Urban Land-Use Effects on Resident Saltmarsh Fish in the Gulf of Mexico by Madeline Wedge A thesis submitted to the Graduate Faculty of Auburn University In partial fulfillment of the Requirements for the Degree of Masters of Science Auburn, Alabama August 3, 2013 Keywords: saltmarsh, land-use, Cyprinodontiformes, fish community, liver, caloric density Approved by Christopher J Anderson, Chair, Assistant Professor of Forestry Stephen A Bullard, Assistant Professor of Fisheries Dennis DeVries, Professor of Fisheries ii ? ? ? ? Abstract Salt marshes are valuable ecosystems and provide a number of important services, including providing habitat for fish. Urban land-use has been shown to alter salt marshes through changes in the hydrology, sedimentation, and vegetation, but little is known about how urban land-use near salt marshes impacts fish. In this study I compared resident fish in urban and reference salt marshes in tidal creeks of Alabama and west-Florida. Reference creeks had very little surrounding development (<3.0 houses km shoreline -1 ) while urban creeks had ?30.0 houses km shoreline -1 . Fish were sampled seasonally for one year along salt marsh edges using baited minnow traps and results were used to characterize fish communities. In addition two common salt marsh resident fish, Fundulus grandis and Poecilia latipinna, were evaluated to determine the impacts of urban land-use on fish condition through Liver Somatic Index (LSI), caloric density, and tissue concentration of metal contaminants. To help interpret fish data, marshes also had various habitat attributes assessed including: plant species composition and biomass, sediment contaminants, slope, salinity, and temperature. Fish abundance and length-weight regressions were compared for common species in addition to characterizing fish communities at both urban and reference marshes. Fish communities varied with season, but reference creek communities were consistently dominated by Fundulus grandis. Urban creeks had higher abundance of other species including Poecilia latipinna, Fundulus confluentus, Gambusia holbrooki, and Adinia xenica. Length-weight relationships showed that F. confluentus, A. xenica, C. variegatus, and F. confluentus were larger at urban marshes, while G. holbrooki was smaller. iii ? Based on the results of a nonmetric multidimensional scaling (NMDS) ordination and a Poisson generalized linear model, urban and reference fish assemblages were significantly correlated with salinity, slope, and sediment contaminants. Condition measures showed F. grandis had lower LSI and caloric density at urban salt marshes compared to reference. However, P. latipinna did not have significantly different condition measures at urban salt marshes compared to reference. Both species showed seasonal patterns related to conditional measures that were likely related to reproduction and annual fattening cycles. Except for zinc, no significant differences were detected in metal concentration between urban and reference F. grandis and many metals associated with urban runoff (Cd, Cr, Pb) were below detection levels for fish from both creek types. Differences in fish condition, fish size and fish community at urban marshes are likely a result of an altered salinity regime and other habitat alterations. iv ? ? ? ? Acknowledgements I would like to thank my advisor Chris Anderson for his support and guidance throughout my masters work. I would also like to thank my advisory committee, Ash Bullard and Dennis DeVries for their advice and input on my research; special thanks to Dennis DeVries for use of his bomb calorimeters. I would like to express my gratitude for the Mcintire-Stennis Cooperative Forestry Program for funding this research. I am grateful for Elise Irwin for use of her boat and Scott Phipps for allowing us to use the Weeks Bay National Estuarine Reserve facilities. I would like to thank Mike Pitts, Dave Young, and the neighborhood associations of Emmanuel Heights, Graham Creek Estates, and Josephine Harbor for use of their boat ramps. My research would not have been possible without the help of many people in the lab and in the field, including Diane Alix, Dave Armstrong, Flynt Barksdale, Jeff Buckingham, Cody Cox, Tammy DeVries, Amanda Fletcher, Chris McKee, and Carlos Ruiz. Special thanks to Craig Roberts for all of his support through this process, including his help in the field and in the lab. v ? ? Table of Contents Abstract ........................................................................................................................................... ii Acknowledgements ........................................................................................................................ iv Table of Tables .............................................................................................................................. vi Table of Figures ............................................................................................................................ vii Chapter 1 ......................................................................................................................................... 1 Chapter 2 ....................................................................................................................................... 20 Introduction ............................................................................................................................... 21 Methods ..................................................................................................................................... 24 Results ....................................................................................................................................... 30 Discussion ................................................................................................................................. 35 Chapter 3 ....................................................................................................................................... 64 Introduction ............................................................................................................................... 65 Methods ..................................................................................................................................... 68 Results ....................................................................................................................................... 71 Discussion ................................................................................................................................. 72 Chapter 4 ....................................................................................................................................... 89 Appendix I .................................................................................................................................... 99 Appendix II ................................................................................................................................. 113 vi ? ? ? Table of Tables ? Table 2.1??????????????????????????????????58 Table 2.2??????????????????????????????????59 Table 2.3??????????????????????????????????60 Table 2.4??????????????????????????????????61 Table 2.5??????????????????????????????????62 Table 2.6??????????????????????????????????63 Table 3.1??????????????????????????????????85? Table 3.2??????????????????????????????????86 Table 3.3??????????????????????????????????87 Table 3.4??????????????????????????????????88 ? ?? vii ? ? ? Table of Figures ? Figure 2.1?????????????????????????????????.45 Figure 2.2?????????????????????????????????.46 Figure 2.3?????????????????????????????????.47 Figure 2.4?????????????????????????????????.48 Figure 2.5?????????????????????????????????.49 Figure 2.6?????????????????????????????????.50 Figure 2.7?????????????????????????????????.51 Figure 2.8?????????????????????????????????.52 Figure 2.9?????????????????????????????????.53 Figure 2.10????????????????????????????????..54 Figure 2.11????????????????????????????????..55 Figure 2.12????????????????????????????????..56 Figure 2.13????????????????????????????????..57 Figure 3.1?????????????????????????????????83 Figure 3.2?????????????????????????????????84 1 ? Chapter 1: Overview of Urban Land-use Impacts on Salt Marshes and Fish Salt marshes are intertidal wetlands dominated by herbaceous vegetation. They are found along sheltered coastlines, lagoons, river mouths, and bays throughout the world (Mitsch et al. 2009). Salt marshes are important ecosystems that provide a number of ecological services. These services include being a source of nutrients and organic matter to nearby coastal habitats, protecting coastlines from wave erosion, being a sink for certain nutrients/pollutants, and providing critical habitat for a variety of organisms, including fish (Kennish 2001). Fish have been shown to greatly benefit from salt marsh habitat with some species requiring salt marshes for their entire life while others require it just for certain life stages (Rozas and Minello 1998). These fish are often important food sources for marine mammals, picivorous birds, and other fish, including a number of economically important species (Raposa et al. 2003). The fish caught in the United States Gulf of Mexico are a significant part of both the commercial and recreational fisheries in the whole United States (Chesney et al. 2000). Therefore, alterations to salt marshes in the Gulf of Mexico could impact these fisheries, and thus have a significant effect on the livelihoods of people dependent on these resources. Coastal areas in the U.S. are experiencing large population growth, particularly in parts of the Gulf of Mexico (Wilson and Fischetti 2010), and this growth coupled with rapid development puts pressure on salt marshes (Beach 2002). Urban land-use has been shown to have a number of effects on salt marshes, including direct loss of marshes and alterations to marsh hydrology, sedimentation, and vegetation (Currin et al. 2010). These alterations can lead to degradation and indirect loss of salt marshes (Peterson and Lowe 2009). All of these alterations can result in changes to the salt marsh habitat, which consequently can impact the 2 ? organisms dependent on them. Because salt marshes provide valuable habitat for fish, Knowing how land-use affects them is important. Man-made structures often accompany urbanization, and these structures can impair salt marsh functioning. Canals and spoil banks can have serious hydrological impacts on salt marshes (Kennish 2001). Knott et al. (1997) found that canal construction in South Carolina caused a shift in fish community composition and a decrease in salt marsh resident Fundulus heteroclitus within the affected salt marsh. The authors hypothesized these results were due to the reduced Spartina alterniflora coverage caused by the construction (Knott et al. 1997). Similarly, a recently dredged channel had a similar fish community compared to a channel that was not dredged (Bilkovic 2011). However, fish and decapod crustaceans communities were similar in the shallow water and marsh surface of canals and natural channels in Louisiana salt marshes, which the authors thought was due to the similar structure of both canals and natural channels (Rozas 1992). In addition, dredge material levees were found to restrict fish and decapod crustacean access to high marsh in Louisiana (Reed et al. 2006). Also, Reed and Foote (1997) found salt marshes in Louisiana that were behind levees had significantly decreased sedimentation rates. Shoreline treatments, such as bulkheads and riprap, are often associated with urban land-use in estuarine systems. These shoreline alterations have been associated with declines in fish diversity and abundance (Bilkovic and Roggero 2008, Bradley 2011) and salt marsh loss (Kennish 2001). Hydrologic impacts can also prevent tidal inundation of salt marshes, which restricts access for fish and decapod crustaceans to the marsh (Harrington and Harrington 1982, Stolen et al. 2009). Urban land-use can also result in extreme salinity fluctuations in salt marshes (Shirley et al. 2005) and conversion from salt marsh to brackish marsh due to the increased freshwater 3 ? runoff (Greer and Stow 2003). The effect of shoreline development on hydrology was found to decrease soil salinity, which facilitated invasion by non-native Phragmites australis in Rhode Island (Silliman and Bertness 2004). Holland et al. (2004) found that salinity range, volume, and magnitude of fluctuations increased in tidal creeks when watershed impervious surface exceeded 10% in the Charleston, South Carolina area. Therefore even low amounts of development in the watershed can have impacts on the hydrology of a tidal creek, which in turn can alter the salt marsh habitat. Salinity was found to be one of the major abiotic factors associated with fish assemblages along an estuarine gradient in Texas (Gelwick et al. 2001). Thus any changes to salinity could result in altered fish communities based on salinity tolerance. However, there has been little work on linking changes in salinity regimes to salt marsh fish communities. Changes in marsh plant composition take a longer time than changes in fish communities, so alterations to the salinity regimes are likely to be seen first in the fish community. Urbanization near salt marshes can change sediment composition and sedimentation rates. Urban salt marshes tend to have coarser sediments due to increased runoff capable of transporting sandy, eroded soils into tidal creeks (Holland et al. 2004). Urbanization was correlated with increased sedimentation in California salt marshes (Mudie and Byrne 1980). Partyka and Peterson (2008) found higher percent total organic carbon and coarser sediments at urban salt marshes compared to reference marshes in Mississippi. Some benthic invertebrates avoid coarse sediments because they decrease sediment stability. Changes in the benthic invertebrate community could potentially reduce fish food sources (Partyka and Peterson 2008). When sedimentation becomes too low, vegetation can become too deeply submerged in water to grow, and salt marsh is lost (Mattheus et al. 2010). This loss of marsh can isolate salt marshes as connectivity decreases and distance between remaining marshes increases, which can 4 ? cause changes in species assemblages. Species richness and resident fish abundance was lower at small salt marshes disconnected from upland habitat compared to marshes connected to land (Meyer 2006). F. heteroclitus had limited occurrence in isolated marshes which suggested they are limited in their dispersal ability (Meyer and Posey 2009). Isolation can also cause changes in the benthic invertebrate communities and decreased species richness (Partyka and Peterson 2008). Thus isolation can ultimately change fish communities dependent on salt marshes. Urban land-use is also often associated with an increase in pollutants such as polychlorinated biphenyls (PCBs), petroleum aromatic hydrocarbons (PAHs), metals such as mercury and lead, and pesticides. Van Dolah et al. (2008) found higher concentrations of pollutants in sediments from urban salt marshes in South Carolina. Pollution in a Florida estuarine system resulted in lower estuarine fish species richness, and most species avoided the polluted areas except for a few detritivore species (Felley and Felley 1986). In coastal habitats of the Mississippi Delta, oil contamination resulted in a higher proportion of more tolerant species making up the fish and decapod crustacean community and resulted in high accumulation of petroleum hydrocarbons in benthic organism tissues (Ko and Day 2004). Similarly, Roth (2009) found fish and decapod crustacean abundance decreased in Louisiana salt marshes exposed to oil, which the author thought was due to the more mobile, transient species leaving the salt marsh. In addition, salt marsh vegetation can change in composition (Bertness et al. 2009, Wigand et al. 2003) and density (Darby and Turner 2008) due to increased nutrients from nearby urban land-use. For instance, eutrophication gave Spartina alterniflora a competitive advantage over Juncus roemerianus in Georgia salt marshes (McFarlin et al. 2008). Invasive P. australis was also more common in marshes with increased nutrient availability and shoreline development (Silliman and Bertness 2004). In contrast, fish abundance and species richness were 5 ? actually found to increase with higher nitrogen loadings (Wigand 2008). However, eutrophication can lead to hypoxia, which has been shown to have a number of negative effects on fish, including death, reduced growth, and reduced reproduction (Brouwer et al. 2005, Breitburg et al. 2009). Thus, fish responses to urban land-use are likely a complex interaction between habitat deterioration (e.g. increased pollutants and altered hydrology) and possible benefits (e.g. increased food availability due to high nutrient loads). Extensive work in freshwater streams has shown that urban land-use within a watershed is linked with decreased fish diversity (Helms et al. 2005, Slawski et al. 2008, Weaver and Garman 1994, Meador et al. 2005, Fitzpatrick et al. 2004) and abundance (Zampella and Bunnell 1998, Weaver and Garman 1994) as well as shifts in fish community composition (Weaver and Garman 1994, Helms et al. 2005, Roy et al. 2005, Wang et al. 2007). However, studies in estuarine environments are not as numerous as their freshwater counterparts. The few studies that have been done in salt marshes have found similar trends to freshwater studies. Urbanization near salt marshes was associated with different fish communities (Felley and Felley 1986), lower abundance (Peterson et al. 2000), and lower prey diversity and abundance (Sanger et al. 2004, Lerberg et al. 2000, Washburn and Sanger 2011, Lawless 2008). Fish diversity was lower at bulkhead and rip-rap compared to unmodified shoreline (marshes) in Maryland (Seitz et al. 2006). Partyka and Peterson (2008) also found lower species richness of fish and decapod crustaceans at hardened shorelines compared to marsh in Mississippi. Larval fish were smaller in size at hardened shorelines in Mississippi (Peterson et al. 2000). Bilkovic and Roggero (2008) determined a threshold of 23% of developed land-use within 200 m and 1000 m of a shoreline before seeing a decline in diversity in the fish and decapod crustacean community. However, this study was also looking at hardened shorelines, so the threshold may not be the same for salt 6 ? marshes that are in developed areas. Most of these studies have looked at comparing alternative habitats to salt marshes, not salt marshes within an urban landscape. How urban land-use potentially altesr the quality of salt marsh habitat for fish is unknown. Fish using salt marshes can be divided into two general groups: transients and residents. These two groups tend to use salt marshes in different ways. Transients use the marsh intermittently and have less habitat specificity than residents, using a variety of estuary habitats (Rountree and Able 2007, Meyer and Posey 2009). Because they are habitat generalists, they are not as strongly influenced by environmental change in one habitat and often are not tied developmentally to salt marshes (Thom et al. 2004, Nordlie 2003). They typically require a subtidal refuge to escape low water levels and are usually not found in marshes at low tide as a result (Able et al. 2008, Kimball and Able 2007). Because of this refuge need, transients are not able to use the marsh for the full high tide given that they need time to travel to and from their low tide refuge to the marsh. The distance between the two can be critical in how much transients can use the marsh as well (Kneib and Wagner 1994). For this reason many transients only use the marsh edge or adjacent subtidal habitats (Peterson and Turner 1994). This restriction also explains the tendency for salt marshes to have higher diversity and abundance of fish at high tide (Kneib and Wagner 1994). Common transients in the Gulf of Mexico include red fish (Sciaenops ocellatus), pinfish (Lagodon rhomboides), spot (Lieostomus xanthurus), and speckled trout (Cynoscion nebulosus). In contrast, resident fish species, particularly species like Fundulus grandis, associate with the salt marsh their whole lives. Residents often rely on marsh pools and upper reaches of tidal creeks and regularly use the actual marsh surface for foraging (Raposa 2008, Peterson and Turner 1994). Residents also tend to have small home ranges, which can include just one marsh (Skinner et al. 2005). Residents are also prey for a number of the transient 7 ? fish species, and are important in connecting the productivity of salt marshes to the larger estuarine system (Valiela et al. 1977, Stout 1984). Despite these differences, both types of species will use salt marshes for food and shelter (Rountree and Able 2007, Able et al. 2008). However, when assessing changes in salt marsh habitat, residents can be more informative because they rely on the marsh their entire lives and thus better reflect changes in the habitat through changes in abundance, size, and condition. F. heteroclitus, a salt marsh resident found along the Atlantic Coast, has been used as a bioindicator species for human impacts on salt marshes and other estuarine environments in a number of studies (Finley et al. 2009, Nacci et al. 2010, LeBlanc et al. 1997, Pait and Nelson 2009, Goto and Wallace 2010). Linking transient fish health and abundance to salt marshes is more difficult, and often studies are limited to stating the presence or absence of these fish as an indicator of salt marsh habitat quality (Rozas 1992, Bilkovic 2011, Seitz et al. 2006). Thus, for this study cyprinodontiform salt marsh residents will be used to assess the difference in habitat quality between urban and reference salt marshes. In this study I focused on the impacts of urban land-use on Cyprinodontiformes in salt marshes dominated by Juncus roemerianus (black-needle rush, henceforth Juncus) in the Gulf of Mexico. These marshes are common along the coasts of Mississippi, Alabama, and western Florida (Stout 1984). While there have been a few studies on how urban land-use affects fish and salt marshes in the Gulf of Mexico (Partyka and Peterson 2008, Hendon et al. 2000, Peterson et al. 2000), none have looked at Juncus marshes. Cyprinodontiformes make up the majority of the resident species in Juncus marshes (Stout 1984), making them ideal for studying habitat quality and community dynamics. 