Rowan / Mountain ash study

Behind my backyard there is a trail which I notice an abundance of Rowan or Mountain Ash. Even though it is winter , the berries still remain a bright red color while the leaves shrivel away and turn brown.

 Hypothesis:

During the winter season, the presence of rowans and mountain ashes in a given ecosystem exerts a positive influence on bird species diversity and abundance of berries due to more fertilization by birds.

Prediction:

I anticipate that regions with an elevated area with more density of rowans and mountain ashes will exhibit increased of bird species in winter. This correlation is expected to be attributed to the presence and accessibility of food resources, particularly berries. The study will involve measurements to assess the abundance of berries in these areas.

For the location gradient the path has three location where the rowans are present and spread apart , at the start of the trail which is more in a hill , around the middle and almost towards the end which is more of a shallow ground.

  • Response Variable: Bird species diversity 

Type: Continuous 

The number and variety of bird species and their abundance in the specified ecosystem during winter.

  • Explanatory Variable: Density of rowans and mountain ashes

Type: Continuous

The measure of the density or distribution of rowans and mountain ashes in the ecosystem, providing an indication of the availability of resources for birds.

or 

  • Explanatory Variable: Presence or absence of berries

Type: Categorical

This variable indicates whether the selected areas have berries available or not, directly addressing the hypothesized relationship between berries and bird species diversity and abundance.

2 thoughts to “Rowan / Mountain ash study”

  1. Sounds like a good start to your hypothesis and experimental design. Given that it is winter, it might make the most sense to focus on the presence / density of rowans/mountain ash rather than berries specifically. Now you need to think of detailed experimental design details. How will you do your point counts and over what area and how many replicates.

  2. Interesting and great observation. The predictor and response variable will be measurable in your field setting. The presence or absence of berries can also be influenced by other factors like wind, snow or animals.

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