Life Sciences Commons^™

Greater Sage-Grouse Brood Locations On Parker Mountain Utah 1998-2009, David Dahlgren

Browse all Datasets

Species of conservation concern are often habitat specialists, posing significant risk to those species when specific plant communities are threatened. Despite this, practitioners habitually focus conservation efforts on these singular communities, while ignoring ecological mechanisms that explain the wildlife-plant relationships. In doing so, practitioners may overlook alternative vegetation communities that could maintain wildlife populations under alternative conditions (e.g., climate change). Here, we term these areas surrogate habitat, defined as "vegetation communities or resource sites that provide similar critical resources to conventional sites," and assess their potential for conservation using a case-study of Greater sage-grouse (Centrocercus urophasianus) on Parker Mountain, Utah …

Data From: Climate Change-Driven Cumulative Mountain Pine Beetle-Caused Whitebark Pine Mortality In The Greater Yellowstone Ecosystem, William W. Macfarlane

Browse all Datasets

In 2018-2019 the Landscape Assessment System (LAS), an aerial survey method was used to assess mountain pine beetle (Dendroctonus ponderosae; MPB) - caused mortality of whitebark pine (Pinus albicaulis) across the Greater Yellowstone Ecosystem (59000 km2; GYE). This consisted of 11,942 km of flightlines, along which 4,434 geo-tagged, oblique aerial photos were captured and processed. A mortality rating of none to severe (0 to 4 nt attack or 5.0 5.4 old attack) was assigned to each photo based on the amount of red (recent attack) and gray (old attack) trees visible. The method produced a photo inventory of 74 percent …

Object-Detection From Multi-View Remote Sensing Images: A Case Study Of Fruit And Flower Detection And Counting On A Central Florida Strawberry Farm, Caiwang Zheng, Tao Liu, Amr Abd-Elrahman, Vance M. Whitaker, Benjamin Wilkinson

Michigan Tech Publications, Part 2

Object detection in remote sensing images is one of the most critical computer vision tasks for various earth observation applications. Previous studies applied object detection models to orthomosaic images generated from the SfM (Structure-from-Motion) analysis to perform object detection and counting. However, some small objects that are occluded from the vertical view but observable in raw images from the oblique views cannot be detected in the orthomosaic image, leading to an occlusion issue that cannot be resolved with the traditional orthophoto-based approach. Taking strawberry detection as a case study, the objective of this study is to detect small objects directly …

Interactive Map Code (R And Rstudio), Peter G. Butterfield

Data Files: White Oaks in Vinton Furnace Experimental Forest

Interactive map code puts data and coordinates into readable table format and creates data visualizations.

Arch Rock (Widths In Dendrochronology Format), Peter G. Butterfield, Ryan W. Mcewan

Data Files: White Oaks in Vinton Furnace Experimental Forest

Data in this collection regards white oak trees (Quercus alba) in Vinton Furnace Experimental Forest, Vinton County, Ohio. Affiliated images are available at http://ecommons.udayton.edu/mcewanlab_6_images.

File type: .csv

About the data:

• Column A: Year
• Column B and onward: Measurements of tree rings in millimeters; sample title appears in row 1
• Measurements taken using a Velmex Unislide and the Tellervo software application.

Coordinates Of Each Sample, Peter G. Butterfield, Ryan W. Mcewan

Data Files: White Oaks in Vinton Furnace Experimental Forest

Data in this collection regards white oak trees (Quercus alba) in Vinton Furnace Experimental Forest, Vinton County, Ohio. Affiliated images are available at http://ecommons.udayton.edu/mcewanlab_6_images.

File type: .csv

About the data:

• Column A: Year
• Column B and onward: Measurements of tree rings in millimeters; sample title appears in row 1
• Measurements taken using a Velmex Unislide and the Tellervo software application.

Watch Rock (Widths In Dendrochronology Format), Peter G. Butterfield, Ryan W. Mcewan

Data Files: White Oaks in Vinton Furnace Experimental Forest

Data in this collection regards white oak trees (Quercus alba) in Vinton Furnace Experimental Forest, Vinton County, Ohio. Affiliated images are available at http://ecommons.udayton.edu/mcewanlab_6_images.

File type: .csv

About the data:

• Column A: Year
• Column B and onward: Measurements of tree rings in millimeters; sample title appears in row 1
• Measurements taken using a Velmex Unislide and the Tellervo software application.

