground tidal marsh biomass, species composition, and aboveground plant carbon content (%C) from six CONUS regions: Cape Cod, MA, Chesapeake Bay, MD, Everglades, FL, Mississippi Delta, LA, San Francisco Bay, CA, and Puget Sound, WA. Using the random forest machine learning algorithm, we tested whether imagery from multiple sensors, Sentinel-1 C-band synthetic aperture radar, Landsat, and the National Agriculture Imagery Program (NAIP), can improve model performance. The final model, driven by six Landsat vegetation indices and with the soil adjusted vegetation index as the most important (n = 409, RMSE = 310 g/m2, 10.3% normalized RMSE), successfully predicted biomass for a range of marsh plant functional types defined by height, leaf angle and growth form. Model results were improved by scaling field-measured biomass calibration data by NAIP-derived 30 m fraction green vegetation. With a mean plant carbon content of 44.1% (n = 1384, 95% C.I. = 43.99%-44.37%), we generated regional 30 m aboveground carbon density maps for estuarine and palustrine emergent tidal marshes as indicated by a modified NOAA Coastal Change Analysis Program map. We applied a multivariate delta method to calculate uncertainties in regional carbon densities and stocks that considered standard error in map area, mean biomass and mean %C. Louisiana palustrine emergent marshes had the highest C density (2.67 ± 0.004 Mg/ha) of all regions, while San Francisco Bay brackish/saline marshes had the highest C density of all estuarine emergent marshes (2.03 ± 0.004 Mg/ha). Estimated C stocks for predefined jurisdictional areas ranged from 1023 ± 39 Mg in the Nisqually National Wildlife Refuge in Washington to 507,761 ± 14,822 Mg in the Terrebonne and St. Mary Parishes in Louisiana. This modeling and data synthesis effort will allow for aboveground C stocks in tidal marshes to be included in the coastal wetland section of the U.S. National Greenhouse Gas Inventory. With the increased availability of free post-processed satellite data, we provide a tractable means of modeling tidal marsh aboveground biomass and carbon at the global extent as well.

Landscape-Scale Controls on Aboveground Forest Carbon Stocks on the Osa Peninsula, Costa Rica

PubMed Central

Taylor, Philip; Asner, Gregory; Dahlin, Kyla; Anderson, Christopher; Knapp, David; Martin, Roberta; Mascaro, Joseph; Chazdon, Robin; Cole, Rebecca; Wanek, Wolfgang; Hofhansl, Florian; Malavassi, Edgar; Vilchez-Alvarado, Braulio; Townsend, Alan

2015-01-01

Tropical forests store large amounts of carbon in tree biomass, although the environmental controls on forest carbon stocks remain poorly resolved. Emerging airborne remote sensing techniques offer a powerful approach to understand how aboveground carbon density (ACD) varies across tropical landscapes. In this study, we evaluate the accuracy of the Carnegie Airborne Observatory (CAO) Light Detection and Ranging (LiDAR) system to detect top-of-canopy tree height (TCH) and ACD across the Osa Peninsula, Costa Rica. LiDAR and field-estimated TCH and ACD were highly correlated across a wide range of forest ages and types. Top-of-canopy height (TCH) reached 67 m, and ACD surpassed 225 Mg C ha-1, indicating both that airborne CAO LiDAR-based estimates of ACD are accurate in tall, high-biomass forests and that the Osa Peninsula harbors some of the most carbon-rich forests in the Neotropics. We also examined the relative influence of lithologic, topoedaphic and climatic factors on regional patterns in ACD, which are known to influence ACD by regulating forest productivity and turnover. Analyses revealed a spatially nested set of factors controlling ACD patterns, with geologic variation explaining up to 16% of the mapped ACD variation at the regional scale, while local variation in topographic slope explained an additional 18%. Lithologic and topoedaphic factors also explained more ACD variation at 30-m than at 100-m spatial resolution, suggesting that environmental filtering depends on the spatial scale of terrain variation. Our result indicate that patterns in ACD are partially controlled by spatial variation in geologic history and geomorphic processes underpinning topographic diversity across landscapes. ACD also exhibited spatial autocorrelation, which may reflect biological processes that influence ACD, such as the assembly of species or phenotypes across the landscape, but additional research is needed to resolve how abiotic and biotic factors contribute to ACD variation across high biomass, high diversity tropical landscapes. PMID:26061884

[Spatial distribution of aboveground biomass of shrubs in Tianlaochi catchment of the Qilian Mountains].

PubMed

Liang, Bei; Di, Li; Zhao, Chuan-Yan; Peng, Shou-Zhang; Peng, Huan-Hua; Wang, Chao

2014-02-01

This study estimated the spatial distribution of the aboveground biomass of shrubs in the Tianlaochi catchment of Qilian Mountains based on the field survey and remote sensing data. A relationship model of the aboveground biomass and its feasibly measured factors (i. e. , canopy perimeter and plant height) was built. The land use was classified by object-oriented technique with the high resolution image (GeoEye-1) of the study area, and the distribution of shrub coverage was extracted. Then the total aboveground biomass of shrubs in the study area was estimated by the relationship model with the distribution of shrub coverage. The results showed that the aboveground biomass of shrubs in the study area was 1.8 x 10(3) t and the aboveground biomass per unit area was 1598.45 kg x m(-2). The distribution of shrubs mainly was at altitudes of 3000-3700 m, and the aboveground biomass of shrubs on the sunny slope (1.15 x 10(3) t) was higher than that on the shady slope (0.65 x 10(3) t).

[Biomass allometric equations of nine common tree species in an evergreen broadleaved forest of subtropical China].

PubMed

Zuo, Shu-di; Ren, Yin; Weng, Xian; Ding, Hong-feng; Luo, Yun-jian

2015-02-01

Biomass allometric equation (BAE) considered as a simple and reliable method in the estimation of forest biomass and carbon was used widely. In China, numerous studies focused on the BAEs for coniferous forest and pure broadleaved forest, and generalized BAEs were frequently used to estimate the biomass and carbon of mixed broadleaved forest, although they could induce large uncertainty in the estimates. In this study, we developed the species-specific and generalized BAEs using biomass measurement for 9 common broadleaved trees (Castanopsis fargesii, C. lamontii, C. tibetana, Lithocarpus glaber, Sloanea sinensis, Daphniphyllum oldhami, Alniphyllum fortunei, Manglietia yuyuanensis, and Engelhardtia fenzlii) of subtropical evergreen broadleaved forest, and compared differences in species-specific and generalized BAEs. The results showed that D (diameter at breast height) was a better independent variable in estimating the biomass of branch, leaf, root, aboveground section and total tree than a combined variable (D2 H) of D and H (tree height) , but D2H was better than D in estimating stem biomass. R2 (coefficient of determination) values of BAEs for 6 species decreased when adding H as the second independent variable into D- only BAEs, where R2 value for S. sinensis decreased by 5.6%. Compared with generalized D- and D2H-based BAEs, standard errors of estimate (SEE) of BAEs for 8 tree species decreased, and similar decreasing trend was observed for different components, where SEEs of the branch decreased by 13.0% and 20.3%. Therefore, the biomass carbon storage and its dynamic estimates were influenced largely by tree species and model types. In order to improve the accuracy of the estimates of biomass and carbon, we should consider the differences in tree species and model types.

Tree Productivity Enhanced with Conversion from Forest to Urban Land Covers.

PubMed

Briber, Brittain M; Hutyra, Lucy R; Reinmann, Andrew B; Raciti, Steve M; Dearborn, Victoria K; Holden, Christopher E; Dunn, Allison L

2015-01-01

Urban areas are expanding, changing the structure and productivity of landscapes. While some urban areas have been shown to hold substantial biomass, the productivity of these systems is largely unknown. We assessed how conversion from forest to urban land uses affected both biomass structure and productivity across eastern Massachusetts. We found that urban land uses held less than half the biomass of adjacent forest expanses with a plot level mean biomass density of 33.5 ± 8.0 Mg C ha(-1). As the intensity of urban development increased, the canopy cover, stem density, and biomass decreased. Analysis of Quercus rubra tree cores showed that tree-level basal area increment nearly doubled following development, increasing from 17.1 ± 3.0 to 35.8 ± 4.7 cm(2) yr(-1). Scaling the observed stem densities and growth rates within developed areas suggests an aboveground biomass growth rate of 1.8 ± 0.4 Mg C ha(-1) yr(-1), a growth rate comparable to nearby, intact forests. The contrasting high growth rates and lower biomass pools within urban areas suggest a highly dynamic ecosystem with rapid turnover. As global urban extent continues to grow, cities consider climate mitigation options, and as the verification of net greenhouse gas emissions emerges as critical for policy, quantifying the role of urban vegetation in regional-to-global carbon budgets will become ever more important.

Tree Productivity Enhanced with Conversion from Forest to Urban Land Covers

PubMed Central

Briber, Brittain M.; Hutyra, Lucy R.; Reinmann, Andrew B.; Raciti, Steve M.; Dearborn, Victoria K.; Holden, Christopher E.; Dunn, Allison L.

2015-01-01

Urban areas are expanding, changing the structure and productivity of landscapes. While some urban areas have been shown to hold substantial biomass, the productivity of these systems is largely unknown. We assessed how conversion from forest to urban land uses affected both biomass structure and productivity across eastern Massachusetts. We found that urban land uses held less than half the biomass of adjacent forest expanses with a plot level mean biomass density of 33.5 ± 8.0 Mg C ha-1. As the intensity of urban development increased, the canopy cover, stem density, and biomass decreased. Analysis of Quercus rubra tree cores showed that tree-level basal area increment nearly doubled following development, increasing from 17.1 ± 3.0 to 35.8 ± 4.7 cm2 yr-1. Scaling the observed stem densities and growth rates within developed areas suggests an aboveground biomass growth rate of 1.8 ± 0.4 Mg C ha-1 yr-1, a growth rate comparable to nearby, intact forests. The contrasting high growth rates and lower biomass pools within urban areas suggest a highly dynamic ecosystem with rapid turnover. As global urban extent continues to grow, cities consider climate mitigation options, and as the verification of net greenhouse gas emissions emerges as critical for policy, quantifying the role of urban vegetation in regional-to-global carbon budgets will become ever more important. PMID:26302444

The contribution of trees outside forests to national tree biomass and carbon stocks--a comparative study across three continents.

PubMed

Schnell, Sebastian; Altrell, Dan; Ståhl, Göran; Kleinn, Christoph

2015-01-01

In contrast to forest trees, trees outside forests (TOF) often are not included in the national monitoring of tree resources. Consequently, data about this particular resource is rare, and available information is typically fragmented across the different institutions and stakeholders that deal with one or more of the various TOF types. Thus, even if information is available, it is difficult to aggregate data into overall national statistics. However, the National Forest Monitoring and Assessment (NFMA) programme of FAO offers a unique possibility to study TOF resources because TOF are integrated by default into the NFMA inventory design. We have analysed NFMA data from 11 countries across three continents. For six countries, we found that more than 10% of the national above-ground tree biomass was actually accumulated outside forests. The highest value (73%) was observed for Bangladesh (total forest cover 8.1%, average biomass per hectare in forest 33.4 t ha(-1)) and the lowest (3%) was observed for Zambia (total forest cover 63.9%, average biomass per hectare in forest 32 t ha(-1)). Average TOF biomass stocks were estimated to be smaller than 10 t ha(-1). However, given the large extent of non-forest areas, these stocks sum up to considerable quantities in many countries. There are good reasons to overcome sectoral boundaries and to extend national forest monitoring programmes on a more systematic basis that includes TOF. Such an approach, for example, would generate a more complete picture of the national tree biomass. In the context of climate change mitigation and adaptation, international climate mitigation programmes (e.g. Clean Development Mechanism and Reduced Emission from Deforestation and Degradation) focus on forest trees without considering the impact of TOF, a consideration this study finds crucial if accurate measurements of national tree biomass and carbon pools are required.

Multi-stage approach to estimate forest biomass in degraded area by fire and selective logging

NASA Astrophysics Data System (ADS)

Santos, E. G.; Shimabukuro, Y. E.; Arai, E.; Duarte, V.; Jorge, A.; Gasparini, K.

2017-12-01

The Amazon forest has been the target of several threats throughout the years. Anthropogenic disturbances in the region can significantly alter this environment, affecting directly the dynamics and structure of tropical forests. Monitoring these threats of forest degradation across the Amazon is of paramount to understand the impacts of disturbances in the tropics. With the advance of new technologies such as Light Detection and Ranging (LiDAR) the quantification and development of methodologies to monitor forest degradation in the Amazon is possible and may bring considerable contributions to this topic. The objective of this study was to use remote sensing data to assess and estimate the aboveground biomass (AGB) across different levels of degradation (fire and selective logging) using multi-stage approach between airborne LiDAR and orbital image. The study area is in the northern part of the state of Mato Grosso, Brazil. It is predominantly characterized by agricultural land and remnants of the Amazon Forest intact and degraded by either anthropic or natural reasons (selective logging and/or fire). More specifically, the study area corresponds to path/row 226/69 of OLI/Landsat 8 image. With a forest mask generated from the multi-resolution segmentation, agriculture and forest areas, forest biomass was calculated from LiDAR data and correlated with texture images, vegetation indices and fraction images by Linear Spectral Unmixing of OLI/Landsat 8 image and extrapolated to the entire scene 226/69 and validated with field inventories. The results showed that there is a moderate to strong correlation between forest biomass and texture data, vegetation indices and fraction images. With that, it is possible to extract biomass information and create maps using optical data, specifically by combining vegetation indices, which contain forest greening information with texture data that contains forest structure information. Then it was possible to extrapolate the biomass to the entire scene (226/69) from the optical data and to obtain an overview of the biomass distribution throughout the area.

Mapping SOC (Soil Organic Carbon) using LiDAR-derived vegetation indices in a random forest regression model

NASA Astrophysics Data System (ADS)

Will, R. M.; Glenn, N. F.; Benner, S. G.; Pierce, J. L.; Spaete, L.; Li, A.

2015-12-01

Quantifying SOC (Soil Organic Carbon) storage in complex terrain is challenging due to high spatial variability. Generally, the challenge is met by transforming point data to the entire landscape using surrogate, spatially-distributed, variables like elevation or precipitation. In many ecosystems, remotely sensed information on above-ground vegetation (e.g. NDVI) is a good predictor of below-ground carbon stocks. In this project, we are attempting to improve this predictive method by incorporating LiDAR-derived vegetation indices. LiDAR provides a mechanism for improved characterization of aboveground vegetation by providing structural parameters such as vegetation height and biomass. In this study, a random forest model is used to predict SOC using a suite of LiDAR-derived vegetation indices as predictor variables. The Reynolds Creek Experimental Watershed (RCEW) is an ideal location for a study of this type since it encompasses a strong elevation/precipitation gradient that supports lower biomass sagebrush ecosystems at low elevations and forests with more biomass at higher elevations. Sagebrush ecosystems composed of Wyoming, Low and Mountain Sagebrush have SOC values ranging from .4 to 1% (top 30 cm), while higher biomass ecosystems composed of aspen, juniper and fir have SOC values approaching 4% (top 30 cm). Large differences in SOC have been observed between canopy and interspace locations and high resolution vegetation information is likely to explain plot scale variability in SOC. Mapping of the SOC reservoir will help identify underlying controls on SOC distribution and provide insight into which processes are most important in determining SOC in semi-arid mountainous regions. In addition, airborne LiDAR has the potential to characterize vegetation communities at a high resolution and could be a tool for improving estimates of SOC at larger scales.

Study of the radiocesium dynamics in the Fukushima forest ecosystems

NASA Astrophysics Data System (ADS)

Yoschenko, Vasyl; Konoplev, Alexei; Takase, Tsugiko; Nanba, Kenji; Onda, Yuichi; Zheleznyak, Mark; Kivva, Sergii

2016-04-01

Accident at Fukushima Dai-ichi NPP on March 11, 2011, has resulted in release into the environment of large amounts of radiocesium (134Cs and 137Cs) and in radioactive contamination of terrestrial and aquatic ecosystems. Up to 2/3 of the most contaminated territory in Fukushima prefecture is covered with forests, and efforts aimed at revitalization of this territory should include, therefore, elaboration of the forestry strategy. In particular, understanding of the radiocesium dynamics in the ecosystem compartments is necessary for the reliable long-term prognosis. Numerous studies revealed and quantified the key processes governing radiocesium redistribution in Fukushima forests at the early stage after the accident, when initially intercepted radiocesium was gradually transported from the trees' crowns to the soil surface and profile with precipitations and litterfall, and the general trend was a decrease of the radiocesium total inventory in the forest biomass. However, at the later stage, the radiocesium activities in the biomass compartments can increase due to its root uptake from the soil profile; the two major processes, radionuclide root uptake and its return to soil, will determine the future radiocesium levels in the forest compartments. Objectives of our study were characterization of the radiocesium distribution at the beginning of the late stage, revealing its dynamics and parameterization of the above-mentioned fluxes for prognosis of the radiocesium long-term redistribution in the typical Fukushima forest ecosystems. The study started at one experimental site (Yamakiya district, Kawamata town, Fukushima Prefecture) in the spring of 2014; to the moment, it has been continuing at several experimental sites in the Fukushima zone characterized by different species composition and soil-landscape conditions. For the typical Japanese cedar (Cryptomeria japonica) and Japanese red pine (Pinus Densiflora) forests, we determined distributions of radiocesium in the ecosystems and in the aboveground biomass compartments by the end of 2014 or 2015. At the best studied Yamakiya site the radiocesium distributions were determined for the two consequent years. In 2014, about 74% of the total radiocesium inventory at this site was localized in soil, 20% was in the litter, and only 6% was associated with the aboveground biomass. Within the tree compartments, the largest radiocesium activity fraction, about 46%, was observed in old foliage. The aggregate soil-to-wood transfer factor was 0.0011 m2/kg d.w. Based on the radiocesium activities measured in the biomass compartments of the studied ecosystems, we derived the estimates of its main fluxes and compared to the apparent dynamics of its inventories in biomass at the Yamakiya site.

Predicting the responses of forest distribution and aboveground biomass to climate change under RCP scenarios in southern China.

PubMed

Dai, Erfu; Wu, Zhuo; Ge, Quansheng; Xi, Weimin; Wang, Xiaofan

2016-11-01

In the past three decades, our global climate has been experiencing unprecedented warming. This warming has and will continue to significantly influence the structure and function of forest ecosystems. While studies have been conducted to explore the possible responses of forest landscapes to future climate change, the representative concentration pathways (RCPs) scenarios under the framework of the Coupled Model Intercomparison Project Phase 5 (CMIP5) have not been widely used in quantitative modeling research of forest landscapes. We used LANDIS-II, a forest dynamic landscape model, coupled with a forest ecosystem process model (PnET-II), to simulate spatial interactions and ecological succession processes under RCP scenarios, RCP2.6, RCP4.5 and RCP8.5, respectively. We also modeled a control scenario of extrapolating current climate conditions to examine changes in distribution and aboveground biomass (AGB) among five different forest types for the period of 2010-2100 in Taihe County in southern China, where subtropical coniferous plantations dominate. The results of the simulation show that climate change will significantly influence forest distribution and AGB. (i) Evergreen broad-leaved forests will expand into Chinese fir and Chinese weeping cypress forests. The area percentages of evergreen broad-leaved forests under RCP2.6, RCP4.5, RCP8.5 and the control scenarios account for 18.25%, 18.71%, 18.85% and 17.46% of total forest area, respectively. (ii) The total AGB under RCP4.5 will reach its highest level by the year 2100. Compared with the control scenarios, the total AGB under RCP2.6, RCP4.5 and RCP8.5 increases by 24.1%, 64.2% and 29.8%, respectively. (iii) The forest total AGB increases rapidly at first and then decreases slowly on the temporal dimension. (iv) Even though the fluctuation patterns of total AGB will remain consistent under various future climatic scenarios, there will be certain responsive differences among various forest types. © 2016 John Wiley & Sons Ltd.

Anthropogenic Land-use Change and the Dynamics of Amazon Forest Biomass

NASA Technical Reports Server (NTRS)

Laurance, William F.

2004-01-01

This project was focused on assessing the effects of prevailing land uses, such as habitat fragmentation, selective logging, and fire, on biomass and carbon storage in Amazonian forests, and on the dynamics of carbon sequestration in regenerating forests. Ancillary goals included developing GIs models to help predict the future condition of Amazonian forests, and assessing the effects of anthropogenic climate change and ENS0 droughts on intact and fragmented forests. Ground-based studies using networks of permanent plots were linked with remote-sensing data (including Landsat TM and AVHRR) at regional scales, and higher-resolution techniques (IKONOS imagery, videography, LIDAR, aerial photographs) at landscape and local scales. The project s specific goals were quite eclectic and included: Determining the effects of habitat fragmentation on forest dynamics, floristic composition, and the various components of above- and below-ground biomass. Assessing historical and physical factors that affect trajectories of forest regeneration and carbon sequestration on abandoned lands. Extrapolating results from local studies of biomass dynamics in fragmented and regenerating forests to landscape and regional scales in Amazonia, using remote sensing and GIS. Testing the hypothesis that intact Amazonian forests are functioning as a significant carbon sink. Examining destructive synergisms between forest fragmentation and fire. Assessing the short-term impacts of selective logging on aboveground biomass. Developing GIS models that integrate current spatial data on forest cover, deforestation, logging, mining, highway and roads, navigable rivers, vulnerability to wild fires, protected areas, and existing and planned infrastructure projects, in an effort to predict the future condition of Brazilian Amazonian forests over the next 20-25 years. Devising predictive spatial models to assess the influence of varied biophysical and anthropogenic predictors on Amazonian deforestation.

Seventy years of continuous encroachment substantially increases 'blue carbon' capacity as mangroves replace intertidal salt marshes.

PubMed

Kelleway, Jeffrey J; Saintilan, Neil; Macreadie, Peter I; Skilbeck, Charles G; Zawadzki, Atun; Ralph, Peter J

2016-03-01

Shifts in ecosystem structure have been observed over recent decades as woody plants encroach upon grasslands and wetlands globally. The migration of mangrove forests into salt marsh ecosystems is one such shift which could have important implications for global 'blue carbon' stocks. To date, attempts to quantify changes in ecosystem function are essentially constrained to climate-mediated pulses (30 years or less) of encroachment occurring at the thermal limits of mangroves. In this study, we track the continuous, lateral encroachment of mangroves into two south-eastern Australian salt marshes over a period of 70 years and quantify corresponding changes in biomass and belowground C stores. Substantial increases in biomass and belowground C stores have resulted as mangroves replaced salt marsh at both marine and estuarine sites. After 30 years, aboveground biomass was significantly higher than salt marsh, with biomass continuing to increase with mangrove age. Biomass increased at the mesohaline river site by 130 ± 18 Mg biomass km(-2)  yr(-1) (mean ± SE), a 2.5 times higher rate than the marine embayment site (52 ± 10 Mg biomass km(-2) yr(-1) ), suggesting local constraints on biomass production. At both sites, and across all vegetation categories, belowground C considerably outweighed aboveground biomass stocks, with belowground C stocks increasing at up to 230 ± 62 Mg C km(-2) yr(-1) (± SE) as mangrove forests developed. Over the past 70 years, we estimate mangrove encroachment may have already enhanced intertidal biomass by up to 283 097 Mg and belowground C stocks by over 500 000 Mg in the state of New South Wales alone. Under changing climatic conditions and rising sea levels, global blue carbon storage may be enhanced as mangrove encroachment becomes more widespread, thereby countering global warming. © 2015 John Wiley & Sons Ltd.

Modeling aboveground biomass of Tamarix ramosissima in the Arkansas River Basin of Southeastern Colorado, USA

USGS Publications Warehouse

Evangelista, P.; Kumar, S.; Stohlgren, T.J.; Crall, A.W.; Newman, G.J.

2007-01-01

Predictive models of aboveground biomass of nonnative Tamarix ramosissima of various sizes were developed using destructive sampling techniques on 50 individuals and four 100-m2 plots. Each sample was measured for average height (m) of stems and canopy area (m2) prior to cutting, drying, and weighing. Five competing regression models (P < 0.05) were developed to estimate aboveground biomass of T. ramosissima using average height and/or canopy area measurements and were evaluated using Akaike's Information Criterion corrected for small sample size (AICc). Our best model (AICc = -148.69, ??AICc = 0) successfully predicted T. ramosissima aboveground biomass (R2 = 0.97) and used average height and canopy area as predictors. Our 2nd-best model, using the same predictors, was also successful in predicting aboveground biomass (R2 = 0.97, AICc = -131.71, ??AICc = 16.98). A 3rd model demonstrated high correlation between only aboveground biomass and canopy area (R2 = 0.95), while 2 additional models found high correlations between aboveground biomass and average height measurements only (R2 = 0.90 and 0.70, respectively). These models illustrate how simple field measurements, such as height and canopy area, can be used in allometric relationships to accurately predict aboveground biomass of T. ramosissima. Although a correction factor may be necessary for predictions at larger scales, the models presented will prove useful for many research and management initiatives.

The carbon cycle and hurricanes in the United States between 1900 and 2011.

PubMed

Dahal, Devendra; Liu, Shuguang; Oeding, Jennifer

2014-06-06

Hurricanes cause severe impacts on forest ecosystems in the United States. These events can substantially alter the carbon biogeochemical cycle at local to regional scales. We selected all tropical storms and more severe events that made U.S. landfall between 1900 and 2011 and used hurricane best track database, a meteorological model (HURRECON), National Land Cover Database (NLCD), U. S. Department of Agirculture Forest Service biomass dataset, and pre- and post-MODIS data to quantify individual event and annual biomass mortality. Our estimates show an average of 18.2 TgC/yr of live biomass mortality for 1900-2011 in the US with strong spatial and inter-annual variability. Results show Hurricane Camille in 1969 caused the highest aboveground biomass mortality with 59.5 TgC. Similarly 1954 had the highest annual mortality with 68.4 TgC attributed to landfalling hurricanes. The results presented are deemed useful to further investigate historical events, and the methods outlined are potentially beneficial to quantify biomass loss in future events.

Hyperspectral forest monitoring and imaging implications

NASA Astrophysics Data System (ADS)

Goodenough, David G.; Bannon, David

2014-05-01

The forest biome is vital to the health of the earth. Canada and the United States have a combined forest area of 4.68 Mkm2. The monitoring of these forest resources has become increasingly complex. Hyperspectral remote sensing can provide a wealth of improved information products to land managers to make more informed decisions. Research in this area has demonstrated that hyperspectral remote sensing can be used to create more accurate products for forest inventory (major forest species), forest health, foliar biochemistry, biomass, and aboveground carbon. Operationally there is a requirement for a mix of airborne and satellite approaches. This paper surveys some methods and results in hyperspectral sensing of forests and discusses the implications for space initiatives with hyperspectral sensing

Geomorphology, disturbance, and the soil and vegetation of two subtropical wet steepland watersheds of Puerto Rico.

Treesearch

Ariel E. Lugo F.N. Scatena

1995-01-01

Relationships between landforms, soil nutrients, forest structure, and the relative importance of different disturbances were quantified in two subtropical wet steepland watersheds in Puerto Rico. Ridges had fewer landslides and treefall gaps, more above-ground biomass, older aged stands, and greater species richness than other landscape positions. Ridge soils had...

Optimal Atmospheric Correction for Above-Ground Forest Biomass Estimation with the ETM+ Remote Sensor.

PubMed

Nguyen, Hieu Cong; Jung, Jaehoon; Lee, Jungbin; Choi, Sung-Uk; Hong, Suk-Young; Heo, Joon

2015-07-31

The reflectance of the Earth's surface is significantly influenced by atmospheric conditions such as water vapor content and aerosols. Particularly, the absorption and scattering effects become stronger when the target features are non-bright objects, such as in aqueous or vegetated areas. For any remote-sensing approach, atmospheric correction is thus required to minimize those effects and to convert digital number (DN) values to surface reflectance. The main aim of this study was to test the three most popular atmospheric correction models, namely (1) Dark Object Subtraction (DOS); (2) Fast Line-of-sight Atmospheric Analysis of Spectral Hypercubes (FLAASH) and (3) the Second Simulation of Satellite Signal in the Solar Spectrum (6S) and compare them with Top of Atmospheric (TOA) reflectance. By using the k-Nearest Neighbor (kNN) algorithm, a series of experiments were conducted for above-ground forest biomass (AGB) estimations of the Gongju and Sejong region of South Korea, in order to check the effectiveness of atmospheric correction methods for Landsat ETM+. Overall, in the forest biomass estimation, the 6S model showed the bestRMSE's, followed by FLAASH, DOS and TOA. In addition, a significant improvement of RMSE by 6S was found with images when the study site had higher total water vapor and temperature levels. Moreover, we also tested the sensitivity of the atmospheric correction methods to each of the Landsat ETM+ bands. The results confirmed that 6S dominates the other methods, especially in the infrared wavelengths covering the pivotal bands for forest applications. Finally, we suggest that the 6S model, integrating water vapor and aerosol optical depth derived from MODIS products, is better suited for AGB estimation based on optical remote-sensing data, especially when using satellite images acquired in the summer during full canopy development.

Selective logging: does the imprint remain on tree structure and composition after 45 years?

PubMed

Osazuwa-Peters, Oyomoare L; Chapman, Colin A; Zanne, Amy E

2015-01-01

Selective logging of tropical forests is increasing in extent and intensity. The duration over which impacts of selective logging persist, however, remains an unresolved question, particularly for African forests. Here, we investigate the extent to which a past selective logging event continues to leave its imprint on different components of an East African forest 45 years later. We inventoried 2358 stems ≥10 cm in diameter in 26 plots (200 m × 10 m) within a 5.2 ha area in Kibale National Park, Uganda, in logged and unlogged forest. In these surveys, we characterized the forest light environment, taxonomic composition, functional trait composition using three traits (wood density, maximum height and maximum diameter) and forest structure based on three measures (stem density, total basal area and total above-ground biomass). In comparison to unlogged forests, selectively logged forest plots in Kibale National Park on average had higher light levels, different structure characterized by lower stem density, lower total basal area and lower above-ground biomass, and a distinct taxonomic composition driven primarily by changes in the relative abundance of species. Conversely, selectively logged forest plots were like unlogged plots in functional composition, having similar community-weighted mean values for wood density, maximum height and maximum diameter. This similarity in functional composition irrespective of logging history may be due to functional recovery of logged forest or background changes in functional attributes of unlogged forest. Despite the passage of 45 years, the legacy of selective logging on the tree community in Kibale National Park is still evident, as indicated by distinct taxonomic and structural composition and reduced carbon storage in logged forest compared with unlogged forest. The effects of selective logging are exerted via influences on tree demography rather than functional trait composition.

Selective logging: does the imprint remain on tree structure and composition after 45 years?

PubMed Central

Osazuwa-Peters, Oyomoare L.; Chapman, Colin A.; Zanne, Amy E.

