"Back from the Brink" – Around we go

The Aquatic Ecosystem Restoration Foundation provides a critique of the investigation into the fall and rise of fish populations in a Northern Wisconsin lake (Ellwood), and the potential links with an invasive aquatic plant (Eurasian watermilfoil) and a common aquatic herbicide (2,4-D).  See the original news story here.  It’s an ongoing saga that we originally commented on in an earlier post

We believe with more rigorous habitat mapping and monitoring, this story (and future ones) will become less interesting because entertaining anecdotes will be replaced with good objective and quantitative data.

BioBase In The News: Aquatic Habitat Mapping "Off-the-Shelf"

From the Peninsula Clarion in Alaska published on 6/19/2014.  Story by U.S. Fish and Wildlife Ecologist Mark Laker with the Kenai National Wildlife Refuge.

Continue reading “BioBase In The News: Aquatic Habitat Mapping "Off-the-Shelf"”

Delineating Invasive Plant Beds the Easy Way

Effective management of invasive aquatic plants requires some fundamental but previously difficult prerequisites.  First, you have to find the infestations; not easy when you can’t see underwater.  Second, you have to create boundaries of the infestation; also not easy when you can’t see underwater or when the plant does not behave and form perfect surface-growing patches that you can trace with your GPS.  So it used to be a game of darts using whatever tools available (e.g. rakes, manual interpretation of GPS and sonar, aquascopes, snorkeling, scribbling on paper maps) to crudely estimate the extent of invasive plant growth.  Needless to say, delineations using this technique have been crude leading to equally crude and often ineffective management.

Continue reading “Delineating Invasive Plant Beds the Easy Way”

ECU Research on Lowrance/BioBase Effectiveness for Seagrass Mapping

Read about exciting new research by Dr. Joe Luczkovich’s lab at East Carolina University demonstrating rapid, precise and cost-effective acoustic techniques for mapping seagrass habitats in North Carolina USA’s Coastal Estuaries.  Dr. Luczkovich and undergraduate research assistant Audrey Pleva talk about the very high accuracy of Lowrance HDS and BioBase for seagrass in shallow areas of Jarrett Bay, Blount’s Bay, and Currituck Sound compared with underwater videography

Below is the abstract from: Audrey Pleva and Joseph Luczkovich.  2013. Effects of salinity on submerged aquatic vegetation’s growth and abundance in North Carolina and assessment of a SONAR’s accuracy to measure vegetation. Unpublished report, Department of Biology,  Institute for Coastal Science and Policy, East Carolina University, Greenville, NC 27858.  Contact Dr. Luczkovich if you have questions or would like a copy of the report.  Contact Navico to get updated (cheaper) pricing from what is cited in the report and to get you started assessing seagrass habitats with Lowrance/Simrad and BioBase!

ABSTRACT

 Submerged aquatic vegetation (SAV) is one of the most important estuarine habitats supporting commercially and recreationally important fishes and invertebrates, providing species food and shelter from predation. Salinity levels, an important factor in SAV growth and survival, are rising in North Carolina due to sea level rise bringing salty water from the Atlantic Ocean into NC, posing a threat to freshwater species. SAV species adapted to a certain salinity level are stressed by long and short term changes in salinity, resulting in patchy or smaller beds. In this project, a recently developed survey technique based on a combined video and echosounder system was used to measure the SAV % cover at three sites, each with different long-term and short-term salinity levels. Our hypothesis was that large short-term changes in salinity would be a stressor for SAV, and that as the range in salinity and the average long-term salinity increased, SAV % cover would decrease. We measured changes in water quality including salinity, temperature, and dissolved oxygen, and SAV cover using boat-based SONAR techniques at Jarrett Bay (JBS), Blount’s Bay (BLB), and Currituck Sound (CTS) in North Carolina during the beginning of the growth season where salinity is a very important growth factor. SONAR data were collected along 30 transects at 10-m intervals across the study area at JBS and BLB, but 60 transects at 25-m intervals at CTS. The accuracy of the SONAR technique was assessed using underwater video at 100 randomly selected points along transects at each site. Accuracy was very high (87.8 %) and relatively equal between all three sites. The salinities and % cover were highly variable among sites, in both the short- and long-term measurements, allowing for an analysis of the relationship between SAV and salinity. Overall mean long-term salinity was negatively correlated (r = -0.7) with SAV percent cover. Short-term salinity increases may cause declines in SAV cover, as freshwater species are displaced by salinity-tolerant SAV species.
Example image of seagrass abundance (% of water column with vegetation) in Currituck Sound, North Carolina.  200 khz Sonar image from Lowrance HDS (right) is coupled and synced with kriging interpolated map of vegetation abundance (left).  Areas of red are where vegetation is growing to or near the surface.  Areas of blue are bare.  Green and yellow is lower lying vegetation.  Datasets are summarized in BioBase with several analytic tools, but spatial data can also be exported for analysis in any third party GIS or statistical analysis platform.

