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Spaceborne Canopy Height Products Should Be Complemented With Airborne Laser Scanning Data: Toward a European Canopy Height Model
No full textAbstract Measuring and mapping vegetation structure is essential for understanding the functioning of terrestrial ecosystems and for informing environmental policies. Recent years have seen a growing demand for high‐resolution data on vegetation structure, driving their prediction at fine resolutions (1–30 m) at state, continental, and global spatial extents by combining satellite data with machine learning. As these initiatives expand, it is crucial to actively discuss the quality and usability of these products. Here, we briefly summarize current efforts to map vegetation structure and show that continental‐to‐global canopy height models (CHMs) exhibit significant errors in canopy heights compared to national airborne laser scanning (ALS) data. We recommend that regions with abundant ALS data, such as Europe, prioritize using ALS‐based canopy height metrics rather than relying on less accurate predictions from satellite products. Despite variations in ALS data characteristics, such as temporal inconsistencies and differences in acquisition characteristics and classification accuracy, the generation of spatially contiguous canopy height products in raster format at fine spatial resolution is necessary and feasible. This requires coordinating efforts for data and survey harmonization, developing standardized processing pipelines and continent‐wide ALS products, and ensuring free access for research and environmental policy. We show that ALS data now cover most of Europe, with newer surveys achieving higher point densities, improving their suitability for vegetation mapping. Beyond numerous applications in forestry, ecology, and conservation, such data sets are crucial for calibrating future Earth Observation missions, making them essential for producing reliable and accurate global, fine‐resolution vegetation structure data.Plain Language Summary Understanding the structure of vegetation is important for studying ecosystems and making informed environmental decisions. To meet the growing need for detailed vegetation data, scientists are combining satellite data with machine learning to estimate vegetation structure at very fine scales. However, these satellite‐based models can have large errors when compared to more accurate measurements collected from airborne laser scanning (ALS). In this study, we show that in regions such as Europe, where extensive ALS data are available, it's better to use these local data than to rely on less accurate predictions from satellite products. Currently, around 30 European countries have completed or are close to completing nationwide airborne laser scanning, with several others partially covered. Newer acquisitions are being collected at increasingly higher point densities, providing more detailed information about 3D vegetation structure. We therefore emphasize the need to create consistent and accessible vegetation height maps using ALS data. This will require better coordination of data collection, standardized processing, and open data access. These detailed maps are not only useful for applications in forestry, ecology, and conservation, but they are also essential for improving future satellite missions that monitor Earth's vegetation.Key Points About 30 European countries now provide nationwide airborne laser scanning, and these data should be prioritized over predicted products Existing airborne laser scanning data should be used to derive continental‐scale vegetation metrics available in raster format Improved transnational coordination is needed to advance vegetation monitoring with airborne laser scanning data in EuropeAbstract Measuring and mapping vegetation structure is essential for understanding the functioning of terrestrial ecosystems and for informing environmental policies. Recent years have seen a growing demand for high‐resolution data on vegetation structure, driving their prediction at fine resolutions (1–30 m) at state, continental, and global spatial extents by combining satellite data with machine learning. As these initiatives expand, it is crucial to actively discuss the quality and usability of these products. Here, we briefly summarize current efforts to map vegetation structure and show that continental‐to‐global canopy height models (CHMs) exhibit significant errors in canopy heights compared to national airborne laser scanning (ALS) data. We recommend that regions with abundant ALS data, such as Europe, prioritize using ALS‐based canopy height metrics rather than relying on less accurate predictions from satellite products. Despite variations in ALS data characteristics, such as temporal inconsistencies and differences in acquisition characteristics and classification accuracy, the generation of spatially contiguous canopy height products in raster format at fine spatial resolution is necessary and feasible. This requires coordinating efforts for data and survey harmonization, developing standardized processing pipelines and continent‐wide ALS products, and ensuring free access for research and environmental policy. We show that ALS data now cover most of Europe, with newer surveys achieving higher point densities, improving their suitability for vegetation mapping. Beyond numerous applications in forestry, ecology, and conservation, such data sets are crucial for calibrating future Earth Observation missions, making them essential for producing reliable and accurate global, fine‐resolution vegetation structure