Louisiana State University LSU Digital Commons
LSU Doctoral Dissertations Graduate School
March 2021
Free-floating Invasive Fern Affects Freshwater Marsh Ecosystem Structure: Changes to Water Quality And Chemistry, Aquatic Vegetation, Fish, and Invertebrates
Charles Wahl Louisiana State University and Agricultural and Mechanical College
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Recommended Citation Wahl, Charles, "Free-floating Invasive Fern Affects Freshwater Marsh Ecosystem Structure: Changes to Water Quality And Chemistry, Aquatic Vegetation, Fish, and Invertebrates" (2021). LSU Doctoral Dissertations. 5466. https://digitalcommons.lsu.edu/gradschool_dissertations/5466
This Dissertation is brought to you for free and open access by the Graduate School at LSU Digital Commons. It has been accepted for inclusion in LSU Doctoral Dissertations by an authorized graduate school editor of LSU Digital Commons. For more information, please [email protected]. FREE-FLOATING INVASIVE FERN AFFECTS FRESHWATER MARSH ECOSYSTEM STRUCTURE: CHANGES TO WATER QUALITY AND CHEMISTRY, AQUATIC VEGETATION, FISH, AND INVERTEBRATES
A Dissertation
Submitted to the Graduate Faculty of the Louisiana State University and Agricultural and Mechanical College in partial fulfillment of the requirements for the degree of Doctor of Philosophy
in
The School of Renewable Natural Resources
by Charles Wahl B.S., Clemson University, 2010 M.S., University of Maryland, Baltimore County, 2016 May 2021 ACKNOWLEDGMENTS
I would like to say thank you to many people, funders and organizations for making my dissertation possible. First and foremost, I would like to say how grateful I am for my advisors Dr. Michael Kaller and Dr. Rodrigo Diaz. I received tremendous amount of help, feedback and encouragement from both of you, all of which have helped me grow into a better scientist and professional. I definitely would not be where I am without the experience and knowledge gained from working under you guys. I am also thankful to my committee members Dr. William Kelso, Dr. Christopher Mudge, and Dr. Vincent Wilson for their assistance and advisement guiding me through the program. Thank you to all the professors and staff along the way who have helped me learn and expand my knowledge of how the natural world operates. A great amount of thanks for my family and friends, who have displayed nothing but support for me and my ventures. Your assistance and encouragement have kept me going through difficult times. Special thanks to the band Phish, whose music brings so much happiness and joy to my life. Traveling around the country for shows, gathering with friends I love, for the music we love, are some of the best moments of my life, and looking forward to the next tour has kept me going through hard times. I would like to thank the following people for field and laboratory assistance, Seth Spinner, Fatima Nguyen, Debra Kelly, Keyla Pruett, Emily Passman, Giovana Matos, Rachel Watson, Darren Richard, Chad Courville, Mariah Taylor, Erin Thayer, Melanie Holton, and Shea Johnson. Thank you to Miami Corporation for allowing me access to conduct a study on your property. Thanks to Louisiana Department of Wildlife and Fisheries, Delta Waterfowl, and Mid- South Aquatic Plant Management Society for providing funds.
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TABLE OF CONTENTS
ACKNOWLEDGMENTS ...... ii
LIST OF TABLES ...... iv
LIST OF FIGURES ...... v
ABSTRACT ...... vii
CHAPTER 1. GENERAL INTRODUCTION ...... 1 Background ...... 1
CHAPTER 2. INVASION OF FLOATING FERN ALTERS FRESHWATER MACROINVERTEBRATE COMMUNITY STRUCTURE WITH IMPLICATIONS FOR BOTTOM-UP PROCESSES ...... 4 Introduction ...... 4 Methods...... 5 Results ...... 8 Discussion ...... 13 Conclusion ...... 18
CHAPTER 3. NUTRIENTS ENHANCE THE NEGATIVE IMPACT OF AN INVASIVE FLOATING PLANT ON WATER QUALITY AND A SUBMERGED MACROPHYTE . 19 Introduction ...... 19 Methods...... 20 Results ...... 22 Discussion ...... 28
CHAPTER 4. INVASIVE FLOATING FERN LIMITS AERIAL COLONIZATION AND ALTERS COMMUNITY STRUCTURE OF AQUATIC INSECTS ...... 31 Introduction ...... 31 Methods...... 32 Results ...... 34 Discussion ...... 37
CHAPTER 5. GENERAL CONCLUSION ...... 41 Synthesis ...... 41
APPENDIX A. SUPPLEMENTAL DATA FOR CHAPTER 2 ...... 44
APPENDIX B. SUPPLEMENTAL DATA FOR CHAPTER 4 ...... 46
LIST OF REFERENCES ...... 51
VITA ...... 69
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LIST OF TABLES
2.1. Mean water quality parameters collected between habitat types for each sampling month (±SE) ...... 9
2.2. Mean light intensity [LUX (±SD)] measurements between giant salvinia and submerged aquatic vegetation (SAV) habitat for all sampling months ...... 9
2.3. Multivariate generalized linear model results (deviation test statistic (Dev., p) of abundance examining taxa response to habitat and month ...... 12
2.4. Taxon scores for non-metric multidimensional scaling (NMDS) axes 1 and 2. Values indicate position along each axis ...... 14
3.1. Mean percent nitrogen and carbon (±SD) in salvinia tissue for the initial cover and nutrients, low (0), medium (3), and high (8 mg N L-1) treatments. Samples were collected initially (0), halfway (3) and at completion of the study (6 weeks) (n = 4) ...... 26
3.2. Linear mixed model and generalized linear mixed models estimates of mean values for dissolved oxygen (DO, mg/L), pH, specific conductance (µS), and light intensity (LUX) at 10 cm depth with, lower and upper 95% confidence limits (CL) among initial salvinia cover, 0, 5 and 20%, and nutrients, low (0), medium (3) and high (8 mg N L-1) ..... 26
4.1. Mean values (±SD) of dissolved oxygen (DO), pH, specific conductance (Cond), and temperature (Temp) in 0, 25, 50, or 100% salvinia cover in field mesocosms located in Baton Rouge, Louisiana ...... 35
4.2. Mean light intensity (lux) (±SD) measured in 0, 25, 50 or 100% salvinia coverages at various depths from mesocosms located in Baton Rouge, Louisiana ...... 36
4.3. Multivariate generalized linear model results (deviation test statistic, p-value) of insect abundance examining taxa response to salvinia cover and month ...... 37
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LIST OF FIGURES
2.1. Sampling sites containing giant salvinia and submerged aquatic vegetation (SAV) in Cameron Parish, Louisiana ...... 6
2.2. Mean abundance of macroinvertebrates per gram of dry mass (±SE) in giant salvinia (salvinia) and submerged aquatic vegetation (SAV) habitat over four sampling months. Only taxa with ≥ 5% relative abundance were labeled with percent ...... 11
2.3. Nonmetric multidimensional scaling (NMDS) ordination plot of macroinvertebrate communities in giant salvinia and submerged aquatic vegetation (SAV) habitat. Color depicts habitat types, giant salvinia (black) and submerged aquatic vegetation [SAV; (gray)], and shapes identify sampling month, August (circle), December (square), February (triangle), and May (diamond) ...... 14
2.4. Redundancy analysis (RDA) biplot of macroinvertebrate communities and environmental variables sampled. Points represent sampling sites and arrows represent environmental gradients. Color depicts habitat types, giant salvinia (black) and submerged aquatic vegetation [SAV; (gray)], and shapes identify sampling month, August (circle), December (square), February (triangle), and May (diamond). Environmental variables include dry biomass, dissolved oxygen (DO), pH, specific conductance, nitrate (NO3), ammonium (NH4), orthophosphate (P-ortho), and light availability at 0.01 m depth (below) ...... 15
3.1. Coontail biomass change over time for 0, 5, and 20% initial giant salvinia cover, and low (0), medium (3) and high (8 mg N L-1) nutrient treatments. Blue line represents mean dry biomass change and grey line represents line of best fit for the study duration. Initial coontail biomass before implementing treatments was 5.12 g [±0.91(±SD)]. Line of best fit equation was added for each treatment (y = mx + b) ...... 23
3.2. Weekly sampling of giant salvinia percent cover (A), dissolved oxygen (B), pH (C), and specific conductance (D) in mesocosms. Three initial salvinia cover, 0 (blue), 5 (red), and 20% (grey), and three nutrients, [low (0), medium (3), and high (8 mg N L-1], treatments. Samples of water quality at week zero were recorded immediately before salvinia and nutrient treatments were implemented. Lines represent mean values, ±95% confidence intervals ...... 25
3.3. Mean light intensity (lux), ±95% confidence intervals, over the duration of the study for the low (0), medium (3), and high (8 mg L-1 N) nutrient treatments and the three initial salvinia coverages (0, 5, and 20%). Light intensity was measured directly above the water surface then below surface at 1, 10, 20 cm, and mesocosm bottom (~26 cm). Exponential growth and decay equation (y = ae±kt) of mean light intensity through the water column was added for each treatment...... 27
4.1. Nonmetric multidimensional scaling (NMDS) ordination plot of aquatic insect assemblage similarity collected from salvinia coverages from outdoor mesocosms
v located in Baton Rouge, Louisiana. Points are individual samples and distance between points represents assemblage similarity with most similar samples being located closest together. Colors reflect percent salvinia cover treatments 0% (black), 25% (blue) 50% (green) and 100% (red). Circles represent 95% confidence interval around the centroid for salvinia cover groups, and a line connects sites furthest from the centroid within a group. Analysis of deviance (ADONIS) identified significant differences in community similarity (ADONIS F = 3.48, R2 = 0.11, p < 0.01), identifying three different communities, 0, 25-50, and 100% community groups ...... 38
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ABSTRACT
Aquatic invertebrates are important to the function freshwater marshes. They are vital to the transfer of energy from primary producers and organic matter to higher trophic levels. The structure of macroinvertebrate communities is directly associated with aquatic macrophyte diversity and abundance. Submerged macrophytes produce oxygen, are a food source, and provide physical habitat, which allows numerous aquatic organisms to exist. Introduction of the invasive free-floating aquatic fern giant salvinia, Salvinia molesta Mitchell, poses a risk to freshwater ecosystems through limited light penetration, decreased submerged macrophyte abundance, altered water quality and, changes in macroinvertebrate community structure and energy transfer. The objective of this dissertation was to understand the impacts of giant salvinia on freshwater structure, specifically the impacts to environmental conditions, native submerged macrophytes, macroinvertebrates and communities, including effect on aerial colonization. Field surveys revealed that giant salvinia affected environmental conditions through decreased light availability, dissolved oxygen, and habitat complexity, and increased concentration of orthophosphate and ammonium. These alterations changed macroinvertebrate community structure, relative to native submerged macrophytes, resulting in decreased macroinvertebrate richness and abundance. Total energy of the macroinvertebrate communities in giant salvinia infestations was greatly reduced, potentially resulting in a loss of transferable energy to adjacent trophic levels. A greenhouse study found that nutrient additions to the water accelerated the negative impact of giant salvinia on environmental conditions and submerged macrophyte biomass. While biomass decreased, the submerged macrophyte was able to tolerate the low light conditions under a full giant salvinia mat for three weeks. Finally, an outdoor mesocosm study showed that a full mat of giant salvinia disrupted the aquatic insect life cycle by limiting aerial colonization of aquatic insects, leading to communities with lower abundance and richness relative to native macrophyte. The inability to complete their lifecycle means individuals cannot replenish themselves, leading to diminished species pool and reduced energy potential. This research exhibited new, unstudied impacts from giant salvinia to ecosystem structure in freshwater marshes. Together these findings demonstrate larger disruptions to freshwater marshes from giant salvinia than previously reported, including large disruptions to the flow and transfer of energy within the aquatic ecosystem.
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CHAPTER 1. GENERAL INTRODUCTION
Background
Freshwater marshes are critical habitats that provide ecosystem services (Costanza et al. 1997, Engelhardt and Ritchie 2001, Fisher et al. 2008, Davidson et al. 2019) including, flood mitigation (Watson et al. 2016, Pattison-Williams et al. 2018), removal of pollutants and nutrients (Vymazal 2007, Vaughn 2018), carbon sequestration (Hopkinson 2012, Hinson et al. 2017), and recreational and cultural activities (Boucek and Rehage 2015, Vargas-Lopez et al. 2020). Southern Louisiana marshes offer habitat for numerous migratory birds and fish that annually generates millions for dollars for the state economy through fishing, hunting, observation and photography (Wainger et al 2018). Freshwater marshes are inherently productive systems and support large biomasses of primary producers (such as phytoplankton, periphyton, and submerged macrophytes) and organic matter comprise the base of the food web (Vadeboncoeur and Steinman 2002, Zhou et al. 2016). Primary producers release oxygen as a biproduct of photosynthesis, allowing numerous aquatic organisms to thrive (Caraco et al. 2006, Vilas et al. 2017). Submerged macrophytes also provide habitat for many species of invertebrates and fish (Castellanos and Rozas 2001), and their complex surface architecture offers macroinvertebrates protection from predators (Cheruvelil et al. 2002, Fisher and Kelso 2007). Additionally, leaf surfaces provide substrate for periphyton colonization and traps organic matter, both of which are resources for macroinvertebrates (Ferreiro et al. 2013, Hao et al. 2017, Hilt et al. 2018). This habitat can support a high abundance and diversity of invertebrates, which offers a prey source for small bodied and young fish (Mason 2002), and in turn attracts larger bodied predatory fish. Macroinvertebrates are important to the transfer of energy through the marsh ecosystem. Different feeding strategies among taxa allow permits consumption of aquatic macrophytes, algae, detritus and particulate organic matter (Poff et al. 2006, Hoffman et al. 2008, Wolters et al. 2019). In turn, macroinvertebrates are preyed upon by other invertebrates, fish, and waterfowl, thus serving an important role in energy transfer by linking primary producers and organic matter to higher trophic levels (Covich et al. 1999, Jones and Sayer 2003, Hershey et al. 2010, Tapp and Webb 2015). Life history of some macroinvertebrate species includes a terrestrial adult phase where individuals exit the aquatic environment and disperse aerially (Verberk et al 2008). The purposes of this life history trait include reproduction and egg laying, colonization of new habitat, and escape from unfavorable conditions. Terrestrial species (e.g., birds, bats, lizards, and arthropods) prey upon adults after emergence, thus macroinvertebrates also distribute energy between the aquatic and terrestrial environments of the marsh ecosystem (Sabo and Power 2002, Salvarina et al. 2018, Twining et al. 2018, Chari et al. 2020). Introduction of invasive aquatic plants threatens the structure of freshwater marshes. Invasive free-floating aquatic plants can negatively affect native submerged macrophyte abundance and ecosystem function by reducing or eliminating light penetration into the water, depleting water nutrients (Rommens et al. 2003, van Gerven et al. 2015), limiting gas exchange through the water surface (Attermeyer et al. 2016), and impacting energy flow and nutrient cycling (Villamagna and Murphy 2010, Wang and Yan 2017). Additionally, decomposing submerged macrophyte and floating plant matter creates an anoxic environment, which can lead to loss of other flora and nutrient release from the sediment (Masifwa et al. 2004, Pinto and O’Farrell 2014), further perpetuating the infestation.
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Giant salvinia (Salvinia molesta) is a free-floating aquatic fern that has become problematic in freshwater environments globally. Native to Brazil, giant salvinia was first recorded outside of the native range in Sri Lanka in 1939 (Room 1990). Since then, giant salvinia has been reported worldwide (Luque et al. 2014, CABI 2019), and was first reported in the U.S. in 1995 (Jonhson 1995). It appeared in Louisiana in 1998, where it was discovered in Toledo Bend Reservoir, located on the Texas-Louisiana state line (McFarland et al. 2004). Presently, giant salvinia has been identified in every parish in Louisiana (Daniel Hill, Louisiana Dept. of Wildlife and Fisheries personal communication). The structure of the plant includes above water fronds, horizontal stems, and submerged rootlike modified fronds (Oliver 1993). Giant salvinia initially grows horizontally across the water surface, then forms vertical mats up to 0.5-1 m thick once the water surface is covered (Coetzee et al. 2020). Giant salvinia does not reproduce sexually, rather, the stems break easily, allowing propagules to colonize locations by wind or water current (Owens et al. 2004). Under favorable environmental conditions, floating mats can double its coverage in as few as 36 h and form thick mats in approximately 10 d (Johnson et al. 2010). Controlling giant salvinia is difficult and cost prohibitive. Modes of control include mechanical, physical, chemical and biological. The first three control modes are adequate for small, isolated invasions, but are cost prohibitive as giant salvinia becomes more problematic. Due to the ability of giant salvinia to form extensive mats in lakes, ponds, reservoirs, and bayous, it has negatively impacted Louisiana economically and environmentally. Alterations to macroinvertebrate communities, following giant salvinia invasion would be expected as the structure and function of the aquatic environment changes. Abundant and diverse submerged macrophyte habitat, spanning the water column, would be replaced by a homogeneous giant salvinia habitat along the water surface. The loss of habitat would increase competition, and the lack of hiding locations could alter predator-prey interactions, potentially changing the abundance and richness of the macroinvertebrate community (Calizza et al. 2017, de Silva and Henry 2020). The mat on the water surface could hinder macroinvertebrate adult emergence or aerial colonization, decreasing taxa abundance due to the inability to replenish themselves. With the importance of macroinvertebrate energy transfer to higher trophic levels, significant changes to species composition, abundance, and distribution could negatively impact higher trophic levels (Gawlik 2002, Toft et al. 2003, Schummer et al. 2008). Although consequences of giant salvinia invasion on light availability and water quality are well studied (Oliver 1993, Flores and Carson 2006, Tipping et al. 2008, Coetzee et al. 2020), information relating to the rate at which giant salvinia alters environmental conditions, including submerged macrophytes, and how this effects macroinvertebrate communities are less understood. Given the central role of macroinvertebrate production in freshwater marshes trophic structure, a better understanding of how these communities are impacted by giant salvinia invasion is necessary. The focus of this research was an assessment of the overall impacts of giant salvinia infestation on the structure and function of freshwater marshes, specifically its effects on environmental quality, a resident macrophyte, and macroinvertebrate community structure and potential energy content. In tropical and subtropical climates, successful control of giant salvinia has been achieved with the salvinia weevil (Cyrtobagous salviniae Calder and Sands) (Room et al. 1981, Tipping et al. 2008, Martin et al. 2018). The salvinia weevil is a specialist feeder of giant salvinia, requiring the plant to complete its life cycle (Sands et al. 1983). Larvae will burrow into the stem of the plant to feed, which damages the plant by limiting growth, ultimately causing the mat to sink (Sands et al. 1983). The salvinia weevil was first introduced to Louisiana in 2001 and has
2 successfully established in the subtropical (southern) part of the state (Flores and Carlson 2006, Mukherjee et al. 2017, Tipping and Center 2003).
