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My research project aims to validate a pattern I observed, that Common snowberry (Symphoricarpos albus) distribution is limited to environments with less than 20% slope gradient, or that common snowberry distribution diminishes as slope gradient percentage increases. During my initial field observations, I started noticing that plant species occurred in one environmental gradient, but not in the other. My first observation was that the dominant tree species would differ between environmental gradients. For example, the riparian area was dominated by black cottonwood (Populus trichocarpa), whereas the upland area was dominated by ponderosa pine (Pinus ponderosa). When I started making observations about the shrub and herb layer I noticed similar patterns, where some species were present in one area, but not in the other.
I chose to focus on common snowberry distribution and started asking questions that may explain why common snowberry was present in the riparian area, but not in the upland area. I questioned slope gradient percentage as a potential indicator of water availability, slope aspect as an indicator of sun exposure, soil type, soil moisture and surrounding topography. When I relate this back to ecological processes, I want to focus my research project on abiotic factors and the physical environment including local topography, the hydrological cycle and the energy cycle. In summary, my research aims to explore that the physical environment (topography, slope, aspect etc.) is an indicator of species occurrence and ecological communities.
Three keys words I would associate with my research project include, ecosystem indicators, ecological communities and physical environment.
This sounds like an interesting research project! My main question is; do you think your predictor variables (abiotic factors) including slope aspect and soil moisture are inter-dependent? Slope aspect greatly influences soil moisture because south-facing slopes experience more solar radiation and warming over the course of the day, which directly influences soil moisture content.
Your predictor variables may also covariate with your response variable, are you going to consider all these variables together when calculating your statistics? Ie. Using an ANCOVA analysis?