Budgets are tight, time is short, labor resources and technical know-how are scarce. These truths are the motivating force behind the ciBioBase system. Recently, we ran an analysis that demonstrates the cost-effectiveness of ciBioBase. We selected 3 peer-reviewed studies that demonstrated three alternative methods for whole lake assessments of vegetation abundance and compared the costs of producing a vegetation biovolume map with ciBioBase. The first two studies Valley and Drake (2007) and Sabol et al. (2009) used a scientific-grade echosounder, associated software, and required expertise in hydroacoustics and Geographic Information Systems (GIS). Hardware and software costs were adjusted to 2012 dollars which actually brought costs down to a total of $18,400. These costs were amortized over 5 years at 5% interest and scaled to daily costs assuming use in a season would not typically exceed 45 days. For both methods, hardware and software costs amounted to approximately $84 a day. We did not factor in time on the water for any of these analyses, or the cost of training in hydroacoustics, geostatistics, and GIS.
Labor costs were relatively large in the Valley and Drake (2007) study because the authors were working in environments that exceeded the capability of the vegetation-detecting algorithm they were using. Specifically, noisy signals generated in surface-growing vegetation canopies were thrown out and thus biasing biovolume (i.e., percent of the water column occupied by vegetation) downward. Consequently, Valley and Drake did ping-by-ping verification and reclassification where signals were obscured by surface-growing vegetation. Summing the modest hardware and high labor costs to manually verify thousands of pings, the cost of producing a vegetation map in a 500-acre lake using methods described in Valley and Drake (2007) was approximately $1,288.
Labor costs were significantly lower in the Sabol et al. (2009) investigation because we assume vegetation did not grow to the surface in the Wisconsin study lake during the investigation and thus the vegetation algorithm processed individual files relatively quickly. Taking the labor costs (10 hrs @ $25/hr) in Sabol et al. (2009) and adding in adjusted amortized hardware and annual maintenance costs, the costs of producing a map on a 500-acre lake was a much lower $357 compared with Valley and Drake (2007).
The third study evaluated the LAKEWATCH volunteer lake monitoring program administered by the University of Florida. LAKEWATCH utilizes commercial-grade Lowrance™ sonar units to log data on bathymetry and vegetation height/biovolume (otherwise known as percent volume inhabited; Hoyer 2009). Entry-level technicians analyze 100 random points from pooled transect files and record depth and estimate plant height to get a lake-wide estimate of percent area covered by vegetation and percent volume inhabited with aquatic plants. Although the objective of LAKEWATCH is not to create high resolution vegetation maps, in order to make apples-to-apples comparisons, we had to scale-up the Hoyer (2009) method to reflect the same survey resolution (16,383 points) of the previous two methods. This resulted in an incredibly high cost of $6,884 to produce the same type of vegetation map as described with the previous two methods.
Because we automate the analysis and mapping of vegetation, there is very little labor outside of conducting the survey, save for a recommended hour of reviewing the data after a trip and verifying the output. Also, the hardware and software costs are minimal because we analyze data from Lowrance™ HDS-line sonar systems that are coupled with differentially corrected GPS systems and retail for $700-$2200. Running the same calculations as the other methods, we estimated the per survey day cost of mapping a 500-acre lake was a very low $125; 2.8 times cheaper than the next lowest described by Sabol et al. (2009).
|Valley and Drake (2007)
|Sabol et al. (2009)
|*High resolution vegetationmapping was not an objective of Hoyer (2009) and thus the following scaled-up cost estimates should be viewed as a hypothetical scenario for an equal comparison to other methods
The low rate of ciBioBase doesn’t consider any of the value-added features of ciBioBase such as:
· Automation: No training needed in hydroacoustics, geostatistics, or GIS. Our cloud-based software analyzes patterns in the acoustic signal and uses standard geostatistical techniques to produce accurate maps.
· Centralization: As data from more systems is uploaded, algorithm performance is continually verified and enhanced. These enhancements are constantly refined in the cloud and are pushed universally to all users, free of charge.
· Crowd-sourcing: Multiple subscribers from an organization can contribute their data to an optional shared repository. Organization members can leverage each other’s efforts and data to produce a single output.
· Speed: Lowrance sonar units occupy little space on board (and actually are portable!) and come with a skimmer transducer that allows data collection of up to speeds of 10 mph. As such a 500-acre lake may take half the time to traverse 25 mi of transect compared with methods 1 and 2.
· Efficiency: Because there’s no “set-up and break down” with our method, hitting “record” is the extent of the effort you need to do to start logging data. While doing so, you can be collecting other important fisheries, aquatic plant, or water quality data on the lake.
· Data Visualization and Verification: We offer visual, geospatial tools to replay your trip and verify the automated output.
Log in and see for yourself! Go here and type email@example.com for the login email and for the password enter “demo.” You’ll first need Microsoft Silverlight, click here to check to see if you already have it installed on your PC or Mac or need to download it.
Hoyer, M.V. 2009. Calculations for successful planning. Lakeline Spring 2009: 39-42.
Sabol, B.M., Kannenberg, J., and Skogerboe, J.G. 2009. Integrating acoustic mapping into
operational aquatic plant management : a case study in Wisconsin. Journal of Aquatic Plant
Valley, R.D. and M.T. Drake 2007. What does resilience of a clear-water state in lakes mean for the spatial heterogeneity of submersed macrophyte biovolume? Aquatic Botany 87: 307-319.