Effects of forest fragmentation on organic carbon pool densities in the Mongolian forest-steppe

Schneider

et al. 2020

Preprint

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Abstract. The Mongolian forest-steppe is highly sensitive to climate change and environmental impact. The intention of this study was to identify, which geoecological parameters control forest distribution and tree growth in this semi-arid environment, and to evaluate the actual and potential tree biomass. For this purpose, we applied a combination of tree biomass and soil mapping, remote sensing and climate data analysis to a study area in the northern Khangai Mountains, central Mongolia. Forests of different landscape units and site conditions generally showed minor differences in tree biomass. We found no significant correlation between tree biomass and NDVI (normalized differentiated vegetation index). Tree biomass was reduced at forest edges, in small fragmented forest stands of the steppe-dominated area, and in large forest stands, compared to all other forest units. The tree biomass of forests on slopes ranged between 25 and 380 Mg ha−1. The mean tree biomass in forests of 10–500 ha was 199–220 Mg ha−1, whereby tree biomass at the forest edges was 50–63 Mg ha−1 less than in the interior parts of the forests. The mean tree biomass of forests > 500 ha was 182 Mg ha−1, whereas that of forests

Section: Study Areamentioning

confidence: 99%

Section: Classification Of Site Conditionsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 98%

Section: Introductionmentioning

confidence: 99%

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confidence: 99%

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Modelled potential forest area in the forest-steppe of central Mongolia is about three times of actual forest area

Schneider

et al. 2020

Preprint

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Interrelations between relief, vegetation, disturbances, and permafrost in the forest‐steppe of central Mongolia

Schneider

Earth Surf Processes Landf

et al. 2021

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In semi‐arid central Asia, relief has a strong impact on the distribution of vegetation and discontinuous permafrost. Our aim was to analyse causal chains and inter‐relationships that control the spatial patterns of forest and permafrost in the forest‐steppe of the northern Khangai Mountains in Mongolia. For this purpose, we conducted soil‐profile descriptions, ground‐penetrating radar sounding, and vegetation mapping to gain information about forest and permafrost distribution. We integrated remote‐sensing analysis and field‐mapping data, including soil properties, vegetation cover, forest fires and anthropogenic forest use. We developed and applied a technique for spatial delineation of permafrost distribution, based on the parameters Topographic Wetness Index (TWI), incoming solar radiation and Normalized Difference Vegetation Index (NDVI). Key outcomes of this study are that the occurrence of discontinuous permafrost within 1 m depth is limited to forest stands larger than 100 ha on north‐facing slopes. Dense ground vegetation supports permafrost, whereas sandy soil texture leads to greater depth of the permafrost table. As the seasonal ice in the active layer progressively melts down during summer, meltwater interflow above the permafrost table provides additional soil moisture downslope. This process is reflected in enhanced vitality of the steppe vegetation on toe slopes below forests with permafrost. This effect can in turn be used to indirectly detect permafrost in forest stands by remote sensing. Permafrost mostly disappears after forest fires and other severe disturbances, but it may re‐establish during forest regrowth. However, climate warming is presently leading to a loss of permafrost regeneration potential after disturbance, and to a shift from climate‐induced and ecosystem‐driven permafrost to entirely ecosystem‐protected permafrost. These trends will result in a further decrease of permafrost area after forest disturbance.

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

Erasmi

et al. 2021

Environ Monit Assess

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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.