Surface water extent dynamics from three periods of continuous Landsat time series; subregional differences across Argentine plains

<p>The Pampean region in Argentina is an extensive plain characterized by abundant shallow lakes that fulfill many environmental, ecological, and social functions. This study aims to detect the multiannual lake area changes in this region during 2001-2009 using remote sensing, including lakes as small as ≥10,000 m² or 1 ha. Landsat scenes of the wet (2008-2009), normal (2006), and dry (2008-2009) seasons were obtained, and using remote sensing techniques, the number and area of shallow lakes were calculated. The spatiotemporal variation of shallow lakes was studied in different climate periods in eight singular subregions. Spatial associations between annual precipitation and lake number and area were analyzed through the development of a Geographic Information System (GIS) at a subregional scale. During the study period the total lake area in the Pampean region decreased by 5257.39 km²(62 %), but each subregion showed different responses to climatic events. In seven of them, the differences between climate periods prove to be statistically significant (P&gt;0.01). The relationship between precipitation and lake number and area revealed the domain of positive association. We conclude that climate factors play a dominant role in lake changes across the Pampean plains. However, other factors such as origin, topographic and edaphic characteristics intensify or mitigate changes in surface hydrology.</p>

Annual 30-meter Dataset for Glacial Lakes in High Mountain Asia from 2008 to 2017

Climate change is intensifying glacier melting and lake development in High Mountain Asia (HMA), which could increase glacial lake outburst flood hazards and impact water resource and hydroelectric power management. However, quantification of variability in size and type of glacial lakes at high resolution has been incomplete in HMA. Here, we developed a HMA Glacial Lake Inventory (Hi-MAG) database to characterize the annual coverage of glacial lakes from 2008 to 2017 at 30 m resolution using Landsat satellite imagery. It is noted that a rapid increase in lake number and moderate area expansion was influenced by a large population of small glacial lake (≤ 0.04 km2), and faster growth in lake number occurred above 5300 m elevation. Proglacial lake dominated areas showed significant lake area expansion, while unconnected lake dominated areas exhibited stability or slight reduction. Small glacial lakes accounted for approximately 15% of the lake area in Eastern Hindu Kush, Western Himalaya, Northern/Western Tien Shan, and Gangdise Mountains, but contributed > 50 % of lake area expansion in these regions over a decade. Our results demonstrate proglacial lakes are a main contributor while small glacial lakes are an overlooked element to recent lake evolution in HMA. Regional geographic variability of debris cover, together with trends in warming and precipitation over the past few decades, largely explain the current distribution of supra- and proglacial lake area across HMA. The Hi-MAG database are available at: https://doi.org/10.5281/zenodo.3700282, it can be used for studies on glacier-climate-lake interactions, glacio-hydrologic models, glacial lake outburst floods and potential downstream risks and water resources.

Metagenome-Assembled Genome of Halomonas sp. Isolate SL48-SHIP-3 from the Microbial Mat of Salt Lake Number 48 (Novosibirsk Region, Russia)

The Halomonas sp. isolate SL48-SHIP-3 genome was obtained from metagenomics sequencing of the microbial mat of Salt Lake Number 48 (54.201806N, 78.179194E; Novosibirsk region, Russia). The sequenced and annotated genome is 2,575,909 bp and encodes 2,368 genes.

Metagenome-Assembled Genome Sequence of Phormidium sp. Strain SL48-SHIP, Isolated from the Microbial Mat of Salt Lake Number 48 (Novosibirsk Region, Russia)

The Phormidium sp. strain SL48-SHIP genome was obtained from metagenomics sequencing of the microbial mat of Salt Lake No. 48 (54.201806 N, 78.179194 E; Novosibirsk Region, Russia). The sequenced and annotated genome is 4,384,607 bp and encodes 3,807 genes.

No magic number: determining cost-effective sample size and enumeration effort for diatom-based environmental assessment analyses

Aquatic microorganisms are commonly used as indicators in environmental assessments. Two key aspects of sampling design for these studies are the number of sites sampled and the enumeration effort of organisms within samples. However, there has been no rigorous determination of a cost-effective balance between them. Here, we use regional diatom data sets from 207 to 493 lakes to determine the influence of sample size (lake number) and enumeration effort (valve count) on the accuracy and cost-effectiveness of commonly used environmental assessment analyses. We find that both lake number and valve count can be considerably reduced from the original data sets. However, there is considerable variation among analyses, such that a single most cost-effective sampling configuration cannot be recommended. For weighted-averaging assemblage versus environment models, we recommend 70–100 lakes and 200 valves for retaining high accuracy. For other analyses, we recommend iteratively building up data sets, using initially high (300 or more) and consistent valve counts and using subsampling to determine when the influence of either lake number or valve count plateaus. This technique is applicable to other types of microorganisms used in environmental assessments.