What’s this Kriging Business?!

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 BioBase uniquely handles.

First, BioBase uniformly interprets acoustic signals and the output is the same regardless of the skill level of the individual collecting the data.  Second, BioBase 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.

Continue reading “What’s this Kriging Business?!”

v2.0 Reports Are Live!

Despite the amazing mapping and visualization tools of BioBase and the questions they spark and help answer, the numbers and old fashioned summary data reports are often tough to beat.  Indeed, many of our users have found our automated summary v1.0 Report of BioBase outputs very helpful for objectively evaluating their aquatic plant management activities.  However, the focus of the version 1 Report was to produce a simple and uniform summary of data collected along users’ trip paths, which often occurred in the form of linear transects.  Sometimes the v1.0 Reports didn’t support an apples to apples comparison.

As our user base expands into system mapping and crowd-sourcing efforts, where trip paths often resemble a bowl of spaghetti, leveraging the power of kriging interpolation becomes even more important.  As such, we’ve just released new automated summary Reporting (v2.0) that will publish both point (i.e., for classic transects) and grid (passive mapping or crowd-sourcing) summary statistics.  The version 2 Reports also output biovolume details in the vegetated areas only as well as within the complete survey zone.   Further, you will find statistics grouped by areas of interest and not only a summary of all data within the merged trips but a uniform summary of each transect that make up the merge!   They’re pretty slick!

Our team has used their previous work experience and interaction with our users to develop reports that are relevant to a wide range of users including lake associations, lake service providers, agency biologists, or university researchers.  We hope you find these reports useful for your work.  Please let us know if you have any questions about how these Reports and data can be used.

You can view the full interactive report with collapsible sections and zoom by clicking here: REPORT SAMPLE   Each report gets a unique URL that can be emailed to customers,  or collaborators.

  Get the v2.0 Reports For Your Past Trips!

This is another great example of how a new feature can be associated to each of your previous uploads.  To get the new v2.0 Report for your previously uploaded trips, click on the Trip Reprocessing tab of the interactive viewer and select “Report” before clicking reprocess.   Try a merged trip first and let us know what you think!  Not a ciBioBase customer yet and don’t have any trips to reprocess?? Why not?  Give us a call and you can join the revolution!

Contour Innovations’ New Office

We recently came to the realization that we had outgrown our original office so it was time for an upgrade! Many of you that have been following our progress have seen that Contour Innovations has been hiring and growing as ciBioBase continues to expand its subscriber base across the world.  We’re sad to leave the birth place of Contour Innovations but we’ve move into a great creative space in NE Minneapolis.  This move is an exciting event for CI!

    

Our new address:
Contour Innovations, LLC
1229 Tyler St. NE, #120   
Minneapolis, MN 55413

This is not a ping pong table, it’s a morale booster . . . okay, it’s a ping pong table:

If you have plans to be in the Minneapolis area, be sure to drop in and check out the new digs . . . and challenge us to a game!

About Contour Innovations, LLC:

Contour Innovations, LLC was founded in 2009 to develop a SaaS Platform for automated processing, interpreting, and centralizing a warehouse of industry specific GIS/spatial data.  We leverage this Platform to launch unique Systems that provide relevant information technology tools to different industries. Our initial systems are focused on acoustic processing of user collected sonar data.  Our first System launch with ciBioBase is already changing the world of aquatic habitat research!

About ciBioBase:

ciBioBase removes the time and labor required to create aquatic maps!  The System was engineered to provide automated cloud based bathymetric and aquatic vegetation mapping and historical trend tools for aquatic habitat analysis.  ciBioBase leverages log file formats recorded to SD cards using today’s Lowrance™ brand depth finders and chart plotters.  Data you collect while on the water is uploaded to an online account where it is processed by our servers automatically!   We rely on automation to make vegetation mapping cost effective by reducing the technical skills, staff, and hours to produce vegetation abundance maps from raw sonar collection.  With the human element gone, you get accurate and objective mapping at lightening speeds!   The result is a uniform and objective output all over the world!

Contact us for details about testing the System or checking us out in a demo account.  We also sell Lowrance HDS units to outfit your data collection boat!

Bathymetry Mapping with ciBioBase!