Watch Rock (Widths In Millimeters), Peter G. Butterfield, Ryan W. Mcewan

Data Files: White Oaks in Vinton Furnace Experimental Forest

Data in this collection regards white oak trees (Quercus alba) in Vinton Furnace Experimental Forest, Vinton County, Ohio. Affiliated images are available at http://ecommons.udayton.edu/mcewanlab_6_images.

File type: .csv

About the data:

• Column A: Year
• Column B and onward: Measurements of tree rings in millimeters; sample title appears in row 1
• Measurements taken using a Velmex Unislide and the Tellervo software application.

Arch Rock (Width In Millimeters), Peter G. Butterfield, Ryan W. Mcewan

Data Files: White Oaks in Vinton Furnace Experimental Forest

Data in this collection regards white oak trees (Quercus alba) in Vinton Furnace Experimental Forest, Vinton County, Ohio. Affiliated images are available at http://ecommons.udayton.edu/mcewanlab_6_images.

File type: .csv

About the data:

• Column A: Year
• Column B and onward: Measurements of tree rings in millimeters; sample title appears in row 1
• Measurements taken using a Velmex Unislide and the Tellervo software application.

Sample Diameter And Date Of Establishment, Peter G. Butterfield, Ryan W. Mcewan

Data Files: White Oaks in Vinton Furnace Experimental Forest

Data in this collection regards white oak trees (Quercus alba) in Vinton Furnace Experimental Forest, Vinton County, Ohio. Affiliated images are available at http://ecommons.udayton.edu/mcewanlab_6_images.

File type: .csv

About the data:

• Column A: Year
• Column B and onward: Measurements of tree rings in millimeters; sample title appears in row 1
• Measurements taken using a Velmex Unislide and the Tellervo software application.

Data For Gridding, Joseph D. Birch, James A. Lutz, Soren Struckman, Jessica Miesel, Justine Karst

Browse all Datasets

Background: Large-diameter trees have an outsized influence on aboveground forest dynamics, composition, and structure. Although their influence on aboveground processes is well studied, their role in shaping belowground fungal communities is largely unknown. We sought to test if (H1) fungal community spatial structure matched aboveground forest structure, (H2) fungal functional guilds exhibited differential associations to aboveground tree, snag, and deadwood, and (H3) that large-diameter trees and snags have a larger influence on fungal community richness than smaller-diameter trees. We used MiSeq sequencing of fungal communities collected from soils in a spatially intensive survey in a portion of Cedar Breaks National …

Fire History And Long-Term Carbon Accumulation In Hemi-Boreal Peatlands Companion Dataset, Dominic Uhelski, Evan Kane, Katherine Heckman, Rodney Chimner

Michigan Tech Research Data

This dataset contains peat property data including location, depth, bulk density, organic matter content, and carbon content, infrared spectra, and radiocarbon dates. Peat cores were collected between 2011 and 2019. Analyses were performed between 2018 and 2021. Samples were collected from peatlands in Michigan, Wisconsin, and Minnesota for the purposes of reconstruction of fire history. The data is associated with a yet-to-be-published manuscript to be submitted to Ecosystems.

A README file is included describing the contents of the dataset and all major spreadsheet files contain a Meta worksheet which describes each column of
data.

Data For Dancing, Joseph D. Birch, James A. Lutz, Justine Karst

Browse all Datasets

Fungal communities can influence the productivity, composition, and survival of trees through cycling nutrients, providing resources, and altering pathogens. Thus, shifts in fungal communities could impact forests by altering interactions between trees and their environments. Fungal community composition may be shaped by stochastic and deterministic processes such as dispersal-limitation, environmental filtering, and partner specificity between trees and fungi. For tree species with large geographic ranges, we expect fungal assembly processes to change with environmental variation across the range of the tree partner. Due to specificity between trees and symbiotic fungi, we expect deterministic to outweigh stochastic processes in root compared …

Conk1 - Forest Pathology Specimen, Robert Z. Selden Jr.

CRHR: Archaeology

Pathology specimen.

Geospatial Data Permanent Plot, Grace K. Attea, Ryan W. Mcewan, John L. Vankat

Data Files

Permanent plot GIS shapefile that measures 100m x 105m and consists of 420 contiguous 5m x 5m subplots. There are 21 transects that run from south to north and 20 subplots per transect that run east to west. This downloadable data is a zipped file containing 8 shapefile building blocks. Geographic Coordinate System: GCS_North_American_1983. Projected Coordinate System: NAD_1983_StatePlane_Ohio_South_FIPS_3402 (meters).

