Volodymyr Trotsiuk

Last Name

Trotsiuk

First Name

Volodymyr

ORCID

0000-0002-8363-656X

Show all metadata

Search Results

Publications 1 - 10 of 38

Disentangling the multi-faceted growth patterns of primary Picea abies forests in the Carpathian arc
Björklund, Jesper; Rydval, Miloš; Schurman, Jonathan S.; et al. (2019)
Agricultural and Forest Meteorology
No Future Growth Enhancement Expected at the Northern Edge for European Beech due to Continued Water Limitation
Klesse, Stefan; Peters, Richard L.; Alfaro-Sánchez, Raquel; et al. (2024)
Global Change Biology
With ongoing global warming, increasing water deficits promote physiological stress on forest ecosystems with negative impacts on tree growth, vitality, and survival. How individual tree species will react to increased drought stress is therefore a key research question to address for carbon accounting and the development of climate change mitigation strategies. Recent tree-ring studies have shown that trees at higher latitudes will benefit from warmer temperatures, yet this is likely highly species-dependent and less well-known for more temperate tree species. Using a unique pan-European tree-ring network of 26,430 European beech (Fagus sylvatica L.) trees from 2118 sites, we applied a linear mixed-effects modeling framework to (i) explain variation in climate-dependent growth and (ii) project growth for the near future (2021–2050) across the entire distribution of beech. We modeled the spatial pattern of radial growth responses to annually varying climate as a function of mean climate conditions (mean annual temperature, mean annual climatic water balance, and continentality). Over the calibration period (1952–2011), the model yielded high regional explanatory power (R² = 0.38–0.72). Considering a moderate climate change scenario (CMIP6 SSP2-4.5), beech growth is projected to decrease in the future across most of its distribution range. In particular, projected growth decreases by 12%–18% (interquartile range) in northwestern Central Europe and by 11%–21% in the Mediterranean region. In contrast, climate-driven growth increases are limited to around 13% of the current occurrence, where the historical mean annual temperature was below ~6°C. More specifically, the model predicts a 3%–24% growth increase in the high-elevation clusters of the Alps and Carpathian Arc. Notably, we find little potential for future growth increases (−10 to +2%) at the poleward leading edge in southern Scandinavia. Because in this region beech growth is found to be primarily water-limited, a northward shift in its distributional range will be constrained by water availability.
Age structure and disturbance dynamics of the relic virgin beech forest Uholka (Ukrainian Carpathians)
Trotsiuk, Volodymyr; Hobi, Martina L.; Commarmot, Brigitte (2012)
Forest Ecology and Management
Finding the balance between open access to forest data while safeguarding the integrity of National Forest Inventory-derived information
Gessler, Arthur; Schaub, Marcus; Bose, Arun; et al. (2024)
New Phytologist
TreeNet–The Biological Drought and Growth Indicator Network
Zweifel, Roman; Etzold, Sophia; Basler, David; et al. (2021)
Frontiers in Forests and Global Change
The TreeNet research and monitoring network has been continuously collecting data from point dendrometers and air and soil microclimate using an automated system since 2011. The goal of TreeNet is to generate high temporal resolution datasets of tree growth and tree water dynamics for research and to provide near real-time indicators of forest growth performance and drought stress to a wide audience. This paper explains the key working steps from the installation of sensors in the field to data acquisition, data transmission, data processing, and online visualization. Moreover, we discuss the underlying premises to convert dynamic stem size changes into relevant biological information. Every 10 min, the stem radii of about 420 trees from 13 species at 61 sites in Switzerland are measured electronically with micrometer precision, in parallel with the environmental conditions above and below ground. The data are automatically transmitted, processed and stored on a central server. Automated data processing (R-based functions) includes screening of outliers, interpolation of data gaps, and extraction of radial stem growth and water deficit for each tree. These long-term data are used for scientific investigations as well as to calculate and display daily indicators of growth trends and drought levels in Switzerland based on historical and current data. The current collection of over 100 million data points forms the basis for identifying dynamics of tree-, site- and species-specific processes along environmental gradients. TreeNet is one of the few forest networks capable of tracking the diurnal and seasonal cycles of tree physiology in near real-time, covering a wide range of temperate forest species and their respective environmental conditions.
