DOI: 10.5061/dryad.wdbrv15tb
title: Data for: Aquatic connectivity treatments increase fish and macroinvertebrate use of Typha invaded Great Lakes coastal wetlands

description: Coastal wetlands provide critical habitat for aquatic organisms and
 important ecosystem services for the terrestrial and aquatic landscapes
 they bridge, but increasingly common invasive macrophytes disrupt plant
 communities, food webs, habitat structure and littoral-pelagic linkages.
 In Laurentian Great Lakes coastal wetlands, invasive cattails (Typha
 ×glauca and T. angustifolia, hereafter Typha) homogenize ecosystem
 structure and reduce nearshore dissolved oxygen, and plant, fish, and
 macroinvertebrate diversity. We hypothesize that management treatments
 that reduce Typha and its abundant litter promote structural heterogeneity
 and mitigate physiochemical and biodiversity impacts. To test this
 hypothesis, we implemented a large-scale (2048 m2 treatment units),
 multi-site (four coastal wetlands) experiment in northern Michigan (USA)
 to examine how invasive Typha mechanical harvesting treatments (biomass
 harvest, aquatic connectivity channels, Typha-dominated control) altered
 fish, macroinvertebrate, plant, larval amphibian abundance and diversity,
 and water quality for two-years post-treatment. We collected fish,
 macroinvertebrates, plant, larval amphibian, and water quality data from
 for two years following the implementation of management treatments. These
 data are presented in this archived dataset. 
description: Study sites We selected four Great Lakes
 coastal wetland complexes in northern Michigan (USA) for our study, one in
 the northern Lower Peninsula and three in the eastern Upper Peninsula. Two
 of the wetlands (Cheboygan Marsh and St. Ignace Marsh) are in the Straits
 of Mackinac, near the confluence of Lakes Michigan and Huron, and two
 (Munuscong Marsh and Sand Island Marsh) are in the St. Marys River, the
 connecting channel between Lakes Superior and Huron (Figure 1). All
 wetlands shared similar connectivity to the open lake, but hydrogeomorphic
 type varied among the wetlands; Cheboygan Marsh and St. Ignace Marsh are
 lacustrine open embayment types, Munuscong Marsh is a connecting channel
 river delta, and Sand Island is a connecting channel protected embayment
 (Albert et al., 2005). Study design
 We conducted our study within invasive Typha-dominated portions
 of the four wetland complexes. Due to the abundance of advanced generation
 hybrids in upper Midwest <em>Typha</em> populations and the
 high frequency of disagreement between morphological traits and molecular
 identification (Geddes et al., 2021), we did not attempt to differentiate
 between hybrid cattail (<em>Typha</em>
 ×<em>glauca</em>) and narrow-leaved cattail (<em>Typha
 angustifolia</em>), but clumped invasive cattails into one taxon for
 this study. Invasive cattails had been widespread in all study wetlands
 for over a decade (Lishawa et al. 2010, Lawrence et al. 2016) and for more
 than 50 years in Cheboygan Marsh (Lishawa et al. 2013) and were the
 dominant emergent plant taxon (&gt; 50% relative dominance) of
 &gt; 25 ha in each focal wetland. To test
 biodiversity responses to invasive <em>Typha</em> harvest and
 aquatic connectivity channel treatments, we used a block design with four,
 32 × 64 m plots nested within each block. Each treatment block consisted
 of four randomly assigned treatments: harvest, harvest-channel (a channel
 nested within a harvested plot), control-channel (a channel nested within
 an unharvested plot), and control (unmanipulated
 <em>Typha</em>­-dominated plot). We created one block in each
 wetland except St. Ignace, which had two blocks (Figure 1c; Figure
 2).  In July and August 2016, we randomly assigned
 treatments, delineated all blocks and plots, and implemented treatments.
