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2014 Pilot Study: Spring Phenology of Submersed Aquatic Plants – Lake Minnetonka, MN

© 2015 – Freshwater Scientific Services, LLC of 15 .

2014 Pilot Study: Spring Phenology of Submersed Aquatic Plants Assessment of Plant Emergence and Growth in Relation to Spring Water Temperature

Lake Minnetonka (East Phelps Bay & St. Albans Bay) Surveying & Analysis by:

James A. Johnson – Freshwater Scientific Services, LLC Funding Provided by: Minnehaha Creek Watershed District – Minnetonka, MN

US Army Engineer Research and Development Center – Gainesville, FL

Aquatic Ecosystem Restoration Foundation – Flint, MI

15771 Creekside Lane Osseo, MN 55369 [email protected] (651) 336-8696


© 2015 – Freshwater Scientific Services, LLC of 15 ... ...

Introduction

Context

Past studies have shown that herbicide treatment with endothall herbicide in the early spring can effectively control curlyleaf pondweed (Johnson et al. 2012, Skogerboe et al. 2012, Poovey et al. 2002, Netherland et al. 2000). Although endothall herbicide is not inherently selective for curlyleaf pondweed, the strategy of treating in the early spring exploits curlyleaf’s propensity for active growth in cool water. Previous studies have shown that endothall effectively controls curlyleaf when water temperature is greater than 50°F (Netherland et al. 2000), and that most native aquatic plants remain relatively dormant and less likely to be affected by herbicides when water temperature is below ~60°F (Barko et al. 1982). Based upon these studies, the current strategy is to treat curlyleaf pondweed with endothall when water temperature is between 50°F and 60°F, with the goal of maximizing curlyleaf control while minimizing the negative impacts to native plants in treated areas. This is the rationale behind the current permit requirement by the Minnesota Department of Natural Resources that endothall applications for curlyleaf must occur when water temperature is between 50° and 60°F. Although this temperature window appears to be very straightforward and easy to measure, it appears much less so when you observe actual early-spring temperature dynamics in real lakes. Several factors can lead to rapid and large changes in the water temperature experienced by plants growing in natural lakes: • Day-Night Temperature Variation: Water temperatures in shallow nearshore areas can

experience diurnal swings of >10°F on warm sunny days.

• Spatial Temperature Variation: Isolated shallow bays may warm much more quickly than more exposed areas adjacent to deeper areas in the same lake, and on calm days, water near the surface in relatively shallow areas can be much warmer than near the bottom (where plant shoots are emerging).

• Mass Water Movement: Winds can quickly push warmed surface water to one shore and pull up cold water on the upwind shore, leading to a large temperature difference on opposite shores.

• Weather Changes: Lakes often experience rapid spring warming and cooling where water temperature may exceeds 60°F for several days only to cool down below 50°F in subsequent days or weeks.

These spatial and temporal fluctuations in water temperature make it difficult to determine when a lake is within this 50° to 60° temperature range. If a lake has warmed to 65°F for a few days but then cools to 50°F after a cold windy night, is it still alright to treat? Should temperature measurements be taken off the end of a resident’s dock in the late evening, or would a morning temperature taken offshore be more representative? These two readings may differ substantially. The 50° to 60°F window is a useful guideline, but a more detailed understanding of the phenology of native aquatic plants and the relationship between temperature, plant emergence, and the onset of active plant growth for different plant species would help to ensure that the timing of such treatments is appropriate to maximize control of curlyleaf while also protecting native plants.



Purpose of Study Previous studies that have studied native phenology have generally focused on only a few native plant species growing in mesocosms (tanks or small constructed research ponds). Our study differs from these past works in that we tracked the emergence and growth of many native plant species in a natural lake while also collecting detailed and continuous records of water temperature, sediment temperature, and light. By tracking these in-lake conditions, our goals were to: (1) Document the timing of plant emergence and the onset of active growth for many native

aquatic plant species as water temperature warmed from 40°F to 70°F

(2) Evaluate how well plant emergence and growth coincided with the 50° to 60° temperature window used to guide early-season endothall treatments

(3) Identify which plant monitoring methods provide the best assessment of plant emergence and active growth for use in future studies

(4) Investigate whether a simple cumulative heat model (Growing Degree Day) could reduce the ambiguity associated with the 50° to 60°F treatment window and allow for easier planning and permitting of early-spring endothall treatments



Description of Study Areas

Our study focused on two plots in Lake Minnetonka (Hennepin County, MN); one in East Phelps Bay (9.5 acres) and the other in St. Albans Bay (10.8 acres; Fig 1 and 2). Each of these study plots extended from shore out to roughly the 4-m depth contour (Fig 2). The study plot in St. Albans Bay was in an isolated portion of the bay, whereas the East Phelps Bay plot was in a more exposed location that likely experienced greater water exchange with open deeper areas. These diffences in exposure were expected to result in slower warming of water in the East Phelps plot. Water clarity in both of these bays was >3 m during the study period, so sediments throughout each of the plots received ample light to support abundant plant growth.

