A5047925002- Soil Geostatistics and Mapping
- Soil Moisture and Remote Sensing
- Soil Carbon and Nitrogen Dynamics
- Soil and Unsaturated Flow
- Climate change and permafrost
- Soil erosion and sediment transport
- Forest ecology and management
- Geochemistry and Geologic Mapping
- Plant Water Relations and Carbon Dynamics
- Land Use and Ecosystem Services
- Research Data Management Practices
- Remote Sensing and LiDAR Applications
- Soil and Land Suitability Analysis
- Remote Sensing in Agriculture
- Atmospheric and Environmental Gas Dynamics
- Environmental and Ecological Studies
- Precipitation Measurement and Analysis
- Forest Management and Policy
- Species Distribution and Climate Change
- Plant Ecology and Soil Science
- Sustainable Agricultural Systems Analysis
- Invertebrate Taxonomy and Ecology
- Geology and Paleoclimatology Research
- Coastal wetland ecosystem dynamics
- Hydrology and Watershed Management Studies
Universidad Nacional Autónoma de México
2018-2025
University of California, Riverside
2022-2024
United States Department of Agriculture
2022-2024
U.S. Salinity Laboratory
2022-2024
Agricultural Research Service
2022-2023
Instituto de Geociencias
2022-2023
University of Delaware
2015-2022
South College
2018-2021
Centro Nacional de Monitoramento e Alertas de Desastres Naturais
2020
Johnson Space Center
2010
This paper describes the technical development and accuracy assessment of most recent improved version SoilGrids system at 250m resolution (June 2016 update). provides global predictions for standard numeric soil properties (organic carbon, bulk density, Cation Exchange Capacity (CEC), pH, texture fractions coarse fragments) seven depths (0, 5, 15, 30, 60, 100 200 cm), in addition to depth bedrock distribution classes based on World Reference Base (WRB) USDA classification systems (ca. 280...
Abstract. Riverine wetlands are created and transformed by geomorphological processes that determine their vegetation composition, primary production soil accretion, all of which likely to influence C stocks. Here, we compared ecosystem stocks (trees, downed wood) N different types riverine (marsh, peat swamp forest mangroves) whose distribution spans from an environment dominated river forces estuarine coastal processes. We also estimated sequestration rates mangroves on the basis...
Abstract. Country-specific soil organic carbon (SOC) estimates are the baseline for Global SOC Map of Soil Partnership (GSOCmap-GSP). This endeavor is key to explaining uncertainty global but requires harmonizing heterogeneous datasets and building country-specific capacities digital mapping (DSM). We identified predictors tested performance five predictive algorithms across Latin America. The included support vector machines (SVMs), random forest (RF), kernel-weighted nearest neighbors...
Soil moisture plays a key role in the Earth’s water and carbon cycles, but acquisition of continuous (i.e., gap-free) soil measurements across large regions is challenging task due to limitations currently available point measurements. Satellites offer critical information for over areas on regular basis (e.g., European Space Agency Climate Change Initiative (ESA CCI), National Aeronautics Administration Moisture Active Passive (NASA SMAP)); however, there are where satellite-derived cannot...
Annual soil moisture estimates are useful to characterize trends in the climate system, capacity of soils retain water and for predicting land atmosphere interactions. The main source spatial information across large areas (e.g., continents) is satellite-based microwave remote sensing. However, satellite datasets have coarse resolution 25-50 km grids); from regional-to-global scales gaps. We provide an alternative approach predict patterns (and associated uncertainty) with higher where no...
Abstract Soil organic carbon (SOC) information is fundamental for improving global cycle modeling efforts, but discrepancies exist from country‐to‐global scales. We predicted the spatial distribution of SOC stocks (topsoil; 0–30 cm) and quantified uncertainty across Mexico conterminous United States (CONUS). used a multisource dataset (>10 000 pedons, between 1991 2010) coupled with simulated annealing regression framework that accounts variable selection. Our model explained ~50%...
Abstract. In the age of big data, soil data are more available and richer than ever, but – outside a few large survey resources they remain largely unusable for informing management understanding Earth system processes beyond original study. Data science has promised fully reusable research pipeline where from past studies used to contextualize new findings reanalyzed insight. Yet synthesis projects encounter challenges at all steps reuse pipeline, including unavailable labor-intensive...
Abstract. Soil Water Erosion (SWE) is the dominant soil degradation driver on a global scale. For quantifying SWE, erosivity an index that reflects potential (i.e., energy) of rainfall to cause SWE. To enhance assessment SWE process at national scale—, objectives this research are a) develop first Mexican time series database for three climate normals CNs (1968–1997, 1978–2007, and 1988–2017) leveraging legacy data, b) estimate across continental Mexico by using daily series. The workflow...
