Results of Monitoring over the West Nile Fever Pathogen in the Territory of the Russian Federation in 2017. Forecast of Epidemic Situation Development in Russia in 2018

In Europe, in the epidemic season 2017, the incidence of West Nile fever did not exceed the index of the previous season. In the US and Canada, there was an increase in the incidence of cases. West Nile fever morbidity rates in the Russian Federation and in separate constituent entities were below the average long-term index and had the lowest value for the period since 2008. 41.6 % of WNF cases were imported to Russia from the distant countries. Analysis of the monitoring results indicated the circulation of WNF virus markers in carriers of the pathogen in 6 constituent entities of the Russian Federation, and the presence of IgG antibodies in healthy population cohorts in 24 RF entities. According to molecular-genetic typing of WNF virus samples from mosquito Culex modestus from the Volgograd Region, WNF virus genotype II was established. Forecasting of epidemiological situation development for the year 2018 does not rule out the possibility of local increase in WNF incidence in certain regions of Russia

Warming response of peatland CO2 sink is sensitive to seasonality in warming trends

Peatlands have acted as net CO2 sinks over millennia, exerting a global climate cooling effect. Rapid warming at northern latitudes, where peatlands are abundant, can disturb their CO2 sink function. Here we show that sensitivity of peatland net CO2 exchange to warming changes in sign and magnitude across seasons, resulting in complex net CO2 sink responses. We use multiannual net CO2 exchange observations from 20 northern peatlands to show that warmer early summers are linked to increased net CO2 uptake, while warmer late summers lead to decreased net CO2 uptake. Thus, net CO2 sinks of peatlands in regions experiencing early summer warming, such as central Siberia, are more likely to persist under warmer climate conditions than are those in other regions. Our results will be useful to improve the design of future warming experiments and to better interpret large-scale trends in peatland net CO2 uptake over the coming few decades.Peatlands have historically acted as a carbon sink, but it is unclear how climate warming will affect this. The response of peatland carbon uptake to warming depends on the timing of summer warming; early warming leads to increased CO2 uptake and later warming to decreased uptake

Peculiarities of the Epidemic Situation on West Nile Fever in the Territory of the Russian Federation in 2018 and Forecast of its Development in 2019

The epidemic rise in the incidence of West Nile fever (WNF) in the season of 2018 was observed in the countries of the European Union (EU) and bordering states and exceeded the values of all previously recorded epidemic rises of 2010–2012. An increase in the incidence rate was registered in the USA and Canada, however, it did not exceed the indicators of epidemic rises of 2007–2012. In the territory of the Russian Federation, the WNF epidemiological process became more intense mainly in the territory of the Southern and North Caucasian Federal Districts. In general, in Russia, the incidence rates were 2 times lower than the average annual rates, but significantly exceeded those of 2017. The epidemic process had a number of peculiarities in the seasonality, the structure of morbidity and the clinical manifestation of WNF. Genotyping of the isolated WNV RNA fragments from clinical and biological material showed that I, II and IV West Nile virus genotypes were circulating in the European part of Russia. Forecast of epidemic situation development in 2019 reveals further increase in the incidence and does not exclude the possibility of a significant localincrease of WNF incidence in certain regions of Russia

Pan-Eurasian Experiment (PEEX): Towards a holistic understanding of the feedbacks and interactions in the land-Atmosphere-ocean-society continuum in the northern Eurasian region

The northern Eurasian regions and Arctic Ocean will very likely undergo substantial changes during the next decades. The Arctic-boreal natural environments play a crucial role in the global climate via albedo change, carbon sources and sinks as well as atmospheric aerosol production from biogenic volatile organic compounds. Furthermore, it is expected that global trade activities, demographic movement, and use of natural resources will be increasing in the Arctic regions. There is a need for a novel research approach, which not only identifies and tackles the relevant multi-disciplinary research questions, but also is able to make a holistic system analysis of the expected feedbacks. In this paper, we introduce the research agenda of the Pan-Eurasian Experiment (PEEX), a multi-scale, multi-disciplinary and international program started in 2012 (https://www.atm.helsinki.fi/peex/). PEEX sets a research approach by which large-scale research topics are investigated from a system perspective and which aims to fill the key gaps in our understanding of the feedbacks and interactions between the land-Atmosphere-Aquatic-society continuum in the northern Eurasian region. We introduce here the state of the art for the key topics in the PEEX research agenda and present the future prospects of the research, which we see relevant in this context

