Thanks to advances in Geographic Information Systems (GIS) computing technology, evaluating changes to lake bottoms over time has gotten much easier! Prior to GIS, biologists and surveyors would go through great pains to ensure that repeated data collection in study areas of interest would precisely fall on the same area or transect. If this condition was not met, data would have to be thrown out because biologists could never be sure that the difference seen between two time periods was real, an artifact of sampling a different area, or a product of sampling in a different way. Consequently, efforts from multiple groups collecting similar data in the same system but in a slightly different way could not be leveraged. This is an unfortunate missed opportunity that ciBioBase uniquely handles.
First, ciBioBase uniformly interprets acoustic signals and the output is the same regardless of the skill level of the individual collecting the data. Second, ciBioBase employs kriging to create a statistically robust uniform map output that figuratively turns Survey 1 by Bob Smith from an orange into an apple and Survey 2 by Amy Johnson in the same area from a grapefruit into an apple. This is unique to kriging which is a geostatistical procedure. All other standard interpolation methods are simply 3D representations of the input data and each map will look different depending on the precise location of your survey points. Only kriging turns different fruits into apples.
Kriging takes irregularly spaced data points and creates a smooth GIS map (also called a raster grid) based on the geostatistical properties of the input data. Generally, points close together are more related than points farther away but the precise relationship can vary from location to location. Kriging uses the actual statistical relationship of neighboring data points to make predictions in unsampled locations. Other popular methods such as Inverse-Distance-Weighted (IDW) interpolation make simple assumptions of relatedness and does not use actual data to influence predictions in unsampled locations.
Through its use of kriging, ciBioBase removes the concern of precisely following the same path from survey to survey; which is very difficult to do on moving water even for the most seasoned surveyor. Further this process can leverage passive data collection while doing other survey work, fishing, or simply enjoying a pleasure cruise and turn it into useful information for water resource management and protection (Figures 1-4).
|Figure 1. Fisheries biologists can collect fish habitat data passively while conducting electrofishing fish surveys.|
|Figure 2. Passively collect depth and vegetation abundance data while enjoying a pleasure cruise with the kids or fishing.|
|Figure 3. Result of merged ciBioBase trip path data from passive data collection (above) resulting in a uniform vegetation map (below).|
|Figure 5. ciBioBase automated summary report excerpt showing both coordinate point and kriging grid summaries|
|Figure 6. Example automated summary report showing results from a standard transect survey. Because data lie along straight paths and are mostly uniformly spaced, point data summaries should be used.|
However, if you idle for long periods time collecting samples on the lake or trying to entice finicky fish to bite, many data points amass in one location (Figure 6) and can bias the statistics from the point data (Figure 7).
In the situation above, the differences between the point and grid data are larger and the grid data becomes more important to use for formal statistical summaries and reports (Figure 8). The upshot is when in doubt, use the grid statistics for your data summaries.
|Figure 8. Differences between point and grid statistical summaries when data along trip path are not uniform. In these situations, use the statistics from the uniform grid for report summaries and lake management decision making.|
A better use of your time
By automating the complexities of creating maps, ciBioBase users do not need to spend precious time and money dealing with manual data collection with survey rods and hand held GPS’s, entering data with a pencil onto a datasheet, and then figuring out how to display the data in GIS and run Geostatistics models to get a map. Before BioBase’s launch in 2011, bottom and vegetation mapping was a costly endeavor and often just wasn’t done. ciBioBase is changing the game and is empowering all citizens regardless of technical expertise with the ability to see what is below the water’s surface, how it’s changing over time, and how to best manage that change.