scholarly journals Remote sensing of net ecosystem productivity based on component spectrum and soil respiration observation in a boreal forest, interior Alaska

2004 ◽  
Vol 109 (D6) ◽  
pp. n/a-n/a ◽  
Author(s):  
Keiji Kushida ◽  
Yongwon Kim ◽  
Noriyuki Tanaka ◽  
Masami Fukuda
Keyword(s):  
Remote Sensing ◽  
Soil Respiration ◽  
Boreal Forest ◽  
Net Ecosystem Productivity ◽  
Ecosystem Productivity ◽  
Interior Alaska ◽  
Forest Interior ◽  
Component Spectrum

scholarly journals High-resolution forest carbon flux mapping and monitoring in the Pacific Northwest with time since disturbance and disturbance legacies inferred from remote sensing and inventory data

2016 ◽  
Author(s):  
Huan Gu ◽  
Christopher A. Williams ◽  
Bardan Ghimire ◽  
Feng Zhao ◽  
Chengquan Huang
Keyword(s):  
Remote Sensing ◽  
Pacific Northwest ◽  
Forest Inventory ◽  
Stand Age ◽  
Net Ecosystem Productivity ◽  
Fine Scale ◽  
Ecosystem Productivity ◽  
Inventory Data ◽  
Forest Inventory Data ◽  
The Pacific

Abstract. Assessment of forest carbon storage and uptake is central to understanding the role forests play in the global carbon cycle and policy-making aimed at mitigating climate change. Current U.S. carbon stocks and fluxes are monitored and reported at fine-scale regionally, or coarse-scale nationally. We proposed a new methodology of quantifying carbon uptake and release across forested landscapes in the Pacific Northwest (PNW) at a fine scale (30 m) by combining remote-sensing based disturbance year, disturbance type, and aboveground biomass with forest inventory data in a carbon modelling framework. Time since disturbance is a key intermediate determinant that aided the assessment of disturbance-driven carbon emissions and removals legacies. When a recent disturbance was detected, time since disturbance can be directly determined by remote sensing-derived disturbance products; and if not, time since last stand-clearing was inferred from remote sensing-derived 30 m biomass map and field inventory-derived species-specific biomass regrowth curves. Net ecosystem productivity (NEP) was further mapped based on carbon stock and flux trajectories that described how NEP changes with time following harvest, fire, or bark beetle disturbances of varying severity. Uncertainties from biomass map and forest inventory data were propagated by probabilistic sampling to provide a probabilistic, statistical distribution of stand age and NEP for each forest pixel. We mapped mean, standard deviation and statistical distribution of stand age and NEP at 30 m in the PNW region. Our map indicated a net ecosystem productivity of 5.2 Tg C y−1 for forestlands circa 2010 in the study area, with net uptake in relatively mature (> 24 year old) forests (13.6 Tg C y−1) overwhelming net negative NEP from tracts that have seen recent harvest (−6.4 Tg C y−1), fires (−0.5 Tg C y−1), and bark beetle outbreaks (−1.4 Tg C y−1). The approach will be applied to forestlands in other regions of the conterminous U.S. to advance a more comprehensive monitoring, mapping and reporting the carbon consequences of forest change across the U.S.

scholarly journals Soil respiration and net ecosystem productivity in a chronosequence of hybrid poplar plantations

2020 ◽  
Vol 100 (4) ◽  
pp. 488-502
Author(s):  
Scott X. Chang ◽  
Zheng Shi ◽  
Barb R. Thomas
Keyword(s):  
Soil Respiration ◽  
Soil Temperature ◽  
Populus Deltoides ◽  
Hybrid Poplar ◽  
Stand Age ◽  
Net Ecosystem Productivity ◽  
Ecosystem Productivity ◽  
Short Rotation ◽  
C Dynamics ◽  
Woody Crop

Forest stand age can affect ecosystem carbon (C) cycling and net ecosystem productivity (NEP). In Canada, establishment of short-rotation plantations on previously agricultural lands has been ongoing, but the effect of stand development on soil respiration (Rs) and NEP in such plantations is poorly understood. These types of data are essential for constraining ecosystem models that simulate C dynamics over the rotation of a plantation. We studied Rs (including autotrophic, Ra, and heterotrophic, Rh) and NEP in 2008 and 2009 in a chronosequence of 5-, 8-, 14-, and 16-yr-old (ages in 2009) hybrid poplar (Populus deltoides × Populus × petrowskyana var. Walker) plantations in northern Alberta. The highest Rs and NEP were generally found in the 14-yr-old stand. Seasonal variations in Rs were similar among the plantations, with most of the variation explained by soil temperature at the 10 cm depth in 2008 with far less explained in 2009, a much drier year. In diurnal measurements, hysteresis was found between soil respiration and soil temperature, with the patterns of hysteresis different among stand ages. Soil respiration in the 14-yr-old plantation had the greatest sensitivity to temperature changes. Stand age did not affect the Rh:Rs ratio, whereas the NEP exhibited strong inter-annual variability. We conclude that stand age was a major factor affecting Rs and NEP, and such effects should be considered in empirical models used to simulate ecosystem C dynamics to evaluate potentials for C sequestration and the C source–sink relationship in short-rotation woody crop systems.

