scholarly journals Radial variations in wood density, and their implications for above-ground biomass estimations, in a tropical high-andean forest

Dendrobiology ◽  
2021 ◽  
Vol 86 ◽  
pp. 19-29
Author(s):  
Andrés González-Melo
Keyword(s):  
Wood Density ◽  
Forest Biomass ◽  
Canopy Openness ◽  
High Mountain ◽  
Above Ground Biomass ◽  
Ground Biomass ◽  
Open Canopy ◽  
Closed Canopy ◽  
Allocation Patterns ◽  
Study Species

Wood density (WD) is a central trait to explain tree functioning, and is also an important predic­tor of tree above-ground biomass (AGB). Therefore, radial trends in WD (i.e., from pith to bark) may have important implications in understanding tree life-history variations, as well as in forest biomass and carbon estimations. The occurrence of these radial trends in WD is thought to vary among forests, particularly with canopy openness and stratification. Yet, most of the studies on this topic in tropical forests have been conducted on lowland closed-canopy forests, while very little is known about the prevalence and magnitude of these trends among trees from open-canopy forests, such as high-mountain forests. I examined radial gradients in WD and explored their implications for AGB estimations. Radial wood cores were taken with increment borers from 69 trees belonging to 18 species from a high-An­dean forest. Each wood core was cut every 1-cm, and WD was measured for every 1-cm segment. Errors in AGB estimations that resulted from not considering radial trends in WD were estimated for each tree and species. Eight out of eighteen species had significant radial trends in WD. Among these species, two species showed decreases of WD towards the bark, one species showed increments of WD from pith to bark, and five species showed U-shaped gradients (i.e., high WD near the pith and bark, and relatively low WD at inter­mediate diameters). The prevalence of U-shaped radial trends in WD may be related to the relatively open and less stratified canopy of the study forest. Not taking into account radial trends in WD led in general to under-estimations of AGB (averaging −7.66 % when using mean WD, and −5.56 % for outer WD) in most of the study species, suggesting that tropical high-Andean forests may possibly store more biomass carbon than has been previously estimated. These findings are important to expand our knowledge on wood allocation patterns during tree ontogeny, and also to improve the accuracy of biomass and carbon estimations in tropical high-Andean forests.

scholarly journals Comparison of Capability of SAR and Optical Data in Mapping Forest above Ground Biomass Based on Machine Learning

2020 ◽  
Vol 5 (1) ◽  
pp. 13
Author(s):  
Negar Tavasoli ◽  
Hossein Arefi
Keyword(s):  
Machine Learning ◽  
Carbon Stock ◽  
Vegetation Indices ◽  
Forest Biomass ◽  
Principal Component ◽  
Optical Data ◽  
Above Ground Biomass ◽  
Ground Biomass ◽  
Texture Characteristics ◽  
Sentinel 2

Assessment of forest above ground biomass (AGB) is critical for managing forest and understanding the role of forest as source of carbon fluxes. Recently, satellite remote sensing products offer the chance to map forest biomass and carbon stock. The present study focuses on comparing the potential use of combination of ALOSPALSAR and Sentinel-1 SAR data, with Sentinel-2 optical data to estimate above ground biomass and carbon stock using Genetic-Random forest machine learning (GA-RF) algorithm. Polarimetric decompositions, texture characteristics and backscatter coefficients of ALOSPALSAR and Sentinel-1, and vegetation indices, tasseled cap, texture parameters and principal component analysis (PCA) of Sentinel-2 based on measured AGB samples were used to estimate biomass. The overall coefficient (R2) of AGB modelling using combination of ALOSPALSAR and Sentinel-1 data, and Sentinel-2 data were respectively 0.70 and 0.62. The result showed that Combining ALOSPALSAR and Sentinel-1 data to predict AGB by using GA-RF model performed better than Sentinel-2 data.

scholarly journals Estimation of Above-Ground Biomass over Boreal Forests on Siberia Using Updated In Situ, ALOS-2 PALSAR-2, and RADARSAT-2 Data

