Analysis with R: Assignment 3

Submit your assignment for the Using output module in a reply to this topic

Remember to include these six elements:

  1. Your research question :question:
  2. The answer :bulb: to your question
  3. AIC-based evidence :1234: to support your conclusion
  4. Density estimate(s) :dart: with confidence intervals
  5. A brief reflection :thinking: on your next step, challenge you solved, problem you still have or leap of understanding
  6. Give specific and useful feedback :thumbsup: to a coursemate

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Firstly, the research questions and hypotheses that I tried to adress were:

  • What is lemur density in the study area (NW of Madagascar)?
  • Is density affected by core length and percentage? And in what magnitude?
  • Does detectability change across the two study forests (Anabohazo and Ankarafa)?

Based on the obtained analysis I can conclude that.

  • The density estimate obtained is 175 lemurs/km-2
  • Density changes depending on core length (for example we have a density of 95 lemurs per squared km at 0m, 144 at 350 m and 218 at 700 m), but this cannot be saig about core percentage. This was obtained from our best candidate model (using half normal detectability function and computing forest and core length as covariates; se table below).
  • Detecability is greatly affected depending on the forests, with an estimate of 7.8 (CI 7.2- 8.6) in Anabohazo compared to 12.8 (CI 11.3- 14.6) in Ankarafa.

The obtained model table containing the potential models including both half normal and hazard rate functions as well as the three (mentioned) potential study covariates is the following:

It is important to note that Core percentage also showed a poor performance according to model summed weights and evidence ratios of models containing this variable compared to the identical ones that did not contain it, hence helping to discard its potential as an explanatory variable.