Specific objectives for each chapter are listed below.
Chapter 2. Invasion of giant salvinia alters freshwater macroinvertebrate community structure with implications for bottom-up processes.
Objectives. 1) Examine how giant salvinia affected environmental conditions, 2) test whether giant salvinia caused a shift in macroinvertebrate community structure, relative to native submerged macrophytes, and 3) determine whether the potential shift modified total energy of the macroinvertebrate community.
Chapter 3. Nutrients enhance the negative impact of an invasive floating plant on water quality and a submerged macrophyte
Objectives. 1) Determine how salvinia affected water quality, light availability, and submerged macrophyte biomass following introduction; and 2) determine how nutrients affect the rate of salvinia growth, changes to water quality, and effects to submerged macrophyte biomass.
Chapter 4. Invasive floating fern limits aerial colonization and alters community structure of aquatic insects
Objectives. 1) Determine how giant salvinia cover affected aquatic insect aerial colonization, and 2) how it affected insect community structure.
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CHAPTER 2. INVASION OF FREE-FLOATING FERN ALTERS FRESHWATER MACROINVERTEBRATE COMMUNITY STRUCTURE WITH IMPLICATIONS FOR BOTTOM-UP
Introduction
Freshwater marshes occur worldwide, comprising 1.9% of land area globally (Lehner and Doll, 2004) and are of conservation concern (Finlayson 2016). The introduction of non- indigenous aquatic plants impacts environmental conditions and the state of the ecosystem in freshwater marshes. Invasive free-floating aquatic plants can negatively affect native submerged aquatic vegetation (hereafter referred as SAV) abundance and ecosystem function by reducing light penetration into the water column, depletion of nutrients (Rommens et al. 2003), gas exchange limitations (Attermeyer et al. 2016), and alteration of nutrient cycling (Wang and Yan 2017). Giant salvinia (Salvinia molesta Mitchell; Salviniaceae) is a free-floating aquatic fern native to Brazil that has become problematic globally. Giant salvinia was first observed outside its native Brazilian range in 1939 and has been identified in 61 countries (Luque et al. 2014, CABI 2019). Giant salvinia has a rapid growth rate, doubling its biomass in 36-53 h (Cary and Weerts 1983, Johnson et al. 2010), and covers the entire water surface in days (Mitchell and Tur 1975). Thus, giant salvinia is considered highly disruptive and difficult to manage in freshwater habitats (Hill et al. 2020). Coastal freshwater marshes provide habitat for numerous species (Engle 2011) and ecosystem services, including flood mitigation (Pattison-Williams et al. 2018), removal of pollutants and excess nutrients (Vymazal 2007), and recreational and cultural activities (Boucek and Rehage 2015, Vargas-Lopez et al. 2020). Submerged aquatic vegetation is important in marsh structure and function influencing water quality (Caraco et al. 2006) and nutrient cycling (Ferreira et al. 2018). The structural compounds in SAV are slow to breakdown, trapping carbon in the sediment and acting as a carbon sink (Hinson et al. 2017). In freshwater systems, SAV provides habitat and food resources for waterfowl (Wilson et al. 2002), macroinvertebrates and fish (Fisher et al. 2012, Schultz and Dibble 2012). A rich diversity of SAV increases habitat complexity, offering refuge to a high number of species (Cheruvelil et al. 2002). This habitat can support a high abundance and diversity of invertebrates, which offers a prey source for small bodied and young fish (Schultz and Dibble 2012) and attracts larger bodied predatory fish. The loss of SAV would decrease habitat abundance and complexity, altering species interactions and modifying the macroinvertebrate community. Macroinvertebrates are critical to the function of the marsh and serve as a link between primary production and the rest of the trophic web (Covich et al. 1999, Jones and Sayer 2003). Disturbance events, such as the introduction of an invasive species, can alter environmental conditions and habitat complexity. Changes to habitat and environmental conditions of the aquatic ecosystem would select tolerant taxa and modify species interactions, such as competition and predator-prey relationships, potentially resulting in shifts in macroinvertebrate community structure, and productivity. Therefore, an altered macroinvertebrate community could be detrimental for the aquatic ecosystem, yet it has not been studied after the introduction of floating invasive plants within coastal freshwater marshes. The objective of this study is to 1) examine how giant salvinia affects environmental conditions, 2) to test whether a shift in macroinvertebrate community structure occurs and determine if the shift modified total energy of the macroinvertebrate community. Air breathing and low dissolved oxygen tolerant insects are
4 common in warm aquatic systems, especially in this region (Colon-Gaud et al. 2004, Kaller and Kelso 2007, Justus et al. 2012, Kang and King 2013, Parys et al. 2013), therefore, it is expected that the differences in physical structure and water chemistry to be more important, similar to Colon-Gaud et al. (2004), Fisher and Kelso (2007), and de Silva and Henry (2020). Thus, it is hypothesized macroinvertebrate communities in giant salvinia would support a diverse and abundant macroinvertebrate community; however, dominant taxa could be different in giant salvinia relative to SAV.
Methods
Field location
Surveys were conducted in a subtropical, coastal, freshwater marsh located in Cameron Parish (county), Louisiana, USA. This region is classified as a subtropical ecoregion, supporting both temperate and tropical organisms. The study site (29.859628, -92.956331; ~22,300 ha) is privately owned and predominantly used for waterfowl hunting and recreational fishing. Giant salvinia was first reported in 2000 and has since persisted in the environment, requiring continued chemical and biological control efforts. Native SAV, such as Ceratophyllum demersum L. (coontail), Cabomba caroliniana A. Gray (fanwort), and Ruppia maritima L. (widgeongrass) are common in the marsh, and locations with one or more of these SAV species were used for reference sampling (Figure 2.1), with C. caroliniana being the predominant SAV sampled. Based on monitoring by the landowner (Chad Courville and Darren Richard, Miami Corporation, personal communication) and myself over previous years, all sampling locations were dominated by SAV prior to the study. Cold temperatures during the winter of 2017-2018 reduced the occurrence giant salvinia from the area and effectively shifted the aquatic environment to SAV dominant habitat. Sampling commenced in August 2018, immediately following giant salvinia establishment and on three further occasions until May 2019, due to control efforts.
Environmental and plant quality variables
Physical and chemical variables were measured at each sampling location. Dissolved oxygen (DO), specific conductance (µS), pH, temperature, and ammonium (NH4) were sampled with a handheld multiprobe (Pro-DS5, YSI Incorporated, Yellow Springs, OH, USA). Water samples were collected in sterile polyethylene containers for chlorophyll-a, phosphorous (orthophosphate, P-ortho) and nitrogen (nitrate, NO3, and nitrite, NO2) analyses. Samples were kept on ice during transport and refrigerated (4°C) after returning to the laboratory on Louisiana State University campus in Baton Rouge, Louisiana. Phosphorus, nitrate and nitrite were analyzed by Hach Method 8048 (United States Environmental Protection Agency Approved), Hach Method 8192 (Cadmium Reduction Method), and Hach Method 8507 (US EPA Approved), respectively, using a spectrophotometer (DR/2500, Hach Company, Inc., Loveland, CO, USA). Five hundred mL of water was filtered using glass fiber filters, and chlorophyll-a was measured by US EPA Method 445.0 (Arar and Collins 1997) using a fluorometer (TD 700, Turner Designs, Inc., San Jose, CA).
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Figure 2.1. Sampling sites containing giant salvinia and submerged aquatic vegetation (SAV) in Cameron Parish, Louisiana.
Light intensity was sampled directly above the water surface, directly below the water surface (0.01 m), at 0.10 and 0.20 m, then in 0.20 m increments until the bottom using a MW700 light meter (Milwaukee Instruments, Rocky Mount, NC, USA). Giant salvinia mat thickness was determined as the distance between the top and bottom of the mat using a homemade plastic tray (0.30 × 0.40 × 0.01 m, L × W × H). The tray was slid through the giant salvinia vertically, once through, the tray was turned horizontally against the bottom of the mat, thickness was determined with a rope, marked in 0.01 m increments, attached to the middle of the tray. Submerged frond (root) length was recorded for 10 randomly selected giant salvinia plants.
Macroinvertebrate and Plant Biomass Sampling
Three giant salvinia infested locations and three native SAV dominant locations were sampled quarterly over nine months (Figure 2.1). At each location, three samples were collected for a total of 72 samples during the study period (72 samples = 2 macrophyte types × 3 locations × 4 quarters × 3 samples). Two samplers were used because macroinvertebrates in SAV are typically stratified vertically throughout the plant bed, whereas when giant salvinia invades, macroinvertebrates orient horizontally to the floating plants. For SAV, a homemade suitcase
6 sampler was used consisting of two 0.65 × 0.45 m hinged panels covered with 0.600 mm mesh. The panels were connected using a hinge and four attached rings, with rope running through, which standardized the width the sampler to open up to 0.55 m. The sampling area was triangular prism shaped (0.65 × 0.65 × 0.55 × 0.45 m) that enclosed a volume of 0.07 m3 (Colon-Gaud and Kelso 2003). Sampling was done by wading to undisturbed SAV beds followed by lowering the suitcase sampler into the bed. Once in place, the trap would be closed and secured shut with latches. Vegetation sticking out of the edges of the sampler was trimmed and discarded. Giant salvinia was sampled using a 0.500 mm mesh lift net (0.29 × 0.35 × 0.20 m; 0.02 m3 volume; Kaller et al. 2013). Samples were collected from the giant salvinia mat by wading to undisturbed areas. During sampling, the lift trap was placed through the giant salvinia mat with top edge first, and quickly scooped under the mat and lifted out of the water. Giant salvinia was mature and in the tertiary growth stage for all sites during the study. Material from the samplers were stored in re-sealable plastic bags with water and placed in the iced cooler until processing. Samples were processed in the laboratory following collection. Samples were processed by flushing and rinsing plant material in 75 L plastic bin filled with water. Plant matter removed from the bin was dried in an oven for 72 h at 65°C to obtain dry mass. Macroinvertebrates were rinsed from plant material and captured on a 0.500 mm sieve then enumerated and identified to lowest taxonomic level, usually genus (Merritt and Cummins 1996).
Caloric value
Caloric values from published data were calculated to determine potential energy of the macroinvertebrate community (Welsh 1975, Fredrickson and Reid 1988, Foley 2015). Only macroinvertebrates with published caloric values were used in the analysis. To quantify calorific value, taxa counts per gram dry biomass were multiplied by the estimated value of each taxa, then the value for all taxa in the sample were summed.
Statistical Analysis
Analyses first examined water quality and plant characteristics differences among months and habitats. Next, multivariate and community analyses examined invertebrate response among habitats and monthly assessments. Finally, multivariate analyses related invertebrate responses to specific water quality and plant variables. Analyses were conducted using R statistical software version 3.4.4 (R Core Team 2019). Generalized linear models (GLM) compared water quality and plant variables among habitats and months. For all variables, the selected combination of link and distribution was determined by comparing candidates and fit statistics. A log link, Gaussian distribution GLM was used for temperature. Log link, gamma distribution GLMs were used for DO, pH, P-ortho, chlorophyll-a, NH4, and plant biomass. Inverse link, gamma distribution GLMs were used for specific conductance, submerged frond length, and giant salvinia mat thickness. Logit link, binomial distribution GLMs were used for NO3 and NO2. Log link, gamma distribution GLM was used for light availability at 0.01 m depth. For macroinvertebrate analysis, taxa were removed that had a total abundance of less than four individuals collected during the study. For comparability, species richness and abundance were standardized per gram of dry plant biomass. GLMs with log links and gamma distributions were used to examine abundance and richness between habitats and among sampling dates. Log
7 link, gamma distribution GLM was used for caloric value difference between habitat and month. A multivariate generalized linear model (MGLM), with a negative binomial distribution and log link, was used to test for differences in macroinvertebrate community between habitats and among sampling dates (package mvabund; Warton et al. 2012). The model was adjusted for multiple comparisons using a step-down resampling procedure. Nonmetric multidimensional scaling (NMDS) of a Bray-Curtis similarity matrix of taxa (k = 4) was used to visualize the similarity between habitat types and among months (Clarke 1993). Comparisons of exploratory ordinations (e.g., principal component analysis and detrended correspondence analysis) indicated that NMDS would be the appropriate analysis (package vegan, Oksanen et al. 2019). Analysis of variance using distance matrices (ADONIS) was used to test the solution from NMDS analysis (package Vegan, Oksanen et al. 2019). Multivariate dispersion test showed that giant salvinia (0.13) and SAV (0.12) were similar in multivariate distance, thus the analysis was appropriate for these data (Anderson and Walsh 2013). Association with habitat (Ordiselect, package Vegan, Oksanen et al. 2019) and community dissimilarity between habitats (similarity percentage, SIMPER, package Vegan, Oksanen et al. 2019) were also examined. A redundancy analysis (RDA) examined how variation in macroinvertebrate community composition was explained by environmental gradients described by water quality variables and plant characteristics, following comparisons to find the method most appropriate to the data (package Vegan, Oksanen et al. 2019). Variables selected for the RDA were initially screened by linear discriminant analysis (LDA), for appropriateness for RDA, and MGLM, described previously, to indicate which environmental variables significantly varied with habitat and month (LDA, package MASS, Chang 2015), and these variables were used in the RDA.
Results
Environmental variables and plant quality
Water quality measurements showed variation between habitat and among months (Table 2.1). Dissolved oxygen (t-value = 4.74, p < 0.01) and pH (t-value = 4.56, p < 0.01) were reduced in giant salvinia. Dissolved oxygen was 2.48-times higher in SAV sites [5.57 mg L-1 (±3.12; n = 12)] compared with giant salvinia sites (2.24 mg L-1 [±2.59 (±SD); n = 12]). pH at sites with SAV was 1.08-times higher [6.48 (±0.32; n = 12)] relative to sites with giant salvinia [6.97 (±0.30; n = 12)]. Specific conductance (t-value = 2.73, p = 0.01), P-Ortho (t-value = -5.62, p < 0.01), and NH4 (t-value = -4.51, p < 0.01) were elevated in giant salvinia sites, relative to SAV sites. Specific conductance was 1.56-times higher in giant salvinia sites [1,493 µS (±1,445; n = 12)] relative to SAV sites [955 µS (±597; n = 12)], phosphate was 4.84-times higher in giant salvinia sites [0.28 mg L-1 (±0.34; n = 12)] compared to SAV sites [0.06 mg L-1 (±0.04; n = 12)], and NH4 was 3.31-times higher in giant salvinia sites [0.12 mg L-1 (±0.10; n = 12)] relative to SAV sites [0.04 mg L-1 (±0.03; n = 12)]. Dry biomass was 2.98-times higher in giant salvinia sites [31.70 g (±10.36; n=36)] compared with SAV sites [10.65 g (±6.39; n=36); t-value = -9.42, p < 0.01]. Mean submerged root length was 0.13 m ±0.04; n = 120) and mean mat thickness was 0.6 m (±0.02; n = 12), neither significantly varied among sampling months. In the SAV, light availability declined gradually with light reaching the bottom of the waterbody (Table 2.2). However, when giant salvinia was present, light availability steeply
8 declined and was 7.7-times lower immediately below the water surface in giant salvinia [4,664 lux (±7,989; n = 12), compared to SAV [36,250 lux (±18,773; n = 12; t-value = 41.68, p < 0.01).
Table 2.1. Mean water quality parameters collected between habitat types for each sampling month (±SE). Habitat Month Temperature °C DO (mg L-1) Specific pH conductance (µS) Salvinia August 27.1 (±0.1) 0.26 (±0.04) 3,529 (±488) 6.74 (±0.11) SAV August 26.9 (±0.1) 1.76 (±0.05) 1,922 (±2) 7.17 (±0.02) Salvinia December 12.2 (±0.4) 4.68 (±1.18) 912 (±125) 6.58 (±0.01) SAV December 11.4 (±0.1) 9.03 (±0.05) 634 (±34) 7.08 (±0.04) Salvinia February 13.2 (±0.1) 2.55 (±0.50) 814 (±46) 6.45 (±0.05) SAV February 13.6 (±0.1) 6.43 (±0.65) 703 (±37) 6.83 (±0.12) Salvinia May 22.5 (±0.1) 1.45 (±0.33) 717 (±81) 6.15 (±0.05) SAV May 24.0 (±0.2) 5.05 (±0.77) 560 (±62) 6.81 (±0.14) Note: Parameters in bold were significantly different between giant salvinia and submerged aquatic vegetation (SAV) habitats (table cont’d.)
