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Organic matter temporal dynamics in the river ecosystem basin using remote sensing

Authors: Tatiana Trifonova; Natalia Mishchenko; Pavel Shutov;

Organic matter temporal dynamics in the river ecosystem basin using remote sensing

Abstract

Environmental research addresses ecosystems of various hierarchical levels. One of the ecosystem types is the river basin. The basin approach has been applied in the research. We consider the river basin as a single ecosystem of complex landscape structure. The research objective was to assess the biological processes in various landscapes within a holistic natural geosystem – a catchment area. The Klyazma River Basin (a part of the Volga River of 40 thousand km2 area) was the research object. It is a complex combination of different landscapes, each marked by a diverse composition of geomorphological and soil-vegetation structures. According to the geomorphological structure and soil and vegetation cover, four landscape provinces and eight key sites have been identified in the studied catchment area where the ecosystem parameter have been measured. The study is based on remote sensing data and the Trends. Earth Land Degradation Monitoring. The calculation of productivity indicators (GPP, NPP) in carbon units and the land use structure analysis are based on Modis data. The soil organic carbon pool was determined by the UN FAO’s data, based on Trends. Earth and QGIS 2.18. The two-factor variance analysis ANOVA has been used for the data statistic processing. The cartographic analysis of the land use structure dynamics of the entire Klyazma Basin resulted in revealing the areas where various land transitions from one category to another have been identified. They are basically associated with the agricultural land overgrowth. The forest area increased by 9% during the period from 2001 to 2017. Considerable increase in the waterlogged, wetlands areas was observed in the eastern part of the Basin, in the Volga-Klyazma Province. The landscapes react differently to changes in climatic parameters and land use. Thus, the active revegetation of farmland by forests gives the increased rate of carbon accumulation in the soil. Landscapes covered with grasses and shrubs are more productive those covered with forest. On the other hand, woody biotopes are more stable in their development over time. Statistical analysis using the two-factor variation analysis ANOVA method resulted in demonstrating that phytoproductivity dynamics of the key sites does not depend on their productivity parameters nor on the site landscape structure, but is mainly determined by a time factor. In different landscapes the biological processes, characterising the organic matter dynamics in the form of plant production, organic matter accumulation and others are shown to differ both in rate and intensity and ambiguously respond to changes in climate parameters and land use. The river basin, as a single ecosystem, showed sufficient stability of the dynamic processes. This suggests that holistic natural ecosystems, such as catchment areas, have internal compensatory mechanisms that maintain the development stability for a long time, while unplanned land use remains the main damaging factor.

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Keywords

carbon balance, phytoproductivity dynamic, Ecology, phytoproductivity dynamics, remote sensing data, landscapes, QH540-549.5, river basin

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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