data.Plain Language Summary Understanding the structure of vegetation is important for studying ecosystems and making informed environmental decisions. To meet the growing need for detailed vegetation data, scientists are combining satellite data with machine learning to estimate vegetation structure at very fine scales. However, these satellite‐based models can have large errors when compared to more accurate measurements collected from airborne laser scanning (ALS). In this study, we show that in regions such as Europe, where extensive ALS data are available, it's better to use these local data than to rely on less accurate predictions from satellite products. Currently, around 30 European countries have completed or are close to completing nationwide airborne laser scanning, with several others partially covered. Newer acquisitions are being collected at increasingly higher point densities, providing more detailed information about 3D vegetation structure. We therefore emphasize the need to create consistent and accessible vegetation height maps using ALS data. This will require better coordination of data collection, standardized processing, and open data access. These detailed maps are not only useful for applications in forestry, ecology, and conservation, but they are also essential for improving future satellite missions that monitor Earth's vegetation.Key Points About 30 European countries now provide nationwide airborne laser scanning, and these data should be prioritized over predicted products Existing airborne laser scanning data should be used to derive continental‐scale vegetation metrics available in raster format Improved transnational coordination is needed to advance vegetation monitoring with airborne laser scanning data in EuropeAbstract Measuring and mapping vegetation structure is essential for understanding the functioning of terrestrial ecosystems and for informing environmental policies. Recent years have seen a growing demand for high‐resolution data on vegetation structure, driving their prediction at fine resolutions (1–30 m) at state, continental, and global spatial extents by combining satellite data with machine learning. As these initiatives expand, it is crucial to actively discuss the quality and usability of these products. Here, we briefly summarize current efforts to map vegetation structure and show that continental‐to‐global canopy height models (CHMs) exhibit significant errors in canopy heights compared to national airborne laser scanning (ALS) data. We recommend that regions with abundant ALS data, such as Europe, prioritize using ALS‐based canopy height metrics rather than relying on less accurate predictions from satellite products. Despite variations in ALS data characteristics, such as temporal inconsistencies and differences in acquisition characteristics and classification accuracy, the generation of spatially contiguous canopy height products in raster format at fine spatial resolution is necessary and feasible. This requires coordinating efforts for data and survey harmonization, developing standardized processing pipelines and continent‐wide ALS products, and ensuring free access for research and environmental policy. We show that ALS data now cover most of Europe, with newer surveys achieving higher point densities, improving their suitability for vegetation mapping. Beyond numerous applications in forestry, ecology, and conservation, such data sets are crucial for calibrating future Earth Observation missions, making them essential for producing reliable and accurate global, fine‐resolution vegetation structure data.Plain Language Summary Understanding the structure of vegetation is important for studying ecosystems and making informed environmental decisions. To meet the growing need for detailed vegetation data, scientists are combining satellite data with machine learning to estimate vegetation structure at very fine scales. However, these satellite‐based models can have large errors when compared to more accurate measurements collected from airborne laser scanning (ALS). In this study, we show that in regions such as Europe, where extensive ALS data are available, it's better to use these local data than to rely on less accurate predictions from satellite products. Currently, around 30 European countries have completed or are close to completing nationwide airborne laser scanning, with several others partially covered. Newer acquisitions are being collected at increasingly higher point densities, providing more detailed information about 3D vegetation structure. We therefore emphasize the need to create consistent and accessible vegetation height maps using ALS data. This will require better coordination of data collection, standardized processing, and open data access. These detailed maps are not only useful for applications in forestry, ecology, and conservation, but they are also essential for improving future satellite missions that monitor Earth's vegetation.Key Points About 30 European countries now provide nationwide airborne laser scanning, and these data should be prioritized over predicted products Existing airborne laser scanning data should be used to derive continental‐scale vegetation metrics available in raster format Improved transnational coordination is needed to advance vegetation monitoring with airborne laser scanning data in EuropeHORIZON EUROPE Widening Participation and Strengthening the European Research Area https://doi.org/10.13039/100019187Leverhulme Trust https://doi.org/10.13039/501100000275Horizon 2020 Framework Programme https://doi.org/10.13039/100010661Deutsche Forschungsgemeinschaft https://doi.org/10.13039/501100001659The Slovenian Research and Innovation Agency https://doi.org/10.13039/501100004329HORIZON EUROPE Marie Sklodowska-Curie Actions https://doi.org/10.13039/100018694European Commission https://doi.org/10.13039/50110000078
