Data from: Range size, local abundance and effect inform species descriptions at scales relevant for local conservation practice
This study describes how metrics defining invasions may be more broadly applied to both native and invasive species in vegetation management, supporting their relevance to local scales of species conservation and management. A sample monitoring dataset is used to compare range size, local abundance and effect as well as summary calculations of landscape penetration (range size × local abundance) and impact (landscape penetration × effect) for native and invasive species in the mixed-grass plant community of western North Dakota, USA.
Data from: Apple flower detection using deep convolutional networks
With the goal of automating bloom intensity estimation, a method a novel method for apple flower detection is presented in which a pre-trained convolutional neural network (CNN) is fine-tuned to become specially sensitive to flowers.
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Data from: Biological control of boxwood blight by Pseudomonas protegens recovered from recycling irrigation systems
A total of 1547 bacterial strains recovered from recycling irrigation systems were evaluated *in vitro* and *in planta* for their biological control efficacy against boxwood (*Buxus* spp.) blight caused by *Calonectria pseudonaviculata* (*Cps*), an emerging fungal disease in the United States. *Pseudomonas protegens* strains produced antifungal secondary metabolites that reduced *Cps* growth and infection.
Data from: Data for the calculation of an indicator of the comprehensiveness of conservation of useful wild plants
The datasets and code presented in this Data in Brief article are related to the research article entitled "Comprehensiveness of conservation of useful wild plants: an operational indicator for biodiversity and sustainable development targets". These data facilitate indicator assessments and serve as a baseline against which future calculations of the indicator can be measured. The data can also contribute to other species distribution modeling, ecological research, and conservation analysis purposes.
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RF-CLASS: Remote-sensing-based Flood Crop Loss Assessment Service System
The Remote-sensing-based Flood Crop Loss Assessment Service System (RF-CLASS) is an Earth Observation (EO) based flood crop loss assessment cyber-service system operated by the Center for Spatial Information Science and Systems (CSISS), George Mason University. RF-CLASS supports flood-related crop statistics and insurance decision-making.
Uniform Soybean Tests, Northern Region
The Uniform Soybean Tests, Northern Region, in place since 1941, evaluate yield, disease resistance, and quality traits of public breeding lines from northern states of the USA and Canadian provinces. The annual reports which compile the test results (PDF format) are available, and new reports are added annually.
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Uniform Soybean Tests, Southern States
The Uniform Soybean Tests, Southern States, in place since 1943, evaluate yield, disease resistance, and quality traits of public breeding lines from the southern states of the USA. The annual reports which compile the test results (PDF format) are available, and new reports are added annually.
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The Triticeae Toolbox
[The Triticeae Toolbox](https://triticeaetoolbox.org/) (T3) webportal hosts data generated by the Triticeae Coordinated Agricultural Project (CAP), funded by the National Institute for Food and Agriculture (NIFA) of the United States Department of Agriculture (USDA). T3 contains SNP, phenotypic, and pedigree data from wheat and barley germplasm in the Triticeae CAP integrating rapidly expanding DNA marker and sequence data with traditional phenotypic data.