-1 -1 -1 -1 -1 NO3 (mg L ) NO2 (mg L ) P-ortho (mg L ) Chl-a (ug L ) NH4 (mg L ) 0.000 (±0.000) 0.000 (±0.000) 0.62 (±0.18) 5.09 (±0.12) 0.23 (±0.05) 0.023 (±0.002) 0.006 (±0.002) 0.07 (±0.02) 19.70 (±2.52) 0.03 (±0.01) 0.006 (±0.002) 0.001 (±0.001) 0.24 (±0.00) 7.68 (±1.08) 0.10 (±0.02) 0.010 (±0.003) 0.003 (±0.001) 0.07 (±0.01) 10.40 (±2.58) 0.05 (±0.01) 0.016 (±0.004) 0.003 (±0.002) 0.13 (±0.04) 14.20 (±3.70) 0.10 (±0.01) 0.010 (±0.000) 0.000 (±0.000) 0.07 (±0.01) 4.44 (±0.19) 0.05 (±0.01) 0.010 (±0.000) 0.003 (±0.000) 0.12 (±0.01) 3.73 (±0.45) 0.06 (±0.00) 0.016 (±0.002) 0.003 (±0.001) 0.01 (±0.00) 13.80 (±3.25) 0.01 (±0.00)
Table 2.2. Mean light intensity [LUX (±SD)] measurements between giant salvinia and submerged aquatic vegetation (SAV) habitat for all sampling months. Depth Giant Salvinia SAV Surface 49,082 (±28,392) 54,642 (±28,086) 1 cm 4,664 (±7,989) 36,250 (±18,773) 10 cm 32 (±35.70) 23,624 (±13,528) 20 cm 3 (±2.93) 14,808 (±10,410) 40 cm 1 (±2.61) 3,497 (±4,050) 60 cm 1 (±1.73) 763 (±856) Note: Light measurements were recorded immediately above the water surface then at different depths through the water column.
Macroinvertebrate community
A total of 22,812 macroinvertebrate specimens (12,412 from SAV and 10,400 from giant salvinia), in 50 lowest practical taxonomic units (LPTs) and 27 families within 12 orders, were identified (Table A.1). Fifteen of 50 LPTs occurred less than four times, thus were removed prior to analysis. Standardized macroinvertebrate abundance per gram was 3.23-times greater in SAV
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[34.35 (±22.61)] compared with in giant salvinia [10.64 (±7.57); t-value = 2.68, p = 0.01], and richness per gram was five-times greater in SAV [1.50 (±0.96)] than giant salvinia [0.30 (±0.14); t-value = 14.29, p < 0.01]. Following initial giant salvinia invasion, macroinvertebrate communities in giant salvinia and SAV were Chironomidae dominant in August (Figure 2.2). Subsequently, communities in giant salvinia became dominated by amphipods, specifically Hyalella sp. In giant salvinia, Chironomidae abundance decreased each month from a mean of 5.92 per gram [±2.92 (±SD)] in August to 0.5 per gram (±0.96) in May. Aside from these two groups, all other LPTs decreased from 24% of the giant salvinia community in August to 4% in December then < 9% in February and May (Figure 2.2). In SAV, the macroinvertebrate community was comprised of Chironomidae (42%), Hyalella (34%), and all other LPTs represented 24% of LPTs throughout the study. Habitat, month, and interaction between the two factors described macroinvertebrate LPT abundance. Significant differences in abundance were most explained by habitat (14 of 36 LPTs; Deviance = 370.6, p < 0.01) followed by month (10 of 36 LPTs; Deviance = 521.5, p < 0.01) and interaction (5 of 36 LPTs; Deviance = 223.1, p < 0.01; Table 2.3; Figure A.1). Of the 14 LPT differing between habitat, nine were more abundant in SAV. Macroinvertebrate community structure between habitats was different. Ordination of macroinvertebrate community composition found distinct groups between habitat types (Figure 2.3 and Table 2.4). Residual STRESS was 0.126, which is within ranges for interpretability (Clarke 1993). The first axis presumably explained community differences based on habitat type. The second axis presumably related to temporal changes within giant salvinia. Habitat (ADONIS F = 4.86, R2 = 0.061, p < 0.01) and month (ADONIS F = 2.58, R2 = 0.097, p = 0.01) explained variation in the macroinvertebrate communities. The dispersion test showed that giant salvinia (0.13) and SAV (0.12) were similar in multivariate distance, thus the analysis was appropriate for these data (Anderson and Walsh 2013). Habitat association analyses identified Gammarus sp., Collembola, Scirtes sp., and Dolichopodidae as most related to giant salvinia ordination group, while Neocorixa sp., Hydrachnidia, Parapoynx sp., and Oxyethira sp. as most related to SAV ordination group (Table 2.4). Similarity percentages (SIMPER) identified 61.4% dissimilarity in community composition between habitat, with Chironomidae and Hyalella sp. as contributing the most to community turnover between habitat type. Previous analyses indicated dry biomass, DO, specific conductance, pH, NO3, P-ortho, NH4, and light availability at all depths significantly varied between habitat and, thus, were included in the RDA. Only one depth (0.01 m) of light availability was selected for the analysis. The first two axes of the ordination explained 87% of the variation (68% in 1st axis). Monte Carlo permutation test indicated axis one (F = 42.01, p < 0.01) and axis two (F = 11.43, p < 0.01) were significant. The first axis was positively correlated with Chironomidae dominant communities (0.727), as well as, pH (0.716), light availability (0.608), and specific conductance (0.519), and negatively correlated with amphipod communities (-0.805) and dry biomass (- 0.659). The second axis was positively correlated with dry biomass (0.534) was negatively correlated with DO (-0.828), pH (-0.262) and light availability (-0.386). A biplot of the first two axes showed increased dry biomass was associated with giant salvinia habitat, while pH and light availability increased with SAV habitat (Figure 2.4).
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Figure 2.2. Mean abundance of macroinvertebrates per gram of dry mass (±SE) in giant salvinia (salvinia) and submerged aquatic vegetation (SAV) habitat over four sampling months. Only taxa with ≥ 5% relative abundance were labeled with percent.
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Table 2.3. Multivariate generalized linear model results (deviation test statistic (Dev., p) of abundance examining taxa response to habitat and month. Habitat Month Habitat x Month Order Taxon Dev. p Dev. p Dev. p Amphipoda Hyalellidae Hyalella 0.846 0.929 16.570 0.032 10.864 0.166 Amphipoda Gammaridae Gammarus 4.952 0.497 13.259 0.107 18.530 0.005 Coleoptera Chrysomelidae Donacia 3.176 0.687 8.615 0.372 0.450 0.961 Coleoptera Dytiscidae Brachyvatus 1.927 0.826 7.133 0.431 1.185 0.961 Dytiscus 1.046 0.929 6.592 0.492 0.680 0.961 Hydroporus 2.863 0.706 6.147 0.542 0.001 0.961 Coleoptera Hydrophilidae Berosus 1.003 0.929 19.108 0.011 7.384 0.397 Laccobius 0.226 0.929 14.841 0.071 0.000 0.961 Tropisternus 5.920 0.349 21.944 0.005 11.046 0.163 Coleoptera Noteridae Hydrocanthus 20.238 0.001 9.588 0.365 1.342 0.961 Coleoptera Scirtidae Scirtes 17.777 0.002 13.665 0.097 8.701 0.348 Collembola Collembola 13.590 0.008 12.455 0.142 1.105 0.961 Diptera Ceratopogonidae Dasyhelea 4.170 0.541 13.316 0.105 6.545 0.488 Probezzia 5.575 0.428 7.869 0.431 1.659 0.961 Diptera Chironomidae 2.985 0.687 4.643 0.723 30.547 0.001 Diptera Culicidae 0.000 0.929 8.815 0.365 0.000 0.975 Diptera Dolichopodidae 3.595 0.659 7.711 0.431 5.886 0.520 Ephemeroptera Baetidae Fallceon 13.558 0.008 2.630 0.911 4.082 0.790 Ephemeroptera Caenidae Brachycercus 0.621 0.929 27.165 0.002 33.120 0.001 Hemiptera Corixidae Neocorixa 59.334 0.001 29.882 0.002 2.095 0.961 Hemiptera Hebridae Hebrus 5.059 0.497 9.228 0.365 6.632 0.488 Hemiptera Naucoridae Pelocoris 21.059 0.001 1.145 0.094 2.306 0.709 Isopoda Asellidae Caecidotea 4.479 0.497 9.564 0.365 2.308 0.961 Isopoda Sphaeromatidae Sphaeroma 2.589 0.791 10.918 0.245 1.378 0.961 Lepidoptera Crambidae Note: Underlined taxon indicates associated with giant salvinia habitat and bold indicates submerged aquatic vegetation. (table cont’d.)
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Habitat Month Habitat x Month Order Taxa Dev. p Dev. p Dev. P Parapoynx 12.279 0.012 20.925 0.007 0.001 0.961 Odonata Aeshnidae
Anax 8.318 0.139 4.498 0.723 0.000 0.961 Odonata Coenagrionidae Coenagion 18.038 0.001 8.716 0.372 16.724 0.010 Enallagma 20.373 0.001 1.145 0.911 2.306 0.961 Odonata Libellulidae Erythemis 11.315 0.023 64.077 0.001 8.836 0.348 Macrothemis 5.462 0.458 21.139 0.006 2.329 0.961 Sympetrum 1.731 0.837 37.262 0.001 16.256 0.015 Trichoptera Hydroptilidae Orthotrichia 12.169 0.013 9.677 0.365 0.000 0.961 Oxyethira 5.75 0.410 12.448 0.142 0.001 0.961 Trichoptera Polycentropodidae Polycentropus 21.557 0.001 9.723 0.365 0.000 0.961 Decapoda Palaemonidae Palaemonetes 25.570 0.001 34.044 0.001 7.681 0.393 Trombidiformes Hydrachnidia 30.830 0.001 2.193 0.911 8.592 0.348
Caloric value
Based on eighteen taxa (96% relative abundance; Table A.1) with previously published calorific values, mean caloric value [kcal g-1 per gram dry biomass (±SD)] in SAV was 3.39- times higher [146 (±92.2); t-value = -2.31, p = 0.02] than giant salvinia [43.1 (±31.2)]. In giant salvinia, mean caloric value ranged from 25.6-58 kcal g-1 across months, with only May being significantly lower (t-value = 2.2, p = 0.03). Mean values were 53.8 (±17.9) and 58 (±43.6) kcal g-1 for August and December, respectively, and 35.2 (±21.8) kcal g-1 in February, then decreased to 25.6 (±20.9) kcal g-1 in May. In SAV, mean caloric value across months ranged from 103-220 kcal g-1, with February being significantly higher (t-value = -2.2, p = 0.03). Caloric value was 119 (±69.3) kcal g-1 in August then 103 (±81.3) December. Caloric value increased to 220 (±112) kcal g-1 in February then was 144 (±42) kcal g-1 in May.
Discussion
This study provides evidence that giant salvinia invasion altered habitat availability and environmental conditions, including light, DO, and nutrients, that rapidly impacted macroinvertebrate communities, resulting in differing communities arising from a common source in native SAV. The stated hypothesis that giant salvinia having a diverse and abundant community was not supported by the data. Initially, macroinvertebrate communities were similar between SAV and giant salvinia, however, over time, giant salvinia communities became species depauperate and lower in biomass and energy. In SAV, macroinvertebrate communities
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Figure 2.3. Nonmetric multidimensional scaling (NMDS) ordination plot of macroinvertebrate communities in giant salvinia and submerged aquatic vegetation (SAV) habitat. Color depicts habitat types, giant salvinia (black) and submerged aquatic vegetation [SAV; (gray)], and shapes identify sampling month, August (circle), December (square), February (triangle), and May (diamond).
Table 2.4. Taxon scores for non-metric multidimensional scaling (NMDS) axes 1 and 2. Values indicate position along each axis. Taxon NMDS1 NMDS2 Taxon NMDS1 NMDS2 Chironomidae 0.286054 0.128081 Donacia 0.108081 -3.752620 Erythemis -0.536790 0.037067 Neocorixa 1.084895 0.300097 Sympetrum 0.249393 0.059069 Scirtes -1.289930 -0.288360 Hyalella -0.182690 -0.070450 Hebrus -0.638390 -0.572350 Gammarus -1.147760 0.330857 Hydroporus 0.704335 -1.064640 Macrothemis 0.651199 0.536902 Polycentropus 0.895946 -0.047930 Brachycercus 0.500009 0.959916 Dasyhelea 0.529612 -0.692150 Fallceon 0.704653 0.021108 Brachyvatus 0.714588 -0.378950 Coenagion 0.612159 0.393508 Culicidae 0.194320 0.925443 Enallagma 0.723942 -0.363630 Orthotrichia 1.037998 1.194264 Pelocoris -0.882360 0.867227 Dytiscus -0.066980 1.773912 Note: Underlined taxon indicates associated with giant salvinia, bold indicates submerged aquatic vegetation, and neither indicates no significant habitat association. (table cont’d.)
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Taxon NMDS1 NMDS2 Taxon NMDS1 NMDS2 Laccobius 0.052827 0.724487 Probezzia 0.545861 0.567446 Collembola -1.132430 0.069116 Anax 0.806876 -0.35286 Palaemonetes 1.027967 0.550221 Dolichopodidae -1.106170 1.721349 Hydrachnidia 1.084711 0.549910 Sphaeroma 0.572078 0.616015 Berosus -0.612120 -0.388860 Caecidotea 0.687103 0.699057 Tropisternus 0.321635 -0.304570 Parapoynx 1.226561 0.915312 Hydrocanthus -0.960320 0.412645 Oxyethira 1.573787 1.382053
Figure 2.4. Redundancy analysis (RDA) biplot of macroinvertebrate communities and environmental variables sampled. Points represent sampling sites and arrows represent environmental gradients. Color depicts habitat types, giant salvinia (black) and submerged aquatic vegetation [SAV; (gray)], and shapes identify sampling month, August (circle), December (square), February (triangle), and May (diamond). Environmental variables include dry biomass, dissolved oxygen (DO), pH, specific conductance, nitrate (NO3), ammonium (NH4), orthophosphate (P-ortho), and light availability at 0.01 m depth (below). remained mostly insects, predominantly Chironomidae, which is expected for freshwater marshes (Bolduc and Afton 2003, Kang and King 2013, Mercer et al. 2017, Weller and Bossert 2017). In giant salvinia, conversely, crustaceans, specifically amphipods, dominated the community. This could be explained by environmental filtering and habitat changes resulting from giant salvinia invasion. Environmental conditions and presumably environmental filtering differed between SAV
15 and giant salvinia habitats. Decreased light penetration may have limited periphyton, phytoplankton, and zooplankton abundance, which although unmeasured, potentially limited functional traits that could exist in the new habitat (Pinto and O’Farrell 2014). Three of the four taxa identified as positively relating to SAV were an air breather (Neocorixa sp.) and two herbivores (Parapoynx sp., and Oxyethira sp.) (Poff et al. 2006). Giant salvinia may have limited access to the surface for air breathing insects. Although external gill breathing macroinvertebrates are typically more sensitive to low DO than air breathing macroinvertebrates (Kaller and Kelso 2007), a thin layer of higher DO exists at the giant salvinia mat and water surface interface (Frodge et al. 1990, Wahl et al. 2020), which may have permitted external gill breathing macroinvertebrates to exist within giant salvinia. In August, gill breathing macroinvertebrates were present when recorded DO was < 1 mg L-1. Taxa may have persisted by a layer of higher DO water near the water-giant salvinia interface, or as demonstrated in Kaller and Kelso (2007) and Justus et al. (2012), these macroinvertebrates may exhibit tolerance to low DO. Decreases in macroinvertebrate abundance and richness have been observed in other invasive free-floating macrophyte species. An increase in Lemna minuta Kunth (duckweed) mat thickness was negatively correlated with the number of aquatic plant species and plant coverage, as well as, a 40% decrease in macroinvertebrate richness (Ceschin et al. 2019). Even though L. minuta results a thinner surface mat, the effects to macroinvertebrates, and the resulting shift in communities, were similar to the effect observed when giant salvinia was present. Giant salvinia habitat may also fail to provide the spatial extent and diversity of habitat as SAV, with its more complex architecture (Fisher and Kelso 2007, Thomaz et al. 2008). The giant salvinia mat was limited to submerged and emergent fronds, and suspended giant salvinia detritus, and presented a homogenous habitat (i.e., monoculture) over the infested area. Conversely, SAV can span the entire water column, offering increased surface area for habitat and predator avoidance (Fisher and Kelso 2007), and increased habitat heterogeneity and species richness (Thomaz et al. 2008). Loss of habitat niches and spatial extent likely contributed to some taxonomic differences, possibly through increased competition (Calizza et al. 2017). The growing giant salvinia mat likely created internal nutrient loading that further reinforced the invasion through nutrient release from the sediment. Reduction in DO following giant salvinia invasion has been well documented (Oliver 1993, Flores and Carson 2006, Tipping et al. 2008) and can cause phosphorus and ammonium to release into the water column from the sediment (Søndergaard et al. 2003, Zhang et al. 2014), creating more favorable conditions to sustain the invasion (Strange et al. 2019). Eicchornia crassipes (Mart.) Solms (water hyacinth) tissue decomposition released phosphorus into the water column, with the concentration of release increasing when DO was < 1 mg L-1 (Masifwa et al. 2004); and in this study, locations with giant salvinia in August had a mean DO concentration <1 mg L-1 and the highest phosphorus and ammonium concentrations. Nutrient availability is a limiting factor for giant salvinia, but internal loading, caused by a reduction in DO and increase in nutrients, can reinforce giant salvinia invasion. Human intervention through chemical, mechanical, or biological control is typically required to shift back to SAV dominance (Tipping et al. 2008, Motitsoe et al. 2020). This transition back, however, is typically temporary with giant salvinia recolonizing within months after control (Oliver 1993). Peeters et al. (2016) found invasive free- floating plants had a higher probability of recolonizing a location which was previously controlled because of lingering phosphorus concentrations. If giant salvinia is reintroduced, via drift, boat, or wildlife, to a previously invaded area then nutrients may be adequate to initiate another invasion. Therefore, although anthropogenic control restored SAV dominance at this
16 site, the high likelihood of giant salvinia reestablishment in systems like this with altered nutrients could have long term impacts to local macroinvertebrate richness and diversity. Reoccurring invasion at a location could act as a sink for several macroinvertebrate taxa. Heterogenous SAV dominant habitat allows a greater richness of macroinvertebrates to exist (Thomaz and Cunha 2010, Lucena-Moya and Duggan 2011), and macroinvertebrates with adult flying stage will disperse from this habitat to colonize other locations (Wissinger 1999). If they colonize an area frequently during a time with little or low giant salvinia coverage, they may not be able to complete their life cycle before the environment shifts to dominance by giant salvinia. If they cannot develop before invasion, they would be subject to changes in environmental filtering and increased competition. Additionally, the mat of vegetation on the water surface may limit adult aquatic insect emergence or egg laying. If adult emergence is impacted, energy transfer from the aquatic to the terrestrial ecosystem, in the form of predation on emerging insect, would be diminished. The flow of energy though the aquatic and adjacent terrestrial ecosystems could be altered by giant salvinia. Previous research has identified giant salvinia energy flow alterations related to decreased light penetration (Rommens et al. 2003, McFarland et al. 2004). These results indicate a reduction in caloric value in the giant salvinia macroinvertebrate community, which could have bottom-up ramifications for the trophic web. Fish and other aquatic predators surviving in the low DO environment under giant salvinia would have lower quality and lower diversity of prey items. Toft et al. (2003) found invertebrate communities and fish diets were altered by the introduction of P. crassipes, shifting from the highly abundant native amphipod, Hyalella azteca Saussure, as fish prey to the amphipod, Crangonyx floridanus Bousfield, that was not consumed by fish. Chironomidae are a common forage item, especially for larval, juvenile, and smaller-bodied fish (Armitage 1995). Therefore, a shift away from Chironomidae dominant communities may hinder trophic interaction and energy transfer. Even when invasive plants are controlled, it may take weeks or years for macroinvertebrate communities to resemble pre-infested communities (Wallace 1990). Waterfowl, especially diving ducks, rely on macroinvertebrates during migration and in wintering habitat (Afton et al. 1991), often selecting habitat abundant with macroinvertebrates (Schummer et al. 2008). Similarly, many wading birds are indirectly dependent on macroinvertebrates, through fish consumption (Gawlik 2002). The reduction in total energy of the macroinvertebrate community could result in altered habitat use and decreased populations of waterfowl and wading birds. A collapse of overwintering diving duck populations is suspected to be caused, in part, by a decrease in macroinvertebrate abundance and total biomass (Tománková et al. 2013). Several species of wading birds have been shown to utilize habitat based on prey, fish availability, and decreased fish abundance, through loss of total energy from macroinvertebrates, could lead to reduced wading bird abundance (Gawlik 2002). Giant salvinia is not consumed as a food source by wildlife due to the high amount of lignin and tannins, which make it hard to digest (Moozhiyil and Pallauf 1986). Additionally, the low nutritional value and high water content would require herbivores to consume high amounts of the plant to meet energy demands. Since few species feed on the plant, the population of giant salvinia will expand unless control efforts are implemented, such as chemical and biological, or sever winter conditions reduce abundance.