8 ? Two of my study species, Fundulus grandis and Poecilia latipinna, are abundant resident salt marsh Cyprinodontiformes in the Gulf of Mexico (Boschung and Mayden 2004, Lee et al. 1980). Both species have a wide salinity tolerance (F. grandis: 0-76 ppt, P. latipinna:0-90 ppt) and a high tolerance for hypoxic conditions (Landry et al. 2007, Timmerman and Chapman 2004). F. grandis reaches an adult size of 70-138 mm and is a generalist feeder, consuming plant matter, invertebrates, and small fish (Boschung and Mayden 2004, Lee et al. 1980). P. latipinna has an adult size of 15-150 mm and feeds primarily on algae, detritus, and mosquito larvae (Lee et al. 1980). F. grandis and P. latipinna are capable of spawning multiple times in one year, although P. latipinna is a livebearer while F. grandis is not (Nordlie 2000, Boschung and Mayden 2004). Not much research has been done on using F. grandis as a bioindicator species for the northern Gulf of Mexico. However, it has been used to study the toxicity of oil and oil dispersants (Liu et al. 2006, Ernst et al. 1977, Russel and Fingerman 1984). Fingerman (1980) found that F. grandis fin regeneration in response to fuel oil exposure varied with season. Liu et al. (2006) found F. grandis had a high survival rate when exposed to oil for 24hrs in a field setting but were sensitive to oil in low dissolved oxygen conditions in the lab. Although F. grandis has not been studied extensively outside of toxicology, the closely related Fundulus heteroclitus has been well studied. F. heteroclitus has been used as a bio-indicator for point- source pollution in Canada due to its high site fidelity and great abundance (Skinner et al. 2005, Finley et al. 2009). F. grandis is also thought to have high site fidelity, or small home range, because the two species are closely related (Lee et al. 1980). This small home range may mean that salt marsh fragmentation, a common effect of urban land-use, can restrict F. grandis movement between marshes, which can impede gene flow, as well as leave populations 9 ? vulnerable to extirpation (Meyer and Posey 2009). Many studies have looked at the impacts of habitat conditions on F. heteroclitus populations. For instance, F. heteroclitus in a polluted marsh in New York had reduced growth rates, higher metabolic rates, and higher food consumption (Goto and Wallace 2010). Small F. heteroclitus were also lacking in a New Jersey marsh dominated by the invasive species, Phragmites australis, which is likely due to the lack of standing water at low tide on the marsh surface (Hagan et al. 2007). In a restored salt marsh F. heteroclitus were found to have similar growth, abundance, and reproduction compared to natural marshes (Teo and Able 2003). Thus, F. heteroclitus has proven to be a useful indicator of salt marsh quality and fish community health. Other marsh residents have been used for land-use studies as well, including Gobiosoma bosc and Gillichthys mirabilis. They were found to be less abundant (Hendon et al. 2000), smaller, and have higher mortality rates within urban salt marshes than reference marshes (McGourty et al. 2009). P. latipinna is similar to F. grandis in that it has been less researched as a bioindicator although its mating habits have been extensively studied (Meffe and Snelson 1993, Schlupp and Ryan 1997, Ptacek and Travis 1997, Witte and Ryan 1998, Witte and Ryan 2002), and it has also been used for toxicity studies involving pesticides. These studies determined the lethal dose of the pesticides, and argued for using P. latipinna because it was an abundant fish in freshwater and estuarine environments that were likely to have high concentrations (Lane and Livingston 1970). Benton et al. (1994) studied the sub-lethal effects of DDT on P. latipinna and found that DDT caused decreased growth and lipid storage. P. latipinna?s tolerance to extreme salinity ranges has also been studied. In hypersaline conditions above 70 ppt, P. latipinna had increased concentrations of plasma ions and high metabolic rates, but below that the fish were able to maintain normal concentrations (Gonzalez et al. 2005). Surprisingly, growth was never affected 10 ? even at the highest salinity concentrations of 90 ppt. McManus and Travis (1998) found no effect from salinity on male P. latipinna growth or maturation. However, rapid changes in salinity, especially from salt water (35 ppt) to freshwater, had detrimental effects on fish growth and resulted in 40% mortality (Backman and Rand 2008). Similarly, over winter survival was higher in salt marshes than freshwater marshes and for larger individuals, possibly because P. latipinna does not osmoregulate efficiently in freshwater (Trexler et al. 1992). This sensitivity to freshwater could be important if salinity is reduced in marshes due to increased freshwater run- off from nearby urban areas. Rapid decreases in salinity are also likely to occur in urban salt marshes given that storm events in urban areas tend to result in rapid freshwater inputs due to storm run-off (Holland et al. 2004). P. latipinna has also been used for assessing habitat quality (Troutman et al. 2007, Gelwick et al. 2001, Stolen et al. 2009). Since urban land-use can result in marsh fragmentation, this suggests that fragmented salt marshes may also have lower P. latipinna densities than continuous marsh. In this study I will focus on assessing changes in salt marsh residents F. grandis and P. latipinna size distributions, abundances, and condition. Condition will be measured through length-weight regressions, liver somatic index, and caloric density as measured by bomb calorimetry. While condition measures can vary seasonally, they have been shown to be useful in environmental monitoring (Leamon et al. 2000, Galloway and Munkittrick 2006). F. heteroclitus has also shown lower LSI scores and smaller average length and weight at highly impacted urban sites (Ferraro et al. 2001). Similarly, lower lipid levels were found in F. heteroclitus at a restored marsh compared to a reference marsh (Weinstein et al. 2009). In addition, F. grandis pollution exposure in a tidal creek receiving industrial and treated wastewater inputs was assessed using liver enzymes (Schoor et al. 1988). Caloric density and fish body weight were 11 ? lower in Oncorhynchus gorbuscha (pink salmon) when exposed to oil for 40 days in a laboratory experiment (Moles and Rice 2012). Caloric density was also lower in Coregonus hoyi (bloater) in Lake Superior compared to Lake Michigan (Vondracek 1996). F. heteroclitus had different caloric densities with different diets (Weisberg and Lotrich 1982). In addition, cyprinodontiform community structure, which includes F. grandis, P. latipinna, and other salt marsh residents (Lee et al. 1980), will be assessed. The results of this study will be useful in assessing urban impacts on other Juncus-dominated salt marshes. Also, this study will further our understanding of how altering habitat and prey sources of commercial fish due to increasing human populations in coastal areas will affect local fisheries. I identified 3 major goals for this research: ? Determine the effects of urban land-use on salt marsh habitat for fish through changes in the cyprinodontiform community. ? Determine if salt marsh residents Fundulus grandis and Poecilia latipinna exhibit differences in size and abundance in urban salt marshes compared to populations in reference salt marshes. ? Analyze F. grandis and P. latipinna condition through length-weight regressions, liver somatic index, and caloric density at urban salt marshes compared to fish condition at reference salt marshes. 12 ? Literature Cited Able, K.W., T.M. Grthues, S.M. Hagan, M.E. Kimball, D.M. Nemerson, and G.L. Taghon. 2008. Long-term response of fishes and other fauna to restoration of former salt may farms: multiple measures of restoration success. 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Ecological Applications 8(3):645-658. 20 ? Chapter 2: Urban Land-use Effects on the Resident Fish Community in Alabama and West-Florida Salt Marshes Abstract Urban land-use has been shown to impact salt marshes. However how this may change salt marsh habitat for fish species is unknown. In this study I compared resident fish in urban and reference salt marshes in tidal creeks of Alabama and west-Florida. Reference creeks had very little surrounding development (<3.0 houses km shoreline -1 ) while urban creeks had ?30.0 houses km shoreline -1 . Fish were sampled seasonally for one year along salt marsh edges using baited minnow traps and results were used to characterize fish communities. To help interpret fish data, marshes also had various habitat attributes assessed including: plant species composition and biomass, sediment contaminants, slope, salinity, and temperature. Fish abundance and length- weight regressions were compared for common species in addition to characterizing fish communities at both urban and reference marshes. Fish communities varied with season, but reference creek communities were consistently dominated by Fundulus grandis. Urban creeks had higher abundance of other species including Poecilia latipinna, Fundulus confluentus, Gambusia holbrooki, and Adinia xenica. Length-weight relationships showed that F. confluentus, A. xenica, C. variegatus, and F. confluentus were larger at urban marshes, while G. holbrooki was smaller. Based on the results of a nonmetric multidimensional scaling (NMDS) ordination and a Poisson generalized linear model, urban and reference fish assemblages were significantly correlated with salinity, slope, and sediment contaminants. 21 ? Introduction Human populations in coastal areas of the United States have nearly doubled from 1960 to 2008 (Wilson and Fischetti 2010), and increasing populations have exerted greater pressure on the natural resources found in coastal areas (Beach 2002). One impact is a corresponding increase in land classified as urban land-use, which is projected to nearly triple from 2000 to 2050 (Nowak and Walton 2005). Urban land-use encompasses a wide range of conditions from commercial use to suburban neighborhoods and has been shown to have a number of hydrologic effects on tidal creeks. For example, salinity in tidal creeks has been shown to increase in range and magnitude of fluctuations with impervious surface cover above 10-20% of the watershed (Holland et al. 2004). This pattern is caused by impervious surfaces increasing the amount of surface runoff received by tidal creeks, which increases the amount of freshwater input. Also, urban land-use has been found to increase pollutant loads (Van Dolah et al. 2008), change sedimentation rates and composition (Reed et al. 2006, Partyka and Peterson 2008) and erode stream channels (Walsh et al. 2005). These watershed level changes caused by increasing urban development can also impact salt marshes within tidal creeks. Urban land-use has been linked to the direct loss of salt marshes (Currin et al. 2010), as well as changing plant communities within salt marshes by altering competition associated with increased nutrients (McFarlin et al. 2008), facilitating invasion of non-native plants (Bertness et al. 2009), and altering plant density and height (Wigand et al. 2003). Lower salinities associated with urban land-use can also convert salt marsh plant communities to plant assemblages composed of more freshwater or brackish species (Greer and 22 ? Stow 2003). By replacing or altering salt marshes, urbanization may result in very different habitats than non-impacted marshes and ultimately affect the organisms dependent on them. Estuarine fishes are one group of organisms that rely on salt marshes (Boesch and Turner 1984). Over 90% of the economically valuable fish in the United States are considered estuarine dependent (Chambers 1992). Because urban land-use may influence salt marshes it may also impact these valuable fish species by altering the habitat provided by salt marshes. Urban impacts to fish habitat may occur from the structural and/or vegetation changes in the salt marsh. Phragmites australis is an invasive plant species to the salt marshes in the United States often associated with urban disturbance, lower salinity and increased nutrients (Silliman and Bertness 2004) and has been shown to correspond to lower quality habitat for fish. For instance, no young Fundulus heteroclitus, a common small fish found in Atlantic salt marshes, were found in a New Jersey marsh dominated by P. australis while reference marshes had young F. heteroclitus (Hagan et al. 2007). Several studies have found that hardened shorelines, (i.e., bulkheads, riprap) which are common to developed shorelines, are associated with declines in fish diversity and abundance relative to vegetated shorelines (Partyka and Peterson 2008, Bilkovic and Roggero 2008, Bradley 2011, Peterson et al. 2000). Also, developing shorelines can fragment and isolate salt marshes, which can cause changes in fish assemblages based on the species? dispersal ability (Meyer and Posey 2009). Bilkovic and Roggero (2008) found a correlation between increased urban land-use within a 100 m radius of the shoreline and changes in fish and decapod crustacean communities, although this relationship was confounded by shoreline type. Significant changes to marshes (plant species, fragmentation) and shorelines clearly cause habitat changes to fish. However, urban effects may exist where salt marshes are still relatively intact, but this has not been studied. 23 ? To understand potential urban impacts, the differences in fish species use of the marsh are important to note. Fish species use salt marsh in two different ways. Some fish species use salt marshes as a part of a suite of estuarine habitats, while others use salt marshes as their primary habitat. Species in the order Cyprinodontiformes that live in salt marshes depend on the marshes their entire lives and are considered salt marsh residents (Stout 1984). Like other residents, these Cyprinodontiformes are food for a variety of bird and predatory fish species, including economically valuable species such as red fish (Sciaenops ocellatus), and provide an important link between marsh productivity and estuarine waters (Stout 1984). A high diversity of Cyprinodontiformes reside in marshes, and high diversity has been shown to increase stability of fish communities (Franssen et al. 2011).Their close association with salt marshes makes Cyprinodontiformes and other resident fish well suited for use as an indicator of salt marsh habitat quality (Finley et al. 2009). Studies that have looked at urban land-use impacts on individual resident species have often found decreased abundances (Hendon et al. 2000), smaller sizes, and higher mortality rates (McGourty et al. 2009). F. heteroclitus had reduced growth rates, higher metabolic rates, and higher food consumption in a polluted urban marsh in New York compared to a reference marsh (Goto and Wallace 2010). Although evidence of an urban effect on fish certainly exists, not all studies have detected impacts. Holland et al. (2004) found no relationship between watershed impervious surface cover and F. heteroclitus abundance in South Carolina salt marshes. However, few studies have looked specifically at resident communities, specifically Cyprinodontiformes, which may be particularly sensitive to land-use change. In this study I focused on the impacts of urban land-use on Cyprinodontiformes in salt marshes dominated by Juncus roemerianus (black-needle rush, henceforth Juncus) in the Gulf of 24 ? Mexico. These marshes are common along the coasts of Mississippi, Alabama, and western Florida (Stout 1984). While there have been a few studies on how urban land-use affects fish and salt marshes in the Gulf of Mexico (Partyka and Peterson 2008, Hendon et al. 2000, Peterson et al. 2000), none have looked at Juncus marshes. Cyprinodontiformes make up the majority of the resident species in Juncus marshes (Stout 1984), making them ideal for studying habitat quality and community dynamics. The objectives for this study were to determine the effects of low- to medium-density urban land-use on salt marsh habitat and resident fish through the following measures: 1) various salt marsh habitat attributes (plant biomass, marsh slope, sediment conditions) and their relation to cyprinodontiform communities, 2) the composition of the cyprinodontiform communities compared to reference marshes, and 3) the size and abundance of various cyprinodontiform species compared to reference marshes. I hypothesized that the diversity of Cyprinodontiformes would be lower at urban marshes compared to reference marshes. I also hypothesized that size and abundance of species with a higher salinity preference would be lower at urban marshes while those with a lower salinity preference would be larger and more abundant. Methods Site Descriptions To evaluate the effect of urbanization on salt marsh fish along the northern Gulf of Mexico, I examined numerous tidal creeks (urban and non-urban) throughout coastal Alabama and the west-Florida Panhandle. To minimize confounding factors, creeks were selected to have a similar watershed size, have several Juncus-dominated salt marshes near the mouth, similar salinity range (based on occurrence of Juncus), and have similar land-use and shoreline 25 ? characteristics within each treatment (urban, reference). Based on this criteria six second-order tidal creeks (three urban and three reference) were selected along the Alabama and Florida coast (Fig. 2.1). Two reference creeks, Long Bayou and Graham Creek, flow into Wolf Bay in Baldwin County, Alabama. Emmanuel Bayou (urban), Stone Quarry Bayou (reference), and Weekley Bayou (urban) flow into Perdido Bay, and Grande Bayou (urban) flows into Pensacola Bay. Urban land use in the study area is typically low- to medium-density residential development, consisting of single family homes and many boat docks on along tidal creeks. To characterize the extent of urban land-use, USGS aerial photos (2004) were used to calculate urban measures within the 500m radius of a central point along the lower reach of each creek. Measures were validated in the field and adjusted for newer development observed. The number of houses counted inside the 500m-radius was used to determine house density (houses ha -1 ) as well as the mean number of houses per km of shoreline. Mean number of boat slips per km shoreline (an indicator of shoreline disturbance and pollution) were also enumerated. Road area (m 2 ha -1 ) was calculated by determining the total length of road multiplied by the mean width of the roads within the 500m radius. Road density was the total length of road per hectare. Based on surrounding urban conditions (Table 2.1) Long Bayou, Graham Creek, and Stone Quarry Bayou were classified as reference creeks, having a housing density of <3.0 houses km shoreline -1 and a road density of <10.0 m ha -1 . Emmanuel Bayou, Weekley Bayou, and Grande Bayou were classified as urban. They had ?10.0 houses km shoreline -1 and >30.0m ha -1 road density. Four salt marshes closest to the creek mouth were selected for sampling, except for Emmanuel Bayou which only had three Juncus marshes. 