scholarly journals GIFT – A Global Inventory of Floras and Traits for macroecology and biogeography

2019 ◽  
Author(s):  
Patrick Weigelt ◽  
Christian König ◽  
Holger Kreft
Keyword(s):  
Plant Species ◽  
Functional Traits ◽  
Land Surface ◽  
Large Scale ◽  
Global Scale ◽  
Land Plant ◽  
Distribution Data ◽  
Small Subset ◽  
Phylogenetic Information ◽  
Global Inventory

AbstractTo understand how traits and evolutionary history shape the geographic distribution of plant life on Earth, we need to integrate high-quality and global-scale distribution data with functional and phylogenetic information. Large-scale distribution data for plants are, however, often restricted to either certain taxonomic groups or geographic regions. For example, range maps only exist for a small subset of all plant species and digitally available point-occurrence information is strongly biased both geographically and taxonomically. An alternative, currently rarely used resource for macroecological and botanical research are regional Floras and checklists, which contain highly curated information about the species composition of a clearly defined area, and which together virtually cover the entire global land surface. Here we report on our recent efforts to mobilize this information for macroecological and biogeographical analyses in the GIFT database, the Global Inventory of Floras and Traits. GIFT integrates plant distributions, functional traits, phylogenetic information, and region-level geographic, environmental and socioeconomic data. GIFT currently holds species lists for 2,893 regions across the whole globe including ~315,000 taxonomically standardized species names (i.e. c. 80% of all known land plant species) and ~3 million species-by-region occurrences. In addition, GIFT contains information about the floristic status (native, endemic, alien and naturalized) and takes advantage of the wealth of trait information in the regional Floras, complemented by data from global trait databases. Based on a hierarchical and taxonomical derivation scheme, GIFT holds information for 83 functional traits and more than 2.3 million trait-by-species combinations and achieves unprecedented coverage in categorical traits such as woodiness (~233,000 spp.) or growth form (~213,000 spp.). Here we present the structure, content and automated workflows of GIFT and a corresponding web-interface (http://gift.uni-goettingen.de) as proof of concept for the feasibility and potential of mobilizing aggregated biodiversity data for global macroecological and biogeographical research.

scholarly journals A high-resolution global dataset of topographic index values for use in large-scale hydrological modelling

2014 ◽  
Vol 11 (6) ◽  
pp. 6139-6166 ◽  
Author(s):  
T. R. Marthews ◽  
S. J. Dadson ◽  
B. Lehner ◽  
S. Abele ◽  
N. Gedney
Keyword(s):  
High Resolution ◽  
Land Surface ◽  
Large Scale ◽  
Global Scale ◽  
Surface Fluxes ◽  
Data Sets ◽  
Topographic Index ◽  
Surface Water Flow ◽  
Land Surface Water ◽  
Compound Topographic Index

Abstract. Modelling land surface water flow is of critical importance for simulating land-surface fluxes, predicting runoff and water table dynamics and for many other applications of Land Surface Models. Many approaches are based on the popular hydrology model TOPMODEL, and the most important parameter of this model is the well-knowntopographic index. Here we present new, high-resolution parameter maps of the topographic index for all ice-free land pixels calculated from hydrologically-conditioned HydroSHEDS data sets using the GA2 algorithm. At 15 arcsec resolution, these layers are 4× finer than the resolution of the previously best-available topographic index layers, the Compound Topographic Index of HYDRO1k (CTI). In terms of the largest river catchments occurring on each continent, we found that in comparison to our revised values, CTI values were up to 20% higher in e.g. the Amazon. We found the highest catchment means were for the Murray-Darling and Nelson-Saskatchewan rather than for the Amazon and St. Lawrence as found from the CTI. We believe these new index layers represent the most robust existing global-scale topographic index values and hope that they will be widely used in land surface modelling applications in the future.