2015-01-01

Selective logging of tropical forests is increasing in extent and intensity. The duration over which impacts of selective logging persist, however, remains an unresolved question, particularly for African forests. Here, we investigate the extent to which a past selective logging event continues to leave its imprint on different components of an East African forest 45 years later. We inventoried 2358 stems ≥10 cm in diameter in 26 plots (200 m × 10 m) within a 5.2 ha area in Kibale National Park, Uganda, in logged and unlogged forest. In these surveys, we characterized the forest light environment, taxonomic composition, functional trait composition using three traits (wood density, maximum height and maximum diameter) and forest structure based on three measures (stem density, total basal area and total above-ground biomass). In comparison to unlogged forests, selectively logged forest plots in Kibale National Park on average had higher light levels, different structure characterized by lower stem density, lower total basal area and lower above-ground biomass, and a distinct taxonomic composition driven primarily by changes in the relative abundance of species. Conversely, selectively logged forest plots were like unlogged plots in functional composition, having similar community-weighted mean values for wood density, maximum height and maximum diameter. This similarity in functional composition irrespective of logging history may be due to functional recovery of logged forest or background changes in functional attributes of unlogged forest. Despite the passage of 45 years, the legacy of selective logging on the tree community in Kibale National Park is still evident, as indicated by distinct taxonomic and structural composition and reduced carbon storage in logged forest compared with unlogged forest. The effects of selective logging are exerted via influences on tree demography rather than functional trait composition. PMID:27293697

Random forest regression modelling for forest aboveground biomass estimation using RISAT-1 PolSAR and terrestrial LiDAR data

NASA Astrophysics Data System (ADS)

Mangla, Rohit; Kumar, Shashi; Nandy, Subrata

2016-05-01

SAR and LiDAR remote sensing have already shown the potential of active sensors for forest parameter retrieval. SAR sensor in its fully polarimetric mode has an advantage to retrieve scattering property of different component of forest structure and LiDAR has the capability to measure structural information with very high accuracy. This study was focused on retrieval of forest aboveground biomass (AGB) using Terrestrial Laser Scanner (TLS) based point clouds and scattering property of forest vegetation obtained from decomposition modelling of RISAT-1 fully polarimetric SAR data. TLS data was acquired for 14 plots of Timli forest range, Uttarakhand, India. The forest area is dominated by Sal trees and random sampling with plot size of 0.1 ha (31.62m*31.62m) was adopted for TLS and field data collection. RISAT-1 data was processed to retrieve SAR data based variables and TLS point clouds based 3D imaging was done to retrieve LiDAR based variables. Surface scattering, double-bounce scattering, volume scattering, helix and wire scattering were the SAR based variables retrieved from polarimetric decomposition. Tree heights and stem diameters were used as LiDAR based variables retrieved from single tree vertical height and least square circle fit methods respectively. All the variables obtained for forest plots were used as an input in a machine learning based Random Forest Regression Model, which was developed in this study for forest AGB estimation. Modelled output for forest AGB showed reliable accuracy (RMSE = 27.68 t/ha) and a good coefficient of determination (0.63) was obtained through the linear regression between modelled AGB and field-estimated AGB. The sensitivity analysis showed that the model was more sensitive for the major contributed variables (stem diameter and volume scattering) and these variables were measured from two different remote sensing techniques. This study strongly recommends the integration of SAR and LiDAR data for forest AGB estimation.

The effect of wildfire and clear-cutting on above-ground biomass, foliar C to N ratios and fiber content throughout succession: Implications for forage quality in woodland caribou (Rangifer tarandus caribou)

NASA Astrophysics Data System (ADS)

Mallon, E. E.; Turetsky, M.; Thompson, I.; Noland, T. L.; Wiebe, P.

2013-12-01

Disturbance is known to play an important role in maintaining the productivity and biodiversity of boreal forest ecosystems. Moderate to low frequency disturbance is responsible for regeneration opportunities creating a mosaic of habitats and successional trajectories. However, large-scale deforestation and increasing wildfire frequencies exacerbate habitat loss and influence biogeochemical cycles. This has raised concern about the quality of the under-story vegetation post-disturbance and whether this may impact herbivores, especially those vulnerable to change. Forest-dwelling caribou (Rangifer tarandus caribou) are declining in several regions of Canada and are currently listed as a species at risk by COSEWIC. Predation and landscape alteration are viewed as the two main threats to woodland caribou. This has resulted in caribou utilizing low productivity peatlands as refuge and the impact of this habitat selection on their diet quality is not well understood. Therefore there are two themes in the study, 1) Forage quantity: above-ground biomass and productivity and 2) Forage quality: foliar N and C to N ratios and % fiber. The themes are addressed in three questions: 1) How does forage quantity and quality vary between upland forests and peatlands? 2) How does wildfire affect the availability and nutritional quality of forage items? 3) How does forage quality vary between sites recovering from wildfire versus timber harvest? Research sites were located in the Auden region north of Geraldton, ON. This landscape was chosen because it is known woodland caribou habitat and has thorough wildfire and silviculture data from the past 7 decades. Plant diversity, above-ground biomass, vascular green area and seasonal foliar fiber and C to N ratios were collected across a matrix of sites representing a chronosequence of time since disturbance in upland forests and peatlands. Preliminary findings revealed productivity peaked in early age stands (0-30 yrs) and biomass peaked in late age stands (71+ yrs). Furthermore the peatlands were found to have greater overall biomass and productivity than the uplands. C to N ratios from summer foliar samples varied across plant functional type with lichen and mosses had the highest C to N ratios and deciduous trees, shrubs and forbs had the lowest ratios. C to N ratios from spring foliar samples also varied across plant functional type in a similar manner and also varied between uplands and peatlands and by age class. This suggests drainage class and stand age but not disturbance type affects the amount and quality of forage within terrestrial ecosystems. Our intention is to assess forage value of abundant species to help understand diet choices, possibly attributable to acquisition of forage low in C and high in N. This, in combination with biomass availability and productivity data, will be important for understanding the mechanisms contributing to caribou decline and for assessing adaptive forest management options under North American conservation initiatives.

Differences in ecosystem carbon distribution and nutrient cycling linked to forest tree species composition in a mid-successional boreal forest

USGS Publications Warehouse

Melvin, April M.; Mack, Michelle C.; Johnstone, Jill F.; McGuire, A. David; Genet, Helene; Schuur, Edward A.G.

2015-01-01

In the boreal forest of Alaska, increased fire severity associated with climate change is expanding deciduous forest cover in areas previously dominated by black spruce (Picea mariana). Needle-leaf conifer and broad-leaf deciduous species are commonly associated with differences in tree growth, carbon (C) and nutrient cycling, and C accumulation in soils. Although this suggests that changes in tree species composition in Alaska could impact C and nutrient pools and fluxes, few studies have measured these linkages. We quantified C, nitrogen, phosphorus, and base cation pools and fluxes in three stands of black spruce and Alaska paper birch (Betula neoalaskana) that established following a single fire event in 1958. Paper birch consistently displayed characteristics of more rapid C and nutrient cycling, including greater aboveground net primary productivity, higher live foliage and litter nutrient concentrations, and larger ammonium and nitrate pools in the soil organic layer (SOL). Ecosystem C stocks (aboveground + SOL + 0–10 cm mineral soil) were similar for the two species; however, in black spruce, 78% of measured C was found in soil pools, primarily in the SOL, whereas aboveground biomass dominated ecosystem C pools in birch forest. Radiocarbon analysis indicated that approximately one-quarter of the black spruce SOL C accumulated prior to the 1958 fire, whereas no pre-fire C was observed in birch soils. Our findings suggest that tree species exert a strong influence over C and nutrient cycling in boreal forest and forest compositional shifts may have long-term implications for ecosystem C and nutrient dynamics.

Assessment of variations in taxonomic diversity, forest structure, and aboveground biomass using remote sensing along an altitudinal gradient in tropical montane forest of Costa Rica

NASA Astrophysics Data System (ADS)

Robinson, C. M.; Saatchi, S. S.; Clark, D.; Fricker, G. A.; Wolf, J.; Gillespie, T. W.; Rovzar, C. M.; Andelman, S.

2012-12-01

This research sought to understand how alpha and beta diversity of plants vary and relate to the three-dimensional vegetation structure and aboveground biomass along environmental gradients in the tropical montane forests of Braulio Carrillo National Park in Costa Rica. There is growing evidence that ecosystem structure plays an important role in defining patterns of species diversity and along with abiotic factors (climate and edaphic) control the phenotypic and functional variations across landscapes. It is well documented that strong subdivisions at local and regional scales are found mainly on geologic or climate gradients. These general determinants of biodiversity are best demonstrated in regions with natural gradients such as tropical montane forests. Altitudinal gradients provide a landscape scale changes through variations in topography, climate, and edaphic conditions on which we tested several theoretical and biological hypotheses regarding drivers of biodiversity. The study was performed by using forest inventory and botanical data from nine 1-ha plots ranging from 100 m to 2800 m above sea level and remote sensing data from airborne lidar and radar sensors to quantify variations in forest structure. In this study we report on the effectiveness of relating patterns of tree taxonomic alpha diversity to three-dimensional structure of a tropical montane forest using lidar and radar observations of forest structure and biomass. We assessed alpha and beta diversity at the species, genus, and family levels utilizing datasets provided by the Terrestrial Ecology Assessment and Monitoring (TEAM) Network. Through the comparison to active remote sensing imagery, our results show that there is a strong relationship between forest 3D-structure, and alpha and beta diversity controlled by variations in abiotic factors along the altitudinal gradient. Using spatial analysis with the aid of remote sensing data, we find distinct patterns along the environmental gradients defining species turnover and changes in functional diversity. The study will provide novel approaches to use detailed spatial information from remote sensing data to study relations between functional and taxonomic dimensions of diversity.

Basin-wide variations in Amazon forest structure and function are mediated by both soils and climate

NASA Astrophysics Data System (ADS)

Quesada, C. A.; Phillips, O. L.; Schwarz, M.; Czimczik, C. I.; Baker, T. R.; Patiño, S.; Fyllas, N. M.; Hodnett, M. G.; Herrera, R.; Almeida, S.; Alvarez Dávila, E.; Arneth, A.; Arroyo, L.; Chao, K. J.; Dezzeo, N.; Erwin, T.; di Fiore, A.; Higuchi, N.; Honorio Coronado, E.; Jimenez, E. M.; Killeen, T.; Lezama, A. T.; Lloyd, G.; López-González, G.; Luizão, F. J.; Malhi, Y.; Monteagudo, A.; Neill, D. A.; Núñez Vargas, P.; Paiva, R.; Peacock, J.; Peñuela, M. C.; Peña Cruz, A.; Pitman, N.; Priante Filho, N.; Prieto, A.; Ramírez, H.; Rudas, A.; Salomão, R.; Santos, A. J. B.; Schmerler, J.; Silva, N.; Silveira, M.; Vásquez, R.; Vieira, I.; Terborgh, J.; Lloyd, J.

2012-06-01

Forest structure and dynamics vary across the Amazon Basin in an east-west gradient coincident with variations in soil fertility and geology. This has resulted in the hypothesis that soil fertility may play an important role in explaining Basin-wide variations in forest biomass, growth and stem turnover rates. Soil samples were collected in a total of 59 different forest plots across the Amazon Basin and analysed for exchangeable cations, carbon, nitrogen and pH, with several phosphorus fractions of likely different plant availability also quantified. Physical properties were additionally examined and an index of soil physical quality developed. Bivariate relationships of soil and climatic properties with above-ground wood productivity, stand-level tree turnover rates, above-ground wood biomass and wood density were first examined with multivariate regression models then applied. Both forms of analysis were undertaken with and without considerations regarding the underlying spatial structure of the dataset. Despite the presence of autocorrelated spatial structures complicating many analyses, forest structure and dynamics were found to be strongly and quantitatively related to edaphic as well as climatic conditions. Basin-wide differences in stand-level turnover rates are mostly influenced by soil physical properties with variations in rates of coarse wood production mostly related to soil phosphorus status. Total soil P was a better predictor of wood production rates than any of the fractionated organic- or inorganic-P pools. This suggests that it is not only the immediately available P forms, but probably the entire soil phosphorus pool that is interacting with forest growth on longer timescales. A role for soil potassium in modulating Amazon forest dynamics through its effects on stand-level wood density was also detected. Taking this into account, otherwise enigmatic variations in stand-level biomass across the Basin were then accounted for through the interacting effects of soil physical and chemical properties with climate. A hypothesis of self-maintaining forest dynamic feedback mechanisms initiated by edaphic conditions is proposed. It is further suggested that this is a major factor determining endogenous disturbance levels, species composition, and forest productivity across the Amazon Basin.

Dead wood biomass and turnover time, measured by radiocarbon, along a subalpine elevation gradient.

PubMed

Kueppers, Lara M; Southon, John; Baer, Paul; Harte, John

2004-12-01

Dead wood biomass can be a substantial fraction of stored carbon in forest ecosystems, and coarse woody debris (CWD) decay rates may be sensitive to climate warming. We used an elevation gradient in Colorado Rocky Mountain subalpine forest to examine climate and species effects on dead wood biomass, and on CWD decay rate. Using a new radiocarbon approach, we determined that the turnover time of lodgepole pine CWD (340+/-130 years) was roughly half as long in a site with 2.5-3 degrees C warmer air temperature, as that of pine (630+/-400 years) or Engelmann spruce CWD (800+/-960 and 650+/-410 years) in cooler sites. Across all sites and both species, CWD age ranged from 2 to 600 years, and turnover time was 580+/-180 years. Total standing and fallen dead wood biomass ranged from 4.7+/-0.2 to 54+/-1 Mg ha(-1), and from 2.8 to 60% of aboveground live tree biomass. Dead wood biomass increased 75 kg ha(-1) per meter gain in elevation and decreased 13 Mg ha(-1) for every degree C increase in mean air temperature. Differences in biomass and decay rates along the elevation gradient suggest that climate warming will lead to a loss of dead wood carbon from subalpine forest.

Quantification of forest carbon degradation in Nicaragua using RapidEye remote sensing data: El Cuá and Wiwili case studies

NASA Astrophysics Data System (ADS)

Argoty, F. N.; Cifuentes, M.; Imbach, P. A.; Vilchez, S.; Casanoves, F.; Ibrahim, M.; Vierling, L. A.

2012-12-01

Forest degradation and deforestation affect ecosystem function and climate regulation services such as carbon storage. Historically, Central America has been a deforestation and forest degradation hotspot. Wiwili and El Cuá municipalities in northern Nicaragua are no exception, where subsistence agriculture and cattle ranch expansion have driven deforestation and other wood extraction activities, leading to various levels of forest degradation. Reduction of Emissions from forest Degradation and Deforestation (REDD) projects are proposed as a tool to slow the degradation and loss of carbon stocks by restoring carbon to its natural levels in order to mitigate carbon dioxide emissions that cause global warming. REDD projects require baseline estimations of current carbon stocks and forest degradation status. We estimated carbon stocks across a forest degradation gradient based on common biophysical variables and commercially available (RapidEye) remote sensing data. We measured 80 temporary forest plots (50x20m) for aboveground biomass to sample a gradient of forest degradation at two municipalities (El Cuá and Wiwili) in northern Nicaragua. We measured biomass in trees (≥10 cm DBH), saplings (5-9.9 cm DBH), other growth forms (ferns, palms and woody vines), and large detritus (snags and downed wood). Biomass was estimated by a range of allometric models and a constant conversion factor (0.47) was applied to calculate aboveground carbon stocks. Remote sensing data from a RapidEye scene for 02/2010 provided data for 5 spectral bands and 19 vegetation indexes at 6 m spatial resolution. Precipitation, temperature, altitude, slope, canopy cover, and aspect were also used as input variables for carbon modeling. We tested linear mixed models, generalized additive mixed models and regression tree approaches to explain carbon stocks based on vegetation indexes and biophysical variables. Additionally, we grouped plots into low (17-168 Mg C ha-1), medium (168-302 Mg C ha-1) and high (302-418 Mg C ha-1) carbon stocks (with conglomerate analysis) to test for a categorical classification approach based on discriminant analysis. Results show a gradient of total aboveground carbon between 17.78 - 379.2 Mg C ha-1. Models predicting carbon stock had an R2 that ranged between 0.32-0.52 (p<0.0001) across the three methods evaluated. Linear mixed models using the MCARI-MTVI2 vegetation index, based on the red-edge band (690-730 nm), showed the best performance. Categorical classification showed improved performance, with a 17% mean classification error, using 20 predictors (MCARI-MTVI2 was the most important). Our results show the importance of the red-edge band and the potential of multi-spectral high-resolution imagery to quantify tropical forest degradation. Although model performance for prediction of continuous biomass values is somewhat constrained, there is potential for coarser applications in the context of developing REDD baselines and monitoring using categorical mapping of forest degradation (with a trade-off in inference power) by means of relatively low-cost remote sensing and ancillary data.

The importance of age-related decline in forest NPP for modeling regional carbon balances.

PubMed

Zaehle, Sönke; Sitch, Stephen; Prentice, I Colin; Liski, Jari; Cramer, Wolfgang; Erhard, Markus; Hickler, Thomas; Smith, Benjamin

2006-08-01

We show the implications of the commonly observed age-related decline in aboveground productivity of forests, and hence forest age structure, on the carbon dynamics of European forests in response to historical changes in environmental conditions. Size-dependent carbon allocation in trees to counteract increasing hydraulic resistance with tree height has been hypothesized to be responsible for this decline. Incorporated into a global terrestrial biosphere model (the Lund-Potsdam-Jena model, LPJ), this hypothesis improves the simulated increase in biomass with stand age. Application of the advanced model, including a generic representation of forest management in even-aged stands, for 77 European provinces shows that model-based estimates of biomass development with age compare favorably with inventory-based estimates for different tree species. Model estimates of biomass densities on province and country levels, and trends in growth increment along an annual mean temperature gradient are in broad agreement with inventory data. However, the level of agreement between modeled and inventory-based estimates varies markedly between countries and provinces. The model is able to reproduce the present-day age structure of forests and the ratio of biomass removals to increment on a European scale based on observed changes in climate, atmospheric CO2 concentration, forest area, and wood demand between 1948 and 2000. Vegetation in European forests is modeled to sequester carbon at a rate of 100 Tg C/yr, which corresponds well to forest inventory-based estimates.

Variation in stem mortality rates determines patterns of above-ground biomass in Amazonian forests: implications for dynamic global vegetation models.

PubMed

Johnson, Michelle O; Galbraith, David; Gloor, Manuel; De Deurwaerder, Hannes; Guimberteau, Matthieu; Rammig, Anja; Thonicke, Kirsten; Verbeeck, Hans; von Randow, Celso; Monteagudo, Abel; Phillips, Oliver L; Brienen, Roel J W; Feldpausch, Ted R; Lopez Gonzalez, Gabriela; Fauset, Sophie; Quesada, Carlos A; Christoffersen, Bradley; Ciais, Philippe; Sampaio, Gilvan; Kruijt, Bart; Meir, Patrick; Moorcroft, Paul; Zhang, Ke; Alvarez-Davila, Esteban; Alves de Oliveira, Atila; Amaral, Ieda; Andrade, Ana; Aragao, Luiz E O C; Araujo-Murakami, Alejandro; Arets, Eric J M M; Arroyo, Luzmila; Aymard, Gerardo A; Baraloto, Christopher; Barroso, Jocely; Bonal, Damien; Boot, Rene; Camargo, Jose; Chave, Jerome; Cogollo, Alvaro; Cornejo Valverde, Fernando; Lola da Costa, Antonio C; Di Fiore, Anthony; Ferreira, Leandro; Higuchi, Niro; Honorio, Euridice N; Killeen, Tim J; Laurance, Susan G; Laurance, William F; Licona, Juan; Lovejoy, Thomas; Malhi, Yadvinder; Marimon, Bia; Marimon, Ben Hur; Matos, Darley C L; Mendoza, Casimiro; Neill, David A; Pardo, Guido; Peña-Claros, Marielos; Pitman, Nigel C A; Poorter, Lourens; Prieto, Adriana; Ramirez-Angulo, Hirma; Roopsind, Anand; Rudas, Agustin; Salomao, Rafael P; Silveira, Marcos; Stropp, Juliana; Ter Steege, Hans; Terborgh, John; Thomas, Raquel; Toledo, Marisol; Torres-Lezama, Armando; van der Heijden, Geertje M F; Vasquez, Rodolfo; Guimarães Vieira, Ima Cèlia; Vilanova, Emilio; Vos, Vincent A; Baker, Timothy R

2016-12-01

Understanding the processes that determine above-ground biomass (AGB) in Amazonian forests is important for predicting the sensitivity of these ecosystems to environmental change and for designing and evaluating dynamic global vegetation models (DGVMs). AGB is determined by inputs from woody productivity [woody net primary productivity (NPP)] and the rate at which carbon is lost through tree mortality. Here, we test whether two direct metrics of tree mortality (the absolute rate of woody biomass loss and the rate of stem mortality) and/or woody NPP, control variation in AGB among 167 plots in intact forest across Amazonia. We then compare these relationships and the observed variation in AGB and woody NPP with the predictions of four DGVMs. The observations show that stem mortality rates, rather than absolute rates of woody biomass loss, are the most important predictor of AGB, which is consistent with the importance of stand size structure for determining spatial variation in AGB. The relationship between stem mortality rates and AGB varies among different regions of Amazonia, indicating that variation in wood density and height/diameter relationships also influences AGB. In contrast to previous findings, we find that woody NPP is not correlated with stem mortality rates and is weakly positively correlated with AGB. Across the four models, basin-wide average AGB is similar to the mean of the observations. However, the models consistently overestimate woody NPP and poorly represent the spatial patterns of both AGB and woody NPP estimated using plot data. In marked contrast to the observations, DGVMs typically show strong positive relationships between woody NPP and AGB. Resolving these differences will require incorporating forest size structure, mechanistic models of stem mortality and variation in functional composition in DGVMs. © 2016 The Authors. Global Change Biology Published by John Wiley & Sons Ltd.

Recent drought-induced decline of forests along a water-balance tipping point for ecosystems in western Canada

NASA Astrophysics Data System (ADS)

Hess, N. J.; Tfaily, M. M.; Heredia-Langnar, A.; Rodriguez, L.; Purvine, E.; Todd-Brown, K. E.

2016-12-01

In western Canada, the forest-prairie boundary corresponds to a hydrologically-defined ecosystem "tipping point" where long-term precipitation is barely sufficient to meet the water use requirements of healthy, closed-canopy forests. In the province of Alberta, the severe subcontinental drought of 2001-2002 heralded the beginning of a 15-year dry period, representing a northward incursion of prairie-like climates into boreal and cordilleran forests. This poses a significant concern for ecosystem functioning of these forests, given GCM projections for continued warming and drying under anthropogenic climate change during this century. Through a multi-scale monitoring approach, we have examined the regional-scale impacts of recent droughts and associated climatic drying on the productivity and health of two important boreal tree species: aspen (Populus tremuloides) and white spruce (Picea glauca). For aspen, the 2016 re-measurement of a regional network of 150 ground plots revealed that tree mortality has escalated, especially in stands exposed to the combined impacts of multi-year drought and insect defoliation. On average, mortality losses exceeded growth gains during 2000-2016 for the 54 aspen plots in Alberta, leading to a net multi-year decline in the aboveground biomass of these stands. For white spruce, tree-ring analysis of 40 stands across Alberta revealed that the prolonged dry period led to a 38% decline in average, tree-level growth in aboveground biomass. In both species, stand age was not a significant factor affecting forest sensitivity to drought and climatic drying, suggesting that these forests are at risk if the trend toward more frequent, severe drought continues in the region.

Recent drought-induced decline of forests along a water-balance tipping point for ecosystems in western Canada

NASA Astrophysics Data System (ADS)

Hogg, E. H.; Michaelian, M.

2017-12-01

In western Canada, the forest-prairie boundary corresponds to a hydrologically-defined ecosystem "tipping point" where long-term precipitation is barely sufficient to meet the water use requirements of healthy, closed-canopy forests. In the province of Alberta, the severe subcontinental drought of 2001-2002 heralded the beginning of a 15-year dry period, representing a northward incursion of prairie-like climates into boreal and cordilleran forests. This poses a significant concern for ecosystem functioning of these forests, given GCM projections for continued warming and drying under anthropogenic climate change during this century. Through a multi-scale monitoring approach, we have examined the regional-scale impacts of recent droughts and associated climatic drying on the productivity and health of two important boreal tree species: aspen (Populus tremuloides) and white spruce (Picea glauca). For aspen, the 2016 re-measurement of a regional network of 150 ground plots revealed that tree mortality has escalated, especially in stands exposed to the combined impacts of multi-year drought and insect defoliation. On average, mortality losses exceeded growth gains during 2000-2016 for the 54 aspen plots in Alberta, leading to a net multi-year decline in the aboveground biomass of these stands. For white spruce, tree-ring analysis of 40 stands across Alberta revealed that the prolonged dry period led to a 38% decline in average, tree-level growth in aboveground biomass. In both species, stand age was not a significant factor affecting forest sensitivity to drought and climatic drying, suggesting that these forests are at risk if the trend toward more frequent, severe drought continues in the region.

Enhanced systems for measuring and monitoring REDD+: Opportunities to improve the accuracy of emission factor and activity data in Indonesia

NASA Astrophysics Data System (ADS)

Solichin

The importance of accurate measurement of forest biomass in Indonesia has been growing ever since climate change mitigation schemes, particularly the reduction of emissions from deforestation and forest degradation scheme (known as REDD+), were constitutionally accepted by the government of Indonesia. The need for an accurate system of historical and actual forest monitoring has also become more pronounced, as such a system would afford a better understanding of the role of forests in climate change and allow for the quantification of the impact of activities implemented to reduce greenhouse gas emissions. The aim of this study was to enhance the accuracy of estimations of carbon stocks and to monitor emissions in tropical forests. The research encompassed various scales (from trees and stands to landscape-sized scales) and a wide range of aspects, from evaluation and development of allometric equations to exploration of the potential of existing forest inventory databases and evaluation of cutting-edge technology for non-destructive sampling and accurate forest biomass mapping over large areas. In this study, I explored whether accuracy--especially regarding the identification and reduction of bias--of forest aboveground biomass (AGB) estimates in Indonesia could be improved through (1) development and refinement of allometric equations for major forest types, (2) integration of existing large forest inventory datasets, (3) assessing nondestructive sampling techniques for tree AGB measurement, and (4) landscape-scale mapping of AGB and forest cover using lidar. This thesis provides essential foundations to improve the estimation of forest AGB at tree scale through development of new AGB equations for several major forest types in Indonesia. I successfully developed new allometric equations using large datasets from various forest types that enable us to estimate tree aboveground biomass for both forest type specific and generic equations. My models outperformed the existing local equations, with lower bias and higher precision of the AGB estimates. This study also highlights the potential advantages and challenges of using terrestrial lidar and the acoustic velocity tool for non-destructive sampling of tree biomass to enable more sample collection without the felling of trees. Further, I explored whether existing forest inventories and permanent sample plot datasets can be integrated into Indonesia's existing carbon accounting system. My investigation of these existing datasets found that through quality assurance tests these datasets are essential to be integrated into national and provincial forest monitoring and carbon accounting systems. Integration of this information would eventually improve the accuracy of the estimates of forest carbon stocks, biomass growth, mortality and emission factors from deforestation and forest degradation. At landscape scale, this study demonstrates the capability of airborne lidar for forest monitoring and forest cover classification in tropical peat swamp ecosystems. The mapping application using airborne lidar showed a more accurate and precise classification of land and forest cover when compared with mapping using optical and active sensors. To reduce the cost of lidar acquisition, this study assessed the optimum lidar return density for forest monitoring. I found that the density of lidar return could be reduced to at least 1 return per 4 m2. Overall, this study provides essential scientific background to improve the accuracy of forest AGB estimates. Therefore, the described results and techniques should be integrated into the existing monitoring systems to assess emission reduction targets and the impact of REDD+ implementation.

Above-ground biomass of mangrove species. I. Analysis of models

NASA Astrophysics Data System (ADS)

Soares, Mário Luiz Gomes; Schaeffer-Novelli, Yara

2005-10-01

This study analyzes the above-ground biomass of Rhizophora mangle and Laguncularia racemosa located in the mangroves of Bertioga (SP) and Guaratiba (RJ), Southeast Brazil. Its purpose is to determine the best regression model to estimate the total above-ground biomass and compartment (leaves, reproductive parts, twigs, branches, trunk and prop roots) biomass, indirectly. To do this, we used structural measurements such as height, diameter at breast-height (DBH), and crown area. A combination of regression types with several compositions of independent variables generated 2.272 models that were later tested. Subsequent analysis of the models indicated that the biomass of reproductive parts, branches, and prop roots yielded great variability, probably because of environmental factors and seasonality (in the case of reproductive parts). It also indicated the superiority of multiple regression to estimate above-ground biomass as it allows researchers to consider several aspects that affect above-ground biomass, specially the influence of environmental factors. This fact has been attested to the models that estimated the biomass of crown compartments.

Estimating aboveground forest biomass carbon and fire consumption in the U.S. Utah High Plateaus using data from the Forest Inventory and Analysis program, Landsat, and LANDFIRE

USGS Publications Warehouse

Chen, Xuexia; Liu, Shuguang; Zhu, Zhiliang; Vogelmann, James E.; Li, Zhengpeng; Ohlen, Donald O.

2011-01-01

The concentrations of CO2 and other greenhouse gases in the atmosphere have been increasing and greatly affecting global climate and socio-economic systems. Actively growing forests are generally considered to be a major carbon sink, but forest wildfires lead to large releases of biomass carbon into the atmosphere. Aboveground forest biomass carbon (AFBC), an important ecological indicator, and fire-induced carbon emissions at regional scales are highly relevant to forest sustainable management and climate change. It is challenging to accurately estimate the spatial distribution of AFBC across large areas because of the spatial heterogeneity of forest cover types and canopy structure. In this study, Forest Inventory and Analysis (FIA) data, Landsat, and Landscape Fire and Resource Management Planning Tools Project (LANDFIRE) data were integrated in a regression tree model for estimating AFBC at a 30-m resolution in the Utah High Plateaus. AFBC were calculated from 225 FIA field plots and used as the dependent variable in the model. Of these plots, 10% were held out for model evaluation with stratified random sampling, and the other 90% were used as training data to develop the regression tree model. Independent variable layers included Landsat imagery and the derived spectral indicators, digital elevation model (DEM) data and derivatives, biophysical gradient data, existing vegetation cover type and vegetation structure. The cross-validation correlation coefficient (r value) was 0.81 for the training model. Independent validation using withheld plot data was similar with r value of 0.82. This validated regression tree model was applied to map AFBC in the Utah High Plateaus and then combined with burn severity information to estimate loss of AFBC in the Longston fire of Zion National Park in 2001. The final dataset represented 24 forest cover types for a 4 million ha forested area. We estimated a total of 353 Tg AFBC with an average of 87 MgC/ha in the Utah High Plateaus. We also estimated that 8054 Mg AFBC were released from 2.24 km2 burned forest area in the Longston fire. These results demonstrate that an AFBC spatial map and estimated biomass carbon consumption can readily be generated using existing database. The methodology provides a consistent, practical, and inexpensive way for estimating AFBC at 30-m resolution over large areas throughout the United States.

Relating P-band AIRSAR backscatter to forest stand parameters

NASA Technical Reports Server (NTRS)

Wang, Yong; Melack, John M.; Davis, Frank W.; Kasischke, Eric S.; Christensen, Norman L., Jr.

1993-01-01

As part of research on forest ecosystems, the Jet Propulsion Laboratory (JPL) and collaborating research teams have conducted multi-season airborne synthetic aperture radar (AIRSAR) experiments in three forest ecosystems including temperate pine forest (Duke, Forest, North Carolina), boreal forest (Bonanza Creek Experimental Forest, Alaska), and northern mixed hardwood-conifer forest (Michigan Biological Station, Michigan). The major research goals were to improve understanding of the relationships between radar backscatter and phenological variables (e.g. stand density, tree size, etc.), to improve radar backscatter models of tree canopy properties, and to develop a radar-based scheme for monitoring forest phenological changes. In September 1989, AIRSAR backscatter data were acquired over the Duke Forest. As the aboveground biomass of the loblolly pine forest stands at Duke Forest increased, the SAR backscatter at C-, L-, and P-bands increased and saturated at different biomass levels for the C-band, L-band, and P-band data. We only use the P-band backscatter data and ground measurements here to study the relationships between the backscatter and stand density, the backscatter and mean trunk dbh (diameter at breast height) of trees in the stands, and the backscatter and stand basal area.