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Conclusion
This study demonstrated that the invasion of giant salvinia reduced habitat availability and complexity through changes in environmental conditions that was evident in shifts in macroinvertebrate communities. Due to its widespread distribution and now verified reduction of biodiversity and energy transfer, invasion of giant salvinia could have larger implications for freshwater ecosystems than previously understood. Research is needed to understand how giant salvinia alters the flow of energy in aquatic ecosystems, specifically how adjacent trophic levels are impacted by alterations to their prey community and the timeframes for macroinvertebrate communities to recover.
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CHAPTER 3. NUTRIENTS ENHANCE THE NEGATIVE IMPACT OF AN INVASIVE FLOATING PLANT ON WATER QUALITY AND A SUBMERGED MACROPHYTE
Introduction
Submerged aquatic macrophytes have an important role in the structure of aquatic ecosystems. These plants offer valuable forage and habitat for many species of fish, invertebrates and water birds (Castellanos and Rozas 2001, Marco-Méndez et al. 2015, Zhou et al. 2020), and their diverse leaf arrangements increase habitat complexity, supporting a range of microhabitats for macroinvertebrates (Warfe and Barmuta 2006, Fisher and Kelso 2007, Fisher et al. 2012). The plant surface allows for periphyton colonization and traps organic matter, both providing resources for aquatic invertebrates (Ferreiro et al. 2013, Hao et al. 2017, Hilt et al. 2018). Waterfowl and wading birds utilize freshwater marshes and submerged macrophytes for foraging, consuming roots, shoots, and seeds from submerged macrophytes, as well as invertebrates living on the plant surface (Tapp and Webb 2015, Stafford et al. 2016, Marco- Méndez et al. 2020). Fish rely on submerged macrophytes during different stages of their life cycle, utilizing the plants to evade predators and to forage for prey (Grenouillet and Pont 2001, Stahr and Shoup 2016). In addition to supporting fauna, submerged macrophytes directly modify the chemistry of the water column by releasing oxygen as a biproduct of photosynthesis, supporting numerous aquatic organisms (Caraco et al. 2006, Vilas et al. 2017). Submerged macrophytes assist in nutrient cycling by up taking and releasing organic elements from the sediment. Freshwater marshes dominated by aquatic macrophytes act as a carbon sink, sequestering atmospheric carbon in the sediment (Hopkinson et al. 2012, Pattison-Williams et al. 2018, Villa and Bernal 2018). Thus, submerged macrophytes are an important resource and habitat in freshwater marshes, therefore altering their communities can be consequential for the ecosystem. The colonization of non-indigenous free-floating plants has negative implications for submerged macrophytes and aquatic ecosystem processes. Free-floating macrophytes create a mat of vegetation on the water surface, limiting light availability under the mat, leading to a reduction of submerged macrophytes (van Gerven et al. 2015, Coetzee and Hill 2020). Successful free-floating invasive macrophytes typically have a high rate of growth, allowing them to quickly reproduce and cover water surface when conditions are appropriate. This abrupt ecosystem reconfiguration changes habitat complexity, altering abiotic and biotic interactions, thus disrupting the flow of energy through the ecosystem (Motitsoe et al. 2020, Strange et al. 2018). Giant salvinia (Salvinia molesta D.S. Mitchell; hereafter referred to as salvinia), is a free- floating aquatic fern, native to Brazil, and is considered highly invasive due to its rapid growth and vegetative reproduction (Oliver 1993, Koutika and Rainey 2015). Stems of salvinia easily break, allowing propagules to drift by wind or water current to non-infested locations (Owens et al. 2004, Heidbüchel et al. 2020). Under ideal conditions, salvinia can double its biomass in as few as 36-53 hours (Cary and Weerts 1983, Johnson et al. 2010) and form a mat in days (Mitchell and Tur 1975). Salvinia infestations can persist for months, even years, often requiring human intervention, such as chemical, mechanical or biological control, to reopen waterways (Martin et al. 2018, Nelson 2020). Nutrient additions to waterbodies alter the ecosystem and can promote invasions of free- floating macrophytes. Nutrients enter water bodies in various means, such as agriculture and
19 urban runoff, wastewater discharge, atmospheric deposition, surface flow, and floodwaters receding from floodplains, with excessive nutrients causing a water body to become eutrophic (Selman and Greenhalgh 2010, Dupas et al. 2015, Wurtsbaugh et al. 2019). The increased nutrients promote algal blooms, resulting in increased turbidity and decreased light transmission through the water, causing large die-offs of submerged macrophytes in the littoral zone (Smith et al. 1999, Chislock et al. 2013). Invasive free-floating macrophytes pose a high risk under increased nutrient environments, as they may exacerbate the negative impacts of algal blooms. An increase in nutrients would enhance growing conditions for these macrophytes, resulting in a faster expansion and covering of open water, potentially increasing total impact on the aquatic ecosystem. A mesocosm study was designed to examine the interaction between salvinia and nutrients, and its effect on water quality and a submerged macrophyte. The objectives are to: 1) determine how salvinia affects water quality, light availability, and submerged macrophyte biomass following introduction; and 2) determine how nutrients affect the rate of salvinia growth and water quality changes. It is hypothesized that under low nutrients, salvinia growth will be limited and may not establish, and changes in water quality would be minimal with submerged macrophyte being able to maintain biomass through the duration of the study. When nutrients are added it is speculated salvinia will thrive, thus reducing water quality and decreasing submerged macrophyte biomass through the duration of the study, and resulting in a complete loss of macrophyte biomass under high nutrient additions.
Methods
Mesocosm design
A mesocosm study was conducted from May through June 2019 in a temperature- controlled greenhouse at the Louisiana State University (LSU) Agricultural Center in Baton Rouge, Louisiana, USA. Mesocosms consisted of black plastic containers (114 L; 0.66 × 0.44 × 0.38 m; L × W × H; surface area = 0.29 m2) filled with local pond water from the LSU aquaculture facility in Baton Rouge. Prior to adding the submerged macrophyte, mesocosms were covered with salvinia for 30 d, which depleted total nitrogen in the mesocosms (0.11 ± 0.31 mg L-1 (mean ± SD); n = 36). After the nutrient depletion period, salvinia from each mesocosm was discarded and fresh plants were used for the study. Using new plants assured that initial salvinia was not already stressed by the low nutrients experienced during the depletion period. Mature tertiary stage salvinia was collected from earthen ponds at the LSU Agricultural Center Reproductive Biology Center in St. Gabriel, Louisiana (13.4 km from mesocosm site). A systemic insecticide (21.4% Imidacloprid; Control Solutions, Pasadena, TX) was applied to the foliage of salvinia 30 d prior to treatment application to control herbivorous insects. Submerged macrophyte was collected from Blind River in Ascension Parish, Louisiana (30.103231, - 90.727329; 52 km from mesocosm site). Initial salvinia coverage and total nitrogen were used to test effects on submerged macrophyte biomass and water quality. Three initial salvinia coverages (0, 5 or 20%) and three nutrient treatments (0, 3 and 8 mg N L-1) were selected. The three salvinia coverages represent coverages observed at field locations following winter die off, where 0% is complete die off and the other two are partial die off (personal observation). Once introduced, salvinia grew undisturbed for the entirety of the study, and percent salvinia cover was measured weekly. Rate
20 of increased salvinia cover was determined from initial coverage until plants reached 100% cover or completion of the study. Nutrient regimes were maintained at those concentrations for the duration of the study. Total nitrogen was sampled weekly with a handheld colorimeter (LaMotte Smart 3, LaMotte Company, Chestertown, MD). Miracle-Gro® (24-8-16, N-P-K; The Scotts Miracle-Gro Co., Marysville, OH) was used to fertilize mesocosms as needed. Nitrogen concentrations were selected to mimic concentrations from a natural water source, the Mississippi River (3 mg N L-1) and agricultural field runoff (8 mg N L-1) (Yu et al. 2008).
Plant quality
To address the objective of how salvinia affected coontail biomass, repeat sampling of submerged macrophyte biomass through time was conducted. Common native submerged macrophyte, coontail (Ceratophyllum demersum L.) and was selected for the study. Coontail grew in 0.65 L planting pots (9 × 8.5 × 8.5 cm) filled with 7 cm of top soil (Organic Valley®, Garick LLC, Cleveland, OH) capped with 2 cm of sand to limit nutrient dispersion into the water column, and five apical shoots (10 cm) were added to each pot. Pots were placed in a mesocosm approximately 10 cm apart. After potting, coontail grew undisturbed for 21 d prior to treatments being implemented (Strange et al. 2018). Coontail biomass was collected weekly (108 pots = 3 nutrients × 3 salvinia coverages × 6 weeks × 2 replicates), and all above sediment biomass (i.e. leaves and shoots) from a pot was removed (when sampled) then placed in a resealable plastic bag until processing. Plant matter was placed in a drying oven for 72 h at 65°C then weighed for dry biomass. To account for initial coontail biomass, five pots were harvested after the 21 d growth period and immediately before treatments were implemented. Treatment location within the mesocosm array and weekly submerged plant sampling were randomized. Salvinia biomass and tissue nutrients were collected from both cover treatments. Initial biomass was determined with five samples of each cover treatment, and all salvinia biomass was collected at the completion of the study. To account for nutrient effects on salvinia, plant tissue was sampled for percent carbon and percent nitrogen at 0, 3 and 6 w after treatment. Salvinia biomass samples were dried in the same manner as coontail biomass. Salvinia tissue samples were processed at the LSU Agricultural Center Soil Test and Plant Analysis Lab, Baton Rouge, Louisiana.
Water quality
Physico-chemical parameters and light availability were collected weekly in each mesocosm (36 mesocosms = 3 nutrients × 3 salvinia coverages × 4 replicates). Dissolved oxygen (DO, mg L-1), pH, and specific conductance (µS) were collected with a handheld multiprobe (Pro-DS5, YSI Incorporated, Yellow Springs, OH). Water temperature (°C) was recorded every 30 minutes using HOBO® pendant temperature loggers (accuracy ± 0.53°C; Onsite Computer Corporation, Bourne, MA). Air temperature (°C) was recorded 0.5 m above the ground and logger was placed inside a solar radiation shield and water temperature loggers were placed inside the mesocosm on the bottom to ensure consistent conditions throughout the experiment [mean air temperature was 26.34°C (±2.49(±SD)) and mean water temperature was 26.84°C (±2.18; n = 18)]. Light transmission through the water column was measured with a handheld light meter (MW700, Milwaukee Instruments, Rocky Mount, NC) directly above and below (1 cm) the water surface, then at 10 cm intervals until the bottom (~26 cm).
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Statistical analysis
Analyses and figures were developed using R statistical software version 3.4.4 (Program R; R Core Team 2019) and JMP (version 15, SAS Institute, Inc., Cary, NC, USA). Analyses examined for differences in water quality and plant characteristics among salvinia cover and nutrients. Best-fit lines (y = mx + b) were produced for coontail biomass change during the experiment. One line was produced using the mean dry biomass per week and the linear fit line was made using smoothing spline (λ ≥ 100). Generalized linear models (GLM; package MASS; Venables and Ripley 2002) compared coontail and salvinia plant quality among initial cover and nutrients. For all variables, the selected combination of link and distribution was determined by comparing candidates and fit statistics. Comparisons of final coontail biomass among initial cover and nutrients were performed using an identity link, gaussian distribution GLM. Comparisons of salvinia growth and percent nitrogen in salvinia tissue were performed using gamma distribution GLMs with identity and log links, respectively. A log link, gaussian distribution, GLM was used for percent carbon comparisons. Linear mixed effect models (LMM; package lme4; Bates et al. 2015) and generalized linear mixed effect models (GLMM; package lme4; Bates et al. 2015) compared water quality and light availability among initial cover and nutrients. The approach allows for the evaluation between response variables and fixed effects, while accounting for measurements over time. The effect of initial cover and nutrients were of interest, thus were selected as fixed effects in all models. The effect of time on the variation of water quality parameters can be expected to differ on a weekly basis; therefore, week was selected as a random variable. Visual inspection of the data suggests that week could be an important random effect, thus additional random effect considering the interaction between week and fixed effects (initial cover and nutrients) were added when comparing models. Multiple LMM and GLMM models were evaluated with different variable, link transformation, and probability distribution combinations with the final models selected for interpretation based on lowest AIC and residual plots indicating model assumptions were met. For the analysis of dissolved oxygen, a LMM compared among initial cover and nutrients. For the analysis of pH, specific conductance, and light intensity, a log link, gamma distribution GLMM compared among initial cover and nutrients. Likelihood ratio tests were conducted to test for significance in water quality differences among nutrient and initial cover treatments. Estimated marginal means (package emmeans; Lenth 2020) were used to examine significant interactions between initial cover and nutrient treatments. In addition to measuring light intensity at depth, the rate of light loss was estimated with an exponential growth and decay model (y = ae±kt; Madden and Kemp 1996).
Results
Plant quality
Initial salvinia coverage and nutrients affected coontail biomass over time. Initial coontail dry biomass, before cover and nutrient treatments were implemented, was 5.12 g [±0.91 (±SD); n=5]. Although coontail was present in all treatments at the end of the experiment, coontail biomass unaffected in low nutrient treatments across all levels of salvinia coverage, whereas biomass decreased in high nutrient treatments with initial 5 and 20% salvinia coverages (Figure
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3.1). Biomass was largely unchanged in medium and high nutrient treatments, and initial 0% salvinia treatment. Nutrients (χ2 = 11.78, p < 0.01) and initial cover (χ2 = 6.06, p = 0.05) significantly decreased coontail biomass at the conclusion of the experiment. Coontail biomass differed between the 0 and 20% initial cover treatments (z-ratio = 2.44, p = 0.04), and between low and high nutrient treatments (z-ratio = -3.41, p < 0.01).
Figure 3.1. Coontail biomass change over time for 0, 5, and 20% initial giant salvinia cover, and low (0), medium (3) and high (8 mg N L-1) nutrient treatments. Blue line represents mean dry biomass change and grey line represents line of best fit for the study duration. Initial coontail biomass before implementing treatments was 5.12 g [±0.91(±SD)]. Line of best fit equation was added for each treatment (y = mx + b).
