Class
Article
College
College of Science
Department
Biology Department
Faculty Mentor
William Pearse
Presentation Type
Oral Presentation
Abstract
Ecological assembly processes, such as environmental filtering, competition, and facilitation drive plant community phylogenetic structure. Detecting the relative influence of these processes, which are known to vary across spatial scales, has proven difficult. We present and test a multi-scale, fractal sampling design, that allows flexible, straightforward sampling of assemblages and the environment they live in, at multiple scales. We use a simulation to demonstrate that our design provides more comparisons between sampling locations (and thereby statistical power) across many scales and especially at smaller and larger scales than a random design. We implemented our design along the Right Hand Fork of the Logan River and found that our design effectively captures different amounts of change in plant phylogenetic diversity across environmental gradients at different scales. We also decomposed the variance for each metric found at different scales and found that the spatial structure of our design did capture more variance in plant assemblages at specific scales. Together, this theoretical and empirical evidence supports the flexibility and efficiency of this method to simultaneously sample environmental and community heterogeneity at small and large scales.
Location
Room 155
Start Date
4-11-2019 1:30 PM
End Date
4-11-2019 2:45 PM
Included in
Sampling Ecological Diversity and Process Across Scales Using Fractal Triads
Room 155
Ecological assembly processes, such as environmental filtering, competition, and facilitation drive plant community phylogenetic structure. Detecting the relative influence of these processes, which are known to vary across spatial scales, has proven difficult. We present and test a multi-scale, fractal sampling design, that allows flexible, straightforward sampling of assemblages and the environment they live in, at multiple scales. We use a simulation to demonstrate that our design provides more comparisons between sampling locations (and thereby statistical power) across many scales and especially at smaller and larger scales than a random design. We implemented our design along the Right Hand Fork of the Logan River and found that our design effectively captures different amounts of change in plant phylogenetic diversity across environmental gradients at different scales. We also decomposed the variance for each metric found at different scales and found that the spatial structure of our design did capture more variance in plant assemblages at specific scales. Together, this theoretical and empirical evidence supports the flexibility and efficiency of this method to simultaneously sample environmental and community heterogeneity at small and large scales.