At Contour Innovations, we often preach the importance of aquatic plant mapping and monitoring, but of equal importance and capability is ciBioBase bathymetric mapping features.  ciBioBase comes with many features that automate the tedious, mundane, yet highly technical GIS processes associated with creating a bathymetric map.  Water resource and lake managers and researchers should be spending their time and talents focusing on thorny management problems, not compiling and managing volumes of data and trying to map them in GIS.  The science of acoustic bottom detection and GIS mapping has been extensively tested, verified, and proven with standard methods.  We automate this.

Because ciBioBase maps only areas you cover up to a 25-m buffer outside of your track, you are assured that maps do not include extrapolated data.  40-m spacing of transects with a criss-cross design assures you that you will get complete coverage and smooth contours (Figure 1). 

Figure 1. Transect coverage showing a “criss-cross” design to assure a high quality bathymetric map.

The Trip Replay feature in ciBioBase further allows you to see disruptions in the contours (Figure 2).  As in the case with Figure 2, there was a temporary disruption in the transducer signal, thus giving an erroneous depth (Figure 2 and 3).  In ciBioBase, these erroneous depths can be edited out; thus creating a smoother, more accurate bathymetric map and associated statistics.

Figure 2. Desktop verification of bathymetric outputs with ciBioBase’s Trip Replay feature.
Figure 3. Areas of disrupted signal can be deleted and the trip reprocessed for a more accurate and smooth bathymetric map.

Other times, these little “donuts” occur because depths temporarily enter a different contour level (e.g., 3ft contours with series depths = 5.99, 6.0, 5.99, 5.98, etc).  Although the 6.0 depth is likely legit, it may be more aesthetically pleasing to remove the 6.0 depth to prevent the creation of a 6ft donut hole.

Once you are happy with the output with individual trips, you can merge them in ciBioBase to create a uniform output (Figure 4).

Figure 4.  Merging function in ciBioBase that allows users to merge individual files or trips into a single, uniform map.

Tying Bathymetry to a Benchmark Elevation
When mapping bathymetry, it may be important to tie the water level to a benchmark water level elevation.  In our Minnesota Lake example, we went to the Minnesota Department of Natural Resource’s Lakefinder website and found important water level information (Figure 5).  On 6/5/2012, we surveyed McCarron’s Lake in Ramsey County, MN.  On 6/7/2012, the elevation-corrected water level reported by citizen volunteers was  840.84 ft above sea level.  The Ordinary High Water Level  (OHW) benchmark for McCarron’s is 842.21 ft (Figure 5).  Using the Data Offset feature in ciBioBase (Figure 6), we can simply add 1.37 ft (elevation correction) plus 1 ft (transducer correction) to get a bathymetric map that is corrected to the OHW (Figure 7).  This eliminates water level as a confounding variable with repeated bathymetric surveys on the same waterbody.  The final products are high resolution, blue-scale imagery as seen in Figure 7 (up to 1-ft contours) or the actual point and grid data that can be imported into any third party GIS or statistical software (Figure 8).

Figure 5. Water level information for McCarron’s Lake in Ramsey County, Minnesota USA.
Figure 6. Data Offset feature in ciBioBase that allows users to correct their bathymetric data to a benchmark water level and transducer depth.
Figure 7. Bathymetric imagery with resolution (both bottom and pixel) that can be controlled by the user.
Figure 8. Export point data along your traveled path or the kriging interpolated grid for use in third party GIS or statistical software.

Life is good in the cloud…

Because of the centralized, cloud-based platform of ciBioBase, we see trip uploads into the system from all types of lakes, ponds, and reservoirs throughout the country and even abroad; so our acoustic and geostatistic algorithms have seen it all!

See for yourself in our demo account at ciBioBase.com.  In the login page, enter demo@cibiobase.com and “demo” for the password.  Operators are standing by to answer any questions you may have!

Lake Mapping and 800 kHz DownScan

BioBase Now Offering 800 kHz DownScan in its dynamic Trip Replay feature.

 

Trip Replay is taking a leap forward with the new option to view your data using the 800 kHz DownScan option when recording with the StructureScan™ add-on.  Anyone that has been uploading data gathered with StructureScan™, by logging all channels, can now view past and future trips with this new feature.