 Plots were oriented with their length (64 m) perpendicular to the
 shoreline so that they crossed the primary water level gradient at each
 site. Each plot was 32 m wide. We harvested and removed all biomass (i.e.,
 standing litter and living vegetation) at 20 cm above the water level from
 the harvest and harvest-channel plots using a low ground-pressure Softrak
 wetland plant harvester (Loglogic, Cullompton, United Kingdom). Within the
 harvest-channel and control-channel plots, we manually cut and removed all
 biomass at the sediment surface using aquatic weed whackers (RedMax,
 Lawrenceville, GA, USA) from 3-m wide by 50-m long channels, which
 bisected the center of each plot along the water depth gradient (Figure
 2). The aquatic weed whackers have flat reciprocating cutting blades,
 which slide along the surface of the sediment, allowing us to cut stems
 approximately 2 cm above the surface with minimal substrate
 disturbance. Field data collection
 We collected water quality and biodiversity data (plant, fish,
 macroinvertebrate, and larval amphibian) for two years following treatment
 implementation, in summer (June – August) 2017 and 2018 from subplots
 within each plot; treatments were implemented at the plot level. Subplot
 distribution and density differed among the taxa sampled (see
 below). Plant Sampling Within each
 plot we established eight, 1 × 1-m subplots for plant community data
 collection. Four subplots were located in plot corners equidistant from
 the plot margins (8 m) and four subplots were located 12 m apart along the
 plot’s meridian to align with the channels (Figure 1c). In mid-July
 through mid-August of each study year (2017 and 2018), we estimated
 percent cover for every species and <em>Typha</em> stem
 density and height from each subplot. Invasive cattail height data were
 used to calculate biomass, using a height-to-biomass allometric equation
 (Lishawa et al., 2015). Fish and Larval Amphibian
 Sampling We established either four or six subplots for
 fish sampling within each plot: four plots within the harvest and control
 treatment plots, which corresponded with the corner vegetation subplots
 (i.e., 8 m from each plot margin), and two additional subplots located 15
 and 30 m into the channels within the harvest-channel and control-channel
 plots (Figure 1c). We sampled fishes three times throughout the growing
 season (June, July, and August) in each year (2017 and 2018) from each
 subplot using three Gee minnow traps (mesh size 0.64 cm) set over one to
 three nights. We used minnow traps in lieu of fyke nets or electrofishing
 because minnow traps are effective at sampling small-bodied fishes in
 dense vegetation (Henning et al., 2014; Jacobus and Webb, 2005; Webb,
 2008), and vegetation density in most subplots precluded efficient
 sampling by these other methods. Minnow traps were set 5 m apart, baited
 with dry dog food, and checked every 24 h. Fishes were identified as
 species (or lowest taxonomic group possible) in the field and enumerated.
 Any adults of difficult-to-identify species (e.g., shiner species) were
 euthanized with 250 mg/L tricaine methanesulfonate (MS-222), fixed in 10%
 formalin, and transferred to 70% ethanol after 24 h for later
 identification in the laboratory. Fish abundance was quantified for each
 subplot as catch-per-unit-effort (CPUE) as the number of fishes captured
 in the set of three minnow traps in each subplot in 24 h. We did not
 include fish data from the Munuscong Marsh treatment block in our analysis
 because fish abundance across all plots and treatments was extremely low,
 indicating that minnow trap sampling at this site was ineffective. Larval
 amphibians were collected in minnow traps during fish sampling and were
 enumerated and released in the field (Skelly and Richardson, 2010). For
 each subplot the CPUE for larval amphibians was defined as the number of
 larvae captured in the set of three minnow traps in a 24 h
 period. Macroinvertebrate sampling
 We collected macroinvertebrate samples in late July through
 early-August in 2017, to correspond with the period when emergent plants
 typically reach maximum annual biomass and late instars of most aquatic
 insects are present and easy to identify (Kashian and Burton, 2000). We
 collected at least three replicate samples per subplot, each replicate
 consisting of 1-m dip net (0.5 mm mesh) sweeps at the water surface,
 mid-depth, and at the substrate surface. In the field, we emptied nets
 into white pans and picked macroinvertebrates (Uzarski et al., 2004). In
 the laboratory, organisms were sorted into the finest taxonomic group
 possible, and richness and abundance metrics were estimated. Crayfish were