Correction: Brentuximab vedotin plus chemotherapy for the treatment of front-line systemic anaplastic large cell lymphoma: subgroup analysis of the ECHELON-2 study at 5 years’ follow-up
No full text
Energy and biomass distribution in soil food webs of temperate and tropical forests
No full textAbstract Soil food webs channel most of the energy in terrestrial ecosystems. Temperate and tropical forests host different soil invertebrate communities, but consequent differences in the structure and functioning of soil food webs between these major biomes remain unknown. Here, we calculate energy fluxes to explore generic patterns in biomass and energy distribution across micro-, meso- and macrofauna in forest ecosystems spanning from southern taiga to tropical rainforests. Tropical soil food webs have either larger (monsoon forest) or smaller (rainforest) animal biomass than temperate ones, but have consistently higher energy flux, higher share of large organisms (macrofauna) in total biomass and distinct energy distribution. Specifically, tropical soil food webs have proportionally higher predation rates than temperate soil food webs and rely more on plant consumption (living roots), but less on bacterial, fungal and litter consumption. Earthworms act as food-web engineers promoting detrital energy pathways (litter, soil and deadwood consumption) in mixed broadleaved forests overriding climate-associated differences among forests. Our study shows a major change in soil food web from “brown” temperate to “green” tropical functional state, explaining functional implications of soil invertebrate community turnover across biomes
Systems acclimation to osmotic stress in zygnematophyte cells
No full textAbstract Zygnematophytes are the closest algal relatives of land plants. They hold key information to infer how the earliest land plants overcame the barrage of terrestrial stressors, the prime of which is osmotic stress. Here, we apply two osmotic stressors on a unicellular and a multicellular representative of zygnematophytes and study their responses over a 25-hour time course, generating 130, 60, and 30 transcriptomic, proteomic, and metabolomic samples combined with photophysiology, sugar analysis, immunocytochemical glycoprotein analysis, and microscopy. Our data highlight a shared protein chassis that shows divergent responses with the same outcome: successful acclimation to osmotic challenges. We establish a model of how the algal sisters of land plants can overcome a prime stressor in the terrestrial habitat and highlight components of the plant terrestrialization toolkit
Tree diversity is changing across tropical Andean and Amazonian forests in response to global change
No full textAbstract Climate and atmospheric changes are impacting forest function and structure worldwide, but their effects on tropical forest diversity are unclear. Nowhere is the scientific challenge greater than in the Andes and the Amazon, which together include the world’s most diverse forests. Here, using 406 permanent plots spanning four decades of intact lowland and montane forest dynamics, we test for long-term change in species richness and assess the influence of climate and other variables. We show that, at a continental scale, species richness appears stable, but this masks substantial regional variation. Species richness increased in Northern Andean and Western Amazon plots, yet declined in the Central Andes, Guyana Shield and Central-Eastern Amazon. Overall, warmer, drier and more seasonal forests lost species, while those at higher elevations, in less fragmented areas and with faster rates of tree turnover experienced increases. Region-specific drivers, particularly precipitation seasonality and demographic factors, modulated these trends. The results highlight the diverse ways in which Amazon–Andes forests are changing and underscore the critical need to preserve large-scale ecosystem integrity to maintain local tree diversity. By doing so, Northern Andean forests in particular could serve as an important refuge for species increasingly displaced by climate change
Peripheral Neuropathy Expands the Neurological Phenotype in Glutaric Aciduria Type 1
No full textABSTRACT Glutaric aciduria type 1 (GA1) is a neurometabolic disorder characterized by striatal injury in infancy and extrastriatal central nervous system abnormalities, the latter depending on the biochemical subtype. Whether the peripheral nervous system (PNS) is also affected has not been systematically studied. Therefore, we conducted a cross‐sectional study of 21 GA1 patients (15 high excretor [HE], 6 low excretor [LE]), identified either by newborn screening (NBS, n = 11) or targeted metabolic diagnostics (TMD, n = 10). All underwent clinical evaluation, cerebral MRI, neurophysiology, and MR‐neurography (MRN) of the sciatic nerve with magnetization transfer imaging and diffusion tensor imaging (DTI). Nerve magnetization transfer ratio (MTR) was analyzed across subgroups and against 21 age‐matched controls, while fractional anisotropy (FA) was assessed within the patient cohort. MRN revealed frequent abnormalities in GA1, particularly among HE patients, who showed lower MTR and FA values, indicating neuropathic changes. These alterations correlated with age, extrastriatal MRI abnormalities, and subependymal nodules, but not with striatal lesions or movement disorder. Clinical neuropathic symptoms were rare (4/15 HE patients) yet consistently associated with abnormal MRN. In HE patients exclusively, neurophysiology demonstrated reduced compound motor action potentials, slowed nerve conduction, and prolonged tibial somatosensory evoked potential latencies. Within the HE subgroup, NBS‐identified patients showed higher MTR values than those identified by targeted metabolic diagnostics, suggesting less severe nerve involvement. These results expand the GA1 phenotype by demonstrating frequent, predominantly subclinical PNS involvement in HE patients, linked to chronic metabolic toxicity. They underscore the need for further research into long‐term complications and therapeutic strategies for HE individuals.Dietmar Hopp Stiftung https://doi.org/10.13039/50110000594
