Relating landscape elements to animal locations. To aid in modeling habitat selection, the incumbent will associate landscape information with animal locations. Landscape variables will be collected at multiple scales, and could include extracting raster data at and around point locations, within grid cells across the landscape, or within buffers along animal movement paths. Deriving landscape metrics from raster layers. Habitat selection models will include parameters characterizing landscape configuration. Processing and analysis of animal movement data. Processing raw animal movement data will be the initial step for much of our analyses
Masters degree in forestry, wildlife, geography, or related natural resources field. Working with geographic data in ArcGIS, QGIS, and R. Extracting raster data to vector attributes. Using Gradient Nearest Neighbor (GNN) forest structure data for habitat modeling. Working with animal movement data, including cleaning and preparing data for analysis and performing descriptive analyses on the data
Position Information Department Institute Natrl Res Dir (RNR) Position Title Faculty Research Assistant Job Title Faculty Research Assistant Appointment Type Academic Teaching/Research Faculty Job Location Portland Position Appointment Percent 100 Appointment Basis 12 Faculty Status Regular Tenure Status Fixed-Term Pay Method Salary Recommended Full-Time Salary Range $42,300 Position Summary The Institute of Natural Resources invites applications for a full-time (1.00 FTE ), 12-month, Faculty Research Assistant position. Reappointment is at the discretion of the Director. The position will focus on understanding the effects of biotic and abiotic factors on the demography and habitat associations of the fisher (Pekania pennanti) in the southern Sierra Nevada. Primary factors of interest include forest management activities such as thinning and prescribed fire, tree mortality related to bark-beetles, and changes in climatic conditions that could influence forest habitat conditions or fisher use of the landscape. The incumbent primarily serves as a geospatial analyst providing geographical analysis and data processing to various projects primarily associated with fisher research. Primary duties are in GIS , spatial modeling, remote sensing, and data processing support. Principle foci include (1) extracting environmental variables from existing raster map layers, in order to relate species (e.g., fisher) locations to the amount and configuration of surrounding habitat elements and topographic elements at multiple scales; (2) deriving landscape metrics from raster layers; (3) processing and analysis of animal movement data; (4) applying remote sensing techniques to map land cover types (e.g. tree mortality) in the study area using satellite imagery. Of note, although some field work is ongoing, most of the data to be used in analysis have already been collected as part of two long term studies of fisher ecology in the southern Sierra Nevada. The incumbent will thus be contributing to final analyses and products that stem from a decade of field work on a species of high regional conservation value, and will be supporting collaborations with other professionals working to address various questions related to fisher ecology in a changing forest environment. Position Duties 20% - Relating landscape elements to animal locations. To aid in modeling habitat selection, the incumbent will associate landscape information with animal locations. Landscape variables will be collected at multiple scales, and could include extracting raster data at and around point locations, within grid cells across the landscape, or within buffers along animal movement paths. These data will be organized appropriately for input into habitat selection models. The incumbent will also perform spatial analyses on proximity of animal locations to landscape features (e.g., streams, roads, land cover edges, etc.) 20% - Deriving landscape metrics from raster layers. Habitat selection models will include parameters characterizing landscape configuration. The incumbent will use FRAGSTATS or other appropriate software to create layers containing these variables. The incumbent should have theoretical knowledge in landscape ecology and will contribute to selecting appropriate metrics for analysis. 15% - Processing and analysis of animal movement data. Processing raw animal movement data will be the initial step for much of our analyses. The incumbent should be familiar with both GPS and radio telemetry data. The incumbent will aid in data preparation, inspection, and management (e.g. cleaning, subsetting) and will carry out exploratory and descriptive analyses to explore patterns in the data (e.g., home-range size, step-length distribution). 