Geospatial Data Trees 1988, Grace K. Attea, Ryan W. Mcewan, John L. Vankat

Data Files

Location and demographic data collected for each individual tree in 1988 in Hueston Woods State Nature Preserve. These maps were digitized from the historical field maps to a GIS shapefile for each sampling year. Geographic Coordinate System: GCS_North_American_1983. Projected Coordinate System: NAD_1983_StatePlane_Ohio_South_FIPS_3402 (meters).

Geospatial Data Trees 1981, Grace K. Attea, Ryan W. Mcewan, John L. Vankat

Data Files

Location and demographic data collected for each individual tree in 1981 in Hueston Woods State Nature Preserve. These maps were digitized from the historical field maps to a GIS shapefile for each sampling year. Geographic Coordinate System: GCS_North_American_1983. Projected Coordinate System: NAD_1983_StatePlane_Ohio_South_FIPS_3402 (meters).

Geospatial Data Trees 2022, Grace K. Attea, Ryan W. Mcewan, John L. Vankat

Data Files

Location and demographic data collected for each individual tree in 2022 in Hueston Woods State Nature Preserve. These maps were digitized to a GIS shapefile for each sampling year. Geographic Coordinate System: GCS_North_American_1983. Projected Coordinate System: NAD_1983_StatePlane_Ohio_South_FIPS_3402 (meters).

Geospatial Data Trees 1994, Grace K. Attea, Ryan W. Mcewan, John L. Vankat

Data Files

Location and demographic data collected for each individual tree in 1994 in Hueston Woods State Nature Preserve. These maps were digitized from the historical field maps to a GIS shapefile for each sampling year. Geographic Coordinate System: GCS_North_American_1983. Projected Coordinate System: NAD_1983_StatePlane_Ohio_South_FIPS_3402 (meters).

Geospatial Data Trees 2000, Grace K. Attea, Ryan W. Mcewan, John L. Vankat

Data Files

Location and demographic data collected for each individual tree in 2000 in Hueston Woods State Nature Preserve. These maps were digitized from the historical field maps to a GIS shapefile for each sampling year. Geographic Coordinate System: GCS_North_American_1983. Projected Coordinate System: NAD_1983_StatePlane_Ohio_South_FIPS_3402 (meters).

Earthworm And Soil Data For Ottawa National Forest, Blair Orr

Michigan Tech Research Data

Two types of analysis were run.

I. Probability of finding L. terrestris in habitat types of the Ottawa National Forests.

Abstract: Parts of the Ottawa National Forest (ONF) provide suitable habitat for invasive earthworms. Extensive earthworm invasion is a relatively recent event on the ONF and this study captures the current state of the earthworm invasion through a four-stage invasive species distribution model (iSDM). The random distribution of earthworms indicates early colonization by earthworms which is moderated by habitat (forest type, soil group, and drainage class). CART modeling was used to determine probability of earthworm invasion. The CART model had …

End-Grain Of Eleven Softwood Species, Dercilio Lopes, Gabrielly Dos Santos Bobadilha, Edward Entsminger, Optimal Llc

College of Forest Resources Publications and Scholarship

End-grain of eleven softwoods species.

End-Grain Of 10 North American Hardwoods, Lopes Dercilio Verly Junior, Greg W. Burgreen, Edward D. Entsminger

College of Forest Resources Publications and Scholarship

This technical note determines the feasibility of using an InceptionV4_ResNetV2 convolutional neural network (CNN) to correctly identify hardwood species from macroscopic images. The method is composed of a commodity smartphone fitted with a 14× macro lens for photography. The end-grains of ten different North American hardwood species were photographed to create a dataset of 1709 images. The stratified 5-fold cross-validation machine-learning method was used, in which the number of testing samples varied from 341 to 342. Data augmentation was performed on-the-fly for each training set by rotating, zooming, and flipping images. It was found that the CNN could correctly identify …

Aquatic Habitat Changes Along The Arkansas River (Supporting Data And Code), Mike Rhodes, Jonathan Spurgeon, Wes Neal, Kristine Evans

College of Forest Resources Publications and Scholarship

The associated code and data are supporting information for an assessment of large-scale changes in aquatic habitats within the varying pools of the Arkansas River, Arkansas, USA following impoundment of the river as part of the McClellan–Kerr Arkansas River Navigation System. We used a combination of Landsat satellite data (30 m resolution) from 1984-2016 and the European Commission Joint Research Center’s (JRC) Global Surface Water dataset (GSW) to assess changes in water availability by aquatic habitat category and river pool in the Arkansas River system. Analysis was completed using Google Earth Engine, with code available in this repository. We also …