26 ? Creek and Marsh Physio-Chemical Measures To provide indications of marsh habitat, various biotic and physiochemical measures were made at each marsh. Water salinity (ppt) and water temperature (?C) were measured using a YSI 30 meter at the midpoint of each salt marsh during four seasonal sampling events between December 2011 and September 2012 (see fish sampling below). Between April 2012 and March 2013, a HOBO U24 conductivity logger was placed just below subtidal depth at each creek between the second and third marsh. Loggers were set to record every 5 minutes and data were averaged per hour for each creek. Vegetation Surveys Although all marshes were dominated by Juncus, marsh vegetation surveys were conducted to evaluate potential differences in minor species composition and overall structure (stem density, biomass). Differences in minor species abundance may indicate longer trends in salinity than that collected with the conductivity loggers. Surveys along the marsh water-edge consisted of percent cover of all species in 3 random 1-m 2 plots (only vegetation that exceeded 10% cover was reported). For a randomly selected 0.25m 2 within each plot, all vegetation w cut at the ground level and returned to the laboratory. Stems were counted (stems m -2 ) and dry- weighed to measure plant biomass and reported as g m -2 . For each marsh, a single random vegetation transect was also conducted, extending perpendicular from the marsh water-edge to the upland edge. Along this transect, percent vegetation cover by each species in a 1-m 2 plot was measured at 10 points evenly spaced along the transect. Vegetation species cover data was collected at each point similar to those taken at the marsh edge. The data were used to characterize overall marsh halophytic plant cover and 27 ? habitat diversity. Salinity preference of plant species (Tiner 1993) was taken into consideration when characterizing the plant community at each marsh. In particular, Cladium jamaicense and Sagittaria lancifolia were noted as common evidence of more brackish or freshwater conditions, while Spartina alterniflora was noted as evidence of polyhaline conditions (Eleuterius 1973). Sediment Analysis Within the three vegetation plots along the marsh water-edge, sediment samples (0-8 cm depth) were taken with a 7.5-cm diameter sediment auger. Sediment samples were combined by marsh, placed in an iced cooler, and returned to the laboratory where they were frozen in a sub- 0?C freezer until analyzed. Sediment concentrations of P and metals (Cd, Cr, Cu, Fe, Mn, Mo Ni, Pb, Zn) were analyzed using Mehlich I extraction (Mehlich 1953) with inductively coupled plasma spectrometry. Concentrations of certain metals in sediments (Cd, Cr, Zn, Pb, Cu, Mn and Mo) were considered a proxy measure of exposure to urban runoff (Steele et al. 2010). Similarly, total petroleum hydrocarbon (TPH) concentration was analyzed for each marsh using the Florida residual petroleum organic method (FDEP, 1995). Total C and N concentration were determined using dry combustion on a LECO CNS-2000 analyzer (Kowalenko 2001). Marsh-edge Slope Analysis The marsh water-edge was also qualitatively assessed for slope steepness at low tide at each marsh. The subtidal slope was considered from the edge of vegetation to 2.0m out perpendicular from the edge. The assessment began at the downstream point where the salt marsh joined the upland and concluded at the upstream junction of marsh and upland. Slope was visually assessed along its entire length and the percentage of shallow, moderate, and steep slope was estimated. Shallow slopes were those areas that gradually dropped to ?0.5m. Moderate 28 ? slopes dropped to between 0.5m and 1.0m. Steep slopes were those that dropped >1.0m. Each category was calculated as a percentage of the total perimeter for each marsh during assessment. Fish Sampling Fish were sampled from each creek in December 2011 and March, July, and September 2012 to capture seasonal variation. For each sampling event, salt marshes were sampled for three consecutive days (two creeks per day) to minimize short-term temporal variation during sampling events. At each salt marsh, five baited minnow traps (22.9 cm x 44.5cm with 2.5cm opening) were deployed (25 per creek) randomly along the edges of each marsh at the falling tide. Traps were retrieved after four hours. Fish caught in traps were immediately put on ice and frozen as soon as possible for later identification and processing in the laboratory. All fish were thawed prior to being processed. For each sampling event, fish were identified and counted by species for each salt marsh. The length of each fish was measured (nearest mm) and weighed (nearest mg). Total numbers of Cyprinodontiformes and total numbers of each species were cacluated as a catch per unit effort (fish trap -1 ). Total cyprinodontiform biomass was also determined using combined fish weights for each salt marsh per trap (g trap -1 ). For each marsh, total cyprinodontiform diversity was calculated per salt marsh using The Shannon-Weiner Diversity Index. Fish abundance was calculated for each creek as the mean number of fish caught per trap. Statistical Analysis Nested analysis of variance (ANOVA) in the program R was used to assess significance of differences between urban and reference treatments for physio-chemical measurements (temperature, salinity, element concentrations in marsh sediment) marsh habitat measurements 29 ? (plant biomass, plant species cover, stem counts, marsh slope) and fish measurements (total abundance, species abundance, total biomass, species richness, and Shannon Index scores). Model nesting structure was marsh measures nested within creek nested within treatment. To compare length-weight relationships between urban and reference creeks, a dummy-coded regression was run on all species that exceeded 20 individuals per creek with weight as the response and length and urban as parameters. Length and weight measurements were log transformed to meet assumptions of a linear regression and statistical significance level was p<0.05. Nonmetric Multidimensional scaling (NMDS) ordination was used to describe differences in fish species composition between urban and reference creeks. Total species composition for each marsh was square-root transformed to reduce the influence of highly abundant species (Quinn and Keough 2002).Each marsh was standardized to values between 0 and 1.0 to balance marshes that had very high and very low abundance, and each species was divided by its maxima to adjust for unequal abundance between species (Quinn and Keough 2002). Data were then put in a Bray-Curtis dissimilarity matrix and then the ordination was run using the matrix. Stress coefficients represent the goodness of fit, and NMDS models are acceptable for interpretation when stress is below <0.2 (McCune and Grace 2002). Species composition data were then correlated to marsh level plant biomass, percent shallow and steep slope, mean salinity, mean temperature, and significant sediment element concentrations (Cd, Cr, Pb, and Zn). Data for salinity and temperature were marsh-level data from the seasonal YSI measures. An analysis of similarities (ANOSIM) was used on the Bray-Curtis dissimilarity matrix of the fish community data by marsh to assess the significance of any differences between the communities. To determine the relationship of marsh habitat characteristics on total fish 30 ? abundance, a generalized linear model with a Poisson distribution was developed at the marsh level to relate total fish abundance to abiotic factors with the parameters plant biomass, percent shallow and steep slopes, temperature, salinity, treatment, and Zn, Cd, Cu, and Ni concentrations in the sediment. The sediment parameters were chosen based on significance and correlation with abundance data. Fish data were marsh-level total abundance per season. All statistical analyses were run in the program R. Results Creek and Marsh Physio-Chemical Measures Urban and reference marshes had comparable mean temperature when fish were sampled (23.2?1.1 ?C and 23.5?1.0 ?C respectively, F=0.03, p=0.85). However, the urban marshes had a larger salinity range (4.2?1.6ppt) than the reference marshes (1.4?0.5ppt, F=10.41, p=0.005, Table 2.2) and urban marshes had significantly lower mean salinity compared to reference marshes (10.8?0.2ppt vs. 14.4?0.1ppt, F=5.85, p=0.018). The conductivity logger data also indicated greater variability in salinity and temperatures in urban creeks compared to reference creeks particularly if examined seasonally. Urban creeks also went below 1.0ppt an average of 133?60 times (Grande Bayou 191, Weekley Bayou 194, Emmanuel Bayou 14), while reference creeks only went below 1.0ppt 14?7 times (Graham Creek 20, Long Bayou 23, Stone Quarry Bayou 0). Urban creeks often had longer periods of low salinity and occasional periods of freshwater flow compared to reference creeks during and following heavy rain events (e.g. Fig. 2.3). The logger data also showed urban creeks having more rapid salinity changes compared to reference creeks. Vegetation Surveys 31 ? Along the marsh edge, urban and reference marshes had similar mean percent cover of Juncus (Table 2.3). Brackish and freshwater species (C. jamaicense and S. lancifolia) were found at both reference and urban marshes in low abundance and mean percent cover was not significantly different. Only two creeks had C. jamaicense on the marsh edge, one urban (Weekley Bayou, 0.8?0.6%) and one reference (Graham Creek, 0.8?0.8%). Urban marshes had lower mean stem density than reference marshes (671?2 no. m -2 vs. 896?2 no. m -2 , F=4.91, p=0.041, Table 2.3). Graham Creek, a reference creek, had the highest stem density (1072? 85 no. m -2 ) while Weekley Bayou, an urban creek, had the lowest (553?76 no. m -2 ). Plant biomass was also significantly lower at urban marshes compared to reference marshes (783?35 g m 2 vs. 1135?32 g m 2 , F=5.32, p=0.034, Table 2.3). Evaluating transects extending across marshes, urban and reference marshes also had similar mean cover of Juncus. However, urban marshes had a higher mean cover of C. jamaicense (4.9?0.2%) in transects than reference marshes (1.9?0.1%) although differences were not significant. Distichlis spicata, Spartina patens, and S. lancifolia were all similar between urban and reference marshes in mean cover of the marsh transect (Table 2.4). Sediment Analysis Sediment concentrations of metals and other elements were frequently different between urban creeks and reference creeks (Table 2.5). Urban salt marshes had significantly higher concentrations of lead (6.14?0.44ppm vs. 2.37?0.08ppm, F=8.00, p=0.012), zinc (6.95?0.23ppm vs. 4.81?0.15ppm, F=4.89, p=0.012), chromium (0.13?0.01ppm vs. 0.08?0.00ppm, F=8.61, p=0.009), molybdenum (0.11?0.01ppm vs. 0.06?0.00ppm, F=5.13, p=0.037) and cadmium 32 ? (0.07?0.00ppm vs. 0.04?0.00ppm F=15.33, p=0.001) than reference marshes. Manganese was significantly lower at urban marshes compared to reference marshes (3.41?0.23ppm vs. 9.98?0.64ppm F=10.36, p=0.005). Carbon and nitrogen concentrations were higher at urban marshes than reference marshes but only carbon was significantly higher (17.25?0.46% vs. 9.98?0.35%, F=12.04, p=0.003). Phosphorus was higher at urban marshes compared to reference creeks, but not significantly. Total petroleum hydrocarbons were below detection levels (<20ppm) in urban or reference marsh sediments. Marsh-edge Slope Marsh slope was different between urban and reference marshes (Fig. 2.4). Emmanuel Bayou had the highest mean percentage of shallow slope (51.7?21.7%), while Graham Creek, a reference creek, had the lowest (1.8?1.1%). Overall, urban marshes had a higher percentage of shallow slope (38.2?8.7% vs. 13.8?4.5%, F=6.29, p=0.023). Mean percentage of moderate slope was similar between urban and reference marshes (22.2?6.2% and 26.5?5.2% respectively, F=0.5334, p=0.48) Reference marshes had a higher percentage of steep slope (59.8?8.4%) compared to urban marshes (39.6?10.0%) but it was not significant (F=2.93, p=0.11). A reference creek (Graham Creek) had the highest mean percent steep slope (88.3?3.0%). Fish Communities Over all seasons, a total of 8 cyprinodontiform species were observed in urban marshes and reference marshes. These included Fundulus grandis (Gulf killifish) Poecilia latipinna (Sailfin molly), Adinia xenica (Diamond killifish), Cyprinodon variegatus (Sheepshead minnow), Fundulus confluentus (Marsh killifish), Fundulus pulvereus (Bayou killifish), Fundulus similis (Longnose killifish), Gambusia holbrooki (Eastern mosquitofish), and Lucania 33 ? parva (Rainwater killifish). F. grandis were significantly less abundant at urban marshes (4.94?0.11 fish trap -1 ) compared to reference marshes (11.04?0.19 fish trap -1 , F=24.19, p<0.001), while F. confluentus was significantly more abundant at urban marshes (0.93?0.03 fish trap -1 vs. 0.15?0.01 fish trap -1 , F=12.94, p<0.001, Table 2.6, Fig. 2.5). P. latipinna, G. holbrooki, and A. xenica, were more abundant at urban marshes while C. variegatus were less abundant at urban marshes, but the differences were not statistically significant. F. similis was only found at reference marshes, although it was rarely encountered. Community composition also varied with season (Fig. 2.6). Mean Shannon-Weiner Index scores were significantly higher in urban marshes (1.14?0.11) than in reference marshes (0.78?0.11, F=10.05, p=0.006, Table 2.6). The creek with the highest score was Weekley Bayou, an urban creek (1.29?0.01), and the lowest was Long Bayou, a reference creek (0.41?0.07). Species richness was similar for urban marshes (5.6?0.3) and reference marshes (6.2?0.2, Table 2.6). Fish Abundance Mean total fish abundance was significantly lower at urban marshes (10.1?0.2 fish trap -1 ) compared to reference marshes (14.3?0.1 fish trap -1 , F=7.59, p=0.007 Table 2.6). Urban marshes also had significantly lower fish biomass than reference marshes (372?5 g trap -1 vs. 924?15 g trap -1 , F=24.07, p<0.001, Table 2.6). Spring (March 2012) had the highest mean abundance of any season (15.6?0.4 fish trap -1 ), and winter (December 2011) had the lowest abundance (8.3?0.3 fish trap -1 , Fig. 2.6). Long Bayou, a reference creek, had the highest mean abundance (19.9?0.6 fish trap -1 , Table 2.6) and the urban creek Grande Bayou had the lowest mean abundance (5.19?0.30 fish trap -1 ). The most abundant species trapped during the study were F. grandis (7.89?0.28 fish trap -1 , Table 2.6). Three species had 6 or fewer individuals captured (L. parva, F. similis, and F. pulvereus). 34 ? Several marsh characteristics were found to be significantly correlated with fish abundance. The results from the GLM with a Poisson distribution found reference marshes had significantly more fish than urban marshes (2.71,1.10-6.68 95%CL, p=0.027). Also, salinity (1.04, 1.03-1.04 95%CL, p<0.0001) and shallow slope (1.02, 1.01-1.03 95%CL, p=0.001) were significantly correlated with total fish abundance. No other parameters were significantly correlated with total fish abundance. Results from NMDS showed clustering of marshes that was not solely based on the marsh location (Fig. 2.13). Correlations revealed significant relationships between the species abundance data and creek, treatment, salinity, Cd concentration in sediment, and percent steep slope which were potentially driving some of the differences. ANOSIM analysis found that urban fish communities were significantly different than reference creeks (R= 0.14, p<0.01). Fish Length-Weight Relationships Length-weight regressions revealed different fish sizes at urban marshes depending on the species. For P. latipinna and F. grandis, length-weight regressions for urban marshes were not significantly different from reference marshes (t=0.884, p=0.082, Fig. 2.8 and t=1.742, p=0.38, Fig. 2.9). However A. xenica (t=2.194, p=0.029 Fig. 2.10), C. variegatus (t= 2.109, p=0.036 Fig. 2.13), and F. confluentus (t=4.176, p=0.036, Fig. 2.12) were all significantly larger (per mm length) at urban marshes compared to reference marshes. Only G. holbrooki (t=-6.679, p<0.01, Fig. 13) was significantly smaller (per mm length) at urban marshes. However, these differences are likely not biologically significant. 35 ? Discussion Based on the results of this study, there were distinguishable differences in salt marsh physio-chemical measures, vegetation, and fish communities between urban and reference marshes. Many of the differences in fish community composition between urban and reference marshes were likely related to salinity. Although these fish have broad ranges of salinity tolerance (Nordlie 2006), the fish community at both urban and reference marshes changed with seasonal shifts in salinity. As seen in the continuous salinity data and the sampling measures, urban salt marsh salinity tended to fluctuate much more rapidly, had a larger range and lower average than reference marshes. The fact that species with low salinity preference (e.g., G. holbrooki, P. latipinna, and F. confluentus; Boschung and Mayden 2004) were often more abundant at urban marshes also suggests that salinity is an important driver of differences between creeks. Similarly, F. similis prefers higher salinity and was only found at reference marshes. These results are consistent with other studies that have examined fish communities and salinity. Marsh fish communities along a salinity gradient in Texas were found to be driven by salinity (Gelwick et al. 2001). Tidal freshwater and oligohaline marshes were also found to have the highest diversity, and this was hypothesized to be due to freshwater species and euryhaline marine species co-occurring. While not measured here, the variability in salinity is likely due to increased freshwater runoff from surrounding impervious surfaces. Urban land-use has been shown to increase surface runoff in freshwater streams (Paul and Meyer 2001), which results in more frequent large flow events and rapid flood peaking (Walsh et al. 2005). Holland et al. (2004) found a similar pattern of increased salinity range and ?flashiness? when impervious cover exceeded 10-20% in South Carolina tidal creeks. Fish communities in an estuarine Florida river also varied with the amount of freshwater flow in the spring. (Greenwood et al. 2007). 36 ? Florida fish and decapod crustacean communities in bays that received large input of freshwater from flood control measures were significantly different from a natural creek and bay system (Shirley et al. 2005). In a community profile of Juncus-salt marshes in the northern Gulf of Mexico, Stout (1984) described F. similis, F. grandis, and C. variegatus as the dominant resident Cyprinodontiformes. In this study, F. similis was rarely encountered and only at reference creeks. F. grandis was dominant at both urban and reference creeks, but P. latipinna was more often a dominant species in these marshes than C. variegatus. Stout (1984) also listed P. latipinna, C. variegatus, L. parva, A. xenica, and F. confluentus as common dominant species in isolated ponds within the salt marsh. This was supported by the high abundances of these species found by Harrington and Harrington (1961) in Florida salt marsh ponds. Interestingly, all of these species (except C. variegatus and L. parva which was rare) were more abundant at urban creeks than at reference creeks. These species may be better adapted to wide salinity swings from freshwater to high salinities, conditions that may commonly occur in salt marsh ponds where salinity ranges may be wider due to less frequent tidal flushing of pools. If similar salinity patterns are occurring along the marsh edges of urban creeks, these pond dominants may be better suited to urban marshes. Mean fish abundance and total fish biomass were significantly greater at reference marshes than urban marshes. Mean total fish biomass in reference marshes was higher (2.5x) than urban marshes reflecting both greater abundance and more frequent larger species (F. grandis). These results suggest that continued urban development in the region may reduce fish productivity even if salt marsh habitats are available. A few other studies have detected relationships between land use and fish abundance in tidal systems. Sanger et al. (2011) found a 37 ? non-significant negative relationship between fish density and impervious cover through sampling with a trawl in tidal creeks of Mississippi and Alabama. Similar to this study, Vernberg et al. (1992) found lower annual and monthly biomass of fish and decapod crustaceans at a high density residential inlet compared to a reference inlet in North Carolina. The Poisson model revealed that total fish abundance was related to marsh salinity and the amount shallow slope. Shallow slopes had greater abundance of fish compared to moderate slopes. McIvor and Odum (1988) also found that shallow slopes had higher abundances of small fish at freshwater marshes in Virginia, and steep sloped marshes were found to have lower abundance of resident fish along them because of increased predation risk. In this study, urban marshes had greater percent shallow slope than reference creeks which may mitigate somewhat for lost fish abundance. Species abundance also differed between urban and reference marshes. F. grandis was significantly more abundant in reference creeks, and F. similis was only found in reference creeks. In contrast, P. latipinna, F. confluentus, A. xenica, C. variegatus, and G. holbrooki were more abundant at urban creeks, although only F. confluentus was significantly so. Sanger et al. (2011) also found P. latipinna, C. variegatus, and G. holbrooki to be associated with urban tidal creeks in Alabama and Mississippi through seining. Differences in species abundance could be due to a number of factors in addition to salinity and slope. Another possible factor could be the lower plant biomass on the marsh edge in urban creeks. While Wigand et al. (2003) found urban land-use was associated with increased nutrient inputs and plant growth, I found Juncus had less percent cover. Less plant biomass means more bare sediment, where algae can grow (Deegan et al. 2007), as well as less cover from predators (Minello 1993, Stolen 2009). This may change the food sources and habitat to favor certain cyprinodontiform species over others, such as the more herbivorous P. latipinna and C. variegatus (Harrington and Harrington 1961). 