Spatial patterning of Artemisia tridentata neighborhoods and relative crowding
Data files
Aug 23, 2022 version files 19.26 MB
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siteA_canopies.dbf
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siteA_canopies.prj
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siteA_canopies.shp
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siteA_canopies.shx
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siteA_ncentroids.dbf
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siteA_ncentroids.prj
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siteA_ncentroids.shp
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siteA_ncentroids.shx
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siteA_neighborhoods.dbf
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siteA_neighborhoods.prj
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siteA_neighborhoods.shp
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siteA_neighborhoods.shx
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siteB_canopies.dbf
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siteB_canopies.prj
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siteB_canopies.shp
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siteB_canopies.shx
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siteB_ncentroids.dbf
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siteB_ncentroids.prj
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siteB_ncentroids.shp
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siteB_ncentroids.shx
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siteB_neighborhoods.dbf
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siteB_neighborhoods.prj
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siteB_neighborhoods.shp
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siteB_neighborhoods.shx
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spatial_patterning_big_sagebrush_DATA_README.rtf
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spatial_patterning_bigsagebrush_RAW_DAC.xlsx
Abstract
Plants reflect resource use in their spatial patterning. Competition for limited resources—such as available soil water in a dryland ecosystem—drives establishment, growth, and mortality, resulting in shifts of spatial arrangement over time. We characterized the spatial patterning of two big sagebrush (Artemisia tridentata subspecies wyomingensis) communities in the upper Green River Basin of Wyoming, USA. We mapped big sagebrush canopies in two, 100-square meter sites and calculated plant neighborhoods as the area closer to a target plant than to any other plant. We assumed that neighborhoods were areas in which the target plant dominates resource use. We found that plant neighborhoods had strong, positive correlations with plant size, indicating that larger neighborhoods may access more belowground resources. We also found that the relationships between experienced crowding, i.e. Crowding Index (CI) by an average neighbor, and neighborhood size, were consistently negative regardless of calculation method. We also found that the residuals of a regression of target plant biomass and neighborhood area were strongly related to the CI calculated via all methods. This means that plants with smaller neighborhoods than expected also experience the greatest crowding by an average neighbor. These results are consistent with negative density dependence and show that greater static crowding predicts smaller neighborhoods in two, undisturbed, intermediate-successional big sagebrush communities. In the future, similar studies of spatial patterning that include interspecific plant-plant interactions will be useful for understanding the relationship between spatial patterning and negative density dependence.
Methods
We collected these data in order to characterize the spatial patterning of Artemisia tridentata plant communities in the upper Green River Basin of Wyoming. During the summer of 2020, we measured plant canopies and mapped their coordinates at two, 10 x 10 meter sites, and captured aerial imagery of the sites. We manually traced plant canopies in ArcMap using both the georeferenced aerial imagery and the coordinates collected in the field. We employed Euclidean allocation in GIS to assign neighborhood polygons to plants and created a dataset of target-plant/neighbor-plant relationships (polygon neighbor analysis) to describe the relative crowding experienced by target plants. Additional details about the data processing are included in the archived Excel document (spatial_patterning_bigsagebrush_RAW_DAC.xlsx).
Usage notes
This archive includes an Excel spreadsheet of all raw space patterning data, variable descriptions, and some metadata notes about data processing. Shapefiles of the neighborhood polygons, plant canopy polygons, and neighborhood centroids are included. While we conducted the majority of our GIS sampling (the creation of the polygon neighbor dataset) in ArcMap, the provided shapefiles are not proprietary so that the analysis may be replicated elsewhere (e.g. R). A README file is also included.