Page 31 - WIS

the target species being present at a sampled location. One could then perform a
regression analysis to see the relationships between data frequency and
environmental or other factors.

The photographic count data can be converted to a binary format (0 or 1)
describing the detection (1) or non-detection (0) of the focal species at sampling
sites during repeated visits. This format allows us to estimate the probability of a
site being occupied and the probability of detecting the species in an occupied
site. Output measures are the percentage of the total area occupied and the

probability of occupancy of a sampled site, which may be parameters of interest
for species monitoring on a larger scale.

5.2.5 Data Analysis

The simplest data analysis method is to build the cumulative species curve;
species richness against the sampling effort (day/sites/replicate). To reduce
recording the same individual, capture recapture and standard observation
approaches can be applied throughout the study. In case of availability of
abundance data, further analyses can be done, such as species accumulation
curves (species richness against abundance/individuals), relative abundance, and
diversity indices (e.g., Shannon index, Simpson index and Evenness). All
biodiversity indices can be computed using computer software or manually using
a formula. Photographic frequencies as abundance indices are not recommended
but can also be done with a well-developed standard method justification.

GUIDANCE DOCUMENT ON WILDLIFE 27
IMPACT STUDY FOR IN ENVIRONMENTAL
IMPACT ASSESSMENT (EIA)