Scots pine (Pinus sylvestris L.) reaction to climate change in the provenance tests in the north of the Russian plain

Species with continuous distribution area will be impacted by climate change in different ways. That is related to the population’s geographical position and climate features of the population formation. Short-term response of Scots pine (Pinus sylvestris L.) was studied with taken into consideration intraspecies features of populations. Provenance tests in the Arkhangelsk (62.60 N, 39.98 E) and Vologda (62.60 N, 39.98E) regions located in the north of the Russian Plain were used. Provenances collection (23 provenances from the northern, middle, and southern taiga subzones and mixed forest zone) from areas with different climate characteristics was considered. Clinal variability and a reaction norm of vegetative and generative response to various levels of temperature change and seed transfer were studied. Average actual height and diameter values for 31-year provenances and calculated values for provenances were compared using ‘latitudinal growth coefficient’ proposed by I.V. Volosevich (1984) for the north of the Russian Plain. Provenance reproductive ability response was assessed using seed-bearing trees’ numbers in provenances of the 1st class of age. Pine growing in the north of the Russian Plain would respond to warming by productivity increasing more significantly than pine growing in the south. Response of pine from the northern and middle taiga subzones on climate warming can be expected on 1.01 m and 1.12 cm to temperature rise by 100°C for height and diameter, and 0.85 m and 0.93 cm for seeds transfer to 1 degree of northern latitude to southward. Probable reaction norm for pine reproduction potential under temperature change by 100°C of the sum of the temperatures above 10ºС and seed transfer by 1 degree of northern latitude can be expected about 6%.

A new species of the genus Mycterodus Spinola (Hemiptera: Auchenorrhyncha: Issidae) from Iran defining southern boundary of generic distribution

Mycterodus meridionalis sp. n. is described from Kerman Province of southern Iran. This is one of the most southern species of the genus Mycterodus Spinola known from between 29º and 30º of northern latitude.

HydroSHEDS v2.0 – Refined global river network and catchment delineations from TanDEM-X elevation data

<p>Since its introduction in 2008, the HydroSHEDS database (www.hydrosheds.org) has transformed large-scale hydro-ecological research and applications worldwide by offering standardized spatial units for hydrological assessments. At its core, HydroSHEDS provides digital hydrographic information that can be applied in Geographic Information Software (GIS) or hydrological models to delineate river networks and catchment boundaries at multiple scales, from local to global. Its various data layers form the basis for applications in a wide range of disciplines including environmental, conservation, socioeconomic, human health, and sustainability studies.</p><p>Version 1 of HydroSHEDS was derived from the digital elevation model of the Shuttle Radar Topography Mission (SRTM) at a pixel resolution of 3 arc-seconds (~90 meters at the equator). It was created using customized processing and optimization algorithms and a high degree of manual quality control. Results are available at varying resolutions, ranging from 3 arc-seconds (~90 m) to 5 minutes (~10 km), and in nested sub-basin structures, making the data uniquely suitable for applications at multiple scales. A suite of related data collections and value-added information, foremost the HydroATLAS compilation of over 50 hydro-environmental attributes for every river reach and sub-basin, continuously enhance the versatility of the HydroSHEDS family of products. Yet version 1 of HydroSHEDS shows some important limitations. In particular, coverage above 60° northern latitude (i.e., largely the Arctic) is missing for the 3 arc-second product and is of low quality for coarser products because no SRTM elevation data are available for this region. Also, some areas are affected by inherent data gaps or other errors that could not be fully resolved at the time of creating version 1 of HydroSHEDS.</p><p>Today, the TanDEM-X dataset (TerraSAR-X add-on for Digital Elevation Measurement), created in partnership between the German Aerospace Agency (DLR) and Airbus, offers a new digital elevation model covering the entire global land surface including northern latitudes. In a collaborative project, this dataset is used to extract HydroSHEDS v2.0, following the same basic specifications as version 1. DLR is processing the original 12 m resolution TanDEM-X data to create a hydrologically pre-conditioned version at 3 arc-second resolution. In this step, corrections with high-resolution vegetation and settlement maps are applied to reduce distortions caused by vegetation cover and in built-up areas. Following this preprocessing, refined hydrological optimization and correction algorithms are used to derive the drainage pathways, including improved ‘stream-burning’ techniques that incorporate recent data products such as high-resolution terrestrial open water masks and improved tracing of drainage pathways as center lines in global lake and river maps. The resulting HydroSHEDS v2.0 database will provide river networks and catchment boundaries at full global coverage. Release of the data under a free license is scheduled for 2022, with regions above 60° northern latitude being completed first in 2021.</p>