Simulating Forest Dynamics of Lowland Rainforests in Eastern Madagascar

NASA Technical Reports Server (NTRS)

Armstrong, Amanda; Fischer, Rico; Huth, Andreas; Shugart, Herman; Fatoyinbo, Temilola

2018-01-01

Ecological modeling and forecasting are essential tools for the understanding of complex vegetation dynamics. The parametric demands of some of these models are often lacking or scant for threatened ecosystems, particularly in diverse tropical ecosystems. One such ecosystem and also one of the world's biodiversity hotspots, Madagascar's lowland rainforests, have disappeared at an alarming rate. The processes that drive tree species growth and distribution remain as poorly understood as the species themselves. We investigated the application of the process-based individual-based FORMIND model to successfully simulate a Madagascar lowland rainforest using previously collected multi-year forest inventory plot data. We inspected the model's ability to characterize growth and species abundance distributions over the study site, and then validated the model with an independently collected forest-inventory dataset from another lowland rainforest in eastern Madagascar. Following a comparative analysis using inventory data from the two study sites, we found that FORMIND accurately captures the structure and biomass of the study forest, with r(squared) values of 0.976, 0.895, and 0.995 for 1:1 lines comparing observed and simulated values across all plant functional types for aboveground biomass (tonnes/ha), stem numbers, and basal area (m(squared)/ha), respectively. Further, in validation with a second study forest site, FORMIND also compared well, only slightly over-estimating shade-intermediate species as compared to the study site, and slightly under-representing shade-tolerant species in percentage of total aboveground biomass. As an important application of the FORMIND model, we measured the net ecosystem exchange (NEE, in tons of carbon per hectare per year) for 50 ha of simulated forest over a 1000-year run from bare ground. We found that NEE values ranged between 1 and -1 t Cha(exp -1)year(exp -1), consequently the study forest can be considered as a net neutral or a very slight carbon sink ecosystem, after the initial 130 years of growth. Our study found that FORMIND represents a valuable tool toward simulating forest dynamics in the immensely diverse Madagascar rainforests.

Towards ground-truthing of spaceborne estimates of above-ground life biomass and leaf area index in tropical rain forests

NASA Astrophysics Data System (ADS)

Köhler, P.; Huth, A.

2010-08-01

The canopy height h of forests is a key variable which can be obtained using air- or spaceborne remote sensing techniques such as radar interferometry or LIDAR. If new allometric relationships between canopy height and the biomass stored in the vegetation can be established this would offer the possibility for a global monitoring of the above-ground carbon content on land. In the absence of adequate field data we use simulation results of a tropical rain forest growth model to propose what degree of information might be generated from canopy height and thus to enable ground-truthing of potential future satellite observations. We here analyse the correlation between canopy height in a tropical rain forest with other structural characteristics, such as above-ground life biomass (AGB) (and thus carbon content of vegetation) and leaf area index (LAI) and identify how correlation and uncertainty vary for two different spatial scales. The process-based forest growth model FORMIND2.0 was applied to simulate (a) undisturbed forest growth and (b) a wide range of possible disturbance regimes typically for local tree logging conditions for a tropical rain forest site on Borneo (Sabah, Malaysia) in South-East Asia. In both undisturbed and disturbed forests AGB can be expressed as a power-law function of canopy height h (AGB = a · hb) with an r2 ~ 60% if data are analysed in a spatial resolution of 20 m × 20 m (0.04 ha, also called plot size). The correlation coefficient of the regression is becoming significant better in the disturbed forest sites (r2 = 91%) if data are analysed hectare wide. There seems to exist no functional dependency between LAI and canopy height, but there is also a linear correlation (r2 ~ 60%) between AGB and the area fraction of gaps in which the canopy is highly disturbed. A reasonable agreement of our results with observations is obtained from a comparison of the simulations with permanent sampling plot (PSP) data from the same region and with the large-scale forest inventory in Lambir. We conclude that the spaceborne remote sensing techniques such as LIDAR and radar interferometry have the potential to quantify the carbon contained in the vegetation, although this calculation contains due to the heterogeneity of the forest landscape structural uncertainties which restrict future applications to spatial averages of about one hectare in size. The uncertainties in AGB for a given canopy height are here 20-40% (95% confidence level) corresponding to a standard deviation of less than ± 10%. This uncertainty on the 1 ha-scale is much smaller than in the analysis of 0.04 ha-scale data. At this small scale (0.04 ha) AGB can only be calculated out of canopy height with an uncertainty which is at least of the magnitude of the signal itself due to the natural spatial heterogeneity of these forests.

NGEE Arctic Plant Traits: Plant Biomass and Traits, Kougarok Road Mile Marker 64, Seward Peninsula, Alaska, beginning 2016

DOE Office of Scientific and Technical Information (OSTI.GOV)

Verity Salmon; Colleen Iversen; Amy Breen

Data includes aboveground biomass and plant traits for destructive harvests performed at the Kougarok hill slope located at Kougarok Road, Mile Marker 64. Data collection began in July 2016. Aboveground biomass and aboveground plant traits are available for shrub and understory species found in vegetation plots. Paired observations of aboveground and belowground plant traits are available for select shrub species.

Using LiDAR to Estimate Total Aboveground Biomass of Redwood Stands in the Jackson Demonstration State Forest, Mendocino, California

NASA Astrophysics Data System (ADS)

Rao, M.; Vuong, H.

2013-12-01

The overall objective of this study is to develop a method for estimating total aboveground biomass of redwood stands in Jackson Demonstration State Forest, Mendocino, California using airborne LiDAR data. LiDAR data owing to its vertical and horizontal accuracy are increasingly being used to characterize landscape features including ground surface elevation and canopy height. These LiDAR-derived metrics involving structural signatures at higher precision and accuracy can help better understand ecological processes at various spatial scales. Our study is focused on two major species of the forest: redwood (Sequoia semperirens [D.Don] Engl.) and Douglas-fir (Pseudotsuga mensiezii [Mirb.] Franco). Specifically, the objectives included linear regression models fitting tree diameter at breast height (dbh) to LiDAR derived height for each species. From 23 random points on the study area, field measurement (dbh and tree coordinate) were collected for more than 500 trees of Redwood and Douglas-fir over 0.2 ha- plots. The USFS-FUSION application software along with its LiDAR Data Viewer (LDV) were used to to extract Canopy Height Model (CHM) from which tree heights would be derived. Based on the LiDAR derived height and ground based dbh, a linear regression model was developed to predict dbh. The predicted dbh was used to estimate the biomass at the single tree level using Jenkin's formula (Jenkin et al 2003). The linear regression models were able to explain 65% of the variability associated with Redwood's dbh and 80% of that associated with Douglas-fir's dbh.

Assessing changes of mangrove forest in a coastal region of southeast China using multi-temporal satellite images

NASA Astrophysics Data System (ADS)

Wang, Min; Cao, Wenzhi; Guan, Qingsong; Wu, Gaojie; Wang, Feifei

2018-07-01

Mangroves provide many ecological, economic, and social benefits to humans. In the Jiulong River Estuary of Fujian Province, China, many mangroves have been lost largely due to human activities and so artificial planting has been implemented. However, the spatial and temporal dynamics of mangrove forests are still largely unknown at this location. This study aimed to identify changes to mangrove distribution and aboveground biomass (AGB) in three periods (1995-2004, 2004-2014 and 1995-2014) in order to influence mangrove management. Landsat satellite imagery and the threshold value method were used to classify mangroves. Landsat satellite imagery, field-based biomass investigations, elevation data and an allometric biomass equation were employed to develop an AGB model using a multiple linear regression method. Both mangrove area and AGB increased from 1995 to 2014 with an increase rate of 5.5% and 7.2% for mangrove area and AGB, respectively. Mangrove expansion was the main cause for AGB and area increase. In addition, AGB increase due to the growth of mangroves without extending the area also has great potential in AGB increase. Similar to AGB, above-ground carbon increased from 57 t C/ha in 1995 to 79 t C/ha in 2014, which demonstrated that mangroves in this region can help to mitigate climate warming. However, a large-scale continuous decrease of mangrove forest in the JRE was observed, likely caused by growing human activities. Moreover, tidal range change during 2004-2014 resulted in a more adverse impact on mangroves.

Estimation of Mangrove Forest Aboveground Biomass Using Multispectral Bands, Vegetation Indices and Biophysical Variables Derived from Optical Satellite Imageries: Rapideye, Planetscope and SENTINEL-2

NASA Astrophysics Data System (ADS)

Balidoy Baloloy, Alvin; Conferido Blanco, Ariel; Gumbao Candido, Christian; Labadisos Argamosa, Reginal Jay; Lovern Caboboy Dumalag, John Bart; Carandang Dimapilis, Lee, , Lady; Camero Paringit, Enrico

2018-04-01

Aboveground biomass estimation (AGB) is essential in determining the environmental and economic values of mangrove forests. Biomass prediction models can be developed through integration of remote sensing, field data and statistical models. This study aims to assess and compare the biomass predictor potential of multispectral bands, vegetation indices and biophysical variables that can be derived from three optical satellite systems: the Sentinel-2 with 10 m, 20 m and 60 m resolution; RapidEye with 5m resolution and PlanetScope with 3m ground resolution. Field data for biomass were collected from a Rhizophoraceae-dominated mangrove forest in Masinloc, Zambales, Philippines where 30 test plots (1.2 ha) and 5 validation plots (0.2 ha) were established. Prior to the generation of indices, images from the three satellite systems were pre-processed using atmospheric correction tools in SNAP (Sentinel-2), ENVI (RapidEye) and python (PlanetScope). The major predictor bands tested are Blue, Green and Red, which are present in the three systems; and Red-edge band from Sentinel-2 and Rapideye. The tested vegetation index predictors are Normalized Differenced Vegetation Index (NDVI), Soil-adjusted Vegetation Index (SAVI), Green-NDVI (GNDVI), Simple Ratio (SR), and Red-edge Simple Ratio (SRre). The study generated prediction models through conventional linear regression and multivariate regression. Higher coefficient of determination (r2) values were obtained using multispectral band predictors for Sentinel-2 (r2 = 0.89) and Planetscope (r2 = 0.80); and vegetation indices for RapidEye (r2 = 0.92). Multivariate Adaptive Regression Spline (MARS) models performed better than the linear regression models with r2 ranging from 0.62 to 0.92. Based on the r2 and root-mean-square errors (RMSE's), the best biomass prediction model per satellite were chosen and maps were generated. The accuracy of predicted biomass maps were high for both Sentinel-2 (r2 = 0.92) and RapidEye data (r2 = 0.91).

Above-ground biomass and structure of pristine Siberian Scots pine forests as controlled by competition and fire.

PubMed

Wirth, C; Schulze, E-D; Schulze, W; von Stünzner-Karbe, D; Ziegler, W; Miljukova, I M; Sogatchev, A; Varlagin, A B; Panvyorov, M; Grigoriev, S; Kusnetzova, W; Siry, M; Hardes, G; Zimmermann, R; Vygodskaya, N N

1999-10-01

The study presents a data set of above-ground biomass (AGB), structure, spacing and fire regime, for 24 stands of pristine Siberian Scots pine (Pinus sylvestris) forests with lichens (n = 20) or Vaccinium/mosses (n = 4) as ground cover, along four chronosequences. The stands of the "lichen" site type (LT) were stratified into three chronosequences according to stand density and fire history. Allometric equations were established from 90 sample trees for stem, coarse branch, fine branch, twig and needle biomass. The LT stands exhibited a low but sustained biomass accumulation until a stand age of 383 years. AGB reached only 6-10 kg dw  m -2 after 200 years depending on stand density and fire history compared to 20 kg dw  m -2 in the "Vaccinium" type (VT) stands. Leaf area index (LAI) in the LT stands remained at 0.5-1.5 and crown cover was 30-60%, whereas LAI reached 2.5 and crown cover was >100% in the VT stands. Although nearest-neighbour analyses suggested the existence of density-dependent mortality, fire impact turned out to have a much stronger effect on density dynamics. Fire scar dating and calculation of mean and initial fire return intervals revealed that within the LT stands differences in structure and biomass were related to the severity of fire regimes, which in turn was related to the degree of landscape fragmentation by wetlands. Self-thinning analysis was used to define the local carrying capacity for biomass. A series of undisturbed LT stands was used to characterise the upper self-thinning boundary. Stands that had experienced a moderate fire regime were positioned well below the self-thinning boundary in a distinct fire-thinning band of reduced major axis regression slope -0.26. We discuss how this downward shift resulted from alternating phases of density reduction by fire and subsequent regrowth. We conclude that biomass in Siberian Scots pine forests is strongly influenced by fire and that climate change will affect ecosystem functions predominantly via changes in fire regimes.

A remote sensing-based model of tidal marsh aboveground carbon stocks for the conterminous United States

USGS Publications Warehouse

Byrd, Kristin B.; Ballanti, Laurel; Thomas, Nathan; Nguyen, Dung; Holmquist, James R.; Simard, Marc; Windham-Myers, Lisamarie

2018-01-01

Remote sensing based maps of tidal marshes, both of their extents and carbon stocks, have the potential to play a key role in conducting greenhouse gas inventories and implementing climate mitigation policies. Our objective was to generate a single remote sensing model of tidal marsh aboveground biomass and carbon that represents nationally diverse tidal marshes within the conterminous United States (CONUS). We developed the first calibration-grade, national-scale dataset of aboveground tidal marsh biomass, species composition, and aboveground plant carbon content (%C) from six CONUS regions: Cape Cod, MA, Chesapeake Bay, MD, Everglades, FL, Mississippi Delta, LA, San Francisco Bay, CA, and Puget Sound, WA. Using the random forest machine learning algorithm, we tested whether imagery from multiple sensors, Sentinel-1 C-band synthetic aperture radar, Landsat, and the National Agriculture Imagery Program (NAIP), can improve model performance. The final model, driven by six Landsat vegetation indices and with the soil adjusted vegetation index as the most important (n = 409, RMSE = 310 g/m2, 10.3% normalized RMSE), successfully predicted biomass for a range of marsh plant functional types defined by height, leaf angle and growth form. Model results were improved by scaling field-measured biomass calibration data by NAIP-derived 30 m fraction green vegetation. With a mean plant carbon content of 44.1% (n = 1384, 95% C.I. = 43.99%–44.37%), we generated regional 30 m aboveground carbon density maps for estuarine and palustrine emergent tidal marshes as indicated by a modified NOAA Coastal Change Analysis Program map. We applied a multivariate delta method to calculate uncertainties in regional carbon densities and stocks that considered standard error in map area, mean biomass and mean %C. Louisiana palustrine emergent marshes had the highest C density (2.67 ± 0.004 Mg/ha) of all regions, while San Francisco Bay brackish/saline marshes had the highest C density of all estuarine emergent marshes (2.03 ± 0.004 Mg/ha). Estimated C stocks for predefined jurisdictional areas ranged from 1023 ± 39 Mg in the Nisqually National Wildlife Refuge in Washington to 507,761 ± 14,822 Mg in the Terrebonne and St. Mary Parishes in Louisiana. This modeling and data synthesis effort will allow for aboveground C stocks in tidal marshes to be included in the coastal wetland section of the U.S. National Greenhouse Gas Inventory. With the increased availability of free post-processed satellite data, we provide a tractable means of modeling tidal marsh aboveground biomass and carbon at the global extent as well.

Estimating herbaceous biomass of grassland vegetation using the reference unit method

Treesearch

Eric D. Boyda; Jack L. Butler; Lan Xu

2015-01-01

Aboveground net primary production provides valuable information on wildlife habitat, fire fuel loads, and forage availability. Aboveground net primary production in herbaceous plant communities is typically measured by clipping aboveground biomass. However, the high costs associated with physically harvesting plant biomass may prevent collecting sufficient...

Simulated Biomass Retrieval from the Spaceborne Tomographic SAOCOM-CS Mission at L-Band

NASA Astrophysics Data System (ADS)

Blomberg, Erik; Soja, Maciej J.; Ferro-Famil, Laurent; Ulander, Lars M. H.; Tebaldini, Stefano

2016-08-01

This paper presents an evaluation of above-ground biomass (ABG) retrieval in boreal forests using simulated tomographic synthetic-aperture radar (SAR) data corresponding to the future SAOCOM-CS (L-band 1.275 GHz) mission. Using forest and radar data from the BioSAR 2008 campaign at the Krycklan test site in northern Sweden the expected performance of SAOCOM-CS is evaluated and compared with the E-SAR airborne L- band SAR (1.300 GHz). It is found that SAOCOM-CS data produce retrievals on par with those obtained with E-SAR, with retrievals having a relative RMSE of 30% or less. This holds true even if the acquisitions are limited to a single polarization, with HH results shown as an example.

Estimating Aboveground Biomass in Tropical Forests: Field Methods and Error Analysis for the Calibration of Remote Sensing Observations

DOE PAGES

Gonçalves, Fabio; Treuhaft, Robert; Law, Beverly; ...

2017-01-07

Mapping and monitoring of forest carbon stocks across large areas in the tropics will necessarily rely on remote sensing approaches, which in turn depend on field estimates of biomass for calibration and validation purposes. Here, we used field plot data collected in a tropical moist forest in the central Amazon to gain a better understanding of the uncertainty associated with plot-level biomass estimates obtained specifically for the calibration of remote sensing measurements. In addition to accounting for sources of error that would be normally expected in conventional biomass estimates (e.g., measurement and allometric errors), we examined two sources of uncertaintymore » that are specific to the calibration process and should be taken into account in most remote sensing studies: the error resulting from spatial disagreement between field and remote sensing measurements (i.e., co-location error), and the error introduced when accounting for temporal differences in data acquisition. We found that the overall uncertainty in the field biomass was typically 25% for both secondary and primary forests, but ranged from 16 to 53%. Co-location and temporal errors accounted for a large fraction of the total variance (>65%) and were identified as important targets for reducing uncertainty in studies relating tropical forest biomass to remotely sensed data. Although measurement and allometric errors were relatively unimportant when considered alone, combined they accounted for roughly 30% of the total variance on average and should not be ignored. Lastly, our results suggest that a thorough understanding of the sources of error associated with field-measured plot-level biomass estimates in tropical forests is critical to determine confidence in remote sensing estimates of carbon stocks and fluxes, and to develop strategies for reducing the overall uncertainty of remote sensing approaches.« less

Size and frequency of natural forest disturbances and the Amazon forest carbon balance

PubMed Central

Espírito-Santo, Fernando D.B.; Gloor, Manuel; Keller, Michael; Malhi, Yadvinder; Saatchi, Sassan; Nelson, Bruce; Junior, Raimundo C. Oliveira; Pereira, Cleuton; Lloyd, Jon; Frolking, Steve; Palace, Michael; Shimabukuro, Yosio E.; Duarte, Valdete; Mendoza, Abel Monteagudo; López-González, Gabriela; Baker, Tim R.; Feldpausch, Ted R.; Brienen, Roel J.W.; Asner, Gregory P.; Boyd, Doreen S.; Phillips, Oliver L.

2014-01-01

Forest inventory studies in the Amazon indicate a large terrestrial carbon sink. However, field plots may fail to represent forest mortality processes at landscape-scales of tropical forests. Here we characterize the frequency distribution of disturbance events in natural forests from 0.01 ha to 2,651 ha size throughout Amazonia using a novel combination of forest inventory, airborne lidar and satellite remote sensing data. We find that small-scale mortality events are responsible for aboveground biomass losses of ~1.7 Pg C y−1 over the entire Amazon region. We also find that intermediate-scale disturbances account for losses of ~0.2 Pg C y−1, and that the largest-scale disturbances as a result of blow-downs only account for losses of ~0.004 Pg C y−1. Simulation of growth and mortality indicates that even when all carbon losses from intermediate and large-scale disturbances are considered, these are outweighed by the net biomass accumulation by tree growth, supporting the inference of an Amazon carbon sink. PMID:24643258

Size and frequency of natural forest disturbances and the Amazon forest carbon balance.

PubMed

Espírito-Santo, Fernando D B; Gloor, Manuel; Keller, Michael; Malhi, Yadvinder; Saatchi, Sassan; Nelson, Bruce; Junior, Raimundo C Oliveira; Pereira, Cleuton; Lloyd, Jon; Frolking, Steve; Palace, Michael; Shimabukuro, Yosio E; Duarte, Valdete; Mendoza, Abel Monteagudo; López-González, Gabriela; Baker, Tim R; Feldpausch, Ted R; Brienen, Roel J W; Asner, Gregory P; Boyd, Doreen S; Phillips, Oliver L

2014-03-18

Forest inventory studies in the Amazon indicate a large terrestrial carbon sink. However, field plots may fail to represent forest mortality processes at landscape-scales of tropical forests. Here we characterize the frequency distribution of disturbance events in natural forests from 0.01 ha to 2,651 ha size throughout Amazonia using a novel combination of forest inventory, airborne lidar and satellite remote sensing data. We find that small-scale mortality events are responsible for aboveground biomass losses of ~1.7 Pg C y(-1) over the entire Amazon region. We also find that intermediate-scale disturbances account for losses of ~0.2 Pg C y(-1), and that the largest-scale disturbances as a result of blow-downs only account for losses of ~0.004 Pg C y(-1). Simulation of growth and mortality indicates that even when all carbon losses from intermediate and large-scale disturbances are considered, these are outweighed by the net biomass accumulation by tree growth, supporting the inference of an Amazon carbon sink.

Differential responses of Bolivian timber species to prescribed fire and other gap treatments

Treesearch

Debora K. Kennard; Francis E. Putz

2005-01-01

We followed the establishment and growth response of 13 commercial tree species to canopy opening, above-ground biomass removal, and experimental burns of low and high intensities in a lowland dry forest in Bolivia. Three patterns of response to treatments were observed among the most abundant commercial tree species. (1) Shade-intolerant species regenerated mostly...

Equations for Estimating Biomass of Herbaceous and Woody Vegetation in Early-Successional Southern Appalachian Pine-Hardwood Forests

Treesearch

Katherine J. Elliott; Barton D. Clinton

1993-01-01

Allometric equations were developed to predict aboveground dry weight of herbaceous and woody species on prescribe-burned sites in the Southern Appalachians. Best-fit least-square regression models were developed using diamet,er, height, or both, as the independent variables and dry weight as the dependent variable. Coefficients of determination for the selected total...

Contrasting impacts of continuous moderate drought and episodic severe droughts on the aboveground-biomass increment and litterfall of three coexisting Mediterranean woody species.

PubMed

Liu, Daijun; Ogaya, Romà; Barbeta, Adrià; Yang, Xiaohong; Peñuelas, Josep

2015-11-01

Climate change is predicted to increase the aridity in the Mediterranean Basin and severely affect forest productivity and composition. The responses of forests to different timescales of drought, however, are still poorly understood because extreme and persistent moderate droughts can produce nonlinear responses in plants. We conducted a rainfall-manipulation experiment in a Mediterranean forest dominated by Quercus ilex, Phillyrea latifolia, and Arbutus unedo in the Prades Mountains in southern Catalonia from 1999 to 2014. The experimental drought significantly decreased forest aboveground-biomass increment (ABI), tended to increase the litterfall, and decreased aboveground net primary production throughout the 15 years of the study. The responses to the experimental drought were highly species-specific. A. unedo suffered a significant reduction in ABI, Q. ilex experienced a decrease during the early experiment (1999-2003) and in the extreme droughts of 2005-2006 and 2011-2012, and P. latifolia was unaffected by the treatment. The drought treatment significantly increased branch litterfall, especially in the extremely dry year of 2011, and also increased overall leaf litterfall. The drought treatment reduced the fruit production of Q. ilex, which affected seedling recruitment. The ABIs of all species were highly correlated with SPEI in early spring, whereas the branch litterfalls were better correlated with summer SPEIs and the leaf and fruit litterfalls were better correlated with autumn SPEIs. These species-specific responses indicated that the dominant species (Q. ilex) could be partially replaced by the drought-resistant species (P. latifolia). However, the results of this long-term study also suggest that the effect of drought treatment has been dampened over time, probably due to a combination of demographic compensation, morphological and physiological acclimation, and epigenetic changes. However, the structure of community (e.g., species composition, dominance, and stand density) may be reordered when a certain drought threshold is reached. © 2015 John Wiley & Sons Ltd.

Examining spectral properties of Landsat 8 OLI for predicting above-ground carbon of Labanan Forest, Berau

NASA Astrophysics Data System (ADS)

Suhardiman, A.; Tampubolon, B. A.; Sumaryono, M.

2018-04-01

Many studies revealed significant correlation between satellite image properties and forest data attributes such as stand volume, biomass or carbon stock. However, further study is still relevant due to advancement of remote sensing technology as well as improvement on methods of data analysis. In this study, the properties of three vegetation indices derived from Landsat 8 OLI were tested upon above-ground carbon stock data from 50 circular sample plots (30-meter radius) from ground survey in PT. Inhutani I forest concession in Labanan, Berau, East Kalimantan. Correlation analysis using Pearson method exhibited a promising results when the coefficient of correlation (r-value) was higher than 0.5. Further regression analysis was carried out to develop mathematical model describing the correlation between sample plots data and vegetation index image using various mathematical models.Power and exponential model were demonstrated a good result for all vegetation indices. In order to choose the most adequate mathematical model for predicting Above-ground Carbon (AGC), the Bayesian Information Criterion (BIC) was applied. The lowest BIC value (i.e. -376.41) shown by Transformed Vegetation Index (TVI) indicates this formula, AGC = 9.608*TVI21.54, is the best predictor of AGC of study area.

Biomass production efficiency controlled by management in temperate and boreal ecosystems

NASA Astrophysics Data System (ADS)

Campioli, M.; Vicca, S.; Luyssaert, S.; Bilcke, J.; Ceschia, E.; Chapin, F. S., III; Ciais, P.; Fernández-Martínez, M.; Malhi, Y.; Obersteiner, M.; Olefeldt, D.; Papale, D.; Piao, S. L.; Peñuelas, J.; Sullivan, P. F.; Wang, X.; Zenone, T.; Janssens, I. A.

2015-11-01

Plants acquire carbon through photosynthesis to sustain biomass production, autotrophic respiration and production of non-structural compounds for multiple purposes. The fraction of photosynthetic production used for biomass production, the biomass production efficiency, is a key determinant of the conversion of solar energy to biomass. In forest ecosystems, biomass production efficiency was suggested to be related to site fertility. Here we present a database of biomass production efficiency from 131 sites compiled from individual studies using harvest, biometric, eddy covariance, or process-based model estimates of production. The database is global, but dominated by data from Europe and North America. We show that instead of site fertility, ecosystem management is the key factor that controls biomass production efficiency in terrestrial ecosystems. In addition, in natural forests, grasslands, tundra, boreal peatlands and marshes, biomass production efficiency is independent of vegetation, environmental and climatic drivers. This similarity of biomass production efficiency across natural ecosystem types suggests that the ratio of biomass production to gross primary productivity is constant across natural ecosystems. We suggest that plant adaptation results in similar growth efficiency in high- and low-fertility natural systems, but that nutrient influxes under managed conditions favour a shift to carbon investment from the belowground flux of non-structural compounds to aboveground biomass.

Fusion of GEDI, ICESAT2 & NISAR data for above ground biomass mapping in Sonoma County, California

NASA Astrophysics Data System (ADS)

Duncanson, L.; Simard, M.; Thomas, N. M.; Neuenschwander, A. L.; Hancock, S.; Armston, J.; Dubayah, R.; Hofton, M. A.; Huang, W.; Tang, H.; Marselis, S.; Fatoyinbo, T.

2017-12-01

Several upcoming NASA missions will collect data sensitive to forest structure (GEDI, ICESAT-2 & NISAR). The LiDAR and SAR data collected by these missions will be used in coming years to map forest aboveground biomass at various resolutions. This research focuses on developing and testing multi-sensor data fusion approaches in advance of these missions. Here, we present the first case study of a CMS-16 grant with results from Sonoma County, California. We simulate lidar and SAR datasets from GEDI, ICESAT-2 and NISAR using airborne discrete return lidar and UAVSAR data, respectively. GEDI and ICESAT-2 signals are simulated from high point density discrete return lidar that was acquired over the entire county in 2014 through a previous CMS project (Dubayah & Hurtt, CMS-13). NISAR is simulated from L-band UAVSAR data collected in 2014. These simulations are empirically related to 300 field plots of aboveground biomass as well as a 30m biomass map produced from the 2014 airborne lidar data. We model biomass independently for each simulated mission dataset and then test two fusion methods for County-wide mapping 1) a pixel based approach and 2) an object oriented approach. In the pixel-based approach, GEDI and ICESAT-2 biomass models are calibrated over field plots and applied in orbital simulations for a 2-year period of the GEDI and ICESAT-2 missions. These simulated samples are then used to calibrate UAVSAR data to produce a 0.25 ha map. In the object oriented approach, the GEDI and ICESAT-2 data are identical to the pixel-based approach, but calibrate image objects of similar L-band backscatter rather than uniform pixels. The results of this research demonstrate the estimated ability for each of these three missions to independently map biomass in a temperate, high biomass system, as well as the potential improvement expected through combining mission datasets.

Mapping forest structure, species gradients and growth in an urban area using lidar and hyperspectral imagery

NASA Astrophysics Data System (ADS)

Gu, Huan

Urban forests play an important role in the urban ecosystem by providing a range of ecosystem services. Characterization of forest structure, species variation and growth in urban forests is critical for understanding the status, function and process of urban ecosystems, and helping maximize the benefits of urban ecosystems through management. The development of methods and applications to quantify urban forests using remote sensing data has lagged the study of natural forests due to the heterogeneity and complexity of urban ecosystems. In this dissertation, I quantify and map forest structure, species gradients and forest growth in an urban area using discrete-return lidar, airborne imaging spectroscopy and thermal infrared data. Specific objectives are: (1) to demonstrate the utility of leaf-off lidar originally collected for topographic mapping to characterize and map forest structure and associated uncertainties, including aboveground biomass, basal area, diameter, height and crown size; (2) to map species gradients using forest structural variables estimated from lidar and foliar functional traits, vegetation indices derived from AVIRIS hyperspectral imagery in conjunction with field-measured species data; and (3) to identify factors related to relative growth rates in aboveground biomass in the urban forests, and assess forest growth patterns across areas with varying degree of human interactions. The findings from this dissertation are: (1) leaf-off lidar originally acquired for topographic mapping provides a robust, potentially low-cost approach to quantify spatial patterns of forest structure and carbon stock in urban areas; (2) foliar functional traits and vegetation indices from hyperspectral data capture gradients of species distributions in the heterogeneous urban landscape; (3) species gradients, stand structure, foliar functional traits and temperature are strongly related to forest growth in the urban forests; and (4) high uncertainties in our ability to map forest structure, species gradient and growth rate occur in residential neighborhoods and along forest edges. Maps generated from this dissertation provide estimates of broad-scale spatial variations in forest structure, species distributions and growth to the city forest managers. The associated maps of uncertainty help managers understand the limitations of the maps and identify locations where the maps are more reliable and where more data are needed.

Becoming less tolerant with age: sugar maple, shade, and ontogeny.

PubMed

Sendall, Kerrie M; Lusk, Christopher H; Reich, Peter B

2015-12-01

Although shade tolerance is often assumed to be a fixed trait, recent work suggests ontogenetic changes in the light requirements of tree species. We determined the influence of gas exchange, biomass distribution, and self-shading on ontogenetic variation in the instantaneous aboveground carbon balance of Acer saccharum. We quantified the aboveground biomass distributions of 18 juveniles varying in height and growing in low light in a temperate forest understory in Minnesota, USA. Gas exchange rates of leaf and stem tissues were measured, and the crown architecture of each individual was quantified. The YPLANT program was used to estimate the self-shaded fraction of each crown and to model net leaf-level carbon gain. Leaf respiration and photosynthesis per gram of leaf tissue increased with plant size. In contrast, stem respiration rates per gram of stem tissue declined, reflecting a shift in the distribution of stem diameter sizes from smaller (with higher respiration) to larger diameter classes. However, these trends were outweighed by ontogenetic increases in self-shading (which reduces the net photosynthesis realized) and stem mass fraction (which increases the proportion of purely respiratory tissue) in terms of influence on net carbon exchange. As a result, net carbon gain per gram of aboveground plant tissue declined with increasing plant size, and the instantaneous aboveground light compensation point increased. When estimates of root respiration were included to model whole-plant carbon gain and light compensation points, relationships with plant size were even more pronounced. Our findings show how an interplay of gas exchange, self-shading, and biomass distribution shapes ontogenetic changes in shade tolerance.

Radioactive and Stable Cesium Distributions in Fukushima Forests

NASA Astrophysics Data System (ADS)

Ioshchenko, V.; Kivva, S.; Konoplev, A.; Nanba, K.; Onda, Y.; Takase, T.; Zheleznyak, M.