Monthly gridded data product of northern wetland methane emissions based on upscaling eddy covariance observations

Natural wetlands constitute the largest and most uncertain source of methane (CH4) to the atmosphere and a large fraction of them are found in the northern latitudes. These emissions are typically estimated using process (“bottom-up”) or inversion (“top-down”) models. However, estimates from these two types of models are not independent of each other since the top-down estimates usually rely on the a priori estimation of these emissions obtained with process models. Hence, independent spatially explicit validation data are needed. Here we utilize a random forest (RF) machine-learning technique to upscale CH4 eddy covariance flux measurements from 25 sites to estimate CH4 wetland emissions from the northern latitudes (north of 45∘ N). Eddy covariance data from 2005 to 2016 are used for model development. The model is then used to predict emissions during 2013 and 2014. The predictive performance of the RF model is evaluated using a leave-one-site-out cross-validation scheme. The performance (Nash–Sutcliffe model efficiency =0.47) is comparable to previous studies upscaling net ecosystem exchange of carbon dioxide and studies comparing process model output against site-level CH4 emission data. The global distribution of wetlands is one major source of uncertainty for upscaling CH4. Thus, three wetland distribution maps are utilized in the upscaling. Depending on the wetland distribution map, the annual emissions for the northern wetlands yield 32 (22.3–41.2, 95 % confidence interval calculated from a RF model ensemble), 31 (21.4–39.9) or 38 (25.9–49.5) Tg(CH4) yr−1. To further evaluate the uncertainties of the upscaled CH4 flux data products we also compared them against output from two process models (LPX-Bern and WetCHARTs), and methodological issues related to CH4 flux upscaling are discussed. The monthly upscaled CH4 flux data products are available at https://doi.org/10.5281/zenodo.2560163 (Peltola et al., 2019)

Gap-filling eddy covariance methane fluxes:Comparison of machine learning model predictions and uncertainties at FLUXNET-CH4 wetlands

Time series of wetland methane fluxes measured by eddy covariance require gap-filling to estimate daily, seasonal, and annual emissions. Gap-filling methane fluxes is challenging because of high variability and complex responses to multiple drivers. To date, there is no widely established gap-filling standard for wetland methane fluxes, with regards both to the best model algorithms and predictors. This study synthesizes results of different gap-filling methods systematically applied at 17 wetland sites spanning boreal to tropical regions and including all major wetland classes and two rice paddies. Procedures are proposed for: 1) creating realistic artificial gap scenarios, 2) training and evaluating gap-filling models without overstating performance, and 3) predicting half-hourly methane fluxes and annual emissions with realistic uncertainty estimates. Performance is compared between a conventional method (marginal distribution sampling) and four machine learning algorithms. The conventional method achieved similar median performance as the machine learning models but was worse than the best machine learning models and relatively insensitive to predictor choices. Of the machine learning models, decision tree algorithms performed the best in cross-validation experiments, even with a baseline predictor set, and artificial neural networks showed comparable performance when using all predictors. Soil temperature was frequently the most important predictor whilst water table depth was important at sites with substantial water table fluctuations, highlighting the value of data on wetland soil conditions. Raw gap-filling uncertainties from the machine learning models were underestimated and we propose a method to calibrate uncertainties to observations. The python code for model development, evaluation, and uncertainty estimation is publicly available. This study outlines a modular and robust machine learning workflow and makes recommendations for, and evaluates an improved baseline of, methane gap-filling models that can be implemented in multi-site syntheses or standardized products from regional and global flux networks (e.g., FLUXNET)

Upscaling wetland methane emissions from the FLUXNET‐CH4 eddy covariance network (UpCH4 v1.0): model development, network assessment, and budget comparison

