Mitochondrial genomes of Pleistocene megafauna retrieved from recent sediment layers of two Siberian lakes.

Ancient environmental DNA (aeDNA) from lake sediments has yielded remarkable insights for the reconstruction of past ecosystems, including suggestions of late survival of extinct species. However, translocation and lateral inflow of DNA in sediments can potentially distort the stratigraphic signal of the DNA. Using three different approaches on two short lake sediment cores of the Yamal peninsula, West Siberia, with ages spanning only the past hundreds of years, we detect DNA and identified mitochondrial genomes of multiple mammoth and woolly rhinoceros individuals-both species that have been extinct for thousands of years on the mainland. The occurrence of clearly identifiable aeDNA of extinct Pleistocene megafauna (e.g. >400 K reads in one core) throughout these two short subsurface cores, along with specificities of sedimentology and dating, confirm that processes acting on regional scales, such as extensive permafrost thawing, can influence the aeDNA record and should be accounted for in aeDNA paleoecology.

Does size matter? Modelling the cooling effect of green infrastructures in a megacity during a heat wave.

The vulnerability of urban ecosystems to global climate change becomes a key issue in research and political agendas. Urban green infrastructures (UGIs) are widely considered as a nature-based solution to mitigate climate change and adapt to local urban climate anomalies in cities. However, UGI-induced cooling effect depends on the size, location and geometry of green spaces, and such dependencies remain overlooked. This research aimed to investigate the cooling effect of UGIs of different size under extreme conditions of 2021 summer heat wave for the case of Moscow megacity (Russia) using a numerical mesoclimatic model COSMO. UGIs objects were assigned to one of the four size categories (S, M, L and XL) based on their area. Their cooling effects at the local, non-local and city scales were evaluated based on comparison between the model outcomes for the realistic land cover and simulations for which UGI of a particular size category were replaced by the built-up areas typical for their surroundings. The highest cooling effect was observed for XL size UGIs, which reduced the local heat-wave-averaged air temperatures by up to 3.4 °C, whereas for the S size UGIs it did not exceed 2 °C. The cooling effectiveness for XL category was higher than for S category by 23 % inside the green spaces (locally), by 40-90 % in the buffer zones around the green space (non-locally) and by 35 % for the whole city. More effective cooling of large UGIs is partially explained by their stronger park breeze effect, i.e., impact on the airflow increasing the divergence over green spaces. However, when standardized to the population affected by cooling, the M size UGIs made the strongest contribution to the thermal environment where people live and work. The stronger non-local cooling induced by the largest UGI objects cannot compensate for their remoteness from the built environment.

COVID-19 pandemic changes the recreational use of Moscow parks in space and time: Outcomes from crowd-sourcing and machine learning.

The limited access to urban green spaces during the COVID-19 pandemic had a negative impact on the human-nature interaction in cities and human well-being. Number of visitors to green areas, initially declined due to imposed restrictions, was restored after they were lifted as established by several studies across the globe However, little is still known about changes in behavior and preferences of park visitors in the post-COVID time. In this study, we investigated spatial-temporal patterns of recreational activities in the three urban parks in Moscow (Russia) prior, during and after the COVID-19 lockdown (in 2019 and 2020). The selected parks represent two different types: a centrally located park with much infrastructure and open landscapes (Gorky Park) and parks located at the outskirts of the city center with a more forested landscape and little infrastructure (Timiryazevski and Sokolniki parks). Recreational activities were identified based on the analysis of social media photos using machine-learning algorithms. As expected, park closures during lockdown resulted in overall decrease in the number of taken photos. After the parks were re-opened, however, the number of photos did not grow immediately. The number of photos only restored after almost three months, and the visiting peak shifted to autumn. Differences between parks were related to the type of the park and its landscape structure. The lowest decrease in the number of photos was observed for the Timiryazevsky park - a semi-natural green area, while the centrally located Gorky Park was the most affected, likely due to the strictest control measures. In comparison to 2019, photos in 2020 were more evenly distributed across the area in all the three parks. Besides, 'natural' areas became the main attractors for the visitors - photos under 'nature observation' category became the most popular. Spatial distribution of the recreational activities in post-lockdown period was characterized by larger distances between photos, likely corresponding to the social distancing. COVID-19 pandemic highlighted the value of green areas for citizens, but also changed their recreational preferences and overall behavior in parks. The observed shift from high density of visitors around entertainments and attractions in 2019 to a more homogeneous and less dense distribution along the natural zones in 2020 reveals a new pattern in visitors behavior and preference, which shall be considered in spatial planning of the parks. Increasing availability of natural green areas and their integration in urban green infrastructures can become the most relevant policy to consider the crucial role of urban nature as a source of resilience in turbulent times.