2015-12-01

Fukushima Dai-ichi NPP accident has resulted in release into the environment of large amounts of 134Cs and 137Cs and in radioactive contamination of terrestrial and aquatic ecosystems. In Fukushima prefecture up to 2/3 of the most contaminated territory is covered with forests, and understanding of its further fate in the forest ecosystems is essential for elaboration of the long-term forestry strategy. At the early stage, radiocesium was intercepted by the trees' canopies. Numerous studies reported redistribution of the initial fallout in Fukushima forests in the followed period due to litterfall and leaching of radiocesium from the foliage with precipitations. By now these processes have transported the major part of deposited radiocesium to litter and soil compartments. Future levels of radiocesium activities in the aboveground biomass will depend on relative efficiencies of the radiocesium root uptake and its return to the soil surface with litterfall and precipitations. Radiocesium soil-to-plant transfer factors for typical tree species, soil types and landscape conditions of Fukushima prefecture have not been studied well; moreover, they may change in time with approaching to the equilibrium between radioactive and stable cesium isotopes in the ecosystem. The present paper reports the results of several ongoing projects carried out by Institute of Environmental Radioactivity of Fukushima University at the experimental sites in Fukushima prefecture. For typical Japanese cedar (Cryptomeria japonica) forest, we determined distributions of radiocesium in the ecosystem and in the aboveground biomass compartments by the end of 2014; available results for 2015 are presented, too, as well as the results of test application of D-shuttle dosimeters for characterization of seasonal variations of radiocesium activity in wood. Based on the radiocesium activities in biomass we derived the upper estimates of its incorporation and root uptake fluxes, 0.7% and 3% of the total inventory in the ecosystem. Measurements of stable cesium concentrations in the biomass compartments enabled obtaining the more precise estimates. Return fluxes of both radioactive and stable cesium also were quantified, which forms the basis for modelling of the long-term redistribution of radiocesium in the studied ecosystem.

Ecological Impacts of Deforestation and Forest Degradation in the Peat Swamp Forests of Northwestern Borneo

NASA Astrophysics Data System (ADS)

Nguyen, Ha Thanh

Tropical peatlands have some of the highest carbon densities of any ecosystem and are under enormous development pressure. This dissertation aimed to provide better estimates of the scales and trends of ecological impacts from tropical peatland deforestation and degradation across more than 7,000 hectares of both intact and disturbed peatlands in northwestern Borneo. We combined direct field sampling and airborne Light Detection And Ranging (LiDAR) data to empirically quantify forest structures and aboveground live biomass across a largely intact tropical peat dome. The observed biomass density of 217.7 +/- 28.3 Mg C hectare-1 was very high, exceeding many other tropical rainforests. The canopy trees were 65m in height, comprising 81% of the aboveground biomass. Stem density was observed to increase across the 4m elevational gradient from the dome margin to interior with decreasing stem height, crown area and crown roughness. We also developed and implemented a multi-temporal, Landsat resolution change detection algorithm for identify disturbance events and assessing forest trends in aseasonal tropical peatlands. The final map product achieved more than 92% user's and producer's accuracy, revealing that after more than 25 years of management and disturbances, only 40% of the area was intact forest. Using a chronosequence approach, with a space for time substitution, we then examined the temporal dynamics of peatlands and their recovery from disturbance. We observed widespread arrested succession in previously logged peatlands consistent with hydrological limits on regeneration and degraded peat quality following canopy removal. We showed that clear-cutting, selective logging and drainage could lead to different modes of regeneration and found that statistics of the Enhanced Vegetation Index and LiDAR height metrics could serve as indicators of harvesting intensity, impacts, and regeneration stage. Long-term, continuous monitoring of the hydrology and ecology of peatland can provide key insights regarding best management practices, restoration, and conservation priorities for this unique and rapidly disappearing ecosystem.

On the Correlation Between Biomass and the P-Band Polarisation Phase Difference, and Its Potential for Biomass and Tree Number Density Estimation

NASA Astrophysics Data System (ADS)

Soja, Maciej J.; Blomberg, Erik; Ulander, Lars M. H.

2015-04-01

In this paper, a significant correlation between the HH/VV phase difference (polarisation phase difference, PPD) and the above-ground biomass (AGB) is observed for incidence angles above 30° in airborne P-band SAR data acquired over two boreal test sites in Sweden. A geometric model is used to explain the dependence of the AGB on tree height, stem radius, and tree number density, whereas a cylinder-over-ground model is used to explain the dependence of the PPD on the same three forest parameters. The models show that forest anisotropy need to be accounted for at P-band in order to obtain a linear relationship between the PPD and the AGB. An approach to the estimation of tree number density is proposed, based on a comparison between the modelled and observed PPDs.

Multi-Sensor Remote Sensing of Forest Dynamics in Central Siberia

NASA Technical Reports Server (NTRS)

Ransom, K. J.; Sun, G.; Kharuk, V. I.; Howl, J.

2011-01-01

The forested regions of Siberia, Russia are vast and contain about a quarter of the world's forests that have not experienced harvesting. However, many Siberian forests are facing twin pressures of rapidly changing climate and increasing timber harvest activity. Monitoring the dynamics and mapping the structural parameters of the forest is important for understanding the causes and consequences of changes observed in these areas. Because of the inaccessibility and large extent of this forest, remote sensing data can play an important role for observing forest state and change. In Central Siberia, multi-sensor remote sensing data have been used to monitor forest disturbances and to map above-ground biomass from the Sayan Mountains in the south to the taiga-tundra boundaries in the north. Radar images from the Shuttle Imaging Radar-C (SIR-C)/XSAR mission were used for forest biomass estimation in the Sayan Mountains. Radar images from the Japanese Earth Resources Satellite-1 (JERS-1), European Remote Sensing Satellite-1 (ERS-1) and Canada's RADARSAT-1, and data from ETM+ on-board Landsat-7 were used to characterize forest disturbances from logging, fire, and insect damage in Boguchany and Priangare areas.

Tall Amazonian forests are less sensitive to precipitation variability

NASA Astrophysics Data System (ADS)

Giardina, Francesco; Konings, Alexandra G.; Kennedy, Daniel; Alemohammad, Seyed Hamed; Oliveira, Rafael S.; Uriarte, Maria; Gentine, Pierre

2018-06-01

Climate change is altering the dynamics, structure and function of the Amazon, a biome deeply connected to the Earth's carbon cycle. Climate factors that control the spatial and temporal variations in forest photosynthesis have been well studied, but the influence of forest height and age on this controlling effect has rarely been considered. Here, we present remote sensing observations of solar-induced fluorescence (a proxy for photosynthesis), precipitation, vapour-pressure deficit and canopy height, together with estimates of forest age and aboveground biomass. We show that photosynthesis in tall Amazonian forests, that is, forests above 30 m, is three times less sensitive to precipitation variability than in shorter (less than 20 m) forests. Taller Amazonian forests are also found to be older, have more biomass and deeper rooting systems1, which enable them to access deeper soil moisture and make them more resilient to drought. We suggest that forest height and age are an important control of photosynthesis in response to interannual precipitation fluctuations. Although older and taller trees show less sensitivity to precipitation variations, they are more susceptible to fluctuations in vapour-pressure deficit. Our findings illuminate the response of Amazonian forests to water stress, droughts and climate change.

Aboveground Biomass and Dynamics of Forest Attributes using LiDAR Data and Vegetation Model

NASA Astrophysics Data System (ADS)

V V L, P. A.

2015-12-01

In recent years, biomass estimation for tropical forests has received much attention because of the fact that regional biomass is considered to be a critical input to climate change. Biomass almost determines the potential carbon emission that could be released to the atmosphere due to deforestation or conservation to non-forest land use. Thus, accurate biomass estimation is necessary for better understating of deforestation impacts on global warming and environmental degradation. In this context, forest stand height inclusion in biomass estimation plays a major role in reducing the uncertainty in the estimation of biomass. The improvement in the accuracy in biomass shall also help in meeting the MRV objectives of REDD+. Along with the precise estimate of biomass, it is also important to emphasize the role of vegetation models that will most likely become an important tool for assessing the effects of climate change on potential vegetation dynamics and terrestrial carbon storage and for managing terrestrial ecosystem sustainability. Remote sensing is an efficient way to estimate forest parameters in large area, especially at regional scale where field data is limited. LIDAR (Light Detection And Ranging) provides accurate information on the vertical structure of forests. We estimated average tree canopy heights and AGB from GLAS waveform parameters by using a multi-regression linear model in forested area of Madhya Pradesh (area-3,08,245 km2), India. The derived heights from ICESat-GLAS were correlated with field measured tree canopy heights for 60 plots. Results have shown a significant correlation of R2= 74% for top canopy heights and R2= 57% for stand biomass. The total biomass estimation 320.17 Mt and canopy heights are generated by using random forest algorithm. These canopy heights and biomass maps were used in vegetation models to predict the changes biophysical/physiological characteristics of forest according to the changing climate. In our study we have used Dynamic Global Vegetation Model to understand the possible vegetation dynamics in the event of climate change. The vegetation represents a biogeographic regime. Simulations were carried out for 70 years time period. The model produced leaf area index and biomass for each plant functional type and biome for each grid in that region.

Bridging scale gaps between regional maps of forest aboveground biomass and field sampling plots using TanDEM-X data

NASA Astrophysics Data System (ADS)

Ni, W.; Zhang, Z.; Sun, G.

2017-12-01

Several large-scale maps of forest AGB have been released [1] [2] [3]. However, these existing global or regional datasets were only approximations based on combining land cover type and representative values instead of measurements of actual forest aboveground biomass or forest heights [4]. Rodríguez-Veiga et al[5] reported obvious discrepancies of existing forest biomass stock maps with in-situ observations in Mexico. One of the biggest challenges to the credibility of these maps comes from the scale gaps between the size of field sampling plots used to develop(or validate) estimation models and the pixel size of these maps and the availability of field sampling plots with sufficient size for the verification of these products [6]. It is time-consuming and labor-intensive to collect sufficient number of field sampling data over the plot size of the same as resolutions of regional maps. The smaller field sampling plots cannot fully represent the spatial heterogeneity of forest stands as shown in Figure 1. Forest AGB is directly determined by forest heights, diameter at breast height (DBH) of each tree, forest density and tree species. What measured in the field sampling are the geometrical characteristics of forest stands including the DBH, tree heights and forest densities. The LiDAR data is considered as the best dataset for the estimation of forest AGB. The main reason is that LiDAR can directly capture geometrical features of forest stands by its range detection capabilities.The remotely sensed dataset, which is capable of direct measurements of forest spatial structures, may serve as a ladder to bridge the scale gaps between the pixel size of regional maps of forest AGB and field sampling plots. Several researches report that TanDEM-X data can be used to characterize the forest spatial structures [7, 8]. In this study, the forest AGB map of northeast China were produced using ALOS/PALSAR data taking TanDEM-X data as a bridges. The TanDEM-X InSAR data used in this study and forest AGB map was shown in Figure 2. The technique details and further analysis will be given in the final report. AcknowledgmentThis work was supported in part by the National Basic Research Program of China (Grant No. 2013CB733401, 2013CB733404), and in part by the National Natural Science Foundation of China (Grant Nos. 41471311, 41371357, 41301395).

Aboveground carbon sequestration in dry temperate forests varies with climate not fire regime.

PubMed

Gordon, Christopher E; Bendall, Eli R; Stares, Mitchell G; Collins, Luke; Bradstock, Ross A

2018-06-01

The storage of carbon in plant tissues and debris has been proposed as a method to offset anthropogenic increases in atmospheric [CO 2 ]. Temperate forests represent significant above-ground carbon (AGC) "sinks" because their relatively fast growth and slow decay rates optimise carbon assimilation. Fire is a common disturbance event in temperate forests globally that should strongly influence AGC because: discrete fires consume above-ground biomass releasing carbon to the atmosphere, and the long-term application of different fire-regimes select for specific plant communities that sequester carbon at different rates. We investigated the latter process by quantifying AGC storage at 104 sites in the Sydney Basin Bioregion, Australia, relative to differences in components of the fire regime: frequency, severity and interfire interval. To predict the potential impacts of future climate change on fire/AGC interactions, we stratified our field sites across gradients of mean annual temperature and precipitation and quantified within- and between-factor interactions between the fire and climate variables. In agreement with previous studies, large trees were the primary AGC sink, accounting for ~70% of carbon at sites. Generalised additive models showed that mean annual temperature was the strongest predictor of AGC storage, with a 54% near-linear decrease predicted across the 6.1°C temperature range experienced at sites. Mean annual precipitation, fire frequency, fire severity and interfire interval were consistently poor predictors of total above-ground storage, although there were some significant relationships with component stocks. Our results show resilience of AGC to frequent and severe wildfire and suggest temperature mediated decreases in forest carbon storage under future climate change predictions. © 2018 John Wiley & Sons Ltd.

Climate controls on forest productivity along the climate gradient of the western Sierra Nevada

NASA Astrophysics Data System (ADS)

Kelly, A. E.; Goulden, M. L.

2010-12-01

The broad climate gradient of the slopes of the western Sierra Nevada mountains supports ecosystems spanning extremes of productivity, biomass, and function. We are using this natural environmental gradient to understand how climate controls NPP, aboveground biomass, species' range limits, and phenology. Our experimental approach combines eddy covariance, sap flow, dendrometer, and litterfall measurements in combination with soil and hydrological data from the Southern Sierra Critical Zone Observatory (SSCZO). We have found that above about 2500 m, forest productivity is limited by winter cold, while below 1200 m, productivity is likely limited by summer drought. The sweet spot between these elevations has a nearly year-long growing season despite a snowpack that persists for as long as six months. Our results show that small differences in temperature can markedly alter the water balance and productivity of mixed conifer forests.

Benefits of tree mixes in carbon plantings

NASA Astrophysics Data System (ADS)

Hulvey, Kristin B.; Hobbs, Richard J.; Standish, Rachel J.; Lindenmayer, David B.; Lach, Lori; Perring, Michael P.

2013-10-01

Increasingly governments and the private sector are using planted forests to offset carbon emissions. Few studies, however, examine how tree diversity -- defined here as species richness and/or stand composition -- affects carbon storage in these plantings. Using aboveground tree biomass as a proxy for carbon storage, we used meta-analysis to compare carbon storage in tree mixtures with monoculture plantings. Tree mixes stored at least as much carbon as monocultures consisting of the mixture's most productive species and at times outperformed monoculture plantings. In mixed-species stands, individual species, and in particular nitrogen-fixing trees, increased stand biomass. Further motivations for incorporating tree richness into planted forests include the contribution of diversity to total forest carbon-pool development, carbon-pool stability and the provision of extra ecosystem services. Our findings suggest a two-pronged strategy for designing carbon plantings including: (1) increased tree species richness; and (2) the addition of species that contribute to carbon storage and other target functions.

The Carbon Cycle and Hurricanes in the United States between 1900 and 2011

PubMed Central

Dahal, Devendra; Liu, Shuguang; Oeding, Jennifer

2014-01-01

Hurricanes cause severe impacts on forest ecosystems in the United States. These events can substantially alter the carbon biogeochemical cycle at local to regional scales. We selected all tropical storms and more severe events that made U.S. landfall between 1900 and 2011 and used hurricane best track database, a meteorological model (HURRECON), National Land Cover Database (NLCD), U. S. Department of Agirculture Forest Service biomass dataset, and pre- and post-MODIS data to quantify individual event and annual biomass mortality. Our estimates show an average of 18.2 TgC/yr of live biomass mortality for 1900–2011 in the US with strong spatial and inter-annual variability. Results show Hurricane Camille in 1969 caused the highest aboveground biomass mortality with 59.5 TgC. Similarly 1954 had the highest annual mortality with 68.4 TgC attributed to landfalling hurricanes. The results presented are deemed useful to further investigate historical events, and the methods outlined are potentially beneficial to quantify biomass loss in future events. PMID:24903486

The carbon cycle and hurricanes in the United States between 1900 and 2011

USGS Publications Warehouse

Dahal, Devendra; Liu, Shu-Guang; Oeding, Jennifer

2014-01-01

Hurricanes cause severe impacts on forest ecosystems in the United States. These events can substantially alter the carbon biogeochemical cycle at local to regional scales. We selected all tropical storms and more severe events that made U.S. landfall between 1900 and 2011 and used hurricane best track database, a meteorological model (HURRECON), National Land Cover Database (NLCD), U. S. Department of Agirculture Forest Service biomass dataset, and pre- and post-MODIS data to quantify individual event and annual biomass mortality. Our estimates show an average of 18.2 TgC/yr of live biomass mortality for 1900–2011 in the US with strong spatial and inter-annual variability. Results show Hurricane Camille in 1969 caused the highest aboveground biomass mortality with 59.5 TgC. Similarly 1954 had the highest annual mortality with 68.4 TgC attributed to landfalling hurricanes. The results presented are deemed useful to further investigate historical events, and the methods outlined are potentially beneficial to quantify biomass loss in future events.

Large Footprint LiDAR Data Processing for Ground Detection and Biomass Estimation

NASA Astrophysics Data System (ADS)

Zhuang, Wei

Ground detection in large footprint waveform Light Detection And Ranging (LiDAR) data is important in calculating and estimating downstream products, especially in forestry applications. For example, tree heights are calculated as the difference between the ground peak and first returned signal in a waveform. Forest attributes, such as aboveground biomass, are estimated based on the tree heights. This dissertation investigated new metrics and algorithms for estimating aboveground biomass and extracting ground peak location in large footprint waveform LiDAR data. In the first manuscript, an accurate and computationally efficient algorithm, named Filtering and Clustering Algorithm (FICA), was developed based on a set of multiscale second derivative filters for automatically detecting the ground peak in an waveform from Land, Vegetation and Ice Sensor. Compared to existing ground peak identification algorithms, FICA was tested in different land cover type plots and showed improved accuracy in ground detections of the vegetation plots and similar accuracy in developed area plots. Also, FICA adopted a peak identification strategy rather than following a curve-fitting process, and therefore, exhibited improved efficiency. In the second manuscript, an algorithm was developed specifically for shrub waveforms. The algorithm only partially fitted the shrub canopy reflection and detected the ground peak by investigating the residual signal, which was generated by deducting a Gaussian fitting function from the raw waveform. After the deduction, the overlapping ground peak was identified as the local maximum of the residual signal. In addition, an applicability model was built for determining waveforms where the proposed PCF algorithm should be applied. In the third manuscript, a new set of metrics was developed to increase accuracy in biomass estimation models. The metrics were based on the results of Gaussian decomposition. They incorporated both waveform intensity represented by the area covered by a Gaussian function and its associated heights, which was the centroid of the Gaussian function. By considering signal reflection of different vegetation layers, the developed metrics obtained better estimation accuracy in aboveground biomass when compared to existing metrics. In addition, the new developed metrics showed strong correlation with other forest structural attributes, such as mean Diameter at Breast Height (DBH) and stem density. In sum, the dissertation investigated the various techniques for large footprint waveform LiDAR processing for detecting the ground peak and estimating biomass. The novel techniques developed in this dissertation showed better performance than existing methods or metrics.

Site preparation burning to improve southern Appalachian pine-hardwood stands: aboveground biomass, forest floor mass, and nitrogen and carbon pools

Treesearch

J.M. Vose; W.T. Swank

1993-01-01

Prescribed fire is currently used as a site preparation treat-ment in mixed pine-hardwood ecosystems of the southern Appalachians.Stands receiving this treatment typically consist of mixtures of pitch pine (Pinus rigidu Mill.), scarlet oak (Quercus coccinea Muenchh.), chestnut oak (Quercus prinus L.), red maple (Acer rubrum L.), and dense under-stories dominated by...

Comparison of modeling approaches for carbon partitioning: Impact on estimates of global net primary production and equilibrium biomass of woody vegetation from MODIS GPP

Treesearch

Takeshi Ise; Creighton M. Litton; Christian P. Giardina; Akihiko Ito

2010-01-01

Partitioning of gross primary production (GPP) to aboveground versus belowground, to growth versus respiration, and to short versus long�]lived tissues exerts a strong influence on ecosystem structure and function, with potentially large implications for the global carbon budget. A recent meta-analysis of forest ecosystems suggests that carbon partitioning...

Local climatic conditions constrain soil yeast diversity patterns in Mediterranean forests, woodlands and scrub biome.

PubMed

Yurkov, Andrey M; Röhl, Oliver; Pontes, Ana; Carvalho, Cláudia; Maldonado, Cristina; Sampaio, José Paulo

2016-02-01

Soil yeasts represent a poorly known fraction of the soil microbiome due to limited ecological surveys. Here, we provide the first comprehensive inventory of cultivable soil yeasts in a Mediterranean ecosystem, which is the leading biodiversity hotspot for vascular plants and vertebrates in Europe. We isolated and identified soil yeasts from forested sites of Serra da Arrábida Natural Park (Portugal), representing the Mediterranean forests, woodlands and scrub biome. Both cultivation experiments and the subsequent species richness estimations suggest the highest species richness values reported to date, resulting in a total of 57 and 80 yeast taxa, respectively. These values far exceed those reported for other forest soils in Europe. Furthermore, we assessed the response of yeast diversity to microclimatic environmental factors in biotopes composed of the same plant species but showing a gradual change from humid broadleaf forests to dry maquis. We observed that forest properties constrained by precipitation level had strong impact on yeast diversity and on community structure and lower precipitation resulted in an increased number of rare species and decreased evenness values. In conclusion, the structure of soil yeast communities mirrors the environmental factors that affect aboveground phytocenoses, aboveground biomass and plant projective cover. © FEMS 2015. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Investigating the relationship between tree heights derived from SIBBORK forest model and remote sensing measurements

NASA Astrophysics Data System (ADS)

Osmanoglu, B.; Feliciano, E. A.; Armstrong, A. H.; Sun, G.; Montesano, P.; Ranson, K.

2017-12-01

Tree heights are one of the most commonly used remote sensing parameters to measure biomass of a forest. In this project, we investigate the relationship between remotely sensed tree heights (e.g. G-LiHT lidar and commercially available high resolution satellite imagery, HRSI) and the SIBBORK modeled tree heights. G-LiHT is a portable, airborne imaging system that simultaneously maps the composition, structure, and function of terrestrial ecosystems using lidar, imaging spectroscopy and thermal mapping. Ground elevation and canopy height models were generated using the lidar data acquired in 2012. A digital surface model was also generated using the HRSI technique from the commercially available WorldView data in 2016. The HRSI derived height and biomass products are available at the plot (10x10m) level. For this study, we parameterized the SIBBORK individual-based gap model for Howland forest, Maine. The parameterization was calibrated using field data for the study site and results show that the simulated forest reproduces the structural complexity of Howland old growth forest, based on comparisons of key variables including, aboveground biomass, forest height and basal area. Furthermore carbon cycle and ecosystem observational capabilities will be enhanced over the next 6 years via the launch of two LiDAR (NASA's GEDI and ICESAT 2) and two SAR (NASA's ISRO NiSAR and ESA's Biomass) systems. Our aim is to present the comparison of canopy height models obtained with SIBBORK forest model and remote sensing techniques, highlighting the synergy between individual-based forest modeling and high-resolution remote sensing.

Methods for estimating aboveground biomass and its components for Douglas-fir and lodgepole pine trees

Treesearch

K.P. Poudel; H. Temesgen

2016-01-01

Estimating aboveground biomass and its components requires sound statistical formulation and evaluation. Using data collected from 55 destructively sampled trees in different parts of Oregon, we evaluated the performance of three groups of methods to estimate total aboveground biomass and (or) its components based on the bias and root mean squared error (RMSE) that...

Aboveground tree biomass statistics for Maine: 1982

Treesearch

Eric H. Wharton; Thomas S. Frieswyk; Anne M. Malley

1985-01-01

Traditional measures of volume inadequately describe the total aboveground wood resource. The 1980-82 inventory of Maine included estimates of aboveground tree biomass on timberland. There are nearly 1,504.4 million green tons of wood and bark in all trees above the ground level, or 88.2 green tons per acre of timberland. Most of the biomass is in growing stock, but 49...

National-scale aboveground biomass geostatistical mapping with FIA inventory and GLAS data: Preparation for sparsely sampled lidar assisted forest inventory

NASA Astrophysics Data System (ADS)

Babcock, C. R.; Finley, A. O.; Andersen, H. E.; Moskal, L. M.; Morton, D. C.; Cook, B.; Nelson, R.

2017-12-01

Upcoming satellite lidar missions, such as GEDI and IceSat-2, are designed to collect laser altimetry data from space for narrow bands along orbital tracts. As a result lidar metric sets derived from these sources will not be of complete spatial coverage. This lack of complete coverage, or sparsity, means traditional regression approaches that consider lidar metrics as explanatory variables (without error) cannot be used to generate wall-to-wall maps of forest inventory variables. We implement a coregionalization framework to jointly model sparsely sampled lidar information and point-referenced forest variable measurements to create wall-to-wall maps with full probabilistic uncertainty quantification of all inputs. We inform the model with USFS Forest Inventory and Analysis (FIA) in-situ forest measurements and GLAS lidar data to spatially predict aboveground forest biomass (AGB) across the contiguous US. We cast our model within a Bayesian hierarchical framework to better model complex space-varying correlation structures among the lidar metrics and FIA data, which yields improved prediction and uncertainty assessment. To circumvent computational difficulties that arise when fitting complex geostatistical models to massive datasets, we use a Nearest Neighbor Gaussian process (NNGP) prior. Results indicate that a coregionalization modeling approach to leveraging sampled lidar data to improve AGB estimation is effective. Further, fitting the coregionalization model within a Bayesian mode of inference allows for AGB quantification across scales ranging from individual pixel estimates of AGB density to total AGB for the continental US with uncertainty. The coregionalization framework examined here is directly applicable to future spaceborne lidar acquisitions from GEDI and IceSat-2. Pairing these lidar sources with the extensive FIA forest monitoring plot network using a joint prediction framework, such as the coregionalization model explored here, offers the potential to improve forest AGB accounting certainty and provide maps for post-model fitting analysis of the spatial distribution of AGB.

Field strategies for the calibration and validation of high-resolution forest carbon maps: Scaling from plots to a three state region MD, DE, & PA, USA.

NASA Astrophysics Data System (ADS)

Dolan, K. A.; Huang, W.; Johnson, K. D.; Birdsey, R.; Finley, A. O.; Dubayah, R.; Hurtt, G. C.

2016-12-01

In 2010 Congress directed NASA to initiate research towards the development of Carbon Monitoring Systems (CMS). In response, our team has worked to develop a robust, replicable framework to quantify and map aboveground forest biomass at high spatial resolutions. Crucial to this framework has been the collection of field-based estimates of aboveground tree biomass, combined with remotely detected canopy and structural attributes, for calibration and validation. Here we evaluate the field- based calibration and validation strategies within this carbon monitoring framework and discuss the implications on local to national monitoring systems. Through project development, the domain of this research has expanded from two counties in MD (2,181 km2), to the entire state of MD (32,133 km2), and most recently the tri-state region of MD, PA, and DE (157,868 km2) and covers forests in four major USDA ecological providences. While there are approximately 1000 Forest Inventory and Analysis (FIA) plots distributed across the state of MD, 60% fell in areas considered non-forest or had conditions that precluded them from being measured in the last forest inventory. Across the two pilot counties, where population and landuse competition is high, that proportion rose to 70% Thus, during the initial phases of this project 850 independent field plots were established for model calibration following a random stratified design to insure the adequate representation of height and vegetation classes found across the state, while FIA data were used as an independent data source for validation. As the project expanded to cover the larger spatial tri-state domain, the strategy was flipped to base calibration on more than 3,300 measured FIA plots, as they provide a standardized, consistent and available data source across the nation. An additional 350 stratified random plots were deployed in the Northern Mixed forests of PA and the Coastal Plains forests of DE for validation.

Architectural plasticity in young Eucalyptus marginata on restored bauxite mines and adjacent natural forest in south-western Australia.

PubMed

Bleby, Timothy M; Colquhoun, Ian J; Adams, Mark A

2009-08-01

The aboveground architecture of Eucalyptus marginata (Jarrah) was investigated in chronosequences of young trees (2.5, 5 and 10 m height) growing in a seasonally dry climate in a natural forest environment with intact soils, and on adjacent restored bauxite mine sites on soils with highly modified A and B horizons above an intact C horizon. Compared to forest trees, trees on restored sites were much younger and faster growing, with straighter, more clearly defined main stems and deeper, narrower crowns containing a greater number of branches that were longer, thinner and more vertically angled. Trees on restored sites also had a higher fraction of biomass in leaves than forest trees, as indicated by 20-25% thicker leaves, 30-70% greater leaf area, 10-30% greater leaf area to sapwood area ratios and 5-30% lesser branch Huber values. Differences in crown architecture and biomass distribution were consistent with putatively greater soil-water, nutrient and light availability on restored sites. Our results demonstrate that under the same climatic conditions, E. marginata displays a high degree of plasticity of aboveground architecture in response to the net effects of resource availability and soil environment. These differences in architecture are likely to have functional consequences in relation to tree hydraulics and growth that, on larger scales, is likely to affect the water and carbon balances of restored forest ecosystems. This study highlights substrate as a significant determinant of tree architecture in water-limited environments. It further suggests that the architecture of young trees on restored sites may need to change again if they are to survive likely longer-term changes in resource availability.

Non-Linear Nitrogen Cycling and Ecosystem Calcium Depletion Along a Temperate Forest Soil Nitrogen Gradient

NASA Astrophysics Data System (ADS)

Sinkhorn, E. R.; Perakis, S. S.; Compton, J. E.; Cromack, K.; Bullen, T. D.

2007-12-01

Understanding how N availability influences base cation stores is critical for assessing long-term ecosystem sustainability. Indices of nitrogen (N) availability and the distribution of nutrients in plant biomass, soil, and soil water were examined across ten Douglas-fir (Pseudotsuga menziesii) stands spanning a three-fold soil N gradient (0-10 cm: 0.21 - 0.69% N, 0-100 cm: 9.2 - 28.8 Mg N ha-1) in the Oregon Coast Range. This gradient is largely the consequence of historical inputs from N2-fixing red alder stands that can add 100-200 kg N ha-1 yr-1 to the ecosystem for decades. Annual net N mineralization and litterfall N return displayed non-linear relationships with soil N, increasing initially, and then decreasing as N-richness increased. In contrast, nitrate leaching from deep soils increased linearly across the soil N gradient and ranged from 0.074 to 30 kg N ha-1 yr-1. Soil exchangeable Ca, Mg, and K pools to 1 m depth were negatively related to nitrate losses across sites. Ca was the only base cation exhibiting concentration decreases in both plant and soil pools across the soil N gradient, and a greater proportion of total available ecosystem Ca was sequestered in aboveground plant biomass at high N, low Ca sites. Our work supports a hierarchical model of coupled N-Ca cycles across gradients of soil N enrichment, with microbial production of mobile nitrate anions leading to depletion of readily available Ca at the ecosystem scale, and plant sequestration promoting Ca conservation as Ca supply diminishes. The preferential storage of Ca in aboveground biomass at high N and low Ca sites, while critical for sustaining plant productivity, may also predispose forests to Ca depletion in areas managed for intensive biomass removal. Long-term N enrichment of temperate forest soils appears capable of sustaining an open N cycle and key symptoms of N-saturation for multiple decades after the cessation of elevated N inputs.

Tropical Land Use Conversion Effects on Soil Microbial Community Structure and Function: Emerging Patterns and Knowledge Gaps

NASA Astrophysics Data System (ADS)

Seeley, M.; Marin-Spiotta, E.

2016-12-01

Modifications in vegetation due to land use conversions (LUC) between primary forests, pasture, cropping systems, tree plantations, and secondary forests drive shifts in soil microbial communities. These microbial community alterations affect carbon sequestration, nutrient cycling, aboveground biomass, and numerous other soil processes. Despite their importance, little is known about soil microbial organisms' response to LUC, especially in tropical regions where LUC rates are greatest. This project identifies current trends and uncertainties in tropical soil microbiology by comparing 56 published studies on LUC in tropical regions. This review indicates that microbial biomass and functional groups shifted in response to LUC, supporting demonstrated trends in changing soil carbon stocks due to LUC. Microbial biomass was greatest in primary forests when compared to secondary forests and in all forests when compared to both cropping systems and tree plantations. No trend existed when comparing pasture systems and forests, likely due to variations in pasture fertilizer use. Cropping system soils had greater gram positive and less gram negative bacteria than forest soils, potentially resulting in greater respiration of older carbon stocks in agricultural soils. Bacteria dominated primary forests while fungal populations were greatest in secondary forests. To characterize changes in microbial communities resulting from land use change, research must reflect the biophysical variation across the tropics. A chi-squared test revealed that the literature sites represented mean annual temperature variation across the tropics (p-value=0.66).