Salvinia biomass and percent cover were affected by nutrients. Initial salvinia dry biomass was 2.16 [±0.16 (±SD)] and 5.10 (±0.01) g for 5 and 20% coverages, respectively. Final biomass in the 5% salvinia cover treatments were 9.95 (±2.06), 26.88 (±8.08), and 42.10 (±8.62) g for low, medium, and high nutrients, respectively. Biomass at the completion of the study in the 20% coverage treatment was 18.38 (±4.09), 43.13 (±8.72), and 47.17 (±4.99) g for low, medium, and high nutrient regimes, respectively. The rate of salvinia growth in the 5% cover treatment for low, medium, and high nutrients were 0.19 (±0.05), 0.59 (±0.19), and 0.95 (±0.21) g dry wt d-1, respectively. The rate of salvinia growth in the 20% cover for low, medium, and high nutrient
23 treatments were 0.19 (±0.10), 0.91 (±0.21), and 1.00 (±0.12) g dry wt d-1, respectively. Salvinia growth was enhanced by initial cover (χ2 = 12.70, p < 0.01) and nutrients (χ2 = 118.78, p < 0.01). Rate of salvinia growth for initial cover of 5% was lower than 20% (β = -0.15, SE = 0.04, z-ratio = -3.40, p < 0.01), and rate of salvinia growth for low nutrients was less than medium nutrients (β = -0.48, SE = 0.07, z-ratio = -7.05, p < 0.01) and high (β = 0.73, SE = 0.09, z-ratio = 8.15, p < 0.01). Additionally, the rate of salvinia growth for medium was lower than high nutrients (β = 0.25, SE = 0.11, z-ratio = 2.35, p = 0.05). The rate of salvinia percent cover increase varied among the nutrient regimes. The rate of salvinia percent cover increase was similar between 5 and 20% coverages within each nutrient regime. For low nutrients, 5% salvinia cover growth rate was 8.5% per week and growth rate for 20% salvinia cover was 10% (Figure 3.2A). Growth rate in medium nutrients for 5% and 20% salvinia cover was 16% per week, respectively (Figure 3.2A). In the high nutrient treatment 5% salvinia cover growth rate was 24% per week and salvinia growth rate for 20% cover was 27% (Figure 3.2A). Percent nitrogen in salvinia tissue was enhanced by nutrients (χ2 = 67.33, p < 0.01; Table 3.1). Percent nitrogen in high nutrients was greater than medium (β = 0.37, SE = 0.08, z-ratio = 4.57, p < 0.01) low (β = 0.67, SE = 0.08, z-ratio = 8.18, p < 0.01), additionally, percent nitrogen in medium nutrients was higher than low nutrients (β = 0.30, SE = 0.08, z-ratio = 3.61, p < 0.01). Percent carbon in salvinia tissue was enhanced by nutrients (χ2 = 12.62, p < 0.01; Table 3.1), and percent carbon in high nutrients was greater than low (β = 0.03, SE = 0.01, z-ratio = 3.55, p < 0.01). Percent nitrogen and percent carbon did not vary between 5 and 20% cover.
Water quality
Dissolved oxygen varied among nutrient and salvinia cover treatments. In the presence of salvinia, DO decreased over the duration of the study with nutrients influencing the rate of change (Figure 3.2B). In the 5% salvinia cover treatments, DO at the conclusion of the study was 1.25 [±0.90 (±SE)] and 1.63-times (±0.92) lower than the 0% cover treatment for low and medium nutrients, respectively. Under high nutrients, DO finished 1.88 (±0.70) and 3.37-times (±0.70) lower in the 5 and 20% salvinia cover treatments, relative to the 0% salvinia cover treatment, respectively. Nutrients, initial salvinia coverage and the interaction of nutrients with initial salvinia coverage interaction (χ2 = 22.65, p < 0.01) affected DO. The 0% salvinia cover in medium nutrient treatment represented the upper limit of DO, while 20% cover in high nutrient treatment was the lower limit (Table 3.2). Dissolved oxygen decreased by 4.37 mg L -1 [±0.45 (±SE), t-ratio = 9.81, p < 0.01] between the highest estimated mean and lowest mean. Under low nutrients, DO in 20% salvinia cover was lower than 0% cover (t-ratio = 4.80, SE = 0.37, p < 0.01). In medium nutrients, DO in 0% salvinia cover was higher than 5% (t-ratio = 6.17, SE = 0.37, p <0.01) and 20% (t-ratio = 8.08, SE =0.37, p < 0.01). At high nutrients, DO in 0% salvinia cover was higher than 5% (t-ratio = 5.93, SE = 0.37, p <0.01) and 20% (t-ratio = 9.43, SE = 0.37, p < 0.01), additionally, DO in the 5% was higher than 20% cover (t-ratio = -3.50, SE = 0.37, p = 0.03). Over the duration of the study, pH decreased in treatments that contained salvinia. At the completion of the study, pH in low nutrient treatments with salvinia was 1.1 [±0.34 (±SE)] times less than no salvinia treatments (Figure 3.2C). Final pH in medium nutrient treatments was 1.33 (±0.36) times less than no salvinia treatments, similarly, final pH in high nutrient treatments containing salvinia was at least 1.32-times (±0.22) less than treatments not containing salvinia
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(Figure 3.2C). Differences in pH were explained by nutrients (χ2 = 12.99, p < 0.01) and initial salvinia coverage (χ2 = 54.27, p < 0.01). The 0% salvinia cover in medium nutrients represented the upper pH limit, while 20% cover in high nutrients was the lower limit (Table 3.2). The model estimated pH changed by 1.95 units between the highest estimated mean (x̄ = 9.12, SE = 0.35, z- ratio = -34.79) and the lowest (x̄ = 7.17, SE = 0.28, z-ratio = -41.01). In low nutrients, there were no differences between salvinia cover treatments. Under medium nutrients, pH in 0% salvinia
Figure 3.2. Weekly sampling of giant salvinia percent cover (A), dissolved oxygen (B), pH (C). and specific conductance (D) in mesocosms. Three initial salvinia cover, 0 (blue), 5 (red), and 20% (grey), and three nutrients, [low (0), medium (3), and high (8 mg N L-1], treatments. Samples of water quality at week zero were recorded immediately before salvinia and nutrient treatments were implemented. Lines represent mean values, ±95% confidence intervals. cover was higher than 5% (β = 0.14, SE = 0.04, z-ratio = 3.26, p < 0.01) and 20% (β = 0.19, SE = 0.04, z-ratio = 4.60, p < 0.01), additionally under high nutrients, pH in 0% cover was higher than 5% (β = 0.17, SE = 0.04, z-ratio = 4.10, p = 0.01) and 20% (β = 0.22, SE = 0.04, z-ratio = 5.34, p < 0.01).
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Table 3.1. Mean percent nitrogen and carbon (±SD) in salvinia tissue for the initial cover and nutrients, low (0), medium (3), and high (8 mg N L-1) treatments. Samples were collected initially (0), halfway (3) and at completion of the study (6 weeks) (n = 4). Week Treatment % Nitrogen % Carbon 0 Initial 2.13 (±0.04) 38.6 (±1.25) 3 5%-Low 1.74 (±0.15) 39.4 (±1.3) 3 5%-Medium 2.52 (±0.25) 39.6 (±0.67) 3 5%-High 4.04 (±0.75) 40.3 (±0.77) 3 20%-Low 1.49 (±0.15) 39.9 (±0.38) 3 20%-Medium 2.61 (±0.03) 40.3 (±0.37) 3 20%-High 3.67 (±0.45) 41.0 (±0.01) 6 5%-Low 2.14 (±0.14) 39.9 (±0.14) 6 5%-Medium 2.15 (±0.30) 40.5 (±0.03) 6 5%-High 2.70 (±0.04) 41.9 (±0.51) 6 20%-Low 1.62 (±0.20) 40.3 (±0.27) 6 20%-Medium 2.11 (±0.48) 41.2 (±0.31) 6 20%-High 3.22 (±0.02) 41.0 (±0.03)
Table 3.2. Linear mixed model and generalized linear mixed models estimates of mean values for dissolved oxygen (DO, mg/L), pH, specific conductance (µS), and light intensity (LUX) at 10 cm depth with, lower and upper 95% confidence limits (CL) among initial salvinia cover, 0, 5 and 20%, and nutrients, low (0), medium (3) and high (8 mg N L-1). Treatment DO (CL) pH (CL) Specific Light Availability conductance (CL) (CL) 0%-Low 8.89a (7.19-10.58) 9.01a (8.09-10.02) 466a (387-562) 8,946a (743-107,628) 5%-Low 7.69ab (6.00-9.39) 8.62a (7.75-9.60) 469a (389-566) 4,334a (359-52,180) 20%-Low 7.12b (5.42-8.81) 8.09a (7.27-9.00) 458a (380-551) 2,232a (185-26,880) 0%-Medium 8.99a (7.30-10.69) 9.12a (8.19-10.14) 472a (391-569) 6,876a (571-82,740) 5%-Medium 6.72b (5.02-8.41) 7.95b (7.15-8.85) 443ab (367-534) 1,624ab (135-19,536) 20%-Medium 6.01b (4.32-7.71) 7.52b (6.76-8.37) 431b (357-519) 467b (39-5,610) 0%-High 8.10a (6.41-9.80) 8.96a (8.05-9.97) 499a (414-601) 7,913a (657-95,235) 5%-High 5.91b (4.22-7.61) 7.55b (6.78-8.40) 437b (363-527) 606b (50-7,276) 20%-High 4.62c (2.93-6.32) 7.17b (6.44-7.98) 445b (369-536) 287b (24-3,441) Note: Letters indicate difference between coverages within a nutrient treatment based on model outputs.
Specific conductance was influenced by salvinia cover and nutrients. When salvinia was not present, it increased over the duration of the study and was 1.06-times [±24.42 (±SE)] greater in high nutrient treatments, relative to low and medium nutrients (Figure 3.2D). Under the medium nutrient treatment, it in salvinia treatments was at least 1.15-times (±9.78) less than no salvinia treatments, and salvinia treatments were at least 1.25-times (±24.80) less than no salvinia treatments when nutrients were high (Figure 3.2D). Initial salvinia coverage and the interactions between nutrients with initial salvinia coverage on specific conductance to be significant (χ2 = 53.49, p < 0.01). The 0% salvinia cover treatment in high nutrients represented the upper limit, while 20% in medium nutrients was the lower limit (Table 3.2). Specific conductance changed by 68 µS between upper CL (x̄ = 499, SE = 33.7, z-ratio = 39.35) and
26 lower CL (x̄ = 431, SE = 29.1, z-ratio = 37.17). Specific conductance did not vary under low nutrients. Under medium nutrients, specific conductance in the 0% salvinia cover was higher than 20% (β = 0.09, SE = 0.09, z-ratio = 3.23, p = 0.03). Within the high nutrient treatments, specific conductance in the 0% salvinia cover was higher than 5% (β = 012, SE = 0.03, z-ratio = 3.60, p = 0.01) and 20% (β = 0.11, SE = 0.03, z-ratio = 4.08, p < 0.01).
Figure 3.3. Mean light intensity (lux), ±95% confidence intervals, over the duration of the study for the low (0), medium (3), and high (8 mg L-1 N) nutrient treatments and the three initial salvinia coverages (0, 5, and 20%). Light intensity was measured directly above the water surface then below surface at 1, 10, 20 cm, and mesocosm bottom (~26 cm). Exponential growth and decay equation (y = ae±kt) of mean light intensity through the water column was added for each treatment.
Light availability was limited by initial cover and nutrients. The rate of exponential decay in light availability increased with salvinia cover and nutrients (Figure 3.3). In the low nutrient treatment, light availability at 10 cm in 0% cover was 2.08 [±3,143 (±SE)] and 3.15-times (±3,000) more than the 5% and 20% salvinia cover treatments, respectively, similarly, in medium nutrients light availability was 2.09 (±2,637) and 5.94-times (±2,281) less for 5% and 20% salvinia cover treatments, respectively, relative to no salvinia. At high nutrients, light availability at 10 cm depth was 4.67 (±2,990) and 18.24-times (±2,780) less in the 5 and 20%
27 salvinia cover treatments, respectively, compared to no salvinia. Differences in light intensity at 10 cm were explained by nutrients, initial salvinia cover, and the interaction of nutrients with initial salvinia coverage (χ2 = 9.90, p = 0.04). The model estimated that 0% salvinia cover in low nutrients represented the upper light intensity limit, while 20% cover in high nutrients was the lower limit (Table 3.2). Light availability at 10 cm changed by 8,659 lux between upper CL (x̄ = 8,946, SE = 8,047, z-ratio = 6.16) and lower CL (x̄ = 287, SE = 258, z-ratio = 2.34). In low nutrients, there were no differences between salvinia cover treatments. Under medium nutrients, light availability at 10 cm in 0% salvinia cover was higher than 20% (β = 2.69, SE = 0.51, z-ratio = 5.28, p < 0.01), additionally under high nutrients, light availability in 0% cover was higher than 5% (β = 2.57, SE = 0.51, z-ratio = 5.05, p = 0.01) and 20% (β = 3.32, SE = 0.51, z-ratio = 6.52, p < 0.01).
Discussion
Our study shows that nutrients were an important factor when determining the impact of salvinia on coontail and water quality. The hypothesis was supported in that under low nutrients, coontail was able to persist and its biomass seemed unaffected by salvinia. The data did not support the prediction that salvinia at higher levels of nutrients would result in the complete loss of coontail biomass. Under low and medium nutrients, coontail biomass did not decrease; however, under high nutrients, coontail biomass decreased when salvinia was present. Despite weeks of being under a salvinia mat, coontail persisted through the duration of the study. Changes in water quality were evident from salvinia presence when nutrients were added, and these changes were enhanced as salvinia cover increased. Shading from salvinia is the most likely explanation of reduced coontail biomass at a high nutrient concentration. Salvinia did not completely cover the no nutrient addition treatments, thus light was not completely cut off and coontail biomass was not affected. It appears that high shading, near 100% salvinia coverage, was necessary to reduce coontail biomass. A ten-week study examining the effects of filamentous algal mats on coontail performance found biomass of coontail was significantly lower under 100% cover mat, however biomass under no mat and 50% mat did not vary (Liu et al. 2012). A similar study examined the effects of >8 weeks of shading on three submerged macrophytes, including coontail, found that shading ≥ 90% of the system was needed to reduce biomass, and the highest accumulation of coontail biomass was 65% shading cover (Kankanamge et al. 2019). Coontail has a low light compensation point, the point on the light curve where the rate of photosynthesis matches the rate of cellular respiration, of 7.2 µmol m-2 s-1 (Sand-Jensen and Madsen 1991) and this may explain why this submerged macrophyte is able to tolerate high shading, thrive in deeper water, and survive long periods under ice (Van et al. 1976, Spencer and Wetzel 1993, Gross et al. 2003). The increased growth under low to moderate levels of shading has been observed for Vallisneria natans L., Myriophyllum spicatum L., and Elodea nuttallii (Planch.) H. St. John (Lu et al. 2013, Zefferman 2014). Coontail is a canopy forming submerged macrophyte, and the shading provided by its floating canopy may create more favorable growing conditions for itself. Because of the duration of the study, this research was unable to determine how much time under full salvinia coverage would be needed to completely eliminate submerged macrophyte biomass and future research should investigate longer time frames to determine how long coontail can survive under a giant salvinia mat. Coontail persisted in the study for three weeks under 100%
28 salvinia cover, and the coontail biomass has been reported to persist after ten weeks of shading (Liu et al. 2012), suggesting coontail is tolerant to shaded environments. The rate of change in dissolved oxygen by salvinia was directly related nutrient levels. Nutrient additions increased the rate of increase of salvinia cover, which exacerbated the impact to DO. The observation of decreased DO in the presence of salvinia was expected (Oliver 1993, Tipping et al. 2008). Decreased DO can be attributed to a reduction of photosynthesis by submerged macrophytes and phytoplankton, limited atmospheric gas exchange due to mat presence, and the decomposition of organic matter (Owens et al. 2005). The extensive formation of salvinia mat can lead to near anoxic conditions, potentially causing internal nutrient loading of the waterbody (Wahl et al. 2020). Previous research has found that DO concentrations ≤ 1 mg L-1 results in increased sediment nutrient release of ammonium (Zhang et al. 2014) and phosphorus (Wu et al. 2014). During the study, DO concentrations remained above stressful or lethal levels for freshwater warmwater stream and wetland fish and invertebrates (Killgore and Hoover 2001, Kaller and Kelso 2007, Justus et al. 2012). However, salvinia decomposition and concurrent hypoxic (2 mg/L) and anoxic conditions have been associated with fish mortality (Flores and Carson 2006). Salvinia reduced overall pH and the rate of change was determined by nutrients. The reduction in pH associated with salvinia has been reported previously (Julien et al. 2009, Coetzee and Hill 2020). In the mesocosms, pH declined until 100% salvinia cover occurred stabilizing around 7. Although unmeasured in this experiment, the reduction in pH could be due to the accumulation of carbon dioxide in the water. The salvinia mat acts as a barrier between atmosphere and water surface, limiting gas exchange and accumulating carbon dioxide in the water (Mitchell 1969, Doeleman 1989, McFarland et al. 2004). Photosynthesis of submerged macrophytes removes carbon dioxide and a reduction in submerged macrophytes would reduce photosynthesis, thus limiting carbon dioxide update. Submerged macrophytes increase pH and DO during daylight hours (photosynthesis) and decrease both variables at night because of respiration (Van et al. 1976). The loss of these plants due to shading from salvinia would reduce day-night variation in pH and DO, with these variable remaining low during day and night. The reduced pH may also be due to localized habitat modification by salvinia to create more ideal growing conditions. Previous research in greenhouse settings have found the highest rate of salvinia growth occurred when pH was around 6.0 (Cary and Weerts 1984, Madsen and Wersal 2008). Salvinia can decrease pH over time to make conditions more suitable, and continuous salvinia coverage can drop pH to as low as 4.5 (personal observation). Sediment release of ammonium has been found to be greatest when pH was at 6 (Zhang et al. 2014), and this may explain why salvinia prefers slightly acidic conditions. The slightly acidic conditions have been found to negatively affect metabolism of submerged macrophyte hydrilla (Hydrilla verticillata L.f.) (Song et al. 2018), thus, the modified environment may reduce competition from other plants. Decreased pH under free-floating macrophyte mats has been also observed for water hyacinth (Eicchornia crassipes Mart. Solms) (Mahmood et al. 2005), mosquito fern (Azolla filiculoides Lam.) (Janes et al. 1996), and water lettuce (Pistia stratiotes L.) (O’Farrell et al. 2011). Submerged macrophytes can also modify local pH. Frodge and Pauley (1990) and Van et al. (1976) found pH in canopies of coontail exceeded 10.0 and was two units higher than the adjacent open water, potentially due to release of phosphorus from the sediment. The rate of phosphorus release from the sediment starts to increase around pH of 8 and continues to increase as the water become more alkaline (Jin et al. 2006, Wu 2014). In this experiment, coontail may have modified the local environment by increasing pH when salvinia was not present. The pond
29 water used to fill the mesocosms had a pH of 7.0, and after the 21-day acclimation period, mean pH across all mesocosms was 8.6 [±0.23 (±SD)]. Nutrient addition amplified the rate of increase in salvinia coverage and exacerbated effects to water quality. Salvinia has been shown to respond positively to modest and high nutrient additions (Cary and Weerts 1984, Oliver 1993, Madsen and Wersal 2008). Nutrient additions to waterbodies, through agriculture or urban runoff, create favorable conditions for salvinia to proliferate and create a mat on the water surface. Moderate nutrient additions can result in salvinia growth and aquatic habitat degradation. Management actions in coastal zones (e.g., diversion for wetland enhancement and restoration) or flood control efforts that route nutrient-rich water into wetlands (Day et al. 2018) also may enhance salvinia at the expense of native aquatic vegetation. Maintaining abundant and diverse community of native submerged macrophytes is critical for land managers, however invasion from salvinia quickly alters environmental conditions, requiring management efforts to maintain submerged macrophytes. Within weeks, salvinia created low DO conditions, decreased pH, and reduced light availability. This research demonstrated that nutrients determine the rate at which salvinia degrades the aquatic environment. Coontail persisted after salvinia covered the water surface, which suggests that an opportunity exists for immediate management to control salvinia to maintain native submerged macrophytes and environmental quality. Submerged macrophyte species that produce seeds and tubers may be able to quickly re-establish locations following prolonged salvinia invasions, however, species that rely on asexual reproduction will not return until re-introduced via wildlife or drift in from the water current. More research is needed to determine the time until submerged macrophyte are completely absent, and how long for submerged macrophyte communities to recover following control of salvinia.
