This is a mini-hotspot protocol because is restricted to biodiversity patterns within a region and landscape based on logistic/practical/ecological constraints. The goal is to match shrub surveys to wildlife surveys at appropriate spatial grains & extents.
Similar to these plots but at reduced, regional scales.
1. Geo-plot the aggregated previous instances of animal/lizard sighting.
2. Draw a circle around aggregations in space and through time (best way to use Ripley k-function analyses).
3. Iteratively do this through time to identify inter-annual replicability (set different time windows) – similar to the analytics of k-function in space. *
4. Overlay with shrub densities via landscape maps.
5. Hit the field and do 3 short transects with t-square protocol within each mini-hotspot.
Goal: A reasonable benchmark is 200 shrubs total per site and approximately 10 mini-hotpots within treatment area and in the reference site.
*2 & 3 – simple way – print up maps, draw circles at spatial appropriate scales for sampling shrubs (i.e. match grain size to shrub size & distribution patterns). There are also very nice resampling statistics available to explore spatiotemporal autocorrelation patterns.