Plant competition and the implications for tropical forest carbon dynamics

NASA Astrophysics Data System (ADS)

Schnitzer, Stefan

2016-04-01

Tropical forests store more than one third of all terrestrial carbon and account for over one third of terrestrial net primary productivity, and thus they are a critical component of the global carbon cycle. Nearly all of the aboveground carbon in tropical forests is held in tree biomass, and long-term carbon fluxes are balanced largely by tree growth and tree death. Therefore, the vast majority of research on tropical forest carbon dynamics has focused on the growth and mortality of canopy trees. By contrast, lianas (woody vines) contribute little biomass relative to trees. However, competition between lianas (woody vines) and trees may result in forest-wide carbon loss if lianas fail to accumulate the carbon that they displace in trees. We tested this hypotheses using a series of large-scale liana-removal studies in the Republic of Panama. We found that lianas limited tree growth and increased tree mortality, thus significantly reducing carbon accumulation in trees. Lianas themselves, however, did not compensate for the carbon that they displaced in trees. Lianas lower the capacity of tropical forests to uptake and store carbon, and the recently observed increases in liana abundance in neotropical forests will likely result in further reductions of carbon uptake.

Treeline advances and associated shifts in the ground vegetation alter fine root dynamics and mycelia production in the South and Polar Urals.

PubMed

Solly, Emily F; Djukic, Ika; Moiseev, Pavel A; Andreyashkina, Nelly I; Devi, Nadezhda M; Göransson, Hans; Mazepa, Valeriy S; Shiyatov, Stepan G; Trubina, Marina R; Schweingruber, Fritz H; Wilmking, Martin; Hagedorn, Frank

2017-02-01

Climate warming is shifting the elevational boundary between forests and tundra upwards, but the related belowground responses are poorly understood. In the pristine South and Polar Urals with shifts of the treeline ecotone documented by historical photographs, we investigated fine root dynamics and production of extramatrical mycorrhizal mycelia (EMM) along four elevational transects reaching from the closed forest to the treeless tundra. In addition, we analysed elevational differences in climate and vegetation structure, and excavated trees to estimate related changes in the partitioning between below- and aboveground biomass. Fine root biomass of trees (<2 mm) increased by 13-79% with elevation, paralleled by a 35-72% increase in ground vegetation fine roots from the closed forest to the tundra. During the first year of decomposition, mass loss of fine root litter from different vegetation types was greater at lower elevations in the forest-tundra ecotone. The ratio between fine roots of trees and stem biomass largely increased with elevation in both regions, but these increases were not accompanied by a distinct production of EMM. Production of EMM, however, increased with the presence of ectomycorrhizal trees at the transition from the tundra to the forest. Our results imply that the recorded upward expansion of forest into former tundra in the Ural Mountains by 4-8 m per decade is decreasing the partitioning of plant biomass to fine roots. They further suggest that climate-driven forest advances will alter EMM production rates with potential feedbacks on soil carbon and nutrient cycling in these ecosystems.

An Integrated, Observation-based System to Monitor Aboveground Forest Carbon Dynamics in Washington, Oregon, and California

NASA Astrophysics Data System (ADS)

Kennedy, R. E.; Hughes, J.; Neeti, N.; Yang, Z.; Gregory, M.; Roberts, H.; Kane, V. R.; Powell, S. L.; Ohmann, J.

2016-12-01

Because carbon pools and fluxes on wooded landscapes are constrained by their type, age and health, understanding the causes and consequences of carbon change requires frequent observation of forest condition and of disturbance, mortality, and growth processes. As part of USDA and NASA funded efforts, we built empirical monitoring system that integrates time-series Landsat imagery, Forest Inventory and Analysis (FIA) plot data, small-footprint lidar data, and aerial photos to characterize key carbon dynamics in forested ecosystems of Washington, Oregon and California. Here we report yearly biomass estimates for every forested 30 by 30m pixel in the states of Washington, Oregon, and California from 1990 to 2010, including spatially explicit estimates of uncertainty in our yearly predictions. Total biomass at the ecoregion scale agrees well with estimates from FIA plot data alone, currently the only method for reliable monitoring in the forests of the region. Comparisons with estimates of biomass modeled from four small-footprint lidar acquisitions in overlapping portions of our study area show general patterns of agreement between the two types of estimation, but also reveal some disparities in spatial pattern potentially attributable to age and vegetation condition. Using machine-learning techniques based on both Landsat image time series and high resolution aerial photos, we then modeled the agent causing change in biomass for every change event in the region, and report the relative distribution of carbon loss attributable to natural disturbances (primarily fire and insect-related mortality) versus anthropogenic causes (forest management and development).

Timber harvest as the predominant disturbance regime in northeastern U.S. forests: Effects of harvest intensification

USGS Publications Warehouse

Brown, Michelle L.; Canham, Charles D.; Murphy, Lora; Donovan, Therese M.

2018-01-01

Harvesting is the leading cause of adult tree mortality in forests of the northeastern United States. While current rates of timber harvest are generally sustainable, there is considerable pressure to increase the contribution of forest biomass to meet renewable energy goals. We estimated current harvest regimes for different forest types and regions across the U.S. states of New York, Vermont, New Hampshire, and Maine using data from the U.S. Forest Inventory and Analysis Program. We implemented the harvest regimes in SORTIE‐ND, an individual‐based model of forest dynamics, and simulated the effects of current harvest regimes and five additional harvest scenarios that varied by harvest frequency and intensity over 150 yr. The best statistical model for the harvest regime described the annual probability of harvest as a function of forest type/region, total plot basal area, and distance to the nearest improved road. Forests were predicted to increase in adult aboveground biomass in all harvest scenarios in all forest type and region combinations. The magnitude of the increase, however, varied dramatically—increasing from 3% to 120% above current landscape averages as harvest frequency and intensity decreased. The variation can be largely explained by the disproportionately high harvest rates estimated for Maine as compared with the rest of the region. Despite steady biomass accumulation across the landscape, stands that exhibited old‐growth characteristics (defined as ≥300 metric tons of biomass/hectare) were rare (8% or less of stands). Intensified harvest regimes had little effect on species composition due to widespread partial harvesting in all scenarios, resulting in dominance by late‐successional species over time. Our analyses indicate that forest biomass can represent a sustainable, if small, component of renewable energy portfolios in the region, although there are tradeoffs between carbon sequestration in forest biomass and sustainable feedstock supply. Integrating harvest regimes into a disturbance theory framework is critical to understanding the dynamics of forested landscapes, especially given the predominance of logging as a disturbance agent and the increasing pressure to meet renewable energy needs.

Intra-and-Inter Species Biomass Prediction in a Plantation Forest: Testing the Utility of High Spatial Resolution Spaceborne Multispectral RapidEye Sensor and Advanced Machine Learning Algorithms

PubMed Central

Dube, Timothy; Mutanga, Onisimo; Adam, Elhadi; Ismail, Riyad

2014-01-01

The quantification of aboveground biomass using remote sensing is critical for better understanding the role of forests in carbon sequestration and for informed sustainable management. Although remote sensing techniques have been proven useful in assessing forest biomass in general, more is required to investigate their capabilities in predicting intra-and-inter species biomass which are mainly characterised by non-linear relationships. In this study, we tested two machine learning algorithms, Stochastic Gradient Boosting (SGB) and Random Forest (RF) regression trees to predict intra-and-inter species biomass using high resolution RapidEye reflectance bands as well as the derived vegetation indices in a commercial plantation. The results showed that the SGB algorithm yielded the best performance for intra-and-inter species biomass prediction; using all the predictor variables as well as based on the most important selected variables. For example using the most important variables the algorithm produced an R2 of 0.80 and RMSE of 16.93 t·ha−1 for E. grandis; R2 of 0.79, RMSE of 17.27 t·ha−1 for P. taeda and R2 of 0.61, RMSE of 43.39 t·ha−1 for the combined species data sets. Comparatively, RF yielded plausible results only for E. dunii (R2 of 0.79; RMSE of 7.18 t·ha−1). We demonstrated that although the two statistical methods were able to predict biomass accurately, RF produced weaker results as compared to SGB when applied to combined species dataset. The result underscores the relevance of stochastic models in predicting biomass drawn from different species and genera using the new generation high resolution RapidEye sensor with strategically positioned bands. PMID:25140631

Regional assessment of boreal forest productivity using an ecological process model and remote sensing parameter maps.

PubMed

Kimball, J. S.; Keyser, A. R.; Running, S. W.; Saatchi, S. S.

2000-06-01

An ecological process model (BIOME-BGC) was used to assess boreal forest regional net primary production (NPP) and response to short-term, year-to-year weather fluctuations based on spatially explicit, land cover and biomass maps derived by radar remote sensing, as well as soil, terrain and daily weather information. Simulations were conducted at a 30-m spatial resolution, over a 1205 km(2) portion of the BOREAS Southern Study Area of central Saskatchewan, Canada, over a 3-year period (1994-1996). Simulations of NPP for the study region were spatially and temporally complex, averaging 2.2 (+/- 0.6), 1.8 (+/- 0.5) and 1.7 (+/- 0.5) Mg C ha(-1) year(-1) for 1994, 1995 and 1996, respectively. Spatial variability of NPP was strongly controlled by the amount of aboveground biomass, particularly photosynthetic leaf area, whereas biophysical differences between broadleaf deciduous and evergreen coniferous vegetation were of secondary importance. Simulations of NPP were strongly sensitive to year-to-year variations in seasonal weather patterns, which influenced the timing of spring thaw and deciduous bud-burst. Reductions in annual NPP of approximately 17 and 22% for 1995 and 1996, respectively, were attributed to 3- and 5-week delays in spring thaw relative to 1994. Boreal forest stands with greater proportions of deciduous vegetation were more sensitive to the timing of spring thaw than evergreen coniferous stands. Similar relationships were found by comparing simulated snow depth records with 10-year records of aboveground NPP measurements obtained from biomass harvest plots within the BOREAS region. These results highlight the importance of sub-grid scale land cover complexity in controlling boreal forest regional productivity, the dynamic response of the biome to short-term interannual climate variations, and the potential implications of climate change and other large-scale disturbances.

Optimal Atmospheric Correction for Above-Ground Forest Biomass Estimation with the ETM+ Remote Sensor

PubMed Central

Nguyen, Hieu Cong; Jung, Jaehoon; Lee, Jungbin; Choi, Sung-Uk; Hong, Suk-Young; Heo, Joon

2015-01-01

The reflectance of the Earth’s surface is significantly influenced by atmospheric conditions such as water vapor content and aerosols. Particularly, the absorption and scattering effects become stronger when the target features are non-bright objects, such as in aqueous or vegetated areas. For any remote-sensing approach, atmospheric correction is thus required to minimize those effects and to convert digital number (DN) values to surface reflectance. The main aim of this study was to test the three most popular atmospheric correction models, namely (1) Dark Object Subtraction (DOS); (2) Fast Line-of-sight Atmospheric Analysis of Spectral Hypercubes (FLAASH) and (3) the Second Simulation of Satellite Signal in the Solar Spectrum (6S) and compare them with Top of Atmospheric (TOA) reflectance. By using the k-Nearest Neighbor (kNN) algorithm, a series of experiments were conducted for above-ground forest biomass (AGB) estimations of the Gongju and Sejong region of South Korea, in order to check the effectiveness of atmospheric correction methods for Landsat ETM+. Overall, in the forest biomass estimation, the 6S model showed the bestRMSE’s, followed by FLAASH, DOS and TOA. In addition, a significant improvement of RMSE by 6S was found with images when the study site had higher total water vapor and temperature levels. Moreover, we also tested the sensitivity of the atmospheric correction methods to each of the Landsat ETM+ bands. The results confirmed that 6S dominates the other methods, especially in the infrared wavelengths covering the pivotal bands for forest applications. Finally, we suggest that the 6S model, integrating water vapor and aerosol optical depth derived from MODIS products, is better suited for AGB estimation based on optical remote-sensing data, especially when using satellite images acquired in the summer during full canopy development. PMID:26263996

Radioactive and stable cesium isotope distributions and dynamics in Japanese cedar forests.

PubMed

Yoschenko, Vasyl; Takase, Tsugiko; Hinton, Thomas G; Nanba, Kenji; Onda, Yuichi; Konoplev, Alexei; Goto, Azusa; Yokoyama, Aya; Keitoku, Koji

2018-06-01

Dynamics of the Fukushima-derived radiocesium and distribution of the natural stable isotope 133 Cs in Japanese cedar (Cryptomeria japonica D. Don) forest ecosystems were studied during 2014-2016. For the experimental site in Yamakiya, Fukushima Prefecture, we present the redistribution of radiocesium among ecosystem compartments during the entire observation period, while the results obtained at another two experimental site were used to demonstrate similarity of the main trends in the Japanese forest ecosystems. Our observations at the Yamakiya site revealed significant redistribution of radiocesium between the ecosystem compartments during 2014-2016. During this same period radionuclide inventories in the aboveground tree biomass were relatively stable, however, radiocesium in forest litter decreased from 20 ± 11% of the total deposition in 2014 to 4.6 ± 2.7% in 2016. Radiocesium in the soil profile accumulated in the 5-cm topsoil layers. In 2016, more than 80% of the total radionuclide deposition in the ecosystem resided in the 5-cm topsoil layer. The radiocesium distribution between the aboveground biomass compartments at Yamakiya during 2014-2016 was gradually approaching a quasi-equilibrium distribution with stable cesium. Strong correlations of radioactive and stable cesium isotope concentrations in all compartments of the ecosystem have not been reached yet. However, in some compartments the correlation is already strong. An increase of radiocesium concentrations in young foliage in 2016, compared to 2015, and an increase in 2015-2016 of the 137 Cs/ 133 Cs concentration ratio in the biomass compartments with strong correlations indicate an increase in root uptake of radiocesium from the soil profile. Mass balance of the radionuclide inventories, and accounting for radiocesium fluxes in litterfall, throughfall and stemflow, enabled a rough estimate of the annual radiocesium root uptake flux as 2 ± 1% of the total inventory in the ecosystem. Copyright © 2017 Elsevier Ltd. All rights reserved.

Comparative analysis of spectral unmixing and neural networks for estimating small diameter tree above-ground biomass in the State of Mississippi

Treesearch

Moham P. Tiruveedhula; Joseph Fan; Ravi R. Sadasivuni; Surya S. Durbha; David L. Evans

2010-01-01

The accumulation of small diameter trees (SDTs) is becoming a nationwide concern. Forest management practices such as fire suppression and selective cutting of high grade timber have contributed to an overabundance of SDTs in many areas. Alternative value-added utilization of SDTs (for composite wood products and biofuels) has prompted the need to estimate their...

Aboveground biomass responses to organic matter removal, soil compaction, and competing vegetation control on 20-year mixed conifer plantations in California

Treesearch

Jianwei Zhang; Matt D. Busse; David H. Young; Gary O. Fiddler; Joseph W. Sherlock; Jeff D. TenPas

2017-01-01

We measured vegetation growth 5, 10, and 20 years following plantation establishment at 12 Long-term Soil Productivity installations in California’s Sierra Nevada and Southern Cascades. The combined effects of soil compaction (none, moderate, severe), organic matter removal (tree bole only, whole tree, whole tree plus forest floor), and competing vegetation...

The evaluation of different forest structural indices to predict the stand aboveground biomass of even-aged Scotch pine (Pinus sylvestris L.) forests in Kunduz, Northern Turkey.

PubMed

Ercanli, İlker; Kahriman, Aydın

2015-03-01

We assessed the effect of stand structural diversity, including the Shannon, improved Shannon, Simpson, McIntosh, Margelef, and Berger-Parker indices, on stand aboveground biomass (AGB) and developed statistical prediction models for the stand AGB values, including stand structural diversity indices and some stand attributes. The AGB prediction model, including only stand attributes, accounted for 85 % of the total variance in AGB (R (2)) with an Akaike's information criterion (AIC) of 807.2407, Bayesian information criterion (BIC) of 809.5397, Schwarz Bayesian criterion (SBC) of 818.0426, and root mean square error (RMSE) of 38.529 Mg. After inclusion of the stand structural diversity into the model structure, considerable improvement was observed in statistical accuracy, including 97.5 % of the total variance in AGB, with an AIC of 614.1819, BIC of 617.1242, SBC of 633.0853, and RMSE of 15.8153 Mg. The predictive fitting results indicate that some indices describing the stand structural diversity can be employed as significant independent variables to predict the AGB production of the Scotch pine stand. Further, including the stand diversity indices in the AGB prediction model with the stand attributes provided important predictive contributions in estimating the total variance in AGB.

[Aboveground architecture and biomass distribution of Quercus variabilis].

PubMed

Yu, Bi-yun; Zhang, Wen-hui; Hu, Xiao-jing; Shen, Jia-peng; Zhen, Xue-yuan; Yang, Xiao-zhou

2015-08-01

The aboveground architecture, biomass and its allocation, and the relationship between architecture and biomass of Quercus variabilis of different diameter classes in Shangluo, south slope of Qinling Mountains were researched. The results showed that differences existed in the aboveground architecture and biomass allocation of Q. variabilis of different diameter classes. With the increase of diameter class, tree height, DBH, and crown width increased gradually. The average decline rate of each diameter class increased firstly then decreased. Q. variabilis overall bifurcation ratio and stepwise bifurcation ratio increased then declined. The specific leaf areas of Q. variabilis of all different diameter classes at vertical direction were 0.02-0.03, and the larger values of leaf mass ratio, LAI and leaf area ratio at vertical direction in diameter level I , II, III appeared in the middle and upper trunk, while in diameter level IV, V, VI, they appeared in the central trunk, with the increase of diameter class, there appeared two peaks in vertical direction, which located in the lower and upper trunk. The trunk biomass accounted for 71.8%-88.4% of Q. variabilis aboveground biomass, while the branch biomass accounted for 5.8%-19.6%, and the leaf biomass accounted for 4.2%-8.6%. With the increase of diameter class, stem biomass proportion of Q. variabilis decreased firstly then increased, while the branch and leaf biomass proportion showed a trend that increased at first then decreased, and then increased again. The aboveground biomass of Q. variabilis was significantly positively correlated to tree height, DBH, crown width and stepwise bifurcation ratio (R2:1), and positively related to the overall bifurcation ratio and stepwise bifurcation ratio (R3:2), but there was no significant correlation. Trunk biomass and total biomass aboveground were negatively related to the trunk decline rate, while branch biomass and leaf biomass were positively related to trunk decline rate, but their correlations were all not significant.

Remote Sensing of Miombo Woodland's Aboveground Biomass and LAI using RADARSAT and Landsat ETM+ Data

NASA Astrophysics Data System (ADS)

Ribeiro, N. S.; Saatchi, S. S.; Shugart, H. H.; Wshington-Allen, R. A.

2007-05-01

Estimations of biomass are critical in Miombo Woodlands because they represent a primary source of food, fiber, and fuel for 340 million rural peoples and another 15 million urban dwellers in southern Africa. The purpose of this study is to estimate woody aboveground biomass and Leaf Area Index (LAI) in Niassa Reserve, northern Mozambique. The objective of this study is to use optical and microwave satellite data with contemporaneous field data to estimate biomass and LAI. Fifty field plots were surveyed across the Niassa Reserve for biomass and LAI in July and December 2004, respectively. Remote sensing data consisting of RADARSAT backscatter (C- band, ë=5.6 cm) and a June 2004 Landsat ETM+ were acquired. Normalized Difference Vegetation Index (NDVI), Simple Ratio (SR), and a land-cover map (72% total accuracy) were derived from the Landsat scene. Field measurements of biomass and LAI correlated with Radarsat backscatter (Rsqbiomass=0.45, RsqLAI = 0.35, P<0.0001 ), NDVI (Rsqbiomass =0.15, RsqLAI=0.14-, p <0.0001 ) and SR (Rsqbiomass=-0.14, RsqLAI= 0.17, p <0.0001). A jackknife stepwise regression technique was used to develop the best predictive models for biomass (biomass = -5.19 +0.074*radarsat+1.56*SR, Rsq=0.53) and LAI (LAI= -0.66+0.01*radarsat+0.22*SR, Rsq=0.45). The addition of NDVI did not improve the model. Forest biomass and LAI maps were then produced for Niassa Reserve with an estimated peak total biomass of 18 kg/hm2 and a mean LAI of 2.8 m2/m2. In the east both biomass and LAI are lower than the western Niassa Reserve.

Modeling aboveground tree woody biomass using national-scale allometric methods and airborne lidar

NASA Astrophysics Data System (ADS)

Chen, Qi

2015-08-01

Estimating tree aboveground biomass (AGB) and carbon (C) stocks using remote sensing is a critical component for understanding the global C cycle and mitigating climate change. However, the importance of allometry for remote sensing of AGB has not been recognized until recently. The overarching goals of this study are to understand the differences and relationships among three national-scale allometric methods (CRM, Jenkins, and the regional models) of the Forest Inventory and Analysis (FIA) program in the U.S. and to examine the impacts of using alternative allometry on the fitting statistics of remote sensing-based woody AGB models. Airborne lidar data from three study sites in the Pacific Northwest, USA were used to predict woody AGB estimated from the different allometric methods. It was found that the CRM and Jenkins estimates of woody AGB are related via the CRM adjustment factor. In terms of lidar-biomass modeling, CRM had the smallest model errors, while the Jenkins method had the largest ones and the regional method was between. The best model fitting from CRM is attributed to its inclusion of tree height in calculating merchantable stem volume and the strong dependence of non-merchantable stem biomass on merchantable stem biomass. This study also argues that it is important to characterize the allometric model errors for gaining a complete understanding of the remotely-sensed AGB prediction errors.

Improving LiDAR Biomass Model Uncertainty through Non-Destructive Allometry and Plot-level 3D Reconstruction with Terrestrial Laser Scanning

NASA Astrophysics Data System (ADS)

Stovall, A. E.; Shugart, H. H., Jr.

2017-12-01

Future NASA and ESA satellite missions plan to better quantify global carbon through detailed observations of forest structure, but ultimately rely on uncertain ground measurement approaches for calibration and validation. A significant amount of the uncertainty in estimating plot-level biomass can be attributed to inadequate and unrepresentative allometric relationships used to convert plot-level tree measurements to estimates of aboveground biomass. These allometric equations are known to have high errors and biases, particularly in carbon rich forests because they were calibrated with small and often biased samples of destructively harvested trees. To overcome this issue, a non-destructive methodology for estimating tree and plot-level biomass has been proposed through the use of Terrestrial Laser Scanning (TLS). We investigated the potential for using TLS as a ground validation approach in LiDAR-based biomass mapping though virtual plot-level tree volume reconstruction and biomass estimation. Plot-level biomass estimates were compared on the Virginia-based Smithsonian Conservation Biology Institute's SIGEO forest with full 3D reconstruction, TLS allometry, and Jenkins et al. (2003) allometry. On average, full 3D reconstruction ultimately provided the lowest uncertainty estimate of plot-level biomass (9.6%), followed by TLS allometry (16.9%) and the national equations (20.2%). TLS offered modest improvements to the airborne LiDAR empirical models, reducing RMSE from 16.2% to 14%. Our findings suggest TLS plot acquisitions and non-destructive allometry can play a vital role for reducing uncertainty in calibration and validation data for biomass mapping in the upcoming NASA and ESA missions.

The outcome of ecosystem manipulation by elevating atmospheric CO2 is influenced by tree identity and mixture

NASA Astrophysics Data System (ADS)

Godbold, Douglas; Smith, Andrew; Lukac, Martin

2013-04-01

Free Air Carbon dioxide Enrichment (FACE) has often been used predict the response of forest ecosystems to a future high CO2 world. Many of these investigations have been restricted to exposure of single species or genotypes to elevated CO2. To investigate the interaction between tree mixture and elevated CO2, Alnus glutinosa, Betula pendula and Fagus sylvatica were planted in areas of single species and a three species polyculture in a free-air CO2 enrichment study (BangorFACE). The trees were exposed to ambient or elevated CO2 for 4 years. Aboveground woody biomass was increased in polyculture under both ambient and elevated CO2, but the response to elevated CO2 was smaller in polyculture than in the monocultures. In some years, a longer leaf retention was shown under high CO2, and is an indication that environmental factors may moderate tree response to high CO2. Fine and coarse root biomass, together with fine root turnover and fine root morphological characteristics were also measured. Fine root biomass and morphology responded differentially to the elevated CO2 at different soil depths in the three species when grown in monocultures. In polyculture, a greater response to elevated CO2 was observed in coarse roots, and fine root area index. Total fine root biomass was positively affected by elevated CO2 at the end of the experiment, but not by species diversity. Our results show that the aboveground and belowground response to elevated CO2 is significantly affected by intra- and inter-specific competition, and that elevated CO2 response may be reduced in forest communities comprised of tree species with contrasting functional traits but also that other environmental factors may induce previously unseen effects.

Quaternion-Based Texture Analysis of Multiband Satellite Images: Application to the Estimation of Aboveground Biomass in the East Region of Cameroon.

PubMed

Djiongo Kenfack, Cedrigue Boris; Monga, Olivier; Mpong, Serge Moto; Ndoundam, René

2018-03-01

Within the last decade, several approaches using quaternion numbers to handle and model multiband images in a holistic manner were introduced. The quaternion Fourier transform can be efficiently used to model texture in multidimensional data such as color images. For practical application, multispectral satellite data appear as a primary source for measuring past trends and monitoring changes in forest carbon stocks. In this work, we propose a texture-color descriptor based on the quaternion Fourier transform to extract relevant information from multiband satellite images. We propose a new multiband image texture model extraction, called FOTO++, in order to address biomass estimation issues. The first stage consists in removing noise from the multispectral data while preserving the edges of canopies. Afterward, color texture descriptors are extracted thanks to a discrete form of the quaternion Fourier transform, and finally the support vector regression method is used to deduce biomass estimation from texture indices. Our texture features are modeled using a vector composed with the radial spectrum coming from the amplitude of the quaternion Fourier transform. We conduct several experiments in order to study the sensitivity of our model to acquisition parameters. We also assess its performance both on synthetic images and on real multispectral images of Cameroonian forest. The results show that our model is more robust to acquisition parameters than the classical Fourier Texture Ordination model (FOTO). Our scheme is also more accurate for aboveground biomass estimation. We stress that a similar methodology could be implemented using quaternion wavelets. These results highlight the potential of the quaternion-based approach to study multispectral satellite images.

Seasonal variation in biomass and carbohydrate partitioning of understory sugar maple (Acer saccharum) and yellow birch (Betula alleghaniensis) seedlings.

PubMed

Gaucher, Catherine; Gougeon, Sébastien; Mauffette, Yves; Messier, Christian

2005-01-01

We investigated seasonal patterns of biomass and carbohydrate partitioning in relation to shoot growth phenology in two age classes of sugar maple (Acer saccharum Marsh.) and yellow birch (Betula alleghaniensis Britt.) seedlings growing in the understory of a partially harvested forest. The high root:shoot biomass ratio and carbohydrate concentration of sugar maple are characteristic of species with truncated growth patterns (i.e., cessation of aboveground shoot growth early in the growing season), a conservative growth strategy and high shade tolerance. The low root:shoot biomass ratio and carbohydrate concentration of yellow birch are characteristic of species with continuous growth patterns, an opportunistic growth strategy and low shade tolerance. In both species, starch represented up to 95% of total nonstructural carbohydrates and was mainly found in the roots. Contrary to our hypothesis, interspecific differences in shoot growth phenology (i.e., continuous versus truncated) did not result in differences in seasonal patterns of carbohydrate partitioning. Our results help explain the niche differentiation between sugar maple and yellow birch in temperate, deciduous understory forests.

Phenodynamics of production and chemical pools in mayapple and flowering dogwood

DOE Office of Scientific and Technical Information (OSTI.GOV)

Taylor, F.G. Jr.

1991-01-01

The objective of this study is to provide an understanding of the seasonality of biomass production and chemical storage among selected forest species as an aid to the analysis and management of a forest ecosystem model. The specific goals to accomplish the objectives included: (1) the construction of phenological calendars to be superimposed on the civil calendar, such that the seasons of the year are not marked by calendar dates but rather by dated groups of phenological events; (2) to develop a capability to predict onset of the generative phase (flowering) from heat unit summation methods; (3) to illustrate themore » role of phenology to biomass production and chemical storage in two indicator species, mayapple and flowering dogwood; and (4) to develop the capability to predict aboveground and below ground standing crop biomass in dogwood. Observations in this study focused on the generative phases (flowering) of individual plants and colonies of plants as indicators of productivity. 16 figs., 11 tabs.« less

Impacts of individual tree species on carbon dynamics in a moist tropical forest environment.

PubMed

Russell, Ann E; Raich, James W; Arrieta, Ricardo Bedoya; Valverde-Barrantes, Oscar; González, Eugenio

2010-06-01

In the moist tropical forest biome, which cycles carbon (C) rapidly and stores huge amounts of C, the impacts of individual species on C balances are not well known. In one of the earliest replicated experimental sites for investigating growth of native tropical trees, we examined traits of tree species in relation to their effects on forest C balances, mechanisms of influence, and consequences for C sequestration. The monodominant stands, established in abandoned pasture in 1988 at La Selva Biological Station, Costa Rica, contained five species in a complete randomized block design. Native species were: Hieronyma alchorneoides, Pentaclethra macroloba, Virola koschnyi, and Vochysia guatemalensis. The exotic species was Pinus patula. By 16 years, the lack of differences among species in some attributes suggested strong abiotic control in this environment, where conditions are very favorable for growth, These attributes included aboveground net primary productivity (ANPP), averaging 11.7 Mg C x ha(-1) x yr(-1) across species, and soil organic C (0-100 cm, 167 Mg C/ha). Other traits differed significantly, however, indicating some degree of biological control. In Vochysia plots, both aboveground biomass of 99 Mg C/ha, and belowground biomass of 20 Mg C/ha were 1.8 times that of Virola (P = 0.02 and 0.03, respectively). Differences among species in overstory biomass were not compensated by understory vegetation. Belowground NPP of 4.6 Mg C x ha(-1) yr(-1) in Hieronyma was 2.4 times that of Pinus (P < 0.01). Partitioning of NPP to belowground components in Hieronyma was more than double that of Pinus (P = 0.03). The canopy turnover rate in Hieronyma was 42% faster than that of Virola (P < 0.01). Carbon sequestration, highest in Vochysia (7.4 Mg C x ha(-1) x yr(-1), P = 0.02), averaged 5.2 Mg C x ha(-1) x yr(-1), close to the annual per capita fossil fuel use in the United States of 5.3 Mg C. Our results indicated that differences in species effects on forest C balances were related primarily to differences in growth rates, partitioning of C among biomass components, tissue turnover rates, and tissue chemistry. Inclusion of those biological attributes may be critical for robust modeling of C cycling across the moist tropical forest biome.

Field-quantified responses of tropical rainforest aboveground productivity to increasing CO2 and climatic stress, 1997-2009

NASA Astrophysics Data System (ADS)

Clark, Deborah A.; Clark, David B.; Oberbauer, Steven F.