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CHAPTER 4. INVASIVE FLOATING FERN LIMITS AERIAL COLONIZATION AND ALTERS COMMUNITY STRUCTURE OF AQUATIC INSECTS
Introduction
In freshwater wetlands, aquatic insects are highly abundant and are closely associated with submerged macrophytes. Aquatic insect abundance, diversity, and biomass in lentic systems has been attributed to submerged macrophyte architecture and biomass (Warfe and Barmuta 2004, Rennie and Jackson 2005). Submerged macrophytes fill the water column, providing important substrate for aquatic insects to evade predations and acquire resources (Walker et al. 2013), and leaves with large surface area and branching offer the greatest quantity of habitat and biomass (Warfe and Barmuta 2006, Hinojosa-Garro et al. 2010). Diverse macrophyte communities generate the critical habitat complexity, thus the structure of insect communities in wetlands can be directly related to macrophyte diversity (McAbendroth et al. 2005, Ferreiro et al. 2011, Thornhill et al. 2017). Aquatic insects are an important component in the structure of freshwater ecosystems. Within trophic webs, aquatic insects directly consume primary producers and organic matter, and serve as a resource for a variety of invertebrate and vertebrate predators, such as fish and waterbirds (Cummings 1973, Hershey et al. 2010, Tapp and Webb 2015, Mermillod-Blondin et al. 2020). Aquatic insect life history involves an egg and larval, or nymph phases in the aquatic environment and an adult phase where they emerge from the water and disperse aerially (Merritt and Cummins 1996). Aerial dispersal allows these invertebrates to colonize new locations, maintain communities, avoid drought, reproduce and lay eggs (Blakely et al. 2006, Batzer and Boix 2016, Jourdan et al. 2019). During their adult phase, aquatic insects are susceptible to predation by terrestrial organisms, such as birds (Murakami and Nakano 2002, Epanchin et al. 2010), bats (Salvarina et al. 2018), lizards (Sabo and Power 2002), arthropods (Paetzold and Tockner 2005, Chari et al. 2020), which allows the direct transfer of energy from the aquatic ecosystem to the terrestrial environment. Disruptions to aquatic insect communities potentially poses a risk to the transfer of energy to terrestrial ecosystems (Twining et al. 2018, Lewis- Phillips et al. 2020). Introduction of non-native floating macrophytes threaten the structure of aquatic ecosystems. Giant salvinia, Salvinia molesta Mitchell (Salviniaceae) (hereafter referred it as salvinia), is a free-floating fern native to Brazil, and considered highly invasive in tropical and subtropical regions (Luque et al. 2014, CABI 2019). It typically invades quiescent and slow moving waterbodies and forms a dense mat of vegetation on the water surface, completely covering the surface, acting as a barrier between the terrestrial and aquatic environments (Rommens et al. 2003). The mat limits light entering the water, which reduces phytoplankton, periphyton, and submerged macrophyte abundances (Oliver 1993, Pinto and O’Farrell 2014, Motitsoe et al. 2020). The loss of submerged macrophytes reduces insect habitat, creates a homogeneous habitat structure, and results in decreased biodiversity (Thomaz and Cunha 2010, Coetzee et al. 2014). Furthermore, salvinia will decrease dissolved oxygen through submerged macrophyte loss and decomposition causing stress to invertebrates, fish, and other aquatic organisms (Marshall and Junor 1981, Flores and Carson 2006, Coetzee and Hill 2020a). Environmental filtering, or the selecting of a subset of species from a regional species pool
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(Lebrija-Trejos et al. 2010), due to reduction in primary producers, habitat structure, and dissolved oxygen, could alter species occurrence and aquatic insect community structure. The presence of a salvinia mat on the water surface may prevent aquatic insects from completing their life cycle by impeding emergence or colonization due their rapid expanse horizontal colonization followed by vertical growth up to one meter thick (Thomas and Room 1986). If individuals were able to emerge from under the mat or arrive from surrounding habitats, they may not be able to recolonize or lay eggs in locations where salvinia is present, leading to communities that are different from uninvaded locations (De Szalay and Resh 2000). Limited studies have been conducted examining salvinia effects on aquatic insect communities, and no literature exists examining the effect of this macrophyte on colonization of adult aquatic insects. The objectives were to: 1) determine how salvinia affected aquatic insect aerial colonization, and 2) how salvinia cover affected insect community structure. It is hypothesized that a salvinia mat would impede aerial colonization of aquatic insects, and abundance and richness would decrease with increasing salvinia coverage, resulting in unique assemblage structure once salvinia reached 100% coverage.
Methods
Mesocosm design
A mesocosm study was designed to examine the effect of salvinia on aerial colonization and community structure of aquatic insects. The study was conducted at the Louisiana State University (LSU) AgCenter Aquaculture Research Station in Baton Rouge, Louisiana, USA (30.368336, -91.183706) from 27 July through 14 November 2018. The research station has over 60 earthen ponds, ~22 ha water surface, and is directly adjacent to the Mississippi River and wooded wetlands and natural ponds on the floodplain and in the river batture, thus providing sources of aquatic insect colonists. The nearest water source was 50 m distance from the study sites. Mesocosms consisted of black 568 L (1.47 × 0.99 × 0.61 m, l × w × h; surface area = 1.16 m2) tanks filled with pond water. Monthly average temperature and precipitation in Baton Rouge during this period was 22.78°C and 145 mm (National Oceanic Atmospheric Administration). To provide habitat for aquatic insects, two 3.8 L planting pots (0.08 × 0.16 m; r × h), filled with 13 cm top soil (Organic Valley®, Garick LLC, Cleveland, OH, USA) covered with 3 cm sand, and ten shoots (0.3 m) of coontail (Ceratophyllum demersum L.), were placed in each mesocosm. Coontail was collected from Blind River in Ascension Parish, Louisiana (52 km from mesocosm site; 30.103231, -90.727329). Immediately following Coontail planting, salvinia coverage treatments were implemented. Mature salvinia in the tertiary growth stage was collected from outdoor ponds at the LSU AgCenter Reproductive Biology Center in St. Gabriel, Louisiana (13.1 km from mesocosm site). Once salvinia was added, an insecticide (22.8% lambda – cyhalothrin; Syngenta Crop Protection, LLC Greensboro, NC) was added to each tank, ensuring all invertebrates had been removed. After approximately 30 days, insects were observed colonizing mesocosms, and the study was initiated. Mesocosms were fertilized monthly with ammonium sulfate (AGRI-AFC, LLC Decatur, AL) to a concentration of 3 mg L-1 nitrogen. Mean water depth over the duration of the study was 0.44 m (±0.04; n=160). Three salvinia cover treatments, 25, 50% and 100%, and a reference coontail treatment (0% salvinia cover), were used to test the effect of salvinia on aquatic insect colonization (40 mesocosms = 4 coverages × 10 replicates). Percent salvinia cover was maintained for the study
32 duration. Cover treatments were maintained for the duration of the study using a gridded frame to calculate percent cover as the (number of squares containing at least half salvinia) / (total number of squares) × 100.
Environmental conditions
Environmental conditions, water quality and light availability were sampled monthly and coincided with aquatic insect assemblage sampling. Dissolved oxygen (DO), specific conductance (µS), pH, and temperature (°C) were collected with a handheld multiprobe (Pro- DS5, YSI Incorporated, Yellow Springs, OH, USA). Light transmission through the water column was measured with a handheld light meter (MW700, Milwaukee Instruments, Rocky Mount, NC, USA). Light intensity (lux) was measured directly above and below (1 cm) the water surface, then at 10 cm increments until the bottom (~40 cm). Additionally, water temperature was recorded every 30 minutes using HOBO® pendant temperature loggers (accuracy ± 0.53°C; Onsite Computer Corporation, Bourne, MA 02532) and measured at 0.2 m depth. Ambient air temperature was recorded ~0.4 m above the ground, in the middle of the mesocosm array, and logger was placed inside a Solar Radiation Shield (Onsite Computer Corporation, Bourne, MA 02532).
Aquatic insects
Aquatic insect assemblages were sampled monthly, over four months (August- November), for a total of 160 community samples during the study (160 samples = 4 covers × 10 replicates × 4 months). Aquatic insects were sampled using a homemade suitcase sampler, consisting of 0.31 × 0.31 m panels covered with 0.400 mm mesh. The panels were attached using a hinge and a chain, which standardized the trap to opening at 0.31 m. The sampling area was triangular prism shaped (0.31 × 0.31 × 0.31 × 0.31 m) that enclosed a volume of 0.009 m3 (Colon-Gaud and Kelso 2003). Sampling was done by lowering the device into coontail plants, once in place, the trap was closed, and excess vegetation sticking out of the edges of the sampler was discarded. If salvinia was present in the sampler with coontail both plants were processed. Although it was not possible to directly observe coontail in the 100% salvinia coverage, the sampler was deployed in the same way to sample salvinia and any coontail present. Material from the sampler was processed immediately following collection by flushing and rinsing plant material in a 75 L plastic bin filled with water. Plant material removed from the bin was then processed to determine dry biomass. If both vegetation types were collected, then biomass was processed separately. Plant material was dried in an oven for 72 h at 65°C to measure dry mass. Aquatic insects rinsed from plant material and were captured on a 0.500 mm sieve then enumerated and identified to lowest practical taxonomic level, usually genus. Larvae and nymph life stages were predominant in the mesocosms, but adult coleopterans were collected and identified.
Statistical analysis
Analyses first examined differences with water quality and light availability among salvinia cover and months. Next, multivariate and community analyses examined invertebrate
33 response among salvinia cover and months. Analyses were conducted using R statistical software version 3.4.4 (R Core Team 2019). Generalized linear models (GLM) compared water quality and light availability among fixed effects of salvinia cover and months. For all variables, the selected combination of link and distribution was determined by comparing candidate models and their fit statistics (푐̂ and AIC). Log link and Gaussian distribution GLMs were used for DO, specific conductance, pH, and dry biomass analyses. GLMs with log link and gamma distribution were used for temperature and light intensity. For aquatic insect analysis, taxa that had a total abundance of less than four individuals collected during the study were not analyzed. For comparability, species richness and abundance by per gram of dry plant biomass were standardized. GLMs with log link and gamma distributions were used to examine abundance per gram and richness per gram among salvinia cover and months. A multivariate generalized linear model (MGLM), with a negative binomial distribution and log link, was used to test for differences in aquatic insect community between habitats and among months (package mvabund; Warton et al. 2012). The model was adjusted for multiple comparisons using a step-down resampling procedure. To visualize the assemblage level similarity between salvinia cover and among months, ordination of taxa was produced using nonmetric multidimensional scaling (NMDS) of a Bray- Curtis similarity matrix (k = 4) (Clarke 1993). Comparisons of exploratory ordinations (e.g., principal component analysis and detrended correspondence analysis) indicated that NMDS would be the appropriate analysis (package vegan, Oksanen et al. 2019). Analysis of variance using distance matrices (ADONIS) was used to test the solution from NMDS analysis (package Vegan, Oksanen et al. 2019). Multivariate dispersion test showed that salvinia cover treatments, 0 (훿2 = 0.080), 25 (훿2 = 0.087), 50 (훿2 = 0.089) and 100% (훿2 = 0.072), were similar in multivariate distance within treatment, and appropriate for the analysis (Anderson and Walsh, 2013). Association with salvinia cover (Ordiselect, package Vegan, Oksanen et al. 2019) and community dissimilarity between coverages (similarity percentage, SIMPER, package Vegan, Oksanen et al. 2019) also were examined.
Results
Environmental conditions
Water quality variables varied among salvinia coverages and months (Table 4.1). Salvinia cover, month, and the interaction of salvinia cover with month affected DO (χ2 = 32.36, p < 0.01). Dissolved oxygen in the 0% salvinia cover was greater than the 25% [± 0.05 (± SE), t- value = -3.53, p < 0.01), 50% (± 0.06, t-value = -5.03, p < 0.01) and 100% (± 0.06, t-value = - 5.26, p < 0.01). Salvinia cover, month, and the interaction of salvinia cover with month also affected pH (χ2 = 36.04, p < 0.01). In the 0% salvinia cover treatment, pH was greater than 25% (± 0.02, t-value = -3.87, p < 0.01), 50% (± 0.02, t-value = -8.63, p < 0.01), and 100% (±0.02, t- value = -11.05, p < 0.01) treatments. Specific conductance was affected by salvinia cover, month, and the interaction of salvinia cover with month (χ2 = 46.63, p < 0.01). In 0% salvinia cover, specific conductance was higher than only the 100% cover treatment (± 0.06, z-ratio = - 2.52, p = 0.01). Water temperature was affected by salvinia cover, month and the interaction of salvinia cover with month (χ2 = 75, p < 0.01). Temperature in the 0% salvinia cover treatment was higher
34 than 25 (± 0.01, t-value = -5.27, p < 0.01) and 50% treatments (± 0.01, t-value = -4.21, p < 0.01). Although not statistically analyzed, ambient air temperature decreased over the study duration, ranging from mean high of 29.20 °C in August to 13.83 °C in November, with a mean study temperature of 23.66 °C (± 7.02). Mean water temperature over the study duration, regardless of salvinia cover, was 25.45 °C (± 5.85).
Table 4.1. Mean values (±SD) of dissolved oxygen (DO), pH, specific conductance (Cond), and temperature (Temp) in 0, 25, 50, or 100% salvinia cover in field mesocosms located in Baton Rouge, Louisiana. Month Cover DO (mg L-1) pH Cond. (µS) Temp. (°C) (%) August 0 7.59 (±1.54)a 9.56 (±0.25)a 256.26 (±25.62)a 28.66 (±0.56)a 25 6.27 (±0.38)b 9.00 (±0.29)b 253.05 (±17.90)a 27.70 (±0.24)b 50 5.68 (±1.03)b 8.30 (±0.30)c 245.41 (±38.35)a 27.90 (±0.21)b 100 5.59 (±0.55)b 7.94 (±0.16)c 220.15 (±39.47)a 28.64 (±0.49)a September 0 7.98 (±1.78)a 9.46 (±0.48)a 266.14 (±34.76)a 28.96 (±1.05)a 25 5.06 (±0.93)b 9.07 (±0.48)ab 252.14 (±22.98)a 27.77 (±0.34)b 50 5.72 (±0.90)b 8.58 (±0.39)b 239.92 (±42.67)a 28.05 (±0.44)b 100 5.67 (±0.29)b 7.97 (±0.14)c 171.43 (±43.55)b 29.07 (±0.55)a October 0 7.00 (±0.91)a 8.42 (±0.41)a 188.05 (±33.92)a 21.11 (±0.06)a 25 4.91 (±0.63)b 7.33 (±0.17)b 157.73 (±22.73)a 21.22 (±0.08)a 50 5.45 (±0.52)b 7.12 (±0.21)b 138.54 (±35.36)a 21.37 (±0.16)a 100 6.43 (±0.31)a 6.52 (±0.43)c 83.43 (±28.55)b 22.55 (±0.19)b November 0 10.95 (±0.64)a 8.56 (±0.34)a 169.01 (±29.73)a 13.36 (± 0.10)a 25 9.56 (±0.32)b 7.66 (±0.20)b 140.91 (±19.47)a 13.13 (±0.07)a 50 9.46 (±0.31)b 7.45 (±0.23)b 120.30 (±34.78)a 13.11 (±0.13)a 100 9.21 (±0.19)b 6.54 (±0.37)c 65.35 (±22.76)b 13.81 (±0.17)b Note: Letters indicate statistically significant differences for a variable within a sampling month based on generalized linear model output.