You may have seen our earlier posts about the BioBase Trip Relay feature.  Your raw data collection is automatically processed by our powerful cloud servers and fully mapped with kriging algorithms and other geo-statistical considerations. Once processed, you can then replay the entire trip, watch your boat travel along your transects, and ground truth the % BV heat map with the water column cross section (on the right side of the image above).   This feature allows our customers to verify every trip output for accuracy and provide objective evidence for anyone that questions your aquatic vegetation maps!

The power and accuracy of the Lowrance™ HDS StructureScan™ allows us to offer a new and amazing cross-section view (DownScan) of the water column for each trip in the Trip Replay feature.  As you can see from the images below, this feature provides amazing views of bottom and vegetation.  It is even possible to notice changes in vegetation types or habitat cover type under your boat.  With our waypoint feature, you can identify vegetation transition zones and areas of interest for typing and delineation.

 

Please let us know if you would like to add StructureScan™ to your current data collection hardware.  Although not mandatory for using BioBase, this option can be added to any HDS™ system at any time for great views underwater.  For details on using or recording StructureScan™ please request a copy of our Standard Operating Procedures.

Another great feature added to the powerful BioBase System.

ABOUT BIOBASE

BioBase was engineered to provide automated cloud based GIS, aquatic vegetation mapping and historical trend tools for aquatic habitat analysis.  BioBase leverages log file formats recorded to SD cards using today’s Lowrance™ brand depth finders and chart plotters.  Data you collect while on the water is uploaded to an online account where it is processed by our servers automatically.   We rely on automation to make vegetation mapping cost effective by reducing the technical skills, staff, and hours to produce vegetation abundance maps from raw sonar collection. With the human element gone, you get accurate and objective mapping at lightening speeds!

Check out more anytime at www.BioBaseMaps.com and on our BioBase BLOG

Crowd Sourcing Lake Mapping

Natural Resource Managers and Climatologists have long recognized the critical importance of observer networks and volunteer citizen monitoring.   With citizen monitoring networks, Managers and Scientists acquire useful data for making more informed predictions and management decisions, while involved citizens gain an ownership stake in building the knowledgebase about the condition of ecosystems and the climate.

Citizen protocols for water quality (e.g., Secchi clarity) and meteorology (e.g., rainfall) data collection are largely objective and are becoming increasingly standardized throughout the nation.  As a result, comprehensive datasets are being merged at large geographic scales to assess the current status and trajectory of water resource and climate conditions.  Despite well-intentioned citizen programs to map and monitor aquatic plants in several US states, most are subjective and non-standardized.  Consequently, results will differ across surveyors, systems, and geographic regions.  This strongly limits the power and usefulness of data collected from these programs.   This is unfortunate because of the importance of aquatic plants for fish habitat and water clarity, and the vulnerability of lakes to invasive aquatic plants.

Contour Innovations has addressed this issue with ciBioBase and is poised to revolutionize citizen aquatic plant monitoring.

Objective data collection and analysis

Few others cover more water than citizens living on lakes.  Why not capture information about bottom conditions while on a pleasure cruise or fishing?  With only a modicum of planning, the lake could be divvied up among users to ensure consistent and uniform coverage.  By loading in a $10 SD card into the slot on a Lowrance HDS unit and hitting record while driving over areas of interest, lake citizens are well on their way to collecting important information on aquatic plant growth.  After a trip, citizens upload the recorded files to ciBioBase’s cloud-based servers which will trigger algorithms to automatically analyze bottom and plant signals, map the output and match it up with your sonar viewer (Figure 1).  Pretty maps? Absolutely! But also, objective statistical reports that summarize the plant growth conditions (e.g., percent cover, biovolume; Figure 2).  By sampling the same area over time, citizens can objectively monitor change as environmental conditions change.  Further, these efforts will provide objective benchmarks by which to evaluate watershed, shoreline, and in-lake management efforts. 
Figure 1. Automated mapping of bottom and vegetation signals matched up a high resolution DownScan sonar trip replay. 
Figure 2. Excerpt from ciBioBase automated statistical summary report.