See an online pdf of a presentation recently given by Dr. Luczkovich describing some of these results.

Guest Blog: Precision aquatic plant assessment and management in Michigan Lakes

By Jennifer L. Jermalowicz-Jones
Restorative LakeSciences is actively involved in the management and restoration of nearly 60 lakes in the state of Michigan and on water bodies in other states such as California and Wisconsin.  As an innovative specialty firm of advanced-degreed limnology experts, our goal is to provide thorough educational training to lake communities while using the most innovative technologies for lake improvements.  BioBase software (Contour Innovations, LLC) in combination with the Lowrance® HDS8 side- and down-scanning capabilities allows us to precisely determine the biovolume of the submersed aquatic vegetation in inland lakes.  Additionally, it also assists in the determination of individual aquatic vegetation bed areas that are mapped by aquatic botanists to be treated precisely with systemic or contact aquatic herbicides or with other removal technologies (Figure 1).  This technology has resulted in highly effective reductions of nuisance aquatic vegetation biovolume and bed densities due to the precision of treatments.  As a result, all of our lake management communities have been satisfied with the strategy and can easily see significant progress within a single season.
Restorative Lake Sciences, Evans Lake, Michigan, ciBioBase, BioBase, Eurasian watermilfoil, mapping, aquatic plants
Figure 1. ciBioBase aquatic vegetation heatmap collected by Grant Jones, Field Operations Manager, Restorative Lake Sciences (left) and Eurasian watermilfoil beds delineated with companion species surveys and the BioBase polygon tool.  Polygons were exported from BioBase and uploaded to Google Earth.
Jennifer L. Jermalowicz-Jones, MS, Ph.D Candidate, is the Water Resources Director at Restorative Lake Sciences and oversees over nearly 60 inland lake projects which include aquatic vegetation mapping and management, lake sediment reduction studies and management, algal quantification and identification and algal management programs, and watershed management programs.  She has over 24 years of experience in lake research and management and is pursuing her doctoral degree from Michigan State University in Water Resource Management.  She is also the President of the Michigan Chapter of the North American Lake Management Society, serves as the Science Advisory Chair on the Michigan Lake and Stream Associations Executive Board of Directors, has won numerous awards and grants for her aquatic ecosystem research, and has presented numerous papers at state and national conferences on water resource and lake management.

Color Enhancing your Sonar Log

ciBioBase’s Trip Replay feature that couples bottom depth, aquatic vegetation biovolume, and bottom hardness maps with your actual Sonar Log empowers you with a verification tool that ensures an accurate map in every system you map, every time.  The sonar log also provides users and our Quality Control team helpful information about signal quality and transducer placement that can help both parties diagnose issues.

A little known feature in ciBioBase allows users to reprocess their Lowrance HDS/Elite sonar log at different color and sensitivity settings (Figure 1).

Figure 1. Trip Reprocessing Tab that allows ciBioBase users to reprocess their trips with new edits.  Try reprocessing your sonar log at a higher color (e.g., 240) for “cooling” the colors in your sonar log in ciBioBase and to bring out subtle bottom features.

Sometimes, your Sonar Log may look a little too “hot” making it difficult to distinguish between plants and bottom (Figure 2).

Lowrance, ciBioBase, Sonar Log
Figure 2.  Sonar Log showing colors that may be “too hot” to distinguish between plants and bottom.

Try reprocessing the sonar log at a colorline of 240 (default is 220).  This will bring in “cooler” colors to the sonar log and may help you better distinguish subtle bottom features and gaps in plant beds (Figure 3).

Figure 3.  Sonar Log reprocessed with a colorline of 240.

Alternatively, Lowrance has a powerful free desktop software program called SonarViewer which allows you to replay your Sonar Log with options to dynamically control sensitivity, colorline, zoom, and range (Figure 4).

Figure 4.  SonarViewer is a free download from Lowrance and has a range of tools for enhancing the contrast of bottom features detected by your Lowrance HDS or Elite.