38 ? The resident Cyprinodontiformes also displayed different sizes between urban and reference creeks. Species A. xenica, C. variegatus, and F. confluentus were significantly larger at urban creeks than reference creeks while G. holbrooki was significantly smaller at urban creeks. However, these differences were small, and may not biologically significant. This difference was unexpected, considering G. holbrooki is typically found in freshwater or very low salinities. However, the majority of individuals were captured after a heavy rain event in the fall. G. holbrooki may have moved into the salt marshes from upstream marsh habitats not assessed in this study. In addition, the two most dominant species, F. grandis and P. latipinna not significant in size at urban marshes compared to reference. The previous factors that affect abundance and community composition (salinity, slope, and plant biomass) may also be influencing fish size (Trexler et al. 1992, Dunson et al. 1998), especially for F. confluentus, A. xenica, and C. variegatus. Another factor that may affect fish size is pollution. Sediment in urban salt marshes had higher levels of certain heavy metals commonly associated with urban runoff than reference salt marshes. However, percent carbon was also significantly higher at urban creeks. Organic matter, which is indirectly measured by the percent carbon, has been shown to increase adsorption of metals (Sanger et al. 1999a). Nevertheless, increased urban development was expected to result in greater exposure to pollutants. Van Dolah et al. (2008) found a relationship between sediment contaminants and urban and suburban land-use. Some species may be more tolerant to the pollutants or may have adapted to the contaminants found in the sediment. F. heteroclitus was found to have adapted to polychlorinated biphenyls (PCBs) and was less sensitive to exposure in New England salt marshes (Nacci et al. 2010). Further research is needed to into the pollutant exposure and bioaccumulation within each species to conclude how much pollution is influencing fish size. 39 ? Conclusions Urban land-use has the potential to change salt marsh habitat for fish. This study looked at urban and reference Juncus-dominated salt marshes in tidal creeks of west Florida and Alabama. Fish were sampled seasonally for one year using minnow traps, and various habitat measures were taken, including sediment concentrations of metals and nutrients, plant composition and density, salinity, and water temperature. Fish abundance and length-weight regressions were compared for common species in addition to characterizing fish communities at both urban and reference marshes. Urban salt marshes were found to have lower total abundance of resident fish, but higher abundance of certain species, namely those with a lower salinity preference. 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Coastline population trend in the United States:1960 to 2008. U.S. Census Bureau. 45 ? Figure 2.1 Map of the study sites. Triangles represent reference creeks and circles represent urban creeks. Perdido?Bay Wolf? Bay Gulf?of?Mexico Alabama Florida Orange? Beach West?Pensacola Graham?Creek? (GC) Long? Bayou?(LB) Stone?Quarry? Bayou?(SQB) Emmanuel Bayou?(EB) Weekley?Bayou? (WB) Grande?Bayou? (GB) 2?km 46 ? 25 20 15 10 5 0 S a lin it y ( p p t ) SQBLBGCWBGBEB 25 20 15 10 5 0 S a lin it y ( p p t ) 20 15 10 5 0 S a lin it y ( p p t ) Figure 2.2 Boxplots for continuous salinity measures of each sampled creek in (a) winter and spring (December-May) (b) summer and fall (June-November) and (c) annual total (March 2012- March 2013). See Fig. 1 for creek abbreviations. a b c Urban? Reference? 47 ? Figure 2.3 Mean hourly salinity at an urban (Emmanuel Bayou) and reference (Stone Quarry Bayou) creek during a 26cm rain event which occurred from 10-12 June 2012. Creek salinity is from data from 1 June through 4 July 2012. S a l i n i ty ( p p t ) 0 2 4 6 8 10 12 14 16 18 20 URB REF JUN 04 JUN 11 JUN 18 JUN 25 JUL 02 48 ? Figure 2.4 Mean percentage of marsh edge slope categories per creek. See Fig. 1 for creek abbreviations. Urban EB GB WB GC LB SQB Per c ent age of M a rs h edge 0 20 40 60 80 100 120 Shallow Moderate Steep Reference 49 ? Figure 2.5 Mean total abundance per trap of major cyprinodontiform species within each creek. See Fig. 1 for creek abbreviations. Species Composition by Creek Urban EB GB WB GC LB SQB 0 5 10 15 20 25 F. grandis P. latipinna F. confluentus A. xenica C. variegatus G. holbrooki 50 ? Fall Urban WB EB GB GC LB SQB F. grandis P. latipinna F. confluentus A. xenica C. variegatus G. holbrooki Reference Summer Urban WB EB GB GC LB SQB Ab un da nc e ( f is h t r ap -1 ) 0 5 10 15 20 25 30 Reference Spring Winter Abun dance ( f ish t r ap -1 ) 0 5 10 15 20 25 30 Figure 2.6 Seasonal species abundance per trap for each creek. See Fig. 1 for abbreviations. 51 ? Figure 2.7 Length-weight plot, trend line and regression results for F. grandis (n=3590). 0 5 10 15 20 25 30 35 2040608010120140 We ig h t ? (g) Length?(mm) Reference Urban Reference?&?Urban t=?0.884? p=0.38 n=3590 52 ? Figure 2.8 Length-weight plot, trend line and regression results for P. latipinna (n=780). 0 1 2 3 4 5 6 7 1020304050607080 Weigh t ? (g ) Length?(mm) Reference Urban Reference Urban t=1.742? p=0.08 n=780 53 ? Figure 2.9 Length-weight plot, trend line and comparative regression results for A. xenica (n=232). 0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 0 5 10 15 20 25 30 35 40 45 50 Weight ? (g) Length?(mm) Reference Urban Reference Urban t=2.194 P=0.029 n=232 54 ? Figure 2.10 Length-weight plot, trend line and comparative regression results for G. holbrooki (n=174). 0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 102030405060 Weight ? (g) Length?(mm) Reference Urban Reference Urban t=?6.679 p=<0.01 n=174 55 ? Figure 2.11 Length-weight plot, trend line and comparative regression results for F. confluentus (n=299). 0 1 2 3 4 5 6 1020304050607080 Weight ? (g) Length?(mm) Urban Reference Urban Reference t=4.176? p<0.01 n=299 56 ? Figure 2.12 Length-weight plot, trend line and comparative regression results for C. variegatus (n=346). 0 1 2 3 4 5 6 7 8 1020304050607080 Weight ? (g) Length?(mm) Reference Urban Reference Urban t=2.109? p=0.036 n=346 57 ? Figure 2.13 NMDS plot run with 6 dimensions at the marsh level. Vectors are for significant environmental variables (percent steep slope, salinity, sediment Cadmium concentration) (p?0.05). Reference creeks are represented by black points and urban by white points. AXEN=A. xenica CVAR=C. variegatus FCON=F. confluentus FGRD=F. grandis FPUL=F. pulvereus SIM=F. similis GHOL=G. holbrooki LPAR=L. parva PLAT=P. latipinna 58 ? Table 2.1 Urban land-use characteristics within 500m radius of each study creek. See Fig. 1 for creek abbreviations. Urban Reference Urban land-use measures WB GB EB GC LB SQB Urban Reference Road area (m 2 ha -1 ) 562.4 281.1 544.2 19.7 0 5.6 462.6?90.9 8.44?5.8 Road density (m ha -1 ) 61.1 36.0 95.5 3.5 0 0.3 64.2?17.2 1.3?1.1 House density (no. ha -1 ) 1.4 1.4 1.0 0.1 0 0.1 1.3?0.1 0.1?0.0 Shoreline house density (no. km shoreline -1 ) 10.2 14.6 10.3 2.7 0 0.0 11.7?1.5 0.9?0.9 Boat slips (no. km shoreline -1 ) 6.3 6.7 6.8 1.9 0 0.0 6.6?0.2 0.6?0.6 59 ? Table2.2 Mean (?SE) creek salinity and temperature measures from seasonal fish sampling (n=92) (YSI) and from conductivity loggers (n=8041) (HOBO). See Fig. 1 for creek abbreviations. Urban Reference EB GB WB GC LB SQB Urban Reference YSI Salinity mean (ppt) 11.5?0.7 8.6?0.9 12.6?1.2 11.6?0.4 14.9?0.3 16.7?0.1 10.8?1.3 14.4?1.1 Salinity range (ppt) 11.2?0.4 18.4?0.9 17.0?1.2 16.2?0.6 15.6?0.9 9.5?0.3 15.9?1.8 13.8?1.7 Salinity min (ppt) 7.8?0.8 2.4?0.5 5.0?1.4 3.5?0.8 7.9?0.9 13.5?0.1 4.8?1.4 8.3?2.2 Salinity max (ppt) 19.0?0.5 20.8?1.2 21.9?0.6 19.7?0.3 23.4?0.1 23.0?0.2 20.7?1.0 22.0?0.9 Temperature mean (?C) 22.7?0.1 23.5?0.9 23.4?0.4 23.8?1.7 24.1?1.6 22.6?1.7 23.2?1.1 23.5?1.0 Temperature range (?C) 15.8?0.2 19.3?0.1 17.2?0.7 15.8?0.7 15.0?0.4 15.9?0.3 17.6?0.8 15.6?0.5 Temperature min (?C) 13.7?0.2 13.4?0.2 14.2?0.3 15.1?0.2 16.4?0.5 13.6?0.4 13.7?0.3 15.0?0.7 Temperature max (?C) 29.5?0.1 32.7?0.3 31.4?0.5 30.9?0.5 31.4?0.1 29.4?0.1 31.3?0.7 30.6?0.5 HOBO Salinity mean (ppt) 14.8?0.0 16.2?0.0 15.6?0.0 13.6?0.0 14.7?0.0 16.4?0.0 15.5?0.4 14.9?0.8 Salinity range (ppt) 20.5 21.9 22.1 18.4 21.9 20.2 21.6?0.5 21.3?1.0 Salinity min (ppt) 0.2 0.1 0.2 0.2 0.2 2.8 0.1?0.0 1.1?0.9 Salinity max (ppt) 20.7 22.0 22.3 18.7 22.1 23.0 21.5?0.5 20.2?1.3 Temperature mean (?C) 24.6?0.1 25.9?0.1 25.9?0.1 26.4?0.1 258?0.1 24.6?0.1 25.5?0.4 25.6?0.5 Temperature range (?C) 19.7 22.9 24.8 18.0 23.9 23.6 34.0?1.5 34.2?1.9 Temperature min (?C) 12.9 11.9 9.7 16.0 10.0 11.1 11.5?1.0 12.4?1.9 Temperature max (?C) 32.6 34.8 34.5 34.1 34.0 34.7 22.4?0.7 21.9?0.2 60 ? Table 2.3 Mean (?SE) percent cover of dominant species, stem densities, and biomass at marsh edge for urban and reference creeks. Significant differences in mean measurement between urban and reference creeks reported per nested ANOVA. See Fig. 1 for creek abbreviations. Urban Reference EB GB WB GC LB SQB Urban Reference F, p Juncus roemarianus 60.6?10.5 71.7?7.6 60.7?9.4 53.2?7.8 48.8?7.4 56.7?6.7 64.6?5.2 52.9?4.1 NS Cladium jamaicense 0 0 0.8?0.6 0.8?0.8 0 0 0.4?0.2 4.0?0.3 NS Distichlis spicata 0 1.1?0.8 0 11.3?4.2 0 0.8?0.6 0.4?1.6 4.0?0.3 NS Spartina alterniflora 0 0 0 0 2.5?2.5 0 0 0.8?0.8 NS Sagittaria lancifolia 1.1?0.6 0 0 0 0 1.3?1.3 0.4?0.2 0.4?0.4 NS Stem density (no. m -2 ) 897?95 553?111 718?152 716?170 755?103 1072?65 671?72 896?77 4.91, 0.041 Biomass (g m -2 ) 1085?231 610?121 875?190 930?197 847?65 1444?59 783 ?87 1135 ?84 5.32, 0.034 61 ? Table 2.4 Mean (?SE) percent cover of dominant species per marsh transect for urban and reference creeks. Significant differences in mean cover between urban and reference creeks reported per nested ANOVA. See Fig. 1 for creek abbreviations. Urban Reference Species GB EB WB GC LB SQB Urban Reference F, p Juncus roemarianus 43.7?3.7 35.4?5.3 34.9?3.7 38.8?4.3 35.8?3.6 39.3?3.0 38.4?2.4 37.9?5.3 NS Cladium jamaicense 1.2?1.0 9.4?3.5 5.1?2.9 5.0?2.2 0.9?0.3 0.2?0.1 4.8?1.5 1.9?0.8 NS Distichlis spicata 9.5?3.1 0 0 6.8?2.2 0.1?0.1 1.9?2.0 3.4?1.2 2.9?1.0 NS Spartina patens 1.5?1.5 0 0 0 3.0?1.6 0.9?02.8 0.5?0.6 1.3?1.0 NS Sagittaria lancifolia 0 0.5?0.3 0 0 0 0 0.1?0.1 0 NS Solidago sempervirens 0.2?0.1 0 0 0.7?0.4 2.0?1.1 0 0.1?0.0 0.9?0.4 8.54, 0.010 Lilaeopsis chinensis 0 0 0 0 0.4?0.2 0.6?0.4 0 0.3?0.2 4.56, 0.048 Salicornia europaea 0 0 0 0 0.8?0.6 0 0 0.3?0.2 NS 62 ? Table 2.5 Mean (?SE) element concentration of sediment for each creek and treatment. Significant differences in mean concentration between urban and reference creeks reported per nested ANOVA. See Fig. 1 for creek abbreviations. Urban Reference Element EB GB WB LB SQB GC Urban Reference F, p Cd (ppm) 0.05 ? 0.01 0.08?0.02 0.08?0.01 0.02?0.00 0.05?0.02 0.04?0.01 0.07?0.01 0.04?0.01 15.33, 0.001 Cr (ppm) 0.16?0.02 0.121?0.03 0.11?0.02 0.07?0.01 0.08?0.00 0.08?0.03 0.13?0.01 0.08?0.01 8.61, 0.009 Cu (ppm) 1.01?0.06 0.27?0.06 0.50?0.11 0.36?0.02 0.53?0.17 0.31?0.04 0.56?0.10 0.40?0.06 NS Fe (ppm) 76.86?4.76 57.60?8.16 39.66?8.89 79.53?11.09 51.78?12.51 67.79?7.33 56.33?6.23 66.37?6.49 NS Mn (ppm) 1.92?0.59 5.55?1.71 2.37?0.80 10.14?3.34 3.94?0.78 15.86?4.29 3.41?0.82 9.98?2.21 10.36, 0.005 Mo (ppm) 0.12?0.03 0.08?0.00 <0.01 <0.01 0.06?0.01 <0.01 0.11?0.02 0.06?0.00 5.13, 0.037 Ni (ppm) 0.41?0.08 0.22?0.03 0.22?0.04 0.30?0.06 0.31?0.05 0.40?0.07 0.27?0.04 0.34?0.03 NS Pb (ppm) 4.08?0.28 9.55?3.51 4.27?1.16 2.65?0.27 1.88?0.55 2.59?.57 6.14?1.47 2.37?0.27 8.00, 0.012 Zn (ppm) 7.40?2.81 6.43?0.34 7.14?0.97 4.12?0.58 5.03?0.94 5.27?1.21 6.95?0.75 4.81?0.52 4.89, 0.041 P (ppm) 44.54?6.95 41.75?2.91 46.91?6.35 56.59?16.98 33.27?3.41 47.64?18.59 44.38?2.91 45.84?8.19 NS C(%) 16.48?1.98 17.02?3.82 18.06?1.99 9.22?1.88 9.16?1.59 11.56?2.99 17.25?1.51 9.98?1.21 12.04, 0.003 N(%) 0.86?0.10 0.85?0.17 0.92?0.10 0.59?0.12 0.56?0.08 0.79?0.21 0.88?0.07 0.65?0.08 NS 63 ? Table 2.6 Mean (?SE) species and total abundance (no. fish trap -1 ), total biomass, Shannon Index and species richness per creek and treatment. Significant differences in mean abundance between urban and reference creeks reported per nested ANOVAs. See Fig. 1 for creek abbreviations. Urban Reference EB GB WB GC LB SQB Urban Reference F, p F. grandis 5.33?1.39 3.88?1.18 5.71?1.15 4.11?1.80 18.14?2.55 10.86?1.09 4.94?0.70 11.04?1.41 24.19, <0.001 P. latipinna 1.83?0.91 0.26?0.15 4.44?1.15 0.98?0.37 0.96?0.46 2.39?0.63 2.21?0.55 1.44?0.31 NS F. confluentus 0.52?0.30 0.39?0.14 1.79?0.54 0.28?0.16 0.05?0.02 0.13?0.05 0.93?0.24 0.15?0.06 12.94, <0.001 F. pulvereus 0 0 0.01?0.01 0.06?0.04 0.04?0.04 0.03?0.03 0 0.04?0.02 NS F. similis 0 0 0 0 0.03?0.02 0.04?0.04 0 0.02?0.01 NS A. xenica 0.18?0.12 0.45?0.33 1.36?0.54 0.04?0.02 0.24?0.10 0.76?0.018 0.71?0.24 0.35?0.09 NS C. variegatus 0.18?0.21 0.08?0.04 1.64?0.77 2.08?1.22 0.39?0.14 0.3?0.017 0.67?0.30 0.92?0.42 NS G. holbrooki 0.6?0.44 0.14?0.09 1.01?0.48 0.81?0.45 0.05?0.04 0.04?0.02 0.58?0.22 0.30?0.16 NS L. parva 0 0 0.01?0.01 0.03?0.02 0 0 0 0.01?0.01 NS Mean abundance 8.65?1.62 5.19?1.22 15.98?2.63 8.38?2.13 19.89?2.47 14.54?1.07 10.05?1.32 14.27?1.35 7.59, 0.007 Total biomass (g trap -1 ) 101 104 166 104 532 290 372 924 20.32, <0.001 Shannon Index 1.01?0.24 0.94?0.12 1.42?0.12 1.15?0.17 0.39?0.13 0.80?0.01 1.14?0.11 0.78?0.11 10.05, p=0.006 Sp. richness 5.0?0.6 5.5?0.3 6.3?0.6 6.8?0.3 6.0?0.4 5.8?0.3 5.6?0.3 6.2?0.2 NS 64 ? Chapter 3: Urban land-use effects on Fundulus grandis and Poecilia latipinna condition Abstract Urbanization has been shown to impact coastal fisheries by reducing the quality of important habitats, including salt marshes. Increasing urban land-use surrounding tidal creeks may impact the health of fish by changing salinities, altering habitat structure, and increasing exposure to pollution. In this study I evaluated the impacts of urban land-use on Fundulus grandis and Poecilia latipinna, two common salt marsh resident fish along the northern Gulf of Mexico. Fish were sampled seasonally along salt marshes near the mouth of six second-order tidal creeks (three surrounded by urban development and three surrounded by forest cover) in Alabama and west-Florida. Because urban runoff commonly contains elevated concentrations of heavy metals, F. grandis was also analyzed for metal contaminants. Results showed F. grandis had lower LSI and caloric density at urban salt marshes compared to reference. However, P. latipinna did not have significantly different condition measures at urban salt marshes compared to reference. Both species showed seasonal patterns related to conditional measures that were likely related to reproduction and annual fattening cycles. Except for zinc, no significant differences were detected in metal concentration between urban and reference F. grandis and many metals associated with urban runoff (Cd, Cr, Pb) were below detection levels for fish from both creek types. Lower fish condition in urban creeks for F. grandis is likely a result of an altered salinity regime. 65 ? Introduction Urbanization and associated anthropogenic impacts have been shown to have a number of effects on estuarine systems. Urban land-use has been associated with increased runoff of nutrients (Arismendez et al. 2009, Yang 2012), heavy metals (Holland et al. 2004, Sanger et al. 1999), pesticides (Sanger et al. 2011), polychlorinated biphenyls (PCBs), polycyclic aromatic hydrocarbons (PAHs) (Van Dolah et al. 2008) and other contaminants (Eom et al. 2010, DiDonato et al. 2009). Some contaminants (e.g. PAHs, PCBs) may remain in a creek system for long periods and organisms continue to be exposed to them (Teal et al. 1992). A range of urban measures, including residential land-use, was significantly correlated with PCB concentration in white perch (Morone americana) fillets in Chesapeake Bay (King et al. 2004). Increased urban runoff into tidal creeks has also been correlated with altered hydrology (Sahoo and Smith 2009) and salinity regimes that can induce osmotic regulatory energy cost and reduce fish habitat suitability (Shirley et al. 2005). For instance, salinity range increased with increasing impervious cover in South Carolina tidal creeks (Holland et al. 2004). Considering at least 90% of commercially valuable fish are considered estuarine dependent (Chambers 1992) understanding how urbanization affects habitat and fish health is important. Measures of fish health and condition have commonly been used to assess environmental effects caused by surrounding land use. For instance, fish have been shown to accumulate toxins after exposure and even develop resistance to them (Yuan et al. 2006). Fish condition and abundance measures have been shown to be useful in environmental monitoring (Leamon et al. 2000, Galloway and Munkittrick 2006, Anderson et al. 2006). Striped bass in the Hudson River showed significant declines in several health measures, including liver weight: body weight ratios, RNA:DNA ratios, swimming ability and bone development, all of which were likely 66 ? related to the high pollution load from urban and industrial sources (Buckley et al. 1985). While sportfish have often been the focus of studies, small forage fish have also been shown to exhibit comparable responses (Yeardley 2000). Mummichogs (Fundulus heteroclitus), a small resident fish of salt marshes along the Atlantic coast of North America, have been used in numerous studies to evaluate the impact of anthropogenic changes on fish condition, including pulp mill effluent (Le Blanc et al. 1997), pollutants (Pait and Nelson 2009, Nacci et al. 2010) invasive species (Weinstein et al. 2009) and restoration efforts (Teo and Able 2003). For instance, mummichogs in a polluted marsh in New York had reduced growth rates, higher metabolic rates, and higher food consumption compared to reference fish (Goto and Wallace 2010). Thus, the condition of mummichog has proven to be a useful indicator of salt marsh quality. Within the Gulf of Mexico, a species closely related to the well-studied mummichog, Fundulus grandis (Gulf killifish) is abundant in salt marshes. Both of these species are salt marsh residents that use the marsh surface extensively for spawning and foraging habitats and then retreat to marsh edges or pools at low tide (Boschung and Mayden 2004, Knieb 1986). Because of its dependence on marsh habitat and tendency to stay within a close home range, F. grandis is a good species for studying anthropogenic impacts on fish condition in the northern Gulf of Mexico. Another resident species that has been used for toxicology experiments is Poecilia latipinna. Its abundance in impacted areas and sensitivity to toxicants (e.g., dieldrin, Lane and Livingston 1970) also make it well suited to studies of anthropogenic impacts in the northern Gulf of Mexico. Potential differences in species condition may be related to increased runoff from urban land-use, which could alter salinity regimes and increase pollutant exposure. Although both species have a wide salinity tolerance range, F. grandis and P. latipinna have slightly different 67 ? salinity preferences. F. grandis is more common in higher salinities within its range (2-28ppt, Fivizzani and Meier 1978) while P. latipinna is more common in lower salinities (<10ppt, Boschung and Mayden 2004). Both species are common in Juncus roemarianus-dominated marshes, which commonly occur along the Mississippi, Alabama, and west Florida coasts in salinities of 10.1 to 24.4ppt (Stout 1984). This understudied marsh type is less common than Spartina alterniflora habitats in the United States, but represents a higher proportion of the marshes along these coasts than in any other area of the country (Stout 1984). Many studies have looked at how fish differ in condition in due to industrial or high density urban land-use (King et al. 2004, Buckley et al. 1985, Yuan et al. 2006), but a paucity of studies exists concerning how low to medium-density urban land-use may impact estuarine fish condition. While a multitude of condition measures exist, this study focused on using changes in liver size and caloric density to assess potential urban effects on F. grandis and P. latipinna. Liver measures such as size and enzyme activity have been used to assess anthropogenic impacts such as dense urban and industrial land-use and pollutant exposure (Ferraro et al. 2001, Schoor et al. 1988). The liver can also store energy in the form of glycogen and a decrease or increase in size to reflect differences in nutrition, reproductive state, condition, sex, season, and toxicant exposure (Hinton and Laur?n 1990). Caloric density can be used as a measure of the whole fish, so it accounts for changes in protein, carbohydrates, and lipids, and any change in the relative contribution of these is reflected in caloric density. Caloric density has been used in other studies to compare differences in productivity (Vondracek 1996) and toxicant exposure (Moles and Rice 2012). The objective for this study was to determine if F. grandis and P. latipinna exhibit differences in condition as measured through Liver Somatic Index scores and caloric density in urban salt marshes compared to reference salt marshes. As a potential predictor of fish health, the 68 ? concentrations of urban derived metals in fish were also compared between creek type. I expected that F. grandis and P. latipinna from urban salt marshes would have lower Liver Somatic Index scores, lower caloric density, and higher metal concentrations compared to those from reference salt marshes. Methods Site Description This study focused on six second-order tidal creeks along the Alabama and Florida coast (Fig. 1). Creeks were selected as part of a broader examination of urban effects on salt marsh habitat in the region (see Methods, Chapter 2). Two creeks were in the Wolf Bay drainage basin (in Alabama), three in the Perdido Bay drainage basin (in Alabama and Florida), and one in the Pensacola Bay drainage basin (in Florida). Three creeks were classified as reference (Long Bayou, Graham Creek, and Stone Quarry Bayou) and the other three as urban (Emmanuel Bayou, Weekley Bayou, and Bayou Grande). Reference creeks had a housing density of <3.0 houses km shoreline -1 and a road density of <10.0 m ha -1 within a 500 m radius of the creek while urban creeks had a housing density of ?10.0 houses km shoreline -1 and >30.0m ha -1 road density within a 500 m radius of the creek (see Chapter 2, Table 2.1). Shoreline hardening and other alterations were present along all the urban creeks while only minor alterations occurred on a small portion of one reference creek (Graham Creek) and the others had no alterations (Table 3.1). In each creek four salt marshes near the mouth were selected as study sites (Emmanuel Bayou only had three salt marshes). Marshes were dominated by J. roemerianus (henceforth Juncus) and were selected to be of comparable