2013-06-01

A directional change in tropical-forest productivity, a large component in the global carbon budget, would affect the rate of increase in atmospheric carbon dioxide ([CO2]). One current hypothesis is that "CO2 fertilization" has been increasing tropical forest productivity. Some lines of evidence instead suggest climate-driven productivity declines. Relevant direct field observations remain extremely limited for this biome. Using a unique long-term record of annual field measurements, we assessed annual aboveground net primary productivity (ANPP) and its relation to climatic factors and [CO2] in a neotropical rainforest through 1997-2009. Over this 12 year period, annual productivity did not increase, as would be expected with a dominant CO2 fertilization effect. Instead, the negative responses of ANPP components to climatic stress far exceeded the small positive responses associated with increasing [CO2]. Annual aboveground biomass production was well explained (73%) by the independent negative effects of increasing minimum temperatures and greater dry-season water stress. The long-term records enable a first field-based estimate of the [CO2] response of tropical forest ANPP: 5.24 g m-2 yr-1 yr-1 (the summed [CO2]-associated increases in two of the four production components; the largest component, leaf litterfall, showed no [CO2] association). If confirmed by longer data series, such a small response from a fertile tropical rainforest would indicate that current global models overestimate the benefits from CO2 fertilization for this biome, where most forests' poorer nutrient status more strongly constrains productivity responses to increasing [CO2]. Given the rapidly intensifying warming across tropical regions, tropical forest productivity could sharply decline through coming decades.

Conventional intensive logging promotes loss of organic carbon from the mineral soil.

PubMed

Dean, Christopher; Kirkpatrick, James B; Friedland, Andrew J

2017-01-01

There are few data, but diametrically opposed opinions, about the impacts of forest logging on soil organic carbon (SOC). Reviews and research articles conclude either that there is no effect, or show contradictory effects. Given that SOC is a substantial store of potential greenhouse gasses and forest logging and harvesting is routine, resolution is important. We review forest logging SOC studies and provide an overarching conceptual explanation for their findings. The literature can be separated into short-term empirical studies, longer-term empirical studies and long-term modelling. All modelling that includes major aboveground and belowground biomass pools shows a long-term (i.e. ≥300 years) decrease in SOC when a primary forest is logged and then subjected to harvesting cycles. The empirical longer-term studies indicate likewise. With successive harvests the net emission accumulates but is only statistically perceptible after centuries. Short-term SOC flux varies around zero. The long-term drop in SOC in the mineral soil is driven by the biomass drop from the primary forest level but takes time to adjust to the new temporal average biomass. We show agreement between secondary forest SOC stocks derived purely from biomass information and stocks derived from complex forest harvest modelling. Thus, conclusions that conventional harvests do not deplete SOC in the mineral soil have been a function of their short time frames. Forest managers, climate change modellers and environmental policymakers need to assume a long-term net transfer of SOC from the mineral soil to the atmosphere when primary forests are logged and then undergo harvest cycles. However, from a greenhouse accounting perspective, forest SOC is not the entire story. Forest wood products that ultimately reach landfill, and some portion of which produces some soil-like material there rather than in the forest, could possibly help attenuate the forest SOC emission by adding to a carbon pool in landfill. © 2016 John Wiley & Sons Ltd.

Quantifying above- and belowground biomass carbon loss with forest conversion in tropical lowlands of Sumatra (Indonesia).

PubMed

Kotowska, Martyna M; Leuschner, Christoph; Triadiati, Triadiati; Meriem, Selis; Hertel, Dietrich

2015-10-01

Natural forests in South-East Asia have been extensively converted into other land-use systems in the past decades and still show high deforestation rates. Historically, lowland forests have been converted into rubber forests, but more recently, the dominant conversion is into oil palm plantations. While it is expected that the large-scale conversion has strong effects on the carbon cycle, detailed studies quantifying carbon pools and total net primary production (NPPtotal ) in above- and belowground tree biomass in land-use systems replacing rainforest (incl. oil palm plantations) are rare so far. We measured above- and belowground carbon pools in tree biomass together with NPPtotal in natural old-growth forests, 'jungle rubber' agroforests under natural tree cover, and rubber and oil palm monocultures in Sumatra. In total, 32 stands (eight plot replicates per land-use system) were studied in two different regions. Total tree biomass in the natural forest (mean: 384 Mg ha(-1) ) was more than two times higher than in jungle rubber stands (147 Mg ha(-1) ) and >four times higher than in monoculture rubber and oil palm plantations (78 and 50 Mg ha(-1) ). NPPtotal was higher in the natural forest (24 Mg ha(-1)  yr(-1) ) than in the rubber systems (20 and 15 Mg ha(-1)  yr(-1) ), but was highest in the oil palm system (33 Mg ha(-1)  yr(-1) ) due to very high fruit production (15-20 Mg ha(-1)  yr(-1) ). NPPtotal was dominated in all systems by aboveground production, but belowground productivity was significantly higher in the natural forest and jungle rubber than in plantations. We conclude that conversion of natural lowland forest into different agricultural systems leads to a strong reduction not only in the biomass carbon pool (up to 166 Mg C ha(-1) ) but also in carbon sequestration as carbon residence time (i.e. biomass-C:NPP-C) was 3-10 times higher in the natural forest than in rubber and oil palm plantations. © 2015 John Wiley & Sons Ltd.

The positive relationships between plant coverage, species richness, and aboveground biomass are ubiquitous across plant growth forms in semi-steppe rangelands.

PubMed

Sanaei, Anvar; Ali, Arshad; Chahouki, Mohammad Ali Zare

2018-01-01

The positive relationships between biodiversity and aboveground biomass are important for biodiversity conservation and greater ecosystem functioning and services that humans depend on. However, the interaction effects of plant coverage and biodiversity on aboveground biomass across plant growth forms (shrubs, forbs and grasses) in natural rangelands are poorly studied. Here, we hypothesized that, while accounting for environmental factors and disturbance intensities, the positive relationships between plant coverage, biodiversity, and aboveground biomass are ubiquitous across plant growth forms in natural rangelands. We applied structural equation models (SEMs) using data from 735 quadrats across 35 study sites in semi-steppe rangelands in Iran. The combination of plant coverage and species richness rather than Shannon's diversity or species diversity (a latent variable of species richness and evenness) substantially enhance aboveground biomass across plant growth forms. In all selected SEMs, plant coverage had a strong positive direct effect on aboveground biomass (β = 0.72 for shrubs, 0.84 for forbs and 0.80 for grasses), followed by a positive effect of species richness (β = 0.26 for shrubs, 0.05 for forbs and 0.09 for grasses), and topographic factors. Disturbance intensity had a negative effect on plant coverage, whereas it had a variable effect on species richness across plant growth forms. Plant coverage had a strong positive total effect on aboveground biomass (β = 0.84 for shrubs, 0.88 for forbs, and 0.85 for grasses), followed by a positive effect of species richness, and a negative effect of disturbance intensity across plant growth forms. Our results shed light on the management of rangelands that is high plant coverage can significantly improve species richness and aboveground biomass across plant growth forms. We also found that high disturbance intensity due to heavy grazing has a strong negative effect on plant coverage rather than species richness in semi-steppe rangelands. This study suggests that proper grazing systems (e.g. rotational system) based on carrying capacity and stocking rate of a rangeland may be helpful for biodiversity conservation, better grazing of livestock, improvement of plant coverage and enhancement of aboveground biomass. Copyright © 2017 Elsevier Ltd. All rights reserved.

Analyzing spatial and temporal trends in Aboveground Biomass within the Acadian New England Forests using the complete Landsat Archive

NASA Astrophysics Data System (ADS)

Kilbride, J. B.; Fraver, S.; Ayrey, E.; Weiskittel, A.; Braaten, J.; Hughes, J. M.; Hayes, D. J.

2017-12-01

Forests within the New England states and Canadian Maritime provinces, here described as the Acadian New England (ANE) forests, have undergone substantial disturbances due to insect, fire, and anthropogenic factors. Through repeated satellite observations captures by USGS's Landsat program, 45 years of disturbance information can be incorporated into modeling efforts to better understand the spatial and temporal trends in forest above ground biomass (AGB). Using Google's Earth Engine, annual mosaics were developed for the ANE study area and then disturbance and recovery metrics were developed using the temporal segmentation algorithm VeRDET. Normalization procedures were developed to incorporate the Landsat Multispectral Scanner (MSS, 1972 - 1985) data alongside the modern era of Landsat Thematic Mapper (TM, 1984-2013), Enhanced Thematic Mapper plus (ETM+, 1999 - present), and Operational Land Imager (OLI, 2013- present) data products. This has enabled the creation of a dataset with an unprecedented spatial and temporal view of forest landscape change. Model training was performed using was the Forest Inventory Analysis (FIA) and New Brunswick Permanent Sample Plot data datasets. Modeling was performed using parametric techniques such as mixed effects models and non-parametric techniques such as k-NN imputation and generalized boosted regression. We compare the biomass estimate and model accuracy to other inventory and modeling studies produced within this study area. The spatial and temporal patterns of stock changes are analyzed against resource policy, land ownership changes, and forest management.

Benchmark map of forest carbon stocks in tropical regions across three continents.

PubMed

Saatchi, Sassan S; Harris, Nancy L; Brown, Sandra; Lefsky, Michael; Mitchard, Edward T A; Salas, William; Zutta, Brian R; Buermann, Wolfgang; Lewis, Simon L; Hagen, Stephen; Petrova, Silvia; White, Lee; Silman, Miles; Morel, Alexandra

2011-06-14

Developing countries are required to produce robust estimates of forest carbon stocks for successful implementation of climate change mitigation policies related to reducing emissions from deforestation and degradation (REDD). Here we present a "benchmark" map of biomass carbon stocks over 2.5 billion ha of forests on three continents, encompassing all tropical forests, for the early 2000s, which will be invaluable for REDD assessments at both project and national scales. We mapped the total carbon stock in live biomass (above- and belowground), using a combination of data from 4,079 in situ inventory plots and satellite light detection and ranging (Lidar) samples of forest structure to estimate carbon storage, plus optical and microwave imagery (1-km resolution) to extrapolate over the landscape. The total biomass carbon stock of forests in the study region is estimated to be 247 Gt C, with 193 Gt C stored aboveground and 54 Gt C stored belowground in roots. Forests in Latin America, sub-Saharan Africa, and Southeast Asia accounted for 49%, 25%, and 26% of the total stock, respectively. By analyzing the errors propagated through the estimation process, uncertainty at the pixel level (100 ha) ranged from ± 6% to ± 53%, but was constrained at the typical project (10,000 ha) and national (>1,000,000 ha) scales at ca. ± 5% and ca. ± 1%, respectively. The benchmark map illustrates regional patterns and provides methodologically comparable estimates of carbon stocks for 75 developing countries where previous assessments were either poor or incomplete.

Geography of Global Forest Carbon Stocks & Dynamics

NASA Astrophysics Data System (ADS)

Saatchi, S. S.; Yu, Y.; Xu, L.; Yang, Y.; Fore, A.; Ganguly, S.; Nemani, R. R.; Zhang, G.; Lefsky, M. A.; Sun, G.; Woodall, C. W.; Naesset, E.; Seibt, U. H.

2014-12-01

Spatially explicit distribution of carbon stocks and dynamics in global forests can greatly reduce the uncertainty in the terrestrial portion of the global carbon cycle by improving estimates of emissions and uptakes from land use activities, and help with green house gas inventory at regional and national scales. Here, we produce the first global distribution of carbon stocks in living woody biomass at ~ 100 m (1-ha) resolution for circa 2005 from a combination of satellite observations and ground inventory data. The total carbon stored in live woody biomass is estimated to be 337 PgC with 258 PgC in aboveground and 79 PgC in roots, and partitioned globally in boreal (20%), tropical evergreen (50%), temperate (12%), and woodland savanna and shrublands (15%). We use a combination of satellite observations of tree height, remote sensing data on deforestation and degradation to quantify the dynamics of these forests at the biome level globally and provide geographical distribution of carbon storage dynamics in terms sinks and sources globally.

Evaluation of stem rot in 339 Bornean tree species: implications of size, taxonomy, and soil-related variation for aboveground biomass estimates

NASA Astrophysics Data System (ADS)

Heineman, K. D.; Russo, S. E.; Baillie, I. C.; Mamit, J. D.; Chai, P. P.-K.; Chai, L.; Hindley, E. W.; Lau, B.-T.; Tan, S.; Ashton, P. S.

2015-10-01

Fungal decay of heart wood creates hollows and areas of reduced wood density within the stems of living trees known as stem rot. Although stem rot is acknowledged as a source of error in forest aboveground biomass (AGB) estimates, there are few data sets available to evaluate the controls over stem rot infection and severity in tropical forests. Using legacy and recent data from 3180 drilled, felled, and cored stems in mixed dipterocarp forests in Sarawak, Malaysian Borneo, we quantified the frequency and severity of stem rot in a total of 339 tree species, and related variation in stem rot with tree size, wood density, taxonomy, and species' soil association, as well as edaphic conditions. Predicted stem rot frequency for a 50 cm tree was 53 % of felled, 39 % of drilled, and 28 % of cored stems, demonstrating differences among methods in rot detection ability. The percent stem volume infected by rot, or stem rot severity, ranged widely among trees with stem rot infection (0.1-82.8 %) and averaged 9 % across all trees felled. Tree taxonomy explained the greatest proportion of variance in both stem rot frequency and severity among the predictors evaluated in our models. Stem rot frequency, but not severity, increased sharply with tree diameter, ranging from 13 % in trees 10-30 cm DBH to 54 % in stems ≥ 50 cm DBH across all data sets. The frequency of stem rot increased significantly in soils with low pH and cation concentrations in topsoil, and stem rot was more common in tree species associated with dystrophic sandy soils than with nutrient-rich clays. When scaled to forest stands, the maximum percent of stem biomass lost to stem rot varied significantly with soil properties, and we estimate that stem rot reduces total forest AGB estimates by up to 7 % relative to what would be predicted assuming all stems are composed strictly of intact wood. This study demonstrates not only that stem rot is likely to be a significant source of error in forest AGB estimation, but also that it strongly covaries with tree size, taxonomy, habitat association, and soil resources, underscoring the need to account for tree community composition and edaphic variation in estimating carbon storage in tropical forests.

Leaf mass per area, not total leaf area, drives differences in above-ground biomass distribution among woody plant functional types.

PubMed

Duursma, Remko A; Falster, Daniel S

2016-10-01

Here, we aim to understand differences in biomass distribution between major woody plant functional types (PFTs) (deciduous vs evergreen and gymnosperm vs angiosperm) in terms of underlying traits, in particular the leaf mass per area (LMA) and leaf area per unit stem basal area. We used a large compilation of plant biomass and size observations, including observations of 21 084 individuals on 656 species. We used a combination of semiparametric methods and variance partitioning to test the influence of PFT, plant height, LMA, total leaf area, stem basal area and climate on above-ground biomass distribution. The ratio of leaf mass to above-ground woody mass (MF /MS ) varied strongly among PFTs. We found that MF /MS at a given plant height was proportional to LMA across PFTs. As a result, the PFTs did not differ in the amount of leaf area supported per unit above-ground biomass or per unit stem basal area. Climate consistently explained very little additional variation in biomass distribution at a given plant size. Combined, these results demonstrate consistent patterns in above-ground biomass distribution and leaf area relationships among major woody PFTs, which can be used to further constrain global vegetation models. © 2016 The Authors. New Phytologist © 2016 New Phytologist Trust.

The radiocesium dynamics in the Fukushima forests at the late stage after deposition

NASA Astrophysics Data System (ADS)

Yoschenko, Vasyl; Takase, Tsugiko; Nanba, Kenji; Konoplev, Alexei; Onda, Yuichi

2017-04-01

Forests cover about 2/3 of the territory of Areas 2 and 3 in the Fukushima prefecture. This territory was heavily contaminated with radiocesium released from the Fukushima Dai-Ichi Nuclear Power Plant in March 2011. The extensive decontamination measures aimed to prepare the return of population have been scheduled and are being implemented at the agricultural and residential lands at this territory. However, these measures will be not applied in the large scale in the Fukushima forests. The current radiocesium levels in wood at this territory exceed the Japanese standards for wood; thus, after return of population, the Fukushima forests may remain excluded from the economical use. Understanding of the further dynamics of radiocesium in the forest ecosystems is necessary for elaboration of the strategy concerning the radioactive contaminated Fukushima forests. In March 2011 radiocesium was intercepted by the tree canopies and then, at the early stage after the accident, was effectively transported to the soil surface with precipitation and litterfall, and partly translocated to wood forming the current levels. The general trend was the decrease of the radiocesium inventory in the aboveground forest biomass. After redistribution in the root-inhabited soil layer radiocesium became available for uptake into the trees through the roots. From the Chernobyl experience, the further levels of radiocesium in the forest ecosystem compartments at the late stage may increase or decrease depending on the intensities of the root uptake and removal fluxes. In the Fukushima forests, the stage of the root uptake has begun recently, and the parameters of the root uptake have not been studied well for the varieties of species, forest types and soil conditions. Our study is aimed to monitoring and modelling of the radiocesium redistribution in the Fukushima forests after the removal of its initial deposition from the tree canopies. The study has been performed since May 2014 at several experimental sites in the typical Fukushima forests (Japanese cedar, Japanese red pine). We observe the dynamics of the radiocesium concentrations and total inventories in the ecosystem compartments and quantify the biogenic fluxes of radiocesium which will determine its further redistribution between the biomass, soil and litter. Our study also includes characterization of the stable cesium distributions in the forest ecosystems and development of the methods for non-destructive monitoring of the radiocesium concentration in wood. We present the observation results for the period of 2014-2016 (annual and seasonal changes in the aboveground biomass, leaching from the forest litter, downward migration in soil), as well as the estimates of the radiocesium fluxes which will be used later for the modelling of its long-term dynamics in the Fukushima forests.

Derivation of a northern-hemispheric biomass map for use in global carbon cycle models

NASA Astrophysics Data System (ADS)

Thurner, Martin; Beer, Christian; Santoro, Maurizio; Carvalhais, Nuno; Wutzler, Thomas; Schepaschenko, Dmitry; Shvidenko, Anatoly; Kompter, Elisabeth; Levick, Shaun; Schmullius, Christiane

2013-04-01

Quantifying the state and the change of the World's forests is crucial because of their ecological, social and economic value. Concerning their ecological importance, forests provide important feedbacks on the global carbon, energy and water cycles. In addition to their influence on albedo and evapotranspiration, they have the potential to sequester atmospheric carbon dioxide and thus to mitigate global warming. The current state and inter-annual variability of forest carbon stocks remain relatively unexplored, but remote sensing can serve to overcome this shortcoming. While for the tropics wall-to-wall estimates of above-ground biomass have been recently published, up to now there was a lack of similar products covering boreal and temperate forests. Recently, estimates of forest growing stock volume (GSV) were derived from ENVISAT ASAR C-band data for latitudes above 30° N. Utilizing a wood density and a biomass compartment database, a forest carbon density map covering North-America, Europe and Asia with 0.01° resolution could be derived out of this dataset. Allometric functions between stem, branches, root and foliage biomass were fitted and applied for different leaf types (broadleaf, needleleaf deciduous, needleleaf evergreen forest). Additionally, this method enabled uncertainty estimation of the resulting carbon density map. Intercomparisons with inventory-based biomass products in Russia, Europe and the USA proved the high accuracy of this approach at a regional scale (r2 = 0.70 - 0.90). Based on the final biomass map, the forest carbon stocks and densities (excluding understorey vegetation) for three biomes were estimated across three continents. While 40.7 ± 15.7 Gt of carbon were found to be stored in boreal forests, temperate broadleaf/mixed forests and temperate conifer forests contain 24.5 ± 9.4 Gt(C) and 14.5 ± 4.8 Gt(C), respectively. In terms of carbon density, most of the carbon per area is stored in temperate conifer (62.1 ± 20.7 Mg(C)/ha(Forest)) and broadleaf/mixed forests (58.0 ± 22.1 Mg(C)/ha(Forest)), whereas boreal forests have a carbon density of only 40.0 ± 15.4 Mg(C)/ha(Forest). While European forest carbon stocks are relatively small, the carbon density is higher compared to the other continents. The derived biomass map substantially improves the knowledge on the current carbon stocks of the northern-hemispheric boreal and temperate forests, serving as a new benchmark for spatially explicit and consistent biomass mapping with moderate spatial resolution. This product can be of great value for global carbon cycle models as well as national carbon monitoring systems. Further investigations concentrate on improving biomass parameterizations and representations in such kind of models. The presented map will help to improve the simulation of biomass spatial patterns and variability and enables identifying the dominant influential factors like climatic conditions and disturbances.

Translating Forest Change to Carbon Emissions and Removals By Linking Disturbance Products, Biomass Maps, and Carbon Cycle Modeling in a Comprehensive Carbon Monitoring Framework for the Conterminous US Forests

NASA Astrophysics Data System (ADS)

Williams, C. A.; Gu, H.

2016-12-01

Protecting forest carbon stores and uptake is central to national and international policies aimed at mitigating climate change. The success of such polices relies on high quality, accurate reporting (Tier 3) that earns the greatest financial value of carbon credits and hence incentivizes forest conservation and protection. Methods for Tier 3 Measuring, Reporting, and Verification (MRV) are still in development, generally involving some combination of direct remote sensing, ground based inventorying, and computer modeling, but have tended to emphasize assessments of live aboveground carbon stocks with a less clear connection to the real target of MRV which is carbon emissions and removals. Most existing methods are also ambiguous as to the mechanisms that underlie carbon accumulation, and any have limited capacity for forecasting carbon dynamics over time. This paper reports on the design and implementation of a new method for Tier 3 MRV, decision support, and forecasting that is being applied to assess forest carbon dynamics across the conterminous US. The method involves parameterization of a carbon cycle model (CASA) to match yield data from the US forest inventory (FIA). A range of disturbance types and severities are imposed in the model to estimate resulting carbon emissions, carbon uptake, and carbon stock changes post-disturbance. Resulting trajectories are then applied to landscapes at the 30-m pixel level based on two remote-sensing based data products. One documents the year, type, and severity of disturbance in recent decades. The second documents aboveground biomass which is used to estimate time since disturbance and associated carbon fluxes and stocks. Results will highlight high-resolution (30 m) annual carbon stocks and fluxes from 1990 to 2010 for select regions of interest across the US. Spatial analyses reveal regional patterns in US forest carbon stocks and fluxes as they respond to forest types, climate, and disturbances. Temporal analyses document effects of recent disturbance trends and demonstrate the method's capacity for quantifying changes in forest carbon over time as needed for UNFCCC reporting.

Aboveground Biomass Estimation Using Reconstructed Feature of Airborne Discrete-Return LIDAR by Auto-Encoder Neural Network

NASA Astrophysics Data System (ADS)

Li, T.; Wang, Z.; Peng, J.

2018-04-01

Aboveground biomass (AGB) estimation is critical for quantifying carbon stocks and essential for evaluating carbon cycle. In recent years, airborne LiDAR shows its great ability for highly-precision AGB estimation. Most of the researches estimate AGB by the feature metrics extracted from the canopy height distribution of the point cloud which calculated based on precise digital terrain model (DTM). However, if forest canopy density is high, the probability of the LiDAR signal penetrating the canopy is lower, resulting in ground points is not enough to establish DTM. Then the distribution of forest canopy height is imprecise and some critical feature metrics which have a strong correlation with biomass such as percentiles, maximums, means and standard deviations of canopy point cloud can hardly be extracted correctly. In order to address this issue, we propose a strategy of first reconstructing LiDAR feature metrics through Auto-Encoder neural network and then using the reconstructed feature metrics to estimate AGB. To assess the prediction ability of the reconstructed feature metrics, both original and reconstructed feature metrics were regressed against field-observed AGB using the multiple stepwise regression (MS) and the partial least squares regression (PLS) respectively. The results showed that the estimation model using reconstructed feature metrics improved R2 by 5.44 %, 18.09 %, decreased RMSE value by 10.06 %, 22.13 % and reduced RMSEcv by 10.00 %, 21.70 % for AGB, respectively. Therefore, reconstructing LiDAR point feature metrics has potential for addressing AGB estimation challenge in dense canopy area.

Understory herb layer exerts strong controls on soil microbial communities in subtropical plantations

NASA Astrophysics Data System (ADS)

Yin, Kai; Zhang, Lei; Chen, Dima; Tian, Yichen; Zhang, Feifei; Wen, Meiping; Yuan, Chao

2016-05-01

The patterns and drivers of soil microbial communities in forest plantations remain inadequate although they have been extensively studied in natural forest and grassland ecosystems. In this study, using data from 12 subtropical plantation sites, we found that the overstory tree biomass and tree cover increased with increasing plantation age. However, there was a decline in the aboveground biomass and species richness of the understory herbs as plantation age increased. Biomass of all microbial community groups (i.e. fungi, bacteria, arbuscular mycorrhizal fungi, and actinomycete) decreased with increasing plantation age; however, the biomass ratio of fungi to bacteria did not change with increasing plantation age. Variation in most microbial community groups was mainly explained by the understory herb (i.e. herb biomass and herb species richness) and overstory trees (i.e. tree biomass and tree cover), while soils (i.e. soil moisture, soil organic carbon, and soil pH) explained a relative low percentage of the variation. Our results demonstrate that the understory herb layer exerts strong controls on soil microbial community in subtropical plantations. These findings suggest that maintenance of plantation health may need to consider the management of understory herb in order to increase the potential of plantation ecosystems as fast-response carbon sinks.

Understory herb layer exerts strong controls on soil microbial communities in subtropical plantations

PubMed Central

Yin, Kai; Zhang, Lei; Chen, Dima; Tian, Yichen; Zhang, Feifei; Wen, Meiping; Yuan, Chao

2016-01-01

The patterns and drivers of soil microbial communities in forest plantations remain inadequate although they have been extensively studied in natural forest and grassland ecosystems. In this study, using data from 12 subtropical plantation sites, we found that the overstory tree biomass and tree cover increased with increasing plantation age. However, there was a decline in the aboveground biomass and species richness of the understory herbs as plantation age increased. Biomass of all microbial community groups (i.e. fungi, bacteria, arbuscular mycorrhizal fungi, and actinomycete) decreased with increasing plantation age; however, the biomass ratio of fungi to bacteria did not change with increasing plantation age. Variation in most microbial community groups was mainly explained by the understory herb (i.e. herb biomass and herb species richness) and overstory trees (i.e. tree biomass and tree cover), while soils (i.e. soil moisture, soil organic carbon, and soil pH) explained a relative low percentage of the variation. Our results demonstrate that the understory herb layer exerts strong controls on soil microbial community in subtropical plantations. These findings suggest that maintenance of plantation health may need to consider the management of understory herb in order to increase the potential of plantation ecosystems as fast-response carbon sinks. PMID:27243577

Understory herb layer exerts strong controls on soil microbial communities in subtropical plantations.

PubMed

Yin, Kai; Zhang, Lei; Chen, Dima; Tian, Yichen; Zhang, Feifei; Wen, Meiping; Yuan, Chao

2016-05-31

The patterns and drivers of soil microbial communities in forest plantations remain inadequate although they have been extensively studied in natural forest and grassland ecosystems. In this study, using data from 12 subtropical plantation sites, we found that the overstory tree biomass and tree cover increased with increasing plantation age. However, there was a decline in the aboveground biomass and species richness of the understory herbs as plantation age increased. Biomass of all microbial community groups (i.e. fungi, bacteria, arbuscular mycorrhizal fungi, and actinomycete) decreased with increasing plantation age; however, the biomass ratio of fungi to bacteria did not change with increasing plantation age. Variation in most microbial community groups was mainly explained by the understory herb (i.e. herb biomass and herb species richness) and overstory trees (i.e. tree biomass and tree cover), while soils (i.e. soil moisture, soil organic carbon, and soil pH) explained a relative low percentage of the variation. Our results demonstrate that the understory herb layer exerts strong controls on soil microbial community in subtropical plantations. These findings suggest that maintenance of plantation health may need to consider the management of understory herb in order to increase the potential of plantation ecosystems as fast-response carbon sinks.

Variation of biomass and carbon pools with forest type in temperate forests of Kashmir Himalaya, India.

PubMed

Dar, Javid Ahmad; Sundarapandian, Somaiah

2015-02-01

An accurate characterization of tree, understory, deadwood, floor litter, and soil organic carbon (SOC) pools in temperate forest ecosystems is important to estimate their contribution to global carbon (C) stocks. However, this information on temperate forests of the Himalayas is lacking and fragmented. In this study, we measured C stocks of tree (aboveground and belowground biomass), understory (shrubs and herbaceous), deadwood (standing and fallen trees and stumps), floor litter, and soil from 111 plots of 50 m × 50 m each, in seven forest types: Populus deltoides (PD), Juglans regia (JR), Cedrus deodara (CD), Pinus wallichiana (PW), mixed coniferous (MC), Abies pindrow (AP), and Betula utilis (BU) in temperate forests of Kashmir Himalaya, India. The main objective of the present study is to quantify the ecosystem C pool in these seven forest types. The results showed that the tree biomass ranged from 100.8 Mg ha(-1) in BU forest to 294.8 Mg ha(-1) for the AP forest. The understory biomass ranged from 0.16 Mg ha(-1) in PD forest to 2.36 Mg ha(-1) in PW forest. Deadwood biomass ranged from 1.5 Mg ha(-1) in PD forest to 14.9 Mg ha(-1) for the AP forest, whereas forest floor litter ranged from 2.5 Mg ha(-1) in BU and JR forests to 3.1 Mg ha(-1) in MC forest. The total ecosystem carbon stocks varied from 112.5 to 205.7 Mg C ha(-1) across all the forest types. The C stocks of tree, understory, deadwood, litter, and soil ranged from 45.4 to 135.6, 0.08 to 1.18, 0.7 to 6.8, 1.1 to 1.4, and 39.1-91.4 Mg ha(-1), respectively, which accounted for 61.3, 0.2, 1.4, 0.8, and 36.3 % of the total carbon stock. BU forest accounted 65 % from soil C and 35 % from biomass, whereas PD forest contributed only 26 % from soil C and 74 % from biomass. Of the total C stock in the 0-30-cm soil, about 55 % was stored in the upper 0-10 cm. Soil C stocks in BU forest were significantly higher than those in other forests. The variability of C pools of different ecosystem components is influenced by vegetation type, stand structure, management history, and altitude. Our results reveal that a higher percentage (63 %) of C is stored in biomass and less in soil in these temperate forests except at the higher elevation broad-leaved BU forest. Results from this study will enhance our ability to evaluate the role of these forests in regional and global C cycles and have great implications for planning strategies for conservation. The study provides important data for developing and validating C cycling models for temperate forests.

Characteristics of initial deposition and behavior of radiocesium in forest ecosystems of different locations and species affected by the Fukushima Daiichi Nuclear Power Plant accident.

PubMed

Komatsu, Masabumi; Kaneko, Shinji; Ohashi, Shinta; Kuroda, Katsushi; Sano, Tetsuya; Ikeda, Shigeto; Saito, Satoshi; Kiyono, Yoshiyuki; Tonosaki, Mario; Miura, Satoru; Akama, Akio; Kajimoto, Takuya; Takahashi, Masamichi

2016-09-01

After the Fukushima Daiichi Nuclear Power Plant (FDNPP) accident, information about stand-level spatial patterns of radiocesium initially deposited in the surrounding forests was essential for predicting the future dynamics of radiocesium and suggesting a management plan for contaminated forests. In the first summer (approximately 6 months after the accident), we separately estimated the amounts of radiocesium ((134)Cs and (137)Cs; Bq m(-2)) in the major components (trees, organic layers, and soils) in forests of three sites with different contamination levels. For a Japanese cedar (Cryptomeria japonica) forest studied at each of the three sites, the radiocesium concentration greatly differed among the components, with the needle and organic layer having the highest concentrations. For these cedar forests, the proportion of the (137)Cs stock in the aboveground tree biomass varied from 22% to 44% of the total (137)Cs stock; it was 44% in highly contaminated sites (7.0 × 10(5) Bq m(-2)) but reduced to 22% in less contaminated sites (1.1 × 10(4) Bq m(-2)). In the intermediate contaminated site (5.0-5.8 × 10(4) Bq m(-2)), 34% of radiocesium was observed in the aboveground tree biomass of the Japanese cedar stand. However, this proportion was considerably smaller (18-19%) in the nearby mixed forests of the Japanese red pine (Pinus densiflora) and deciduous broad-leaved trees. Non-negligible amounts of (134)Cs and (137)Cs were detected in both the sapwood and heartwood of all the studied tree species. This finding suggested that the uptake or translocation of radiocesium had already started within 6 months after the accident. The belowground compartments were mostly present in the organic layer and the uppermost (0-5 cm deep) mineral soil layer at all the study sites. We discussed the initial transfer process of radiocesium deposited in the forest and inferred that the type of initial deposition (i.e., dry versus wet radiocesium deposition), the amount of rainfall after the accident, and the leaf biomass by the tree species may influence differences in the spatial pattern of radiocesium by study plots. The results of the present study and further studies of the spatial pattern of radiocesium are important for modeling future radiocesium distribution in contaminated forest ecosystems. Copyright © 2015 Elsevier Ltd. All rights reserved.

