The multiple-use of forests and the ecosystem services may generate higher returns than agricultural land rent in Ukrainian Polissya - Andrii Bilous; Roman Zadorozhniuk; Valentyn Bilous; Petro Diachuk; Oleksandr Labenko; Svitlana Bilous; Andrii Lashko; Yaroslav Kovbasa; Oleksandr Hrytsenko; Dmitry Schepaschenko; Fulvio Di Fulvio; Anatoly Shvidenko; et al. (European Journal of Forest Research, 2026)
Ecosystem service flows are acquiring paramount importance in designing land use policies, the setting local development priorities and social fabric in rural areas. Understanding the dynamics of the monetary value of forest ecosystem services (ES) is important for guiding private landowners in selecting appropriate management alternatives and motivating them to adopt multiple-use forest practices and expand forest cover, according to the New EU Forest Strategy for 2030. In this study, we estimated the spatio-temporal changes in biophysical parameters and the potential annual revenue from four major forest ES within a typical area of the Polissya region, Ukraine. The assessed ES included wood supply, CO 2 sequestration, mushroom and wild berry harvesting, and hunting. We further assessed the competitiveness of income generated under different combinations of ecosystem service utilization and forest regeneration types, comparing it to agricultural land rent using equivalent annual income valuation. We found that the total annual monetary flow from these ES increased by 19.3%, mostly due to forest land expansion and changes in forest structure of study area. On average, provisioning ES (both wood and non-wood forest products) contribute up to 90% of the total annual revenue, with similar contributions from each. This study underscores the competitive potential of forestry utilizing various ES as a viable land-use alternative for local landowners, with the highest expected discount rate of 2.3–3.5%. Our results highlight how forest-based management can serve as a key strategy for increasing forest cover while ensuring economic sustainability at the local level.

Climate change threatens the sustainability of current timber harvesting practices across a latitudinal gradient in Siberia - Eric J. Gustafson; Melissa S. Lucash; Anatoly Z. Shvidenko; Brian R. Sturtevant; Dmitry Schepaschenko; Colin Mast; Neil Williams (European Journal of Forest Research, 2025)

Climate change and disturbance interact to alter landscape reflectivity (albedo) in boreal forests across a large latitudinal gradient in Siberia - Eric J. Gustafson; Melissa S. Lucash; Anatoly Z. Shvidenko; Brian R. Sturtevant; Brian R. Miranda; Dmitry Schepaschenko; Hana Matsumoto (Science of The Total Environment, 2024)

Dominance and rarity in tree communities across the globe: Patterns, predictors and threats - Iris Hordijk; Lalasia Bialic‐Murphy; Thomas Lauber; Devin Routh; Lourens Poorter; Malin C. Rivers; Hans ter Steege; Jingjing Liang; Peter B. Reich; Sergio de‐Miguel; Gert‐Jan Nabuurs; Javier G. P. Gamarra; et al. (Global Ecology and Biogeography, 2024)
Aim Ecological and anthropogenic factors shift the abundances of dominant and rare tree species within local forest communities, thus affecting species composition and ecosystem functioning. To inform forest and conservation management it is important to understand the drivers of dominance and rarity in local tree communities. We answer the following research questions: (1) What are the patterns of dominance and rarity in tree communities? (2) Which ecological and anthropogenic factors predict these patterns? And (3) what is the extinction risk of locally dominant and rare tree species? Location Global. Time period 1990–2017. Major taxa studied Trees. Methods We used 1.2 million forest plots and quantified local tree dominance as the relative plot basal area of the single most dominant species and local rarity as the percentage of species that contribute together to the least 10% of plot basal area. We mapped global community dominance and rarity using machine learning models and evaluated the ecological and anthropogenic predictors with linear models. Extinction risk, for example threatened status, of geographically widespread dominant and rare species was evaluated. Results Community dominance and rarity show contrasting latitudinal trends, with boreal forests having high levels of dominance and tropical forests having high levels of rarity. Increasing annual precipitation reduces community dominance, probably because precipitation is related to an increase in tree density and richness. Additionally, stand age is positively related to community dominance, due to stem diameter increase of the most dominant species. Surprisingly, we find that locally dominant and rare species, which are geographically widespread in our data, have an equally high rate of elevated extinction due to declining populations through large‐scale land degradation. Main conclusions By linking patterns and predictors of community dominance and rarity to extinction risk, our results suggest that also widespread species should be considered in large‐scale management and conservation practices.