size and condition between creeks. Fish Sampling 69 ? Fish were collected from each creek once per season (i.e., winter, spring, summer, and fall: December 2011, March 2012, July 2012, and September 2012 respectively) since condition measures have been shown to change seasonally (Leamon et al. 2000, Galloway and Munkittrick 2006). For each sampling event, fish were collected for three consecutive days (each day two creeks were sampled) using baited minnow traps (22.9 cm x 44.5cm with 2.5cm opening) randomly set along water edge of each marsh at the falling tide. At each salt marsh, 5 minnow traps were deployed (20 per creek) and collected four hours later. Fish caught in traps were immediately put on ice and frozen as soon as possible for identification and processing in the laboratory. Fish Condition All fish were thawed prior to being processed. F. grandis and P. latipinna were enumerated per marsh and per sampling event. The length of each fish was measured (nearest mm) and weighed (nearest mg). A representative subset of 10 fish of each species per marsh was used for the condition measures. The subset consisted of 2 fish, a male and female if possible, of five size classes for F. grandis (?90cm, 89-73cm, 72-57cm, 56-41cm and ?40cm) and P. latipinna (?60cm, 50-59cm, 40-49cm, 31-39cm ?30cm). In cases where the entire breadth of size classes were not present, size classes with the greatest abundance were sampled again to fill the subset. The subset of fish had their liver removed and weighed (nearest mg). Liver Somatic Index (LSI) was calculated for each fish as follows: LSI = 10 3 ? (liver weight/body weight) 70 ? Livers were then placed with the rest of the fish in a drying pan for analysis of caloric density. The same subset was dried in an oven at 70?C and weighed every day until constant mass was achieved. Each fish was then ground to homogenize the sample and re-dried until a constant mass was reached again. Two 0.1 -0.2g pellets per fish were ignited for caloric content in a semi-mirco bomb calorimeter (Parr Instrument Co., Model 1425 and Model 6725). If the two subsamples were not within 2% of each other, a third subsample was run. However, when fish dry weight was 0.2-0.4g, only two pellets were run. In the event that the dry weight of the fish was <0.2g, the whole fish was analyzed in one pellet without being ground. Results of pellet incineration were averaged per fish to get caloric density per gram of dry weight. Caloric density per gram of wet weight was calculated by multiplying caloric density per gram of dry weight to the ratio of dry weight to wet weight (Glover et al. 2010). This was calculated for each fish and used for statistical comparison. Ground F. grandis that remained after bomb calorimetry was combined per creek for the summer and fall sampling and analyzed for heavy metal contaminants and other metals commonly associated with urban runoff (Al, Fe, As, Cd, Cr, Ni, Pb, Zn, and Cu; Paul and Meyer 2001) using Inductively Coupled Plasma (ICP) Atomic Emission Spectroscopy with a Varian Vista-MPX Axial Spectrometer (Odom and Kone 1997). P. latipinna was not analyzed due to insufficient sample being left after bomb calorimetry. Statistical Analysis To determine the effect of treatment (urban vs. reference), fish condition measures were analyzed with nested Analysis of Variance (ANOVA). Seasonal fish measures were averaged per marsh and nested within creek and then within treatment. To compare seasonal trends related to 71 ? fish measures, fish measures were averaged per creek and plotted per sampling event. Significance level was set at p<0.05 and all analyses were run in the program R. Results A total of 291 P. latipinna and 741 F. grandis were used for analyzing fish LSI while 366 P. latipinna and 741 F. grandis were used for the caloric density analysis (Table 3.1). There was a lower number of P. latipinna were analyzed for LSI due to some fish thawing for too long and the livers broke down into an immeasurable state. LSI had different responses based on species and treatment. Urban marshes had similar P. latipinna LSI (1046?66) compared to reference creeks (1163?70, Table 3.2). Weekley Bayou, an urban creek, had the lowest LSI for P. latipinna (969?49) while a reference creek, Graham Creek, had the highest LSI (1407?136, Table 3.2). F. grandis LSI was significantly lower at urban marshes compared to reference marshes (788?38 vs. 921?26, F=10.11, p=0.002, Table 3.3). A reference creek, Long Bayou, had the largest F. grandis LSI (984?49) and the lowest was an urban creek, Emmanuel Bayou (786?102 Table 3.4). LSI also varied across seasons for both species (Figs. 3.1a, 3.2a). Caloric density also differed between species and treatments. P. latipinna had similar caloric density at urban marshes (1039?45 cal g -1 ) compared to reference marshes (1074?30 cal g -1 , Table 3.2). A reference creek, Long Bayou, had the highest caloric density (1100?36 cal g -1 ) for P. latipinna and an urban creek, Emmanuel Bayou, had the lowest (981?30 cal g -1 , Table 3.2). F. grandis caloric density was significantly lower at urban marshes compared to reference creeks (982?13 cal g -1 vs. 1005?9 cal g -1 , F=5.41, p=0.023, Table 3.3). A reference creek, Long Bayou, had the highest caloric density for F. grandis (1019?9 cal g -1 ) and an urban creek, 72 ? Emmanuel Bayou, the lowest (950?19 cal g -1 , Table 3.3). Caloric density also varied across season for both species, but both species in urban and reference marshes followed similar patterns (Figs. 3.1b, 3.2b). Most metal concentrations were not significantly different in the F. grandis from reference or urban marshes (Table 3.4), and many were below detection levels (e.g. arsenic, lead, chromium). F. grandis did have significantly higher zinc at urban marshes (134.9?3.3 vs. 118.6?2.6, F=9.30, p=0.023) but all other trace elements were not significantly different in urban marshes compared to reference marshes. Discussion Urban salt marshes were shown to have F. grandis with lower condition, while P. latipinna had similar condition to reference marshes. The lack of significance for P. latipinna may have been partially caused by the difficultly in acquiring consistent numbers of P. latipinna from all sites. While both LSI and caloric density showed variation with season, urban creeks were lower than reference creeks for both measures for most of the year. Higher LSI measures in reference creeks suggest that these fish were generally more fit which may relate to better food quality, less exposure to pollutants or a combination of these factors. Seasonal fluctuations were likely related to reproduction, which in Alabama is from April to September for P. latipinna and March through August for F. grandis (Boschung and Mayden 2004). Cyprinodontiformes, including F. grandis and P. latipinna, invest large amounts of energy into reproduction (Meffe and Snelson 1993), and lipid reserves have been shown to vary seasonally in a number of Cyprinodontiformes in the Gulf of Mexico (de Vlaming et al. 1978). In F. heteroclitus, LSI 73 ? scores were shown to decrease as gonadal somatic index increased (Galloway and Munkittrick 2006) further suggesting that seasonal LSI shifts may be related to reproduction. The liver has been shown to respond with morphological changes to toxicant exposure and most research relating measures of fish liver size has assessed pollutant effects. For example, P. latipinna had lower percent lipid and weight gain when exposed to DDT (Benton et al. 1994). G. affinis, which is related to P. latipinna, had smaller livers in freshwater creeks contaminated by mining activity (Franssen 2009). F. heteroclitus, which is closely related to F. grandis, had smaller livers at urban-industrial impacted sites in Connecticut, and liver glycogen content (a form of energy storage) showed higher variation at impacted sites than at reference sites (Ferraro et al. 2001). In this study however there was very little evidence that toxic exposure was substantially higher. Sediment analyses indicated no significant levels of polycyclic aromatic hydrocarbons (see Chapter 2 Results) although there were instances of statistically higher metal concentrations in urban creeks, these differences may not have been substantial enough to generate a difference in fish health, since F. grandis metal concentration was not significantly different at urban marshes. The lower condition of urban fish of both species may also be a result of the metabolic costs of having to deal with salinity swings. While these species have been shown to be very tolerant of a wide range of salinities and temperatures, metabolic costs to living in such conditions still occur (Gonzalez and Head 2005, Nordlie 2006). Also, the rate of change in salinity can affect fish health and survival. C. variegatus, commonly found along the Gulf of Mexico, has one of the widest ranges of salinity tolerances for a cyprinodontiform species, yet it had 100% mortality when salinity was changed from 32ppt to freshwater and back in two hours (Serafy et al. 1997). Urban creeks in this study had wider ranges of salinity and more rapid 74 ? salinity changes, especially after rain events (Figs. 2.2 and 2.3, Chapter 2). P. latipinna has been shown to have increased metabolic demands in low salinity water (Trexler et al. 1992) and considering F. grandis has a higher salinity preference (Nordlie 2006), both species would likely exhibit responses to rapidly changing salinity in urban salt marshes. Similar to LSI, caloric density was significantly higher in reference creeks for F. grandis but not for P. latipinna. The F. grandis mean caloric density was slightly higher at both urban (4.32 Kcal g dry wt. -1 ) and reference (4.29 Kcal g dry wt. -1 ) sites compared to average values reported from Mississippi Juncus marshes (4.04Kcal g dry wt. -1 ) (de la Cruz 1983). Caloric density for F. grandis at urban (0.98 Kcal g wet wt -1 ) and reference creeks (1.00 Kcal g wet wt -1 ) were lower than caloric density measured for F. heteroclitus from North Carolina S. alterniflora marshes (1.31 Kcal g wet wt -1 ,Thayer et al. 1973). Thayer et al. (1973) reported that differences in caloric density can be related to reproductive state and lipid content. F. heteroclitus had higher lipid content in Spartina alterniflora?dominated marshes compared to marshes dominated by Phragmites australis, an invasive species in the United States (Weinstein et al. 2009). The authors reported that F. heteroclitus in marshes with P. australis had lower caloric density because of reduced access to the marsh surface by adults, less frequent flooding of the marsh, and less refuge for young fish. The differences in caloric density could also reflect a change in food sources. F. heteroclitus fed different diets exhibited different caloric density (Weisberg and Lotrich 1982) and F. grandis lipid content was higher when fed fish-feed in brackish mariculture ponds compared to wild fish (MacGregor et al. 1983). Caloric density was found to vary seasonally for three fish species in the Great Lakes, although it was not found to be significantly correlated with productivity of the lake, except for one species (Vondracek 1996). Although diet could not be assessed in this study, other research in urban estuaries has found different benthic 75 ? infauna communities and decapod crustaceans compared to reference sites (Partyka and Peterson 2008, Sanger et al. 2004, Lerberg et al. 2000, Washburn and Sanger 2010, Lawless 2008). These altered communities could be providing lower quality food resources for resident fish, which may be reflected in lower caloric density found in this study. Conclusions This study evaluated the impacts of low-medium density urban land-use on resident salt marsh fish condition. Salt marshes were located in six tidal creeks in west Florida and Alabama (3 urban and 3 reference). F. grandis and P. latipinna were collected seasonally using minnow traps and using a representative range of lengths for each species, LSI and caloric density were compared for differences between creek types. 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WINTER SPRING SUMMER FALL Calo r i c Den s i t y ( c a l / g wet wt -1 ) 900 1000 1100 1200 1300 1400 WINTER SPRING SUMMER FALL LSI 700 800 900 1000 1100 1200 1300 1400 Figure 3.1 Mean (?SE) seasonal a) Liver Somatic Index and b) caloric density (cal g wet wt. -1 ) for P. latipinna at urban and reference creeks. Urban is represented by black points and reference by white points. a? b? 84 ? ? WINTER SPRING SUMMER FALL LSI 500 600 700 800 900 1000 1100 ? WINTER SPRING SUMMER FALL Ca lor i c De ns it y ( c al / g we t w t -1 ) 940 960 980 1000 1020 1040 1060 Figure 3.2 Mean (?SE) seasonal a) Liver Somatic Index and b) caloric density (cal g wet wt. -1 ) for F. grandis at urban and reference creeks. Urban is represented by black points and reference by white points. a? b? 85 ? Table 3.1 Sample size for caloric density and Liver Somatic Index (LSI) seasonally by creek and treatment. Discrepancies for LSI are presented parenthetically. Urban Reference EB GB WB GC LB SQB Urban Reference P. latipinna Winter 23 10(9) 21(19) 23 10(9) 30 54(51) 63(62) Spring 12(5) 11(7) 26(21) 21(9) 0 3(2) 49(33) 24(11) Summer 2 0 33 (14) 5(4) 7(4) 16(5) 35 (16) 28(13) Fall 14(10) 0 28(24) 10(9) 25(23) 40(39) 42(34) 75(71) F. grandis Winter 11 22 21 (20) 12 27 40 54 (53) 79 Spring 30 40 38 40 40 40 108 120 Summer 30 36 40 28 40 40 106 108 Fall 25 12 40 10 40 40 77 90 86 ? Table 3.2 Mean (?SE) length, weight, condition measures and significant ANOVA results for P. latipinna per creek and treatment. Urban Reference EB GB WB GC LB SQB Urban Reference F,p Length (mm) 40.6?3.4 40.4?2.5 42.9?0.4 39.8?2.5 48.7?1.7 47.9?1.0 41.4?1.2 45.5?1.5 4.50, p=0.04 Weight (g) 1.22?0.28 1.15?0.28 1.39?0.05 1.05?0.37 1.99?0.24 1.85?0.11 1.26?0.12 1.63?0.18 NS Caloric density (cal g wet wt. -1 ) 981?30 1048?100 1074?58 1065?71 1100?36 1057?80 1039?45 1074?30 NS Liver weight (mg) 13.7?3.0 10.0?2.9 12.8?3.3 12.9?2.9 20.6?3.9 26.3?1.6 11.6?1.4 18.9?2.7 NS LSI 979?76 1250?132 969?49 1407?136 1164?49 978?105 1046?66 1163?70 NS 87 ? Table 3.3 Mean (?SE) length, weight, condition measures and significant ANOVA results for F. grandis per creek and treatment. Urban Reference EB GB WB GC LB SQB Urban Referenc e F,p Length (mm) 66.2?4.7 79.4?2.1 68.8?2.4 75.3?0.2 78.1?0.9 73.7?2.5 72.0?2.4 75.7?0.9 NS Weight (g) 5.61?1.1 8 8.08?0.74 6.17?0.87 6.83?0.16 8.29?0.22 7.06?0.64 6.71?0.54 7.39?0.3 4 20.58, p<0.00 1 Caloric density (cal g wet wt. -1 ) 950?19 1008?26 979?19 1009?14 1019?9 986?13 982?13 1005?9 5.41 p=0.02 3 Liver weight (mg) 55.8?16. 4 70.0?7.8 60.1?4.6 70.7?4.8 88.5?4.6 72.2?10.1 62.5?6.0 77.2?3.4 6.21, p=0.01 5 LSI 786?102 787?45 792?25 856?39 984?49 923?76 788?38 921?26 10.11 p=0.00 2 88 ? Table 3.4 Element concentration and mean (?SE) urban and reference for F. grandis in summer (July 2012) and fall (September 2012) per creek and treatment. SUMMER FALL Urban Reference Urban Reference Element EB GB WB GC LB SQB EB GB WB GC LB SQB Urban Reference F, p Al (ppm) 118 596 489 335 83 179 198 224 61 196 217 181 324.9?84.1 198.5?33.1 NS B (ppm) 6 7 6 5 5 7 4 4 5 4 4 4 5?10.5 5?0.5 NS Fe (ppm) 131 443 280 262 93 132 135 177 71 165 174 150 233.1?53.7 162.5?23.1 NS As (ppm) <0.1 <0.1 <0.1 <0.1 <0.1 <0.1 <0.1 <0.1 <0.1 <0.1 <0.1 <0.1 - - - Cd (ppm) <0.1 <0.1 <0.1 <0.1 <0.1 <0.1 <0.1 <0.1 <0.1 <0.1 <0.1 <0.1 - - - Cr (ppm) <0.1 <0.1 <0.1 <0.1 <0.1 <0.1 <0.1 <0.1 <0.1 <0.1 <0.1 <0.1 - - - Ni (ppm) <0.1 <0.1 <0.1 <0.1 <0.1 <0.1 <0.1 <0.1 <0.1 <0.1 <0.1 <0.1 - - - Pb (ppm) <0.1 <0.1 <0.1 <0.1 <0.1 <0.1 <0.1 <0.1 <0.1 <0.1 <0.1 <0.1 - - - Zn (ppm) 133 132 129 108 117 125 149 131 115 122 116 123 134.9?3.3 118.6?2.6 9.30, p=0.023 Cu (ppm) 13 11 13 9 13 12 21 14 13 12 11 16 14.4?1.6 12.2?1.0 NS 89 ? Chapter 4. Thesis Summary In this study I evaluated the impacts of urban land-use near Juncus-dominated salt marshes along the Gulf of Mexico through an evaluation of the resident cyprinodontiform community composition, size and abundance of individual species, and condition of two dominant species: Fundulus grandis and Poecilia latipinna. Most measures related to habitat conditions, fish abundance/biomass, and species composition showed significant differences at urban salt marshes compared to reference salt marshes. Plant biomass and stem density along the marsh edge were significantly lower at urban salt marshes compared to reference salt marshes. Salinity tended to fluctuate much more rapidly, had a larger range, and lower mean at urban marshes than reference marshes. Urban marshes had higher concentrations of metals (Cd, Cr, Mo, Zn, Pb) and carbon in the sediment compared to reference marshes. Urban marshes also had greater percent shallow slope than reference marshes. The cyprinodontiform community was significantly different at urban and reference salt marshes. Six species were more abundant at urban creeks, while only two were less abundant at urban creeks compared to reference creeks. Of the six species in greater abundance at urban creeks, five (P. latipinna, F. confluentus, G. holbrooki, A. xenica, F. confluentus) are often more abundant in brackish marshes than salt marshes (Boshung and Mayden 2004). The two species that were more abundant at reference salt marshes (F. similis and F. grandis) prefer higher salinities. Stout (1984) described F. similis, F. grandis, and C. variegatus as being dominant resident fish in Juncus-dominated marshes. Interestingly, two of these three were more common at reference marshes. Also the species more common at urban creeks (except G. holbrooki) were described by Stout (1984) as pond dominants in Juncus-marshes. These findings suggest that species found in urban marshes may be well adapted to the type of variable salinities expected in interior salt marsh ponds. 90 ? The condition of the fish at urban marshes was also different compared to reference marshes. Three species (F. confluentus, A. xenica, F. confluentus) were significantly larger (per mm length) at urban marshes compared to reference marshes (Figs. 2.8-2.12). One species, G. holbrooki , was significantly smaller at urban creeks. The most abundant species, P. latipinna and F. grandis, were not significantly different in size at urban creeks. However, the other condition measures for these species did show a response. Liver Somatic Index and caloric density were lower for both F. grandis and P. latipinna at urban creeks compared to reference creeks, but not significantly for P. latipinna. It was expected that P. latipinna might show better condition measures in urban salt marshes because of its tendency to occur in less saline waters, and this was supported by the additional condition measures. The changes in cyprinodontiform community and condition may be driven by a number of factors, but I believe that they are mainly driven by habitat alterations. Tolerance of contaminants from urban runoff likely played a role in the observed differences. Only heavy metals were evaluated in this study, and some were significantly elevated in marsh sediment of urban creeks (Table 2.3). Other contaminants may also be present that were not sampled, such as pesticides. These have been found to impact fish health (Lane and Livingston 1970, Benton et al. 1994, McCain et al. 1996) and might explain the lower condition of F. grandis and P. latipinna in urban creeks. F. heteroclitus, a closely related species, has been shown to adapt to pollutant loads (Nacci et al. 2010). If certain species are able to adapt better than others, their size and abundance may reflect this. The lower condition and abundance may also be a result of the stress of having to deal with salinity swings. While all of the Cyprinodontiformes in this study have demonstrated wide ranges of salinity tolerance the range of salinities that they have been found at in the field is 91 ? smaller (Griffith 1974, Nordlie 2006). For instance, F. Martin et al. (2009) found P. latipinna to be in higher abundance and better condition (greater weight) at brackish marshes compared to freshwater marshes in Louisiana. Thus P. latipinna may be best suited as a population in intermediate salinities, rather than in fresh or higher salinities, as seen in this study. Tolan and Nelson (2009) found salinity to be the driving factor in nekton community structure in Texas tidal creeks, more so even than dissolved oxygen, which was the original focus of their study. Perhaps more important than each species salinity preference is its ability to handle rapid increases and decreases in temperature. C. variegatus has the widest salinity range of all the species in this study, but it had 100% mortality in an experiment where it was rapidly changed from saltwater (32 ppt) to freshwater and back (Serafy et al. 1997). Fish abundance and fish condition could be influenced by the change in food source that often accompanies urbanization near salt marshes. While not directly measured, a number of studies have found different benthic infauna at urban salt marshes compared to reference marshes (Sanger et al. 2004, Lerberg et al. 2000, Washburn and Sanger 2011, Lawless 2008). Intraspecific and interspecific competition could also be occurring (Weisberg 1986), but most of the fish caught in this study have broad diets (Boschung and Mayden 2004), which would alleviate any food competition. However, without quantifying the food resources a limited food resource for competition to occur is impossible to determine. In addition to changing food resources, a reduction in plant cover may also increase spawning habitat for certain species. F. confluentus spawns on the substrate, typically on algal mats, which may explain partly the higher abundance of F. confluentus at urban marshes. C. variegatus also uses bare