Foliar traits such as specific leaf area (SLA), leaf nitrogen (N), and phosphorus (P) concentrations play important roles in plant economic strategies and ecosystem functioning. Various global maps ...of these foliar traits have been generated using statistical upscaling approaches based on in-situ trait observations. Here, we intercompare such global upscaled foliar trait maps at 0.5° spatial resolution (six maps for SLA, five for N, three for P), categorize the upscaling approaches used to generate them, and evaluate the maps with trait estimates from a global database of vegetation plots (sPlotOpen). We disentangled the contributions from different plant functional types (PFTs) to the upscaled maps and quantified the impacts of using different plot-level trait metrics on the evaluation with sPlotOpen: community weighted mean (CWM) and top-of-canopy weighted mean (TWM). We found that the global foliar trait maps of SLA and N differ drastically and fall into two groups that are almost uncorrelated (for P only maps from one group were available). The primary factor explaining the differences between these groups is the use of PFT information combined with remote sensing-derived land cover products in one group while the other group mostly relied on environmental predictors alone. The maps that used PFT and corresponding land cover information exhibit considerable similarities in spatial patterns that are strongly driven by land cover. The maps not using PFTs show a lower level of similarity and tend to be strongly driven by individual environmental variables. Upscaled maps of both groups were moderately correlated to sPlotOpen data aggregated to the grid-cell level (R = 0.2–0.6) when processing sPlotOpen in a way that is consistent with the respective trait upscaling approaches, including the plot-level trait metric (CWM or TWM) and the scaling to the grid cells with or without accounting for fractional land cover. The impact of using TWM or CWM was relevant, but considerably smaller than that of the PFT and land cover information. The maps using PFT and land cover information better reproduce the between-PFT trait differences of sPlotOpen data, while the two groups performed similarly in capturing within-PFT trait variation.
Our findings highlight the importance of explicitly accounting for within-grid-cell trait variation, which has important implications for applications using existing maps and future upscaling efforts. Remote sensing information has great potential to reduce uncertainties related to scaling from in-situ observations to grid cells and the regression-based mapping steps involved in the upscaling.
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•Analyses revealed two fundamentally different categories of upscaled trait maps.•Differences between categories mainly driven by use of plant functional types (PFT).•Additional differences due to whole community vs. top-of-canopy trait metrics.•Upscaling without PFT does not capture the observed trait differences between them.•Accounting for within-grid-cell trait variation crucial for upscaling and evaluation.
The Global Map continues the long Florentine cartographic tradition, which is characterized by the ability, the tendency to perfection and the artistic vision but, above all, the passion. Like the ...one of its general manager Andrea Bonomo, for which the maps are the main instrument of knowledge.
The Global Map continues the long Florentine cartographic tradition, which is characterized by the ability, the tendency to perfection and the artistic vision but, above all, the passion. Like the ...one of its general manager Andrea Bonomo, for which the maps are the main instrument of knowledge.
Lithology describes the geochemical, mineralogical, and physical properties of rocks. It plays a key role in many processes at the Earth surface, especially the fluxes of matter to soils, ecosystems, ...rivers, and oceans. Understanding these processes at the global scale requires a high resolution description of lithology. A new high resolution global lithological map (GLiM) was assembled from existing regional geological maps translated into lithological information with the help of regional literature. The GLiM represents the rock types of the Earth surface with 1,235,400 polygons. The lithological classification consists of three levels. The first level contains 16 lithological classes comparable to previously applied definitions in global lithological maps. The additional two levels contain 12 and 14 subclasses, respectively, which describe more specific rock attributes. According to the GLiM, the Earth is covered by 64% sediments (a third of which are carbonates), 13% metamorphics, 7% plutonics, and 6% volcanics, and 10% are covered by water or ice. The high resolution of the GLiM allows observation of regional lithological distributions which often vary from the global average. The GLiM enables regional analysis of Earth surface processes at global scales. A gridded version of the GLiM is available at the PANGEA Database (http://dx.doi.org/10.1594/PANGAEA.788537).
Key Points
Global lithological map of high resolution
Three levels of lithological information are provided
A gridded version of the map is available
•We proposed a mapping model to consistently identify hierarchical urban boundaries (HUBs) for global urban settlements.•Our HUBs are physical boundaries supported by remote sensing, which are more ...objective and internationally comparable.•We generated a global vector database of HUBs based on 30-meter data and reinvestigated global urban settlements.•We pioneeringly confirmed the universality of the Rank-size rule in the urban systems of 47 countries by using HUBs.•We showed the potential of HUBs to measure the characteristics of urbanization at the macro and micro levels.