Optimal Wavelength Selection on Hyperspectral Data with Fused Lasso for Biomass Estimation of Tropical Rain Forest

NASA Astrophysics Data System (ADS)

Takayama, T.; Iwasaki, A.

2016-06-01

Above-ground biomass prediction of tropical rain forest using remote sensing data is of paramount importance to continuous large-area forest monitoring. Hyperspectral data can provide rich spectral information for the biomass prediction; however, the prediction accuracy is affected by a small-sample-size problem, which widely exists as overfitting in using high dimensional data where the number of training samples is smaller than the dimensionality of the samples due to limitation of require time, cost, and human resources for field surveys. A common approach to addressing this problem is reducing the dimensionality of dataset. Also, acquired hyperspectral data usually have low signal-to-noise ratio due to a narrow bandwidth and local or global shifts of peaks due to instrumental instability or small differences in considering practical measurement conditions. In this work, we propose a methodology based on fused lasso regression that select optimal bands for the biomass prediction model with encouraging sparsity and grouping, which solves the small-sample-size problem by the dimensionality reduction from the sparsity and the noise and peak shift problem by the grouping. The prediction model provided higher accuracy with root-mean-square error (RMSE) of 66.16 t/ha in the cross-validation than other methods; multiple linear analysis, partial least squares regression, and lasso regression. Furthermore, fusion of spectral and spatial information derived from texture index increased the prediction accuracy with RMSE of 62.62 t/ha. This analysis proves efficiency of fused lasso and image texture in biomass estimation of tropical forests.

A comparison of above-ground dry-biomass estimators for trees in the Northeastern United States

Treesearch

James A. Westfall

2012-01-01

In the northeastern United States, both component and total aboveground tree dry-biomass estimates are available from several sources. In this study, comparisons were made among four methods to promote understanding of the similarities and differences in live-tree biomass estimators. The methods use various equations developed from biomass data collected in the United...

Description and prediction of individual tree biomass on pinon (Pinus edulis) in northern New Mexico

Treesearch

Mark Loveall; John T. Harrington

2008-01-01

The purpose of this study was to gain reliable information on the distribution of aboveground biomass of an important component of the woodlands of north-central New Mexico, and to develop prediction equations that may be used to quickly compute biomass from relatively simple field measurements. Improved understanding of and ability to predict aboveground biomass...

High-resolution mapping of wetland vegetation biomass and distribution with L-band radar in southeastern coastal Louisiana

NASA Astrophysics Data System (ADS)

Thomas, N. M.; Simard, M.; Byrd, K. B.; Windham-Myers, L.; Castaneda, E.; Twilley, R.; Bevington, A. E.; Christensen, A.

2017-12-01

Louisiana coastal wetlands account for approximately one third (37%) of the estuarine wetland vegetation in the conterminous United States, yet the spatial distribution of their extent and aboveground biomass (AGB) is not well defined. This knowledge is critical for the accurate completion of national greenhouse gas (GHG) inventories. We generated high-resolution baselines maps of wetland vegetation extent and biomass at the Atchafalaya and Terrebonne basins in coastal Louisiana using a multi-sensor approach. Optical satellite data was used within an object-oriented machine learning approach to classify the structure of wetland vegetation types, offering increased detail over currently available land cover maps that do not distinguish between wetland vegetation types nor account for non-permanent seasonal changes in extent. We mapped 1871 km2 of wetlands during a period of peak biomass in September 2015 comprised of flooded forested wetlands and leaf, grass and emergent herbaceous marshes. The distribution of aboveground biomass (AGB) was mapped using JPL L-band Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR). Relationships between time-series radar imagery and field data collected in May 2015 and September 2016 were derived to estimate AGB at the Wax Lake and Atchafalaya deltas. Differences in seasonal biomass estimates reflect the increased AGB in September over May, concurrent with periods of peak biomass and the onset of the vegetation growing season, respectively. This method provides a tractable means of mapping and monitoring biomass of wetland vegetation types with L-band radar, in a region threatened with wetland loss under projections of increasing sea-level rise and terrestrial subsidence. Through this, we demonstrate a method that is able to satisfy the IPCC 2013 Wetlands Supplement requirement for Tier 2/Tier 3 reporting of coastal wetland GHG inventories.

Estimation of aboveground biomass in Mediterranean forests by statistical modelling of ASTER fraction images

NASA Astrophysics Data System (ADS)

Fernández-Manso, O.; Fernández-Manso, A.; Quintano, C.

2014-09-01

Aboveground biomass (AGB) estimation from optical satellite data is usually based on regression models of original or synthetic bands. To overcome the poor relation between AGB and spectral bands due to mixed-pixels when a medium spatial resolution sensor is considered, we propose to base the AGB estimation on fraction images from Linear Spectral Mixture Analysis (LSMA). Our study area is a managed Mediterranean pine woodland (Pinus pinaster Ait.) in central Spain. A total of 1033 circular field plots were used to estimate AGB from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) optical data. We applied Pearson correlation statistics and stepwise multiple regression to identify suitable predictors from the set of variables of original bands, fraction imagery, Normalized Difference Vegetation Index and Tasselled Cap components. Four linear models and one nonlinear model were tested. A linear combination of ASTER band 2 (red, 0.630-0.690 μm), band 8 (short wave infrared 5, 2.295-2.365 μm) and green vegetation fraction (from LSMA) was the best AGB predictor (Radj2=0.632, the root-mean-squared error of estimated AGB was 13.3 Mg ha-1 (or 37.7%), resulting from cross-validation), rather than other combinations of the above cited independent variables. Results indicated that using ASTER fraction images in regression models improves the AGB estimation in Mediterranean pine forests. The spatial distribution of the estimated AGB, based on a multiple linear regression model, may be used as baseline information for forest managers in future studies, such as quantifying the regional carbon budget, fuel accumulation or monitoring of management practices.

Soil amendments effects on radiocesium translocation in forest soils.

PubMed

Sugiura, Yuki; Ozawa, Hajime; Umemura, Mitsutoshi; Takenaka, Chisato

2016-12-01

We conducted an experiment to investigate the potential of phytoremediation by soil amendments in a forest area. To desorb radiocesium ( 137 Cs) from variable charges in the soil, ammonium sulfate (NH 4 + ) and elemental sulfur (S) (which decrease soil pH) were applied to forest soil collected from contaminated area at a rate of 40 and 80 g/m 2 , respectively. A control condition with no soil treatment was also considered. We defined four groups of aboveground conditions: planted with Quercus serrata, planted with Houttuynia cordata, covered with rice straw as litter, and unplanted/uncovered (control). Cultivation was performed in a greenhouse with a regular water supply for four months. Following elemental sulfur treatment, soil pH values were significantly lower than pH values following ammonium sulfate treatment and no treatment. During cultivation, several plant species germinated from natural seeds. No clear differences in aboveground tissue 137 Cs concentrations in planted Q. serrata and H. cordata were observed among the treatments. However, aboveground tissue 137 Cs concentration values in the germinated plants following elemental sulfur treatment were higher than the values following the ammonium sulfate treatment and no treatment. Although biomass values for Q. serrata, H. cordata, and germinated plants following elemental sulfur treatment tended to be low, the total 137 Cs activities in the aboveground tissue of germinated plants were higher than those following ammonium sulfate treatment and no treatment in rice straw and unplanted conditions. Although no significant differences were observed, 137 Cs concentrations in rice straw following ammonium sulfate and elemental sulfur treatments tended to be higher than those in the control case. The results of this study indicate that elemental sulfur lowers the soil pH for a relatively long period and facilitates 137 Cs translocation to newly emerged and settled plants or litter, but affects plant growth in large concentrations and/or anaerobic conditions. Combining elemental sulfur application with forest management practices, such as mowing and thinning, could be a suitable method of decontamination of the forest environment. Copyright © 2016 Elsevier Ltd. All rights reserved.

The effect of topography on arctic-alpine aboveground biomass and NDVI patterns

NASA Astrophysics Data System (ADS)

Riihimäki, Henri; Heiskanen, Janne; Luoto, Miska

2017-04-01

Topography is a key factor affecting numerous environmental phenomena, including Arctic and alpine aboveground biomass (AGB) distribution. Digital Elevation Model (DEM) is a source of topographic information which can be linked to local growing conditions. Here, we investigated the effect of DEM derived variables, namely elevation, topographic position, radiation and wetness on AGB and Normalized Difference Vegetation Index (NDVI) in a Fennoscandian forest-alpine tundra ecotone. Boosted regression trees were used to derive non-parametric response curves and relative influences of the explanatory variables. Elevation and potential incoming solar radiation were the most important explanatory variables for both AGB and NDVI. In the NDVI models, the response curves were smooth compared with AGB models. This might be caused by large contribution of field and shrub layer to NDVI, especially at the treeline. Furthermore, radiation and elevation had a significant interaction, showing that the highest NDVI and biomass values are found from low-elevation, high-radiation sites, typically on the south-southwest facing valley slopes. Topographic wetness had minor influence on AGB and NDVI. Topographic position had generally weak effects on AGB and NDVI, although protected topographic position seemed to be more favorable below the treeline. The explanatory power of the topographic variables, particularly elevation and radiation demonstrates that DEM-derived land surface parameters can be used for exploring biomass distribution resulting from landform control on local growing conditions.

Modelling moose–forest interactions under different predation scenarios at Isle Royale National Park, USA

USGS Publications Warehouse

DeJager, Nathan R.; Rohweder, Jason; Miranda, Brian R.; Sturtevant, Brian R.; Fox, Timothy J.; Romanski, Mark C.

2017-01-01

Loss of top predators may contribute to high ungulate population densities and chronic over-browsing of forest ecosystems. However, spatial and temporal variability in the strength of interactions between predators and ungulates occurs over scales that are much shorter than the scales over which forest communities change, making it difficult to characterize trophic cascades in forest ecosystems. We applied the LANDIS-II forest succession model and a recently developed ungulate browsing extension to model how the moose population could interact with the forest ecosystem of Isle Royale National Park, USA, under three different wolf predation scenarios. We contrasted a 100-yr future without wolves (no predation) with two predation scenarios (weak, long-term average predation rates and strong, higher than average rates). Increasing predation rates led to lower peak moose population densities, lower biomass removal rates, and higher estimates of forage availability and landscape carrying capacity, especially during the first 40 yr of simulations. Thereafter, moose population density was similar for all predation scenarios, but available forage biomass and the carrying capacity of the landscape continued to diverge among predation scenarios. Changes in total aboveground live biomass and species composition were most pronounced in the no predation and weak predation scenarios. Consistent with smaller-scale studies, high browsing rates led to reductions in the biomass of heavily browsed Populus tremuloides, Betula papyrifera, and Abies balsamea, and increases in the biomass of unbrowsed Picea glauca and Picea mariana, especially after the simulation year 2050, when existing boreal hardwood stands at Isle Royale are projected to senesce. As a consequence, lower predation rates corresponded with a landscape that progressively shifted toward dominance by Picea glauca and Picea mariana, and lacking available forage biomass. Consistencies with previously documented small-scale successional shifts, and population estimates and trends that approximate those from this and other boreal forests that support moose provide some confidence that these dynamics represent a trophic cascade and therefore provide an important baseline against which to evaluate long-term and large-scale effects of alternative predator management strategies on ungulate populations and forest succession.

Unravelling ecosystem functions at the Amazonia-Cerrado transition: II. Carbon stocks and CO2 soil efflux in cerradão forest undergoing ecological succession

NASA Astrophysics Data System (ADS)

Peixoto, Karine S.; Marimon-Junior, Ben Hur; Marimon, Beatriz S.; Elias, Fernando; de Farias, Josenilton; Freitag, Renata; Mews, Henrique A.; das Neves, Eder C.; Prestes, Nayane Cristina C. S.; Malhi, Yadvinder

2017-07-01

The transition region between two major South American biomes, the Amazon forest and the Cerrado (Brazilian savanna), has been substantially converted into human-modified ecosystems. Nevertheless, the recovery dynamics of ecosystem functions in this important zone of (ecological) tension (ZOT) remain poorly understood. In this study, we compared two areas of cerradão (a forest-woodland of the Brazilian savanna; Portuguese augmentative of cerrado), one in secondary succession (SC) and one adjacent and well preserved (PC), to test whether the ecosystem functions lost after conversion to pasture were restored after 22 years of regeneration. We tested the hypothesis that the increase in annual aboveground biomass in the SC would be greater than that in the PC because of anticipated successional gains. We also investigated soil CO2 efflux, litter layer content, and fine root biomass in both the SC and PC. In terms of biomass recovery our hypothesis was not supported: the biomass did not increase in the successional area over the study period, which suggested limited capacity for recovery in this key ecosystem compartment. By contrast, the structure and function of the litter layer and root mat were largely reconstituted in the secondary vegetation. Overall, we provide evidence that 22 years of secondary succession were not sufficient for these short and open forests (e.g., cerradão) in the ZOT to recover ecosystem functions to the levels observed in preserved vegetation of identical physiognomy.

Widespread decline of Congo rainforest greenness in the past decade.

PubMed

Zhou, Liming; Tian, Yuhong; Myneni, Ranga B; Ciais, Philippe; Saatchi, Sassan; Liu, Yi Y; Piao, Shilong; Chen, Haishan; Vermote, Eric F; Song, Conghe; Hwang, Taehee

2014-05-01

Tropical forests are global epicentres of biodiversity and important modulators of climate change, and are mainly constrained by rainfall patterns. The severe short-term droughts that occurred recently in Amazonia have drawn attention to the vulnerability of tropical forests to climatic disturbances. The central African rainforests, the second-largest on Earth, have experienced a long-term drying trend whose impacts on vegetation dynamics remain mostly unknown because in situ observations are very limited. The Congolese forest, with its drier conditions and higher percentage of semi-evergreen trees, may be more tolerant to short-term rainfall reduction than are wetter tropical forests, but for a long-term drought there may be critical thresholds of water availability below which higher-biomass, closed-canopy forests transition to more open, lower-biomass forests. Here we present observational evidence for a widespread decline in forest greenness over the past decade based on analyses of satellite data (optical, thermal, microwave and gravity) from several independent sensors over the Congo basin. This decline in vegetation greenness, particularly in the northern Congolese forest, is generally consistent with decreases in rainfall, terrestrial water storage, water content in aboveground woody and leaf biomass, and the canopy backscatter anomaly caused by changes in structure and moisture in upper forest layers. It is also consistent with increases in photosynthetically active radiation and land surface temperature. These multiple lines of evidence indicate that this large-scale vegetation browning, or loss of photosynthetic capacity, may be partially attributable to the long-term drying trend. Our results suggest that a continued gradual decline of photosynthetic capacity and moisture content driven by the persistent drying trend could alter the composition and structure of the Congolese forest to favour the spread of drought-tolerant species.

Improving estimation of tree carbon stocks by harvesting aboveground woody biomass within airborne LiDAR flight areas

NASA Astrophysics Data System (ADS)

Colgan, M.; Asner, G. P.; Swemmer, A. M.

2011-12-01

The accurate estimation of carbon stored in a tree is essential to accounting for the carbon emissions due to deforestation and degradation. Airborne LiDAR (Light Detection and Ranging) has been successful in estimating aboveground carbon density (ACD) by correlating airborne metrics, such as canopy height, to field-estimated biomass. This latter step is reliant on field allometry which is applied to forest inventory quantities, such as stem diameter and height, to predict the biomass of a given tree stem. Constructing such allometry is expensive, time consuming, and requires destructive sampling. Consequently, the sample sizes used to construct such allometry are often small, and the largest tree sampled is often much smaller than the largest in the forest population. The uncertainty resulting from these sampling errors can lead to severe biases when the allometry is applied to stems larger than those harvested to construct the allometry, which is then subsequently propagated to airborne ACD estimates. The Kruger National Park (KNP) mission of maintaining biodiversity coincides with preserving ecosystem carbon stocks. However, one hurdle to accurately quantifying carbon density in savannas is that small stems are typically harvested to construct woody biomass allometry, yet they are not representative of Kruger's distribution of biomass. Consequently, these equations inadequately capture large tree variation in sapwood/hardwood composition, root/shoot/leaf allocation, branch fall, and stem rot. This study eliminates the "middleman" of field allometry by directly measuring, or harvesting, tree biomass within the extent of airborne LiDAR. This enables comparisons of field and airborne ACD estimates, and also enables creation of new airborne algorithms to estimate biomass at the scale of individual trees. A field campaign was conducted at Pompey Silica Mine 5km outside Kruger National Park, South Africa, in Mar-Aug 2010 to harvest and weigh tree mass. Since harvesting of trees is not possible within KNP, this was a unique opportunity to fell trees already scheduled to be cleared for mining operations. The area was first flown by the Carnegie Airborne Observatory in early May, prior to harvest, to enable correlation of LiDAR-measured tree height and crown diameter to harvested tree mass. Results include over 4,000 harvested stems and 13 species-specific biomass equations, including seven Kruger woody species previously without allometry. We found existing biomass stem allometry over-estimates ACD in the field, whereas airborne estimates based on harvest data avoid this bias while maintaining similar precision to field-based estimates. Lastly, a new airborne algorithm estimating biomass at the tree-level reduced error from tree canopies "leaning" into field plots but whose stems are outside plot boundaries. These advances pave the way to better understanding of savanna and forest carbon density at landscape and regional scales.

Forest Soil Phosphorus Resources and Fertilization Affect Ectomycorrhizal Community Composition, Beech P Uptake Efficiency, and Photosynthesis

PubMed Central

Zavišić, Aljosa; Yang, Nan; Marhan, Sven; Kandeler, Ellen; Polle, Andrea

2018-01-01

Phosphorus (P) is an important nutrient, whose plant-available form phosphate is often low in natural forest ecosystems. Mycorrhizal fungi mine the soil for P and supply their host with this resource. It is unknown how ectomycorrhizal communities respond to changes in P availability. Here, we used young beech (Fagus sylvatica L.) trees in natural forest soil from a P-rich and P-poor site to investigate the impact of P amendment on soil microbes, mycorrhizas, beech P nutrition, and photosynthesis. We hypothesized that addition of P to forest soil increased P availability, thereby, leading to enhanced microbial biomass and mycorrhizal diversity in P-poor but not in P-rich soil. We expected that P amendment resulted in increased plant P uptake and enhanced photosynthesis in both soil types. Young beech trees with intact soil cores from a P-rich and a P-poor forest were kept in a common garden experiment and supplied once in fall with triple superphosphate. In the following summer, labile P in the organic layer, but not in the mineral top soil, was significantly increased in response to fertilizer treatment. P-rich soil contained higher microbial biomass than P-poor soil. P treatment had no effect on microbial biomass but influenced the mycorrhizal communities in P-poor soil and shifted their composition toward higher similarities to those in P-rich soil. Plant uptake efficiency was negatively correlated with the diversity of mycorrhizal communities and highest for trees in P-poor soil and lowest for fertilized trees. In both soil types, radioactive P tracing (H333PO4) revealed preferential aboveground allocation of new P in fertilized trees, resulting in increased bound P in xylem tissue and enhanced soluble P in bark, indicating increased storage and transport. Fertilized beeches from P-poor soil showed a strong increase in leaf P concentrations from deficient to luxurious conditions along with increased photosynthesis. Based on the divergent behavior of beech in P-poor and P-rich forest soil, we conclude that acclimation of beech to low P stocks involves dedicated mycorrhizal community structures, low P reserves in storage tissues and photosynthetic inhibition, while storage and aboveground allocation of additional P occurs regardless of the P nutritional status. PMID:29706979

Response of NDVI, biomass, and ecosystem gas exchange to long-term warming and fertilization in wet sedge tundra.

PubMed

Boelman, Natalie T; Stieglitz, Marc; Rueth, Heather M; Sommerkorn, Martin; Griffin, Kevin L; Shaver, Gaius R; Gamon, John A

2003-05-01

This study explores the relationship between the normalized difference vegetation index (NDVI), aboveground plant biomass, and ecosystem C fluxes including gross ecosystem production (GEP), ecosystem respiration (ER) and net ecosystem production. We measured NDVI across long-term experimental treatments in wet sedge tundra at the Toolik Lake LTER site, in northern Alaska. Over 13 years, N and P were applied in factorial experiments (N, P and N + P), air temperature was increased using greenhouses with and without N + P fertilizer, and light intensity (photosynthetically active photon flux density) was reduced by 50% using shade cloth. Within each treatment plot, NDVI, aboveground biomass and whole-system CO(2) flux measurements were made at the same sampling points during the peak-growing season of 2001. We found that across all treatments, NDVI is correlated with aboveground biomass ( r(2)=0.84), GEP ( r(2)=0.75) and ER ( r(2)=0.71), providing a basis for linking remotely sensed NDVI to aboveground biomass and ecosystem carbon flux.

Data for developing allometric models and evaluating carbon stocks of the Zambezi Teak Forests in Zambia.

PubMed

Ngoma, Justine; Moors, Eddy; Kruijt, Bart; Speer, James H; Vinya, Royd; Chidumayo, Emmanuel N; Leemans, Rik

2018-04-01

This paper presents data on carbon stocks of tropical tree species along a rainfall gradient. The data was generated from the Sesheke, Namwala, and Kabompo sites in Zambia. Though above-ground data was generated for all these three sites, we uprooted trees to determine below-ground biomass from the Sesheke site only. The vegetation was assessed in all three sites. The data includes tree diameter at breast height (DBH), total tree height, wood density, wood dry weight and root dry weight for large (≥ 5 cm DBH) and small (< 5 cm DBH) trees. We further presented Root-to-Shoot Ratios of uprooted trees. Data on the importance-value indices of various species for large and small trees are also determined. Below and above-ground carbon stocks of the surveyed tree species are presented per site. This data were used by Ngoma et al. (2018) [1] to develop above and below-ground biomass models and the reader is referred to this study for additional information, interpretation, and reflection on applying this data.

Benchmark map of forest carbon stocks in tropical regions across three continents

PubMed Central

Saatchi, Sassan S.; Harris, Nancy L.; Brown, Sandra; Lefsky, Michael; Mitchard, Edward T. A.; Salas, William; Zutta, Brian R.; Buermann, Wolfgang; Lewis, Simon L.; Hagen, Stephen; Petrova, Silvia; White, Lee; Silman, Miles; Morel, Alexandra

2011-01-01

Developing countries are required to produce robust estimates of forest carbon stocks for successful implementation of climate change mitigation policies related to reducing emissions from deforestation and degradation (REDD). Here we present a “benchmark” map of biomass carbon stocks over 2.5 billion ha of forests on three continents, encompassing all tropical forests, for the early 2000s, which will be invaluable for REDD assessments at both project and national scales. We mapped the total carbon stock in live biomass (above- and belowground), using a combination of data from 4,079 in situ inventory plots and satellite light detection and ranging (Lidar) samples of forest structure to estimate carbon storage, plus optical and microwave imagery (1-km resolution) to extrapolate over the landscape. The total biomass carbon stock of forests in the study region is estimated to be 247 Gt C, with 193 Gt C stored aboveground and 54 Gt C stored belowground in roots. Forests in Latin America, sub-Saharan Africa, and Southeast Asia accounted for 49%, 25%, and 26% of the total stock, respectively. By analyzing the errors propagated through the estimation process, uncertainty at the pixel level (100 ha) ranged from ±6% to ±53%, but was constrained at the typical project (10,000 ha) and national (>1,000,000 ha) scales at ca. ±5% and ca. ±1%, respectively. The benchmark map illustrates regional patterns and provides methodologically comparable estimates of carbon stocks for 75 developing countries where previous assessments were either poor or incomplete. PMID:21628575

Height and Biomass of Mangroves in Africa from ICEsat/GLAS and SRTM

NASA Technical Reports Server (NTRS)

Fatoyinbo, Temilola E.; Simard, Marc

2012-01-01

The accurate quantification of forest 3-D structure is of great importance for studies of the global carbon cycle and biodiversity. These studies are especially relevant in Africa, where deforestation rates are high and the lack of background data is great. Mangrove forests are ecologically significant and it is important to measure mangrove canopy heights and biomass. The objectives of this study are to estimate: 1. The total area, 2. Canopy height distributions and 3. Aboveground biomass of mangrove forests in Africa. To derive mangrove 3-D structure and biomass maps, we used a combination of mangrove maps derived from Landsat ETM+, LiDAR canopy height estimates from ICEsat/GLAS (Ice, Cloud, and land Elevation Satellite/Geoscience Laser Altimeter System) and elevation data from SRTM (Shuttle Radar Topography Mission) for the African continent. More specifically, we extracted mangrove forest areas on the SRTM DEM using Landsat based landcover maps. The LiDAR (Light Detection and Ranging) measurements from the large footprint GLAS sensor were used to derive local estimates of canopy height and calibrate the Interferometric Synthetic Aperture Radar (InSAR) data from SRTM. We then applied allometric equations relating canopy height to biomass in order to estimate above ground biomass (AGB) from the canopy height product. The total mangrove area of Africa was estimated to be 25 960 square kilometers with 83% accuracy. The largest mangrove areas and greatest total biomass was 29 found in Nigeria covering 8 573 km2 with 132 x10(exp 6) Mg AGB. Canopy height across Africa was estimated with an overall root mean square error of 3.55 m. This error also includes the impact of using sensors with different resolutions and geolocation error which make comparison between measurements sensitive to canopy heterogeneities. This study provides the first systematic estimates of mangrove area, height and biomass in Africa. Our results showed that the combination of ICEsat/GLAS and SRTM data is well suited for vegetation 3-D mapping on a continental scale.

Estimating terrestrial aboveground biomass estimation using lidar remote sensing: a meta-analysis

NASA Astrophysics Data System (ADS)

Zolkos, S. G.; Goetz, S. J.; Dubayah, R.

2012-12-01

Estimating biomass of terrestrial vegetation is a rapidly expanding research area, but also a subject of tremendous interest for reducing carbon emissions associated with deforestation and forest degradation (REDD). The accuracy of biomass estimates is important in the context carbon markets emerging under REDD, since areas with more accurate estimates command higher prices, but also for characterizing uncertainty in estimates of carbon cycling and the global carbon budget. There is particular interest in mapping biomass so that carbon stocks and stock changes can be monitored consistently across a range of scales - from relatively small projects (tens of hectares) to national or continental scales - but also so that other benefits of forest conservation can be factored into decision making (e.g. biodiversity and habitat corridors). We conducted an analysis of reported biomass accuracy estimates from more than 60 refereed articles using different remote sensing platforms (aircraft and satellite) and sensor types (optical, radar, lidar), with a particular focus on lidar since those papers reported the greatest efficacy (lowest errors) when used in the a synergistic manner with other coincident multi-sensor measurements. We show systematic differences in accuracy between different types of lidar systems flown on different platforms but, perhaps more importantly, differences between forest types (biomes) and plot sizes used for field calibration and assessment. We discuss these findings in relation to monitoring, reporting and verification under REDD, and also in the context of more systematic assessment of factors that influence accuracy and error estimation.

Testing the generality of above-ground biomass allometry across plant functional types at the continent scale.

PubMed

Paul, Keryn I; Roxburgh, Stephen H; Chave, Jerome; England, Jacqueline R; Zerihun, Ayalsew; Specht, Alison; Lewis, Tom; Bennett, Lauren T; Baker, Thomas G; Adams, Mark A; Huxtable, Dan; Montagu, Kelvin D; Falster, Daniel S; Feller, Mike; Sochacki, Stan; Ritson, Peter; Bastin, Gary; Bartle, John; Wildy, Dan; Hobbs, Trevor; Larmour, John; Waterworth, Rob; Stewart, Hugh T L; Jonson, Justin; Forrester, David I; Applegate, Grahame; Mendham, Daniel; Bradford, Matt; O'Grady, Anthony; Green, Daryl; Sudmeyer, Rob; Rance, Stan J; Turner, John; Barton, Craig; Wenk, Elizabeth H; Grove, Tim; Attiwill, Peter M; Pinkard, Elizabeth; Butler, Don; Brooksbank, Kim; Spencer, Beren; Snowdon, Peter; O'Brien, Nick; Battaglia, Michael; Cameron, David M; Hamilton, Steve; McAuthur, Geoff; Sinclair, Jenny

2016-06-01

Accurate ground-based estimation of the carbon stored in terrestrial ecosystems is critical to quantifying the global carbon budget. Allometric models provide cost-effective methods for biomass prediction. But do such models vary with ecoregion or plant functional type? We compiled 15 054 measurements of individual tree or shrub biomass from across Australia to examine the generality of allometric models for above-ground biomass prediction. This provided a robust case study because Australia includes ecoregions ranging from arid shrublands to tropical rainforests, and has a rich history of biomass research, particularly in planted forests. Regardless of ecoregion, for five broad categories of plant functional type (shrubs; multistemmed trees; trees of the genus Eucalyptus and closely related genera; other trees of high wood density; and other trees of low wood density), relationships between biomass and stem diameter were generic. Simple power-law models explained 84-95% of the variation in biomass, with little improvement in model performance when other plant variables (height, bole wood density), or site characteristics (climate, age, management) were included. Predictions of stand-based biomass from allometric models of varying levels of generalization (species-specific, plant functional type) were validated using whole-plot harvest data from 17 contrasting stands (range: 9-356 Mg ha(-1) ). Losses in efficiency of prediction were <1% if generalized models were used in place of species-specific models. Furthermore, application of generalized multispecies models did not introduce significant bias in biomass prediction in 92% of the 53 species tested. Further, overall efficiency of stand-level biomass prediction was 99%, with a mean absolute prediction error of only 13%. Hence, for cost-effective prediction of biomass across a wide range of stands, we recommend use of generic allometric models based on plant functional types. Development of new species-specific models is only warranted when gains in accuracy of stand-based predictions are relatively high (e.g. high-value monocultures). © 2015 John Wiley & Sons Ltd.

Species richness of arbuscular mycorrhizal fungi: associations with grassland plant richness and biomass.

PubMed

Hiiesalu, Inga; Pärtel, Meelis; Davison, John; Gerhold, Pille; Metsis, Madis; Moora, Mari; Öpik, Maarja; Vasar, Martti; Zobel, Martin; Wilson, Scott D

2014-07-01

Although experiments show a positive association between vascular plant and arbuscular mycorrhizal fungal (AMF) species richness, evidence from natural ecosystems is scarce. Furthermore, there is little knowledge about how AMF richness varies with belowground plant richness and biomass. We examined relationships among AMF richness, above- and belowground plant richness, and plant root and shoot biomass in a native North American grassland. Root-colonizing AMF richness and belowground plant richness were detected from the same bulk root samples by 454-sequencing of the AMF SSU rRNA and plant trnL genes. In total we detected 63 AMF taxa. Plant richness was 1.5 times greater belowground than aboveground. AMF richness was significantly positively correlated with plant species richness, and more strongly with below- than aboveground plant richness. Belowground plant richness was positively correlated with belowground plant biomass and total plant biomass, whereas aboveground plant richness was positively correlated only with belowground plant biomass. By contrast, AMF richness was negatively correlated with belowground and total plant biomass. Our results indicate that AMF richness and plant belowground richness are more strongly related with each other and with plant community biomass than with the plant aboveground richness measures that have been almost exclusively considered to date. © 2014 The Authors. New Phytologist © 2014 New Phytologist Trust.