Global patterns of tree wood density - Hui Yang; Siyuan Wang; Rackhun Son; Hoontaek Lee; Vitus Benson; Weijie Zhang; Yahai Zhang; Yuzhen Zhang; Jens Kattge; Gerhard Boenisch; Dmitry Schepaschenko; Zbigniew Karaszewski; et al. (Global Change Biology, 2024)
Wood density is a fundamental property related to tree biomechanics and hydraulic function while playing a crucial role in assessing vegetation carbon stocks by linking volumetric retrieval and a mass estimate. This study provides a high‐resolution map of the global distribution of tree wood density at the 0.01° (~1 km) spatial resolution, derived from four decision trees machine learning models using a global database of 28,822 tree‐level wood density measurements. An ensemble of four top‐performing models combined with eight cross‐validation strategies shows great consistency, providing wood density patterns with pronounced spatial heterogeneity. The global pattern shows lower wood density values in northern and northwestern Europe, Canadian forest regions and slightly higher values in Siberia forests, western United States, and southern China. In contrast, tropical regions, especially wet tropical areas, exhibit high wood density. Climatic predictors explain 49%–63% of spatial variations, followed by vegetation characteristics (25%–31%) and edaphic properties (11%–16%). Notably, leaf type (evergreen vs. deciduous) and leaf habit type (broadleaved vs. needleleaved) are the most dominant individual features among all selected predictive covariates. Wood density tends to be higher for angiosperm broadleaf trees compared to gymnosperm needleleaf trees, particularly for evergreen species. The distributions of wood density categorized by leaf types and leaf habit types have good agreement with the features observed in wood density measurements. This global map quantifying wood density distribution can help improve accurate predictions of forest carbon stocks, providing deeper insights into ecosystem functioning and carbon cycling such as forest vulnerability to hydraulic and thermal stresses in the context of future climate change.

Global patterns and environmental drivers of forest functional composition - Elise Bouchard; Eric B. Searle; Pierre Drapeau; Jingjing Liang; Javier G. P. Gamarra; Meinrad Abegg; Giorgio Alberti; Angelica Almeyda Zambrano; Esteban Alvarez‐Davila; Luciana F. Alves; Valerio Avitabile; Gerardo Aymard; et al. (Global Ecology and Biogeography, 2024)
Aim To determine the relationships between the functional trait composition of forest communities and environmental gradients across scales and biomes and the role of species relative abundances in these relationships. Location Global. Time period Recent. Major taxa studied Trees. Methods We integrated species abundance records from worldwide forest inventories and associated functional traits (wood density, specific leaf area and seed mass) to obtain a data set of 99,953 to 149,285 plots (depending on the trait) spanning all forested continents. We computed community‐weighted and unweighted means of trait values for each plot and related them to three broad environmental gradients and their interactions (energy availability, precipitation and soil properties) at two scales (global and biomes). Results Our models explained up to 60% of the variance in trait distribution. At global scale, the energy gradient had the strongest influence on traits. However, within‐biome models revealed different relationships among biomes. Notably, the functional composition of tropical forests was more influenced by precipitation and soil properties than energy availability, whereas temperate forests showed the opposite pattern. Depending on the trait studied, response to gradients was more variable and proportionally weaker in boreal forests. Community unweighted means were better predicted than weighted means for almost all models. Main conclusions Worldwide, trees require a large amount of energy (following latitude) to produce dense wood and seeds, while leaves with large surface to weight ratios are concentrated in temperate forests. However, patterns of functional composition within‐biome differ from global patterns due to biome specificities such as the presence of conifers or unique combinations of climatic and soil properties. We recommend assessing the sensitivity of tree functional traits to environmental changes in their geographic context. Furthermore, at a given site, the distribution of tree functional traits appears to be driven more by species presence than species abundance.

Pantropical distribution of short-rotation woody plantations: spatial probabilities under current and future climate - Katharina Schulze; Žiga Malek; Dmitry Schepaschenko; Myroslava Lesiv; Steffen Fritz; Peter H. Verburg (Mitigation and Adaptation Strategies for Global Change, 2023)
Short-rotation woody plantations (SRWPs) play a major role in climate change mitigation and adaptation plans, because of their high yields of woody biomass and fast carbon storage. However, their benefits, trade-offs and growing-success are heavily location-dependent. Therefore, spatial data on the distribution of SRWPs are indispensable for assessing current distribution, trade-offs with other uses and potential contributions to climate mitigation. As current global datasets lack reliable information on SRWPs and full global mapping is difficult, we provide a consistent and systematic approach to estimate the spatial distribution of SRWPs in (sub-)tropical biomes under current and future climate. We combined three advanced methods (maximum entropy, random forest and multinomial regression) to evaluate spatially explicit probabilities of SRWPs. As inputs served a large empirical dataset on SRWP observations and 17 predictor variables, covering biophysical and socio-economic conditions. SRWP probabilities varied strongly between regions, and might not be feasible in major parts of (sub-)tropical biomes, challenging the feasibility of global mitigation plans that over-rely on tree plantations. Due to future climatic changes, SRWP probabilities decreased in many areas, particularly pronounced in higher emission scenarios. This indicates a negative feedback with higher emissions resulting in less mitigation potential. Less suitable land for SRWPs in the future could also result in fewer wood resources from these plantations, enhancing pressure on natural forests and hampering sustainability initiatives that use wood-based alternatives. Our results can help adding a more nuanced treatment of mitigation options and forest management in research on biodiversity and land use change.

