Zabihi, Khodabakhsh
Recent Submissions
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Predicting multi-species Bark Beetle (Coleoptera: Curculionidae: Scolytinae) occurrence in Alaska: open-access big GIS-data mining to provide robust inferenceUniversity of Kansas, 2021-07-03Native bark beetles (Coleoptera: Curculionidae: Scolytinae) are a multi-species complex that rank among the key disturbances of coniferous forests of western North America. Many landscape-level variables are known to influence beetle outbreaks, such as suitable climatic conditions, spatial arrangement of incipient populations, topography, abundance of mature host trees, and disturbance history that include former outbreaks and fire. We assembled the first open access data, which can be used in open source GIS platforms, for understanding the ecology of the bark beetle organism in Alaska. We used boosted classification and regression tree as a machine learning data mining algorithm to model-predict the relationship between 14 environmental variables, as model predictors, and 838 occurrence records of 68 bark beetle species compared to pseudo-absence locations across the state of Alaska. The model predictors include topography- and climate-related predictors as well as feature proximities and anthropogenic factors. We were able to model, predict, and map the multi-species bark beetle occurrences across the state of Alaska on a 1-km spatial resolution in addition to providing a good quality environmental dataset freely accessible for the public. About 16% of the mixed forest and 59% of evergreen forest are expected to be occupied by the bark beetles based on current climatic conditions and biophysical attributes of the landscape. The open access dataset that we prepared, and the machine learning modeling approach that we used, can provide a foundation for future research not only on scolytines but for other multi-species questions of concern, such as forest defoliators, and small and big game wildlife species worldwide.
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Alaska Map of Bark Beetle Presence in 2016 and 2017A shapefile of 68 species locations, surveyed by the USFS from 2016 to 2017, includes 3 bark beetle species. The geographic projection of the map was set at NAD 1983 Alaska Albers.
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Alaska Map of 1-km Space Grid PointsA lattice point grid with a 1-km Euclidean distance in a total point number of 1,522,655 in Alaska. The map is prepared as a shapefile and the geographic projection is NAD 1983 Alaska Albers.
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Alaska Map of Bark Beetle Pseudo-AbsenceWe created a shapefile of 5000 pseudo-absence points, with a minimum Euclidean distance from each other of 1-km across Alaska, as a background dataset with which to compare bark beetle presences. The 5000 random point locations were generated in ArcMap 10.4 (ESRI Inc., Redlands, CA), with the geographic projection of NAD 1983 Alaska Albers.
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Alaska Map of Bark Beetle PresenceA shapefile that we created after compiling 838 records of 68 bark beetle species, as the presence points for the model, provided by the University of Alaska Museum (UAM; http://arctos.database.museum/SpecimenSearch.cfm) in a separate tabulated record for each species. The geographic projection was set at NAD 1983 Alaska Albers. The year the species were identified varied from 1953 to 2018, with nearly half being observed after 2011. Among the pooled bark beetle species, the most dominant genera were, Dryocoetes (n=133), Trypodendron (n=107), Ips (n=104), and Dendroctonus (n=83) (Appendix I). And, the most common species were the striped ambrosia beetle (Trypodendron lineatum (n=74)), Dryocoetes affaber (n=69), the spruce beetle (Dendroctonus rufipennis (n=66)), and the northern spruce engraver (Ips perturbatus (n=52)). The host evergreen trees from which the bark beetle specimens were collected consisted of white spruce (Picea glauca), black spruce (P. mariana), Sitka spruce (P. sitchensis), western hemlock (Tsuga heterophylla), lodgepole pine (Pinus contorta), mountain hemlock (Tsuga mertensiana), Lutz spruce (P.a x lutzii), Tamarack (Larix laricina), Yellow cedar (Cupressus nootkatensis), and Western red cedar (Thuja plicata)).
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Final Map (Figure 7)Classified prediction map of multi-species bark beetle occurrences in different forest types: Mixed and evergreen forests that predicted not to favor bark beetle occurrences (value 0), mixed forests that expected to favor bark beetle occurrences (value 1), and evergreen forests that predicted to be occupied by different bark beetle species (value 2). The 2011 NLCD was the reference map to extract forest type and area across the state of Alaska. The map is prepared at 1-km spatial resolution and the geographic projection is NAD 1983 Alaska Albers.
