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.

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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