Urban boundary is the spatial basis for urban statistics and urban planning. However, the city definition by which the urban boundary is determined is not comparable among different countries. A globally consistent delimitation of hierarchical urban boundaries (HUBs) is rare but urgently needed. In this research, we proposed a model to consistently identify HUBs according to physical urban entity. The main quantitative basis of our model is the density, size and spatial relationship of the artificial impervious surface. We produced a vector dataset of global HUBs (named GHUB) based on 30-meter resolution remote sensing products. Cross-product comparison shows the effectiveness and advantages of our model. We furtherly, for the first time, investigated and compared the physical form and spatial characteristics of global urban settlements through the same lens supported by GHUB. We have identified 10,242 urban settlements with an area above five square kilometers, 39.18% of them are located within 100 km of the coastline. Urban settlements are not the “reinforced concrete forest” as commonly thought. The global average proportion of open space within urban settlements is 41.51%. The total area of urban open space in the world is 279.47 thousand square kilometers. Notably, we verified the Rank-size rule of urban settlement is universal, meanwhile, the verification results of different urban systems in 47 countries show that the Zipf’s exponent varies from country to country. Our work can help to consistently investigate global urban settlements without being affected by various definitions of cities. The GHUB can not only be applied to various urban studies but also can support global affairs such as the Sustainable Development Goal 11 due to its international comparability.
Large-scale and precise measurement of mangrove canopy height is crucial for understanding and evaluating wetland ecosystems' condition, health, and productivity. This study generates a global ...mangrove canopy height map with a 30 m resolution by integrating Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) photon-counting light detection and ranging (LiDAR) data with multi-source imagery. Initially, high-quality mangrove canopy height samples were extracted using meticulous processing and filtering of ICESat-2 data. Subsequently, mangrove canopy height models were established using the random forest (RF) algorithm, incorporating ICESat-2 canopy height samples, Sentinel-2 data, TanDEM-X DEM data and WorldClim data. Furthermore, a global 30 m mangrove canopy height map was generated utilizing the Google Earth Engine platform. Finally, the global map's accuracy was evaluated by comparing it with reference canopy heights derived from both space-borne and airborne LiDAR data. Results indicate that the global 30 m resolution mangrove height map was found to be consistent with canopy heights obtained from space-borne (r = 0.88, Bisa = −0.07 m, RMSE = 3.66 m, RMSE% = 29.86 %) and airborne LiDAR (r = 0.52, Bisa = −1.08 m, RMSE = 3.39 m, RMSE% = 39.05 %). Additionally, our findings reveal that mangroves worldwide exhibit an average height of 12.65 m, with the tallest mangrove reaching a height of 44.94 m. These results demonstrate the feasibility and effectiveness of using ICESat-2 data integrated with multi-source imagery to generate a global mangrove canopy height map. This dataset offers reliable information that can significantly support government and organizational efforts to protect and conserve mangrove ecosystems.
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•A new global 30 m resolution mangrove canopy height (MCH) map was created.•Integrating ICESat-2 and multi-source images helps to map global mangrove MCH.•MCH exhibits a latitudinal trend, rising near equator and decreasing toward poles.•Over 1298 km2 airborne LiDAR data were collected to verify the global MCH map.•RH100 displayed the most robust correlation with airborne LiDAR canopy heights.
•N deposition reduces soil microbial biomass (SMB) in grasslands and forests.•N deposition increases SMB in croplands.•SMB was most negatively affected by N deposition in acid soils.•Soil ...acidification act as a key mechanism in the responses of SMB to N deposition.•N deposition overall increased SMB by 10.0% across the globe during 2000–2020.
Soil microorganisms are key for biodiversity and ecosystem processes. Recent meta-analyses based on nitrogen (N) addition experiments reported an overall negative impact of elevated N on soil microbial biomass on a global scale. However, individual studies have reported divergent effects of N addition, ranging from strongly negative to even positive. Moreover, N deposition varies temporally and spatially worldwide. It remains uncertain how the effects of N deposition on soil microbial biomass vary across global terrestrial ecosystems over time. Through the synthesis of 374 N addition experiments across six continents, we revealed that low quantities of N increased the soil microbial biomass, but high N amounts strongly reduced it. Moreover, the N addition effects were strongly contingent on the ecosystem type, being highly negative in grasslands (−19.3 ± 6.2%, mean and 95% confidence intervals), negative in forests (−8.6 ± 4.2%), and positive in croplands (15.1 ± 12.3%). Further, the soil microbial biomass was most negatively affected by N addition in acidic soils. By combining our meta-analysis results from N addition experiments and global N deposition data, we revealed that the global soil microbial biomass increased by 10.0% in response to cumulative N deposition from 2000–2020. However, regions encompassing the Eastern U.S., Southern Brazil, Europe, and Eastern Asia, with high N deposition rates and large forested areas of acidic soils, were hotspots for microbial biomass loss. Our findings challenge the long-held notion that N deposition has universal negative impacts on soil microbial biomass. Instead, we show that the N deposition impacts on soil microbial biomass are dependent on the amounts of elevated N, ecosystem type, and soil pH, for which N-deposition-induced soil acidification acts as an internal mechanism.