sediment for spawning, and G. holbrooki and P. latipinna as livebearers are not tied to a habitat for reproduction (Boschung and Mayden 2004). All three of 92 ? these species had higher abundance at urban creeks, although not significantly. A decrease in plant biomass and plant cover could also be providing less cover from predators (Daiber 1982). Along the marsh edge this may mean an increase in predation by aquatic predators such as fish. This would be mediated by the amount of shallow slope along the marsh edge. This reasoning is supported by the high fish abundance at Weekley Bayou, where there was high percent shallow slope at the marshes. If little shallow slope exists, Cyprinodontiformes may shift from the marsh edge to interior habitats such as tidal pools and creeks that are too shallow for aquatic predators. This is likely why Graham Creek had such low abundance. The steep slopes along the marsh edge may have limited fish to interior habitats which were not sampled. The interior habitats also support fish and the sampling effort along the marsh edge likely results in a bias towards the fish that frequent the edge rather than the interior. Habitat alterations may also mean urban marshes cannot support the same fish biomass. Meyer (2006) found salt marshes in North Carolina that were smaller and more isolated did not have self-sustaining populations of F. heteroclitus. These marshes were lacking small individuals, suggesting no recruitment or reproduction. Fish densities at tidal marshes in Louisiana, including G. holbrooki, P. latipinna, and C. variegatus, were lower at fragmented freshwater and oligohaline marshes compared to non-fragment marshes (Hitch et al. 2011). While this study has demonstrated that development near salt marshes can affect the resident fish communities, many questions remain. Changes in food resources and reproduction may be driving some of the differences observed in this study, but these were not examined. This study did not assess contaminants within the water column. Evaluating the possible contaminant load would further understanding of how urban land-use may impact these systems. DDT and dieldrin, both pesticides, have been shown to impact P. latipinna (Benton et al. 1994, Lane and 93 ? Livingston 1970). F. grandis had accumulated PCBs, DDT, and polycyclic aromatic hydrocarbons (PAHs) in Tampa Bay, Florida. C. variegatus was shown to be sensitive to crude oil and an oil dispersant (Adams et al. 1999). Also, Sanger et al. (2011) found elevated levels of PCBs, DDT, and PAHs in a number of urban tidal creeks in the Gulf of Mexico, which makes these contaminants important to investigate. Having demonstrated differences in abundance and condition, the effects of these changes on transient fish and other predators of these resident Cyrpinodontiformes are important to know. Transient fish are often economically valuable fish such as speckled trout (Cynoscion nebulosus), Southern flounder (Paralichthys lethostigma), and red drum (Sciaenops ocellatus). Maintaining healthy prey resources will help sustain these fisheries. Also, while not evaluated in this study, F. jenkinsi is a species of concern that is closely tied to salt marshes. Typically this species is abundant in salinities less than 16ppt and in marshes receiving significant freshwater inputs (Lopez et al. 2011). These fit the conditions found at this study?s urban salt marshes. Peterson et al. (2003) suggests that the patchy and temporal nature of low salinity salt marshes may affect F. jekinsi recruitment. If that is the case, urban salt marshes may provide a more consistent, albeit with greater salinity swings, low salinity salt marsh habitat. Research into how valuable urban salt marshes are to this vulnerable species could be important for future management and protection of this species. This study can inform future land development and planning near these tidal creeks. The differences observed in this study make it apparent that salt marshes need to be protected within the tidal creek systems of the Gulf of Mexico. Previous studies have shown the benefit of salt marshes compared to hardened shorelines for providing fish habitat (Partyka and Peterson 2008, Seitz et al. 2006, Bilkovic and Rogerro 2008), but not how salt marshes within an urban 94 ? landscape may be impacted. This study has demonstrated that urban marshes are indeed altered in the fish habitat they provide. Thus, while it is important to keep salt marshes even in urban landscapes, it is even more important to maintain vegetated buffers and non-developed areas around salt marshes. Having vegetated buffers and stormwater retention may help alleviate some of the spikes in freshwater and help remove contaminants from runoff. Riparian buffers have been shown to decrease nutrient loads (Mayer et al. 2007) and remove metals and pesticides (Palone and Todd 1998, Castelle et al. 1994) flowing to streams. Another alternative could be creating areas for runoff to filter into the ground, such as rain gardens and ditches, rather than running directly into the tidal creeks. These would provide the same benefit as riparian buffers, while also allowing for waterfront access. Salt marshes themselves can act as a buffer by acting as a sink for excess nutrients (Mitch et al. 2009). While salt marshes are clearly altered with nearby development, benefits exist for having these habitats within the larger estuarine system even in an altered state. Salt marshes provide a number of ecological services including protecting coastlines from wave erosion, being a sink for certain nutrients/pollutants, and providing critical habitat for a variety of organisms, such as fish (Kennish 2001). While studies have found that development can impact salt marshes, they also have shown that certain ecosystem services may still be provided by urban marshes, which is why they are promoted as an alternative to hardened shorelines (Currin et al. 2010). By removing salt marshes from the estuarine system those ecosystem services are no longer available. Several studies have shown altered fish assemblages at altered shorelines (i.e. bulkheads and riprap, Bilkovic and Roggero 2008, Bradley 2011, Partyka and Peterson 2008), which may have consequences for the commercial and recreational fisheries. By maintaining saltmarshes within tidal creeks these 95 ? important ecosystems are still able to provide a number of important ecosystem services, although perhaps in a diminished way. 96 ? Literature Cited Adams, S.M., K.D. Ham, M.S. Greeley, R.F. LeHew, D.E. Hinton, and C.F. Saylor. 1996. Downstream gradients in bioindicator responses: point source contaminant effects on fish health. Canadian Journal of Fisheries and Aquatic Sciences 53:2177-2187. Assessing the Impact of Coastal Development on Ecosystem Health. NOAA Technical Benton, M.J., A.C. Nimrod, and W.H. Benson. 1994. Evaluation of growth and energy storage as biological markers of DDT exposure in sailfin mollies. Ecotoxicology and Environmental Safety 29:1-12. 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Environmental Monitoring and Assessment 159:15-34. Washburn, T., and D. Sanger. 2011. Land use effects on macrobenthic communities in southeastern United States tidal creeks. Environmental Monitoring and Assessment 180:177- 188. Weisberg, S.B., 1986. Competition and coexistence among four estuarine species of Fundulus. American Zoologist 26(1):249-257. 99 ? Appendix I. Habitat Data Table 1. Mean percent plant cover for each plant species along each marsh transect. See Fig. 2.1 for creek abbreviations. Site J. roemarianus C. jamaicense D. spicata S.patens S. lancifolia S. sempervirens L. chinensis S. europaea GB1 60 0.5 0.5 6 0 0.1 0 0 GB2 35.5 4 0.8 0 0 0.2 0 0 GB3 38 0.1 36.5 0 0 0 0 0 GB4 42.8 0 0 0 0 0.5 0 0 EB1 39.4 9.5 0 0 0.1 0 0 0 EB2 38.3 14.1 0 0 1.5 0 0 0 EB3 28.5 4.6 0 0 0 0 0 0 WB1 24.9 0 0 0 0 0 0 0 WB2 31 0.5 0 0 0 0 0 0 WB3 29 20 0 0 0 0 0 0 WB4 54.5 0 0 0 0 0 0 0 SQB1 39.4 0.5 7.5 0 0 0 0 0 SQB2 40.7 0 0 0 0 0 0 0 SQB3 37.1 0 0.1 3.5 0 0 1.5 0 SQB4 40 0.1 0 0.1 0 0 1 0 GC1 49.5 0 17.5 0 0 1.6 0 0 GC2 27.5 7.6 0 0 0 0 0 0 GC3 33.5 10.5 0.1 0 0 0.5 0 0 GC4 44.6 2 9.5 0 0 0.5 0 0 LB1 46.5 1.5 0 0 0 0 0 0 LB2 22 1 0 8 0 2 0.5 0 LB3 34 1 0.5 0 0 3 0 0 LB4 40.5 0 0 4 0 3 1 3 100 ? Table 2. Salinity and water temperature for each marsh at each seasonal fish sampling event measured with YSI? Season Site Salinity (ppt) Temperature (?C) WINTER EB1 18.2 13.4 SPRING EB1 9.0 19.2 SUMMER EB1 6.3 29.1 FALL EB1 7.7 29.7 WINTER EB2 18.7 13.8 SPRING EB2 8.5 18.1 SUMMER EB2 11.0 29.5 FALL EB2 8.1 29.5 WINTER EB3 20.0 13.9 SPRING EB3 10.1 18.0 SUMMER EB3 11.5 29.4 FALL EB3 9.0 29.3 WINTER GB1 17.7 13.7 SPRING GB1 1.7 20.5 SUMMER GB1 5.1 33.2 FALL GB1 2.1 26.6 WINTER GB2 20.1 13.7 SPRING GB2 2.1 20.7 SUMMER GB2 4.0 33.2 FALL GB2 4.1 27.4 WINTER GB3 22.3 13.1 SPRING GB3 2.1 20.8 SUMMER GB3 10.3 32.2 FALL GB3 3.8 27.2 WINTER GB4 23.2 13.0 SPRING GB4 6.4 21.3 SUMMER GB4 8.2 32.2 FALL GB4 3.8 26.8 WINTER GC1 18.7 15.3 SPRING GC1 1.9 19.6 SUMMER GC1 16.3 31.8 FALL GC1 7.9 30.0 WINTER GC2 20.0 15.6 SPRING GC2 2.6 19.6 SUMMER GC2 13.3 28.1 FALL GC2 7.0 29.4 WINTER GC3 19.9 14.7 SPRING GC3 3.9 19.8 101 ? SUMMER GC3 16.7 31.6 FALL GC3 8.3 29.9 WINTER GC4 20.0 14.7 SPRING GC4 5.4 19.9 SUMMER GC4 16.1 30.8 FALL GC4 6.8 30.1 WINTER LB1 23.4 17.8 SPRING LB1 5.3 19.1 SUMMER LB1 17.9 31.6 FALL LB1 9.7 29.0 WINTER LB2 23.7 15.5 SPRING LB2 9.1 19.7 SUMMER LB2 18.0 31.3 FALL LB2 8.8 28.7 WINTER LB3 23.3 16.4 SPRING LB3 10.7 19.6 SUMMER LB3 18.1 31.4 FALL LB3 8.6 30.0 WINTER LB4 23.3 15.8 SPRING LB4 11.2 19.8 SUMMER LB4 18.3 31.2 FALL LB4 8.8 29.4 WINTER SQB1 22.9 14.0 SPRING SQB1 13.5 19.2 SUMMER SQB1 16.1 29.4 FALL SQB1 13.5 29.7 WINTER SQB2 22.4 14.3 SPRING SQB2 13.9 19.1 SUMMER SQB2 16.1 29.3 FALL SQB2 13.7 28.5 WINTER SQB3 23.4 12.8 SPRING SQB3 14.5 18.9 SUMMER SQB3 16.2 29.4 FALL SQB3 13.4 28.2 WINTER SQB4 23.3 13.1 SPRING SQB4 14.6 18.8 SUMMER SQB4 16.2 29.3 FALL SQB4 13.3 28.2 WINTER WB1 20.9 14.6 SPRING WB1 14.6 20.3 SUMMER WB1 2.4 30.9 FALL WB1 2.4 24.8 WINTER WB2 22.7 14.1 102 ? SPRING WB2 15.4 20.5 SUMMER WB2 3.8 30.1 FALL WB2 3.1 26.0 WINTER WB3 21.0 14.5 SPRING WB3 15.0 20.9 SUMMER WB3 5.8 32.0 FALL WB3 13.2 29.4 WINTER WB4 23.1 13.4 SPRING WB4 16.5 20.6 SUMMER WB4 8.5 32.4 FALL WB4 13.7 29.1 103 ? 0 5 10 15 20 25 30 35 40 0 5 10 15 20 25 3/31/2012 4/30/2012 5/31/2012 6/30/2012 7/31/2012 8/31/2012 9/30/2012 10/31/2012 11/30/2012 12/31/2012 1/31/2013 2/28/2013 Temperature ? (?C) Salinity ? (ppt) Emmanuel?Bayou Salinity Temperature Figure 1. Hourly averages of salinity and temperature data from conductivity loggers for each creek. Long Bayou is missing data from 9/8/12-1/4/13.?? ?? 104 ? 0 5 10 15 20 25 30 35 40 0 5 10 15 20 25 3/31/2012 4/30/2012 5/31/2012 6/30/2012 7/31/2012 8/31/2012 9/30/2012 10/31/2012 11/30/2012 12/31/2012 1/31/2013 2/28/2013 Temperature ? (?C) Salinity ? (ppt) Grande?Bayou Salinity Temperature 105 ? 0 5 10 15 20 25 30 35 40 0 5 10 15 20 25 3/31/2012 4/30/2012 5/31/2012 6/30/2012 7/31/2012 8/31/2012 9/30/2012 10/31/2012 11/30/2012 12/31/2012 1/31/2013 2/28/2013 Temperature ? (?C) Salinity ? (ppt) Weekley?Bayou Salinity Temperature 106 ? 0 5 10 15 20 25 30 35 40 0 5 10 15 20 25 3/30/2012 4/30/2012 5/31/2012 6/30/2012 7/31/2012 8/31/2012 9/30/2012 10/31/2012 11/30/2012 12/31/2012 1/31/2013 2/28/2013 Temperature ? (?C) Salinity ? (ppt) Graham?Creek Salinity Temperature 107 ? 0 5 10 15 20 25 30 35 40 0 5 10 15 20 25 3/31/2012 4/30/2012 5/31/2012 6/30/2012 7/31/2012 8/31/2012 9/30/2012 10/31/2012 11/30/2012 12/31/2012 1/31/2013 2/28/2013 Temperature ? (?C) Salinity ? (ppt) Long?Bayou Salinity Temperature 108 ? 0 5 10 15 20 25 30 35 40 0 5 10 15 20 25 3/31/2012 4/30/2012 5/31/2012 6/30/2012 7/31/2012 8/31/2012 9/30/2012 10/31/2012 11/30/2012 12/31/2012 1/31/2013 2/28/2013 Temperature ? (?C) Salinity ? (ppt) Stone?Quarry?Bayou Salinity Temperature 109 ? Table 3. Soil concentrations of elements at each marsh. Site Ca (ppm) Cd (ppm) Cr (ppm) Cu (ppm) Fe (ppm) K (ppm) Mg (ppm) Mn (ppm) Mo (ppm) Na (ppm) Ni (ppm) P (ppm) Pb (ppm) Zn (ppm) %C %N %S EB1 1198 0.07 0.17 0.89 71.5 472 1572 0.92 0.18 7527 0.30 31.0 3.80 3.40 13 0.68 0.76 EB2 2571 0.03 0.12 1.02 86.4 1064 3582 1.91 0.08 20243 0.57 48.6 3.81 5.99 19 1.00 1.71 EB3 2219 0.05 0.18 1.11 72.7 1058 3427 2.95 0.08 19691 0.37 54.0 4.64 12.81 18 0.90 1.45 GB1 1161 0.02 0.11 0.38 81.9 462 1582 2.25 <0.03 8654 0.13 37.0 4.14 5.77 7 0.37 0.47 GB2 2622 0.10 0.18 0.34 52.4 1639 5011 4.25 <0.04 31061 0.28 38.8 8.12 6.90 21 1.04 1.35 GB3 3448 0.11 0.05 0.25 47.9 1810 5489 10.28 0.07 36075 0.26 41.0 6.14 5.94 24 1.16 1.20 GB4 4434 0.08 0.15 0.10 48.2 1145 3546 5.44 <0.04 19030 0.22 50.1 19.79 7.13 16 0.81 1.12 GC1 2417 <0.02 0.07 0.33 87.7 1064 3417 25.21 <0.05 19059 0.59 35.2 3.46 6.48 18 1.20 0.45 GC2 4169 0.03 0.17 0.40 69.9 1033 3114 5.51 <0.05 18067 0.38 102.9 3.68 8.08 16 1.13 0.76 GC3 996 0.05 0.03 0.24 56.5 401 1333 12.77 <0.03 5945 0.28 29.0 1.64 2.91 7 0.42 0.29 GC4 1276 <0.01 0.03 0.25 57.0 379 1156 19.94 <0.03 6499 0.33 23.4 1.56 3.60 6 0.42 0.19 LB1 1979 0.02 0.09 0.39 68.9 1243 3121 9.09 <0.04 18018 0.38 106.5 3.08 5.19 13 0.88 0.53 LB2 900 <0.01 0.06 0.33 53.4 424 1179 2.43 <0.03 5550 0.18 30.4 1.87 3.09 5 0.32 0.17 LB3 1648 0.02 0.08 0.34 99.6 767 2205 10.33 <0.03 12523 0.22 45.7 2.78 3.13 8 0.47 0.53 LB4 1530 <0.01 0.06 0.40 96.2 1076 2874 18.72 <0.04 18112 0.43 43.7 2.89 5.06 12 0.68 0.57 SQB1 2999 0.08 0.07 0.95 77.6 637 1787 2.55 <0.04 8731 0.30 34.7 3.31 4.35 9 0.55 0.79 SQB2 4114 0.07 0.08 0.58 50.4 645 1753 3.46 <0.03 9585 0.32 37.9 1.84 4.67 6 0.39 0.50 SQB3 5893 0.02 0.09 0.48 60.9 1069 3080 6.18 0.07 17168 0.43 37.2 1.70 7.72 13 0.76 1.08 SQB4 6159 0.03 0.09 0.13 18.2 881 2309 3.57 0.05 14639 0.17 23.3 0.66 3.40 9 0.52 0.59 WB1 7475 0.07 0.15 0.24 17.3 749 2773 1.08 <0.04 12759 0.11 34.7 1.35 5.54 15 0.75 0.86 WB2 2507 0.09 0.11 0.67 43.2 874 3107 1.49 <0.04 15455 0.23 37.2 5.72 7.53 15 0.78 0.86 WB3 2972 0.05 0.13 0.69 60.5 1329 4560 2.26 <0.05 26944 0.31 58.2 6.51 9.71 23 1.16 1.71 WB4 2907 0.10 0.06 0.42 37.7 1166 3849 4.65 <0.04 22500 0.22 57.6 3.50 5.78 19 0.98 1.31 110 ? Table 4. Stem counts, stem density, and plant biomass for each marsh. Site Stem count Stem density m -2 Biomass m -2 EB1 477 636.0 568.0 EB2 456 608.0 863.1 EB3 679 905.3 1358.9 GB1 530 706.7 862.1 GB2 615 820.0 862.3 GB3 361 481.3 534.3 GB4 759 1012.0 1127.6 GC1 843 1124.0 1653.5 GC2 439 585.3 710.5 GC3 1023 1364.0 1942.9 GC4 911 1214.7 1467.9 LB1 439 585.3 656.7 LB2 573 764.0 984.8 LB3 401 534.7 819.1 LB4 741 988.0 1041.3 SQB1 531 708.0 911.9 SQB2 721 961.3 1222.1 SQB3 752 1002.7 991.7 SQB4 686 914.7 1214.3 WB1 287 382.7 585.3 WB2 200 266.7 180.2 WB3 454 605.3 345.4 WB4 718 957.3 1328.4 111 ? Table 5. Percent shallow, moderate, and steep marsh edge slope for each marsh. Site Shallow Moderate Steep LB1 5 25 70 LB2 0 15 85 LB3 45 35 20 LB4 27 11 62 GC1 1 5 94 GC2 1 10 89 GC3 0 10 90 GC4 5 15 80 SQB1 25 50 25 SQB2 13 54 33 SQB3 8 43 49 SQB4 35 45 20 WB1 13 12 75 WB2 15 5 80 WB3 70 30 0 WB4 35 35 30 EB1 90 9 1 EB2 15 5 80 EB3 50 10 40 GB1 15 75 10 GB2 50 30 20 GB3 2 18 80 GB4 65 15 20 112 ? Table 6. Mean percent plant cover of plant species along the marsh edge for each marsh. Site J. roemarianus C. jamaicense D. spicata S. alterniflora S. lancifolia S. sempervirens I. sagittata L. lineare GC1 79.7 0 0 0 0 0.3 0 0 GC2 43.3 0 0 0 0 0 0 0 GC3 51.3 3.3 23.3 0 0 0 0 0 GC4 38.3 0 21.7 0 0 0 0.3 0.3 LB1 63.3 0 0 0 0 0 0 0 LB2 50.0 0 0 0 0 0 0 0 LB3 18.3 0 0 10.0 0 0 0 0 LB4 63.3 0 0 0 0 0 0 0 GB1 66.7 0 0.7 0 0 0 0 0 GB2 61.7 0 3.7 0 0 0 0 0 GB3 56.7 0 0 0 0 0 0 0 GB4 101.7 0 0 0 0 0 0 0 WB1 25.0 1.7 0 0 0 0 0 0 WB2 47.7 1.7 0 0 0 0.3 0 0 WB3 66.7 0 0 0 0 0 0 0 WB4 103.3 0 0 0 0 0 0 0 EB1 36.7 0 0 0 3.3 0 0 0 EB2 75.0 0 0 0 0 0 0 0 EB3 70.0 0 0 0 0 0 0 0 SQB1 60.0 0 0 0 5 0 0 0 SQB2 55.0 0 0 0 0 0 0 0 SQB3 60.0 0 3.3 0 0 0 0 0 SQB4 51.7 0 0 0 0 0 0 0 113 ? Appendix II. Fish Data ? Table 7. Fish LSI and associated measures averaged for each sampling event at each marsh. All lengths are total length unless indicated with an SL for standard length. See Fig. 2.13 for species abbreviations. Date Site Species Sex Length (mm) Weigh (g)t N liver weight (g) LSI 12/12/2011 GB2 PLAT M 58 3.0024 1 0.0212 1415.91 12/12/2011 GB4 PLAT F 38 0.8259 6 0.0089 1351.27 12/12/2011 GB4 PLAT M 37 0.8840 2 0.0055 1253.26 12/12/2011 GB1 FGRD F 78 6.6123 4 0.0827 1131.38 12/12/2011 GB1 FGRD M 77 6.7425 6 0.0519 842.36 12/12/2011 GB2 FGRD F 82 7.6685 5 0.0571 742.43 12/12/2011 GB2 FGRD I 45 1.0081 1 0.0059 585.26 12/12/2011 GB2 FGRD M 77 6.6673 4 0.0395 6644.47 12/12/2011 GB4 FGRD F 61 2.8438 1 0.0208 731.42 12/12/2011 GB4 FGRD M 55 1.9377 1 0.0178 918.61 12/12/2011 WB2 FGRD F 55 2.4289 5 0.0204 843.96 12/12/2011 WB2 FGRD I 46 1.1974 2 0.0085 710.27 12/12/2011 WB2 FGRD M 56 2.4510 3 0.0271 1081.83 12/12/2011 WB2 PLAT F 39 1.0635 6 0.0089 1003.27 12/12/2011 WB2 PLAT M 44 1.4771 3 0.0102 914.54 12/12/2011 WB3 FGRD NA 52 1.8427 10 0.0161 883.80 12/12/2011 WB3 PLAT NA 42 1.3097 10 0.0155 1035.38 12/12/2011 WB4 FGRD F 57 2.3690 1 0.0279 1177.71 12/14/2011 EB1 PLAT F 36 0.8013 7 0.0105 1529.86 12/14/2011 EB1 PLAT M 45 1.5388 3 0.0203 1368.50 12/14/2011 EB2 FGRD I 40 0.6370 1 0.0054 847.72 12/14/2011 EB2 PLAT F 37 0.8080 7 0.0091 958.74 114 ? 12/14/2011 EB2 PLAT M 35 0.7386 3 0.0102 1331.11 3/11/2012 EB1 FGRD F 73 7.2304 4 0.3153 960.30 3/11/2012 EB1 FGRD M 75 7.5622 4 0.0319 354.96 3/11/2012 EB2 FGRD F 84 11.2070 4 0.1982 1757.77 3/11/2012 EB2 FGRD I 44 1.0059 2 0.0065 696.65 3/11/2012 EB2 FGRD M 77 7.9618 5 0.0772 868.33 12/14/2012 EB3 FGRD F 61 3.0501 3 0.0301 1042.61 12/14/2012 EB3 FGRD I 45 1.1120 3 0.0106 856.38 12/14/2012 EB3 FGRD M 72 5.4402 4 0.0402 716.67 12/14/2012 EB3 PLAT F 42 1.1109 2 0.0142 1281.45 12/14/2012 SQB1 FGRD F 78 7.0163 3 0.0625 935.57 12/14/2012 SQB1 FGRD I 49 1.3886 3 0.0160 1114.84 12/14/2012 SQB1 FGRD M 66 3.7509 4 0.0514 1396.53 12/14/2012 SQB1 PLAT F 44 1.2672 6 0.0165 1329.20 12/14/2012 SQB1 PLAT M 50 1.9803 4 0.0441 1047.51 12/14/2012 SQB2 FGRD F 76 7.4400 4 0.0529 657.81 12/14/2012 SQB2 FGRD I 52 1.6609 2 0.0238 1504.19 12/14/2012 SQB2 FGRD M 81 8.4974 4 0.0894 733.18 12/14/2012 SQB2 PLAT F 56 2.8041 5 0.0535 548.37 12/14/2012 SQB2 PLAT M 57 3.1226 5 0.0453 621.87 12/14/2012 SQB3 FGRD F 71 6.9547 4 0.0970 1246.65 12/14/2012 SQB3 FGRD I 42 0.8025 2 0.0083 1038.50 12/14/2012 SQB3 FGRD M 65 3.9910 4 0.0421 1127.80 12/14/2012 SQB4 FGRD F 77 7.5159 3 0.0967 1079.96 12/14/2012 SQB4 FGRD I 44 1.0588 4 0.0084 821.50 12/14/2012 SQB4 FGRD M 76 6.0536 3 0.0476 805.39 12/14/2012 SQB4 PLAT F 45 1.3986 6 0.0203 1088.61 12/14/2012 SQB4 PLAT M 39 0.8507 4 0.0081 1319.00 12/15/2012 GC2 FGRD M 55 2.1030 1 0.0239 1136.47 12/15/2012 GC2 PLAT F 31 0.6018 3 0.0074 963.15 115 ? 12/15/2012 GC3 FGRD NA 71 5.1468 8 0.0497 935.71 12/15/2012 GC3 PLAT NA 43 1.5138 10 0.0160 853.32 12/15/2012 GC4 PLAT F 36 0.7474 5 0.0109 1032.01 12/15/2012 GC4 PLAT M 34 0.5996 5 0.0089 1196.62 12/15/2012 LB1 FGRD F 77 6.0428 1 0.0546 903.55 12/15/2012 LB1 FGRD I 40 0.7768 1 0.0103 1325.95 12/15/2012 LB1 FGRD M 110 18.7886 1 0.2407 1281.10 12/15/2012 LB1 PLAT F 42 1.3238 6 0.0185 904.25 12/15/2012 LB1 PLAT M 46 1.3414 3 0.0124 904.32 12/15/2012 LB2 FGRD F 63 3.0043 3 0.0269 898.19 12/15/2012 LB2 FGRD I 57 1.9902 1 0.0210 1055.17 12/15/2012 LB3 FGRD F 86 10.1200 4 0.1115 1131.75 12/15/2012 LB3 FGRD I 50 1.6473 2 0.0095 528.53 12/15/2012 LB3 FGRD M 84 10.0073 4 0.0949 921.59 12/15/2012 LB4 FGRD F 74 6.6626 5 0.0690 1040.35 12/15/2012 LB4 FGRD M 77 7.8086 5 0.0850 1102.18 3/9/2012 GB1 FGRD F 72 6.1951 5 0.0845 1392.92 3/9/2012 GB1 FGRD M 75 6.9791 5 0.0355 592.49 3/9/2012 GB1 PLAT F 42 1.1509 5 0.0054 1319.41 3/9/2012 GB2 FGRD F 75 6.2645 5 0.0751 1264.68 3/9/2012 GB2 FGRD I 50 1.3473 1 0.0036 267.20 3/9/2012 GB2 FGRD M 83 8.5734 4 0.0408 458.74 3/9/2012 GB2 PLAT F 37 0.9022 1 0.0134 563.60 3/9/2012 GB3 FGRD F 85 9.9276 5 0.1341 1584.06 3/9/2012 GB3 FGRD M 79 7.3909 5 0.0532 691.91 3/9/2012 GB3 PLAT F 36 0.7149 1 0.0048 436.48 3/9/2012 GB4 FGRD F 78 8.3075 5 0.0717 789.52 3/9/2012 GB4 FGRD M 86 9.7472 5 0.0446 514.90 3/9/2012 WB1 FGRD F 103 14.6406 4 0.1212 893.15 3/9/2012 WB1 FGRD M 93 14.2022 4 0.0964 707.74 116 ? 3/9/2012 WB2 FGRD F 67 8.0627 5 0.1507 1904.58 3/9/2012 WB2 FGRD I 45 1.2577 1 0.0097 771.25 3/9/2012 WB2 FGRD M 77 7.7601 4 0.0509 713.50 3/9/2012 WB2 PLAT F 47 1.6772 1 0.0114 699.88 3/9/2012 WB2 PLAT M 43 1.4653 5 0.0093 1006.28 3/9/2012 WB3 FGRD F 76 7.3758 4 0.1037 1302.74 3/9/2012 WB3 FGRD I 44 0.9807 1 0.0043 438.46 3/9/2012 WB3 FGRD M 70 5.5044 5 0.0285 513.65 3/9/2012 WB3 PLAT F 45 1.5005 5 0.0195 973.70 3/9/2012 WB3 PLAT M 58 2.7583 2 0.0171 534.06 3/9/2012 WB4 FGRD F 80 9.6172 4 0.1285 1284.87 3/9/2012 WB4 FGRD M 74 7.6056 5 0.0486 725.88 3/9/2012 WB4 PLAT F 39 1.0012 6 0.0144 1114.66 3/9/2012 WB4 PLAT M 46 1.6023 2 0.0095 1165.42 3/10/2012 GC1 FGRD F 84 10.1698 4 0.1331 1148.02 3/10/2012 GC1 FGRD M 71 5.8435 4 0.0269 466.56 3/10/2012 GC2 FGRD F 82 9.0396 5 0.0981 977.86 3/10/2012 GC2 FGRD M 85 9.0945 5 0.0459 513.62 3/10/2012 GC2 PLAT F 51 2.1072 1 0.0293 959.09 3/10/2012 GC3 FGRD F 81 8.8258 6 0.1062 1225.07 3/10/2012 GC3 FGRD M 90 11.4100 4 0.0845 727.64 3/10/2012 GC3 PLAT F 35 0.6623 1 0.0031 699.64 3/10/2012 GC4 FGRD F 75 6.8625 6 0.0572 741.52 3/10/2012 GC4 FGRD M 74 6.0327 4 0.0418 658.97 3/10/2012 GC4 PLAT F 46 1.6932 5 0.0286 2138.65 3/10/2012 GC4 PLAT M 49 1.7364 2 0.0154 1003.49 3/10/2012 LB1 FGRD F 83 9.6422 5 0.0997 1093.71 3/10/2012 LB1 FGRD F 80 8.6768 5 0.0556 523.80 3/10/2012 LB2 FGRD F 90 11.6466 4 0.1297 1039.51 3/10/2012 LB2 FGRD I 45 1.1415 1 0.0095 832.24 117 ? 