Light availability and dry biomass were also impacted by salvinia presence in the mesocosms. The reduction in light availability increased with salvinia cover and nutrients (Table 4.2). Salvinia cover, month and the interaction of salvinia cover with month decreased light availability (χ2 = 90.28, p < 0.01). Light availability at 10 cm in the 0% [30,415 ± 3,098 lux (mean ±SE)] salvinia cover treatment was 1.72-times higher than 25% (17,658 ± 2,362 lux, t- value = -1.95, p = 0.05), 3.79-times greater than 50% (8,023 ± 1,397 lux, t-value = -6.40, p < 0.01), and 766-times greater than 100% (39.7 ± 3.65 lux, t-value = -28.44, p < 0.01). Salvinia cover, month, and the interaction of salvinia cover with month affected dry mass (χ2 = 21.87, p = 0.01). Dry mass from 100% salvinia cover samples (22.89 ± 0.47 g (mean ±SE)) were 8.77-times more than 0% (2.61 ± 0.23 g, t-value = -38.30, p < 0.01), 5.11-times more than 25% (4.48 ±0.28 g, t-value = -33.56, p < 0.01), and 3.93-times more than 50% (5.83 ± 0.34 g, t- value = -29.25, p < 0.01). Dry mass from the 100% salvinia cover was greater than 0% (t-value = -10.30, p < 0.01), 25% (t-value = -11.00, p < 0.01) and 50% (t-value = -11.38, p < 0.01) coverages. Additionally, dry mass from the 50% salvinia cover was higher than 0% cover (t- value = -2.27, p = 0.02).
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Table 4.2. Mean light intensity (lux) (±SD) measured in 0, 25, 50 or 100% salvinia coverages at various depths from mesocosms located in Baton Rouge, Louisiana. Depth 0% 25% 50% 100% Above 59,390 (±33,325) 57,823 (±30,592) 60,400 (±34,426) 58,708 (±33,696) 1 cm 40,858 (±22,283) 39,543 (±20,936) 40,153 (±24,399) 4,655 (±5,238) 10 cm 30,415 (±19,597)a 17,658 (±14,939)b 8,023 (±8,839)c 40 (±23)d 20 cm 24,465 (±16,907) 11,528 (±11,768) 3,743 (±3,627) 20 (±7) 30 cm 18,801 (±15,374) 4,788 (±6,092) 2,867 (±3,643) 17 (±7) Bottom 13,224 (±13,496) 259 (±2,740) 1,824 (±2,187) 16 (±8) Note: Letters indicate statistical differences in light availability at 10 cm depth among salvinia coverages, based on generalized linear model (GLM) output (χ2 = 90.28, p < 0.01).
Aquatic insects
A total of 8,383 aquatic insect specimens (2,157 from 0%, 2,246 from 25%, 2,329 from 50% and 1,651 from 100%) in 40 lowest practical taxonomic units (LPTs) in 28 families within 6 orders, were identified throughout the four month trial (Table B.1). Eighteen of the 40 LPTs occurred less than four times, thus were removed prior to analysis. Standardized aquatic insect abundance per gram dry biomass in 0% (29.01 ± 4.48 individuals (mean ± SE)) salvinia cover was 1.97-times greater than 25% (14.66 ± 2.27 individuals, z-ratio = 4.99, p < 0.01), 2.39-times greater than 50% (12.12 ± 1.72 individuals, z-ratio = 6.32, p < 0.01), and 16.48-times greater than 100% (1.76 ± 0.16 individuals, z-ratio = 19.14, p < 0.01). Standardized aquatic insect richness per gram dry biomass in 0% (2.87 ± 0.30 LPTs) salvinia cover was 1.46-times greater than 25% (1.97 ± 0.21 LPTs, z-ratio = 3.12, p = 0.01), 1.91-times greater than 50% (1.50 ± 0.18 LPTs, z-ratio = 5.16, p < 0.01), and 17.93-times greater than 100% (0.16 ± 0.01 LPTs, z-ratio = 24.41, p < 0.01). Relative insect abundance of standardized per gram of dry biomass varied with salvinia cover. Assemblages in 0% and 25% salvinia cover were Chironomidae (Diptera) dominant with 66 and 45% relative abundance, respectively. In 0% salvinia cover, other LPTs with ≥ 5% relative abundance were Berosus sp. (Coleoptera; 14%), Buenoa sp. (Hemiptera; 6%), and Sympetrum sp. (Odonata; 7%), and in 25% cover Berosus sp. (Coleoptera; 5%), Anax sp. (5%; Odonata), Erythemis sp. (Odonata; 24%), Sympetrum sp. (Odonata; 9%). In the 50% and 100% salvinia cover treatments, Erythemis sp. (Odonata; 53%) and Scirtes sp. (Coleoptera; 67%) were the dominant taxon, respectively. Other taxon above 5% relative abundance in the 50% salvinia cover were Chironomidae (Diptera; 23%) and Sympetrum sp. (Odonata; 9%), and in the 100% cover Chironomidae (Diptera; 17%) and Erythemis sp. (Odonata; 13%). Salvinia cover and month described aquatic insect LPT abundance. Significant differences in abundance were most explained by salvinia cover (16 of 22 LPTs; Deviance = 884.9, p < 0.01) followed by month (7 of 22 LPTs; Deviance = 313.3, p < 0.01; Table 4.3). Examination of associations of LPT with salvinia cover revealed that taxa responded differently to coverage treatments; however, most taxa abundances were lower in 100% cover, with the lone exception of Scirtes sp. (Table B.2). Overall, aquatic insect assemblage structure showed variation among salvinia coverages. Ordination of aquatic insect community (22 LPTs with ≥ 4 individuals) compositions found three distinct groups (Figure 4.1 and Table B.3), with 25 and 50% salvinia cover treatments being one similar group. Residual STRESS was 0.111, which is within range for interpretability (Clarke
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Table 4.3. Multivariate generalized linear model results (deviation test statistic, p-value) of insect abundance examining taxa response to salvinia cover and month. Salvinia Cover Month Order Family Taxon Dev. p Dev. p Coleoptera Dytiscidae Brachyvatus sp. 14.52 0.035 21.29 0.002 Dytiscus sp. 3.43 0.473 5.91 0.556 Eretes sp. 29.34 0.001 13.06 0.089 Laccophilus sp. 26.78 0.001 10.97 0.157 Coleoptera Halplidae Peltodytes sp. 7.20 0.220 0.36 0.964 Coleoptera Hydrophilidae Berosus sp. 60.57 0.001 15.42 0.036 Helocombus sp. 12.40 0.050 20.50 0.003 Laccobius sp. 42.04 0.001 24.55 0.001 Tropisternus sp. 41.59 0.001 11.99 0.123 Coleoptera Noteridae Hydrocanthus sp. 13.98 0.035 7.59 0.348 Coleoptera Scirtidae Scirtes sp. 175.89 0.001 30.45 0.001 Diptera Ceratopogonidae Probezzia sp. 4.82 0.473 2.17 0.964 Diptera Chironomidae -- 46.98 0.001 12.01 0.123 Diptera Culicidae -- 29.85 0.001 14.08 0.072 Ephemeroptera Baetidae Fallceon sp. 14.39 0.032 4.49 0.738 Hemiptera Hebridae Hebrus sp. 10.56 0.074 9.32 0.241 Hemiptera Notonectidae Buenoa sp. 68.37 0.001 1.93 0.964 Odonata Aeshnidae Anax sp. 54.73 0.001 24.05 0.001 Odonata Coenagironidae Coenagrion sp. 26.22 0.001 9.02 0.241 Odonata Corduliidae Cordulia sp. 11.74 0.065 51.59 0.001 Odonata Libellulidae Erythemis sp. 76.40 0.001 10.13 0.199 Sympetrum sp. 113.11 0.001 12.44 0.110 Note: Taxon names are italicized for proper nomenclature.
1993). The first axis presumably explained community differences between 100% salvinia cover and the other cover treatments. The second axis likely explained community differences between 0% salvinia cover and the two-remaining salvinia cover treatments, 25% and 50%. Salvinia cover, month, and the interaction of cover with month (ADONIS F = 3.48, R2 = 0.11, p < 0.01), explained variation in aquatic insect communities. Habitat association analyses identified Buenoa sp. (Hemiptera) and Eretes sp. (Coleoptera) as associated with 0% salvinia cover; Laccophilus sp. (Coleoptera), Laccobius sp. (Coleoptera), Hydrocanthus sp. (Coleoptera), and Erythemis sp. (Odonata) with the 25% or 50% cover treatments, and Scirtes sp. (Coleoptera) with 100% salvinia cover (Table B.3). Similarity percentages (SIMPER) identified 73.3% dissimilarity between 0 and 100% cover groups, 71.2% dissimilarity between 0 and 25% cover groups, and 71.8% dissimilarity between 0 and 50% cover groups. Additionally, SIMPER identified 64.4% dissimilarity between 25 and 50% cover groups, 66.7% dissimilarity between 25 and 100% cover groups, and 67.2% dissimilarity between 50 and 100% cover groups.
Discussion
This mesocosm research provided evidence that salvinia changed environmental conditions, including available habitat, and limited aerial colonization when a full mat was present, resulting
37 in assemblages containing fewer individuals and lower richness of aquatic insects. Giant salvinia was stacked upon itself in 100% cover and formed a mat three plants thick. A decrease in aquatic insect abundance and richness, with increased salvinia cover, supported the hypothesis, but aerial colonization was impeded only when salvinia covered 100% of the water surface. The 0 and 100% salvinia coverages contained unique aquatic insect assemblages, while 25 and 50% coverages yielded communities there were similar but different from the other treatments.
Figure 4.1. Nonmetric multidimensional scaling (NMDS) ordination plot of aquatic insect assemblage similarity collected from salvinia coverages from outdoor mesocosms located in Baton Rouge, Louisiana. Points are individual samples and distance between points represents assemblage similarity with most similar samples being located closest together. Colors reflect percent salvinia cover treatments 0% (black), 25% (blue) 50% (green) and 100% (red). Circles represent 95% confidence interval around the centroid for salvinia cover groups, and a line connects sites furthest from the centroid within a group. Analysis of deviance (ADONIS) identified significant differences in community similarity (ADONIS F = 3.48, R2 = 0.11, p < 0.01), identifying three different communities, 0, 25-50, and 100% community groups.
Individual taxa responded to salvinia cover treatments differently. Chironomidae (Diptera) is an abundant and common aquatic insect in freshwater wetlands (Kang and King 2013, Mercer et al. 2017, Weller and Bossert 2017) and had the highest abundance in the 0%
38 salvinia cover; however, their abundance decreased when salvinia was introduced. This decline may have been due to changes in environmental conditions, or to increased predation on Chironomidae, which could be supported by the observed increased abundance of predators, Erythemis sp., Sympetrum sp., and Anax sp., (Odonata) in the 25-50% coverage group. Relative to an open system, the size of the mesocosms limits the amount of habitat, thus insets may not be able to evade predation as effectively as in natural conditions. The increase in predator abundance in both 25% and 50% coverage treatments could have been made possible by an increase in habitat (Huikkonen et al. 2019). The only taxon to be positively associated with salvinia, specifically 100% cover, was Scirtes sp. (Scirtidae: Coleoptera), which has been found in Salvinia minima Baker in southern Louisiana (Parys et al. 2013). Individuals in the Scirtidae family feed on fine particulate organic matter and decaying plant material, such as herbaceous and wood detritus; additionally, larvae breath atmospheric air and have terrestrial life phases (Ruta et al. 2018, Watts and Zwick 2019). Thus, salvinia could be a food source and provide access to atmospheric air for Scirtes sp. Salvinia mats reduce horizontal light reflection, especially later in the growing season when multiple plant layers are present, thus adults may not recognize the aquatic environment leading to fewer number of taxa colonizing the habitat. Most aquatic insects are polarotactic, attracted to reflected light, and adults detect water surface through horizontal polarization of light reflected from the water surface (Schwind 1995, Horváth and Csabai 2014, Heinloth et al. 2018). Light reflecting horizontally off the water has a high degree of linear polarization giving it a dark appearance, which attracts adult aquatic insects (Horváth 1995, May 2019). Therefore, artificial objects with reflective surfaces, such as dark colored cars, oil, and solar panels, attract adult aquatic insects attempting to colonize the surface (Kriska et al. 2006, Száz et al. 2016). The detection of water varies with aquatic insects, with some species of dragonflies (Odonata) being able to detect open water at lower degrees of linear polarization than species of Ephemeroptera and Diptera (Krista et al. 2009). Habitat complexity differences among cover treatments may also explain variation in aquatic insect community structure. Ordination analysis identified three different aquatic insect groupings, which relate to habitat complexity. The 0 and 100% salvinia covers contain one habitat type, coontail or salvinia, while 25-50% coverages had both habitat types present. Increased habitat complexity, due to the addition of salvinia with coontail, offers additional niches, promoting species coexistence through reduced competition (Huston and DeAngelis 1994, Smith et al. 2014, Casartelli and Ferragut 2018), and increased refuge from predation (Diehl and Kornijów 1998, Wolters et al. 2018). At moderate densities, invasive floating plant Eicchornia crassipes Martius (water hyacinth) has shown to increased abundance and diversity of aquatic invertebrates, due to increased habitat heterogeneity and complexity provided by the plant (Villamagna and Murphy 2010). The flow of energy through the aquatic and adjacent terrestrial ecosystems could be impaired due to salvinia. The change in aquatic insect community structure, due to environmental filtering, has been observed in salvinia (Motitsoe et al. 2020), and other floating invasive macrophytes, such as Lemna minuta Kunth (duckweed; Ceschin et al. 2020), Pistia stratiotes L. (water lettuce; Coetzee et al. 2019), and P. crassipes (Coetzee et al. 2014). Invasion of P. crasspies has shown to impact food web structure through bottom-up processes because of alterations to phytoplankton, macrophyte, and macroinvertebrate communities (Schultz and Dibble 2012, Wang and Yan 2017). Fish and waterfowl select habitat based on aquatic insect abundance (Little and Budd 1992, Diehl and Kornijów 1998, Tománková et al. 2013, Schummer
39 et al. 2008), and wading birds select foraging locations based on fish abundance (Gawlik 2002, Kloskowski et al. 2010), thus, alterations to aquatic insect community structure could change habitat use and decrease ecosystem productivity. Reduction in aerial colonization could also result in a decreased ecosystem productivity as the insect community would not be replenished and further change community structure from uninvaded locations. Salvinia is a fast growing macrophyte that forms expansive mats and rapidly changes local environmental conditions. In favorable lake conditions, salvinia can double its biomass and surface coverage in 2-4 days (Finlayson 1984, Room and Thomas 1986, Johnson et al. 2010), with mats can covering hundreds of square meters of water within a couple months following introduction (Mitchell 1969, Mitchell and Tur 1975). Aquatic insects must cope with the sudden changes in water quality and habitat. This would presumably change environmental filtering and species interactions, leading to a change in aquatic insect community structure (Fisher and Kelso 2007, Thomaz et al. 2008, Calizza et al. 2017). Given the growth rate in unmanaged field conditions, invaded locations could quickly become 100% covered in salvinia, therefore, results from the 25-50% treatments represent ephemeral, transitional communities, which would ultimately give way to 100% salvinia mat. This study highlights impacts from salvinia that have not been previously examined. The presence of a full salvinia mat limited aquatic insect aerial colonization, resulting in structure that was different from the assemblage in the native submerged macrophyte. This change to the structure of this lower trophic level could have implications to energy flow in aquatic and adjacent terrestrial ecosystems, indicating larger implications from salvinia than previously understood. These results currently represent a local phenomenon, but the results should be explored further with additional research examining if similar results occur in other regions, or in a field setting, and how is energy transfer to higher trophic levels impacted by changes in community structure of aquatic insects. Evidence from this study, and invasive plant studies (e.g., Watkins et al. 1983, Villamagna and Murphy 2010), suggest that management to eradicate or suppress salvinia to low levels may conserve biodiversity and ecosystem services. The use of chemical and biological methods to control floating invasive plants has been successful restoring aquatic habitat (Coetzee et al. 2020b, Motitsoe et al. 2020).