Simulating riverine nutrient transport on global scale

2020 ◽  
Author(s):  
Tobias Stacke ◽  
Stefan Hagemann ◽  
Gibran Romero-Mujalli ◽  
Jens Hartmann ◽  
Helmuth Thomas
Keyword(s):  
Land Surface ◽  
Large Scale ◽  
Climate Models ◽  
River Flow ◽  
Climate Change Impacts ◽  
Global Scale ◽  
Nutrient Loads ◽  
Input Dataset ◽  
Ocean Models ◽  
Energy And Momentum

<p>The currently ongoing CMIP6 simulations feature Earth System Models with interactively coupled components for atmosphere, ocean and land surface. Water, energy and momentum between these components are exchanged conservatively. This is crucial to compute climate interactions and their feedbacks consistently. Currently, the representation of biogeochemical cycles in land surface and ocean models is advancing including not only a carbon cycle but also processes based on nutrients like nitrogen or phosphorus. Some land surface models (LSM) already compute leaching of such constituents from the soil, and some ocean models (OM) consider nutrient influx from the land for a number of processes, e.g. biological activity. However, the OMs usually use observed data as input instead of the nutrient loads computed by the LSMs. This setup cannot represent the effects of climate or land use change on nutrient availability and therefore limits the applications of ESMs in respect to climate change impacts.</p><p>For this reason, we are extending our hydrological discharge model, the HDM, to not only transport water but also other constituents. The HDM is an established component of regional (GCOAST, ESM ROM, Reg-CM-ES) as well as global (MPI-ESM) climate models but also applicable as stand-alone model. In a first step, only inert transport is simulated without considering any chemical reactions or biological transformation during river flow. The transport is realized using the same linear cascade infrastructure as used for water transport. However, a successful offline validation of these new features does not only require a realistic routing scheme and consequently the representation of the most important reactions during transport, but also the generation of sensible input data either from large scale models or from observations. In our presentation, we will outline the state of this work together with the compiled input dataset.</p>

scholarly journals Development of a global dataset of Wetland Area and Dynamics for Methane Modeling (WAD2M)

2020 ◽  
Author(s):  
Zhen Zhang ◽  
Etienne Fluet-Chouinard ◽  
Katherine Jensen ◽  
Kyle McDonald ◽  
Gustaf Hugelius ◽  
...  
Keyword(s):  
Land Surface ◽  
Large Scale ◽  
Southern Oscillation ◽  
Microwave Remote Sensing ◽  
Global Scale ◽  
Annual Maximum ◽  
Time Step ◽  
Wetland Area ◽  
Wetland Extent

Abstract. Seasonal and interannual variations in global wetland area is a strong driver of fluctuations in global methane (CH4) emissions. Current maps of global wetland extent vary with wetland definition, causing substantial disagreement and large uncertainty in estimates of wetland methane emissions. To reconcile these differences for large-scale wetland CH4 modeling, we developed a global Wetland Area and Dynamics for Methane Modeling (WAD2M) dataset at ~25 km resolution at equator (0.25 arc-degree) at monthly time-step for 2000–2018. WAD2M combines a time series of surface inundation based on active and passive microwave remote sensing at coarse resolution (~25 km) with six static datasets that discriminate inland waters, agriculture, shoreline, and non-inundated wetlands. We exclude all permanent water bodies (e.g. lakes, ponds, rivers, and reservoirs), coastal wetlands (e.g., mangroves and sea grasses), and rice paddies to only represent spatiotemporal patterns of inundated and non-inundated vegetated wetlands. Globally, WAD2M estimates the long-term maximum wetland area at 13.0 million km2 (Mkm2), which can be separated into three categories: mean annual minimum of inundated and non-inundated wetlands at 3.5 Mkm2, seasonally inundated wetlands at 4.0 Mkm2 (mean annual maximum minus mean annual minimum), and intermittently inundated wetlands at 5.5 Mkm2 (long-term maximum minus mean annual maximum). WAD2M has good spatial agreements with independent wetland inventories for major wetland complexes, i.e., the Amazon Lowland Basin and West Siberian Lowlands, with high Cohen's kappa coefficient of 0.54 and 0.70 respectively among multiple wetlands products. By evaluating the temporal variation of WAD2M against modeled prognostic inundation (i.e., TOPMODEL) and satellite observations of inundation and soil moisture, we show that it adequately represents interannual variation as well as the effect of El Niño-Southern Oscillation on global wetland extent. This wetland extent dataset will improve estimates of wetland CH4 fluxes for global-scale land surface modeling. The dataset can be found at http://doi.org/10.5281/zenodo.3998454 (Zhang et al., 2020).

scholarly journals Predicting plant conservation priorities on a global scale

2018 ◽  
Vol 115 (51) ◽  
pp. 13027-13032 ◽  
Author(s):  
Tara A. Pelletier ◽  
Bryan C. Carstens ◽  
David C. Tank ◽  
Jack Sullivan ◽  
Anahí Espíndola
Keyword(s):  
Plant Species ◽  
Conservation Status ◽  
Plant Conservation ◽  
Global Scale ◽  
Land Plant ◽  
Conservation Priorities ◽  
Conservation Assessment ◽  
Biodiversity Science ◽  
Machine Learning Approach ◽  
The One