Data that most closely corresponds to water quality, fish habitat, and nuisance conditions


Prior to ciBioBase, lake citizens, service providers, and natural resource agencies had little choice but to express plant growth in the lake as “abundant” or “sparse” with sophistication ranging up to digitally drawn maps around the outside of plant beds that they could see from looking over the side of the boat or from an aerial photo.  Anything that could not be seen with the naked eye or from an aerial photograph was ignored.  Quantification was limited to what could be pulled up with a rake and expressed as a presence/absence  metric of frequency of occurrence.
From a water quality and fish habitat perspective, these methods have left the fishery and water resource manager, lakeshore owner, and angler wanting.  Traditional plant assessment methods as described would give the same value to the strikingly contrasting environments depicted in Figure 3).  In the panel on the left, plants only occupy approximately 60% of the water column.  There are adequate hiding places for prey and room for predators to swim around in search of prey.  Plants are adequate to anchor sediments and prevent stirring of sediments that can make the lake murky.  Last but not least, a boat can easily pass through without disturbing the habitat.  Contrast this with the panel on the right.  Although the visual delineation or rake throw prescribed by traditionalists would give the same information on density as the panel on the left, fish habitat and water recreation conditions are strikingly different between the two environments.  In this simulated invasive aquatic plant community (e.g., Eurasian watermilfoil or Hydrilla) without any edge, predatory fish have difficulty finding prey, boat propellers are stopped in their tracks and outboard impellers imperiled!  Essentially, the differences described between the environments in Figure 3 can be summarized in the ciBioBase biovolume maps and statistical outputs.  Ask your service provider or local water resource manager how they measure aquatic plant growth conditions in your favorite lake and evaluate whether they stack up to what ciBioBase provides.
Figure 3.  Contrasting aquatic plant environments that are often represented equally in traditional assessment methods.  On the left is growth that typifies a diverse, native aquatic plant community as opposed to topped-out growth that typifies invasive plant communities.  By mapping biovolume (percent of water column occupied by vegetaton), ciBioBase distinguishes the differences between these plant communities.
Centralized database – Apples to Apples

All data uploaded to ciBioBase are processed uniformly in a centralized database and made available to subscribers in a private organizational account.  Data from Lake Minnetonka in Minnesota can be compared with data from East Lake Tohopekaliga in Florida or data from Esthwaite Water in the UK and comparisons will be apples to apples.  The centralization feature of ciBioBase comes with these tangible benefits as well as intangible ones like fostering greater collaboration between groups interested in aquatic resource conservation.
Merged uniform outputs from multiple surveyors

A new buzzword has been entering the vernacular of natural resource managers called “precision conservation” brought on by advances in aerial photography, lasers (LiDAR), automated sensors, and greater computing power.  We can now identify miniscule areas on the landscape that are sources of runoff and pollution and strategically target those areas to install “Best Management Practices” or BMP’s like rain gardens or grit chambers.  However, thus far the dialog surrounding precision conservation has largely been terrestrial.  ciBioBase is bringing precision conservation to lakes through its merge trips function (Figure 4).
As ciBioBase account managers our users can compile trips from subscribers within their  organization to create a highly precise map of bottom and vegetation (Figure 4).  This division of labor describes the essence of this blog’s title whereby the collective efforts or intelligence of the many are more powerful than any one individual.  No one person is willing or able to track how the lake is changing from day to day as runoff from an increasingly common 4-in rain comes streaming (literally) in, but a dozen active citizens might.  The result is a near real-time data feed on changes in lake conditions that will greatly inform how the lake responds to environmental change, where to target conservation efforts, and whether implemented management policies are producing their desired effects.
Figure 4. Multiple citizens in the same organization can work together by merging trips, thereby creating the most accurate bottom and plant map on the face of the planet!

Aquatic Plant Abundance Mapping and Resilience!

Merriam-Webster Defines resilience as an ability to recover from or adjust easily to misfortune or change.  Eminent University of Wisconsin-Madison Ecologist Dr. Steve Carpenter further adds that resilience is the ability for a system to withstand a “shock” without losing its basic functions, http://www.youtube.com/watch?v=msiIV5NdLVs

Resilience is a relatively easy concept to understand, but it can be difficult to measure in lakes without monitoring subtle changes over time.  This stresses the importance of long-term monitoring and being on guard for new changes to water quality, aquatic plants, and fish.  Volunteer networks and agencies across the country are making great strides in monitoring water quality by dropping a disk in the water and scooping up some water and sending it to a lab for analysis.  In essence, taking the lake’s “blood” sample.  Indeed, water quality samples can be very telling.  But what is happening to the rest of the lake “body”?  How is it changing in relation to its liquid diet of runoff or medication to treat invasive species?  Unfortunately, until now, natural resource agencies, lake managers, and volunteers have not had the capabilities to objectively and efficiently assess these changes without time-intensive, coarse surveys of vegetation cover.