Use SonarViewer to review your files prior to upload to ciBioBase if you suspect possible signal quality issues or are testing different transducer setups for optimal signal quality.  Signal Quality should also be continually monitored by watching your SONAR page on your HDS or Elite while collecting data on the water.  A helpful rule of thumb is that a signal that is clear and crisp to your eyes is most likely clear and crisp to ciBioBase algorithms.

Quantitative Aquatic Vegetation Management

Aquatic plants are often integral components of lake ecosystems and invasive species often disrupt the ecological balance of lakes.  Past aquatic plant assessments were qualitative and imprecise leading to poorly informed management decisions and prescriptions which have carried significant environmental and economic costs.  New acoustic and cloud computing technologies have revolutionized the aquatic industry and now highly precise estimates of aquatic plant abundance, growth patterns, and response to management can be quantitatively assessed.  New BioBase reports take this into consideration in multiple areas:

Aquatic plant management and monitoring
Aquatic plant management and habitat assessments with quantitative metrics

BioBase creates a standard report for each file that is uploaded to the system.  One section of the standard report (Biovolume by Quantity) identifies the relationship between data collected and % of data points that fall within a certain biovolume (% of the water column occupied by plants) range.  For example, in the image above 6.8% of data points collected and processed had plant biovolume above 80%, 5.19% of points had biovolume between 60-80% and 11.99% of data points showed biovoume above 60% (5.19+6.80).  If a management technique was used it would be very easy to identify, with quantitative plant management metrics, that objectives were met.  This may mean that nuisance plants above 60% biovolume were reduced by 90%.  Now we know if this is the case.

Using qualitative or subjective determinations of plant growth with only periodic surveys has led to problems of repeatability by other surveyors, lack of precise understanding of how much growth has changed over time, and an inability to rapidly detect change in lake conditions.  Now we can objectively determine if management techniques are having their desired effect.

Lake managers and plant monitoring groups can now take data to the next level with the three dimensional aspect of plant delineation using water column percent biovolume and BioBase standard reports.

Optimal Percent SAV Biovolume? 50% is a Good Start

At Contour Innovations we’ve long argued the importance of objectively assessing submersed aquatic vegetation (SAV) abundance to better inform management decisions.  Our last blog post discussing a recent controversy over the role of herbicides in indirectly affecting fisheries declines in Wisconsin reinforces why this is so important.  When we talk abundance per se, we need a metric that is quantitative, yet is intuitive.   The percent of the water column taken up by vegetation growth (i.e., percent “biovolume”) represents such a metric and is the primary variable that is mapped in ciBioBase.  Zero means no growth (blue).  100% represents growth all the way to the surface (red; Figure 1).

SAV, Aquatic Vegetation map, Lowrance HDS, Surface growing vegetation
Figure 1. SAV Biovolume map (left), boat tracks (red lines), boat location (red dot), and sonar chart of vegetation growing to the lake surface on Orchard Lake, MN.

Zero is undesirable in lake environments where vegetation growth is natural or where an artificial lake is managed for vegetation-dependent fisheries (e.g., largemouth bass or northern pike).  No vegetation growth can also cause and be an effect of water quality impairments as discussed here).  In contrast, 100% is undesirable from an aquatic recreation standpoint because props get tangled up and it’s difficult to navigate your boat through surface mats of vegetation (Figure 2).

Figure 2. Aquatic Vegetation (100% Biovolume) growing all the way to the water surface on Orchard Lake, MN and impediments to motorized recreation. 

If no plant growth is bad (0%), but plant growth all the way to the surface (100%) is bad, then good MUST be somewhere in between.  Indeed!  From a Fisheries standpoint, 40-60% average biovolume is good because there is habitat for vegetation-dependent species like largemouth bass, bluegill, northern pike, and indicator species like blackchin shiners that are sensitive to vegetation loss (Figure 3).

Figure 3.  Probability of sampling blackchin shiners as a function of increasing SAV % biovolume  in Square Lake, MN (Adapted from Valley et al. 2010 Hydrobiologia 644:385-399)

From a water quality standpoint, 40-60% biovolume is sufficient to anchor sediments and will promoting better water clarity than if nothing was growing.  Finally, 40-60% biovolume means that most growth is below the depth of your outboard prop and thus you generally won’t encounter the situation as seen in Figure 1.

