Nadja Tchebakova

The effects of climate, permafrost and fire on vegetation change in Siberia in a changing climate

Observations and general circulation model projections suggest significant temperature increases in Siberia this century that are expected to have profound effects on Siberian vegetation. Potential vegetation change across Siberia was modeled, coupling our Siberian BioClimatic Model with several Hadley Centre climate change scenarios for 2020, 2050 and 2080, with explicit consideration of permafrost and fire activity. In the warmer and drier climate projected by these scenarios, Siberian forests are predicted to decrease and shift northwards and forest?steppe and steppe ecosystems are predicted to dominate over half of Siberia due to the dryer climate by 2080. Despite the large predicted increases in warming, permafrost is not predicted to thaw deep enough to sustain dark (Pinus sibirica, Abies sibirica, and Picea obovata) taiga. Over eastern Siberia, larch (Larix dahurica) taiga is predicted to continue to be the dominant zonobiome because of its ability to withstand continuous permafrost. The model also predicts new temperate broadleaf forest and forest?steppe habitats by 2080. Potential fire danger evaluated with the annual number of high fire danger days (Nesterov index is 4000?10?000) is predicted to increase by 2080, especially in southern Siberia and central Yakutia. In a warming climate, fuel load accumulated due to replacement of forest by steppe together with frequent fire weather promotes high risks of large fires in southern Siberia and central Yakutia, where wild fires would create habitats for grasslands because the drier climate would no longer be suitable for forests.

Ecosystems and climate interactions in the boreal zone of northern Eurasia

The climate system and terrestrial ecosystems interact as they change. In northern Eurasia these interactions are especially strong, span all spatial and timescales, and thus have become the subject of an international program: the Northern Eurasia Earth Science Partnership Initiative (NEESPI). Without trying to cover all areas of these interactions, this paper introduces three examples of the principal micrometeorological, mesometeorological and subcontinental feedbacks that control climate–terrestrial ecosystem interactions in the boreal zone of northern Eurasia. Positive and negative feedbacks of forest paludification, of windthrow, and of climate-forced displacement of vegetation zones are presented. Moreover the interplay of different scale feedbacks, the multi-faceted nature of ecosystems–climate interactions and their potential to affect the global Earth system are shown. It is concluded that, without a synergetic modeling approach that integrates all major feedbacks and relationships between terrestrial ecosystems and climate, reliable projections of environmental change in northern Eurasia are impossible, which will also bring into question the accuracy of global change projections.

Evapotranspiration in Northern Eurasia: Impact of forcing uncertainties on terrestrial ecosystem model estimates

The ecosystems in Northern Eurasia (NE) play an important role in the global water cycle and the climate system. While evapotranspiration (ET) is a critical variable to understand this role, ET over this region remains largely unstudied. Using an improved version of the Terrestrial Ecosystem Model with five widely used forcing data sets, we examine the impact that uncertainties in climate forcing data have on the magnitude, variability, and dominant climatic drivers of ET for the period 1979–2008. Estimates of regional average ET vary in the range of 241.4–335.7 mm yr−1 depending on the choice of forcing data. This range corresponds to as much as 32% of the mean ET. Meanwhile, the spatial patterns of long-term average ET across NE are generally consistent for all forcing data sets. Our ET estimates in NE are largely affected by uncertainties in precipitation (P), air temperature (T), incoming shortwave radiation (R), and vapor pressure deficit (VPD). During the growing season, the correlations between ET and each forcing variable indicate that T is the dominant factor in the north and P in the south. Unsurprisingly, the uncertainties in climate forcing data propagate as well to estimates of the volume of water available for runoff (here defined as P-ET). While the Climate Research Unit data set is overall the best choice of forcing data in NE according to our assessment, the quality of these forcing data sets remains a major challenge to accurately quantify the regional water balance in NE.

