Publications by authors named "Martin Herold"

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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Aboveground biomass density (AGBD) estimates from Earth Observation (EO) can be presented with the consistency standards mandated by United Nations Framework Convention on Climate Change (UNFCCC). This article delivers AGBD estimates, in the format of Intergovernmental Panel on Climate Change (IPCC) Tier 1 values for natural forests, sourced from National Aeronautics and Space Administration's (NASA's) Global Ecosystem Dynamics Investigation (GEDI) and Ice, Cloud and land Elevation Satellite (ICESat-2), and European Space Agency's (ESA's) Climate Change Initiative (CCI). It also provides the underlying classification used by the IPCC as geospatial layers, delineating global forests by ecozones, continents and status (primary, young (≤20 years) and old secondary (>20 years)).

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Countries within the tropics face ongoing challenges in completing or updating their national forest inventories (NFIs), critical for estimating aboveground biomass (AGB) and for forest-related greenhouse gas (GHG) accounting. While previous studies have explored the integration of map information with local reference data to fill in data gaps, limited attention has been given to the specific challenges presented by the clustered plot designs frequently employed by NFIs when combined with remote sensing-based biomass map units. This research addresses these complexities by conducting four country case-studies, encompassing a variety of NFI characteristics within a range of AGB densities.

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Climate change and increasing human activities are impacting ecosystems and their biodiversity. Quantitative measurements of essential biodiversity variables (EBV) and essential climate variables are used to monitor biodiversity and carbon dynamics and evaluate policy and management interventions. Ecosystem structure is at the core of EBVs and carbon stock estimation and can help to inform assessments of species and species diversity.

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The article presents results of using remote sensing images and machine learning to map and assess land potential based on time-series of potential Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) composites. Land potential here refers to the potential vegetation productivity in the hypothetical absence of short-term anthropogenic influence, such as intensive agriculture and urbanization. Knowledge on this ecological land potential could support the assessment of levels of land degradation as well as restoration potentials.

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African forest are increasingly in decline as a result of land-use conversion due to human activities. However, a consistent and detailed characterization and mapping of land-use change that results in forest loss is not available at the spatial-temporal resolution and thematic levels suitable for decision-making at the local and regional scales; so far they have only been provided on coarser scales and restricted to humid forests. Here we present the first high-resolution (5 m) and continental-scale mapping of land use following deforestation in Africa, which covers an estimated 13.

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Article Synopsis
  • The study examines variations in anthropogenic carbon net flux estimates from land, focusing on how definitions of "managed" vs. "unmanaged" forest land influence these calculations, using global Earth Observation datasets for accuracy.
  • In Brazil, from 2001 to 2020, Earth Observation (EO) data classified Brazil as a net carbon sink, while national reports indicated a net carbon source, highlighting discrepancies that can be traced back to differing methodologies and factors used in both datasets.
  • Results from Indonesia showed similar estimates between EO and national reports, but Malaysia revealed significant differences in both magnitude and sign, illustrating the complexities in accurately measuring forest carbon fluxes due to lack of detailed forest type data
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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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Tyrosine kinase 2 (TYK2) is a nonreceptor tyrosine kinase that belongs to the JAK family also comprising JAK1, JAK2, and JAK3. TYK2 is an attractive target for various autoimmune diseases as it regulates signal transduction downstream of IL-23 and IL-12 receptors. Selective TYK2 inhibition offers a differentiated clinical profile compared to currently approved JAK inhibitors.

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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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Countries have pledged to different national and international environmental agreements, most prominently the climate change mitigation targets of the Paris Agreement. Accounting for carbon stocks and flows (fluxes) is essential for countries that have recently adopted the United Nations System of Environmental-Economic Accounting - ecosystem accounting framework (UNSEEA) as a global statistical standard. In this paper, we analyze how spatial carbon fluxes can be used in support of the UNSEEA carbon accounts in five case countries with available in-situ data.

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Article Synopsis
  • Planted forests play a vital role in combating climate change and provide essential timber, non-timber products, and ecosystem services, with East Asia housing about 36% of these forests globally.
  • Despite their significance, detailed information on the geographic distribution and tree species composition of these forests has been lacking.
  • This study presents the first comprehensive spatial database of planted forests in East Asia, highlighting that China contributes 87% of the predicted 948,863 km² area, and offers accurate maps that enhance understanding of these forests' contributions to climate change mitigation and inform conservation strategies.
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Space-based remote sensing can make an important contribution toward monitoring greenhouse gas emissions and removals from the agriculture, forestry, and other land use (AFOLU) sector, and to understanding and addressing human-caused climate change through the UNFCCC Paris Agreement. Space agencies have begun to coordinate their efforts to identify needs, collect and harmonize available data and efforts, and plan and maintain a long-term roadmap for observations. International cooperation is crucial in developing and realizing the roadmap, and the Committee on Earth Observation Satellites (CEOS) is a key coordinating driver of this effort.

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Amazonian forests function as biomass and biodiversity reservoirs, contributing to climate change mitigation. While they continuously experience disturbance, the effect that disturbances have on biomass and biodiversity over time has not yet been assessed at a large scale. Here, we evaluate the degree of recent forest disturbance in Peruvian Amazonia and the effects that disturbance, environmental conditions and human use have on biomass and biodiversity in disturbed forests.

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Multiple sclerosis (MS) is a focal inflammatory and demyelinating disease. The inflammatory infiltrates consist of macrophages/microglia, T and B cells. Remyelination (RM) is an endogenous repair process which frequently fails in MS patients.

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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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Tropical deforestation continues at alarming rates with profound impacts on ecosystems, climate, and livelihoods, prompting renewed commitments to halt its continuation. Although it is well established that agriculture is a dominant driver of deforestation, rates and mechanisms remain disputed and often lack a clear evidence base. We synthesize the best available pantropical evidence to provide clarity on how agriculture drives deforestation.

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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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National forest inventories (NFIs) are a reliable source for national forest measurements. However, they are usually not developed for linking with remotely sensed (RS) biomass information. There are increasing needs and opportunities to facilitate this link towards better global and national biomass estimation.

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This article describes a data-driven framework based on spatiotemporal machine learning to produce distribution maps for 16 tree species ( Mill., Mill., L.

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Background: Atrial fibrillation (AF) affects 46.3 million people; its prevalence has tripled over the last 50 years. AF leads to formation of blood clots increasing four-fold the risk of a stroke.

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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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