A case study in MN, WI, NC, and FL lakes

CI is currently involved in a collaborative research project where acoustic data with Lowrance HDS was passively collected while conducting point-intercept surveys.  Acoustic data (.sl2 files) were uploaded to ciBioBase and the Biovolume value for each species survey point was extracted from the exported raster grid (“Extract Value From Point” in the Spatial Analyst Toolbox in ArcGIS or see our Point-Intercept on Steroids blog).  Figure 4 displays a wealth of information about the status of plant growth and management in the surveyed lakes.  With on-the-fly data entry for the plant species surveys and uploading of the .sl2 file to ciBioBase, a similar graph could be produced within hours of finishing a survey, and thus facilitating informed and rapid decision making.

Figure 4.  Biovolume at invasive species sample points and native sample points free of invasive species.  Non-vegetated sites are not included in the analysis.  Lakes range from intermediate nutrient levels, Mesotrophic (M), to high nutient levels, eutrophic (E).  Berry, Gibbs, Swan, Wingra, and Round are in WI; Gray’s, Gideon’s, and St. Alban’s Bays are bays of Lake Minnetonka, MN; Waccamaw is NC; Tracy, Kissimmee, Istokpoga are FL lakes.  All MN and WI lakes are infested with Eurasian watermilfoil.  All NC and FL lakes are infested with Hydrilla.  Waccamaw is bog stained and the hydrilla is a recent infestation

Specifically this graph tells us the following:

  1. Invasives grow closer to the surface of lakes than natives and growth seems to be highest in lakes of intermediate productivity (meso-eutrophic)
  2. Natives appear to grow at the 40-60% biovolume level regardless of productivity.
  3. Native growth can be an objective benchmark from which to judge the success of invasive management in non-eradication management regimes.
  4. Aquatic Plant management was successful at bringing down invasive growth to the level of natives in Gray’s Bay of Lake Minnetonka, Kissimmee, and Istokpoga
Something as simple as what is displayed in Figure 4 can bring an objective point of reference to the table when discussing the often controversial nature of aquatic plant management.  With data such as these, discussions by various user and management groups can center on the acceptable level of growth to meet Fisheries, Water Quality, and Invasive Species management goals (which we argue can occur at some intermediate level of plant growth).  Without both species AND abundance data, various factions will continue to take up positions with anecdotal evidence that support their prejudices and the discourse will never get to where it needs to be to tackle these important water resource issues.

Detect Change in Your Lake Before it’s Too Late!

Citizens all over the globe love their lakes and go to great lengths and spend lots of money to protect and manage them.  In the US, the Environmental Protection Agency supports a multitude of State, Local, and citizen efforts to monitor water quality in lakes and has implemented a rigorous National Lakes Assessment.  Despite these efforts, lakes across the nation continue to be impacted from runoff pollution and invasive species proliferation under our noses. How does this happen?

Continue reading “Detect Change in Your Lake Before it’s Too Late!”

Patterns of aquatic plant species domination

In an earlier blog post, we informed you of collaborative research in which CI is involved.  We’ve touched on how species presence/absence surveys using methods like point-intercept and full system acoustic surveys of abundance can be combined to fully understand the dynamics of aquatic plant communities and how they are responding to range of “forces.”  These forces may be natural like seasonal or interannual variability, human induced but unintentional like accelerated eutrophication, or the introduction of invasive species, or intentional management interventions to control nuisance aquatic plant growth.  Whatever the case, entire lake ecosystems are likely to be affected these forces including plant species composition, abundance, and spatial patterns of plant growth.

We can generally expect a bell curve-like response of plant growth at differing levels of productivity (Figure 1).  In nutrient-poor oligotrophic lakes, aquatic plants are typically never very abundant because of nutrient limitations or sediment hardness.  At the other side of the spectrum in overly productive or hypereutrophic systems, the lake is often too murky from algae growth or sediment suspension to support much plant growth.  Goldilocks finds her sweet spot in moderately productive meso- or eutrophic lakes (Figure 1).  The cumulative effects of various stressors continually move the ball towards the right of the productivity curve where thresholds are being approached and sometimes breached.  We’ve spoken about this resilience issue also in a previous post.

Figure 1. Conceptual model describing general patterns of aquatic plant abundance  in  shallow to moderately  deep lakes as a function of lake productivity.  O = Oligotrophic or low nutrient levels; M = Mesotrophic or moderate nutrient levels; E = Eutrophic or high nutrient levels; HE = Hypereutrophic or really high nutrient levels.

