Using anova and partitioning of the sum of the squares once you have your data. Partitioning allows the overall variability in a dataset to be ascribed to different types or sources of variability, with the relative importance of each being quantified by the size of each component of the overall sum of squares

Hi Maina,

Though this two issues are closely interwined, you can distinguish themselves with careful researc design.

Using PRA (Participatory Rural Appraisal) technique can be proved helpful here despite of more depency on quantitative random sample. As the community lives there for life long withstanding it, they are best acquinted with the scenario and proper knowledge of the reason aaffecting them. Thereby, you can consider to incorporate bottom up research methodology associating indigenous community e.g. some specific PRA tools like Focus Group Discussion, historical timeline, Cause-Effect Method, Pairwise ranking system.

Hope this help.