Toward a forest biomass reference measurement system for remote sensing applications - Nicolas Labrière; Stuart J. Davies; Mathias I. Disney; Laura I. Duncanson; Martin Herold; Simon L. Lewis; Oliver L. Phillips; Shaun Quegan; Sassan S. Saatchi; Dmitry G. Schepaschenko; Klaus Scipal; Plinio Sist; et al. (Global Change Biology, 2023)
Forests contribute to climate change mitigation through carbon storage and uptake, but the extent to which this carbon pool varies in space and time is still poorly known. Several Earth Observation missions have been specifically designed to address this issue, for example, NASA's GEDI, NASA‐ISRO's NISAR and ESA's BIOMASS. Yet, all these missions' products require independent and consistent validation. A permanent, global, in situ, site‐based forest biomass reference measurement system relying on ground data of the highest possible quality is therefore needed. Here, we have assembled a list of almost 200 high‐quality sites through an in‐depth review of the literature and expert knowledge. In this study, we explore how representative these sites are in terms of their coverage of environmental conditions, geographical space and biomass‐related forest structure, compared to those experienced by forests worldwide. This work also aims at identifying which sites are the most representative, and where to invest to improve the representativeness of the proposed system. We show that the environmental coverage of the system does not seem to improve after at least the 175 most representative sites are included, but geographical and structural coverages continue to improve as more sites are added. We highlight the areas of poor environmental, geographical, or structural coverage, including, but not limited to, Canada, the western half of the USA, Mexico, Patagonia, Angola, Zambia, eastern Russia, and tropical and subtropical highlands (e.g. in Colombia, the Himalayas, Borneo, Papua). For the proposed system to succeed, we stress that (1) data must be collected and processed applying the same standards across all countries and continents; (2) system establishment and management must be inclusive and equitable, with careful consideration of working conditions; and (3) training and site partner involvement in downstream activities should be mandatory.

A spatial assessment of the forest carbon budget for Ukraine - Myroslava Lesiv; Anatoly Shvidenko; Dmitry Schepaschenko; Linda See; Steffen Fritz (Mitigation and Adaptation Strategies for Global Change, 2019)

Recent Advances in Forest Observation with Visual Interpretation of Very High-Resolution Imagery - Dmitry Schepaschenko; Linda See; Myroslava Lesiv; Jean-François Bastin; Danilo Mollicone; Nandin-Erdene Tsendbazar; Lucy Bastin; Ian McCallum; Juan Carlos Laso Bayas; Artem Baklanov; Christoph Perger; Martina Dürauer; et al. (Surveys in Geophysics, 2019)

Ground Data are Essential for Biomass Remote Sensing Missions - Jérôme Chave; Stuart J. Davies; Oliver L. Phillips; Simon L. Lewis; Plinio Sist; Dmitry Schepaschenko; John Armston; Tim R. Baker; David Coomes; Mathias Disney; Laura Duncanson; Bruno Hérault; et al. (Surveys in Geophysics, 2019)

Estimating the global distribution of field size using crowdsourcing - Myroslava Lesiv; Juan Carlos Laso Bayas; Linda See; Martina Duerauer; Domian Dahlia; Neal Durando; Rubul Hazarika; Parag Kumar Sahariah; Mar'yana Vakolyuk; Volodymyr Blyshchyk; Andrii Bilous; Ana Perez‐Hoyos; et al. (Global Change Biology, 2019)
There is an increasing evidence that smallholder farms contribute substantially to food production globally, yet spatially explicit data on agricultural field sizes are currently lacking. Automated field size delineation using remote sensing or the estimation of average farm size at subnational level using census data are two approaches that have been used. However, both have limitations, for example, automatic field size delineation using remote sensing has not yet been implemented at a global scale while the spatial resolution is very coarse when using census data. This paper demonstrates a unique approach to quantifying and mapping agricultural field size globally using crowdsourcing. A campaign was run in June 2017, where participants were asked to visually interpret very high resolution satellite imagery from Google Maps and Bing using the Geo‐Wiki application. During the campaign, participants collected field size data for 130 K unique locations around the globe. Using this sample, we have produced the most accurate global field size map to date and estimated the percentage of different field sizes, ranging from very small to very large, in agricultural areas at global, continental, and national levels. The results show that smallholder farms occupy up to 40% of agricultural areas globally, which means that, potentially, there are many more smallholder farms in comparison with the two different current global estimates of 12% and 24%. The global field size map and the crowdsourced data set are openly available and can be used for integrated assessment modeling, comparative studies of agricultural dynamics across different contexts, for training and validation of remote sensing field size delineation, and potential contributions to the Sustainable Development Goal of Ending hunger, achieve food security and improved nutrition and promote sustainable agriculture.