The spatial distribution of subsurface parameters such as permeability are increasingly relevant for regional to global climate, land surface, and hydrologic models that are integrating groundwater ...dynamics and interactions. Despite the large fraction of unconsolidated sediments on Earth's surface with a wide range of permeability values, current global, high‐resolution permeability maps distinguish solely fine‐grained and coarse‐grained unconsolidated sediments. Representative permeability values are derived for a wide variety of unconsolidated sediments and applied to a new global map of unconsolidated sediments to produce the first geologically constrained, two‐layer global map of shallower and deeper permeability. The new mean logarithmic permeability of the Earth's surface is −12.7 ± 1.7 m2 being 1 order of magnitude higher than that derived from previous maps, which is consistent with the dominance of the coarser sediments. The new data set will benefit a variety of scientific applications including the next generation of climate, land surface, and hydrology models at regional to global scales.
Key Points
Mean global permeability is higher with detailed unconsolidated mapping
Representative permeability values are applied to a new global map to produce first geologically constrained, two‐layer global map of shallower and deeper permeability
Maps are crucial for next generation of land surface, hydrologic, and climate models
A correct quantification of mass and energy exchange processes among Earth's land surface, groundwater, and atmosphere requires an accurate parameterization of soil hydraulic properties. Pedotransfer ...functions (PTFs) are useful in this regard because they estimate these otherwise difficult to obtain characteristics using texture and other ubiquitous soil data. Most PTFs estimate parameters of empirical hydraulic functions with modest accuracy. In a continued pursuit of improving global‐scale PTF estimates, we evaluated whether improvements can be obtained when estimating parameters of hydraulic functions that make physically based assumptions. To this end, we developed a PTF that estimates the parameters of the Kosugi retention and hydraulic conductivity functions (Kosugi, 1994, https://doi.org/10.1029/93WR02931, 1996, https://doi.org/10.1029/96WR01776), which explicitly assume a lognormal pore size distribution and apply the Young‐Laplace equation to derive a corresponding pressure head distribution. Using a previously developed combination of machine learning and bootstrapping, the developed five hierarchical PTFs allow for estimates under practical data‐poor to data‐rich conditions. Using an independent global data set containing nearly 50,000 samples (118,000 retention points), we demonstrated that the new Kosugi‐based PTFs outperformed two van Genuchten‐based PTFs calibrated on the same data. The new PTFs were applied to a 1 × 1 km2 global map of texture and bulk density, thus producing maps of the parameters, field capacity, wilting point, plant available water, and associated uncertainties. Soil hydraulic parameters exhibit a much larger variability in the Northern Hemisphere than in the Southern Hemisphere, which is likely due to the geographical distribution of climate zones that affect weathering and sedimentation processes.
Key Points
We developed a set of hierarchical pedotransfer functions for the semiphysical Kosugi water retention model
An evaluation using globally representative data demonstrated that the PTFs outperformed PTFs based on the van Genuchten retention model
Global maps of hydraulic parameters, derived quantities, and associated uncertainties were produced at 1‐km resolution
Abstract Litter decomposition is a key ecological process that determines carbon (C) and nutrient cycling in terrestrial ecosystems. The initial concentrations of C and nutrients in litter play a ...critical role in this process, yet the global patterns of litter initial concentrations of C, nitrogen (N) and phosphorus (P) are poorly understood. We employed machine learning with a global database to quantitatively assess the global patterns and drivers of leaf litter initial C, N and P concentrations, as well as their returning amounts (i.e. amounts returned to soils). The medians of litter C, N and P concentrations were 46.7, 1.1, and 0.1%, respectively, and the medians of litter C, N and P returning amounts were 1.436, 0.038 and 0.004 Mg ha −1 year −1 , respectively. Soil and climate emerged as the key predictors of leaf litter C, N and P concentrations. Predicted global maps showed that leaf litter N and P concentrations decreased with latitude, while C concentration exhibited an opposite pattern. Additionally, the returning amounts of leaf litter C, N and P all declined from the equator to the poles in both hemispheres. Synthesis : Our results provide a quantitative assessment of the global concentrations and returning amounts of leaf litter C, N and P, which showed new light on the role of leaf litter in global C and nutrients cycling.