3/10/2012 LB2 FGRD M 82 8.6066 5 0.0424 472.81 3/10/2012 LB3 FGRD F 81 9.4513 4 0.1209 1041.58 3/10/2012 LB3 FGRD M 79 8.4794 5 0.0374 380.74 3/10/2012 LB4 FGRD F 91 11.8238 4 0.1702 1303.96 3/10/2012 LB4 FGRD I 44 0.9762 1 0.0084 860.48 3/10/2012 LB4 FGRD M 94 12.5839 4 0.0467 367.17 3/11/2012 EB1 FGRD F 73 7.2304 4 0.0788 960.30 3/11/2012 EB1 FGRD M 75 7.5622 4 0.0319 354.96 3/11/2012 EB1 PLAT F 42 1.4703 4 0.0185 1130.25 3/11/2012 EB2 FGRD F 84 11.2070 4 0.1982 1757.77 3/11/2012 EB2 FGRD I 47 1.3747 1 0.0075 545.57 3/11/2012 EB2 FGRD M 77 7.9618 5 0.0772 858.33 3/11/2012 EB3 FGRD F 86 11.7406 5 0.1604 1212.43 3/11/2012 EB3 FGRD I 41 0.7935 1 0.0035 441.08 3/11/2012 EB3 FGRD M 81 9.7399 4 0.0836 909.18 3/11/2012 EB3 PLAT F 42 1.2013 1 0.0093 1339.05 3/11/2012 SQB1 FGRD F 84 11.3037 4 0.1933 1528.43 3/11/2012 SQB1 FGRD I 42 0.8592 1 0.0135 1571.23 3/11/2012 SQB1 FGRD M 81 9.1106 4 0.0578 600.25 3/11/2012 SQB1 PLAT F 38 0.8553 1 0.0048 1345.36 3/11/2012 SQB2 FGRD F 85 10.0572 4 0.1379 1261.95 3/11/2012 SQB2 FGRD M 78 8.6268 5 0.0720 716.04 3/11/2012 SQB2 PLAT M 70 5.0146 1 0.0240 802.50 3/11/2012 SQB3 FGRD F 83 9.4946 4 0.0941 1121.07 3/11/2012 SQB3 FGRD M 80 8.3231 5 0.0706 847.70 3/11/2012 SQB4 FGRD F 81 9.2719 5 0.1031 1107.65 7/17/2012 GB1 FGRD F 75 6.4423 3 0.0289 335.24 7/17/2012 GB1 FGRD M 63 3.5393 3 0.0108 307.17 7/17/2012 GB2 FGRD F 76 7.1843 6 0.0625 718.54 7/17/2012 GB2 FGRD M 66 4.2047 3 0.0186 403.60 118 ? 7/17/2012 GB3 FGRD F 63 3.2558 1 0.0218 669.57 7/17/2012 GB4 FGRD F 87 10.0643 4 0.0737 707.27 7/17/2012 GB4 FGRD I 48 1.2932 1 0.0037 286.11 7/17/2012 GB4 FGRD M 84 9.8540 5 0.0529 513.62 7/17/2012 WB1 FGRD F 69 4.9609 5 0.0343 557.31 7/17/2012 WB1 FGRD M 56 2.4962 2 0.0078 318.35 7/17/2012 WB1 PLAT F 39 1.0537 6 0.0065 1107.46 7/17/2012 WB2 FGRD F 68 5.1357 4 0.0457 642.43 7/17/2012 WB2 FGRD I 43 0.8821 2 0.0024 275.72 7/17/2012 WB2 FGRD M 69 5.2539 3 0.0349 576.82 7/17/2012 WB2 PLAT F 41 1.2193 5 0.0105 1010.41 7/17/2012 WB3 FGRD F 69 5.9640 4 0.0378 421.00 7/17/2012 WB3 PLAT F 50 2.2129 3 0.0151 1251.83 7/17/2012 WB4 FGRD F 77 8.0900 4 0.1233 1030.12 7/17/2012 WB4 FGRD I 45 1.3023 2 0.0027 198.14 7/17/2012 WB4 FGRD M 88 10.0938 3 0.0961 938.31 7/18/2012 LB1 FGRD F 80 8.9419 4 0.1042 1027.87 7/18/2012 LB1 FGRD I 45 1.0627 1 0.0148 1392.68 7/18/2012 LB1 FGRD M 75 7.6385 5 0.0650 851.06 7/18/2012 LB1 PLAT F 41 1.2491 2 0.0148 1182.12 7/18/2012 LB2 FGRD F 84 9.3239 4 0.0781 797.49 7/18/2012 LB2 FGRD I 44 1.0388 1 0.0078 750.87 7/18/2012 LB2 FGRD M 82 8.6822 5 0.0842 789.87 7/18/2012 LB3 FGRD F 86 11.1213 4 0.1348 1417.85 7/18/2012 LB3 FGRD I 45 1.1852 2 0.0047 395.98 7/18/2012 LB3 FGRD M 81 9.2039 4 0.0803 879.03 7/18/2012 LB4 FGRD F 86 10.0875 4 0.1156 1155.90 7/18/2012 LB4 FGRD I 43 1.0214 1 0.0077 753.87 7/18/2012 LB4 FGRD M 78 7.8158 5 0.0762 1007.40 7/18/2012 LB4 PLAT F 43 1.2085 1 0.0058 561.21 119 ? 7/18/2012 LB4 PLAT M 48 1.7582 1 0.0125 1248.73 7/19/2012 EB1 FGRD F 55 2.1361 3 0.0132 637.44 7/19/2012 EB1 FGRD I 41 0.9176 6 0.0057 636.57 7/19/2012 EB1 FGRD M 55 2.3980 1 0.0174 725.60 7/19/2012 EB1 PLAT F 40 0.9072 1 0.0069 1046.43 7/19/2012 EB2 FGRD F 73 6.6604 4 0.0690 795.62 7/19/2012 EB2 FGRD I 44 0.9551 2 0.0020 200.13 7/19/2012 EB2 FGRD M 77 6.3803 5 0.0374 500.39 7/19/2012 EB2 PLAT M 38 SL 1.3838 1 0.0037 267.38 7/19/2012 EB3 FGRD F 83 9.7088 5 0.0795 753.54 7/19/2012 EB3 FGRD I 47 1.2054 1 0.0048 398.21 7/19/2012 EB3 FGRD M 86 9.4541 4 0.0864 823.09 7/19/2012 SQB1 FGRD F 82 8.6686 4 0.0956 981.15 7/19/2012 SQB1 FGRD I 52 1.6726 1 0.0110 657.66 7/19/2012 SQB1 FGRD M 80 8.5604 4 0.0766 971.72 7/19/2012 SQB1 PLAT F 45 1.6044 4 0.0086 614.22 7/19/2012 SQB2 FGRD F 85 9.4067 4 0.1321 1359.58 7/19/2012 SQB2 FGRD I 47 1.1825 1 0.0026 219.87 7/19/2012 SQB2 FGRD M 83 9.3282 5 0.0925 885.67 7/19/2012 SQB3 FGRD F 86 10.9933 4 0.1374 1188.94 7/19/2012 SQB3 FGRD I 48 1.3232 2 0.0061 574.07 7/19/2012 SQB3 FGRD M 82 8.8776 4 0.0859 757.28 7/19/2012 SQB3 PLAT F 34 0.6998 1 0.0032 259.15 7/19/2012 SQB4 FGRD F 83 9.3099 4 0.0697 737.04 7/19/2012 SQB4 FGRD I 45 1.1740 2 0.0064 534.00 7/19/2012 SQB4 FGRD M 71 5.4081 4 0.0469 861.77 7/29/2012 GC2 FGRD F 67 4.7616 5 0.0531 951.59 7/29/2012 GC2 FGRD M 98 4.4341 3 0.0335 735.10 7/29/2012 GC2 PLAT M 44 1.2480 1 0.0031 1508.57 7/29/2012 GC3 FGRD F 80 7.1631 3 0.0715 871.88 120 ? 7/29/2012 GC3 FGRD M 71 5.9994 7 0.0393 573.07 7/29/2012 GC3 PLAT F 40 1.0659 3 0.0128 1428.99 7/29/2012 GC4 FGRD F 82 8.6849 4 0.0955 972.93 7/29/2012 GC4 FGRD I 57 2.3471 1 0.0251 1069.40 7/29/2012 GC4 FGRD M 76 6.8573 5 0.0451 651.07 9/7/2012 GC3 PLAT F 30 SL 0.6990 1 0.0089 1732.05 9/7/2012 GC3 PLAT M 46 1.3968 1 0.0054 457.27 9/7/2012 GC4 FGRD F 82 8.3033 8 0.0873 1046.03 9/7/2012 GC4 FGRD M 78 7.3112 2 0.0747 1023.91 9/7/2012 GC4 PLAT F 40 1.1832 6 0.0095 1723.25 9/7/2012 GC4 PLAT M 51 1.9080 1 0.0134 1554.74 12/15/2011 GC4 FGRD F 65 3.6972 1 0.0213 576.11 12/15/2011 GC4 FGRD M 64 3.0305 1 0.0262 864.54 9/7/2012 LB1 FGRD F 84 10.0361 4 0.1394 1197.35 9/7/2012 LB1 FGRD M 84 10.2000 5 0.1532 1383.01 9/7/2012 LB1 PLAT F 42 1.2695 6 0.0104 1019.31 9/7/2012 LB1 PLAT M 49 1.8409 3 0.0167 1559.44 9/7/2012 LB2 FGRD F 79 7.6817 5 0.0865 1168.50 9/7/2012 LB2 FGRD M 81 9.1561 5 0.1038 1073.29 9/7/2012 LB2 PLAT F 54 2.8835 2 0.0184 1148.15 9/7/2012 LB2 PLAT M 57 3.1781 2 0.0258 1255.29 9/7/2012 LB3 FGRD F 83 9.2957 4 0.1234 1137.07 9/7/2012 LB3 FGRD I 41 0.8985 1 0.0032 356.15 9/7/2012 LB3 FGRD M 80 8.9894 5 0.1226 1389.00 9/7/2012 LB3 PLAT F 50 2.4700 3 0.0278 1819.21 9/7/2012 LB4 FGRD F 82 9.6566 4 0.1296 1258.79 9/7/2012 LB4 FGRD I 42 0.8233 1 0.0057 692.34 9/7/2012 LB4 FGRD M 76 7.2609 5 0.0974 1208.64 9/7/2012 LB4 PLAT F 44 1.2812 4 0.0137 1024.24 9/7/2012 LB4 PLAT M 51 2.2871 3 0.0300 865.82 121 ? 9/8/2012 EB1 FGRD F 57 2.3566 4 0.0104 430.67 9/8/2012 EB1 FGRD I 46 1.1428 2 0.0045 389.84 9/8/2012 EB1 FGRD M 65 3.9609 4 0.0197 478.41 9/8/2012 EB1 PLAT F 34 SL 1.0234 1 0.0062 579.17 9/8/2012 EB1 PLAT M 39 0.9523 3 0.0079 949.84 9/8/2012 EB2 FGRD F 56 2.4287 2 0.0159 653.66 9/8/2012 EB2 FGRD I 44 1.0753 3 0.0123 1227.76 9/8/2012 EB2 PLAT F 34 0.6678 3 0.0068 1142.93 9/8/2012 EB2 PLAT M 45 1.4870 1 0.0170 969.57 9/8/2012 EB3 FGRD F 81 9.3666 4 0.1231 956.64 9/8/2012 EB3 FGRD I 45 0.9789 1 0.0054 551.64 9/8/2012 EB3 FGRD M 83 9.7503 4 0.0889 848.97 9/8/2012 EB3 PLAT F 54 2.7962 2 0.0265 878.29 9/8/2012 SQB1 FGRD F 80 8.0409 4 0.0965 1121.20 9/8/2012 SQB1 FGRD I 47 1.2042 1 0.0134 1112.77 9/8/2012 SQB1 FGRD M 78 7.9018 5 0.0603 825.47 9/8/2012 SQB1 PLAT F 46 1.9143 5 0.0224 1067.79 9/8/2012 SQB1 PLAT M 48 1.7909 5 0.0221 1216.26 9/8/2012 SQB2 FGRD F 83 9.3884 4 0.1113 1055.39 9/8/2012 SQB2 FGRD I 48 1.3226 1 0.0098 740.96 9/8/2012 SQB2 FGRD M 73 6.5208 5 0.0557 743.95 9/8/2012 SQB2 PLAT F 45 1.5487 5 0.0155 936.39 9/8/2012 SQB2 PLAT M 50 2.1875 5 0.0338 601.01 9/8/2012 SQB3 FGRD F 79 8.0346 4 0.0651 721.88 9/8/2012 SQB3 FGRD I 48 1.2427 1 0.0026 209.22 9/8/2012 SQB3 FGRD M 73 6.5207 5 0.0406 568.85 9/8/2012 SQB3 PLAT F 49 1.8371 8 0.0212 849.33 9/8/2012 SQB3 PLAT M 50 1.7317 2 0.0188 442.99 9/8/2012 SQB4 FGRD F 78 7.8176 5 0.0986 941.01 9/8/2012 SQB4 FGRD M 76 7.3749 5 0.0459 594.43 122 ? 9/8/2012 SQB4 PLAT F 47 1.8510 5 0.0451 803.26 9/8/2012 SQB4 PLAT M 54 2.5768 4 0.0395 658.25 9/9/2012 GB1 FGRD F 101 15.8983 4 0.1663 966.76 9/9/2012 GB1 FGRD M 91 11.7630 3 0.1209 991.42 9/9/2012 GB2 FGRD F 76 6.6403 4 0.0509 742.52 9/9/2012 GB2 FGRD M 73 5.5972 1 0.0402 718.22 9/9/2012 GB4 FGRD F 100 13.6345 3 0.1356 953.48 9/9/2012 GB4 FGRD M 98 14.6309 5 0.1029 687.80 9/9/2012 WB1 FGRD F 71 5.5568 5 0.0391 597.12 9/9/2012 WB1 FGRD M 64 3.6886 5 0.0164 441.67 9/9/2012 WB1 PLAT F 45 1.7171 5 0.0154 1038.19 9/9/2012 WB1 PLAT M 43 1.3794 4 0.0112 1227.27 9/9/2012 WB2 FGRD F 70 6.2416 5 0.0312 447.51 9/9/2012 WB2 FGRD M 70 6.0775 5 0.0432 574.30 9/9/2012 WB2 PLAT F 47 1.7494 2 0.0109 1338.17 9/9/2012 WB2 PLAT M 48 1.8499 6 0.0084 1395.11 9/9/2012 WB3 FGRD F 80 7.9254 5 0.0968 1101.72 9/9/2012 WB3 FGRD I 44 0.9939 1 0.0066 664.05 9/9/2012 WB3 FGRD M 76 7.4782 4 0.0698 834.42 9/9/2012 WB3 PLAT F 40 1.0889 4 0.0122 511.16 9/9/2012 WB3 PLAT M 39 0.9023 2 0.0094 574.51 9/9/2012 WB4 FGRD F 84 9.3966 4 0.1080 883.24 9/9/2012 WB4 FGRD M 74 8.0308 6 0.0936 921.64 123 ? Table 8. Caloric density and associated fish measures averaged for each sampling event at each marsh. All lengths are total length unless indicated with an SL for standard length. See Fig. 2.13 for species abbreviations. Date Site Species Sex Length (mm) Wet weight (g) N Dry weight (g) Calories dry wt. -1 (cal g -1 ) Calories wet wt. -1 (cal g -1 ) 15-Dec-11 GC3 FGRD NA 71 5.1468 8 1.2288 4119.73 977.51 15-Dec-11 GC3 PLAT NA 43 1.6061 9 0.4258 4628.34 1183.40 12-Dec-11 GB1 FGRD F 78 6.6123 4 1.6081 4274.98 1036.83 12-Dec-11 GB1 FGRD M 77 6.7425 6 1.6733 4353.92 1074.62 12-Dec-11 GB2 FGRD F 82 7.6685 5 1.8481 4393.94 1056.51 12-Dec-11 GB2 FGRD I 45 1.0081 1 0.2457 4210.28 1026.15 12-Dec-11 GB2 FGRD M 77 6.6673 4 1.6457 4328.53 1057.00 12-Dec-11 GB2 PLAT M 58 3.0024 1 0.8586 4472.11 1278.89 12-Dec-11 GB4 FGRD F 61 2.8438 1 0.6634 4037.70 941.91 12-Dec-11 GB4 FGRD M 55 1.9377 1 0.4463 3940.49 907.59 12-Dec-11 GB4 PLAT F 39 0.8691 7 0.2266 4755.65 1238.19 12-Dec-11 GB4 PLAT M 37 0.8840 2 0.2218 4784.11 1139.67 12-Dec-11 WB1 PLAT F 34 0.5063 1 0.1842 4837.53 1759.97 12-Dec-11 WB2 FGRD F 55 2.4289 5 0.5396 4037.53 884.35 12-Dec-11 WB2 FGRD I 44 1.1974 2 0.2517 4077.87 857.22 12-Dec-11 WB2 FGRD M 56 2.4510 3 0.5463 4009.04 893.19 12-Dec-11 WB2 PLAT F 39 1.0635 6 0.2590 4404.94 1056.53 12-Dec-11 WB2 PLAT M 44 1.1684 4 0.2909 4409.64 1032.05 12-Dec-11 WB3 FGRD NA 50 1.6935 9 0.4088 4292.03 4292.03 12-Dec-11 WB3 PLAT NA 42 1.3097 10 0.3341 4328.58 1084.06 12-Dec-11 WB4 FGRD F 57 2.3690 1 0.5310 4083.63 915.33 14-Dec-11 EB1 PLAT F 36 0.8013 7 0.2056 4597.52 1158.02 14-Dec-11 EB1 PLAT M 45 1.5388 3 0.4153 4621.36 1211.89 14-Dec-11 EB2 FGRD I 40 0.6370 1 0.1382 4243.27 920.60 14-Dec-11 EB2 PLAT F 37 0.8080 7 0.1931 4431.78 1052.47 14-Dec-11 EB2 PLAT M 35 0.7386 3 0.1733 4441.81 1007.48 124 ? 14-Dec-11 EB3 FGRD F 61 3.0501 3 0.7103 4566.40 1069.24 14-Dec-11 EB3 FGRD I 45 1.1120 3 0.2456 4306.60 953.58 14-Dec-11 EB3 FGRD M 72 5.5652 4 1.2790 4230.30 975.27 14-Dec-11 EB3 PLAT F 44 1.3164 3 0.3221 4497.55 1103.39 14-Dec-11 SQB1 FGRD F 78 7.0163 3 1.6898 4131.61 968.64 14-Dec-11 SQB1 FGRD I 49 1.3886 3 0.3339 4190.80 10009.44 14-Dec-11 SQB1 FGRD M 66 3.7509 4 0.8803 4169.18 978.46 14-Dec-11 SQB1 PLAT F 44 1.2672 6 0.3269 4677.99 1204.55 14-Dec-11 SQB1 PLAT M 50 1.9802 4 0.5357 4500.58 1211.17 14-Dec-11 SQB2 FGRD F 76 7.4400 4 1.7983 4210.03 1003.43 14-Dec-11 SQB2 FGRD I 52 1.6609 2 0.3921 4246.85 1000.64 14-Dec-11 SQB2 FGRD M 81 8.4974 4 2.1317 4089.14 1006.40 14-Dec-11 SQB2 PLAT F 56 2.8049 5 0.7183 4376.14 1147.48 14-Dec-11 SQB2 PLAT M 57 3.1226 5 0.8101 4394.39 1138.09 14-Dec-11 SQB3 FGRD F 71 6.9547 4 1.6619 4322.75 1013.99 14-Dec-11 SQB3 FGRD I 42 0.8025 2 0.1833 4419.89 1009.22 14-Dec-11 SQB3 FGRD M 65 3.9910 4 0.9426 4242.17 1002.98 14-Dec-11 SQB4 FGRD F 77 7.5159 3 1.8790 4113.05 989.73 14-Dec-11 SQB4 FGRD I 44 1.0588 4 0.2527 4214.85 996.79 14-Dec-11 SQB4 FGRD M 76 6.0536 3 1.4895 4199.01 1031.32 14-Dec-11 SQB4 PLAT F 45 1.3986 6 0.3754 4486.70 1207.74 14-Dec-11 SQB4 PLAT M 39 0.8482 4 0.2216 4457.21 1157.48 15-Dec-11 GC2 FGRD I 35 SL 0.7978 1 0.1884 4193.08 990.19 15-Dec-11 GC2 FGRD M 55 2.1030 1 0.4763 3952.68 895.23 15-Dec-11 GC2 PLAT F 34 0.6018 3 0.1539 4727.26 1211.32 15-Dec-11 GC4 FGRD F 65 3.6972 1 0.9113 4428.70 1091.60 15-Dec-11 GC4 FGRD M 64 3.0305 1 0.7462 4197.37 1033.52 15-Dec-11 GC4 PLAT F 36 0.7474 5 0.1993 4915.06 1301.70 15-Dec-11 GC4 PLAT M 32 0.5348 3 0.1417 5037.76 1334.72 15-Dec-11 LB1 FGRD F 77 6.0428 1 1.5089 4531.40 1131.50 15-Dec-11 LB1 FGRD I 40 0.7768 1 0.1929 4729.75 1174.52 125 ? 15-Dec-11 LB1 FGRD M 110 18.7886 1 4.9568 4331.54 1142.74 15-Dec-11 LB1 PLAT F 42 1.3238 6 0.3888 4930.58 1413.94 15-Dec-11 LB1 PLAT M 41 1.1371 4 0.3214 4988.48 1393.42 15-Dec-11 LB2 FGRD F 63 3.0043 3 0.7619 4362.51 1106.82 15-Dec-11 LB2 FGRD I 57 1.9902 1 0.5207 4362.76 1141.44 15-Dec-11 LB3 FGRD F 86 10.1200 4 2.5454 4431.03 1114.20 15-Dec-11 LB3 FGRD I 50 1.6473 2 0.3854 4574.40 1075.23 15-Dec-11 LB3 FGRD M 84 10.0073 4 2.5303 4273.36 1073.17 15-Dec-11 LB4 FGRD F 74 6.6626 5 1.7030 4259.93 1055.49 15-Dec-11 LB4 FGRD M 77 7.8086 5 1.9768 4149.97 1034.39 9-Mar-12 GB1 FGRD F 72 6.1951 5 1.3593 4373.45 963.45 9-Mar-12 GB1 FGRD M 75 6.9791 5 1.5440 4383.08 971.15 9-Mar-12 GB1 PLAT F 42 1.2076 7 0.2554 4573.25 961.27 9-Mar-12 GB1 PLAT M 34 0.6167 2 0.1129 4616.75 839.51 9-Mar-12 GB2 FGRD F 75 6.2645 5 1.3545 4325.23 931.98 9-Mar-12 GB2 FGRD I 50 1.3473 1 0.2944 4378.19 956.68 9-Mar-12 GB2 FGRD M 83 8.5734 4 1.8257 4184.95 896.71 9-Mar-12 GB2 PLAT F 37 0.9022 1 0.1981 5250.79 1152.94 9-Mar-12 GB3 FGRD F 85 9.9276 5 2.2085 4435.08 992.84 9-Mar-12 GB3 FGRD M 79 7.3909 5 1.6148 4366.24 957.87 9-Mar-12 GB3 PLAT F 36 0.7149 1 0.1343 4395.72 825.77 9-Mar-12 GB4 FGRD F 78 8.3075 5 1.6858 4249.40 918.26 9-Mar-12 GB4 FGRD M 86 9.7472 5 2.1183 4024.48 877.45 9-Mar-12 WB1 FGRD F 103 14.6506 4 3.2556 4354.69 976.33 9-Mar-12 WB1 FGRD M 93 14.2022 4 3.2034 4347.11 980.52 9-Mar-12 WB2 FGRD F 67 8.0626 5 1.8151 4302.88 943.79 9-Mar-12 WB2 FGRD I 45 1.2577 1 0.2473 4376.01 860.45 9-Mar-12 WB2 FGRD M 77 7.7601 4 1.7180 4163.30 931.80 9-Mar-12 WB2 PLAT F 47 1.6772 1 0.3550 3933.38 832.55 9-Mar-12 WB2 PLAT M 43 1.4653 5 0.3189 4532.23 968.98 9-Mar-12 WB3 FGRD F 76 7.3758 4 1.6969 4270.42 989.33 126 ? 9-Mar-12 WB3 FGRD I 44 0.9807 1 0.2117 4149.14 895.66 9-Mar-12 WB3 FGRD M 70 5.5044 5 1.2562 4143.19 955.33 9-Mar-12 WB3 PLAT F 43 1.3458 6 0.3165 4449.56 1018.29 9-Mar-12 WB3 PLAT M 52 2.1226 4 0.4956 4196.77 988.07 9-Mar-12 WB4 FGRD F 80 9.6172 4 2.2204 4198.13 975.18 9-Mar-12 WB4 FGRD M 71 6.6756 6 1.5353 4222.16 965.26 9-Mar-12 WB4 PLAT F 39 1.0012 6 0.2307 4758.89 1077.91 9-Mar-12 WB4 PLAT M 53 2.5796 4 0.6155 4225.85 1009.30 10-Mar-12 GC1 FGRD F 84 10.0636 5 2.2761 4258.55 954.33 10-Mar-12 GC1 FGRD M 77 7.9297 5 1.7941 4285.30 961.62 10-Mar-12 GC1 PLAT M 40 1.0025 1 0.2123 4255.59 901.21 10-Mar-12 GC2 FGRD F 82 9.0396 5 2.0728 4342.64 992.58 10-Mar-12 GC2 FGRD M 85 9.0495 5 2.0502 4191.08 951.71 10-Mar-12 GC2 PLAT F 51 2.1072 1 0.5041 4659.64 1114.71 10-Mar-12 GC3 FGRD F 81 8.8258 6 2.0638 4390.99 1021.42 10-Mar-12 GC3 FGRD M 90 11.4100 4 2.6190 4102.50 940.57 10-Mar-12 GC3 PLAT F 35 0.6623 1 0.1495 4955.52 1118.60 10-Mar-12 GC3 PLAT M 39 0.9316 3 0.2078 4393.53 1006.95 10-Mar-12 GC4 FGRD F 75 6.8626 6 1.5434 4290.20 958.44 10-Mar-12 GC4 FGRD M 74 6.0327 4 1.3274 4127.02 906.67 10-Mar-12 GC4 PLAT F 46 1.6932 5 0.3986 4747.52 1120.97 10-Mar-12 GC4 PLAT M 49 1.7364 2 0.3920 4757.72 1073.12 10-Mar-12 LB1 FGRD F 83 9.6422 5 2.2464 4256.35 984.73 10-Mar-12 LB1 FGRD M 80 8.6768 5 1.8221 4100.44 865.61 10-Mar-12 LB2 FGRD F 90 11.6466 4 2.6809 4151.18 955.96 10-Mar-12 LB2 FGRD I 45 1.1415 1 0.2168 4511.05 856.76 10-Mar-12 LB2 FGRD M 82 8.6066 5 1.9546 4026.21 898.94 10-Mar-12 LB3 FGRD F 79 8.5243 5 1.9741 4270.47 994.12 10-Mar-12 LB3 FGRD M 79 8.4794 5 2.0089 4169.18 983.55 10-Mar-12 LB4 FGRD F 91 11.8238 4 2.7395 4076.83 941.70 10-Mar-12 LB4 FGRD I 44 0.9762 1 0.1963 4429.02 890.61 127 ? 10-Mar-12 LB4 FGRD M 87 10.5844 5 2.4407 4009.46 944.48 11-Mar-12 EB1 FGRD F 73 7.2304 4 1.6356 4414.20 997.06 11-Mar-12 EB1 FGRD I 38 0.7173 1 0.1459 4456.30 906.42 11-Mar-12 EB1 FGRD M 69 6.2899 5 1.4523 4256.67 959.42 11-Mar-12 EB1 PLAT F 42 1.3494 6 0.2921 4556.17 943.96 11-Mar-12 EB1 PLAT M 45 1.5936 4 0.3388 4065.85 855.40 11-Mar-12 EB2 FGRD F 84 11.2070 4 2.5469 4283.92 956.90 11-Mar-12 EB2 FGRD I 47 1.3747 1 0.3049 4325.33 959.33 11-Mar-12 EB2 FGRD M 77 7.9352 5 1.8006 4131.50 908.59 11-Mar-12 EB3 FGRD F 86 11.7406 5 2.8341 4461.92 1043.48 11-Mar-12 EB3 FGRD I 41 0.7935 1 0.1584 4467.97 891.90 11-Mar-12 EB3 FGRD M 81 9.7399 4 2.2565 4294.90 986.10 11-Mar-12 EB3 PLAT F 42 1.2013 1 0.2738 4682.16 1067.16 11-Mar-12 EB3 PLAT M 43 1.3388 1 0.2930 4349.58 951.92 11-Mar-12 SQB1 FGRD F 84 11.3037 4 2.6437 4347.22 1019.03 11-Mar-12 SQB1 FGRD I 42 0.8592 1 0.1891 4883.65 1074.83 11-Mar-12 SQB1 FGRD M 78 8.0589 5 1.9131 4211.66 988.16 11-Mar-12 SQB1 PLAT F 38 0.8533 1 0.2066 4541.32 1099.54 11-Mar-12 SQB2 FGRD F 77 8.3252 5 1.9867 4370.04 1026.59 11-Mar-12 SQB2 FGRD M 78 8.6268 5 2.0793 4243.07 1007.25 11-Mar-12 SQB2 PLAT M 64 4.0046 2 0.9038 4164.34 943.82 11-Mar-12 SQB3 FGRD F 76 7.9631 5 1.8673 4388.35 1010.49 11-Mar-12 SQB3 FGRD M 80 8.3231 5 1.9391 4154.24 966.35 11-Mar-12 SQB4 FGRD F 81 9.2719 5 2.1113 4310.08 987.80 11-Mar-12 SQB4 FGRD M 83 9.4132 5 2.1732 4190.89 965.97 17-Jul-12 GB1 FGRD F 70 5.4034 4 1.3412 4264.74 1028.38 17-Jul-12 GB1 FGRD M 63 3.5393 3 0.8375 4456.92 1053.79 17-Jul-12 GB2 FGRD F 76 7.1843 6 1.6454 4283.99 966.18 17-Jul-12 GB2 FGRD M 65 3.8477 4 0.9092 4311.26 1004.36 17-Jul-12 GB3 FGRD F 63 3.2558 1 0.8000 4646.75 1141.78 17-Jul-12 GB4 FGRD F 87 10.0643 4 2.3809 4292.47 1018.16 128 ? 17-Jul-12 GB4 FGRD I 48 1.2932 1 0.2844 4224.93 929.14 17-Jul-12 GB4 FGRD M 84 9.8540 5 2.7440 4261.11 1165.45 17-Jul-12 WB1 FGRD F 67 4.4509 6 1.0051 6587.13 1470.46 17-Jul-12 WB1 FGRD I 43 1.0045 2 0.1869 4683.75 868.15 17-Jul-12 WB1 FGRD M 56 2.4962 2 0.5163 4657.98 965.36 17-Jul-12 WB1 PLAT F 39 1.0450 7 0.2129 5150.22 1033.92 17-Jul-12 WB1 PLAT M 41 1.0099 3 0.2194 4765.92 1036.53 17-Jul-12 WB2 FGRD F 68 5.1357 4 1.1901 4648.45 1056.77 17-Jul-12 WB2 FGRD I 43 0.8821 2 0.1835 4797.03 978.29 17-Jul-12 WB2 FGRD M 65 4.3829 4 1.0049 4688.75 1055.43 17-Jul-12 WB3 FGRD F 69 5.9640 4 1.4165 4739.54 1071.02 17-Jul-12 WB3 FGRD I 41 0.9080 2 0.1774 4531.15 884.74 17-Jul-12 WB3 FGRD M 78 9.0262 4 2.0841 4503.09 1026.70 17-Jul-12 WB3 PLAT F 44 1.6167 5 0.3496 4549.44 943.58 17-Jul-12 WB3 PLAT M 40 0.9122 5 0.1996 4382.07 952.61 17-Jul-12 WB4 FGRD F 77 8.0900 4 2.0061 4662.19 1102.83 17-Jul-12 WB4 FGRD I 45 1.3023 2 0.2721 4486.46 929.37 17-Jul-12 WB4 FGRD M 81 8.2518 4 1.9407 4451.75 1026.57 17-Jul-12 WB4 PLAT M 45 1.2769 3 0.2789 4046.03 883.91 18-Jul-12 LB1 FGRD F 80 8.9419 4 2.1482 4412.52 1037.87 18-Jul-12 LB1 FGRD I 45 1.0627 1 0.2399 4388.80 990.75 18-Jul-12 LB1 FGRD M 75 7.6385 5 1.8360 4340.47 1023.77 18-Jul-12 LB1 PLAT F 41 1.2491 2 0.2676 4964.95 1065.46 18-Jul-12 LB2 FGRD F 84 9.3239 4 2.2024 4256.82 979.89 18-Jul-12 LB2 FGRD I 44 1.0388 1 0.2296 4140.02 915.04 18-Jul-12 LB2 FGRD M 82 8.6822 5 2.1271 4263.84 1024.76 18-Jul-12 LB3 FGRD F 86 11.1213 4 2.6515 4484.47 1082.66 18-Jul-12 LB3 FGRD I 45 1.1852 2 0.2603 4267.16 938.40 18-Jul-12 LB3 FGRD M 81 9.2017 4 2.1589 4467.37 1049.58 18-Jul-12 LB4 FGRD F 86 10.0875 4 2.4239 4013.31 946.52 18-Jul-12 LB4 FGRD I 43 1.0214 1 0.2094 4403.71 902.82 129 ? 18-Jul-12 LB4 FGRD M 78 7.8158 5 1.8796 4229.63 980.01 18-Jul-12 LB4 PLAT F 44 1.4043 3 0.3022 4366.13 918.69 18-Jul-12 LB4 PLAT M 52 1.8705 2 0.4228 4117.26 926.71 19-Jul-12 EB1 FGRD F 55 2.1361 3 0.4775 4460.19 998.22 19-Jul-12 EB1 FGRD I 41 0.9176 6 0.1965 4489.40 960.11 19-Jul-12 EB1 FGRD M 55 2.3980 1 0.5441 4626.08 1049.64 19-Jul-12 EB1 PLAT F 40 0.9072 1 0.2002 4632.60 1022.32 19-Jul-12 EB2 FGRD F 73 6.6604 4 1.5072 4080.11 900.95 19-Jul-12 EB2 FGRD I 44 0.9551 2 0.2070 4262.63 923.98 19-Jul-12 EB2 FGRD M 77 7.6294 4 1.7791 4203.58 970.46 19-Jul-12 EB2 PLAT M 38 SL 1.3838 1 0.3220 4147.39 965.07 19-Jul-12 EB3 FGRD F 83 9.7088 5 2.3522 4354.88 1031.88 19-Jul-12 EB3 FGRD I 47 1.2054 1 0.2685 4066.88 905.89 19-Jul-12 EB3 FGRD M 86 9.4541 4 2.1742 4234.42 970.40 19-Jul-12 SQB1 FGRD F 82 8.6686 4 1.9913 4292.78 960.56 19-Jul-12 SQB1 FGRD I 48 1.3090 2 0.2777 4421.42 942.56 19-Jul-12 SQB1 FGRD M 80 8.5604 4 2.0480 4590.13 1083.64 19-Jul-12 SQB1 PLAT F 45 1.5761 8 0.3432 4569.72 961.95 19-Jul-12 SQB1 PLAT M 46 1.2954 2 0.2847 4067.63 891.25 19-Jul-12 SQB2 FGRD F 85 9.4067 4 2.2474 4431.70 1054.33 19-Jul-12 SQB2 FGRD I 47 1.1825 1 0.2609 4342.28 958.06 19-Jul-12 SQB2 FGRD M 83 9.3282 5 2.2659 4307.63 1009.40 19-Jul-12 SQB3 FGRD F 86 10.9933 4 2.5906 4249.27 992.20 19-Jul-12 SQB3 FGRD I 48 1.3232 2 0.2833 4321.43 928.71 19-Jul-12 SQB3 FGRD M 82 8.8776 4 2.1033 4298.54 999.85 19-Jul-12 SQB3 PLAT F 40 1.1111 4 0.2359 4681.20 965.90 19-Jul-12 SQB3 PLAT M 48 1.6456 2 0.3539 4431.96 943.45 19-Jul-12 SQB4 FGRD F 83 9.3099 4 2.1624 4145.78 951.31 19-Jul-12 SQB4 FGRD I 45 1.1740 2 0.2434 4513.72 930.67 19-Jul-12 SQB4 FGRD M 71 5.4081 4 1.2282 4184.34 921.30 29-Jul-12 GC2 FGRD F 67 4.7616 5 1.1836 4443.90 1082.95 130 ? 29-Jul-12 GC2 FGRD M 68 4.4341 3 1.1041 4547.65 1132.45 29-Jul-12 GC2 PLAT M 38 0.8485 3 0.2180 4565.97 1173.84 29-Jul-12 GC3 FGRD F 80 7.1631 3 1.8244 4330.49 1101.09 29-Jul-12 GC3 FGRD M 71 5.9994 7 1.5183 4571.52 1159.25 29-Jul-12 GC3 PLAT F 40 1.0659 3 0.2662 5117.67 1206.53 29-Jul-12 GC3 PLAT M 36 0.6107 5 0.1479 4430.04 1069.47 29-Jul-12 GC4 FGRD F 82 8.6849 4 2.1834 4496.04 1115.85 29-Jul-12 GC4 FGRD I 57 2.3471 1 0.5695 4774.19 1158.41 29-Jul-12 GC4 FGRD M 76 6.8573 5 1.6677 4373.65 1065.16 29-Jul-12 GC4 PLAT M 40 0.7033 2 0.1717 4292.02 1040.62 7-Sep-12 GC3 PLAT F 30 SL 0.6990 1 0.1374 4870.92 957.46 7-Sep-12 GC3 PLAT M 46 1.3968 1 0.3143 4390.77 987.99 7-Sep-12 GC4 FGRD F 82 8.3033 8 1.9491 4399.88 1039.05 7-Sep-12 GC4 FGRD M 78 7.3112 2 1.7794 4641.11 1130.28 7-Sep-12 GC4 PLAT F 40 1.1832 6 0.2565 4742.27 1015.19 7-Sep-12 GC4 PLAT M 39 1.1040 2 0.2528 4433.02 951.24 7-Sep-12 LB1 FGRD F 77 6.5781 5 2.0611 4525.38 1242.78 7-Sep-12 LB1 FGRD M 84 10.2000 5 2.4739 4466.65 1053.80 7-Sep-12 LB1 PLAT F 42 1.2695 6 0.3127 4920.22 1274.38 7-Sep-12 LB1 PLAT M 48 1.7785 4 0.4471 4797.73 1156.81 7-Sep-12 LB2 FGRD F 79 7.6817 5 1.8325 4269.99 990.78 7-Sep-12 LB2 FGRD M 81 9.1561 5 2.2167 4161.12 1004.10 7-Sep-12 LB2 PLAT F 54 2.8835 2 0.6769 4826.61 1119.65 7-Sep-12 LB2 PLAT M 57 3.1791 2 0.8389 5094.71 1318.42 7-Sep-12 LB3 FGRD F 83 9.2457 4 2.2871 4338.92 1014.27 7-Sep-12 LB3 FGRD I 41 0.8985 1 0.1825 4595.16 933.35 7-Sep-12 LB3 FGRD M 80 8.9894 5 2.1846 4304.23 1012.31 7-Sep-12 LB3 PLAT F 50 2.4700 3 0.5466 4419.60 991.49 7-Sep-12 LB3 PLAT I 22 SL 0.2748 1 0.0489 4370.87 777.79 7-Sep-12 LB4 FGRD F 82 9.6566 4 2.3761 4216.43 1017.71 7-Sep-12 LB4 FGRD I 42 0.8233 1 0.1810 4430.83 974.10 131 ? 