MODIS time-series-derived indicators for the beginning of the growing season in boreal coniferous forest — A comparison with CO2 flux measurements and phenological observations in Finland

2014 ◽  
Vol 140 ◽  
pp. 625-638 ◽  
Author(s):  
Kristin Böttcher ◽  
Mika Aurela ◽  
Mikko Kervinen ◽  
Tiina Markkanen ◽  
Olli-Pekka Mattila ◽  
...  
Keyword(s):  
Time Series ◽  
Coniferous Forest ◽  
Co2 Flux ◽  
Growing Season ◽  
Flux Measurements

The growing season carbon balance of a sub-boreal clearcut 5 years after harvesting using two independent approaches to measure ecosystem CO2 flux

2002 ◽  
Vol 32 (5) ◽  
pp. 852-862 ◽  
Author(s):  
Thomas G Pypker ◽  
Arthur L Fredeen
Keyword(s):  
Minor Component ◽  
Co2 Flux ◽  
Bowen Ratio ◽  
Growing Season ◽  
Component Model ◽  
Growing Period ◽  
Belowground Respiration ◽  
Flux Measurements ◽  
Main Components ◽  
A Minor

From 27 June to 3 September 1999, CO2 fluxes from a 5-year-old, 84.15-ha vegetated clearcut in sub-boreal British Columbia were measured using a Bowen ratio energy balance (BREB) system and a second approach (the component model) that was based on scaled up CO2-flux measurements from belowground and plants (spruce seedlings and representative deciduous species). Over the 69-day study period both methods estimated the site to be a small sink for CO2 (–22.4 and –85 g C·m–2, respectively). Differences between the sink size of the two approaches largely resulted from a divergence in the data after 7 August when the BREB data indicated a switch from sink to source approximately 14 days in advance of the same change from sink to source seen in the component model data. The main components of the CO2 flux within the clearcut were belowground respiration (338 g C·m–2) and deciduous plant photosynthesis (–375 g C·m–2). The conifer seedlings were only a minor component in overall CO2 flux over the growing season (–48 g C·m–2). The small overall sink estimated for the site for the approximately 2.5-month growing period would likely have been surmounted by the belowground respiration if the yearly CO2 fluxes had been taken into account. For example, an additional 68 g C·m–2 was added to the atmosphere from 3 to 23 September (based on belowground respiration data only), after deciduous plants senesced. This source alone was enough to push the site from a sink to a source for CO2.

scholarly journals Analogy-Based Crop Yield Forecasts Based on Temporal Similarity of Leaf Area Index

2021 ◽  
Vol 13 (16) ◽  
pp. 3069
Author(s):  
Yadong Liu ◽  
Junhwan Kim ◽  
David H. Fleisher ◽  
Kwang Soo Kim
Keyword(s):  
Time Series ◽  
Leaf Area Index ◽  
Leaf Area ◽  
Crop Yield ◽  
Satellite Data ◽  
Growing Season ◽  
Environmental Data ◽  
Area Index ◽  
Current Season ◽  
Wide Range

Seasonal forecasts of crop yield are important components for agricultural policy decisions and farmer planning. A wide range of input data are often needed to forecast crop yield in a region where sophisticated approaches such as machine learning and process-based models are used. This requires considerable effort for data preparation in addition to identifying data sources. Here, we propose a simpler approach called the Analogy Based Crop-yield (ABC) forecast scheme to make timely and accurate prediction of regional crop yield using a minimum set of inputs. In the ABC method, a growing season from a prior long-term period, e.g., 10 years, is first identified as analogous to the current season by the use of a similarity index based on the time series leaf area index (LAI) patterns. Crop yield in the given growing season is then forecasted using the weighted yield average reported in the analogous seasons for the area of interest. The ABC approach was used to predict corn and soybean yields in the Midwestern U.S. at the county level for the period of 2017–2019. The MOD15A2H, which is a satellite data product for LAI, was used to compile inputs. The mean absolute percentage error (MAPE) of crop yield forecasts was <10% for corn and soybean in each growing season when the time series of LAI from the day of year 89 to 209 was used as inputs to the ABC approach. The prediction error for the ABC approach was comparable to results from a deep neural network model that relied on soil and weather data as well as satellite data in a previous study. These results indicate that the ABC approach allowed for crop yield forecast with a lead-time of at least two months before harvest. In particular, the ABC scheme would be useful for regions where crop yield forecasts are limited by availability of reliable environmental data.