Aquatic Habitat Changes Along The Arkansas River (Supporting Data For Analysis), Jonathan Spurgeon, Mike Rhodes, Wes Neal, Kristine Evans

College of Forest Resources Publications and Scholarship

The associated code and data represent a second set of supporting information for an assessment of large-scale changes in aquatic habitats within the varying pools of the Arkansas River, Arkansas, USA following impoundment of the river as part of the McClellan–Kerr Arkansas River Navigation System. We used a combination of Landsat satellite data (30 m resolution) from 1984-2016 and the European Commission Joint Research Center’s (JRC) Global Surface Water dataset (GSW) to assess changes in water availability by aquatic habitat category and river pool in the Arkansas River system. Here we provide compiled .csv files of Arkansas River gauge data, …

Species Distribution Models To Inform At-Risk Species Status Assessments In The Southeastern Us, Carlos Ramirez-Reyes, Mona Nazeri, Garrett Street, Francisco Vilella, D. Todd Jones-Farrand, Kristine O. Evans

College of Forest Resources Publications and Scholarship

The USFWS is working collaboratively with State Wildlife Agencies, Universities, Non-profits and others in the southeast to address the National Listing Workplan. The USFWS needs up-to-date information on current status and the likely impact of future changes to develop Species Status Assessments (SSAs), which help inform listing decisions. States, Universities and other partners are providing species expertise, location data, analytical support and logistical support (e.g. surveys). However, a significant knowledge gap remains in understanding potential species distributions, from which status surveys can be more strategically implemented. This project provides a bridge between species location information and the SSAs by developing …

Data Archive: Using A Coproduction Approach To Map Future Forest Retention Likelihood In The Southeastern United States, Rachel E. Greene, Kristine O. Evans, Michael T. Gray, D. Todd Jones-Farrand, William G. Wathen

College of Forest Resources Publications and Scholarship

Supporting data for publication titled: Using a Coproduction Approach to Map Future Forest Retention Likelihood in the Southeastern United States;

Journal of Forestry, 2020, 28–43 doi:10.1093/jofore/fvz063

Data For Tree Mortality Calibration Of Satellite And Lidar-Derived Fire Severity Estimates, N. Macriss, T. J. Furniss, S.M.A. Jeronimo, E. L. Crowley, O. W. Germain, S. Germain, V. R. Kane, A. J. Larson, J. A. Lutz

Browse all Datasets

The 55 JFSP plots were established to capture forest types, fire histories, and severity levels beyond those found within the YFPD. The plots were square 50 m × 50 m plots established in Pinus ponderosa, Pinus jeffreyi, and Abies concolor – Pinus lambertiana forest types between 1,431 m and 2,250 m elevation. Plots were installed post-fire based on a randomly chosen locations stratified by burn severity levels as calculated from the differenced Normalized Burn Ratio (dNBR). For details on site selection see Furniss et al. (in review). In the field, plots were located using a handheld GPS and …

Conservation Database For The Gulf Coast Region Of The United States, Andrew Shamaskin, Sathishkumar Samiappan, Jiangdong Liu, Kristine Evans, Anna Linhoss

College of Forest Resources Publications and Scholarship

Strategic, data-driven conservation approaches are gaining popularity. A high-resolution geospatial database indicating the ecosystem functions and socioeconomic activity can be very useful for any conservation expert or funding agency. This database presents the developed measures that are derived from openly available geospatial and non-geospatial data sources, and is intended to provide ecological and socioeconomic evidence to support conservation planning efforts along the Gulf Coast Region of the United States. This database was developed by the Strategic Conservation Assessment of Gulf Coast Landscapes (SCA) Project, which is building a series of online tools that can aid in conservation planning efforts along …

Data Files Column Key: Effects Of Amur Honeysuckle (Lonicera Maackii) On Headwater Streams, Julia I. Chapman, Eric B. Borth, Ryan W. Mcewan

Data Files

Document provides a description for each column heading used in the data files contained in the collection "Effects of Amur Honeysuckle (Lonicera maackii) on Headwater Streams."

File is in comma-separated values (.csv) format; to view the file in Excel (.xlsx), see the supplemental file.