Likewise, we could replace the Y-axis in Figure 1 with Species Richness and we’d have the same conceptual model and predictions for how lakes should respond to environmental or human stressors.  Maybe this brings back memories of the Intermediate Disturbance Hypothesis a la Connell (1978) for our readers with an academic history in Ecology?

Having understood these patterns, researchers and managers have done much work to assess aquatic plant communities, make prescriptions on their management or conservation, and evaluate outcomes of management efforts.  Still, assessment techniques have generally been focused either on species occurrence patterns or gross plant abundance patterns but rarely both, and especially at the whole-lake scale.
For instance, the point-intercept method has been used to describe species occurrence patterns in many systems throughout the upper Midwestern US (Madsen et al. 2002, Beck et al. 2010, Mikulyuk et al 2010, Valley and Heiskary 2012).  Indeed, this work and many other studies not cited here has contributed great knowledge on factors contributing patterns of what species grow where.  But they can’t tell us “how much.”
In contrast, hydroacoustics assessments of plant abundance has shed light on how various factors affect patterns of plant abundance in lakes (Valley and Drake 2007, Winfield et al. 2007, Zhu et al. 2007, Sabol et al. 2009, Netherland and Jones 2012).  So hydroacoustics can tell us “how much” but generally not what species grow where unless you are dealing with monocultures.
Duh! Combine results from both methods!
Although it seems obvious regarding the proper solution, prior to today, there were many budget and technological difficulties that made combining both species and abundance surveys at the whole lake scale not very feasible.
Most of these barriers were with the acoustic techniques.  Equipment was costly, it required a lot of specialized training to operate and make sense of the data, you needed powerful computers and a lot of data storage capacity.  
Innovations in acoustic and computing technology has smashed these barriers and now valuable high resolution data on aquatic plant abundance can be logged passively to a $650 depth finder while you conduct your species occurrence surveys.  When you return from the field, just add “upload sonar data” to your list of things to tidy up before heading home for dinner.  30-min later all the abundance data will be waiting in the queue to be combined with your frequency of occurrence species data.
Combining point-intercept and acoustic data into meaningful statistics
In our point-intercept on steroids post we described how to append a biovolume column to your point-intercept data file.  In this investigation we have now taken matters to the next step and defined a potentially useful metric (Dominance) and evaluated its utility across several Minnesota and Wisconsin Lakes and one natural North Carolina Lake (Table 1).
Table 1.  Lakes part of a collaborative study demonstrating a technique for quantifying the impact of individual species on plant abundance patterns.  Zmax = max depth in feet; Prod. = productivity as described in Figure 1.  Invasive plants include Eurasian watermilfoil (EWM), Curly-leaf pondweed (CLP), and Hydrilla (HYD).
What we define as Dominance is a metric that ranges from 0 (no plant growth at all) to 1 (surface growth of one species).  The number of species combined with the biovolume at a survey point determines the dominance value.  So at each survey point:
Species1 / Total Species* x Biovolume = Dominance
*Excludes emergent and free-floating species
This means that 10 species sampled at point X with a biovolume of 100% only gets a value of 0.1.  In many natural glacial lakes, surface growth of aquatic plants is common in shallow areas, but typically, many species contribute to the local assemblage.  In a disturbed or invasive dominated lake, surface growth is common but usually only 1-2 species (e.g., D = 1 and 0.5 respectively) contribute to these dense beds.
Figure 2 demonstrates what we find in lakes that range from oligotrophic, uninfested lakes to borderline hypereutrophic infested lakes.
Figure 2. Patterns in aquatic plant growth in lakes that span a range of productivity (ordered from left to right – see Figure 1 for productivity definitions).  BVw is the average total biovolume in the surveyed areas generated from ciBioBase grid reports. Freq. Monocultures is the frequency of species survey points that had only 1 or 2 species and growth was near the water surface.  BV Natives is the biovolume of species survey points where only native submersed or floating leaf plants were growing.  BV Invasives is the biovolume at sites with invasive species present.
First, with the exception of bog stained Waccamaw that naturally depresses plant growth, the overall abundance of plants as expressed as average biovolume (Blue bars- BVw) by in large follows the bell shaped curve in Figure 1.  Second, the biovolume where only native plants grow is pretty stable across all lake types (again excluding Waccamaw) and invasives (in this case Eurasian watermilfoil) push the biovolume higher.  This patterns of biovolume at surveyed points give us another quantitative indicator about the actual impact of invasives and could serve as a benchmark for management objectives.  Third, the red bars tell us how frequent during each survey we saw surface growing beds of one species.  Interestingly, the frequency increases as the lakes become more productive with invasive plants.
Lake Wingra – an extreme example of Eurasian watermilfoil domination