Your body’s immune system is the engine of resilience.  When your immune system becomes compromised, you become vulnerable to a wide range of ailments that may not be a threat to someone with a healthy immune system.  The same goes for lakes.  In the glaciated region of the Upper Midwestern US and Canada, healthy lakes are those that have intact watersheds where the hydrologic cycle is in balance.  Without going into great depth, keeping water where it falls (or at least slowing it down), goes a long way in keeping the hydrologic cycle in balance.  Healthy glacial lakes also have clear water, a diverse assemblage of native aquatic plants, and balanced fish communities.  When humans or the environment alter any one of these components, the lake must adjust in order to compensate for those alterations and remain in a healthy state.  The ability of the lake to do so is this concept of resilience (Figure 1).

Figure 1.  Conceptual diagram of a resilient system.  The height of the slope and the deepness of the valley are the compensatory mechanisms that bring a lake back to some resilient baseline condition after a short-term “shock” like a flood or a temporary septic failure.  Lakes with forested watersheds, clear water, native aquatic plants, and balanced fish communities are typically in this condition.

Slowly, as more curb and gutter goes in, green lawns replace native grasses, personal swimming beaches replace marshes, fish are overharvested or overstocked, or invasive species are introduced, the lake slowly loses its ability to compensate (Figure 2).  All of a sudden you hear “I’ve never seen that before” become more common when people describe a phenomenon on the lake that well, they’ve never seen before.   You may start to observe more algae blooms, more attached algae on rocks and plants, plants growing where they’ve never grown before, invasive species taking hold and thriving.  This is an example of the lake losing resilience and succumbing to the vagaries of the environment.  Under these circumstances, the lake can’t compensate anymore and you never know what you will see from year to year.  With no baseline, objective assessment of aquatic plant abundance and no monitoring of change in abundance and cover from year to year, it makes it even harder to know how much the lake has actually changed and what you need to try to get back to with implemented best management practices .

Figure 2.  An example of the consequences of the cumulative impacts of environmental and human stressors on lake resilience.  As lakes become more impacted by various watershed and in lake practices and invasive species, resilience is slowly worn away.  The valley becomes more shallow and a new “domain” enters the picture.  Lake conditions slosh around from one state to the next depending on the vagaries of weather and other disturbances.  Not knowing to expect from one year to the next becomes the norm.

A demonstration of the difference between a resilient lake and one that is losing resilience can be found in a paper published by Valley and Drake in Aquatic Botany in 2007 entitled “What does resilience of a clear-water state in lakes mean for the spatial heterogeneity of submersed macrophyte biovolume?”  Valley and Drake found very consistent patterns of vegetation growth from one sampling period to the next over three years in a clear lake (Square Lake, Washington Co. MN USA; Figure 3).  Each survey in Figure 3 took two days to survey and another week to make these plots.  Not including time on the water, ciBioBase produces these same plots in an hour.
 

Figure 3.  Submerged aquatic plant biovolume (% of water column inhabited by plants) as a function of depth in Square Lake, Washington Co., MN USA.  Notice the consistency of the pattern of vegetation growth from one time period to the next (study took place for 3 years from 2002-2004; Valley and Drake 2007).  Water clarity in Square Lake is high with diverse aquatic plants.

In contrast, patterns of vegetation growth were quite variable in a moderately turbid lake with abundant Eurasian watermilfoil; West Auburn Lake, Carver Co. MN USA; Figure 4).  For example, in summer 2003, a bloom of attached algae formed on Eurasian watermilfoil stems and effectively weighed down the stems and prevented them from reaching the surface.  This bloom was unique to 2003 and was not observed at any other time during the study.

Figure 4.  Plant growth as a function of depth in a moderately turbid Minnesota Lake with abundant Eurasian watermilfoil (West Auburn Lake, Carver Co. MN USA; Valley and Drake 2007).  Plants grew shallower and more variable in this more disturbed lake. 