The relative importance of environmental factors on the interannual variability of carbon fluxes in the boreal forest

2020 ◽  
Author(s):  
Mariam El-Amine ◽  
Alexandre Roy ◽  
Pierre Legendre ◽  
Oliver Sonnentag
Keyword(s):  
Environmental Factors ◽  
Boreal Forest ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Carbon Sink ◽  
Growing Season ◽  
Carbon Uptake ◽  
Net Ecosystem Productivity ◽  
Ecosystem Productivity ◽  
Environmental Controls

<p>As climate change will cause a more pronounced rise of air temperature in northern high latitudes than in other parts of the world, it is expected that the strength of the boreal forest carbon sink will be altered. To better understand and quantify these changes, we studied the influence of different environmental controls (e.g., air and soil temperatures, soil water content, photosynthetically active radiation, normalized difference vegetation index) on the timing of the start and end of the boreal forest growing season and the net carbon uptake period in Canada. The influence of these factors on the growing season carbon exchanges between the atmosphere and the boreal forest were also evaluated. There is a need to improve the understanding of the role of the length of the growing season and the net carbon uptake period on the strength of the boreal forest carbon sink, as an extension of these periods might not necessarily result in a stronger carbon sink if other environmental factors are not optimal for carbon sequestration or enhance respiration.</p><p>Here, we used 31 site-years of observation over three Canadian boreal forest stands: Eastern, Northern and Southern Old Black Spruce in Québec, Manitoba and Saskatchewan, respectively. Redundancy analyses were used to highlight the environmental controls that correlate the most with the annual net ecosystem productivity and the start and end of the growing season and the net carbon uptake period. Preliminary results show that the timing at which the air temperature becomes positive correlates the most strongly with the start of the net carbon uptake period (r = 0.70, p < 0.001) and the start of the growing season (r = 0.55, p < 0.01). Although the increase of the normalized difference vegetation index also correlates with the start of these periods, a thorough examination of this result shows that the latter happens well before the former. No dependency between any environmental control and the end of the net carbon uptake period was identified. Also, the annual net ecosystem productivity is highly correlated with the length of the net carbon uptake period (r = 0.54, p < 0.01). Other environmental controls such as annual precipitations, the mean annual soil temperature or the maximum yearly normalized difference vegetation index have a smaller impact on the annual net ecosystem productivity. By extending the dataset to include forest stands that represent a wider climate and permafrost variability, we will examine the generalizability of these results.</p>

scholarly journals Response of Net Ecosystem Productivity of Three Boreal Forest Stands to Drought

Ecosystems ◽  
2007 ◽  
Vol 10 (6) ◽  
pp. 1039-1055 ◽  
Author(s):  
N. Kljun ◽  
T. A. Black ◽  
T. J. Griffis ◽  
A. G. Barr ◽  
D. Gaumont-Guay ◽  
...  
Keyword(s):  
Boreal Forest ◽  
Net Ecosystem Productivity ◽  
Ecosystem Productivity ◽  
Forest Stands

scholarly journals Response of Net Ecosystem Productivity of Three Boreal Forest Stands to Drought

Ecosystems ◽  
2006 ◽  
Vol 9 (7) ◽  
pp. 1128-1144 ◽  
Author(s):  
N. Kljun ◽  
T. A. Black ◽  
T. J. Griffis ◽  
A. G. Barr ◽  
D. Gaumont-Guay ◽  
...  
Keyword(s):  
Boreal Forest ◽  
Net Ecosystem Productivity ◽  
Ecosystem Productivity ◽  
Forest Stands

scholarly journals Assessing Wildfire Burn Severity and Its Relationship with Environmental Factors: A Case Study in Interior Alaska Boreal Forest

2021 ◽  
Vol 13 (10) ◽  
pp. 1966
Author(s):  
Christopher W Smith ◽  
Santosh K Panda ◽  
Uma S Bhatt ◽  
Franz J Meyer ◽  
Anushree Badola ◽  
...  
Keyword(s):  
Boreal Forest ◽  
Ground Truth ◽  
Burn Severity ◽  
Classification Methods ◽  
Spectral Indices ◽  
Ground Truth Data ◽  
Burn Scar ◽  
Interior Alaska ◽  
Remote Sensing Methods ◽  
The Relationship

In recent years, there have been rapid improvements in both remote sensing methods and satellite image availability that have the potential to massively improve burn severity assessments of the Alaskan boreal forest. In this study, we utilized recent pre- and post-fire Sentinel-2 satellite imagery of the 2019 Nugget Creek and Shovel Creek burn scars located in Interior Alaska to both assess burn severity across the burn scars and test the effectiveness of several remote sensing methods for generating accurate map products: Normalized Difference Vegetation Index (NDVI), Normalized Burn Ratio (NBR), and Random Forest (RF) and Support Vector Machine (SVM) supervised classification. We used 52 Composite Burn Index (CBI) plots from the Shovel Creek burn scar and 28 from the Nugget Creek burn scar for training classifiers and product validation. For the Shovel Creek burn scar, the RF and SVM machine learning (ML) classification methods outperformed the traditional spectral indices that use linear regression to separate burn severity classes (RF and SVM accuracy, 83.33%, versus NBR accuracy, 73.08%). However, for the Nugget Creek burn scar, the NDVI product (accuracy: 96%) outperformed the other indices and ML classifiers. In this study, we demonstrated that when sufficient ground truth data is available, the ML classifiers can be very effective for reliable mapping of burn severity in the Alaskan boreal forest. Since the performance of ML classifiers are dependent on the quantity of ground truth data, when sufficient ground truth data is available, the ML classification methods would be better at assessing burn severity, whereas with limited ground truth data the traditional spectral indices would be better suited. We also looked at the relationship between burn severity, fuel type, and topography (aspect and slope) and found that the relationship is site-dependent.

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