Development of a data driven process-based model for remote sensing of terrestrial ecosystem productivity, evapotranspiration, and above-ground biomass

NASA Astrophysics Data System (ADS)

El Masri, Bassil

2011-12-01

Modeling terrestrial ecosystem functions and structure has been a subject of increasing interest because of the importance of the terrestrial carbon cycle in global carbon budget and climate change. In this study, satellite data were used to estimate gross primary production (GPP), evapotranspiration (ET) for two deciduous forests: Morgan Monroe State forest (MMSF) in Indiana and Harvard forest in Massachusetts. Also, above-ground biomass (AGB) was estimated for the MMSF and the Howland forest (mixed forest) in Maine. Surface reflectance and temperature, vegetation indices, soil moisture, tree height and canopy area derived from the Moderate Resolution Imagining Spectroradiometer (MODIS), the Advanced Microwave Scanning Radiometer (AMRS-E), LIDAR, and aerial imagery respectively, were used for this purpose. These variables along with others derived from remotely sensed data were used as inputs variables to process-based models which estimated GPP and ET and to a regression model which estimated AGB. The process-based models were BIOME-BGC and the Penman-Monteith equation. Measured values for the carbon and water fluxes obtained from the Eddy covariance flux tower were compared to the modeled GPP and ET. The data driven methods produced good estimation of GPP and ET with an average root mean square error (RMSE) of 0.17 molC/m2 and 0.40 mm/day, respectively for the MMSF and the Harvard forest. In addition, allometric data for the MMSF were used to develop the regression model relating AGB with stem volume. The performance of the AGB regression model was compared to site measurements using remotely sensed data for the MMSF and the Howland forest where the model AGB RMSE ranged between 2.92--3.30 Kg C/m2. Sensitivity analysis revealed that improvement in maintenance respiration estimation and remotely sensed maximum photosynthetic activity as well as accurate estimate of canopy resistance will result in improved GPP and ET predictions. Moreover, AGB estimates were found to decrease as large grid size is used in rasterizing LIDAR return points. The analysis suggested that this methodology could be used as an operational procedure for monitoring changes in terrestrial ecosystem functions and structure brought by environmental changes.

Trade-offs in plant responses to herbivory influence trophic routes of production in a freshwater wetland.

PubMed

Cherry, Julia A; Gough, Laura

2009-09-01

Responses of aquatic macrophytes to leaf herbivory may differ from those documented for terrestrial plants, in part, because the potential to maximize growth following herbivory may be limited by the stress of being rooted in flooded, anaerobic sediments. Herbivory on aquatic macrophytes may have ecosystem consequences by altering the allocation of nutrients and production of biomass within individual plants and changing the quality and quantity of aboveground biomass available to consumers or decomposers. To test the effects of leaf herbivory on plant growth and production, herbivory of a dominant macrophyte, Nymphaea odorata, by chrysomelid beetles and crambid moths was controlled during a 2-year field experiment. Plants exposed to herbivory maintained, or tended to increase, biomass and aboveground net primary production relative to controls, which resulted in 1.5 times more aboveground primary production entering the detrital pathway of the wetland. In a complementary greenhouse experiment, the effects of simulated leaf herbivory on total plant responses, including biomass and nutrient allocation, were investigated. Plants in the greenhouse responded to moderate herbivory by maintaining aboveground biomass relative to controls, but this response occurred at the expense of belowground growth. Results of these studies suggest that N. odorata may tolerate moderate levels of herbivory by reallocating biomass and resources aboveground, which in turn influences the quantity, quality and fate of organic matter available to herbivores and decomposers.

Forest Biomass Mapping From Lidar and Radar Synergies

NASA Technical Reports Server (NTRS)

Sun, Guoqing; Ranson, K. Jon; Guo, Z.; Zhang, Z.; Montesano, P.; Kimes, D.

2011-01-01

The use of lidar and radar instruments to measure forest structure attributes such as height and biomass at global scales is being considered for a future Earth Observation satellite mission, DESDynI (Deformation, Ecosystem Structure, and Dynamics of Ice). Large footprint lidar makes a direct measurement of the heights of scatterers in the illuminated footprint and can yield accurate information about the vertical profile of the canopy within lidar footprint samples. Synthetic Aperture Radar (SAR) is known to sense the canopy volume, especially at longer wavelengths and provides image data. Methods for biomass mapping by a combination of lidar sampling and radar mapping need to be developed. In this study, several issues in this respect were investigated using aircraft borne lidar and SAR data in Howland, Maine, USA. The stepwise regression selected the height indices rh50 and rh75 of the Laser Vegetation Imaging Sensor (LVIS) data for predicting field measured biomass with a R(exp 2) of 0.71 and RMSE of 31.33 Mg/ha. The above-ground biomass map generated from this regression model was considered to represent the true biomass of the area and used as a reference map since no better biomass map exists for the area. Random samples were taken from the biomass map and the correlation between the sampled biomass and co-located SAR signature was studied. The best models were used to extend the biomass from lidar samples into all forested areas in the study area, which mimics a procedure that could be used for the future DESDYnI Mission. It was found that depending on the data types used (quad-pol or dual-pol) the SAR data can predict the lidar biomass samples with R2 of 0.63-0.71, RMSE of 32.0-28.2 Mg/ha up to biomass levels of 200-250 Mg/ha. The mean biomass of the study area calculated from the biomass maps generated by lidar- SAR synergy 63 was within 10% of the reference biomass map derived from LVIS data. The results from this study are preliminary, but do show the potential of the combined use of lidar samples and radar imagery for forest biomass mapping. Various issues regarding lidar/radar data synergies for biomass mapping are discussed in the paper.

Net primary production and phenology on a southern Appalachian watershed

DOE Office of Scientific and Technical Information (OSTI.GOV)

Day, F.P. Jr.; Monk, C.D.

1977-01-01

Net primary production (NPP) is an important function of plant communities which has not often been examined seasonally in a forested ecosystem. The major objective of the study was to measure above-ground NPP seasonally and relate it to phenological activity on a hardwood forest watershed at Coweeta Hydrologic Laboratory, North Carolina. NPP was estimated as the increase in biomass, estimated from regression equations on diameter. Diameter increases were measured by venier tree bands. Phenological observations were made on bud break, leaf emergence, flowering, mature fruit, leaf senescence, and leaf fall. The species studied intensively were Acer rubrum, Quercus prinus, Caryamore » glabra, Cornus florida, and Liriodendron tulipifera. Liriodendron was found to be the most productive species per individual, but Quercus prinus was the most productive per unit ground area. The total watershed estimate of aboveground NPP was 8,754 kg ha/sup -1/yr/sup -1/ and included 47.9 percent leaves, 33.2 percent wood, 7.8 percent bark, 4.8 percent reproductive tissues, 4.2 percent loss to consumers, and 2.1 percent twigs. Increases in leaf biomass were most rapid in the spring, but woody tissue production peaked in June and continued through August. Since leaf production peaked in the spring, the plants' photosynthetic machinery was activated early in the growing season to support woody tissue production, which followed the period of rapid leaf growth, and reproductive activity. Flowering occurred during the leaf expansion period except for Acer rubrum, which flowered before leaf emergence. Fruit maturation occurred during late summer to early fall, when there were no additional biomass increases. Acer rubrum was an exception as its fruit matured during the period of leaf expansion.« less

Net primary production and phenology on a southern Appalachian watershed

DOE Office of Scientific and Technical Information (OSTI.GOV)

Day, F.P. Jr.; Monk, C.D.

1977-10-01

Net primary production (NPP) is an important function of plant communities which has not often been examined seasonally in a forested ecosystem. The major objective of the study was to measure above-ground NPP seasonally and relate it to phenological activity on a hardwood forest watershed at Coweeta Hydrologic Laboratory, North Carolina. NPP was estimated as the increase in biomass, estimated from regression equations on diameter. Diameter increases were measured by vernier tree bands. Phenological observations were made on bud break, leaf emergence, flowering, mature fruit, leaf senescence, and leaf fall. The species studied intensively were Acer rubrum, Quercus prinus, Caryamore » glabra, Cornus florida, and Liriodendron tulipifera. Liriodendron was found to be the most productive species per individual, but Quercus prinus was the most productive per unit ground area. The total watershed estimate of aboveground NPP was 8,754 kg ha/sup -1/ yr/sup -1/ and included 47.9% leaves, 33.2% wood, 7.8% bark, 4.8% reproductive tissues, 4.2% loss to consumers, and 2.1% twigs. Increases in leaf biomass were most rapid in the spring, but woody tissue production peaked in June and continued through August. Since leaf production peaked in the spring, the plants' photosynthetic machinery was activated early in the growing season to support woody tissue production, which followed the period of rapid leaf growth, and reproductive activity. Flowering ocurred during the leaf expansion period except for Acer rubrum, which flowered before leaf emergence. Fruit maturation occurred during late summer to early fall, when there were no additional biomass increases. Acer rubrum was an exception as its fruit matured during the period of leaf expansion.« less

Combined effects of nitrogen addition and organic matter manipulation on soil respiration in a Chinese pine forest.

PubMed

Wang, Jinsong; Wu, L; Zhang, Chunyu; Zhao, Xiuhai; Bu, Wensheng; Gadow, Klaus V

2016-11-01

The response of soil respiration (Rs) to nitrogen (N) addition is one of the uncertainties in modelling ecosystem carbon (C). We reported on a long-term nitrogen (N) addition experiment using urea (CO(NH 2 ) 2 ) fertilizer in which Rs was continuously measured after N addition during the growing season in a Chinese pine forest. Four levels of N addition, i.e. no added N (N0: 0 g N m -2  year -1 ), low-N (N1: 5 g N m -2  year -1 ), medium-N (N2: 10 g N m -2  year -1 ), and high-N (N3: 15 g N m -2  year -1 ), and three organic matter treatments, i.e. both aboveground litter and belowground root removal (LRE), only aboveground litter removal (LE), and intact soil (CK), were examined. The Rs was measured continuously for 3 days following each N addition application and was measured approximately 3-5 times during the rest of each month from July to October 2012. N addition inhibited microbial heterotrophic respiration by suppressing soil microbial biomass, but stimulated root respiration and CO 2 release from litter decomposition by increasing either root biomass or microbial biomass. When litter and/or root were removed, the "priming" effect of N addition on the Rs disappeared more quickly than intact soil. This is likely to provide a point of view for why Rs varies so much in response to exogenous N and also has implications for future determination of sampling interval of Rs measurement.

Spatial complexities in aboveground carbon stocks of a semi-arid mangrove community: A remote sensing height-biomass-carbon approach

NASA Astrophysics Data System (ADS)

Hickey, S. M.; Callow, N. J.; Phinn, S.; Lovelock, C. E.; Duarte, C. M.

2018-01-01

Mangroves are integral to ecosystem services provided by the coastal zone, in particular carbon (C) sequestration and storage. Allometric relationships linking mangrove height to estimated biomass and C stocks have been developed from field sampling, while various forms of remote sensing has been used to map vegetation height and biomass. Here we combine both these approaches to investigate spatial patterns in living biomass of mangrove forests in a small area of mangrove in north-west Australia. This study used LiDAR data and Landsat 8 OLI (Operational Land Imager) with allometric equations to derive mangrove height, biomass, and C stock estimates. We estimated the study site, Mangrove Bay, a semi-arid site in north-western Australia, contained 70 Mg ha-1 biomass and 45 Mg C ha-1 organic C, with total stocks of 2417 Mg biomass and 778 Mg organic C. Using spatial statistics to identify the scale of clustering of mangrove pixels, we found that living biomass and C stock declined with increasing distance from hydrological features (creek entrance: 0-150 m; y = -0.00041x + 0.9613, R2 = 0.96; 150-770 m; y = -0.0008x + 1.6808, R2 = 0.73; lagoon: y = -0.0041x + 3.7943, R2 = 0.78). Our results illustrate a set pattern of living C distribution within the mangrove forest, and then highlight the role hydrologic features play in determining C stock distribution in the arid zone.

CTFS/ForestGEO: A global network to monitor forest interactions with a changing climate

NASA Astrophysics Data System (ADS)

Anderson-Teixeira, K. J.; Muller-Landau, H.; McMahon, S.; Davies, S. J.

2013-12-01

Forests are an influential component of the global carbon cycle and strongly influence Earth's climate. Climate change is altering the dynamics of forests globally, which may result in significant climate feedbacks. Forest responses to climate change entail both short-term ecophysiological responses and longer-term directional shifts in community composition. These short- and long-term responses of forest communities to climate change may be better understood through long-term monitoring of large forest plots globally using standardized methodology. Here, we describe a global network of forest research plots (CTFS/ForestGEO) of utility for understanding forest responses to climate change and consequent feedbacks to the climate system. CTFS/ForestGEO is an international network consisting of 51 sites ranging in size from 2-150 ha (median size: 25 ha) and spanning from 25°S to 52°N latitude. At each site, every individual > 1cm DBH is mapped and identified, and recruitment, growth, and mortality are monitored every 5 years. Additional measurements include aboveground productivity, carbon stocks, soil nutrients, plant functional traits, arthropod and vertebrates monitoring, DNA barcoding, airborne and ground-based LiDAR, micrometeorology, and weather monitoring. Data from this network are useful for understanding how forest ecosystem structure and function respond to spatial and temporal variation in abiotic drivers, parameterizing and evaluating ecosystem and earth system models, aligning airborne and ground-based measurements, and identifying directional changes in forest productivity and composition. For instance, CTFS/ForestGEO data have revealed that solar radiation and night-time temperature are important drivers of aboveground productivity in moist tropical forests; that tropical forests are mixed in terms of productivity and biomass trends over the past couple decades; and that the composition of Panamanian forests has shifted towards more drought-tolerant species. Ongoing monitoring will be vital to understanding global forest dynamics in an era of climate change.

Tropical Andean Forests Are Highly Susceptible to Nutrient Inputs—Rapid Effects of Experimental N and P Addition to an Ecuadorian Montane Forest

PubMed Central

Homeier, Jürgen; Hertel, Dietrich; Camenzind, Tessa; Cumbicus, Nixon L.; Maraun, Mark; Martinson, Guntars O.; Poma, L. Nohemy; Rillig, Matthias C.; Sandmann, Dorothee; Scheu, Stefan; Veldkamp, Edzo; Wilcke, Wolfgang; Wullaert, Hans; Leuschner, Christoph

2012-01-01

Tropical regions are facing increasing atmospheric inputs of nutrients, which will have unknown consequences for the structure and functioning of these systems. Here, we show that Neotropical montane rainforests respond rapidly to moderate additions of N (50 kg ha−1 yr−1) and P (10 kg ha−1 yr−1). Monitoring of nutrient fluxes demonstrated that the majority of added nutrients remained in the system, in either soil or vegetation. N and P additions led to not only an increase in foliar N and P concentrations, but also altered soil microbial biomass, standing fine root biomass, stem growth, and litterfall. The different effects suggest that trees are primarily limited by P, whereas some processes—notably aboveground productivity—are limited by both N and P. Highly variable and partly contrasting responses of different tree species suggest marked changes in species composition and diversity of these forests by nutrient inputs in the long term. The unexpectedly fast response of the ecosystem to moderate nutrient additions suggests high vulnerability of tropical montane forests to the expected increase in nutrient inputs. PMID:23071734

Multiscale assessment of water limitations on forest carbon cycling in the western United States

NASA Astrophysics Data System (ADS)

Berner, L. T.; Law, B. E.

2016-12-01

Water is a key environmental constraint on carbon uptake, storage, and release by forests in the western United States. Climate in this region is becoming warmer and drier, thus highlighting the need to better understand how forest carbon cycling responds to variation in water availability. Here, we describe how forest carbon cycling varied spatially along local to regional gradients in climatic water availability. We examined local variation in net primary productivity (NPP) and aboveground biomass (AGB) using 12 intensive field plots in Oregon's Cascade Mountains. Regional analysis of forest NPP and AGB was based on federal forest inventories (>8,000 plots) in Washington, Oregon, and California, multiple biomass maps and MODIS NPP (2003-2012). We also quantified annual forest AGB mortality due to bark beetles and fires across the region from 2003-2012 by combining several disturbance and biomass data sets. Over each spatial extent, forest NPP and AGB increased curvilinearly with average growing-year climate moisture index, computed as the cumulative difference between precipitation and potential evapotranspiration from October-September and averaged over preceding decades. Thus, climatic water availability strongly constrains forest carbon uptake and storage, particularly in the driest areas, but also in the wettest. Forest AGB mortality rates from bark beetles and fires peaked in moderately dry forests and then declining rapidly in the wettest areas. Annual forest AGB mortality from bark beetles was about twice as high as from fires. Bark beetle impacts were most pronounced in the Rock Mountains, while fire impacts were most pronounced in western portion of the region. Our multiscale analysis based on field inventory and remote sensing data sets demonstrates that climatic water availability is a key environmental constraint on forest carbon cycling in the western US. Consequently, continued warming and drying can be expected to have substantial impacts on forest carbon cycling in this region over the coming century.

Forest carbon in lowland Papua New Guinea: Local variation and the importance of small trees

PubMed Central

Vincent, John B; Henning, Bridget; Saulei, Simon; Sosanika, Gibson; Weiblen, George D

2015-01-01

Efforts to incentivize the reduction of carbon emissions from deforestation and forest degradation require accurate carbon accounting. The extensive tropical forest of Papua New Guinea (PNG) is a target for such efforts and yet local carbon estimates are few. Previous estimates, based on models of neotropical vegetation applied to PNG forest plots, did not consider such factors as the unique species composition of New Guinea vegetation, local variation in forest biomass, or the contribution of small trees. We analysed all trees >1 cm in diameter at breast height (DBH) in Melanesia's largest forest plot (Wanang) to assess local spatial variation and the role of small trees in carbon storage. Above-ground living biomass (AGLB) of trees averaged 210.72 Mg  ha−1 at Wanang. Carbon storage at Wanang was somewhat lower than in other lowland tropical forests, whereas local variation among 1-ha subplots and the contribution of small trees to total AGLB were substantially higher. We speculate that these differences may be attributed to the dynamics of Wanang forest where erosion of a recently uplifted and unstable terrain appears to be a major source of natural disturbance. These findings emphasize the need for locally calibrated forest carbon estimates if accurate landscape level valuation and monetization of carbon is to be achieved. Such estimates aim to situate PNG forests in the global carbon context and provide baseline information needed to improve the accuracy of PNG carbon monitoring schemes. PMID:26074730

Carbon storage in old-growth forests of the Mid-Atlantic: toward better understanding the eastern forest carbon sink.

PubMed

McGarvey, Jennifer C; Thompson, Jonathan R; Epstein, Howard E; Shugart, Herman H

2015-02-01

Few old-growth stands remain in the matrix of secondary forests that dominates the eastern North American landscape. These remnant stands offer insight on the potential carbon (C) storage capacity of now-recovering secondary forests. We surveyed the remaining old-growth forests on sites characteristic of the general Mid-Atlantic United States and estimated the size of multiple components of forest C storage. Within and between old-growth stands, variability in C density is high and related to overstory tree species composition. The sites contain 219 ± 46 Mg C/ha (mean ± SD), including live and dead aboveground biomass, leaf litter, and the soil O horizon, with over 20% stored in downed wood and snags. Stands dominated by tulip poplar (Liriodendron tulipifera) store the most live biomass, while the mixed oak (Quercus spp.) stands overall store more dead wood. Total C density is 30% higher (154 Mg C/ha), and dead wood C density is 1800% higher (46 Mg C/ha) in the old-growth forests than in the surrounding younger forests (120 and 5 Mg C/ha, respectively). The high density of dead wood in old growth relative to secondary forests reflects a stark difference in historical land use and, possibly, the legacy of the local disturbance (e.g., disease) history. Our results demonstrate the potential for dead wood to maintain the sink capacity of secondary forests for many decades to come.

Rapid forest recovery of carbon and water fluxes after a tropical firestorm

NASA Astrophysics Data System (ADS)

Brando, P. M.; Silverio, D. V.; Migliavacca, M.; Santos, C.; Kolle, O.; Balch, J.; Maracahipes, L.; Bustamante, M.; Coe, M. T.; Trumbore, S.

2017-12-01

Forest disturbances interact synergistically and drive potentially large and persistent degradation of ecosystem services in the tropics. Here we analyze multi-year measurements of carbon (C) and water (evapotranspiration; ET) fluxes in forests recovering from 7 years of prescribed fires. Located in southeast Amazonia, the experimental forest consisted of three 50-ha plots burned annually, triennially, or not at all between 2004-2010. During the subsequent seven-year recovery period from 2011 to present, tree survivorship and biomass sharply declined, with aboveground C stocks decreasing by 70-94% along forest edges. While vegetation regrowth in the forest understory triggered partial canopy closure, light-demanding grasses covered roughly the same area in 2015 that they did in 2012. However, the spatial distribution of grasses drastically changed, while C4 grass species replaced C3 ones. Surprisingly, the observed alterations in forest structure and dynamics rendered minor or no changes in total C fluxes and ET, probably because plants in the burned forest increased light- and reduced ecosystem water-use efficiency. Hence, delayed post-fire mortality of large trees can reduce forest C stocks and create opportunities for the establishment of invasive grasses, Yet, post-fire vegetation growth can rapidly restore C uptake and ET by optimizing resources use. These results show that tropical forests can rapidly recover the capacity to cycle water and carbon following disturbances, but also that a full recovery of biomass and vegetation dominance may take many years or decades.

Family Differences Influence the Aboveground Biomass of Loblolly Pine Plantations

Treesearch

P.E. Pope; D.L. Graney

1979-01-01

We compared the aboveground biomass of 4 half-sib families of loblolly pine (Pinus taeda L.) 11 years after planting. Total dry weights differed significantly among families in plantations on the same soil type with the same site index. Differences in biomass resulted from differences in stem form and branch size. Distribution of growth -the proportion of tree weight...

Methods for estimating aboveground biomass and its components for five Pacific Northwest tree species

Treesearch

Krishna P. Poudel; Temesgen. Hailemariam

2015-01-01

Performance of three groups of methods to estimate total and/or component aboveground biomass was evaluated using the data collected from destructively sampled trees in different parts of Oregon. First group of methods used analytical approach to estimate total and component biomass using existing equations, and produced biased estimates for our dataset. The second...

Role of tree size in moist tropical forest carbon cycling and water deficit responses.

PubMed

Meakem, Victoria; Tepley, Alan J; Gonzalez-Akre, Erika B; Herrmann, Valentine; Muller-Landau, Helene C; Wright, S Joseph; Hubbell, Stephen P; Condit, Richard; Anderson-Teixeira, Kristina J

2017-06-06

Drought disproportionately affects larger trees in tropical forests, but implications for forest composition and carbon (C) cycling in relation to dry season intensity remain poorly understood. In order to characterize how C cycling is shaped by tree size and drought adaptations and how these patterns relate to spatial and temporal variation in water deficit, we analyze data from three forest dynamics plots spanning a moisture gradient in Panama that have experienced El Niño droughts. At all sites, aboveground C cycle contributions peaked below 50-cm stem diameter, with stems ≥ 50 cm accounting for on average 59% of live aboveground biomass, 45% of woody productivity and 49% of woody mortality. The dominance of drought-avoidance strategies increased interactively with stem diameter and dry season intensity. Although size-related C cycle contributions did not vary systematically across the moisture gradient under nondrought conditions, woody mortality of larger trees was disproportionately elevated under El Niño drought stress. Thus, large (> 50 cm) stems, which strongly mediate but do not necessarily dominate C cycling, have drought adaptations that compensate for their more challenging hydraulic environment, particularly in drier climates. However, these adaptations do not fully buffer the effects of severe drought, and increased large tree mortality dominates ecosystem-level drought responses. © 2017 Smithsonian. Institute New Phytologist © 2017 New Phytologist Trust.

Lidar and Hyperspectral Remote Sensing for the Analysis of Coniferous Biomass Stocks and Fluxes

NASA Astrophysics Data System (ADS)

Halligan, K. Q.; Roberts, D. A.

2006-12-01

Airborne lidar and hyperspectral data can improve estimates of aboveground carbon stocks and fluxes through their complimentary responses to vegetation structure and biochemistry. While strong relationships have been demonstrated between lidar-estimated vegetation structural parameters and field data, research is needed to explore the portability of these methods across a range of topographic conditions, disturbance histories, vegetation type and climate. Additionally, research is needed to evaluate contributions of hyperspectral data in refining biomass estimates and determination of fluxes. To address these questions we are a conducting study of lidar and hyperspectral remote sensing data across sites including coniferous forests, broadleaf deciduous forests and a tropical rainforest. Here we focus on a single study site, Yellowstone National Park, where tree heights, stem locations, above ground biomass and basal area were mapped using first-return small-footprint lidar data. A new method using lidar intensity data was developed for separating the terrain and vegetation components in lidar data using a two-scale iterative local minima filter. Resulting Digital Terrain Models (DTM) and Digital Canopy Models (DCM) were then processed to retrieve a diversity of vertical and horizontal structure metrics. Univariate linear models were used to estimate individual tree heights while stepwise linear regression was used to estimate aboveground biomass and basal area. Three small-area field datasets were compared for their utility in model building and validation of vegetation structure parameters. All structural parameters were linearly correlated with lidar-derived metrics, with higher accuracies obtained where field and imagery data were precisely collocated . Initial analysis of hyperspectral data suggests that vegetation health metrics including measures of live and dead vegetation and stress indices may provide good indicators of carbon flux by mapping vegetation vigor or senescence. Additionally, the strength of hyperspectral data for vegetation classification suggests these data have additional utility for modeling carbon flux dynamics by allowing more accurate plant functional type mapping.

Improving artificial forest biomass estimates using afforestation age information from time series Landsat stacks.

PubMed

Liu, Liangyun; Peng, Dailiang; Wang, Zhihui; Hu, Yong

2014-11-01

China maintains the largest artificial forest area in the world. Studying the dynamic variation of forest biomass and carbon stock is important to the sustainable use of forest resources and understanding of the artificial forest carbon budget in China. In this study, we investigated the potential of Landsat time series stacks for aboveground biomass (AGB) estimation in Yulin District, a key region of the Three-North Shelter region of China. Firstly, the afforestation age was successfully retrieved from the Landsat time series stacks in the last 40 years (from 1974 to 2013) and shown to be consistent with the surveyed tree ages, with a root-mean-square error (RMSE) value of 4.32 years and a determination coefficient (R (2)) of 0.824. Then, the AGB regression models were successfully developed by integrating vegetation indices and tree age. The simple ratio vegetation index (SR) is the best candidate of the commonly used vegetation indices for estimating forest AGB, and the forest AGB model was significantly improved using the combination of SR and tree age, with R (2) values from 0.50 to 0.727. Finally, the forest AGB images were mapped at eight epochs from 1985 to 2013 using SR and afforestation age. The total forest AGB in seven counties of Yulin District increased by 20.8 G kg, from 5.8 G kg in 1986 to 26.6 G kg in 2013, a total increase of 360 %. For the persistent forest area since 1974, the forest AGB density increased from 15.72 t/ha in 1986 to 44.53 t/ha in 2013, with an annual rate of about 0.98 t/ha. For the artificial forest planted after 1974, the AGB density increased about 1.03 t/ha a year from 1974 to 2013. The results present a noticeable carbon increment for the planted artificial forest in Yulin District over the last four decades.

Rising Mean Annual Temperature Increases Carbon Flux and Alters Partitioning, but Does Not Change Ecosystem Carbon Storage in Hawaiian Tropical Montane Wet Forest

NASA Astrophysics Data System (ADS)

Litton, C. M.; Giardina, C. P.; Selmants, P.

2014-12-01

Terrestrial ecosystem carbon (C) storage exceeds that in the atmosphere by a factor of four, and represents a dynamic balance among C input, allocation, and loss. This balance is likely being altered by climate change, but the response of terrestrial C cycling to warming remains poorly quantified, particularly in tropical forests which play a disproportionately large role in the global C cycle. Over the past five years, we have quantified above- and belowground C pools and fluxes in nine permanent plots spanning a 5.2°C mean annual temperature (MAT) gradient (13-18.2°C) in Hawaiian tropical montane wet forest. This elevation gradient is unique in that substrate type and age, soil type, soil water balance, canopy vegetation, and disturbance history are constant, allowing us to isolate the impact of long-term, whole ecosystem warming on C input, allocation, loss and storage. Across the gradient, soil respiration, litterfall, litter decomposition, total belowground C flux, aboveground net primary productivity, and estimates of gross primary production (GPP) all increase linearly and positively with MAT. Carbon partitioning is dynamic, shifting from below- to aboveground with warming, likely in response to a warming-induced increase in the cycling and availability of soil nutrients. In contrast to observed patterns in C flux, live biomass C, soil C, and total ecosystem C pools remained remarkably constant with MAT. There was also no difference in soil bacterial taxon richness, phylogenetic diversity, or community composition with MAT. Taken together these results indicate that in tropical montane wet forests, increased temperatures in the absence of water limitation or disturbance will accelerate C cycling, will not alter ecosystem C storage, and will shift the products of photosynthesis from below- to aboveground. These results agree with an increasing number of studies, and collectively provide a unique insight into anticipated warming-induced changes in tropical forest C cycling.

Effects of field plot size on prediction accuracy of aboveground biomass in airborne laser scanning-assisted inventories in tropical rain forests of Tanzania.

PubMed

Mauya, Ernest William; Hansen, Endre Hofstad; Gobakken, Terje; Bollandsås, Ole Martin; Malimbwi, Rogers Ernest; Næsset, Erik

2015-12-01

Airborne laser scanning (ALS) has recently emerged as a promising tool to acquire auxiliary information for improving aboveground biomass (AGB) estimation in sample-based forest inventories. Under design-based and model-assisted inferential frameworks, the estimation relies on a model that relates the auxiliary ALS metrics to AGB estimated on ground plots. The size of the field plots has been identified as one source of model uncertainty because of the so-called boundary effects which increases with decreasing plot size. Recent research in tropical forests has aimed to quantify the boundary effects on model prediction accuracy, but evidence of the consequences for the final AGB estimates is lacking. In this study we analyzed the effect of field plot size on model prediction accuracy and its implication when used in a model-assisted inferential framework. The results showed that the prediction accuracy of the model improved as the plot size increased. The adjusted R 2 increased from 0.35 to 0.74 while the relative root mean square error decreased from 63.6 to 29.2%. Indicators of boundary effects were identified and confirmed to have significant effects on the model residuals. Variance estimates of model-assisted mean AGB relative to corresponding variance estimates of pure field-based AGB, decreased with increasing plot size in the range from 200 to 3000 m 2 . The variance ratio of field-based estimates relative to model-assisted variance ranged from 1.7 to 7.7. This study showed that the relative improvement in precision of AGB estimation when increasing field-plot size, was greater for an ALS-assisted inventory compared to that of a pure field-based inventory.

Effects of precipitation changes on switchgrass photosynthesis, growth, and biomass: A mesocosm experiment.

PubMed

Hui, Dafeng; Yu, Chih-Li; Deng, Qi; Dzantor, E Kudjo; Zhou, Suping; Dennis, Sam; Sauve, Roger; Johnson, Terrance L; Fay, Philip A; Shen, Weijun; Luo, Yiqi

2018-01-01

Climate changes, including chronic changes in precipitation amounts, will influence plant physiology and growth. However, such precipitation effects on switchgrass, a major bioenergy crop, have not been well investigated. We conducted a two-year precipitation simulation experiment using large pots (95 L) in an environmentally controlled greenhouse in Nashville, TN. Five precipitation treatments (ambient precipitation, and -50%, -33%, +33%, and +50% of ambient) were applied in a randomized complete block design with lowland "Alamo" switchgrass plants one year after they were established from tillers. The growing season progression of leaf physiology, tiller number, height, and aboveground biomass were determined each growing season. Precipitation treatments significantly affected leaf physiology, growth, and aboveground biomass. The photosynthetic rates in the wet (+50% and +33%) treatments were significantly enhanced by 15.9% and 8.1%, respectively, than the ambient treatment. Both leaf biomass and plant height were largely increased, resulting in dramatically increases in aboveground biomass by 56.5% and 49.6% in the +50% and +33% treatments, respectively. Compared to the ambient treatment, the drought (-33% and -50%) treatments did not influence leaf physiology, but the -50% treatment significantly reduced leaf biomass by 37.8%, plant height by 16.3%, and aboveground biomass by 38.9%. This study demonstrated that while switchgrass in general is a drought tolerant grass, severe drought significantly reduces Alamo's growth and biomass, and that high precipitation stimulates its photosynthesis and growth.