Increased sensitivity to drought across successional stages in natural Norway spruce (Picea abies (L.) Karst.) forests of the Calimani Mountains, Romania
Svobodová, Kristýna; Langbehn, Thomas; Björklund, Jesper; et al. (2019)
Trees
Assessing the response of forest productivity to climate extremes in Switzerland using model–data fusion
Trotsiuk, Volodymyr; Hartig, Florian; Cailleret, Maxime; et al. (2020)
Global Change Biology
The response of forest productivity to climate extremes strongly depends on ambient environmental and site conditions. To better understand these relationships at a regional scale, we used nearly 800 observation years from 271 permanent long‐term forest monitoring plots across Switzerland, obtained between 1980 and 2017. We assimilated these data into the 3‐PG forest ecosystem model using Bayesian inference, reducing the bias of model predictions from 14% to 5% for forest stem carbon stocks and from 45% to 9% for stem carbon stock changes. We then estimated the productivity of forests dominated by Picea abies and Fagus sylvatica for the period of 1960–2018, and tested for productivity shifts in response to climate along elevational gradient and in extreme years. Simulated net primary productivity (NPP) decreased with elevation (2.86 ± 0.006 Mg C ha−1 year−1 km−1 for P. abies and 0.93 ± 0.010 Mg C ha−1 year−1 km−1 for F. sylvatica). During warm–dry extremes, simulated NPP for both species increased at higher and decreased at lower elevations, with reductions in NPP of more than 25% for up to 21% of the potential species distribution range in Switzerland. Reduced plant water availability had a stronger effect on NPP than temperature during warm‐dry extremes. Importantly, cold–dry extremes had negative impacts on regional forest NPP comparable to warm–dry extremes. Overall, our calibrated model suggests that the response of forest productivity to climate extremes is more complex than simple shift toward higher elevation. Such robust estimates of NPP are key for increasing our understanding of forests ecosystems carbon dynamics under climate extremes.
A Combined Tree Ring and Vegetation Model Assessment of European Forest Growth Sensitivity to Interannual Climate Variability
Klesse, Stefan; Babst, Flurin; Lienert, Sebastian; et al. (2018)
Global Biogeochemical Cycles
Testing the efficacy of tree-ring methods for detecting past disturbances
Trotsiuk, Volodymyr; Pederson, Neil; Druckenbrod, Daniel L.; et al. (2018)
Forest Ecology and Management
Advancing simulations of water fluxes, soil moisture and drought stress by using the LWF-Brook90 hydrological model in R
Schmidt-Walter, Paul; Trotsiuk, Volodymyr; Meusburger, Katrin; et al. (2020)
Agricultural and Forest Meteorology
Soil vegetation atmosphere transport (SVAT) models are important for the quantification of water fluxes, soil water availability, drought stress and their uncertainties under climate change. We present LWFBrook90R, an enhanced implementation of the well-established, process-based SVAT model LWF-Brook90 for the R environment for statistical computing. The package provides new functions and sub-models for model parameterization, and facilitates parallel computing, sensitivity analysis and inverse calibration of the model. A case study comprising i) basic forward water balance simulations for temperate grassland vegetation, deciduous and evergreen forest, ii) a parallelized sensitivity analysis, and iii) Bayesian calibrations based on soil water storage observed in a poplar (Populus nigra × P. maximowiczii) Short Rotation Forest (SRF) demonstrates the utility of the R package. The sensitivity analysis revealed parameters affecting plant-available soil water storage capacity and the vegetation's timing and level of water demand to be most important for the annual course of simulated soil water storage, with seasonal and interannual differences in parameter importance rankings. The subsequent calibration yielded a very high agreement between daily simulated and observed soil water storage (0-200 cm soil depth) for the calibration and validation datasets, with Nash-Sutcliffe efficiencies of 0.97 and 0.95, respectively. The final model predicted high though realistic rates of annual evapotranspiration (2011: 844 ± 3.8 mm y-1, 2012: 733 ± 4.5 mm y-1) for the poplar SRF, regularly exceeding grass reference evaporation (ET0) by 20-47% during the months of the growing season. However, basing calibrations solely on observed soil water storage probably resulted in biased partitioning of evapotranspiration towards interception losses. The integration of the LWF-Brook90 hydrological model into R with its wide variety of extensions was successfully tested and may provide efficient, reliable and reproducible water balance predictions by facilitating complex statistical analyses and large-scale applications of the model.

Publications 1 - 10 of 38

Volodymyr Trotsiuk

Last Name

First Name

ORCID

Organisational unit

Filters

Search Results