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You are here:
  1. Home
  2. Research
  3. Faculty Labs
  4. Walter Applied Spatial Ecology Laboratory
  5. Research Projects

Research Projects

Current Projects

Spatial analysis of black bears to assess harvest vulnerability in relation to landowner distribution
Landscape genetics of white-tailed deer to assess population structure for surveillance of chronic wasting disease
The effects of targeted removal of deer groups on the epidemiology of chronic wasting disease in wild white-tailed deer in Pennsylvania

Completed Projects

Developing an Adaptive Management Approach for Potential Surveillance and Spread of Chronic Wasting Disease in White-tailed Deer in Pennsylvania
Surveillance and monitoring of river otter populations in Pennsylvania
Modeling potential habitat for pheasant population restoration

Walter Applied Spatial Ecology Laboratory

  • Walter Applied Spatial Ecology Laboratory Overview
  • Lab Members
  • Join the Lab
  • Publications
  • Research Projects
    • Research Projects Overview
    • Current Projects
      • Current Projects Overview
      • The effects of targeted removal of deer groups on the epidemiology of chronic wasting disease in wild white-tailed deer in Pennsylvania
    • Completed Projects
      • Completed Projects Overview
      • Modeling potential habitat for pheasant population restoration
  • Additional Labs
    • Additional Labs Overview
    • Spatial Data Analysis Lab
    • Landscape Genetics Lab
    • Stable Isotope Ecology Lab
  • Applied Spatial Ecology Workshop
  • Manual of Applied Spatial Ecology
    • Manual of Applied Spatial Ecology Overview
    • Figures
    • Acknowledgments
    • Preface
    • Chapter 1 - Data Manipulation and Management
      • Chapter 1 - Data Manipulation and Management Overview
      • 1.1 Load R software and packages
      • 1.2 Geographic coordinate systems
      • 1.3 Projected coordinate systems
      • 1.4 Transformations Between Coordinate Systems
      • 1.5 Import and Format Datasets
      • 1.6 Manipulate Polygon Layer
      • 1.7 Manipulate Raster Data Layer
      • 1.8 Creating a Hexagonal Polygon Grid Over a Study Area
      • 1.9 Creating a Square Polygon Grid Over a Study Area
      • 1.10 Creating buffers
    • Chapter 2 - Climate Data Interpolation
      • Chapter 2 - Climate Data Interpolation Overview
      • Introduction
      • 2.1 Incorporating Background Spatial Layers
      • 2.2 Accessing Climate Data
      • 2.3 Cleaning Raw Climate Data
      • 2.4 Using data in R
      • 2.5 Importing Dynamically Downscaled Global Climate Data
    • Chapter 3 - Movement Methods
      • Chapter 3 - Movement Methods Overview
      • Introduction
      • 3.1 Importing datasets from a web source
      • 3.2 Movement trajectories
      • 3.3 Distance between locations
      • 3.4 First Passage Time (FPT)
      • 3.5 Regular Trajectories
      • 3.6 Net Squared Displacement
      • 3.7 Movement Trajectory Animation
    • Chapter 4 - Home Range Estimation
      • Chapter 4 - Home Range Estimation Overview
      • 4.1 Kernel Density Estimation (KDE) with reference bandwidth selection (href)
      • 4.2 KDE with least-squares cross validation bandwidth selection (hlscv)
      • 4.3 KDE with plug-in bandwidth selection (hplug-in)
      • 4.4 Brownian Bridge Movement Models (BBMM)
      • 4.5 Movement-based Kernel Density Estimation (MKDE)
      • 4.6 Dynamic Brownian Bridge Movement Model (dBBMM)
      • 4.7 Characteristic Hull Polygons (CHP)
      • 4.8 Local Convex Hull (LoCoH)
    • Chapter 5 - Overlap Indices
      • Chapter 5 - Overlap Indices Overview
      • Introduction
      • 5.1 Percent overlap
      • 5.2 Probability overlap
      • 5.3 Bhattacharyya’s affinity
      • 5.4 Utilization distribution overlap index
      • 5.5 Hellinger’s distance
      • 5.6 Volume of intersection index
    • Chapter 6 - Three-dimensional Analysis
      • Chapter 6 - Three-dimensional Analysis Overview
      • 6.1 Three-dimensional home range
      • 6.2 Three-dimensional exploration of digital elevation models (DEMs)
    • Chapter 7 - Landscape Metrics
      • Chapter 7 - Landscape Metrics Overview
      • Introduction
      • 7.1 Landscape metrics for a single area
      • 7.2 Landscape metrics within polygons
      • 7.3 Landscape Metrics within buffers
    • Chapter 8 - Resource Selection
      • Chapter 8 - Resource Selection Overview
      • Introduction
      • 8.1 Minimum Convex Polygon
      • 8.2 Preparing linear measures
      • 8.3 Preparing additional covariates
      • 8.4 Selection ratios
      • 8.5 Resource selection functions
    • Chapter 9 - Spatial Epidemiology in WinBUGS
      • Chapter 9 - Spatial Epidemiology in WinBUGS Overview
      • Introduction
      • 9.1 Data preparation in R
      • 9.2 Raster manipulation in R
      • 9.3 Combine Data Formats in R
      • 9.4 Data preparation of NDVI covariate
      • 9.5 Data preparation for R2WinBUGS
      • 9.6 Data preparation within ArcMap
      • 9.7 Check model
      • 9.8 Load data
      • 9.9 Compiling chains
      • 9.10 Load initial values
      • 9.11 Sample monitor tool
      • 9.12 Update tool
      • 9.13 Further considerations
    • Chapter 10 - Miscellaneous Code
      • Chapter 10 - Miscellaneous Code Overview
      • 10.1 Remove or search for duplicated GPS locations in a data frame
      • 10.2 Need to convert back to a matrix to be able to export the data or manipulate the data
      • 10.3 Remove quotations marks around values in results table or printout
      • 10.4 Bin numeric variables into categories
      • 10.5 Recode variables in Rcmdr
      • 10.6 Jitter UTM coordinates before making SpatialPointsDataFrame
      • 10.7 Remove extraneous locations or remove all data for a single animal by animal ID
      • 10.8 Generate sequential numbers as ID’s for each location then add back to original dataset
      • 10.9 Rename data by deleting a portion of the string
      • 10.10 Grab text included in strings of varying lengths
      • 10.11 Rename levels of factor
      • 10.12 Recode numeric values as factors into categories
      • 10.13 Add leading zeros to single digit numbers to match datasets
      • 10.14 Force a DBRB class output to a data frame
      • 10.15 Subset GPS locations by a date range
      • 10.16 Drivers for rdgal input/ouput but run command for complete list if needed
    • Literature Cited
    • Complete Manual pdf
    • Exercise Datasets
  • Contact
PA Cooperative Research Unit

Social Media

  • @walterASEL
PA Cooperative Research Unit

Social Media

  • @walterASEL
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