East Phelps Bay St. Albans Bay

Figure 1. Location of Lake Minnetonka and study plots

East Phelps Bay

St. Albans Bay

Lake Minnetonka

Figure 2. Water depth (ft) in the East Phelps Bay study plot (9.5 acres) and St. Albans Bay study plot (10.8 acres); generated using ciBioBase. Thicker black lines show the approximate boundaries of areas monitored in each bay. Probe locations denoted by yellow dots.

9

3 6

12

3

9

6

12



Methods

Monitoring Temperature & Light In the early spring of 2014 (at the time of ice-out), we installed data-logging temperature and light probes (Onset Computer Corp.; Bourne, MA) in East Phelps Bay (on April 22) and St. Albans Bay (on April 25), both bays of Lake Minnetonka (Fig 1 and 2). The official ice-out date for Lake Minnetonka in 2014 was April 24. In each bay, we deployed probes at three locations corresponding to 1m, 2m, and 3m water depth. We installed 2 probes at each of these locations, one ~30 cm above the sediment surface to recorded light and temperature near the bottom, and the second ~5 cm below the sediment surface to record sediment temperature experienced by propagules and root-stock. All deployed probes logged readings every 30 minutes continuously from deployment through June 17, 2014. In addition, we collected manual temperature profiles at each of the locations weekly during the study. For installation at each location, we attached 2 probes to a 1-m long stake (1-in. PVC pipe) with the sensors positioned 40 cm apart. We used an extension pole with a threaded end to push each stake into the sediment (top of stakes also threaded to allow attachment to pole). Before installing each stake, we measured water depth to the nearest cm and placed a rubber band around the installation pole to mark the depth to which the stake must be installed to ensure proper probe positions relative to the sediment-water interface. We then pushed the pole and the attached stake vertically into the sediment until the rubber band was even with the surface of the water, then turned the extention pole to release the stake from the threaded attachment. After deployment, we inspected each stake using underwater cameras (Marcum camera for inspection, and GoPRO camera for photographs) to ensure proper probe positioning. To simplify probe retrieval at the end of the study, we connected the 2-m and 3-m stakes with a 200-ft section of plastic clothesline (non-buoyant) prior to installation. At the end of the monitoring period, we used a rake to snag the center of this line, and then used the line to pull out the stakes at each end; the 1-m stake was clearly visible from the surface and was easily installed and removed by hand.

Figure 3. Stake with attached probes. Top probe (A) recorded temperature and light (light sensor installed facing up), and bottom probe (B) recorded temperature only (sensor buried ~5 cm below sediment surface).

Figure 4. Installed stake with attached probes. Uppermost probe ~30 cm above the sediment while the bottom probe’s sensor is buried ~5 cm below the sediment surface. Light sensors were positioned to the south to avoid being in the shadow of the stake.