If stressors continue unabated, then the lake can “tip” into a new, highly resilient domain of poor health (Figure 5).  The feedback mechanisms that used to keep the lake in a healthy state have now switched to new feedback mechanisms that are keeping it in an unhealthy state.  Algae begets more algae, carp beget more carp, stunted bluegill beget more stunted bluegill, if invasive plants are lucky enough to grow, they beget more invasive plants.  Getting the lake back to the original state is nearly impossible at this point.  It’s like Sisyphus rolling the rock uphill only to have it roll right back down again!  Although controversial, at some point, citizens, regulators, and lake managers need to start rethinking expectations and adapting management approaches in highly degraded systems.  Rather than trying to restore a lake to a Pre-European settlement condition through expensive, risky, and Draconian measures, it may be more reasonable to ask: “How can we have good enough water quality to support naturally reproducing stocks of game fish?”  “Can we manage invasive plants in a way that maintains fish habitat AND recreational opportunities?”  After the wailing and gnashing of teeth subsides and some agreement is reached on objectives and management strategies, then it becomes essential to determine whether implemented management practices are having their desired effect.  It doesn’t take two weeks and $10’s of thousands of dollars to do a vegetation survey.  Volunteers can do it, lake consultants can do it, state agencies can do it and they’ll all do it the same objective way with ciBioBase and they can all work together!

Figure 5.  Example of a lake that has flipped into a degraded regime regulated by new feedback mechanisms that keep it in the degraded state. 

The Upshot

Resilience is an easy concept to understand on a basic level, but hard to measure in lakes and changes slowly over time.  This stresses the importance of long-term monitoring and being on guard for those things “you’ve never seen before.”  Uploading data to ciBioBase every time you are on the water gives an objective and quantitative snapshot of the current conditions in your lake of interest.  Be watchful for anomalies in monitored areas.  Vegetation growth should follow a relatively predictable pattern from year to year and if it doesn’t, that may be the first indication that the lake is losing resilience and precautionary conservation measures should be taken.  Conservation measures may include better onsite storm water infiltration (e.g., rain gardens, nearshore vegetation buffers), maintaining a modest amount of aquatic plant growth in the lake, maintaining a balanced fish community in terms of species, size, and abundance.  These efforts will go a long way in protecting the long-term integrity of our beloved lakes!

Suggested Readings:

Carpenter, S.R., 2003. Regime shifts in lake ecosystems: pattern and variation. In: Excellence in Ecology, vol. 15, Ecology Institute Oldendorf/Luhe, Germany.

Scheffer, M., 1998. Ecology of Shallow Lakes. Chapman and Hall, London.

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.


Contour Innovations Welcomes Jesse Amo

Contour Innovations, LLC is proud to announce the addition of Jesse Amo to the position of Aquatic Biologist and Technical Sales.  Jesse will focus his efforts on sales, education and in-person demos for local government units and lake associations.  “Jesse’s enthusiasm, passion and wealth of knowledge in aquatic habitats make him a great steward for executing Contour Innovations vision of changing the way we assess aquatic environments using cloud computing and acoustics” commented Ray Valley, Contour Innovations’ Chief Aquatic Biologist.

Jesse brings a diverse mix of education and experience to the Contour Innovations team.  Jesse holds a Bachelors of Science degree in Zoology (fish and wildlife emphasis) from North Dakota State University with particular interest in aquatic ecosystems.   He is currently pursuing a graduate certificate in Geographic Information Science and Cartography from the University of North Dakota’s online program.   He draws on experience gathered while working with the Minnesota Department of Natural Resources, National Park Service, US Forest Service, US Fish & Wildlife Service, Minnesota lake associations, Minnesota Soil and Water Conservation Districts and various academic research programs.  He is also active in the Minnesota Association of Conservation Professionals and the American Fisheries Society.

In addition to his work in aquatic biology, Jesse  served 6 years in the Army National Guard and quickly adapted to several military occupational specialties.  He is a combat veteran who served a 12 month tour of duty in Iraq in 2004-2005.  His personal interests include many outdoor endeavors such as canoeing, fishing, hiking, cycling, and research and observation of ecosystems.  Jesse is driven to find innovative ways in increase our understanding and management of aquatic ecosystems.

Jesse’s motivation and understanding of aquatic systems made him a great addition to our rapidly growing team.  We’re excited to have him on board!

You can contact Jesse at JesseA@ContourInnovations.com

What to do with all this Lake Habitat Data!?

