One of the most significant environmental changes across the Tibetan Plateau (TP) is the rapid lake expansion. The expansion of thermokarst lakes affects the global biogeochemical cycles and local climate regulation by rising levels, expanding area, and increasing water volumes. Meanwhile, microbial activity contributes greatly to the biogeochemical cycle of carbon in the thermokarst lakes, including organic matter decomposition, soil formation, and mineralization. However, the impact of lake expansion on distribution patterns of microbial communities and methane cycling, especially those of water and sediment under ice, remain unknown. This hinders our ability to assess the true impact of lake expansion on ecosystem services and our ability to accurately investigate greenhouse gas emissions and consumption in thermokarst lakes. Here, we explored the patterns of microorganisms and methane cycling by investigating sediment and water samples at an oriented direction of expansion occurred from four points under ice of a mature-developed thermokarst lake on TP. In addition, the methane concentration of each water layer was examined. Microbial diversity and network complexity were different in our shallow points (MS, SH) and deep points (CE, SH). There are differences of microbial community composition among four points, resulting in the decreased relative abundances of dominant phyla, such as Firmicutes in sediment, Proteobacteria in water, Thermoplasmatota in sediment and water, and increased relative abundance of Actinobacteriota with MS and SH points. Microbial community composition involved in methane cycling also shifted, such as increases in USC gamma, Methylomonas, and Methylobacter, with higher relative abundance consistent with low dissolved methane concentration in MS and SH points. There was a strong correlation between changes in microbiota characteristics and changes in water and sediment environmental factors. Together, these results show that lake expansion has an important impact on microbial diversity and methane cycling.

Tibetan Plateau (TP) lakes are important water resources, which are experiencing quick expansion in recent decades. Previous researches mainly focus on analyzing the relationship between terrestrial water storage (TWS) change and lake water storage (LWS) change in the total inner TP, it is still lack of researches about the spatial difference and the characteristic of sub-region in the inner TP. In this study, we estimated the area change of 34 lakes by using Landsat images in the northeastern TP during 1976-2013, and LWS change by using the Shuttle Radar Topography Mission (SRTM). The results suggested that LWS had shrunk from 1976 to 1994, and then expanded quickly until 2013. LWS had a serious decrease by 13.6 Gt during 1976-1994, and then it increased quickly by 35.4 Gt during 1994-2013. We estimated TWS change, soil moisture change, and permafrost degradation based on the satellite data and related models during 2003-2013. The results indicated that their changing rates were 1.86 Gt/y, 0.22 Gt/y, and -0.19 Gt/y, respectively. We also calculated the change of groundwater based on the mass balance with a decreasing trend of -0.054 Gt/y. The results suggested that the cause of TWS change was the increase of LWS. We analyzed the cause of lake change according to water balance, and found that the primary cause of lake expansion was the increasing precipitation (80.7%), followed by glacier meltwater (10.3%) and permafrost degradation (9%). The spatial difference between LWS change and TWS change should be studied further, which is important to understand the driving mechanism of water resources change.

Anthropogenic climate change has been linked to the degradation of permafrost across northern ecosystems, with notable implications for regional to global carbon dynamics. However, our understanding of the spatial distribution, temporal trends, and seasonal timing of episodic landscape deformation events triggered by permafrost degradation is hampered by the limited spatial and temporal coverage of high-resolution optical, RADAR, LIDAR, and hyperspectral remote sensing products. Here we present an automated approach for detecting permafrost degradation (thermoerosion), using meso-scale high-frequency remote sensing products (i.e., Landsat image archive). This approach was developed, tested, and applied in the ice-rich lowlands of the Noatak National Preserve (NOAT; 12,369 km(2)) in northwestern Alaska. We identified thermoerosion (TE) by capturing the spectral signal associated with episodic sediment plumes in adjacent water bodies following TE. We characterized and extracted this episodic turbidity signal within lakes during the snow-free period (June 15-October 1) for 1986-2016 (continuous data limited to 1999-2016), using the cloud-based geospatial parallel processing platform, Google Earth Engine (TM). Thermoerosional detection accuracy was calculated using seven consecutive years of sub-meter high-resolution imagery (2009-2015) covering 798 (similar to 33%) of the 2456 lakes in the NOAT lowlands. Our automated TE detection algorithm had an overall accuracy and kappa coefficient of 86% and 0.47 +/- 0.043, indicating that episodic sediment pulses had a moderate agreement with landscape deformation associated with permafrost degradation. We estimate that lake shoreline erosion, thaw slumps, catastrophic lake drainage, and gully formation accounted for 62, 23, 13, and 2%, respectively, of active TE across the NOAT lowlands. TE was identified in similar to 5% of all lakes annually in the lowlands between 1999 and 2016, with a wide range of inter-annual variation (ranging from 0.2% in 2001 to 22% in 2004). Inter-annual variability in TE occurrence and spatial patterns of TE probability were correlated with annual snow cover duration and snow persistence, respectively, suggesting that earlier snowmelt accelerates permafrost degradation (e.g. TE) in this region. This work improves our ability to detect and attribute change in permafrost degradation across space and time.