2018 ◽  
Vol 10 (10) ◽  
pp. 1550 ◽  
Author(s):  
Martyna Stelmaszczuk-Górska ◽  
Mikhail Urbazaev ◽  
Christiane Schmullius ◽  
Christian Thiel
Keyword(s):  
Boreal Forests ◽  
Learning Algorithm ◽  
Forest Biomass ◽  
Radar Data ◽  
Accurate Estimate ◽  
Above Ground Biomass ◽  
Ground Biomass ◽  
Multi Temporal ◽  
L Band

The estimation of above-ground biomass (AGB) in boreal forests is of special concern as it constitutes the highest carbon pool in the northern hemisphere. In particularly, monitoring of the forests in the Russian Federation is important as some regions have not been inventoried for many years. This study explores the combination of multi-frequency, multi-polarization, and multi-temporal radar data as one key approach to provide an accurate estimate of forest biomass. The data from L-band Advanced Land Observing Satellite 2 (ALOS-2) Phased Array L-Band Synthetic Aperture Radar 2 (PALSAR-2), together with C-band RADARSAT-2 data, were applied for AGB estimation. Backscatter coefficients from L- and C-band radar were used independently and in combination with a non-parametric model to retrieve AGB data for a boreal forest in Siberia (Krasnoyarskiy Kray). AGB estimation was performed using the random forests machine learning algorithm. The results demonstrated that high estimation accuracies can be achieved at a spatial resolution of 0.25 ha. When the L-band data alone were used for the retrieval, a corrected root-mean-square error (RMSEcor) of 29.4 t ha−1 was calculated. A marginal decrease in RMSEcor was observed when only the filtered L-band backscatter data, without ratio and texture, were used (29.1 t ha−1). The inclusion of the C-band data reduced the over and underestimation; the bias was reduced from 5.5 t ha−1 to 4.7 t ha−1; and a RMSEcor of 30.2 t ha−1 was calculated.

scholarly journals Above-ground biomass and structure of 260 African tropical forests

2013 ◽  
Vol 368 (1625) ◽  
pp. 20120295 ◽  
Author(s):  
Simon L. Lewis ◽  
Bonaventure Sonké ◽  
Terry Sunderland ◽  
Serge K. Begne ◽  
Gabriela Lopez-Gonzalez ◽  
...  
Keyword(s):  
Tropical Forests ◽  
Positive Relationship ◽  
Mass Density ◽  
Negative Relationship ◽  
Congo Basin ◽  
Stem Density ◽  
Above Ground Biomass ◽  
African Countries ◽  
Ground Biomass ◽  
Closed Canopy

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.

scholarly journals Recent above-ground biomass changes in central Chukotka (Russian Far East) using field sampling and Landsat satellite data

2020 ◽  
Author(s):  
Iuliia Shevtsova ◽  
Ulrike Herzschuh ◽  
Birgit Heim ◽  
Luise Schulte ◽  
Simone Stünzi ◽  
...  
Keyword(s):  
Land Cover ◽  
Plant Biomass ◽  
Russian Far East ◽  
Far East ◽  
Additive Model ◽  
Northern Taiga ◽  
Above Ground Biomass ◽  
Study Region ◽  
Ground Biomass ◽  
Closed Canopy

Abstract. Upscaling plant biomass distribution and dynamics is essential for estimating carbon stocks and carbon balance. In this respect, the Russian Far East is among the least investigated subarctic regions despite its known vegetation sensitivity to ongoing warming. We representatively harvested above-ground biomass (AGB, separated by dominant taxa) at 40 sampling plots in central Chukotka. We used ordination to relate field-based taxa projective cover and Landsat-derived vegetation indices. A general additive model was used to link the ordination scores to AGB. We then mapped AGB for paired Landsat-derived time-slices (i.e. 2000/2001/2002 and 2016/2017), in four study regions covering a wide vegetation gradient from closed-canopy larch forests to barren alpine tundra. We provide AGB estimates and changes in AGB that were previously lacking for central Chukotka at a high spatial resolution and a detailed description of taxonomical contributions. Generally, AGB in the study region ranges from 0 to 16 kg m−2, with Cajander larch providing the highest contribution. Comparison of changes in AGB within the investigated period shows that the greatest changes (up to 1.25 kg m−2 yr−1) occurred in the northern taiga and in areas where land cover changed to larch closed-canopy forest. As well as the notable changes, increases in AGB also occur within the land cover classes. Our estimations indicate a general increase in total AGB throughout the investigated tundra-taiga and northern taiga, whereas the tundra showed no evidence of change in AGB.