Fifteen data points per second, four hours on Lake X today, several more tomorrow.  Lake Y and Z to follow.  Repeat next year and the year after.  Since no one has to process the data, it can be collected during non-dedicated mapping time by hitting record on your Lowrance HDS each time  your on the water.  Simple math tells you that this is going to lead to A LOT of data.  What are you going to do with it all?

This “problem” is new to biologists and lake management practitioners in the 21st Century.  Decision making in a data “poor” environment has been much more common and indeed is still a real problem.  The “problem” of too much data, really isn’t a problem at all.  Modern computing technology can return only information that is important to you and archive the rest for safe keeping.

With regards to aquatic plant assessment and monitoring in lakes, never before have we been able to rapidly collect and interpret information about how much plants are growing and where.   So, we spend three hours going back and forth on our favorite 230 acre, upload our data to ciBioBase and get a pretty map and some statistics on the density of the vegetation (Figure 1).  So what?  What does it mean?

Figure 1.Example automated summary report from ciBioBase.

Well, admittedly it is difficult to judge whether 78% of the lake being covered with vegetation (PAC) is normal.  What is normal?  This exemplifies the importance of collecting baseline information to judge whether changes from time A or B are significant.

The invasive aquatic plant, Eurasian watermilfoil has a tendency to grow to the surface of lakes, displace native plant species, and impede navigation.  The extent of surface growth and overall cover of Eurasian watermilfoil and other invasive plant species are typically the conditions that lake managers and citizens want to reduce.  ciBioBase provides a rapid and objective way to monitor how cover and surface growth of vegetation is changing as the lake is affected by various stressors and our responses to them (e.g., herbicide treatments).  For instance, often a water resource agency or citizen group will state objectives in a lake management plan something to the effect of “Objective 1: reduce the abundance of Eurasian watermilfoil by 80%.”  What should be asked next is 80% of what? What is our yardstick?  We can’t expect to be successful at water and fisheries resource conservation without clearly defining management targets and evaluating whether we’re getting there.

Furthermore, there is a tight link between water quality and aquatic plant growth.  Clear lakes with all native plant species often have high cover of vegetation, but relatively little surface-growing vegetation (except near shore or in shallow bays).  As more nutrients run into the lake from lawns and parking lots, aquatic plants initially increase in abundance and grow closer to the surface to get sunlight from the clouding water.  If we continue to mow our lawns down to the lake edge, over fertilize, and route water from parking lots and roofs into our lakes unabated, then aquatic plants crash because the water is too turbid to support plant growth.  Next thing you know, largemouth bass, bluegill, and northern pike disappear and you find your lake on the EPA’s Impaired Water’s List and now you need to spend million’s to clean it up.  ciBioBase can be used to prevent you from getting to that point.

One precise way of doing so is to monitor the maximum depth that vegetation grows in your lake.  There is a tight link between water clarity and the depth that plants grow in lakes (Figure 2).  The extent of plant growth integrates the short-term dynamic nature of water clarity and gives a measure of the overall water clarity conditions for the year.  The conventional water clarity monitoring routine involves citizens and lake managers taking a dozen trips a season to the middle of the lake to drop a Secchi disk down and measure the distance where the disk disappears from sight.  With one 3-hr mid-summer ciBioBase survey, you can get a measure of water clarity conditions for the entire season.  This depth should remain relatively consistent from year to year in stable watershed and lake conditions.  A change of two feet over the course of a couple of years should raise a flag that conditions in the lake may be changing and initiate some initial investigation into possible causes.



Figure 2. Relationship between the maximum depth of vegetation growth as a function of water clarity from 33 Minnesota lakes where lakes were mapped with sonar and water clarity data was collected with a Secchi disk.

To bring this discussion full circle, we should ask: how do we know the change in point A or B is due to a real change in lake conditions and not an artifact of our sampling?  This question plagued the 20th Century Lake Manager to the point of gridlock.  In the 21st century, we can overwhelm the question with data to get almost a census of the current conditions rather than a small statistical sample fraught with error.  Lake Managers don’t have to physically wade through all this data to find the answer.  High-powered computers and processing algorithms can do the heavy lifting, the lake manager or concerned citizen can focus on implementing practices that will result in clean water and healthy lake habitats.

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