How do natural fluctuations factor into your lake management?

Since its inception in 2011, BioBase has helped a large number of lake managers and researchers across the globe create detailed, near real-time aquatic plant abundance maps.  But what happens when “real-time” becomes a “long-time?”  What is the “natural” range of aquatic plant growth in lakes? To what degree does an invasive species change the total plant abundance in a lake over the long-term? Likewise, to what degree does the removal of the invasive through management affect plant abundance within this historical context? These are questions research has yet to answer.   Why not given how much is at stake??

Technological constraints were an initial barrier that Lowrance and BioBase has addressed.  A large consumer technology industry has created affordable and sophisticated sensors and automated difficult tasks collecting and processing the information.

But the second barrier of a commitment to long-term monitoring perhaps presents the bigger challenge to the aquatic and fisheries resource industry.  Evaluations, if they happen at all, are rarely more than a “before-after” snapshot that does not place the differences displayed within a historical context of natural aquatic plant growth. The “before” snapshot in a 2012-2013 comparison might’ve been strikingly different if the project was delayed a year and the before snapshot came in 2013.

With one simple case-study in a Minnesota Lake we present a very visual example of how much aquatic plant abundance changes from year to year in a monitored lake.  We arrived at these results with very little labor input and think they have strong implications for how the aquatic plant management industry approaches management evaluations

The Lake:
Orchard Lake has been Contour Innovations’ (and now Navico’s) “sentinel” lake since July 2011; a demonstration and testing site for developments to Lowrance and BioBase.  You might’ve seen this lake splashed throughout our marketing materials including the C-MAP Genesis service for anglers. Orchard is a typical 234-acre (94-ha) 31-ft (9.5 m) deep, moderately nutrient-rich Minnesota glacial lake.  Although surrounded by waters infested with non-native Eurasian watermilfoil, Orchard Lake has thus far missed this “bullet” and does not have the species or any other invasive other than the long-established Curly-leaf pondweed (Table 1).

Table 1. Frequency of occurrence of submersed aquatic plant species in depths less than 15-ft, sampled in Orchard Lake, Dakota Co., MN at 94 points spaced uniformly across the lake in July of each year.  Curly-leaf pondweed is the only non-native in the lake as of this writing and this species typically scenesces prior to July in Minnesota.  Most sites were a mix of the listed species and rarely did any one species dominate the local assemblage

The Surveys:
Using Lowrance HDS and BioBase every July since 2011, Contour Innovations/Navico staff have motored back and forth on Orchard Lake logging sonar and since 2012, stopping every 262 ft (80 m) to throw a rake and identify the species that are growing (Figures 1 and 2).

 

Figure 1. Target 40-m transects and aquatic plant sampling points created in ArcMap (Fishnet toolbox utility) and converted to .gpx and imported into Lowrance Chartplotter.
Figure 2. Actual tracks recorded during one lake survey

Watch Change

Below we display a time-series gallery of processed map images from BioBase from repeated surveys in Orchard Lake along with some basic meteorological summary data (April to July).  Further, we demonstrate a visually intuitive way of describing a historical benchmark from all surveys and compare each repeated survey to the historical average.

2011 – Near normal temperature (0.8 deg F above avg), near normal rainfall (1 in above avg):

Aquatic plant biovolume surveyed with Lowrance HDS and processed by BioBase in July 2011.  Red areas indicate vegetation growing at or near the surface, yellow and green is submerged growth, and blue are areas of no growth.  Avg Biovolume = 49%.

2012 – A warm (5 deg F above avg), wet (4.7 in above avg) summer:

Aquatic plant biovolume in July 2012.  Less growth than 2011.  Avg. Biovolume = 40%.

2013 – Near normal temperatures (0.5 deg F above avg), less wet than 2012, but still above average (2.89 in above avg):

Aquatic plant biovolume in July 2013.  More growth than 2011 and 2012.  Avg Biovolume = 53%.

2014 – Slightly cooler than average summer temperatures (-0.7 deg F), and record-breaking rainfall (6.81 in above avg):

Aquatic plant biovolume in 2014.  Lowest growth across all years.  Also the wettest June on record in Minnesota. Avg Biovolume = 37%.

Putting the pictures together: Map Math!

First, using the Raster Calculator in the ArcGIS Spatial Analyst Toolbox (Spatial Analyst Extension required), let’s describe the “average” plant growth condition across all years in order to define our “benchmark” for future comparisons:

Average vegetation biovolume map across all 4 years – 2011 map + 2012 map + 2013 map + 2014 map divided by 4. Regular monitoring of plant growth in untreated reference lakes or bays is needed to incorporate the vagaries of climate and effects on aquatic plant growth.  Averaging maps across all years establishes a “benchmark” condition from which to base future comparisons.

Subtracting 2011 from the average:

Green areas represent higher than average aquatic vegetation growth, blue areas represent lower than average vegetation growth (Avg difference = +3% biovolume – slightly higher than average)

Subtracting 2012 from the average:

Green areas represent higher than average aquatic vegetation growth, blue areas represent lower than average vegetation growth (Avg difference = -5% biovolume; notice the large decrease in the bed along the Eastern part of the lake)

Subtracting 2013 from the average:

Green areas represent higher than average aquatic vegetation growth, blue areas represent lower than average vegetation growth (Avg difference = +7% biovolume; notice a complete reversal of relative growth along the Eastern part of the lake compared with 2012)

Subtracting 2014 from the average:

Green areas represent higher than average aquatic vegetation growth, blue areas represent lower than average vegetation growth (Avg difference = -5% biovolume – lower than average – a see-saw of change!)

Subtracting 2015, 2016….n from average?:

What will next year, and the year after that, and the year after that bring?  Only repeated monitoring can answer these questions


Does excessive rainfall affect aquatic plant growth?

During the time span that surveys on Orchard Lake began, we’ve experienced some wetter than average summers, especially in 2012 and 2014.  Interestingly these happened to be the lowest aquatic plant growth years over the 4 year time span (Figure 13).  Still, with only four survey years, this only begs the question that several more years of monitoring should help answer.

Figure 13. Whole lake average biovolume in Orchard Lake (Dakota Co., MN USA) plotted against rainfall from April to July at Minneapolis/St. Paul International Airport (Data courtesy of the National Weather Service).


Back perception up with real data!
In 4 short years and only 8 days total on the water, we’ve seen how incredibly dynamic aquatic plant abundance is in one eutrophic Minnesota Lake with no aggressive invasive species. These changes would never have been detected by even the most comprehensive species-rake surveys, much less visual surveys!  This is a striking example of the importance of regular monitoring of aquatic plant growth to place results from management within the appropriate historical context.  Lowrance and BioBase makes mapping plant abundance easy so practitioners can focus on the more important question of why differences are being seen.

Author: biobasemaps

BioBase is a cloud platform for the automated mapping of aquatic habitats (lakes, rivers, ponds, coasts). Standard algorithms process sonar datafiles (EcoSound) and high resolution satellite imagery (EcoSat). Depth and vegetation maps and data reports are rapidly created and stored in a private cloud account for analysis, and sharing. This blog highlights a range of internal and external research, frequently asked questions, feature descriptions and highlights, tips and tricks, and photo galleries.

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