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Binary Map (Figure 6)Classified prediction map of multi-species bark beetle occurrence using 95% confidence interval of assessment/test points to differentiate predicted index of relative occurrence (RIO) of the ecological model. Value 1 (presence) represents the favorable habitats and value 0 (absence) represents regions that may not be occupied by scolytines community based on the current climatic conditions and biophysical attributes of the landscape. The map is prepared at 1-km spatial resolution and the geographic projection is NAD 1983 Alaska Albers.
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Model 3 (Appendix IV)Predicted distribution map of bark beetles in Alaska using model 3 (model with excluded roads). The map is prepared at 1-km spatial resolution and the geographic projection is NAD 1983 Alaska Albers.
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Model 2 (Figure 3)Predicted distribution map of bark beetles in Alaska using model 2 or ecological model (model without spatially-dependent predictors). The map is prepared at 1-km spatial resolution and the geographic projection is NAD 1983 Alaska Albers.
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Model 1 (Appendix III)Predicted distribution map of bark beetles in Alaska using model 1 (full model). The map is prepared at 1-km spatial resolution and the geographic projection is NAD 1983 Alaska Albers.
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Alaska Map of Distance to InfrastructureThe Alaska map of distance to infrastructure is a raster image file that includes Euclidean distance value from the Alaska infrastructure. We prepared the map at 60-m spatial resolution using a vector map of the Alaska infrastructure. The geographic projection was set at NAD 1983 Alaska Albers.
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Alaska Map of Distance to Main RoadsThe Alaska map of distance to main roads is a raster image file that includes Euclidean distance value from the Alaska main roads. We prepared the map at 60-m spatial resolution using a vector map of the Alaska main roads. The geographic projection was set at NAD 1983 Alaska Albers.
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Alaska Map of Distance to TownsThe Alaska map of distance to towns is a raster image file that includes Euclidean distance value from the Alaska towns and cities. We prepared the map at 60-m spatial resolution using a vector map of the Alaska towns and cities. The geographic projection was set at NAD 1983 Alaska Albers.
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Alaska Map of Distance to Drainage NetworkThe Alaska map of distance to drainage network is a raster image file that includes Euclidean distance value from the Alaska drainage network with more ephemeral water channels. We prepared the map at 60-m spatial resolution using a vector map of the Alaska drainage network. The geographic projection was set at NAD 1983 Alaska Albers.
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Alaska Map of Distance to Lakes and RiversThe Alaska map of distance to lakes and rivers is a raster image file that includes Euclidean distance value from the Alaska lakes and rivers with more permanently standing or flowing water. We prepared the map at 60-m spatial resolution using a vector map of the Alaska lakes and rivers. The geographic projection was set at NAD 1983 Alaska Albers.
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Alaska Map of Distance to CoastlineThe distance to coastline map of Alaska is a raster image file that includes Euclidean distance value from the Alaska coastline. We prepared the map at 60-m spatial resolution using a vector map of the Alaska coastline. The geographic projection was set at NAD 1983 Alaska Albers.
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Alaska Aspect MapWe prepared an aspect map of Alaska at 60-m spatial resolution using the Alaskan Digital Elevation Model (DEM). The geographic projection was set at NAD 1983 Alaska Albers.
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Alaska Slope MapWe prepared a slope map of Alaska at 60-m spatial resolution using the Alaskan Digital Elevation Model (DEM). The geographic projection was set at NAD 1983 Alaska Albers.
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Alaska Digital Elevation Model (DEM)The Digital Elevation Model (DEM) is a raster image file that includes an elevation value at 60-m spatial resolution. The geographic projection was set at NAD 1983 Alaska Albers.
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Alaska Mean Monthly Temperature in 2010The folder includes the 2010 average monthly temperature across the state of Alaska as a raster image file. The spatial resolution is 60-m and the geographic projection is NAD 1983 Alaska Albers.