A

B



Monitoring Aquatic Plant Emergence and Growth In each plot, we established 15 sample points; 5 points spaced along each of the 1-m, 2-m, and 3-m contours. We surveyed plants at these points weekly between late April and mid June using rake samples, underwater video, and surface observations (Apr 22, Apr 25, May 4, May 9, May 21, May 28, Jun 4, and Jun 18). We used the rake method described by Johnson and Newman (2011) to collect plants from ~0.1m2 of the lake bottom at each location. The retrieved plants were identified and assigned density ratings in the field (0-3 scale). In addition, we estimated the average plant height of each taxon at each location by measuring plants retrieved on the rake and visual observations (plants growing in the immediate vicinity), and noted whether each taxon was actively growing, as determined by the presence of new sprouts or shoots. Monitoring Aquatic Plant Biomass During the period of time when plants began to exhibit active growth, we bagged the retreived plant samples from each rake sample and sent them to Mike Netherland’s lab at the University of Florida–Gainesville for sorting and biomass determination. Much of the collected plant material consisted of “old growth” remaining from the previous season; we did not separate old growth from new growth. Most samples contained attached zebra mussels that were difficult to remove from the plants. Many mussels fell off of the plants during collection and processing, but we did not make a concerted effort to remove the numerous small zebra mussels still attached. Sonar Assessment of Plant Growth (ciBioBase) During each survey, we logged sonar data with a Lowrance sonar unit while slowly navigating a winding transect that covered each of the study plots (transect spacing ~10 m). The recorded sonar files were uploaded to the ciBioBase server (ciBioBase.com; Contour Innovations LLC, St. Paul, MN) using the Minnehaha Creek Watershed District’s ciBioBase subscription for analysis of plant coverage, biovolume, and overall plant height. Calculation of Growing Degree Days We used the Growing Degree Day (GDD) method typically used to predict the emergence and growth of agricultural crops and pest (Miller et al. 2001) to evaluate whether a GDD cumulative heat model provided any advantages over simply using surface water temperature to predict aquatic plant phenology. The GDD method uses mean daily temperature and a base temperature that corresponds to the minimum temperature at which active plant growth occurs. For each degree that the mean daily temperature exceeds the base temperature, the system accumulates one GDD. These GDD’s are summed over time to estimate the cumulative amount of exposure to heat, which is a strong determinant of cumulative enzyme activity, and thus growth, in plants. There is some precedence for applying this method to aquatic systems; to predict aquatic plant propagule sprouting (Spencer et al. 2000) and fish growth (Neuheimer et al. 2007). We calculated air-based GDD using records of the daily mean air temperature at the MSP airport (MN State Climatology Office) during the study period for base temperatures of 40°, 45°, and 50°F. We also calculated water-based GDD using the logged water temperatures and a base of 45°F (Fig 5). Given that water temperature in our plots was already in the low 40’s at the time of ice-out, a lower base temperature (<45°F) would not be useful. We plotted cumulative GDD over time for both air and water to determine if air temperature could be used as a reliable predictor of in-lake GDD.



Results & Discussion

Water Temperature

The Twin Cities metropolitan area experienced an unusually cool spring in 2014, leading to a late ice-out and a slower than normal warming of metro area lakes. Mean daily water temperatures in the study bays (measured ~30 cm above the sediment) warmed slowly from ~40°F immediately after ice-out to 50°F in the first week of May, remained between 50°F and 60°F through the third week of May, and then hovered between 65°F and 75°F through mid June (Fig 5). This long cool spring was not typical for metro area lakes, but it provided an interesting opportunity to observe plant growth over a long, slow warming period rather than the more rapid spring warming typically seen in metro-area lakes. This slow warming resulted in a slower phenological progression in the study bays than we would typically see, allowing for more detailed observations of how temperature was related to plant emergence and growth. However, we can not be sure that these results are typical for years with more normal spring warming. Additional studies covering more lakes and additional years will be necessary to make general predictions of temperature effects on aquatic plant phenology in Minnesota. Any similar future studies should consider surveying plants more frequently than every week, particulary if water temperatures warm more rapidly than seen in our study. Sediment Temperature Immediately after ice-out, the sediment temperature at all locations was very similar to the temperature of the overlying water (~40°F). As the water warmed, sediment temperature also increased, but lagged slightly behind the water temperature. In the 2 shallowest sites (1m deep), sediments generally remained within 1-2°F of the overlying water temperature, but the temperature lag was greater (2-8°F) in the deeper 2-m and 3-m locations. This lag was greatest during the periods of most rapid increases in water temperature; when the rate of water warming slowed, the sediment temperature generally caught up within a few days. Despite this lag, it appears that propagules in the top 5-10 cm of sediment would experience roughly the same temperatures as the overlying water, but with a slight lag in the timing. This suggests that in years when rapid warming makes it difficult to treat lakes in the 50-60° temperature window (due to the logistics of treating many lakes in a very short time), native species that emerge from propagules in the lake sediments may experience delayed sprouting (later than expected based upon water temperature), providing an added margin of safety in such “late” treatments. Light Several past studies have shown that light and temperature may both be important triggers for plant emergence and active growth in some situations (Flint and Madsen 1995, Madsen and Adams 1988). The light probes that we used recorded simple illumination (intensity across visible light wavelengths) rather than photosynthetically active radiation (PAR). PAR provides a more accurate assessment of the wavelengths used by plants, and would have been a critical measurement if light was the primary factor limiting plant growth in our study. However, the water clarity in the study bays remained high throughout our study (>3m) and light availability did not likely limit plant growth at our monitored sites. Consequently, daily differences in illumination did not appear to be an important factor affecting plant emergence or growth in our study plots. For future studies, light measurements may prove to be more useful by allowing lakes with lower water clarity to be grouped and analyzed separately from sites where plant growth was not limited by light availability.