scholarly journals Modelling the productivity of Siberian larch forests from Landsat NDVI time series in fragmented forest stands of the Mongolian forest-steppe

2021 ◽  
Vol 193 (4) ◽  
Author(s):  
Stefan Erasmi ◽  
Michael Klinge ◽  
Choimaa Dulamsuren ◽  
Florian Schneider ◽  
Markus Hauck
Keyword(s):  
Climate Change ◽  
Time Series ◽  
Global Climate Change ◽  
Global Climate ◽  
Siberian Larch ◽  
Growing Season ◽  
Forest Productivity ◽  
Forest Steppe ◽  
Fragmented Forest ◽  
Southern Fringe

AbstractThe monitoring of the spatial and temporal dynamics of vegetation productivity is important in the context of carbon sequestration by terrestrial ecosystems from the atmosphere. The accessibility of the full archive of medium-resolution earth observation data for multiple decades dramatically improved the potential of remote sensing to support global climate change and terrestrial carbon cycle studies. We investigated a dense time series of multi-sensor Landsat Normalized Difference Vegetation Index (NDVI) data at the southern fringe of the boreal forests in the Mongolian forest-steppe with regard to the ability to capture the annual variability in radial stemwood increment and thus forest productivity. Forest productivity was assessed from dendrochronological series of Siberian larch (Larix sibirica) from 15 plots in forest patches of different ages and stand sizes. The results revealed a strong correlation between the maximum growing season NDVI of forest sites and tree ring width over an observation period of 20 years. This relationship was independent of the forest stand size and of the landscape’s forest-to-grassland ratio. We conclude from the consistent findings of our case study that the maximum growing season NDVI can be used for retrospective modelling of forest productivity over larger areas. The usefulness of grassland NDVI as a proxy for forest NDVI to monitor forest productivity in semi-arid areas could only partially be confirmed. Spatial and temporal inconsistencies between forest and grassland NDVI are a consequence of different physiological and ecological vegetation properties. Due to coarse spatial resolution of available satellite data, previous studies were not able to account for small-scaled land-cover patches like fragmented forest in the forest-steppe. Landsat satellite-time series were able to separate those effects and thus may contribute to a better understanding of the impact of global climate change on natural ecosystems.

The use of CO2 flux time series for parameter and carbon stock estimation in carbon cycle research

2011 ◽  
Vol 18 (1) ◽  
pp. 179-193 ◽  
Author(s):  
Timothy Charles Hill ◽  
Edmund Ryan ◽  
Mathew Williams
Keyword(s):  
Time Series ◽  
Carbon Cycle ◽  
Carbon Stock ◽  
Co2 Flux ◽  
Stock Estimation

Eddy covariance CO2 flux above a Gmelin larch forest on continuous permafrost in Central Siberia during a growing season

2008 ◽  
Vol 93 (3-4) ◽  
pp. 133-147 ◽  
Author(s):  
Y. Nakai ◽  
Y. Matsuura ◽  
T. Kajimoto ◽  
A. P. Abaimov ◽  
S. Yamamoto ◽  
...  
Keyword(s):  
Eddy Covariance ◽  
Co2 Flux ◽  
Growing Season ◽  
Larch Forest ◽  
Central Siberia ◽  
Continuous Permafrost

scholarly journals Ozone deposition into a boreal forest over a decade of observations: evaluating deposition partitioning and driving variables

2012 ◽  
Vol 12 (24) ◽  
pp. 12165-12182 ◽  
Author(s):  
Ü. Rannik ◽  
N. Altimir ◽  
I. Mammarella ◽  
J. Bäck ◽  
J. Rinne ◽  
...  
Keyword(s):  
Boreal Forest ◽  
Water Vapour ◽  
Environmental Variables ◽  
Total Ozone ◽  
Explanatory Power ◽  
Growing Season ◽  
Sink Strength ◽  
Ozone Deposition ◽  
Air Space ◽  
Flux Measurements

