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

Stefan Erasmi,Choimaa Dulamsuren,Michael Klinge,Florian Schneider,Markus Hauck

doi:10.1007/s10661-021-08996-1

Abstract

The 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.

Highlights

Terrestrial carbon of aboveground biomass plays a major role in the global carbon cycle
Seasonal composites of Normalized Difference Vegetation Index (NDVI) data from a 20-year multi-sensor Landsat time series were tested for correlations with dendrochronological tree ring growth of Siberian larch in the southern boreal forests of northern Mongolia
The analysis concept was based on the hypothesis that the general vegetation greenness is correlated with ecosystem productivity and productivity can be captured by satellite-based vegetation indices like the NDVI

Summary

Introduction

Terrestrial carbon of aboveground biomass plays a major role in the global carbon cycle. Changing climate is assumed to have a considerable impact on vegetation growth and tree productivity, especially in areas that are considered as hotspots of global climate change, like the eastern part of Central Asia (Turco et al, 2015). Depending on the climatic conditions, annual stem increment in boreal of forest can either be limited by low temperatures or drought during the growing season (Beck et al, 2011; Hauck et al, 2019; Zhou et al, 2020). The forest-steppe related to the semi-arid regions of Central Asia is more and more subjected to forest disturbance by fire and windthrow (Nyamjav et al, 2007). These forests often show decreases in productivity (Dulamsuren et al, 2010, 2013)

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Results

Discussion

Conclusion