Growing Degree Day Model

The mean daily air temperature was much more variable than the mean daily water temperature (Fig 5), but both showed more predictable warming patterns when converted to GDD. The plot of air GDD45 (base 45°F) followed roughly the same upward trend as the plot for water GDD45, but was consistently ~100 growing degree days ahead on any given date (air GDD shifted upward). By subtracting 100 degree days from the cumulative total of the air GDD we were able to align this plot with the water-based GDD plots from the fastest warming sites (St. Albans Bay, 1m and 2m sites). Although it is likely that the agreement we saw between the air-based GDD model (GDD45-100) and the water-based GDD45 model would not hold true for all lakes, our results suggest that it may be possible to accurately estimate and even predict in-lake GDD based upon weather data and short-term forecasts. Such predictions could streamline the planning and permitting of early-spring endothall treatments by reducing the need for daily temperature monitoring, reporting, and accounting for large swings in temperature. Furthermore, the GDD model would allow for a simplified prediction of accumulated heat using short-term weather forecasts, allowing applicators and lake groups to schedule treatments further in advance. Additional studies are needed across more lakes and years to determine whether the 2014 results are specific to these bays or are generally applicable to other lakes in the region, but it appears that the GDD model may provide some useful advantages over using lake temperature alone. Assessment of Plant Emergence and Growth

The early-season growth of invasive curlyleaf pondweed (Potamogeton crispus) and Eurasian watermilfoil (Myriophyllum spicatum) are well documented in previous studies (Skogerboe et al. 2012, Bolduan et al. 1994). In our study, these invasive plants were among the earliest species to exhibit active growth (Fig 6). Although a few native plant species also showed signs of emergence and active growth in water cooler than 50°F (Potamogeton praeIongus and Ranunculus aquatillis), the vast majority of native plants did not show substantial signs of activity until water warmed to ~60°F (Fig 6). P. praelongus activity was particularly interesting in that it appeared to have 2 distinct phases of growth activity. The first phase began shortly after ice-out (even before curlyleaf began growing actively) and consisted of new stems and leaves growing out of erect stems that remained from the previous growing season. The second phase occurred several weeks later as the water warmed, and consisted of emergence of small shoots from the sediment, presumably from propagules. R. aquatillis also exhibited very early emergence (weeks before most other plants), but did not increase in height until late May. In both of our study plots, we frequently encountered “old growth” plant fragments remaining from the previous year; most notably Zosterella dubia, Potamogeton praelongus, Chara sp., Najas guadalupensis, Myriophyllum spicatum, Ceratophyllum demersum). All of these species produced new sprouts from these remaining plant fragments, so presence alone was not a good indicator of emergence or active growth; noting the existence of new active shoots emerging from these old stems was critical for evaluating the phenology of these species.



Sonar Assessment of Plants Although sonar was not able to distinguish between individual plant species, it provided a high-resolution assessment of changes in overall plant height throughout the plots (Fig 7-9). The ciBioBase analysis produced an interpolated point-grid for each plot with associated values for water depth and % biovolume (% of water column occupied by plants). We calculated plant height at each of these grid points by multiplying the water depth by the % biovolume. We then calculated the mean plant height in each plot for each surveyed date. The sonar-derived mean plant height differs from our manual plant height measurements in that (1) it does not distinguish between the height of different taxa, and (2) it produces an area-based mean plant height that includes points with no vegetation whereas the manual plant heights represent the mean height of measured plants and thus includes no zeroes. This area-based mean proved to be much less sensitive to the active growth of sparse plants and did not contribute substantially to our assessment of native plant phenology. However, it did provided an excellent way to document the onset of active growth in areas with dense Eurasian watermilfoil and curlyleaf pondweed (Fig 7-9). Plant Biomass Plant biomass did not contribute substantially to our assessment of plant phenology in the study plots. Although the biomass of a few species appeared to increase during the monitored period, these changes were not as clear as the changes seen in plant height (Fig 7). Biomass estimates from our study plots appeared to be heavily affected by the “old growth” remaining from the previous season. Furthermore, the numerous zebra mussels attached to plant samples likely added substantially to the biomass estimates. Future phenological studies should consider only including new growth in biomass estimates and should evaluate whether it is worth the effort to remove attached mussels. Overall, early-season changes in plant height seemed to be much easier to assess and provided a much better indicator of active plant growth than biomass.