Abstract. This study scrutinizes a decade-long series of ozone deposition measurements in a boreal forest in search for the signature and relevance of the different deposition processes. The canopy-level ozone flux measurements were analysed for deposition characteristics and partitioning into stomatal and non-stomatal fractions, with the main focus on growing season day-time data. Ten years of measurements enabled the analysis of ozone deposition variation at different time-scales, including daily to inter-annual variation as well as the dependence on environmental variables and concentration of biogenic volatile organic compounds (BVOC-s). Stomatal deposition was estimated by using multi-layer canopy dispersion and optimal stomatal control modelling from simultaneous carbon dioxide and water vapour flux measurements, non-stomatal was inferred as residual. Also, utilising the big-leaf assumption stomatal conductance was inferred from water vapour fluxes for dry canopy conditions. The total ozone deposition was highest during the peak growing season (4 mm s−1) and lowest during winter dormancy (1 mm s−1). During the course of the growing season the fraction of the non-stomatal deposition of ozone was determined to vary from 26 to 44% during day time, increasing from the start of the season until the end of the growing season. By using multi-variate analysis it was determined that day-time total ozone deposition was mainly driven by photosynthetic capacity of the canopy, vapour pressure deficit (VPD), photosynthetically active radiation and monoterpene concentration. The multi-variate linear model explained the high portion of ozone deposition variance on daily average level (R2 = 0.79). The explanatory power of the multi-variate model for ozone non-stomatal deposition was much lower (R2 = 0.38). The set of common environmental variables and terpene concentrations used in multivariate analysis were able to predict the observed average seasonal variation in total and non-stomatal deposition but failed to explain the inter-annual differences, suggesting that some still unknown mechanisms might be involved in determining the inter-annual variability. Model calculation was performed to evaluate the potential sink strength of the chemical reactions of ozone with sesquiterpenes in the canopy air space, which revealed that sesquiterpenes in typical amounts at the site were unlikely to cause significant ozone loss in canopy air space. The results clearly showed the importance of several non-stomatal removal mechanisms. Unknown chemical compounds or processes correlating with monoterpene concentrations, including potentially reactions at the surfaces, contribute to non-stomatal sink term.

scholarly journals Low-cost chamber design for simultaneous CO2 and O2 flux measurements between tree stems and the atmosphere

2021 ◽  
Author(s):  
Juliane Helm ◽  
Henrik Hartmann ◽  
Martin Göbel ◽  
Boaz Hilman ◽  
David Herrera ◽  
...  
Keyword(s):  
Low Cost ◽  
Co2 Flux ◽  
Co2 Efflux ◽  
Stem Respiration ◽  
Ecosystem Carbon ◽  
O2 Concentration ◽  
Flux Measurements ◽  
Stem Co2 Efflux ◽  
Tree Stem

Abstract Tree stem CO2 efflux is an important component of ecosystem carbon fluxes and has been the focus of many studies. While CO2 efflux can easily be measured, a growing number of studies have shown that it is not identical with actual in situ respiration. Complementing measurements of CO2 flux with simultaneous measurements of O2 flux provides an additional proxy for respiration, and the combination of both fluxes can potentially help getting closer to actual measures of respiratory fluxes. To date, however, the technical challenge to measure relatively small changes in O2 concentration against its high atmospheric background has prevented routine O2 measurements in field applications. Here we present a new and low-cost field-tested device for autonomous real-time and quasi-continuous long-term measurements of stem respiration by combining CO2 (NDIR based) and O2 (quenching based) sensors in a tree stem chamber. Our device operates as a cyclic closed system and measures changes in both CO2 and O2 concentration within the chamber over time. The device is battery-powered with a &gt; 1 week power independence and data acquisition is conveniently achieved by an internal logger. Results from both field and laboratory tests document that our sensors provide reproducible measurements of CO2 and O2 exchange fluxes under varying environmental conditions.

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