The conservation status of most plant species is currently unknown, despite the fundamental role of plants in ecosystem health. To facilitate the costly process of conservation assessment, we developed a predictive protocol using a machine-learning approach to predict conservation status of over 150,000 land plant species. Our study uses open-source geographic, environmental, and morphological trait data, making this the largest assessment of conservation risk to date and the only global assessment for plants. Our results indicate that a large number of unassessed species are likely at risk and identify several geographic regions with the highest need of conservation efforts, many of which are not currently recognized as regions of global concern. By providing conservation-relevant predictions at multiple spatial and taxonomic scales, predictive frameworks such as the one developed here fill a pressing need for biodiversity science.

scholarly journals Large-scale characteristics of the distribution of blowing-snow sublimation

2008 ◽  
Vol 49 ◽  
pp. 11-16 ◽  
Author(s):  
Konosuke Sugiura ◽  
Tetsuo Ohata
Keyword(s):  
Northern Hemisphere ◽  
Land Surface ◽  
Large Scale ◽  
Hydrological Cycle ◽  
Analysis Data ◽  
Global Scale ◽  
Blowing Snow ◽  
Scale Characteristics ◽  
Global Datasets ◽  
Northern And Southern Hemispheres

AbstractTo consider the large-scale characteristics of blowing-snow sublimation and its importance in the hydrological cycle in the cryosphere, we investigated the sublimation of blowing snow particles on a global scale using the global datasets of the European Centre for Medium-RangeWeather Forecasts (ECMWF) re-analysis data and the International Satellite Land Surface Climatology Project (ISLSCP) Initiative I data for 1987. The sublimation fluxes of blowing snow particles were estimated globally with 2.5˚ resolution at 6 hour intervals. We found that the sublimation of blowing snow particles occurs more widely in the Northern Hemisphere than in the Southern Hemisphere, does not increase monotonously with latitude, and becomes more active in the polar coast regions and highlands, although the annual mean sublimation fluxes of the Northern and Southern Hemispheres are almost equal. In addition, we confirmed the characteristic seasonal changes in the area of sublimation in the Northern Hemisphere. Although we need to incorporate continuous parameters from systematic ground-based studies of the structure of blowing snow in specific fields to reduce uncertainty regarding the characteristics of blowing snow, our results point to a need to review the current understanding of the hydrological cycle.

scholarly journals Evaluating the hydrological consistency of satellite based water cycle components

2016 ◽  
Author(s):  
Oliver López ◽  
Rasmus Houborg ◽  
Matthew F. McCabe
Keyword(s):  
Land Surface ◽  
Water Budget ◽  
Large Scale ◽  
Water Cycle ◽  
Satellite Observation ◽  
Global Scale ◽  
Satellite Observations ◽  
Arid Environments ◽  
Basin Scale ◽  
Wide Range

Abstract. Advances in multi-satellite based observations of the earth system have provided the capacity to retrieve information across a wide-range of land surface hydrological components and provided an opportunity to characterize terrestrial processes from a completely new perspective. Given the spatial advantage that space-based observations offer, several regional-to-global scale products have been developed, offering insights into the multi-scale behaviour and variability of hydrological states and fluxes. However, one of the key challenges in the use of satellite-based products is characterizing the degree to which they provide realistic and representative estimates of the underlying retrieval: that is, how accurate are the hydrological components derived from satellite observations? The challenge is intrinsically linked to issues of scale, since the availability of high-quality in-situ data is limited, and even where it does exist, is generally not commensurate to the resolution of the satellite observation. Basin-scale studies have shown considerable variability in achieving water budget closure with any degree of accuracy using satellite estimates of the water cycle. In order to assess the suitability of this type of approach for evaluating hydrological observations, it makes sense to first test it over environments with restricted hydrological inputs, before applying it to more hydrological complex basins. Here we explore the concept of hydrological consistency, i.e. the physical considerations that the water budget impose on the hydrologic fluxes and states to be temporally and spatially linked, to evaluate the reproduction of a set of large-scale evaporation (E) products by using a combination of satellite rainfall (P) and Gravity Recovery and Climate Experiment (GRACE) observations of storage change, focusing on arid and semi-arid environments, where the hydrological flows can be more realistically described. Our results indicate no persistent hydrological consistency in these environments, suggesting the need for continued efforts in improving satellite observations, particularly for the retrieval of evaporation, and the need to more directly account for anthropogenic influences such as agricultural irrigation into our large scale water cycle studies.