The results of our study confirm that the current approach to timing early-spring endothall treatments to occur when water temperatures are between 50° and 60°F provides a reasonably good way to maximize curlyleaf control while also protecting most of the native plant species in our study plots. The majority of the native plants we encountered did not exhibit active growth until the very end of May, when water temperatures generally exceeded 65°F. However, some native aquatic plant species appeared to show signs of activity at temperatures well below 60°F, making them more susceptible to damage by such treatments than previously thought; specifically P. praelongus and R. aquatillis. Although timing early-spring endothall treatments based upon the 50°F to 60°F temperature window appears to be appropriate for protecting most native aquatic plant species, we believe that the inherent variability of water temperature makes this a hard target to hit consistently. Strict adherence to this temperature window without considering the rate of warming and length of time plants have been exposed to warmer waters may lead to poorly timed treatments. Incorporating a cumulative GDD model would help managers, applicators, and DNR staff make better decisions for timing in years with rapid warming or oscillation between warm and cold periods. Furthermore, the use of a cumulative heat model based upon air temperature (calibrated to in-lake temperature) would provide a better way to predict the optimal timing of the treatment days in advance based upon weather forecasts.

Management Context


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Figure 5. Plots showing (top) mean daily air and water temperature at 1, 2, and 3-m sites in each bay (SA=St. Albans Bay, EP=East Phelps Bay; measured 30 cm above the sediment); (middle) cumulative Growing Degree Days (GDD) based upon air temperature and base temperatures of 40°, 45°, and 50°F; (bottom) cumulative GDD based upon water temperatures using a base of 45°F, along with an adjusted GDD45° based upon air temperature (subtracted 100 degree days to align with water GDD traces).

Cumulative Growing Degree Days (Water Temperature)

Cumulative Growing Degree Days (Air Temperature)

Water and Air Temperature



Figure 6. Plots showing changes in plant height for fast-growing, medium-growing, and slow-growing taxa during the monitored period; results from both bays combined. Note different vertical scales. Mean plant height is based upon the height of plants from each taxon retrieved in rake samples and observed from the surface.

Fast-Growing Taxa

Medium-Growing Taxa

Slow-Growing Taxa



Figure 7. Plots showing estimated plant growth over time using alternative methods: (1) sonar assessment of overall plant height (ciBioBase) throughout the study plots (change in plant height converted to daily growth rate), and (2) plant biomass sampling.

Sonar Assessment (ciBioBase)

Biomass Sampling



Apr 22 Apr 25 May 4

May 9 May 22 May 28

Jun 4 Jun 18

Figure 8. Sonar-derived maps of plant height in the East Phelps Bay study plot. Each color gradation (light to dark) represents a 1-ft increment in plant height.



Apr 25 May 4 May 9

May 21 May 28 Jun 4

Jun 18

Figure 9. Sonar-derived maps of plant height in the St. Albans Bay study plot. Each color gradation (light to dark) represents a 1-ft increment in plant height.



References

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Extension Service. Bozeman, MT. pp. 8 http://www.ipm.montana.edu/Training/PMT../2006/mt200103.pdf Netherland MD, Skogerboe JD, Owens CS, Madsen JD. 2000. Influence of water temperature on the efficacy of

diquat and endothall versus curlyleaf pondweed. J Aquat Plant Manage. 38:25-32. Neuheimer AB, Taggert CT. 2007. The growing degree-day and fish size-at-age: the overlooked metric. Can J Fish

Aquat Sci. 64:375-385. http://d.umn.edu/biology/documents/Venturelli2.pdf Poovey AG, Skogerboe JG, Owens CS. 2002. Spring treatments of diquat and endothall for curlyleaf pondweed

control. J Aquat Plant Manage. 40(2):63-67. Skogerboe JD, Getsinger KD, Poovey AG. 2012. Early season applications of endothall and 2,4-D for selective control

of Eurasian watermilfoil and curlyleaf pondweed in Minnesota lakes: year two evaluations of submersed plant communities. APCRP Technical Notes. US Army Enginner Research and Development Center. Vicksburg, MS.

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