Above-ground biomass and productivity in a rain forest of eastern South America

2008 ◽  
Vol 24 (4) ◽  
pp. 355-366 ◽  
Author(s):  
Jérôme Chave ◽  
Jean Olivier ◽  
Frans Bongers ◽  
Patrick Châtelet ◽  
Pierre-Michel Forget ◽  
...  
Keyword(s):  
Wood Density ◽  
Primary Productivity ◽  
Net Primary Productivity ◽  
Basal Area ◽  
Leaf Biomass ◽  
Stem Density ◽  
Above Ground Biomass ◽  
Field Station ◽  
Ground Biomass ◽  
The Mean

AbstractThe dynamics of tropical forest woody plants was studied at the Nouragues Field Station, central French Guiana. Stem density, basal area, above-ground biomass and above-ground net primary productivity, including the contribution of litterfall, were estimated from two large permanent census plots of 12 and 10 ha, established on contrasting soil types, and censused twice, first in 1992–1994, then again in 2000–2002. Mean stem density was 512 stems ha−1 and basal area, 30 m2 ha−1. Stem mortality rate ranged between 1.51% and 2.06% y−1. In both plots, stem density decreased over the study period. Using a correlation between wood density and wood hardness directly measured by a Pilodyn wood tester, we found that the mean wood density was 0.63 g cm−3, 12% smaller than the mean of wood density estimated from the literature values for the species occurring in our plot. Above-ground biomass ranged from 356 to 398 Mg ha−1 (oven-dry mass), and it increased over the census period. Leaf biomass was 6.47 Mg ha−1. Our total estimate of aboveground net primary productivity was 8.81 MgC ha−1 y−1 (in carbon units), not accounting for loss to herbivory, branchfalls, or biogenic volatile organic compounds, which may altogether account for an additional 1 MgC ha−1 y−1. Coarse wood productivity (stem growth plus recruitment) contributed to 4.16 MgC ha−1 y−1. Litterfall contributed to 4.65 MgC ha−1 y−1 with 3.16 MgC ha−1 y−1 due to leaves, 1.10 MgC ha−1 y−1 to twigs, and 0.39 MgC ha−1 y−1 to fruits and flowers. The increase in above-ground biomass for both trees and lianas is consistent with the hypothesis of a shift in the functioning of Amazonian rain forests driven by environmental changes, although alternative hypotheses such as a recovery from past disturbances cannot be ruled out at our site, as suggested by the observed decrease in stem density.

scholarly journals Recent above-ground biomass changes in central Chukotka (Russian Far East) using field sampling and Landsat satellite data

2021 ◽  
Vol 18 (11) ◽  
pp. 3343-3366
Author(s):  
Iuliia Shevtsova ◽  
Ulrike Herzschuh ◽  
Birgit Heim ◽  
Luise Schulte ◽  
Simone Stünzi ◽  
...  
Keyword(s):  
Land Cover ◽  
Plant Biomass ◽  
Russian Far East ◽  
Far East ◽  
Additive Model ◽  
Northern Taiga ◽  
Above Ground Biomass ◽  
Study Region ◽  
Ground Biomass ◽  
Closed Canopy

Abstract. Upscaling plant biomass distribution and dynamics is essential for estimating carbon stocks and carbon balance. In this respect, the Russian Far East is among the least investigated sub-Arctic regions despite its known vegetation sensitivity to ongoing warming. We representatively harvested above-ground biomass (AGB; separated by dominant taxa) at 40 sampling plots in central Chukotka. We used ordination to relate field-based taxa projective cover and Landsat-derived vegetation indices. A general additive model was used to link the ordination scores to AGB. We then mapped AGB for paired Landsat-derived time slices (i.e. 2000/2001/2002 and 2016/2017), in four study regions covering a wide vegetation gradient from closed-canopy larch forests to barren alpine tundra. We provide AGB estimates and changes in AGB that were previously lacking for central Chukotka at a high spatial resolution and a detailed description of taxonomical contributions. Generally, AGB in the study region ranges from 0 to 16 kg m−2, with Cajander larch providing the highest contribution. Comparison of changes in AGB within the investigated period shows that the greatest changes (up to 1.25 kg m−2 yr−1) occurred in the northern taiga and in areas where land cover changed to larch closed-canopy forest. As well as the notable changes, increases in AGB also occur within the land-cover classes. Our estimations indicate a general increase in total AGB throughout the investigated tundra–taiga and northern taiga, whereas the tundra showed no evidence of change in AGB.