scholarly journals HESS Opinions: Improving the evaluation of groundwater representation in continental to global scale models

2020 ◽  
Author(s):  
Tom Gleeson ◽  
Thorsten Wagener ◽  
Petra Döll ◽  
Samuel C. Zipper ◽  
Charles West ◽  
...  
Keyword(s):  
Model Evaluation ◽  
Land Surface ◽  
Large Scale ◽  
Earth Science ◽  
Groundwater Resources ◽  
Global Scale ◽  
Data Availability ◽  
Scale Models ◽  
Sustainability Problems ◽  
Evaluation Approaches

Abstract. Continental- to global-scale hydrologic and land surface models increasingly include representations of the groundwater system, driven by crucial Earth science and sustainability problems. These models are essential for examining, communicating, and understanding the dynamic interactions between the Earth System above and below the land surface as well as the opportunities and limits of groundwater resources. A key question for this nascent and rapidly developing field is how to evaluate the realism and performance of such large-scale groundwater models given limitations in data availability and commensurability. Our objective is to provide clear recommendations for improving the evaluation of groundwater representation in continental- to global-scale models. We identify three evaluation approaches, including comparing model outputs with available observations of groundwater levels or other state or flux variables (observation-based evaluation); comparing several models with each other with or without reference to actual observations (model-based evaluation); and comparing model behavior with expert expectations of hydrologic behaviors that we expect to see in particular regions or at particular times (expert-based evaluation). Based on current and evolving practices in model evaluation as well as innovations in observations, machine learning and expert elicitation, we argue that combining observation-, model-, and expert-based model evaluation approaches may significantly improve the realism of groundwater representation in large-scale models, and thus our quantification, understanding, and prediction of crucial Earth science and sustainability problems. We encourage greater community-level communication and cooperation on these challenges, including among global hydrology and land surface modelers, local to regional hydrogeologists, and hydrologists focused on model development and evaluation.

scholarly journals Spatiotemporal Comparison and Validation of Three Global-Scale Fractional Vegetation Cover Products

2019 ◽  
Vol 11 (21) ◽  
pp. 2524 ◽  
Author(s):  
Duanyang Liu ◽  
Kun Jia ◽  
Xiangqin Wei ◽  
Mu Xia ◽  
Xiwang Zhang ◽  
...  
Keyword(s):  
Vegetation Cover ◽  
Land Surface ◽  
Large Scale ◽  
High Spatial Resolution ◽  
Remote Sensing Data ◽  
Global Scale ◽  
Glass Product ◽  
Fractional Vegetation Cover ◽  
Temporal Profiles

Fractional vegetation cover (FVC) is an important parameter for many environmental and ecological models. Large-scale and long-term FVC products are critical for various applications. Currently, several global-scale FVC products have been generated with remote sensing data, such as VGT bioGEOphysical product Version 2 (GEOV2), PROBA-V bioGEOphysical product Version 3 (GEOV3) and Global LAnd Surface Satellite (GLASS) FVC products. However, studies comparing and validating these global-scale FVC products are rare. Therefore, in this study, the performances of three global-scale time series FVC products, including the GEOV2, GEOV3, and GLASS FVC products, are investigated to assess their spatial and temporal consistencies. Furthermore, reference FVC data generated from high-spatial-resolution data are used to directly evaluate the accuracy of these FVC products. The results show that these three FVC products achieve general agreements in terms of spatiotemporal consistencies over most regions. In addition, the GLASS and GEOV2 FVC products have reliable spatial and temporal completeness, whereas the GEOV3 FVC product contains much missing data over high-latitude regions, especially during wintertime. Furthermore, the GEOV3 FVC product presents higher FVC values than GEOV2 and GLASS FVC products over the equator. The main differences between the GEOV2 and GLASS FVC products occur over deciduous forests, for which the GLASS product presents slightly higher FVC values than the GEOV2 product during wintertime. Finally, temporal profiles of the GEOV2 and GLASS FVC products show better consistency than the GEOV3 FVC product, and the GLASS FVC product presents more reliable accuracy (R2 = 0.7878, RMSE = 0.1212) compared with the GEOV2 (R2 = 0.5798, RMSE = 0.1921) and GEOV3 (R2 = 0.7744, RMSE = 0.2224) FVC products over these reference FVC data.