 sampled using the same method as fishes. In the field, we observed
 dramatically different patterns of invertebrate abundance by treatment
 within the Munuscong block, where large numbers of Asellidae were present
 in the control and harvest treatments. Therefore we statistically
 evaluated this metric (invertebrate abundance [number / m2]) as a full
 model (all blocks), with Munuscong block excluded, and with the Munuscong
 block alone.  Water quality sampling
 We measured standard water quality parameters to relate taxonomic
 data with abiotic conditions. These parameters included water depth,
 temperature, dissolved oxygen, turbidity, pH, specific conductivity
 (determined in situ), total N, total P, and chlorophyll a (determined in
 the lab). In situ water quality parameters were measured at each subplot
 and sampling date using a YSI Professional Plus Multiparameter Instrument
 (Xylem Inc., Yellow Springs OH, USA) and a Hach 2100Q Portable
 Turbidimeter (Hach, Loveland CO, USA). Nutrients (total N and P) were
 field-collected during fish sampling and analyzed using standard methods
 on a SEAL AutoAnalyzer 3 spectrophotometer (SEAL Analytical, Mequon, WI,
 USA). Chloride, fluoride, and sulfur were also collected during fish
 sampling, lab-filtered through a MF-Millipore 0.45 um MCE membrane filter,
 and analyzed on a Dionex Integrion High-Performance Ion Chromatography
 system (Thermo Fisher Scientific Inc., Waltham MA, USA). Chlorophyll a
 samples were collected by filtering a known volume of water through a 45
 µm filter in the field. Filters were stored on ice and chlorophyll a was
 analyzed using a Turner Designs TD-700 Fluorometer (Turner Designs, San
 Jose, CA, USA). All analyses were completed at the University of Michigan
 Biological Station, in Pellston Michigan, USA.
description: Data is saved in Excel file (.xlsx) format and can be opened with
 Microsoft Excel or Google Sheets. 
description: # Aquatic connectivity treatments increase fish and macroinvertebrate use
 of Typha invaded Great Lakes coastal wetlands: Data --- We conducted a
 large-scale study investigating the effects of invasive cattail (Typha
 spp.) mechanical treatments (harvest, channel, control) on biodiversity in
 four Great Lakes coastal wetlands. The dataset contains water quality,
 plant, fish, macroinvertebrate, and amphibian taxonomic data from the two
 years following treatment implementation. We found that harvest and
 channel treatments decreased Typha dominance, and channel treatments were
 more effective; harvest treatments increased total biodiversity; and
 channel treatments shifted the community composition toward aquatic
 species. ## Description of the Data and file structure The data are
 structured in five spreadsheets (Total, Plants, Fish, Invertebrates, and
 Amphibians) as individual tabs in the excel file. The Total spreadsheet
 contains all environmental data and all taxonomic data from the full
 study. The individual taxonomic group spreadsheets (e.g., Plants) contains
 the taxonomic data of that group and associated environmental data.
 Columns within all spreadsheets begin with date (year) site, treatment,
 subplot identifiers. Environmental data include: organic (depth of organic
 sediment(cm)), unveg (percent of 1x1 m subplot that was unvegetated), veg
 (percent of 1x1 m subplot that was vegetated), detritusAW (percent cover
 of detritus above the water), detritusBW (percent cover of detritus below
 the water), water_depth (measured water depth (cm)), pH (measured in
 situ), cond (conductivity, measured in situ), temp (water temperature
 measured in situ), DO (dissolved oxygen, measured in situ). Diversity
 metrics follow environmental data and include: alltaxa_H (Shannon
 diversity of all taxa), alltaxa_simp(Simpson diversity of all taxa),
 alltaxa_rich(taxa richness of all taxa), H and richness for each specific
 taxonomic group (e.g., H_plant = plant Shannon diversity). Finally,
 specific taxonomic data are included with six letter shorthand
 representing the first three letters of the genus and first three letters
 of the species. For instance, typang represents Typha angustifolia. In the
 case of invertebrates and fish, taxa are also included as family
 groupings, and are indicated with a prefix of “F_” as in, “F_cyprinidae”
 representing all individual fish collected from the family Cyprinidae.
 Additionally, the relative dominance by functional groups are included for
 plants (e.g. “grassRD” represents the proportion of total plants
 represented by grasses), and the total count by functional feeding groups
 are included for invertebrates (e.g. “Collectors”). Missing data are
 represented by NA. ## Sharing/access Information NA