Potential Climate-Induced Vegetation Change in Siberia in the Twenty-First Century

Siberian climate change investigations had already registered climate warming by the end of the twentieth century, especially over the decade of 1991–2000. Our goal is to model hot spots of potential climate-induced vegetation change across central Siberia for three time periods: from 1960 to 1990, from 1990 to 2020 and from 1990 to 2080. January and July temperature and annual precipitation anomalies between climatic means before 1960 and for the 1960–1990 period are calculated from the observed data across central Siberia. Anomalies for 2020 and 2080 are derived from two climate change scenarios HADCM3 A1FI and B1 of the Hadley Centre. Our Siberian bioclimatic model operates using three climate indices (degree-days above 5°C, degree-days below 0°C, annual moisture index) and permafrost active layer depth. These are mapped for 1990, 2020 and 2080 and then coupled with our bioclimatic models to predict vegetation distributions and “hot spots” of vegetation change for indicated time slices. Our analyses demonstrate the far-reaching effects of a changing climate on vegetation cover. Hot spots of potential Siberian vegetation change are predicted for 1990. Observations of vegetation change in Siberia have already been documented in the literature. Vegetation habitats should be significantly perturbed by 2020, and markedly perturbed by 2080. Because of a dryer climate, forest-steppe and steppe ecosystems, rather than forests, are predicted to dominate central Siberian landscapes. Despite the predicted increase in warming, permafrost is not predicted to thaw deep enough to support dark taiga over the Siberian plain, where the larch taiga will continue to be the dominant zonobiome. On the contrary, in the southern mountains in the absence of permafrost, dark taiga is predicted to remain the dominant orobiome.

Quantifying historical and future net exchanges of greenhouse gases of CO 2 , CH 4 and N 2 O between land and the atmosphere in Northern Eurasia

Qianlai Zhuang1, Tong Yu1, David W Kicklighter2, Jerry Melillo2, Yongxia Cai3, John Reilly3, Andrei Sokolov3, Erwan Monier3, Andrey Sirin3 Nadja Tchebakova4, V.N. Sukachev4, Shamil Maksyutov5 and Anatoly Shvidenko6 1Purdue University, USA 2The Ecosystems Center of the Marine Biological Laboratory, USA 3Massachusetts Institute of Technology, USA 4Russian Academy of Sciences, Russia 5National Institute for Environmental Studies, Japan 6International Institute for Applied Systems Analysis (IIASA), AustriaT study was aimed at assessing the profitability and constraints faced by fish farmers in the southern sector of Ghana. Four regions in the southern sector were selected, namely, Greater Accra, Volta, Western and Ashanti region. A standardized structured questionnaire were distributed among 320 respondents. A multiple linear regression analytical tool was employed to estimate the factors which affect profitability of fish farming while the Net Farm Income (NFI) analytical tool was used to analyse the cost and returns of fish farming. The weighted average formula was used together with the Kendall’s Coefficient of Concordance to analyse the constraints of fish farming. The data was analysed using SPSS (version 24) and STATA (version 14) software. Results from the study showed that farm ownership, educational level, access to market, FBO membership, and extension service significantly affect the profits of fish farming. However, the age, gender, form of sale of fish and type of market were not significant in influencing profit. The mean total cost, revenue and profit of GH₵ 6293.37, GH₵ 12859.44 and GH₵ 6566.07 were obtained respectively. The return on investment was 104.33%. The constraints analysis showed that, high cost of inputs and lack of clear government policies and incentives were the most pressing constraints faced. Aquaculture in the southern sector of Ghana is a profitable business venture, but it is normally on a small scale, and hence the need for commercialization. Aquaculture can greatly contribute to the total reduction in the short falls of demand and supply of fish products in the country and be a potential source of animal protein, income generation and employment. More extension officers should be deployed to the southern sector to educate fish farmers on the best fish farming practices. Government should build processing factories to facilitate fish storage, processing and marketing.T based approach are widely used in the study of different process (dispersal limitation, habitat filtering and limitation similarity) underlying community assembly. However, most researches are based on trait mean value, which only consider interspecific trait variation. Due to the genetic and environmental difference, functional trait can also exhibit significant intraspecific trait variation (ITV). Thus disentangle whether and how will the detection of relative importance of ecological process be influenced by the inclusion of ITV is of significant meaning for our understanding of community assembly. Here, we collected community composition data and 8 functional traits in a young (24-ha) and old (25-ha) growth forest plot. We analyzed the relative importance of different process based a recent developed modeling technique (STEPCAM). Moreover, we detect the effect of ITV on the relative importance with and without ITV. We found that dispersal limitation are most important at 20 m in two forest plot, followed by habitat filtering, and limiting similarity had minor effect. When taking ITV into consideration, the proportion of deterministic process (habitat filtering and limiting similarity) improved at early successional stage, while such effect was not found at late successional stage. Moreover, based on single trait, we found the deterministic process only improved for the nutrition absorb related trait when we consider of ITV at late successional stage, which imply the importance of soil condition on community assembly at this scale. In conclusion, our study highlights the importance of ITV for the detection of trait based ecological process in this temperate forest across successional stage.