To systematically evaluate cover crop effects on cotton yield and weed suppression, we conducted a random-effects meta-analysis investigating 10 moderating variables in 104 articles, yielding 1117 independent studies over 48 years.
The Air Temperature Based Thermal Stream Habitat Model was originally developed from weather station information across the Columbia River basin in the Pacific Northwest. Multiple regression was used to predict mean annual air temperatures from elevation, latitude, and longitude with good success R^2 ~ 0.89). The model was developed as an alternative to PRISM data interpolations based on spline surface smoothing and should more accurately represent thermal conditions in stream valleys.
This simple Stream Temperature Modeling and Monitoring approach uses thermograph data and geomorphic predictor variables from GIS software and digital elevation models (DEM). Multiple regression models are used to predict stream temperature metrics throughout a stream network with moderate accuracy (R^2 ~ 0.65). The models can provide basic descriptions of spatial patterns in stream temperatures, suitable habitat distributions for aquatic species, or be used to assess temporal trends related to climate or management activities if multiple years of temperature data are available.
Data from: Cultivar resistance to common scab disease of potato is dependent on the pathogen species
All data from the paper "Cultivar resistance to common scab disease of potato is dependent on the pathogen species." Three separate datasets are included:
1.A csv file with the disease severity of three common scab pathogens across 55 different potato cultivars in a greenhouse pot assay (Figures 2-5 in the associated paper). The included R script was used with this data to perform the ANOVA for the data from the greenhouse pot assay (Table 2 in the associated paper). This script can be used in R for any similar dataset to calculate the significance and percent of total variation for any number of user-defined fixed effects.
2. A zipped file with all of the qPCR data for the expression of the txtAB genes (Figure 6 in the associated paper).
3. An Excel file with the HPLC data for making the thaxtomin detection standard curve and quantifying the amount of thaxtomin in the test sample.
Data from: Multiple immune pathways control susceptibility of Arabidopsis thaliana to the parasitic weed Phelipanche aegyptiaca
Four files are included in this dataset. 1. An R script for generating odds ratio graphs that depict both the 95% and 99% confidence interval across all tested mutants in the referenced paper. 2. An example csv file for use with the R script. 3. A SAS script for running the Proc Glimmix procedure for generating odds ratios of attachments for all tested mutants in the referenced paper. 4. An example JMP file for use with the SAS script.
Images are used frequently in plant phenotyping to capture measurements. This chapter offers a repeatable method for capturing two-dimensional measurements of plant parts in field or laboratory settings using a variety of camera styles (cellular phone, DSLR), with the addition of a printed calibration pattern. The method is based on calibrating the camera using information available from the EXIF tags from the image, as well as visual information from the pattern. Code is provided to implement the method, as well as a dataset for testing. We include steps to verify protocol correctness by imaging an artifact. The use of this protocol for two-dimensional plant phenotypoing will allow data capture from different cameras and environments, with comparison on the same physical scale.
The NorWeST webpage hosts stream temperature data and climate scenarios in a variety of user-friendly digital formats for streams and rivers across the western U.S. Temperature data and model outputs, registered to NHDPlus stream lines, are posted to the website after QA/QC procedures and development of the final temperature model within a river basin.
National Stream Internet (NSI) project was developed as a means of providing a consistent, flexible analytical infrastructure that can be applied with many types of stream data anywhere in the country. A key part of that infrastructure is the NSI network, a digital GIS layer which has a specific topological structure that was designed to work effectively with SSNMs. The NSI network was derived from the National Hydrography Dataset Plus, Version 2 (NHDPlusV2) following technical procedures that ensure compatibility with SSNMs.
The Dynamic Mapping Tool provides a spatial index to over 5,500 sites on streams and rivers in the U.S. and Canada where full year stream temperatures are currently being monitored by numerous agencies. You can filter stream temperature sites by state, agency, year and contact.