Mapping global cropland and field size - Steffen Fritz; Linda See; Ian McCallum; Liangzhi You; Andriy Bun; Elena Moltchanova; Martina Duerauer; Fransizka Albrecht; Christian Schill; Christoph Perger; Petr Havlik; Aline Mosnier; et al. (Global Change Biology, 2015)
A new 1 km global IIASA ‐ IFPRI cropland percentage map for the baseline year 2005 has been developed which integrates a number of individual cropland maps at global to regional to national scales. The individual map products include existing global land cover maps such as GlobCover 2005 and MODIS v.5, regional maps such as AFRICOVER and national maps from mapping agencies and other organizations. The different products are ranked at the national level using crowdsourced data from Geo‐Wiki to create a map that reflects the likelihood of cropland. Calibration with national and subnational crop statistics was then undertaken to distribute the cropland within each country and subnational unit. The new IIASA ‐ IFPRI cropland product has been validated using very high‐resolution satellite imagery via Geo‐Wiki and has an overall accuracy of 82.4%. It has also been compared with the EarthStat cropland product and shows a lower root mean square error on an independent data set collected from Geo‐Wiki. The first ever global field size map was produced at the same resolution as the IIASA ‐ IFPRI cropland map based on interpolation of field size data collected via a Geo‐Wiki crowdsourcing campaign. A validation exercise of the global field size map revealed satisfactory agreement with control data, particularly given the relatively modest size of the field size data set used to create the map. Both are critical inputs to global agricultural monitoring in the frame of GEOGLAM and will serve the global land modelling and integrated assessment community, in particular for improving land use models that require baseline cropland information. These products are freely available for downloading from the http://cropland.geo-wiki.org website.

Carbon stock and density of northern boreal and temperate forests - Martin Thurner; Christian Beer; Maurizio Santoro; Nuno Carvalhais; Thomas Wutzler; Dmitry Schepaschenko; Anatoly Shvidenko; Elisabeth Kompter; Bernhard Ahrens; Shaun R. Levick; Christiane Schmullius (Global Ecology and Biogeography, 2014)
Aim To infer a forest carbon density map at 0.01° resolution from a radar remote sensing product for the estimation of carbon stocks in Northern Hemisphere boreal and temperate forests. Location The study area extends from 30° N to 80° N , covering three forest biomes – temperate broadleaf and mixed forests ( TBMF ), temperate conifer forests ( TCF ) and boreal forests ( BFT ) – over three continents ( N orth A merica, E urope and A sia). Methods This study is based on a recently available growing stock volume ( GSV ) product retrieved from synthetic aperture radar data. Forest biomass and spatially explicit uncertainty estimates were derived from the GSV using existing databases of wood density and allometric relationships between biomass compartments (stem, branches, roots, foliage). We tested the resultant map against inventory‐based biomass data from R ussia, Europe and the USA prior to making intercontinent and interbiome carbon stock comparisons. Results Our derived carbon density map agrees well with inventory data at regional scales ( r 2 = 0.70–0.90). While 40.7 ± 15.7 petagram of carbon ( P g C ) are stored in BFT , TBMF and TCF contain 24.5 ± 9.4 P g C and 14.5 ± 4.8 P g C , respectively. In terms of carbon density, we found 6.21 ± 2.07 kg C m −2 retained in TCF and 5.80 ± 2.21 kg C m −2 in TBMF , whereas BFT have a mean carbon density of 4.00 ± 1.54 kg C m −2 . Indications of a higher carbon density in Europe compared with the other continents across each of the three biomes could not be proved to be significant. Main conclusions The presented carbon density and corresponding uncertainty map give an insight into the spatial patterns of biomass and stand as a new benchmark to improve carbon cycle models and carbon monitoring systems. In total, we found 79.8 ± 29.9 P g C stored in northern boreal and temperate forests, with Asian BFT accounting for 22.1 ± 8.3 P g C .

Can the uncertainty of full carbon accounting of forest ecosystems be made acceptable to policymakers? - Anatoly Shvidenko; Dmitry Schepaschenko; Ian McCallum; Sten Nilsson (Climatic Change, 2010)

Selection of Indices for the Monitoring of Spruce Forests within Impact Zone of the Metallurgical Enterprise - Tatiana Tokareva; Dmitry Schepaschenko (Water, Air, & Soil Pollution, 2000)