Publications by authors named "Dmitry Schepaschenko"

Naturally regenerated forests and managed tree systems provide different levels of carbon, biodiversity, and livelihood benefits. Here, we show that tree cover gains in the moist tropics during 1982-2015 were 56% ± 3% naturally regenerated forests and 27% ± 2.6% managed tree systems, with these differences in forest type, not only natural conditions (climate, soil, and topography), driving observed carbon recovery rates.

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Unraveling the mechanisms underlying the maintenance of species diversity is a central pursuit in ecology. It has been hypothesized that ectomycorrhizal (EcM) in contrast to arbuscular mycorrhizal fungi can reduce tree species diversity in local communities, which remains to be tested at the global scale. To address this gap, we analyzed global forest inventory data and revealed that the relationship between tree species richness and EcM tree proportion varied along environmental gradients.

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Species' traits and environmental conditions determine the abundance of tree species across the globe. The extent to which traits of dominant and rare tree species differ remains untested across a broad environmental range, limiting our understanding of how species traits and the environment shape forest functional composition. We use a global dataset of tree composition of >22,000 forest plots and 11 traits of 1663 tree species to ask how locally dominant and rare species differ in their trait values, and how these differences are driven by climatic gradients in temperature and water availability in forest biomes across the globe.

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As more satellite imagery has become openly available, efforts in mapping the Earth's surface have accelerated. Yet the accuracy of these maps is still limited by the lack of data needed to train machine learning algorithms. Citizen science has proven to be a valuable approach for collecting data through applications like Geo-Wiki and Picture Pile, but better approaches for optimizing volunteer time are still required.

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Boreal forests form the largest terrestrial biome globally. Climate change is expected to induce large changes in vegetation of high latitude ecosystems, but there is considerable uncertainty about where, when, and how those changes will occur. Such vegetation change produces major feedback to the climate system, including by modifying albedo (reflectivity).

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Article Synopsis
  • * Analysis of data from over 1 million forest plots and thousands of tree species shows that wood density varies significantly by latitude, being up to 30% denser in tropical forests compared to boreal forests, and is influenced mainly by temperature and soil moisture.
  • * The research also finds that disturbances like human activity and fire alter wood density at local levels, affecting forest carbon stock estimates by up to 21%, emphasizing the importance of understanding environmental impacts on forest ecosystems.
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The uptake of carbon dioxide (CO) by terrestrial ecosystems is critical for moderating climate change. To provide a ground-based long-term assessment of the contribution of forests to terrestrial CO uptake, we synthesized in situ forest data from boreal, temperate and tropical biomes spanning three decades. We found that the carbon sink in global forests was steady, at 3.

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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.

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Since 24 February 2022, Ukraine has experienced full-scale military aggression initiated by the Russian Federation. The war has had a major negative impact on vegetation cover of war-affected regions. We explored interactions between pre-war forest management and the impacts of military activities in three of the most forested Ukrainian areas of interest (AOI), affected by the war.

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Forests are a substantial terrestrial carbon sink, but anthropogenic changes in land use and climate have considerably reduced the scale of this system. Remote-sensing estimates to quantify carbon losses from global forests are characterized by considerable uncertainty and we lack a comprehensive ground-sourced evaluation to benchmark these estimates. Here we combine several ground-sourced and satellite-derived approaches to evaluate the scale of the global forest carbon potential outside agricultural and urban lands.

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Understanding what controls global leaf type variation in trees is crucial for comprehending their role in terrestrial ecosystems, including carbon, water and nutrient dynamics. Yet our understanding of the factors influencing forest leaf types remains incomplete, leaving us uncertain about the global proportions of needle-leaved, broadleaved, evergreen and deciduous trees. To address these gaps, we conducted a global, ground-sourced assessment of forest leaf-type variation by integrating forest inventory data with comprehensive leaf form (broadleaf vs needle-leaf) and habit (evergreen vs deciduous) records.

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Determining the drivers of non-native plant invasions is critical for managing native ecosystems and limiting the spread of invasive species. Tree invasions in particular have been relatively overlooked, even though they have the potential to transform ecosystems and economies. Here, leveraging global tree databases, we explore how the phylogenetic and functional diversity of native tree communities, human pressure and the environment influence the establishment of non-native tree species and the subsequent invasion severity.

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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.

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Article Synopsis
  • The latitudinal diversity gradient (LDG) reflects a global trend showing that species richness typically increases towards the tropics, but understanding its causes has been challenging due to insufficient data.
  • A new high-resolution map of local tree species richness was created using extensive global forest inventory data and local biophysical factors, analyzing around 1.3 million sample plots.
  • Findings indicate that annual mean temperature is a significant predictor of tree species richness, aligning with the metabolic theory of biodiversity, but additional local factors also play a crucial role, especially in tropical regions.
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Article Synopsis
  • Spatially explicit data on global forest management is essential for understanding forest status and planning for sustainability and conservation efforts.
  • Researchers created a reference dataset and a detailed global forest management map, detailing different management classes like intact forests and plantations, using expert input and crowdsourcing.
  • The dataset includes 226,000 unique locations and utilizes PROBA-V satellite imagery to produce a 100m resolution map for 2015, achieving accuracy rates between 58% and 80%.
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During December 2020, a crowdsourcing campaign to understand what has been driving tropical forest loss during the past decade was undertaken. For 2 weeks, 58 participants from several countries reviewed almost 115 K unique locations in the tropics, identifying drivers of forest loss (derived from the Global Forest Watch map) between 2008 and 2019. Previous studies have produced global maps of drivers of forest loss, but the current campaign increased the resolution and the sample size across the tropics to provide a more accurate mapping of crucial factors leading to forest loss.

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One of the most fundamental questions in ecology is how many species inhabit the Earth. However, due to massive logistical and financial challenges and taxonomic difficulties connected to the species concept definition, the global numbers of species, including those of important and well-studied life forms such as trees, still remain largely unknown. Here, based on global ground-sourced data, we estimate the total tree species richness at global, continental, and biome levels.

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To meet the ambitious objectives of biodiversity and climate conventions, the international community requires clarity on how these objectives can be operationalized spatially and how multiple targets can be pursued concurrently. To support goal setting and the implementation of international strategies and action plans, spatial guidance is needed to identify which land areas have the potential to generate the greatest synergies between conserving biodiversity and nature's contributions to people. Here we present results from a joint optimization that minimizes the number of threatened species, maximizes carbon retention and water quality regulation, and ranks terrestrial conservation priorities globally.

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Since the collapse of the Soviet Union and transition to a new forest inventory system, Russia has reported almost no change in growing stock (+ 1.8%) and biomass (+ 0.6%).

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Forest biomass is an essential indicator for monitoring the Earth's ecosystems and climate. It is a critical input to greenhouse gas accounting, estimation of carbon losses and forest degradation, assessment of renewable energy potential, and for developing climate change mitigation policies such as REDD+, among others. Wall-to-wall mapping of aboveground biomass (AGB) is now possible with satellite remote sensing (RS).

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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.

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Knowledge of the spatial distribution of agricultural abandonment following the collapse of the Soviet Union is highly uncertain. To help improve this situation, we have developed a new map of arable and abandoned land for 2010 at a 10 arc-second resolution. We have fused together existing land cover and land use maps at different temporal and spatial scales for the former Soviet Union (fSU) using a training data set collected from visual interpretation of very high resolution (VHR) imagery.

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