scholarly journals Global-Scale Comparison of MISR and MODIS Land Surface Albedos

2011 ◽  
Vol 24 (3) ◽  
pp. 732-749 ◽  
Author(s):  
Bernard Pinty ◽  
Malcolm Taberner ◽  
Vance R. Haemmerle ◽  
Susan R. Paradise ◽  
Eric Vermote ◽  
...  
Keyword(s):  
Land Surface ◽  
Large Scale ◽  
Robust Statistics ◽  
Atmospheric Correction ◽  
Global Scale ◽  
Model Parameters ◽  
Bidirectional Reflectance Factor ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Highly Correlated ◽  
Mean Differences

Abstract The Moderate Resolution Imaging Spectroradiometer (MODIS) white-sky surface albedos are compared with similar products generated on the basis of the Multiangle Imaging SpectroRadiometer (MISR) surface bidirectional reflectance factor (BRF) model parameters available for the year 2005. The analysis is achieved using global-scale statistics to characterize the broad patterns of these two independent albedo datasets. The results obtained in M. Taberner et al. have shown that robust statistics can be established and that both datasets are highly correlated. As a result, the slight but consistent biases and trends identified in this paper, derived from statistics obtained on a global basis, should be considered sufficiently reliable to merit further investigation. The present paper reports on the zonal- and seasonal-mean differences retrieved from the analysis of the MODIS and MISR surface albedo broadband products. The MISR − MODIS differences exhibit a systematic positive bias or offset in the range of 0.01–0.03 depending on the spectral domain of interest. Results obtained in the visible domain exhibit a well-marked and very consistent meridional trend featuring a “smile effect” such that the MISR − MODIS differences reach maxima at the highest latitudes in both hemispheres. The analysis of seasonal variations observed in MISR and MODIS albedo products reveals that, in the visible domain, the MODIS albedos generate weaker seasonal changes than MISR and that the differences increase poleward from the equatorial regions. A detailed investigation of MODIS and MISR aerosol optical depth retrievals suggests that this large-scale meridional trend is probably not caused by differences in the aerosol load estimated by each instrument. The scale and regularity of the meridional trend suggests that this may be due to the particular sampling regime of each instrument in the viewing azimuthal planes and/or approximations in the atmospheric correction processes. If this is the case, then either MODIS is underestimating, or MISR overestimating, the surface anisotropy or both.

scholarly journals Assimilation of wide-swath altimetry observations to correct large-scale river routing model parameters

2019 ◽  
Author(s):  
Charlotte M. Emery ◽  
Sylvain Biancamaria ◽  
Aaron Boone ◽  
Sophie Ricci ◽  
Mélanie C. Rochoux ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Land Surface ◽  
Large Scale ◽  
Amazon Basin ◽  
Global Scale ◽  
Hydrologic Model ◽  
Model Parameters ◽  
True Value ◽  
Input Parameters ◽  
River Routing

Abstract. Land surface models combined with river routing models are widely used to study the continental part of the water cycle. They give global estimates of water flows and storages but not without non-negligible uncertainties; among which inexact input parameters have a significant part. The incoming Surface Water and Ocean Topography (SWOT) satellite mission, with a launch schedule for 2021, will be dedicated to measure water surface elevations, widths and surface slopes of rivers larger than 100 meters at global scale. SWOT will provide a significant amount of new data for river hydrology and they could be combined, through data assimilation, to global-scale models in order to correct their input parameters and reduce their associated uncertainty. The objective of this study is to present a data assimilation platform based on the asynchronous ensemble Kalman filter (AEnKF) that assimilates synthetical SWOT observations of water elevations to correct the input parameters of a large scale hydrologic model over a 21-day time window. The study is applied on the ISBA-CTRIP model over the Amazon basin and focuses on correcting the spatial distribution of the river Manning coefficients. The data assimilation algorithm, tested through a set of Observing System Simulation Experiments (OSSE), is able to retrieve the true value of the Manning coefficients within one assimilation cycle most of the time and shows perspectives in tracking the Manning coefficient temporal variations. Ultimately, in order to deal with potential bias between the observed and the model bathymetry, the assimilation of water elevation anomalies was also tested and showed promising results.

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