25% - Apply remote sensing techniques to map land cover types using satellite imagery. In the southern Sierra Nevada, forests are rapidly changing due to drought and beetle-related tree mortality. Understanding how fishers respond to these changes requires up to date land cover data. The incumbent will apply supervised land cover classification techniques to RapidEye satellite imagery in order provide consistently updated land cover layers at high spatial resolution (5 meter). This will require imagery acquisition and preprocessing tasks such as applying atmospheric corrections. The incumbent will create training and validation datasets by visually interpreting 1-meter NAIP imagery. The incumbent will also calculate vegetation indices to use as input into a random forest classifier. The incumbent will create percent tree mortality maps by sampling the 5 meter land cover map and performing a random forest regression using Landsat data. 20% - Other duties. The incumbent will carry out other tasks related to the research project as needed. GIS -related tasks may include creating sampling grids, generating random points or polygons that meet specific criteria, and making maps for use in the field. Other responsibilities may include producing maps, graphs and charts for publications and reports. Some fieldwork related to research on fishers and other wildlife species is expected. Minimum/Required Qualifications Masters degree in forestry, wildlife, geography, or related natural resources field. Must have the following competencies in GIS : - Working with geographic data in ArcGIS, QGIS , and R - Extracting raster data to vector attributes - Using Gradient Nearest Neighbor ( GNN ) forest structure data for habitat modeling - Working with animal movement data, including cleaning and preparing data for analysis and performing descriptive analyses on the data - Modeling animal home ranges in R using kernel density estimation - Experience with spatial analysis tools and techniques (e.g. minimum distance, map algebra, moving windows, zonal statistics) - Reclassifying raster data and more generally making raster calculations - Working with raster Digital Elevation Models (DEMs) to create maps of slope and aspect - Experience automating tasks using computer programming routines (in R, Python, ArcGIS ModelBuilder) - Creating publication quality maps and figures Must have the following competencies in remote sensing: - Identifying land cover characteristics by visually interpreting high resolution satellite data across various elevations in the southern Sierra Nevada, California - Creating training and validation datasets for supervised classifications (ArcGIS/ QGIS ) - Using RapidEye, Landsat, and NAIP data products - Performing atmospheric corrections to satellite data - Performing Random Forest classification and regression using R - Performing Principal Components Analysis on raster data in R - Conducting accuracy assessments of land cover classifications - Creating scatter plots to help distinguish land cover types in the spectral domain Must have the following competencies in landscape ecology: - Calculating landscape metrics in FRAGSTATS (e.g. edge metrics, land cover proportions, etc.) - Formatting raster datasets for input to FRAGSTATS - A theoretical understanding of various landscape metrics, including those related to habitat configuration and composition. - Understanding of spatial scale and the implications of differing scales of analysis Must have the following additional skills: - Data organization and database management (Microsoft Access and Excel) - Writing skills, including experience with grant writing. - Ability to work well as part of a team and communicate with co-workers and collaborators This position requires driving a University vehicle or a personal vehicle on behalf of the University; therefore, the incumbent must successfully complete a Motor Vehicle History Check, possess and maintain a current, valid driver’s license in their state of residence, be determined to be position qualified and self-report convictions (as per Voluntary and Compulsory Driver Standards OAR 125-155-0200) as per OAR 576-056-0000 et seq. Preferred (Special) Qualifications - Experience performing animal survival analysis - Field skills relevant to wildlife research or forest ecology such as locating animals via radio telemetry, bird banding, setting and checking traps for fishers and western pond turtles (Actinemys marmorata), handling animals to apply radio collars /tags and collect data on animal health, record measurements, etc. Field work will help provide context when working with data. A demonstrable commitment to promoting and enhancing diversity. Working Conditions / Work Schedule This position requires a clear and unambiguous commitment to compliance of all National Collegiate Athletic Association (NCAA) regulations for Division I (FBS) universities. No Posting Detail Information Posting Number P02595UF Number of Vacancies 1 Anticipated Appointment Begin Date 11/30/2018 Anticipated Appointment End Date Posting Date 11/09/2018 Full Consideration Date Closing Date 11/23/2018 Indicate how you intend to recruit for this search Competitive / External - open to ALL qualified applicants Special Instructions to Applicants When applying you will be required to attach the following electronic documents: 1) A resume/CV; For additional information please contact: Sean Matthews at email@example.com. OSU commits to inclusive excellence by advancing equity and diversity in all that we do. We are an Affirmative Action/Equal Opportunity employer, and particularly encourage applications from members of historically underrepresented racial/ethnic groups, women, individuals with disabilities, veterans, LGBTQ community members, and others who demonstrate the ability to help us achieve our vision of a diverse and inclusive community. This position requires driving a university vehicle or a personal vehicle on behalf of the university; therefore, the incumbent must successfully complete a motor vehicle history check, possess and maintain a current, valid driver’s license in their state of residence, be determined to be position qualified and self-report convictions as per University Policy 05-030 et seq. Offers of employment are contingent upon meeting all minimum qualifications including the motor vehicle check requirement.
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