Child agency in family language policy: children's perspectives in Chinese–German families
No full textChina Scholarship Council 10.13039/50110000454
Conventional versus advanced imaging selection for endovascular treatment of basilar artery occlusion strokes
No full textAbstract Introduction Endovascular thrombectomy (EVT) is an effective treatment for basilar artery occlusion (BAO) stroke in select patients. While there is a growing body of literature suggesting that advanced imaging modalities such as computed tomography perfusion (CTP) and magnetic resonance (MR) may not be necessary for selecting anterior circulation large vessel occlusion stroke patients for EVT, whether advanced imaging may be superior to conventional imaging (non-contrast CT and CT angiography) in identifying good treatment candidates among BAO patients is less clear. Patients and methods This was a multicenter retrospective cohort study of BAO EVT patients treated from 2013 to 2022 in the Stroke Thrombectomy and Aneurysm Registry. Patients selected for EVT by advanced imaging (CTP or MR) were matched with those selected by conventional imaging using propensity score matching (PSM) accounting for possible confounders. Primary outcome was functional independence at 90 days. Other outcomes include bedridden state or death at 90-days and symptomatic intracranial hemorrhage (sICH). Results 268 patients were included. 150 patients were selected for BAO EVT by conventional imaging, 86 by CTP, and 32 by MR. Patients selected by advanced imaging were significantly older than those selected by conventional imaging (median age 71 vs 64 years, p = 0.001); patient characteristics were otherwise similar between cohorts. After PSM, 90-day outcomes were similar between the two cohorts (p = 0.56), with similar rates of functional independence (39.4% vs 35.1%, p = 0.65), bedridden state or death (40.4% vs 44.7%, p = 0.66), and sICH (3.3% vs 5.7%, p = 0.49) for conventional and advanced imaging groups, respectively. Results were similar across treatment time windows (all p > 0.05). Conclusions Selecting patients for basilar EVT using conventional versus advanced imaging did not result in different clinical outcomes, regardless of treatment time windows. Conventional imaging appears sufficient as a first-line tool for selecting basilar EVT patients in routine clinical practice
Seed germination traits reveal naturalization potential: Global insights from temperate European herbaceous species
No full textSeed germination is a key stage in a plant's life cycle, influencing regeneration from seed by determining the post‐germination environment, plant fitness and evolutionary potential. Therefore, seed germination traits are expected to play a fundamental role in the naturalization of alien seed plants; yet broad‐scale empirical evidence of this remains limited. Using seed germination data for 1146 native temperate European herbaceous species, we tested whether species that have become naturalized outside their native range differ from non‐naturalized species in overall germinability (final germination proportion) and in their germination responses to six environmental cues across temperate, tropical dry and tropical humid macroclimatic zones of naturalization. We also assessed whether germinability and responses to these cues are associated with the geographic extent of naturalization, using a phylogenetically informed meta‐analysis that integrates 18,596 standardized laboratory germination records with global naturalization data. Naturalization was a common phenomenon, with 60% of species having naturalized in temperate regions and over 30% having naturalized in tropical regions. Naturalized species showed consistently higher overall germinability, germination at lower temperatures and higher requirements for seed scarification compared to non‐naturalized species, while other germination traits varied with the macroclimatic zone of naturalization. The extent of naturalization was also positively, though weakly, related to higher germinability and to the same germination traits that distinguished naturalized from non‐naturalized species. Synthesis . This study provides global‐scale evidence that the naturalization of European herbaceous species is related to specific germination traits acquired in the native range. Our findings indicate that traits such as high germinability, low stratification requirements and responsiveness to scarification act as preadaptations that facilitate naturalization by increasing opportunities for establishment. They also show that standardized laboratory germination tests using seeds sourced from native populations represent a cost‐effective tool for improving global risk assessments and for predicting naturalization potential under climate change through alterations in regeneration from seed