vegetation | Ag Data Commons

LTAR - Meteorological Stations - R.J. Cook Agronomy Farm - Cook East

USDA-ARS Northwest Sustainable Agroecosystems Research (NSAR) and Washington State University (WSU) established a long-term meteorological and eddy covariance tower in 2017.

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Sustainable Corn CAP Research Data (USDA-NIFA Award No. 2011-68002-30190): ARDN Products

ARDN (Agricultural Research Data Network) annotations for Sustainable Corn CAP Research Data (USDA-NIFA Award No. 2011-68002-30190). These data are a subset of the Sustainable Corn CAP (Cropping Systems Coordinated Agricultural Project: Climate Change, Mitigation, and Adaptation in Corn-based Cropping Systems) data specifically developed for Agricultural Research Data Network with csv and json files for easy ingestion into crop models.

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Data from: Late Glacial and Holocene records of tree-killing conifer bark beetles in Europe and North America: Implications for forest disturbance dynamics

This study identifies existing fossil records containing bark beetle remains from the end of the Last Glacial Maximum (~14,000 cal. yr BP) to present day using the online databases Neotoma and BugsCEP and literature searches, and compares these data with modern distribution data of selected tree-killing species.

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Vegetation, rainfall simulation, and overland flow experiments before and after tree removal in woodland-encroached sagebrush steppe: the SageSTEP hydrology study

Simulated rainfall and overland-flow experiments are useful for enhancing understanding of surface hydrologic and erosion processes, quantifying runoff and erosion rates, and developing and testing predictive quantitative models. This extensive dataset consists of rainfall simulation and overland flow experimental plot data coupled with associated measures of vegetation, ground cover, and surface soil properties across point to hillslope scales. Data were collected at three woodland-encroached sagebrush (*Artemisia* spp.) rangelands in the Great Basin, USA, under undisturbed/untreated conditions and 1 yr to 9 yr following fire and/or mechanical tree-removal treatments.

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sharpshootR: A Soil Survey Toolkit

Miscellaneous soil data management, summary, visualization, and conversion utilities to support soil survey operations within the USDA-NRCS. Many of the functions are highly specialized and inherit default arguments from the names used by the various NCSS (National Cooperative Soil Survey) databases.

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soilDB: Soil Database Interface

soilDB is one of the Algorithms for Quantitative Pedology (AQP) suite of R packages, and comprises a collection of functions for reading data from USDA-NCSS soil databases including SoilWeb, Series Extent Explorer, and Soil Data Explorer.

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Algorithms for Quantitative Pedology (AQP)

Algorithms for Quantitative Pedology (AQP) is a collection of code, ideas, documentation, and examples wrapped-up into several R packages. The AQP suite of R packages are used to generate figures for SoilWeb, Series Extent Explorer, and Soil Data Explorer.

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Java Newhall Simulation Model (jNSM)

The Java Newhall Simulation Model or jNSM is a mesoscale model that is appropriate for use in regional geospatial analyses that support the MLRA update of published digital soil geographic databases (SSURGO/STATSGO2). This software can be used with monthly, serially complete records from weather stations, Soil Climate Analysis Network (SCAN) stations, and local soil climate monitoring sensors.

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Data from: Data on foliar nutrient concentration of invasive plants in the recipient habitat and their native habitat

To understand the underlying mechanism of extensive growth rate of the highly invasive plant, Old World climbing fern (*Lygodium microphyllum*), in its native habitat in Queensland, Australia and recipient habitat in Florida, United States, the leaf tissue samples from the native and invaded habitats are analyzed.

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LandPKS (Land Potential Knowledge System): Mobile App for Extension, Land-Use and Project Planning, M&E and On-Farm Research

**LandPKS** comprises a free modular mobile phone app connected to cloud-based storage, global databases, and models, downloadable from Google Play or the iTunes App Store; a system for storing and accessing user data; and a system for sharing data, information and knowledge. LandPKS is being developed to help users determine the sustainable potential of their land, including its restoration potential, based on its unique soil, topography and climate. The land potential assessments will be updated based on new evidence regarding the success or failure of new management and restoration systems on different soils.

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