Monitoring Arctic and high-latitude wildfires in 2019 and 2020

<p>The boreal summers of 2019 and 2020 were witness to extensive high northern latitude wildfire activity, most notably within the Arctic Circle across eastern Russia. Near-real-time monitoring of the wildfire activity, based on satellite observations of active fires, showed widespread and persistent fires at a scale that had not been observed in the previous years that satellite observations are available. The European Centre for Medium-Range Weather Forecasts (ECMWF) through its operation of, and contribution to, different Copernicus Services is in a unique position to provide detailed information to monitor high-latitude wildfire activity, including their evolution and potential impacts, when they occur. Fire weather forecasts from the Copernicus Emergency Management Service (CEMS), and surface climate anomalies from the Copernicus Climate Change Service (C3S) both provide context to the environmental conditions required for wildfires to persist. Analyses based on observations of fire radiative power, along with analyses and forecasts of associated atmospheric pollutants, from the Copernicus Atmosphere Monitoring Service (CAMS) aid in quantifying the scale and intensity in near-real-time and the subsequent atmospheric impacts. We present an analysis of Arctic and high northern latitude wildfires during the summers of 2019 and 2020, reviewing the underlying meteorological/climatological conditions, the estimated emissions and transport of smoke constituents over the Arctic Ocean. We will show that the different datasets, while being relatively independent, show a strong correspondence and provide a wealth of information required to monitor and provide context for wildfire activity.</p>

Anthology of Dirofilariasis in Russia (1915–2017)

Dirofilariasis is a helminths vector-borne disease caused by two species of Dirofolaria—D. repens and D. immitis. The former is overwhelmingly associated with human dirofilariasis. The vector of the worm are mosquitoes of the family Culicidae (largely Culex, Aedes and Anopheles). The definitive hosts of Dirofilaria are dogs and to a lesser extent cats. Humans are an accidental host. A total of 1200 human cases caused by Dirofilaria were registered in the territory of the ex-USSR during the period 1915–2016. Zonal differences have been seen in the prevalence of infected dogs and mosquitoes. Studies undertaken in the southern part of the Russian Federation (RF) revealed the prevalence of Dirofilaria in dogs to be 20.8% with wild variations of larva density. Studies carried out in the central part of the RF found that the prevalence of parasites in dogs was 4.1%. Aedes mosquitoes were infected less than Culex and Anopheles mosquitoes. The latter were infected by D. repens more often than Culex and Aedes. Zonal differences were also traced in regard to Dirofilaria prevalence in humans, thus allowing identification of three zones of risk of infection (low, moderate, and stable), reflected in a series of constructed maps. Although Dirofilariasis was known on the territory of Russia from 1915, only sporadic cases of the disease were reported occasionally. Its number was showed an increasing trend only during the 1980s–1990s, reaching the level of hundreds of cases. The majority of cases were confined to the southern parts of Russia with geographic coordinates of 43°–45° on the northern latitude. Comparison of the timing of the global trend of climate warming during the 1990s with the temporal pattern of Dirofilaria on the territory of Russia during the same period demonstrated a close association between two phenomena. With the continuous process of global climate warming, the incidence of dirofilariasis both in man and dogs goes unabated exemplified by the territorial expansion of the disease northwards and eastwards attaining the latitude of 56°–57° on the northern latitude in the European and Asian parts of Russia. It appears that within the period of the last 20–25 years, the population at risk has doubled. Under these circumstances, dirofilariases in Russia should be considered as an emerging public health problem necessitating the establishment of a comprehensive epidemiological monitoring system with strong entomological and veterinary components. Based on the results obtained, an appropriate control intervention could be developed.

Developing a New Machine-Learning Algorithm for Estimating Chlorophyll-a Concentration in Optically Complex Waters: A Case Study for High Northern Latitude Waters by Using Sentinel 3 OLCI

The monitoring of Chlorophyll-a (Chl-a) concentration in high northern latitude waters has been receiving increased focus due to the rapid environmental changes in the sub-Arctic, Arctic. Spaceborne optical instruments allow the continuous monitoring of the occurrence, distribution, and amount of Chl-a. In recent years, the Ocean and Land Color Instruments (OLCI) onboard the Sentinel 3 (S3) A and B satellites were launched, which provide data about various aquatic environments on advantageous spatial, spectral, and temporal resolutions with high SNR. Although S3 OLCI could be favorable to monitor high northern latitude waters, there have been several challenges related to Chl-a concentration retrieval in these waters due to their unique optical properties coupled with challenging environments including high sun zenith angle, presence of sea ice, and frequent cloud covers. In this work, we aim to overcome these difficulties by developing a machine-learning (ML) approach designed to estimate Chl-a concentration from S3 OLCI data in high northern latitude optically complex waters. The ML model is optimized and requires only three S3 OLCI bands, reflecting the physical characteristic of Chl-a as input in the regression process to estimate Chl-a concentration with improved accuracy in terms of the bias (five times improvements.) The ML model was optimized on data from Arctic, coastal, and open waters, and showed promising performance. Finally, we present the performance of the optimized ML approach by computing Chl-a maps and corresponding certainty maps in highly complex sub-Arctic and Arctic waters. We show how these certainty maps can be used as a support to understand possible radiometric calibration issues in the retrieval of Level 2 reflectance over these waters. This can be a useful tool in identifying erroneous Level 2 Remote sensing reflectance due to possible failure of the atmospheric correction algorithm.