The consistency between quality-based erosion assessments and modeling varies across Mexico. Erosion studies, from regional to global scales, typically use either expert knowledge or data-driven approaches. Expert involves photo-interpretation of satellite imagery combined with fieldwork classify degrees. Data-driven approaches models such as the Revised Universal Soil Loss Equation (RUSLE) estimate soil loss rates. In Mexico, both strategies have been applied nationally, but discrepancies...
There is an increasing need for approaches to determine reference emission levels and implement policies address the objectives of Reducing Emissions from Deforestation Forest Degradation, plus improving forest management, carbon stock enhancement conservation (REDD+). Important aspects approaching emissions reductions include coordination sharing technology, data, protocols experiences within among countries maximize resources apply knowledge build robust monitoring, reporting verification...
Abstract There is a need to optimize resources for large‐scale environmental monitoring efforts, especially in developing countries. We tested flexible framework the design (i.e., selection of study sites) an observatory network (EON) using publicly available data Mexico. This country represents challenge designing EONs because its megadiversity and large climate ecological heterogeneity. address three pervasive challenges EONs: (1) How characterize delineate ecologically similar areas, (2)...
Abstract. Soil moisture is key for understanding soil–plant–atmosphere interactions. We provide a soil pattern recognition framework to increase the spatial resolution and fill gaps of ESA-CCI (European Space Agency Climate Change Initiative v4.5) dataset, which contains > 40 years satellite global grids with ∼ 27 km. use terrain parameters coupled bioclimatic type information predict finer-grained (i.e., downscaled) moisture. assess impact on prediction accuracy by cross-validating...
Abstract Mangroves cover less than 0.1% of Earth’s surface, store large amounts carbon per unit area, but are threatened by global environmental change. The capacity mangroves productivity could be characterized their canopy greenness, this property has not been systematically tested across gradients mangrove forests and national scales. Here, we analyzed time series Normalized Difference Vegetation Index (NDVI), mean air temperature total precipitation between 2001 2015 (14 years) to...
Abstract. A critical aspect of predicting soil organic carbon (SOC) concentrations is the lack available information; where information on characteristics available, it usually focused regions high agricultural interest. To date, in Chile, a large proportion SOC data have been collected areas intensive or forestry use; however, vast beyond these forms land use few no available. Here we present new database for country, which result an unprecedented national effort under framework Global Soil...
The proper estimation of above-ground biomass (AGB) stocks managed forests is a prerequisite to quantifying their role in climate change mitigation. aim this study was analyze the spatial variability AGB and its uncertainty between actively pine unmanaged pine-oak reference central Mexico. To investigate determinants AGB, we analyzed variables related forest management, stand structure, topography, climate. We developed linear (LM), generalized additive (GAM), Random Forest (RF) empirical...
Site Index has been widely used as an age normalised metric in order to account for variation forest height at a range of spatial scales. Although previous research modelling methods describe the regional Index, little examined gains that can be achieved through use regression kriging or ensemble methods. In this study, extensive set environmental surfaces were covariates predict measurements covering Pinus radiata D. Don plantations Chile. Using dataset, objectives (i) compare predictive...
Abstract. Over the past decade, Brazil has experienced severe droughts across its territory, with important implications for soil moisture dynamics. Soil variability a direct impact on agriculture, water security and ecosystem services. Nevertheless, there is currently little information how different biomes responds to drought. In this study, we used satellite data from European Space Agency, 2009 2015, analyze differences in responses drought each biome of Brazil: Amazon, Atlantic Forest,...
Abstract. Texture is a fundamental soil property for multiple applications in environmental and earth sciences. Knowing its spatial distribution allows better understanding of the response conditions to changes environment, such as land use. This paper describes technical development Colombia's first texture maps, obtained via ensemble national global digital mapping products. work compiles new database with 4203 profiles, which were harmonized at five standard depths (0–5, 5–15, 15–30,...
Abstract Soil nitrogen (N) is an important driver of plant productivity and ecosystem functioning; consequently, it critical to understand its spatial variability from local‐to‐global scales. Here, we provide a quantitative assessment the three‐dimensional distribution soil N across United States (CONUS) using digital mapping approach. We used random forest‐regression kriging algorithm predict concentrations associated uncertainty six depths (0–5, 5–15, 15–30, 30–60, 60–100, 100–200 cm) at...
The National Forestry Commission of Mexico continuously monitors forest structure within the country's continental territory by implementation Forest and Soils Inventory (INFyS). Due to challenges involved in collecting data exclusively from field surveys, there are spatial information gaps for important attributes. This can produce bias or increase uncertainty when generating estimates required support management decisions. Our objective is predict distribution tree height density all...