Wetlands are responsible for 20%–31% of global methane (CH4) emissions and account for a large source of uncertainty in the global CH4 budget. Data-driven upscaling of CH4 fluxes from eddy covariance measurements can provide new and independent bottom-up estimates of wetland CH4 emissions. Here, we develop a six-predictor random forest upscaling model (UpCH4), trained on 119 site-years of eddy covariance CH4 flux data from 43 freshwater wetland sites in the FLUXNET-CH4 Community Product. Network patterns in site-level annual means and mean seasonal cycles of CH4 fluxes were reproduced accurately in tundra, boreal, and temperate regions (Nash-Sutcliffe Efficiency ∼0.52–0.63 and 0.53). UpCH4 estimated annual global wetland CH4 emissions of 146 ± 43 TgCH4 y−1 for 2001–2018 which agrees closely with current bottom-up land surface models (102–181 TgCH4 y−1) and overlaps with top-down atmospheric inversion models (155–200 TgCH4 y−1). However, UpCH4 diverged from both types of models in the spatial pattern and seasonal dynamics of tropical wetland emissions. We conclude that upscaling of eddy covariance CH4 fluxes has the potential to produce realistic extra-tropical wetland CH4 emissions estimates which will improve with more flux data. To reduce uncertainty in upscaled estimates, researchers could prioritize new wetland flux sites along humid-to-arid tropical climate gradients, from major rainforest basins (Congo, Amazon, and SE Asia), into monsoon (Bangladesh and India) and savannah regions (African Sahel) and be paired with improved knowledge of wetland extent seasonal dynamics in these regions. The monthly wetland methane products gridded at 0.25° from UpCH4 are available via ORNL DAAC (https://doi.org/10.3334/ORNLDAAC/2253)

Results of the West Nile Fever Agent Monitoring in the Russian Federation in 2019 and the Forecast of Epidemic Situation Development in 2020

The trend towards an increase in the West Nile fever incidence among the population in the Russian Federation, recorded in the season of 2018, continued and led to a significant increase in the incidence in 2019 (the indicator was 2 times higher than the long-term average). The features of manifestations of the epidemiological process of WNF in 2019 were identified: early registration of cases of the disease, activation of natural and natural-anthropourgic foci in the Southern Federal District (90 % of the total incidence in the Russian Federation), an increase in the share of neuro-invasive forms, dominance of patients aged 50 and older in the structure of the incidence, late epidemic season ending. It was established that in the season of 2019, the lineage 2 of WNV circulated in the European part of Russia. In the Volgograd Region, simultaneous presence of the West Nile virus and Sindbis virus in mosquitoes Culex pipiens and Culex modestus was identified. It was shown that the most significant factors for predicting the epidemiological situation on West Nile fever in the Volgograd Region are the average seasonal summer air temperature and monthly average indicators of relative humidity in the spring and summer periods, and the average monthly air temperatures in the spring and summer in the Rostov Region. In the Astrakhan Region, a significant correlation dependence of the influence of the considered factors on the incidence of the population has not been established. The forecast of the development of epidemic situation in 2020 does not exclude a possible increase in the incidence in the territories of the European part of Russia, endemic for West Nile fever, and the occurrence of local outbreaks in individual constituent entities, if the complex of climatic conditions and social factors favorable for West Nile virus coincide

Warming response of peatland CO2 sink is sensitive to seasonality in warming trends

Peatlands have acted as net CO2 sinks over millennia, exerting a global climate cooling effect. Rapid warming at northern latitudes, where peatlands are abundant, can disturb their CO2 sink function. Here we show that sensitivity of peatland net CO2 exchange to warming changes in sign and magnitude across seasons, resulting in complex net CO2 sink responses. We use multiannual net CO2 exchange observations from 20 northern peatlands to show that warmer early summers are linked to increased net CO2 uptake, while warmer late summers lead to decreased net CO2 uptake. Thus, net CO2 sinks of peatlands in regions experiencing early summer warming, such as central Siberia, are more likely to persist under warmer climate conditions than are those in other regions. Our results will be useful to improve the design of future warming experiments and to better interpret large-scale trends in peatland net CO2 uptake over the coming few decades

Warming response of peatland CO2 sink is sensitive to seasonality in warming trends

Peatlands have acted as net CO2 sinks over millennia, exerting a global climate cooling effect. Rapid warming at northern latitudes, where peatlands are abundant, can disturb their CO2 sink function. Here we show that sensitivity of peatland net CO2 exchange to warming changes in sign and magnitude across seasons, resulting in complex net CO2 sink responses. We use multiannual net CO2 exchange observations from 20 northern peatlands to show that warmer early summers are linked to increased net CO2 uptake, while warmer late summers lead to decreased net CO2 uptake. Thus, net CO2 sinks of peatlands in regions experiencing early summer warming, such as central Siberia, are more likely to persist under warmer climate conditions than are those in other regions. Our results will be useful to improve the design of future warming experiments and to better interpret large-scale trends in peatland net CO2 uptake over the coming few decades