In northern Mongolia, at the southern boundary of the Siberian boreal forest belt, the distribution of steppe and forest is generally linked to climate and topography, making this region highly sensitive to climate change and human impact. Detailed investigations on the limiting parameters of forest and steppe in different biomes provide necessary information for paleoenvironmental reconstruction and prognosis of potential landscape change. In this study, remote sensing data and gridded climate data were analyzed in order to identify main distribution patterns of forest and steppe in Mongolia and to detect environmental factors driving forest development. Forest distribution and vegetation vitality derived from the normalized differentiated vegetation index (NDVI) were investigated for the three types of boreal forest present in Mongolia (taiga, subtaiga and forest–steppe), which cover a total area of 73 818 km ² . In addition to the forest type areas, the analysis focused on subunits of forest and nonforested areas at the upper and lower treeline, which represent ecological borders between vegetation types. Climate and NDVI data were analyzed for a reference period of 15 years from 1999 to 2013. The presented approach for treeline delineation by identifying representative sites mostly bridges local forest disturbances like fire or tree cutting. Moreover, this procedure provides a valuable tool to distinguish the potential forested area. The upper treeline generally rises from 1800 m above sea level (a.s.l.) in the northeast to 2700 m a.s.l. in the south. The lower treeline locally emerges at 1000 m a.s.l. in the northern taiga and rises southward to 2500 m a.s.l. The latitudinal gradient of both treelines turns into a longitudinal one on the eastern flank of mountain ranges due to higher aridity caused by rain-shadow effects. Less productive trees in terms of NDVI were identified at both the upper and lower treeline in relation to the respective total boreal forest type area. The mean growing season temperature (MGST) of 7.9–8.9 ^∘ C and a minimum MGST of 6 ^∘ C are limiting parameters at the upper treeline but are negligible for the lower treeline. The minimum of the mean annual precipitation (MAP) of 230–290 mm yr ⁻¹ is a limiting parameter at the lower treeline but also at the upper treeline in the forest–steppe ecotone. In general, NDVI and MAP are lower in grassland, and MGST is higher compared to the corresponding boreal forest. One exception occurs at the upper treeline of the subtaiga and taiga, where the alpine vegetation consists of mountain meadow mixed with shrubs. The relation between NDVI and climate data corroborates that more precipitation and higher temperatures generally lead to higher greenness in all ecological subunits. MGST is positively correlated with MAP of the total area of forest–steppe, but this correlation turns negative in the taiga. The limiting factor in the forest–steppe is the relative humidity and in the taiga it is the snow cover distribution. The subtaiga represents an ecological transition zone of approximately 300 mm yr ⁻¹ precipitation, which occurs independently from the MGST. Since the treelines are mainly determined by climatic parameters, the rapid climate change in inner Asia will lead to a spatial relocation of tree communities, treelines and boreal forest types. However, a direct deduction of future tree vitality, forest composition and biomass trends from the recent relationships between NDVI and climate parameters is challenging. Besides human impact, it must consider bio- and geoecological issues like, for example, tree rejuvenation, temporal lag of climate adaptation and disappearing permafrost.

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.

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.

Glacial and lacustrine sediments from the Mongolian Altai provide paleoclimatic information for the late Pleistocene in Mongolia, for which only a few sufficiently studied archives exist. Glacial stages referred to global cooling events are reported for the last glacial maximum (27–21 ka) and the late glacial period (18–16 ka). Sedimentary archives from the first part of the last glacial period are infrequent. We present proxy data for this period from two different archives (88–63 and 57–30 ka). Due to the limitation of effective moisture, an increase of precipitation is discussed as one trigger for glacier development in the cold-arid regions of central Asia. Our pollen analysis from periods of high paleolake levels in small catchments indicate that the vegetation was sparse and of dry desert type between 42–29 and 17–11 ka. This apparent contradiction between high lake levels and dry landscape conditions, the latter supported by intensified eolian processes, points to lower temperatures and cooler conditions causing reduced evaporation to be the main trigger for the high lake levels during glacier advances. Rising temperatures that cause melting of glacier and permafrost ice and geomorphological processes play a role in paleolake conditions. Interpreting lake-level changes as regional or global paleoclimate signals requires detailed investigation of geomorphological settings and mountain–basin relationships.

Rapid urbanization processes and indiscriminate disposal of urban wastewaters are major causes for anthropogenic lake-sediment deposition and eutrophication. However, information about the spatial and temporal variation of macrophyte and phytoplankton distribution as indicators for water contamination is limited. To gain insights into the dynamics, we analyzed lake-cover changes of Bellandur and Varthur Lake in the S-Indian megacity of Bengaluru for the post-rainy seasons of the years 2002–2019. Supervised maximum likelihood classifications were conducted on 62 freely available, true-color satellite images in order to distinguish between macrophytes, algae, and free water surface. The image-derived results were verified by supervised classification and manual mapping of two simultaneously recorded multispectral satellite images (Sentinel-2 and WorldView-2). Seasonal interrelations between macrophytes and algae distribution were similar for both lakes. The increase in macrophyte cover during post-rainy season negatively correlated with algal abundance. Macrophyte expansion progressively suppressed algae development at both lakes, reflective of increasing eutrophication caused by on-going wastewater input. Seasonal variation in precipitation, wind direction, and temperature seemed to trigger intra-annual shifts of macrophytes and algae while similar macrophyte spread intensities during the post-monsoon season indicated independence of nutrient loads in the lake water.

The landform ensemble of the Tsetseg Nuur Basin in Western Mongolia provides an archive for periods of different geomorphologic processes induced by changing climate conditions during the Holocene and late Pleistocene times. The geomorphologic map of Tsetseg Nuur basin in the Mongolian Altai illustrates the spatial relation and interaction between different types of sedimentation in semi-arid regions of Central Asia. The map is an instrument to visualize the geomorphologic settings, providing valuable information to distinguish periods of geomorphologic processes and to analyze the landscape evolution. This enables the creation of a relative morphostratigraphy of periods with different hydrological environments, mainly marked by the stages of lake level evolution in an interior drainage basin. The relative chronology calculated from the map receives an absolute chronostratigraphy through radiometric dating from selected sections investigated during field-work.