ESTIMATION OF ABOVE GROUND BIOMASS OF THE THREE SITES (GRAZED SITE, PROTECTED SITE AND SEED SOWN SITE) FOR COMPARING THEIR PRODUCTIVITY IN KASHMIR VALLEY

2017 ◽  
Vol 23 (2) ◽  
Author(s):  
AFSHAN ANJUM BABA ◽  
SYED NASEEM UL-ZAFAR GEELANI ◽  
ISHRAT SALEEM ◽  
MOHIT HUSAIN ◽  
PERVEZ AHMAD KHAN ◽  
...  
Keyword(s):  
Protected Areas ◽  
Aboveground Biomass ◽  
Plant Biomass ◽  
Summer Season ◽  
Above Ground Biomass ◽  
Spring Season ◽  
Kashmir Valley ◽  
Ground Biomass ◽  
Maximum Value ◽  
Protected Site

The plant biomass for protected areas was maximum in summer (1221.56 g/m2) and minimum in winter (290.62 g/m2) as against grazed areas having maximum value 590.81 g/m2 in autumn and minimum 183.75 g/m2 in winter. Study revealed that at Protected site (Kanidajan) the above ground biomass ranged was from a minimum (1.11 t ha-1) in the spring season to a maximum (4.58 t ha-1) in the summer season while at Grazed site (Yousmarag), the aboveground biomass varied from a minimum (0.54 t ha-1) in the spring season to a maximum of 1.48 t ha-1 in summer seasonandat Seed sown site (Badipora), the lowest value of aboveground biomass obtained was 4.46 t ha-1 in spring while as the highest (7.98 t ha-1) was obtained in summer.

scholarly journals The climatic imprint of bimodal distributions in vegetation cover for western Africa

2016 ◽  
Vol 13 (11) ◽  
pp. 3343-3357 ◽  
Author(s):  
Zun Yin ◽  
Stefan C. Dekker ◽  
Bart J. J. M. van den Hurk ◽  
Henk A. Dijkstra
Keyword(s):  
Land Cover ◽  
Congo Basin ◽  
Shortwave Radiation ◽  
Mean Annual Precipitation ◽  
Above Ground Biomass ◽  
Precipitation Regime ◽  
Ground Biomass ◽  
Western Africa ◽  
Precipitation Regimes ◽  
Woody Cover

Abstract. Observed bimodal distributions of woody cover in western Africa provide evidence that alternative ecosystem states may exist under the same precipitation regimes. In this study, we show that bimodality can also be observed in mean annual shortwave radiation and above-ground biomass, which might closely relate to woody cover due to vegetation–climate interactions. Thus we expect that use of radiation and above-ground biomass enables us to distinguish the two modes of woody cover. However, through conditional histogram analysis, we find that the bimodality of woody cover still can exist under conditions of low mean annual shortwave radiation and low above-ground biomass. It suggests that this specific condition might play a key role in critical transitions between the two modes, while under other conditions no bimodality was found. Based on a land cover map in which anthropogenic land use was removed, six climatic indicators that represent water, energy, climate seasonality and water–radiation coupling are analysed to investigate the coexistence of these indicators with specific land cover types. From this analysis we find that the mean annual precipitation is not sufficient to predict potential land cover change. Indicators of climate seasonality are strongly related to the observed land cover type. However, these indicators cannot predict a stable forest state under the observed climatic conditions, in contrast to observed forest states. A new indicator (the normalized difference of precipitation) successfully expresses the stability of the precipitation regime and can improve the prediction accuracy of forest states. Next we evaluate land cover predictions based on different combinations of climatic indicators. Regions with high potential of land cover transitions are revealed. The results suggest that the tropical forest in the Congo basin may be unstable and shows the possibility of decreasing significantly. An increase in the area covered by savanna and grass is possible, which coincides with the observed regreening of the Sahara.

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