Lake Wingra is a shallow, eutrophic lake near the campus of University of Wisconsin in Madison, Wisconsin.  Wingra resides in an urban watershed and the lake today is a reflection of a long legacy of watershed and in lake impacts from high runoff, sedimentation, and invasive species proliferation such as common carp and Eurasian watermilfoil.  More information on this lake can be found here.
Today, the lake is dominated by Eurasian watermilfoil (there’s that word again: dominated).  What we are doing now is putting numbers behind this descriptive word so the situation can be improved.
So what does “domination” mean in Wingra?  It means that 50% of the sampled points in the lake had only Eurasian watermilfoil or one other species growing to the surface (Figure 2).  It means that 130 acres of the 281 total acres mapped (45%) were essentially surface-growing monocultures of Eurasian watermilfoil (Figure 3).  These represent objective benchmarks that form the foundation of solutions.  It’s probably not a stretch to assume that 129 acres of surface growing Eurasian watermilfoil is not desirable.  With the tools described here local managers and citizens can work out what is desirable and take measures to get there.  But getting there requires objective, repeatable assessment methods that shed light on both species AND abundance patterns.
Figure 3.  Contours (yellow) delineating the extent of surface-growing Eurasian watermilfoil  beds on Lake Wingra (Dane Co. WI).  The background map is a heat map of aquatic plant biovolume collected with a Lowrance HDS-5 and processed with ciBiobBase.  Areas of red is vegetation growth near the surface.  The few red areas outside of the yellow contour lines represent areas where 1 or more native species contributed to the surface growth.

The future: national risk assessment models
Contour Innovations is currently developing data import capabilities to overlay species surveys on ciBioBase maps.  This will have immediate local benefits for our clients, but the real power of such functionality is the building of a powerful national database of species and abundance surveys.  This can lead to independent research efforts to model aquatic plant growth patterns and model risk of certain aquatic systems to domination by an invasive aquatic plant species.  But a critical mass of cooperation by the water and fisheries resource community including academia and public and private institutions is needed to develop robust models.  Contact us if you are interested in being a part of this effort.  We will be taking this concept to the road at the Midwest Aquatic Plant Management Society meeting in Cleveland, Western Aquatic Plant Management Society in Idaho, Minnesota Chapter of the American Fisheries Society in St. Cloud MN and other to be determined venues.
Ray Valley
Chief Aquatic Biologist
Literature Cited
Beck, M. W., L. Hatch, B. Vondracek, and R. D. Valley. 2010. Development of a macrophyte-based index of biotic integrity for Minnesota lakes. Ecological Indicators 10:968-979.
Connell, J. H. 1978. Diversity in tropical rain forests and coral reefs. Science 199:1302–1310.
Madsen, J. D., K. D. Getsinger, R. M. Stewart, and C. O. Owens. 2002. Whole Lake fluridone treatments for selective control of Eurasian watermilfoil: II. impacts on submersed plant communities. Lake and Reservoir Management 18:191–200.
Mikulyuk, A., J. Hauxwell, P. Rasmussen, S. Knight, K. I. Wagner, M. E. Nault, and D. Ridgely. 2010. Testing a methodology for assessing plant communities in temperate inland lakes. Lake and Reservoir Management 26:54–62. doi: 
Sabol, B. M., J. Kannenberg, and J. G. Skogerboe. 2009. Integrating Acoustic Mapping into Operational Aquatic Plant Management : a case study in Wisconsin. Journal of Aquatic Plant Management 47:44–52.
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.
Valley, R. D., and S. Heiskary. 2012. Short-term declines in curlyleaf pondweed in Minnesota: potential influences of snowfall. Lake and Reservoir Management 28:338–345.
Winfield, I. J., C. Onoufriou, M. J. O’Connell, M. Godlewska, R. M. Ward, A. F. Brown, and M. L. Yallop. 2007. Assessment in two shallow lakes of a hydroacoustic system for surveying aquatic macrophytes. Hydrobiologia 584:111–119.
Zhu, B., D. G. Fitzgerald, S. B. Hoskins, L. G. Rudstam, C. M. Mayer, and E. L. Mills. 2007. Quantification of historical changes of submerged aquatic vegetation cover in two bays of Lake Ontario with three complementary methods. Journal of Great Lakes Research 33:122–135.