40
CHAPTER 5. GENERAL CONCLUSION
Synthesis
Invasion of giant salvinia has significantly influenced the structure and function of freshwater marsh macrophyte communities. This research documented significant changes in environmental conditions and ecosystem structure in invaded habitats. Further, these changes were reflected in the abundance and species composition of resident macroinvertebrates. Effects of giant salvinia on macroinvertebrates in invaded marshes has had limited evaluation, and results from this dissertation help elucidate how this invasive plant can alter macroinvertebrate community abundance and composition, as well as potential energy and nutrient flow to higher trophic levels. Overall, giant salvinia reduced dissolved oxygen, pH and light availability and increased concentrations of orthophosphate and ammonium. Nutrients are a limiting factor for giant salvinia, thus internal nutrient loading, due to low dissolved oxygen conditions, is a way to provide resources to sustain infestations for prolonged. Following initial giant salvinia invasion in the field (Chapter 2), macroinvertebrate communities resembled those in native submerged macrophytes, but community structure shifted as infestation duration increased, resulting in a community populated by few taxa, primarily crustaceans. In the greenhouse mesocosm study (Chapter 3), Ceratophyllum demersum tolerated low light conditions, persisting under a complete giant salvinia mat for weeks, which has been observed with this submerged macrophyte and other free-floating invasive species. This coexistence of native and the invasive macrophytes may explain why macroinvertebrate communities in the field did not immediately shift following giant salvinia invasion (Chapter 2). Some taxa were able to tolerate changes in environmental conditions due to increased habitat structure; however, as C. demersum abundance decreased, individuals would have been subject to increased species interactions and an overall loss of available habitat. Invasion of giant salvinia limits submerged macrophyte, periphyton, and phytoplankton production, causing bottom-up effects, that alter energy flow through the ecosystem. Large, abrupt changes in ecosystem structure, leading to a reconfiguration of ecological states is known as a regime shift (Scheffer et al. 2001, Biggs et al. 2009). Ecosystems typically show resistance or a capacity to maintain a current state under rising environmental pressures due to ecological feedbacks that maintain ecosystem status (Harrison 1979, Capon et al. 2015), until disruptions are large enough to shift to another dominant state (Scheffer et al. 2001, Beisner et al. 2003a). Field data (Chapter 2) indicated a regime shift was progressing into the studied marsh given that given giant salvinia coverage increased for a longer period during the year or over successive years. Increased concentrations of orthophosphate and ammonium suggest internal nutrient availability by sedimentary nutrient release, which would reinforce the giant salvinia regime state (Netten et al. 2010). Once established, internal feedback loops may resist switching back to the submerged macrophyte state (Capon et al. 2015, Peeters et al. 2016). In the field study, giant salvinia was controlled biologically, which limited the spatial and temporal extent of the observed mat development. A cascading effect of giant salvinia establishment on habitat, physiochemistry, and ultimately on macroinvertebrate community structure could have a negative impact on energy and nutrient transfer in the marsh trophic web. Total macroinvertebrate energy value of macroinvertebrates in giant salvinia was significantly lower than native macrophytes, with
41 energetic valuing decreasing with increased infestation duration. In the mesocosm study (Chapter 4), giant salvinia impeded aerial colonization. The inability to complete their life cycle leads initially to reduced abundances and eventually to a diminished species pool, until giant salvinia is controlled. An additional mesocosm study was attempted examining how colonization and community structure were influenced by the combination of giant salvinia and the presence of predators, two fish species (Table B.4). However, due to timing of macroinvertebrate aerial colonization, an insufficient number of macroinvertebrates were collected for analysis before termination of the study. In the greenhouse study (Chapter 3), nutrient additions enhanced growth of giant salvinia, which accelerated environmental degradation, and it is speculated that locations with high nutrient waters may not have enough time for macroinvertebrate communities to recover before being reinvaded by giant salvinia. Fish and wading birds have been known to select habitat based on macroinvertebrate abundance (Gawlik 2002, Schummer et al. 2008, Kloskowski et al. 2010, Tománková et al. 2013), and the depleted macroinvertebrate densities would limit transfer of energy and nutrients to resident predators. Transfer of energy to terrestrial predators could be decreased as well. Emergence of macroinvertebrates would be limited to taxa that survived environmental changes and species interactions. Under field conditions (Chapter 2), the dominant taxa in giant salvinia were amphipods, which do not have a terrestrial life phase, thus their energy contribution to terrestrial predators would be reduced compared with aerially dispersing insects. Alterations in environmental conditions due to giant salvinia would also be detrimental to fish. Creation of hypoxic conditions as giant salvinia expands coverage would force fish to seek new locations with adequate dissolved oxygen, and anoxic conditions would eliminate most fish from the invaded location (Zhu and Wang 2013, Abdel-Tawwab et al. 2019). Despite anoxic conditions below the mat, a thin layer of dissolved oxygen may exist at the plant-water interface (Wahl et al. 2020) allowing small bodied fish to persist until dissolved oxygen concentrations increase. Assuming fish can exist under the mat, or may recolonize once environmental conditions return to pre-invaded levels, their food resources would be greatly reduced, which could hinder growth and fitness, and lower competitive and reproductive potential (Tessier and Woodruff 2002, Huss et al. 2008, Vrtílek and Reichard 2015). Biological control of giant salvinia may limit duration of giant salvinia invasion in southern Louisiana. Salvinia weevil geographic distribution is limited by climate, but it can successfully overwinter in the subtropical region of Louisiana, which has resulted in establishment of a sustainable population. A plant-herbivore relationship has developed in which giant salvinia experiences little herbivory at low weevil densities and is able to become established and grow. As the abundance of giant salvinia increases, salvinia weevils, given appropriate temperatures, will reproduce and increase population size, resulting in a control of mats in a few months. This herbivory allows the aquatic system to maintain a submerged macrophyte dominant state and restore historic water quality and macroinvertebrate communities. However, timing of this cycle may be of concern for resident macroinvertebrates. Locations invaded with giant salvinia in fall would likely be covered by a mat during spring and summer, resulting in delayed aerial colonization until mid-summer. Taxa that emerge and colonize early in the season may not be able to become established in locations covered with giant salvinia. Controlling giant salvinia, through mechanical, chemical, or biological options, is the best strategy to lessen environmental impacts and maintain biodiversity. Giant salvinia is a global threat to freshwater ecosystems and these data highlight additional consequences to
42 ecosystem productivity. Additionally, giant salvinia alters macroinvertebrate community structure and can impede completion of their life cycle, although submerged macrophyte and macroinvertebrate communities may not be immediately impacted from giant salvinia. Rapid management efforts to control giant salvinia may lessen the impacts on submerged macrophytes, macroinvertebrates, and higher trophic level interactions.
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APPENDIX A. SUPPLEMENTAL DATA FOR CHAPTER 2
Table A.1. List of taxa identified from quarterly sampling of giant salvinia and submerged aquatic vegetation in Cameron Parish, Louisiana. Taxa in bold were used in the caloric value analysis. Order Family Genus Amphipoda Gammaridae Gammarus sp. Amphipoda Hyalellidae Hyalella sp. Coleoptera Chrysomelidae Donacia sp. Coleoptera Dytiscidae Brachyvatus sp. Coleoptera Dytiscidae Dytiscus sp. Coleoptera Dytiscidae Hydroporus sp. Coleoptera Hydrophilidae Berosus sp. Coleoptera Hydrophilidae Laccobius sp. Coleoptera Hydrophilidae Tropisternus sp. Coleoptera Noteridae Hydrocanthus sp. Coleoptera Scirtidae Scirtes sp. Collembola -- -- Diptera Ceratopogonidae Dasyhelea sp. Diptera Ceratopogonidae Probezzia sp. Diptera Chironomidae -- Diptera Culicidae -- Diptera Dolichopodidae -- Ephemeroptera Baetidae Fallceon sp. Ephemeroptera Caenidae Brachycercus sp. Hemiptera Corixidae Neocorixa sp. Hemiptera Hebridae Hebrus sp. Hemiptera Naucoridae Pelocoris sp. Isopoda Asellidae Caecidotea sp. Isopoda Sphaeromatidae Sphaeroma sp. Lepidoptera Crambidae Parapoynx sp. Odonata Aeshnidae Anax sp. Odonata Coenagrionidae Coenagion sp. Odonata Coenagrionidae Enallagma sp. Odonata Libellulidae Erythemis sp. Odonata Libellulidae Macrothemis sp. Odonata Libellulidae Sympetrum sp. Trichoptera Hydroptilidae Orthotrichia sp. Trichoptera Hydroptilidae Oxyethira sp. Trichoptera Polycentropodidae Polycentropus sp. Decapoda Palaemonidae Palaemonetes sp. Trombidiformes -- --
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Figure A.1. Multivariate generalized linear model (MGLM) plots of (A) log transformed abundance against habitat types. The twelve most abundant taxa were examined. Black circle indicates giant salvinia habitat and red triangle indicates SAV. (B) residuals vs fits plot to check assumption of negative-binomial regression. (C) mean-variance plot.
45
APPENDIX B. SUPPLEMENTAL DATA FOR CHAPTER 4
Table B.1. Number of aquatic insects collected from field mesocosms sampling in Baton Rouge, Louisiana from 0, 25, 50, or 100% salvinia coverages. Order Family Genus 0% 25% 50% 100% Coleoptera Carabidae Chlaenius sp. 1 0 0 1 Coleoptera Dytiscidae Brachyvatus sp. 0 12 7 1 Coleoptera Dytiscidae Dytiscus sp. 3 1 0 1 Coleoptera Dytiscidae Eretes sp. 18 3 0 0 Coleoptera Dytiscidae Hydroporus sp. 0 0 2 0 Coleoptera Dytiscidae Laccophilus sp. 10 33 8 0 Coleoptera Halplidae Haliplus sp. 1 2 0 0 Coleoptera Halplidae Peltodytes sp. 4 0 0 1 Coleoptera Helophoridae Helophorus sp. 0 3 0 0 Coleoptera Heteroceridae -- 0 0 1 0 Coleoptera Hydraenidae Hydraena sp. 0 0 2 0 Coleoptera Hydrochidae Hydrochus sp. 0 1 0 0 Coleoptera Hydrophilidae Berosus sp. 277 121 68 8 Coleoptera Hydrophilidae Laccobius sp. 3 28 54 5 Coleoptera Hydrophilidae Tropisternus sp. 35 46 40 2 Coleoptera Hydrophilidae Helocombus sp. 0 1 8 0 Coleoptera Noteridae Hydrocanthus sp. 2 9 12 1 Coleoptera Noteridae Protnoterus sp. 0 1 1 0 Coleoptera Scirtidae Scirtes sp. 0 4 9 1136 Coleoptera Staphylinidae Pontamalota sp. 0 0 1 0 Diptera Ceratopogonidae Probezzia sp. 2 8 2 9 Diptera Chironomidae -- 1372 957 585 265 Diptera Culicidae -- 3 19 43 0 Diptera Stratiomyidae Odontomyia sp. 0 0 0 1 Diptera Tabanidae Tabanus sp. 0 1 0 0 Ephemeroptera Baetidae Fallceon sp. 20 15 25 0 Hemiptera Gerridae Limnoporus sp. 0 1 0 0 Hemiptera Hebridae Hebrus sp. 0 11 3 1 Hemiptera Hebridae Lipogomphus sp. 0 0 2 0 Hemiptera Mesovelidae Mesovelia sp. 1 0 0 0 Hemiptera Naucoridae Pelocoris sp. 0 0 2 0 Hemiptera Notonectidae Buenoa sp. 76 17 4 0 Hemiptera Veliidae Microvelia sp. 0 1 2 0 Odonata Aeshnidae Anax sp. 2 124 79 3 Odonata Coenagironidae Coenagrion sp. 0 42 8 2 Odonata Coenagironidae Ischnura sp. 0 0 1 0 Odonata Corduliidae Cordulia sp. 19 13 10 1 Odonata Libellulidae Erythemis sp. 120 528 1126 212 Odonata Libellulidae Sympetrum sp. 187 243 229 1 Trichoptera Hydroptilidae Orthotrichia sp. 1 1 0 0 Note: Bold represents taxon used in multivariate analyses. Taxon names are italicized for proper nomenclature
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Table B.2. Generalized linear model (GLM) comparison results [mean difference (diff.) z-ratio (z), standard error (SE), and p-value (p)] of taxa that had abundances explained by salvinia cover treatments, 0, 25, 50, and 100%. Taxon comp. diff. SE z p Brachyvatus sp. 0-25% -0.301 0.098 -3.013 0.01 25-100% 0.275 0.098 -2.816 0.03 Eretes sp. 0-25% 0.385 0.098 3.933 <0.01 0-50% 0.460 0.098 4.699 <0.01 0-100% 0.460 0.098 4.699 <0.01 Laccophilus sp. 0-25% -0.576 0.178 -3.209 <0.01 25-50% 0.625 0.178 3.508 <0.01 25-100% 0.825 0.178 4.630 <0.01 Berosus sp. 0-25% 4.160 1.270 3.288 <0.01 0-50% 5.610 1.270 4.433 <0.01 0-100% 6.990 1.270 5.519 <0.01 Laccobius sp. 0-25% -0.628 0.219 -2.867 0.02 0-50% -1.278 0.219 -5.835 <0.01 25-50% -0.650 0.218 -2.987 0.02 50-100% 1.225 0.218 5.629 <0.01 Tropisternus sp. 0-100% 0.845 0.237 3.561 <0.01 25-100% 1.100 0.236 4.667 <0.01 50-100% 0.950 0.236 4.030 <0.01 Hydrocanthus sp. 0-50% -0.252 0.092 -2.742 0.03 50-100% 0.275 0.092 3.012 0.01 Scirtes sp. 0-100% -28.360 2.440 -11.606 <0.01 25-100% -28.300 2.430 -11.657 <0.01 50-100% -28.175 2.430 -11.605 <0.01 Chironomidae sp. 0-50% 20.700 5.580 3.700 <0.01 0-100% 28.700 5.580 5.133 <0.01 25-100% 17.300 5.550 3.119 0.01 Culicidae 0-50% -1.001 0.309 -3.242 0.01 50-100% 1.075 0.307 3.504 0.03 Buenoa sp. 0-25% 1.519 0.278 5.456 <0.01 0-50% 1.844 0.278 6.623 <0.01 0-100% 1.944 0.278 6.982 <0.01 Anax sp. 0-25% -3.072 0.761 -4.034 <0.01 25-100% 3.025 0.756 3.999 <0.01 Coenagrion sp. 0-25% -1.042 0.316 -3.297 0.01 25-50% 0.850 0.314 2.706 0.03 25-100% 1.000 0.314 3.184 0.01 Erythemis sp. 0-25% -9.900 3.660 -2.703 0.03 0-50% -24.800 3.660 -6.786 <0.01 25-50% -14.900 3.640 -4.110 <0.01 50-100% 22.900 3.640 6.281 <0.01 Sympetrum sp. 0-100% 4.816 1.100 4.378 <0.01 (table cont’d)
47
Taxon comp. diff. SE z p 25-100% 6.050 1.090 5.535 <0.01 50-100% 5.700 1.090 5.215 <0.01
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Table B.3. Values (species scores) indicate taxa position along non-metric multidimensional scaling (NMDS) ordination axes and association with salvinia cover groups. Taxon NMDS1 NMDS2 Taxon NMDS1 NMDS2 Brachyvatus sp. -0.18677045 -0.13159477 Probezzia sp. 0.25852367 0.03172307 Dytiscus sp. 0.29200244 0.31704438 Chironomidae 0.09593278 0.22982120 Eretes sp. -0.47504686 0.74206255 Culicidae -0.30193120 -0.41913003 Laccophilus sp. -0.59263331 -0.23620258 Fallceon sp. -0.22799846 -0.03007147 Peltodytes sp. 0.21564620 0.64554649 Hebrus sp. -0.30923154 -0.33970082 Berosus sp. -0.30551485 0.27099722 Buenoa sp. -0.47209681 0.73890888 Laccobius sp. -0.03825539 -0.66453964 Anax sp. -0.24111020 -0.35139243 Tropisternus sp. -0.37200784 -0.19208508 Coenagrion sp. -0.26824183 -0.3763528 Helocombus sp. 0.09896457 -0.78277333 Cordulia sp. -0.21803458 -0.11355486 Hydrocanthus sp. -0.29930965 -0.58901784 Erythemis sp. 0.28056228 -0.06184869 Scirtes sp.* 1.07720919 0.03312056 Sympetrum sp. -0.33880197 0.05773646 Note: NMDS1 (axis 1) was positively correlated with 100% salvinia cover group, and NMDS2 (axis 2) was positively associated with 0% cover treatment and negatively associated with 25-50% cover group. Bold indicates taxa associated with a 0% cover, underline indicates association with combined 25-50% cover, asterisk indicates association with 100% salvinia cover, and none indicates no cover association. Taxon names are italicized for proper nomenclature.
Table B.4. Mean standardized aquatic insect abundance and richness per gram of dry plant biomass (±SD). Salvinia Cover Fish Abundance per g Richness per g (%) 0 None 3.77 (±2.88) 0.78 (±0.40) L. macrochirus 3.03 (±5.80) 0.46 (±0.43) G. affinis 1.83 (±1.56) 0.45 (±0.26) 25 None 2.98 (±3.95) 0.98 (±0.78) L. macrochirus 7.94 (±10.57) 0.75 (±0.64) G. affinis 3.40 (±3.82) 0.76 (±0.63) 50 None 3.14 (±4.97) 1.03 (±0.81) L. macrochirus 5.23 (±8.80) 0.97 (±0.89) G. affinis 4.77 (±7.09) 0.92 (±1.08) Note: This study was conducted from February through June 2020. Two giant salvinia cover treatments, 25%, and 50%, and a reference submerged macrophyte treatment, 0% cover, were examined in combination with two species of fish, Lepomis macrochirus Rafinesque and Gambusia affinis S. F. Baird and Girard, and a no fish treatment, none, (45 mesocosms = 3 coverages × 3 fish × 5 replicates). One individual from each fish species was placed in a mesocosm. Mean length and weight for L. macrochirus and G. affinis were 60.73 ±2.55 mm (±SD), 3.15 ±0.47 g, and 41.2 (±1.70) mm, 1.84 (±2.92) g, respectively (n=15). Aquatic insect communities were sampled monthly, over four months (180 samples = 45 mesocosms × 4 months).
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VITA
Charles Frederick Wahl grew up in northern Illinois in the town of Elburn. He attended Clemson University earning a Bachelor of Science degree in 2010 in Wildlife and Fisheries Biology. After completing his B.S., he took a research associate position at the University of Maryland, Baltimore County, which later provided an opportunity to attend graduate school, earning a Master of Science degree in Geography and Environmental Systems in 2016. He worked for the Louisiana Department of Wildlife and Fisheries for a year before accepting a research associate position at Louisiana State University in 2016, which has provided the opportunity to earn a Ph.D. in Renewable Natural Resources. He plans to continue to pursue his interest in research and aquatic ecology upon graduation.
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