7-Sep-12 LB4 FGRD M 76 7.2609 5 1.7868 4192.22 1002.02 7-Sep-12 LB4 PLAT F 44 1.2812 4 0.2898 4688.47 1062.48 7-Sep-12 LB4 PLAT M 51 2.2871 3 0.6008 4664.59 1204.47 8-Sep-12 EB1 FGRD F 57 2.3566 4 0.4915 4235.59 884.69 8-Sep-12 EB1 FGRD I 46 1.1428 2 0.2347 4073.25 836.99 8-Sep-12 EB1 FGRD M 65 3.9316 4 0.8458 4265.13 917.36 8-Sep-12 EB1 PLAT F 44 1.1462 2 0.2278 4400.79 878.58 8-Sep-12 EB1 PLAT M 39 0.9523 3 0.2011 4631.50 969.25 8-Sep-12 EB2 FGRD F 56 2.4287 2 0.5217 4209.26 904.28 8-Sep-12 EB2 FGRD I 44 1.0753 3 0.2233 4255.03 877.67 8-Sep-12 EB2 PLAT F 33 0.5730 5 0.1047 4198.46 729.34 8-Sep-12 EB2 PLAT I 20 0.1077 1 0.0164 4431.53 674.81 8-Sep-12 EB2 PLAT M 45 1.4870 1 0.3329 4454.72 997.29 8-Sep-12 EB3 FGRD F 81 9.3666 4 2.1396 4207.37 938.37 8-Sep-12 EB3 FGRD I 45 0.9789 1 0.1945 4221.09 838.70 8-Sep-12 EB3 FGRD M 77 8.1446 5 1.9410 4169.87 961.88 8-Sep-12 EB3 PLAT F 54 2.7962 2 0.5997 4184.38 920.57 8-Sep-12 SQB1 FGRD F 80 8.0409 4 1.8943 4172.82 964.41 8-Sep-12 SQB1 FGRD I 47 1.2042 1 0.2704 4440.95 997.20 8-Sep-12 SQB1 FGRD M 78 7.9018 5 1.9091 4133.89 992.49 8-Sep-12 SQB1 PLAT F 46 1.9143 5 0.4387 4298.19 984.32 8-Sep-12 SQB1 PLAT M 48 1.7909 5 0.4375 4408.13 1064.49 8-Sep-12 SQB2 FGRD F 83 9.3884 4 2.2968 4274.16 1013.73 8-Sep-12 SQB2 FGRD I 48 1.3226 1 0.2988 4288.03 968.75 8-Sep-12 SQB2 FGRD M 73 8.5208 5 1.5338 4083.96 786.43 8-Sep-12 SQB2 PLAT F 45 1.5487 5 0.3621 4358.98 1025.06 8-Sep-12 SQB2 PLAT M 50 2.1875 5 0.5255 4384.24 1022.12 8-Sep-12 SQB3 FGRD F 79 8.0346 4 1.8486 4189.88 940.57 8-Sep-12 SQB3 FGRD I 48 1.2427 1 0.2681 4356.47 939.86 8-Sep-12 SQB3 FGRD M 73 6.5207 5 1.5536 4220.32 967.32 8-Sep-12 SQB3 PLAT F 49 1.8371 8 0.3958 4481.54 1011.03 132 ? 8-Sep-12 SQB3 PLAT M 50 1.7317 2 0.3810 4100.40 904.40 8-Sep-12 SQB4 FGRD F 78 7.8176 5 1.7597 4155.60 933.96 8-Sep-12 SQB4 FGRD M 76 7.3749 5 1.7495 4123.63 935.12 8-Sep-12 SQB4 PLAT F 47 1.8510 5 0.4529 4687.94 1158.52 8-Sep-12 SQB4 PLAT M 51 2.2406 5 0.5376 4407.14 1062.11 9-Sep-12 GB1 FGRD F 101 15.8983 4 4.0515 4466.45 1145.23 9-Sep-12 GB1 FGRD M 91 11.7630 3 2.9142 4376.74 1082.54 9-Sep-12 GB2 FGRD F 76 6.6403 4 1.4425 4328.81 947.33 9-Sep-12 GB2 FGRD M 73 5.5972 1 1.1931 4310.06 918.73 9-Sep-12 GB4 FGRD F 100 13.6345 3 3.2866 4188.70 1006.03 9-Sep-12 GB4 FGRD M 98 14.6309 5 3.4712 4208.20 996.65 10-Sep-12 WB1 FGRD F 71 5.5568 5 1.3495 4578.41 1101.41 10-Sep-12 WB1 FGRD M 64 3.6679 5 0.8850 4528.63 1090.39 10-Sep-12 WB1 PLAT F 45 1.7171 5 0.4061 5143.76 1200.09 10-Sep-12 WB1 PLAT I 22 0.1699 1 0.0289 5057.95 860.36 10-Sep-12 WB1 PLAT M 43 1.3794 4 0.3339 5003.07 1158.84 10-Sep-12 WB2 FGRD F 70 6.2416 5 1.4268 4315.25 962.03 10-Sep-12 WB2 FGRD M 70 6.0775 5 1.3662 4451.58 981.40 10-Sep-12 WB2 PLAT F 43 1.4025 4 0.2989 4847.22 1034.50 10-Sep-12 WB2 PLAT M 48 1.8499 6 0.4257 4832.11 1069.29 10-Sep-12 WB3 FGRD F 80 7.9254 5 1.7903 4308.66 960.09 10-Sep-12 WB3 FGRD I 44 0.9939 1 0.2053 4296.91 887.57 10-Sep-12 WB3 FGRD M 76 7.4782 4 1.6343 4273.62 960.22 10-Sep-12 WB3 PLAT F 40 1.0889 4 0.2324 4767.75 1024.76 10-Sep-12 WB3 PLAT M 39 0.9023 2 0.1913 4657.15 990.35 10-Sep-12 WB4 FGRD F 75 5.9938 4 2.0862 4221.40 1522.64 10-Sep-12 WB4 FGRD I 45 1.0709 1 0.2193 3827.15 783.73 10-Sep-12 WB4 FGRD M 85 11.5098 5 2.0824 4362.89 802.93 10-Sep-12 WB4 PLAT F 49 1.9637 1 0.4028 4327.71 887.71 10-Sep-12 WB4 PLAT M 51 2.0795 1 0.4614 4611.14 1023.12 133 ? Table 9. Species measures averaged for each sampling event at each marsh. All lengths are total length unless indicated with an SL for standard length. See Fig. 2.13 for species abbreviations. Date Site Species Length (mm) Weight (g) Sex N 12/14/2011 EB1 FCON 33 0.3965 F 1 12/14/2011 EB1 PLAT 36 0.7818 F 17 12/14/2011 EB1 PLAT 42 1.1311 M 5 12/14/2011 EB2 FGRD 40 0.6370 I 1 12/14/2011 EB2 PLAT 37 0.7971 F 13 12/14/2011 EB2 PLAT 37 0.8423 M 4 12/14/2011 EB3 AXEN 31 0.4575 I 1 12/14/2011 EB3 FCON 46 1.3868 M 1 12/14/2011 EB3 FGRD 61 2.9167 F 10 12/14/2011 EB3 FGRD 66 4.1612 M 8 12/14/2011 EB3 FGRD 47 1.1890 I 6 12/14/2011 EB3 PLAT 44 1.3164 F 3 12/12/2011 GB1 FGRD 71 5.1968 M 6 12/12/2011 GB1 FGRD 65 4.2385 F 4 12/12/2011 GB1 FCON 44 1.0151 F 1 12/12/2011 GB2 PLAT 58 3.0024 M 1 12/12/2011 GB2 FGRD 36 1.1805 M 10 12/12/2011 GB2 FGRD 45 1.2854 F 13 12/12/2011 GB2 FGRD 45 1.0081 I 1 12/12/2011 GB2 AXEN 38 0.8866 M 1 12/12/2011 GB2 AXEN 33 0.6511 F 1 12/12/2011 GB3 NO FISH 0 12/12/2011 GB4 FGRD 55 1.9377 M 1 12/12/2011 GB4 FGRD 61 2.8438 F 1 12/12/2011 GB4 PLAT 37 1.3499 M 2 12/12/2011 GB4 PLAT 35 1.1615 F 7 134 ? 12/12/2011 GB4 FCON 42 0.9007 F 1 12/12/2011 GB4 AXEN 36 1.1463 M 17 12/12/2011 GB4 AXEN 35 0.9909 F 7 12/12/2011 GB4 AXEN 22 0.1489 I 1 12/15/2011 GC1 NO FISH 0 12/15/2011 GC2 CVAR 35 0.9068 F 28 12/15/2011 GC2 CVAR 45 2.0602 M 3 12/15/2011 GC2 CVAR 39 1.2160 I 13 12/15/2011 GC2 FCON 44 1.1017 F 1 12/15/2011 GC2 FCON 40 0.8398 M 1 12/15/2011 GC2 FGRD 55 2.1030 M 1 12/15/2011 GC2 FGRD 35 0.7978 I 1 12/15/2011 GC2 PLAT 31 0.6018 F 3 12/15/2011 GC3 FGRD 71 5.1468 8 12/15/2011 GC3 PLAT 43 1.3608 28 12/15/2011 GC3 CVAR 37 1.2092 85 12/15/2011 GC3 FCON 41 0.9191 7 12/15/2011 GC4 CVAR 37 1.1449 F 6 12/15/2011 GC4 FGRD 65 3.6972 F 1 12/15/2011 GC4 FGRD 64 3.0305 M 1 12/15/2011 GC4 FPUL 39 0.7446 M 1 12/15/2011 GC4 PLAT 35 0.7114 F 6 12/15/2011 GC4 PLAT 34 0.5996 M 5 12/15/2011 LB1 CVAR 34 0.7338 F 2 12/15/2011 LB1 CVAR 28 0.4215 I 2 12/15/2011 LB1 FCON 36 0.6057 F 1 12/15/2011 LB1 FCON 42 0.9860 M 2 12/15/2011 LB1 FGRD 77 6.0428 F 1 12/15/2011 LB1 FGRD 110 18.7886 M 1 12/15/2011 LB1 FGRD 40 0.7768 I 1 135 ? 12/15/2011 LB1 FPUL 39 0.7951 F 1 12/15/2011 LB1 FPUL 36 0.4809 M 1 12/15/2011 LB1 PLAT 39 1.0365 F 15 12/15/2011 LB1 PLAT 37 0.8763 M 8 12/15/2011 LB2 FGRD 63 3.0043 F 3 12/15/2011 LB2 FGRD 57 1.9902 I 1 12/15/2011 LB3 FGRD 80 8.5213 M 11 12/15/2011 LB3 FGRD 85 10.5555 F 9 12/15/2011 LB3 FGRD 53 2.0008 I 3 12/15/2011 LB3 AXEN 29 0.4291 I 1 12/15/2011 LB3 CVAR 30 0.5282 I 1 12/15/2011 LB4 FGRD 72 5.9331 M 31 12/15/2011 LB4 FGRD 68 4.9330 F 55 12/15/2011 LB4 FGRD 51 1.7364 I 10 12/15/2011 LB4 CVAR 54 3.9204 M 2 12/15/2011 LB4 CVAR 48 2.6448 F 1 12/14/2011 SQB1 AXEN 31 0.4825 I 5 12/14/2011 SQB1 FCON 46 1.1877 F 9 12/14/2011 SQB1 FCON 44 0.9377 M 1 12/14/2011 SQB1 FGRD 63 3.5123 F 13 12/14/2011 SQB1 FGRD 49 1.4274 I 17 12/14/2011 SQB1 FGRD 61 3.0241 M 15 12/14/2011 SQB1 PLAT 45 1.3768 F 11 12/14/2011 SQB1 PLAT 50 1.9803 M 4 12/14/2011 SQB2 FCON 56 2.3820 F 2 12/14/2011 SQB2 FCON 42 0.8587 M 1 12/14/2011 SQB2 FGRD 73 6.5054 F 8 12/14/2011 SQB2 FGRD 52 1.6609 I 2 12/14/2011 SQB2 FGRD 82 9.2868 M 7 12/14/2011 SQB2 PLAT 55 2.7147 F 21 12/14/2011 SQB2 PLAT 55 2.7891 M 11 136 ? 12/14/2011 SQB3 AXEN 30 0.5334 F 5 12/14/2011 SQB3 AXEN 34 0.7767 M 6 12/14/2011 SQB3 CVAR 45 1.9282 F 1 12/14/2011 SQB3 FCON 43 0.9013 F 2 12/14/2011 SQB3 FGRD 60 3.7787 F 28 12/14/2011 SQB3 FGRD 46 1.1899 I 8 12/14/2011 SQB3 FGRD 58 2.6460 M 17 12/14/2011 SQB3 FPUL 46 1.2087 M 2 12/14/2011 SQB4 FGRD 66 3.9083 F 21 12/14/2011 SQB4 FGRD 65 3.6027 M 26 12/14/2011 SQB4 FGRD 50 1.4646 I 21 12/14/2011 SQB4 AXEN 34 0.5961 I 3 12/14/2011 SQB4 CVAR 56 3.9688 M 2 12/14/2011 SQB4 FCON 43 0.9842 F 4 12/14/2011 SQB4 FCON 37 SL 1.0764 M 1 12/14/2011 SQB4 FSIM 48 0.9939 I 3 12/14/2011 SQB4 PLAT 45 1.3721 F 9 12/14/2011 SQB4 PLAT 39 0.8709 M 6 12/12/2011 WB1 PLAT 34 0.5063 F 1 12/12/2011 WB2 FGRD 37 1.1082 M 3 12/12/2011 WB2 FGRD 43 1.8210 F 5 12/12/2011 WB2 FGRD 41 1.5091 I 2 12/12/2011 WB2 PLAT 37 1.1124 M 4 12/12/2011 WB2 PLAT 38 1.2408 F 29 12/12/2011 WB2 FCON 38 0.6651 M 1 12/12/2011 WB2 FCON 50 1.6587 F 7 12/12/2011 WB2 AXEN 56 2.2719 M 3 12/12/2011 WB2 AXEN 58 2.0859 F 8 12/12/2011 WB2 CVAR 56 2.0362 F 5 12/12/2011 WB3 FGRD 43 1.3504 24 12/12/2011 WB3 PLAT 40 1.0758 53 137 ? 12/12/2011 WB3 CVAR 40 1.4480 11 12/12/2011 WB3 AXEN 32 0.6587 30 12/12/2011 WB3 FCON 44 1.0948 42 12/12/2011 WB4 AXEN 29 0.4550 F 2 12/12/2011 WB4 AXEN 31 0.5732 M 2 12/12/2011 WB4 FCON 38 0.7440 F 5 12/12/2011 WB4 FCON 41 0.8628 M 2 12/12/2011 WB4 FGRD 57 2.3690 F 1 12/12/2011 WB4 GHOL 22 0.0966 I 1 3/9/2012 GB1 AXEN 31 0.5602 F 1 3/9/2012 GB1 CVAR 37 1.0535 F 1 3/9/2012 GB1 CVAR 30 0.5279 I 1 3/9/2012 GB1 FCON 44 1.2470 F 8 3/9/2012 GB1 FGRD 72 5.6770 F 8 3/9/2012 GB1 FGRD 72 5..8484 M 8 3/9/2012 GB1 PLAT 42 1.2076 F 7 3/9/2012 GB1 PLAT 34 0.6167 M 2 3/9/2012 GB2 FCON 50 1.9214 F 6 3/9/2012 GB2 FGRD 78 6.6301 F 15 3/9/2012 GB2 FGRD 50 1.3473 I 1 3/9/2012 GB2 FGRD 76 6.6176 M 12 3/9/2012 GB2 PLAT 37 0.9022 F 1 3/9/2012 GB3 CVAR 47 2.4690 F 2 3/9/2012 GB3 FCON 59 3.0863 F 3 3/9/2012 GB3 FGRD 84 9.3899 F 7 3/9/2012 GB3 FGRD 76 6.5037 M 9 3/9/2012 GB3 PLAT 36 0.7149 F 1 3/9/2012 GB4 AXEN 34 0.6429 F 3 3/9/2012 GB4 AXEN 34 0.8014 M 1 3/9/2012 GB4 FCON 58 2.4563 F 1 3/9/2012 GB4 FGRD 75 6.6138 F 41 138 ? 3/9/2012 GB4 FGRD 78 7.2512 M 41 3/9/2012 WB1 CVAR 49 2.7054 M 3 3/9/2012 WB1 FGRD 103 14.6506 F 4 3/9/2012 WB1 FGRD 93 14.2022 M 4 3/9/2012 WB2 AXEN 29 0.4618 F 1 3/9/2012 WB2 AXEN 31 0.5498 M 2 3/9/2012 WB2 CVAR 40 1.5533 F 11 3/9/2012 WB2 CVAR 32 0.7119 I 3 3/9/2012 WB2 CVAR 40 1.4038 M 4 3/9/2012 WB2 FCON 46 1.4454 F 3 3/9/2012 WB2 FCON 46 1.6110 M 3 3/9/2012 WB2 FGRD 65 7.4022 F 7 3/9/2012 WB2 FGRD 45 1.2577 I 1 3/9/2012 WB2 FGRD 71 6.5114 M 5 3/9/2012 WB2 PLAT 47 1.6772 F 1 3/9/2012 WB2 PLAT 43 1.4653 M 5 3/9/2012 WB3 AXEN 31 0.5640 F 7 3/9/2012 WB3 AXEN 33 0.6478 M 10 3/9/2012 WB3 CVAR 45 2.4058 F 27 3/9/2012 WB3 CVAR 34 0.8665 I 5 3/9/2012 WB3 CVAR 45 2.3324 M 30 3/9/2012 WB3 FCON 48 1.6059 F 11 3/9/2012 WB3 FCON 46 1.1031 M 1 3/9/2012 WB3 FGRD 64 4.0688 F 19 3/9/2012 WB3 FGRD 44 0.9807 I 1 3/9/2012 WB3 FGRD 66 4.3399 M 25 3/9/2012 WB3 GHOL 40 0.6543 F 2 3/9/2012 WB3 PLAT 44 1.4143 F 17 3/9/2012 WB3 PLAT 53 2.1812 M 8 3/9/2012 WB4 AXEN 31 0.5693 F 17 3/9/2012 WB4 AXEN 21 0.1860 I 1 139 ? 3/9/2012 WB4 AXEN 32 0.6578 M 13 3/9/2012 WB4 CVAR 51 3.3973 F 3 3/9/2012 WB4 FCON 45 1.3075 F 17 3/9/2012 WB4 FCON 43 1.1190 M 10 3/9/2012 WB4 FGRD 73 6.8138 F 14 3/9/2012 WB4 FGRD 69 5.4914 M 16 3/9/2012 WB4 PLAT 39 0.9810 F 7 3/9/2012 WB4 PLAT 53 2.5796 M 4 3/10/2012 GC1 FCON 50 1.8270 F 1 3/10/2012 GC1 FGRD 83 9.5194 F 8 3/10/2012 GC1 FGRD 79 8.6337 M 6 3/10/2012 GC1 LPAR 40 0.9039 F 1 3/10/2012 GC1 PLAT 40 1.0025 M 1 3/10/2012 GC2 AXEN 33 0.5849 F 1 3/10/2012 GC2 CVAR 47 2.4814 F 19 3/10/2012 GC2 CVAR 50 2.7617 M 2 3/10/2012 GC2 FCON 55 2.1464 M 1 3/10/2012 GC2 FGRD 82 8.5432 F 32 3/10/2012 GC2 FGRD 81 8.0208 M 23 3/10/2012 GC2 PLAT 51 2.1072 F 1 3/10/2012 GC3 CVAR 42 1.6188 F 1 3/10/2012 GC3 FCON 45 1.3125 F 1 3/10/2012 GC3 FCON 61 3.2785 M 1 3/10/2012 GC3 FGRD 81 9.0298 F 11 3/10/2012 GC3 FGRD 84 9.7316 M 9 3/10/2012 GC3 LPAR 40 0.7822 M 1 3/10/2012 GC3 PLAT 35 0.6623 F 1 3/10/2012 GC3 PLAT 39 0.9316 M 3 3/10/2012 GC4 AXEN 35 0.8216 M 1 3/10/2012 GC4 CVAR 48 2.7479 F 3 3/10/2012 GC4 CVAR 48 2.5178 M 2 140 ? 3/10/2012 GC4 FCON 44 1.2334 F 2 3/10/2012 GC4 FGRD 74 6.5156 F 31 3/10/2012 GC4 FGRD 74 6.1924 M 23 3/10/2012 GC4 PLAT 46 1.6932 F 5 3/10/2012 GC4 PLAT 49 1.7364 M 2 3/10/2012 LB1 CVAR 42 1.6128 F 1 3/10/2012 LB1 CVAR 36 0.9337 M 1 3/10/2012 LB1 FGRD 84 9.4429 F 54 3/10/2012 LB1 FGRD 82 8.7087 M 52 3/10/2012 LB2 CVAR 44 1.8385 F 1 3/10/2012 LB2 CVAR 53 3.5619 M 2 3/10/2012 LB2 FGRD 81 8.8829 F 61 3/10/2012 LB2 FGRD 45 1.1415 I 1 3/10/2012 LB2 FGRD 81 8.4831 M 46 3/10/2012 LB3 CVAR 50 2.9926 F 3 3/10/2012 LB3 CVAR 54 3.8181 M 2 3/10/2012 LB3 FGRD 82 8.8018 F 54 3/10/2012 LB3 FGRD 83 8.9153 M 56 3/10/2012 LB4 CVAR 52 3.5234 F 6 3/10/2012 LB4 CVAR 54 3.9249 M 4 3/10/2012 LB4 FGRD 85 9.6360 F 63 3/10/2012 LB4 FGRD 44 0.9762 I 1 3/10/2012 LB4 FGRD 89 10.6472 M 83 3/10/2012 LB4 FSIM 95 10.3313 M 1 3/11/2012 EB1 CVAR 40 1.6292 F 5 3/11/2012 EB1 CVAR 39 1.5035 M 5 3/11/2012 EB1 FCON 46 1.4667 F 11 3/11/2012 EB1 FCON 44 1.2565 M 3 3/11/2012 EB1 FGRD 68 5.6761 F 14 3/11/2012 EB1 FGRD 44 1.1617 I 9 3/11/2012 EB1 FGRD 66 5.1577 M 16 141 ? 3/11/2012 EB1 PLAT 42 1.2309 F 34 3/11/2012 EB1 PLAT 43 1.4098 M 10 3/11/2012 EB2 FCON 43 1.1736 F 9 3/11/2012 EB2 FGRD 78 8.4622 F 16 3/11/2012 EB2 FGRD 47 1.3747 I 1 3/11/2012 EB2 FGRD 74 6.5648 M 27 3/11/2012 EB3 AXEN 32 0.5629 F 5 3/11/2012 EB3 AXEN 34 0.8192 M 2 3/11/2012 EB3 FCON 47 1.4806 F 1 3/11/2012 EB3 FGRD 81 9.4681 F 19 3/11/2012 EB3 FGRD 44 1.0754 I 3 3/11/2012 EB3 FGRD 74 7.2140 M 19 3/11/2012 EB3 PLAT 42 1.2013 F 1 3/11/2012 EB3 PLAT 43 1.3388 M 1 3/11/2012 SQB1 AXEN 36 0.9236 F 10 3/11/2012 SQB1 CVAR 50 2.6988 F 1 3/11/2012 SQB1 CVAR 52 3.3395 M 1 3/11/2012 SQB1 FCON 49 1.8163 F 1 3/11/2012 SQB1 FCON 46 1.2004 M 1 3/11/2012 SQB1 FGRD 73 6.5092 F 48 3/11/2012 SQB1 FGRD 42 0.8592 I 1 3/11/2012 SQB1 FGRD 80 8.1999 M 41 3/11/2012 SQB1 PLAT 38 0.8553 F 1 3/11/2012 SQB2 AXEN 37 0.8987 F 5 3/11/2012 SQB2 AXEN 35 0.7803 M 2 3/11/2012 SQB2 CVAR 53 3.9201 M 3 3/11/2012 SQB2 FCON 52 2.0342 F 3 3/11/2012 SQB2 FGRD 75 7.1529 F 52 3/11/2012 SQB2 FGRD 77 7.0387 M 45 3/11/2012 SQB2 PLAT 64 4.0046 M 2 3/11/2012 SQB3 AXEN 37 0.9394 F 4 142 ? 3/11/2012 SQB3 CVAR 52 3.5891 F 12 3/11/2012 SQB3 CVAR 50 3.0822 M 2 3/11/2012 SQB3 FGRD 72 6.0598 F 47 3/11/2012 SQB3 FGRD 76 6.8796 M 34 3/11/2012 SQB4 AXEN 35 0.8269 F 5 3/11/2012 SQB4 AXEN 37 0.9766 M 1 3/11/2012 SQB4 CVAR 58 4.7500 F 1 3/11/2012 SQB4 FCON 51 1.7832 - 1 3/11/2012 SQB4 FGRD 81 9.1892 F 44 3/11/2012 SQB4 FGRD 77 7.0646 M 18 7/17/2012 GB1 FCON 50 1.6515 F 1 7/17/2012 GB1 FCON 43 1.0460 M 1 7/17/2012 GB1 FGRD 70 5.4034 F 4 7/17/2012 GB1 FGRD 63 3.5393 M 3 7/17/2012 GB2 CVAR 47 2.1321 F 1 7/17/2012 GB2 FGRD 67 4.4909 F 26 7/17/2012 GB2 FGRD 59 2.8113 M 27 7/17/2012 GB3 FGRD 63 3.2558 F 1 7/17/2012 GB4 CVAR 47 2.4601 F 1 7/17/2012 GB4 FCON 58 2.5401 F 1 7/17/2012 GB4 FGRD 75 6.5446 F 17 7/17/2012 GB4 FGRD 51 1.7512 I 9 7/17/2012 GB4 FGRD 79 8.2784 M 79 7/17/2012 WB1 FCON 52 1.8565 F 7 7/17/2012 WB1 FCON 53 1.8216 M 2 7/17/2012 WB1 FGRD 58 2.7164 F 22 7/17/2012 WB1 FGRD 45 1.0792 I 8 7/17/2012 WB1 FGRD 56 2.4328 M 3 7/17/2012 WB1 GHOL 44 0.9692 F 2 7/17/2012 WB1 PLAT 40 1.0412 F 23 7/17/2012 WB1 PLAT 41 1.0099 M 3 143 ? 7/17/2012 WB2 CVAR 42 1.6449 F 2 7/17/2012 WB2 CVAR 43 1.7358 M 5 7/17/2012 WB2 FCON 50 1.7995 F 17 7/17/2012 WB2 FCON 51 1.8949 M 5 7/17/2012 WB2 FGRD 65 4.4644 F 9 7/17/2012 WB2 FGRD 46 1.2899 I 6 7/17/2012 WB2 FGRD 73 6.0247 M 6 7/17/2012 WB2 LPAR 42 0.8973 F 1 7/17/2012 WB2 PLAT 41 1.1791 F 36 7/17/2012 WB2 PLAT 40 0.9231 M 5 7/17/2012 WB3 AXEN 35 0.7520 F 7 7/17/2012 WB3 AXEN 40 1.2908 M 1 7/17/2012 WB3 CVAR 41 1.5324 F 6 7/17/2012 WB3 CVAR 30 0.5213 I 1 7/17/2012 WB3 CVAR 42 1.7566 M 4 7/17/2012 WB3 FCON 51 1.9374 F 33 7/17/2012 WB3 FGRD 60 3.5815 F 21 7/17/2012 WB3 FGRD 44 1.1011 I 31 7/17/2012 WB3 FGRD 65 4.8605 M 18 7/17/2012 WB3 GHOL 43 0.8105 F 1 7/17/2012 WB3 PLAT 40 1.0531 F 55 7/17/2012 WB3 PLAT 41 0.9267 M 8 7/17/2012 WB4 AXEN 35 0.8487 F 1 7/17/2012 WB4 CVAR 42 1.8814 F 6 7/17/2012 WB4 CVAR 39 1.5777 M 5 7/17/2012 WB4 FCON 50 1.8892 F 13 7/17/2012 WB4 FCON 45 1.2701 M 5 7/17/2012 WB4 FGRD 63 4.0968 F 33 7/17/2012 WB4 FGRD 47 1.4866 I 19 7/17/2012 WB4 FGRD 71 6.5606 M 27 7/17/2012 WB4 GHOL 32 0.3474 F 1 144 ? 7/17/2012 WB4 PLAT 45 1.2769 M 3 7/18/2012 LB1 FGRD 82 9.4508 F 20 7/18/2012 LB1 FGRD 45 1.1604 I 13 7/18/2012 LB1 FGRD 72 6.3435 M 19 7/18/2012 LB1 PLAT 41 1.2491 F 2 7/18/2012 LB2 AXEN 36 0.8302 F 1 7/18/2012 LB2 FCON 63 3.4776 F 1 7/18/2012 LB2 FGRD 70 5.9037 F 84 7/18/2012 LB2 FGRD 49 1.5204 I 14 7/18/2012 LB2 FGRD 72 5.9994 M 69 7/18/2012 LB3 FCON 60 3.2989 F 1 7/18/2012 LB3 FGRD 70 5.5485 F 57 7/18/2012 LB3 FGRD 46 1.2340 I 22 7/18/2012 LB3 FGRD 74 6.6688 M 38 7/18/2012 LB4 AXEN 40 1.2591 F 1 7/18/2012 LB4 AXEN 39 1.2363 M 2 7/18/2012 LB4 FGRD 73 5.8919 F 92 7/18/2012 LB4 FGRD 46 1.2110 I 3 7/18/2012 LB4 FGRD 77 7.0939 M 49 7/18/2012 LB4 PLAT 44 1.4043 F 3 7/18/2012 LB4 PLAT 52 1.8705 M 2 7/19/2012 EB1 AXEN 35 0.7270 F 3 7/19/2012 EB1 CVAR 46 2.0172 M 1 7/19/2012 EB1 FCON 48 1.3619 F 1 7/19/2012 EB1 FGRD 55 2.1361 F 3 7/19/2012 EB1 FGRD 41 1.0604 I 7 7/19/2012 EB1 FGRD 55 2.3980 M 1 7/19/2012 EB1 PLAT 40 0.9072 F 1 7/19/2012 EB2 FCON 55 2.3298 F 1 7/19/2012 EB2 FGRD 69 5.6957 F 10 7/19/2012 EB2 FGRD 44 1.0622 I 6 145 ? 7/19/2012 EB2 FGRD 79 7.5297 M 7 7/19/2012 EB2 PLAT 38 SL 1.3838 M 1 7/19/2012 EB3 FCON 56 2.3655 F 1 7/19/2012 EB3 FGRD 78 7.7769 F 18 7/19/2012 EB3 FGRD 47 1.2901 I 9 7/19/2012 EB3 FGRD 89 10.1399 M 14 7/19/2012 SQB1 AXEN 35 0.7942 F 2 7/19/2012 SQB1 CVAR 59 5.0400 F 1 7/19/2012 SQB1 FGRD 70 5.3847 F 24 7/19/2012 SQB1 FGRD 49 1.4491 I 17 7/19/2012 SQB1 FGRD 79 7.8501 M 21 7/19/2012 SQB1 PLAT 44 1.6224 F 15 7/19/2012 SQB1 PLAT 46 1.2954 M 2 7/19/2012 SQB2 FCON 56 2.4103 F 1 7/19/2012 SQB2 FGRD 77 7.5750 F 36 7/19/2012 SQB2 FGRD 46 1.1819 I 5 7/19/2012 SQB2 FGRD 84 9.5612 M 15 7/19/2012 SQB2 GHOL 51 1.4505 F 1 7/19/2012 SQB3 AXEN 31 0.4454 F 2 7/19/2012 SQB3 FGRD 75 7.4283 F 19 7/19/2012 SQB3 FGRD 48 1.3615 I 10 7/19/2012 SQB3 FGRD 77 7.6657 M 13 7/19/2012 SQB3 GHOL 37 0.5238 F 1 7/19/2012 SQB3 PLAT 40 1.1111 F 4 7/19/2012 SQB3 PLAT 48 1.6456 M 2 7/19/2012 SQB4 FGRD 75 7.5071 F 36 7/19/2012 SQB4 FGRD 48 1.5062 I 3 7/19/2012 SQB4 FGRD 67 4.4679 M 7 7/29/2012 GC1 NO FISH 0 7/29/2012 GC2 CVAR 48 3.3891 F 1 146 ? 7/29/2012 GC2 CVAR 44 2.1212 M 1 7/29/2012 GC2 FGRD 67 4.7616 F 5 7/29/2012 GC2 FGRD 68 4.4341 M 3 7/29/2012 GC2 PLAT 38 0.8485 M 3 7/29/2012 GC3 CVAR 52 3.4117 F 1 7/29/2012 GC3 CVAR 43 1.8186 M 1 7/29/2012 GC3 FCON 47 1.5468 F 1 7/29/2012 GC3 FGRD 73 5.4210 F 9 7/29/2012 GC3 FGRD 55 1.9425 I 1 7/29/2012 GC3 FGRD 71 5.8830 M 11 7/29/2012 GC3 PLAT 40 1.0659 F 3 7/29/2012 GC3 PLAT 36 0.6107 M 5 7/29/2012 GC4 FGRD 81 8.3037 F 11 7/29/2012 GC4 FGRD 57 2.2915 I 2 7/29/2012 GC4 FGRD 74 5.7898 M 15 7/29/2012 GC4 PLAT 40 0.7033 M 2 9/7/2012 GC1 GHOL 32 0.4769 F 21 9/7/2012 GC1 GHOL 22 0.1066 M 2 9/7/2012 GC2 GHOL 38 0.6108 F 13 9/7/2012 GC2 GHOL 19 SL 0.1497 I (M) 1 9/7/2012 GC2 GHOL 21 SL 0.2119 M 1 9/7/2012 GC3 AXEN 34 0.6870 F 1 9/7/2012 GC3 GHOL 38 0.6259 F 21 9/7/2012 GC3 GHOL 17 SL 0.0954 I 2 9/7/2012 GC3 GHOL 21 SL 0.1353 M 1 9/7/2012 GC3 PLAT 30 SL 0.6690 F 1 9/7/2012 GC3 PLAT 46 1.3968 M 1 9/7/2012 GC4 FGRD 84 8.9276 F 13 9/7/2012 GC4 FGRD 78 6.8679 M 4 9/7/2012 GC4 GHOL 43 0.9296 F 3 9/7/2012 GC4 PLAT 40 1.1832 F 6 147 ? 9/7/2012 GC4 PLAT 39 1.1040 M 2 9/7/2012 LB1 AXEN 35 0.6907 F 2 9/7/2012 LB1 AXEN 33 0.6906 M 3 9/7/2012 LB1 FCON 46 1.3988 F 1 9/7/2012 LB1 FGRD 69 5.7363 F 30 9/7/2012 LB1 FGRD 83 10.1628 M 25 9/7/2012 LB1 GHOL 38 0.7658 F 1 9/7/2012 LB1 PLAT 42 1.2764 F 28 9/7/2012 LB1 PLAT 48 1.7785 M 4 9/7/2012 LB2 AXEN 28 SL 0.5918 M 1 9/7/2012 LB2 CVAR 51 3.0050 F 2 9/7/2012 LB2 CVAR 54 4.0935 M 1 9/7/2012 LB2 FCON 44 1.5220 M 1 9/7/2012 LB2 FGRD 76 6.9159 F 54 9/7/2012 LB2 FGRD 81 8.5629 M 66 9/7/2012 LB2 FSIM 95 10.0680 F 1 9/7/2012 LB2 PLAT 54 2.8835 F 2 9/7/2012 LB2 PLAT 57 3.1781 M 2 9/7/2012 LB3 AXEN 30 0.5045 F 1 9/7/2012 LB3 FGRD 68 5.3270 F 43 9/7/2012 LB3 FGRD 46 1.2310 I 3 9/7/2012 LB3 FGRD 74 7.0438 M 24 9/7/2012 LB3 GHOL 44 1.1562 F 1 9/7/2012 LB3 GHOL 23 0.1166 I 1 9/7/2012 LB3 PLAT 50 2.4700 F 3 9/7/2012 LB3 PLAT 22 SL 0.2748 I 1 9/7/2012 LB4 AXEN 38 1.0346 F 4 9/7/2012 LB4 AXEN 34 0.7007 M 3 9/7/2012 LB4 FGRD 73 6.0985 F 79 9/7/2012 LB4 FGRD 45 1.2210 I 4 9/7/2012 LB4 FGRD 76 6.9543 M 48 148 ? 9/7/2012 LB4 PLAT 44 1.2812 F 4 9/7/2012 LB4 PLAT 51 2.2871 M 3 9/8/2012 EB1 FCON 52 1.6574 F 1 9/8/2012 EB1 FGRD 57 2.1906 F 5 9/8/2012 EB1 FGRD 46 1.1428 I 2 9/8/2012 EB1 FGRD 65 3.9609 M 4 9/8/2012 EB1 GHOL 37 0.5408 F 6 9/8/2012 EB1 PLAT 44 1.1462 F 2 9/8/2012 EB1 PLAT 39 0.9253 M 3 9/8/2012 EB2 FGRD 56 2.4287 F 2 9/8/2012 EB2 FGRD 44 1.0753 I 3 9/8/2012 EB2 GHOL 29 0.2493 F 19 9/8/2012 EB2 GHOL 21 0.0902 I 4 9/8/2012 EB2 GHOL 26 0.1439 M 3 9/8/2012 EB2 PLAT 34 0.5730 F 5 9/8/2012 EB2 PLAT 20 0.1077 I 1 9/8/2012 EB2 PLAT 45 1.4870 M 1 9/8/2012 EB3 FGRD 68 5.3772 F 45 9/8/2012 EB3 FGRD 48 1.2555 I 7 9/8/2012 EB3 FGRD 77 7.6718 M 28 9/8/2012 EB3 GHOL 31 0.3227 F 2 9/8/2012 EB3 GHOL 27 0.1887 M 1 9/8/2012 EB3 PLAT 54 2.7962 F 2 9/8/2012 SQB1 AXEN 38 1.0472 F 1 9/8/2012 SQB1 FCON 56 2.5562 F 3 9/8/2012 SQB1 FGRD 69 5.3886 F 24 9/8/2012 SQB1 FGRD 48 1.2162 I 2 9/8/2012 SQB1 FGRD 75 6.7086 M 22 9/8/2012 SQB1 PLAT 44 1.3576 F 23 9/8/2012 SQB1 PLAT 49 1.8128 M 7 9/8/2012 SQB2 FGRD 71 5.7053 F 21 149 ? 9/8/2012 SQB2 FGRD 48 1.4093 I 2 9/8/2012 SQB2 FGRD 72 5.8272 M 14 9/8/2012 SQB2 GHOL 50 1.3464 F 1 9/8/2012 SQB2 PLAT 45 1.5085 F 10 9/8/2012 SQB2 PLAT 50 2.1381 M 11 9/8/2012 SQB3 AXEN 31 0.5054 F 2 9/8/2012 SQB3 FGRD 73 6.4388 F 16 9/8/2012 SQB3 FGRD 48 1.3162 I 2 9/8/2012 SQB3 FGRD 71 6.3089 M 9 9/8/2012 SQB3 PLAT 48 1.8372 F 14 9/8/2012 SQB3 PLAT 50 1.7317 M 2 9/8/2012 SQB4 AXEN 34 0.7009 F 5 9/8/2012 SQB4 AXEN 35 0.7697 M 3 9/8/2012 SQB4 FGRD 71 6.0947 F 28 9/8/2012 SQB4 FGRD 73 6.3692 M 11 9/8/2012 SQB4 PLAT 47 1.7317 F 21 9/8/2012 SQB4 PLAT 55 2.7710 M 15 9/9/2012 GB1 AXEN 35 0.6915 F 1 9/9/2012 GB1 FGRD 101 15.8983 F 4 9/9/2012 GB1 FGRD 91 11.7633 M 3 9/9/2012 GB1 GHOL 23 0.1133 I 1 9/9/2012 GB2 AXEN 41 1.2482 F 1 9/9/2012 GB2 FGRD 76 6.6403 F 4 9/9/2012 GB2 FGRD 73 5.5972 M 1 9/9/2012 GB2 GHOL 33 0.4241 F 7 9/9/2012 GB2 GHOL 22 0.1099 I 2 9/9/2012 GB2 GHOL 26 0.1839 M 1 9/9/2012 GB4 FGRD 100 13.6345 F 3 9/9/2012 GB4 FGRD 98 14.6309 M 5 9/9/2012 WB1 FGRD 66 4.1326 F 13 9/9/2012 WB1 FGRD 41 SL 1.2416 I 1 150 ? 9/9/2012 WB1 FGRD 64 3.6767 M 7 9/9/2012 WB1 GHOL 32 0.3852 F 16 9/9/2012 WB1 GHOL 22 0.0950 I 3 9/9/2012 WB1 GHOL 24 0.1120 M 1 9/9/2012 WB1 PLAT 44 1.4926 F 46 9/9/2012 WB1 PLAT 22 0.1699 I 1 9/9/2012 WB1 PLAT 43 1.3710 M 20 9/9/2012 WB2 FCON 55 2.3112 F 3 9/9/2012 WB2 FCON 49 1.6459 M 2 9/9/2012 WB2 FGRD 66 5.0367 F 10 9/9/2012 WB2 FGRD 70 6.0775 M 5 9/9/2012 WB2 FPUL 54 2.0634 M 1 9/9/2012 WB2 GHOL 35 0.4404 F 28 9/9/2012 WB2 PLAT 44 1.4901 F 7 9/9/2012 WB2 PLAT 47 1.7718 M 11 9/9/2012 WB3 AXEN 35 0.8403 M 1 9/9/2012 WB3 FCON 49 1.8879 F 10 9/9/2012 WB3 FCON 41 0.8448 M 1 9/9/2012 WB3 FGRD 63 3.9674 F 17 9/9/2012 WB3 FGRD 47 1.2902 I 10 9/9/2012 WB3 FGRD 72 6.1451 M 12 9/9/2012 WB3 GHOL 32 0.4030 F 25 9/9/2012 WB3 PLAT 40 1.0889 F 4 9/9/2012 WB3 PLAT 39 0.9023 M 2 9/9/2012 WB4 AXEN 32 0.5686 F 1 9/9/2012 WB4 FGRD 71 5.7226 F 22 9/9/2012 WB4 FGRD 47 1.2324 I 3 9/9/2012 WB4 FGRD 72 6.0938 M 23 9/9/2012 WB4 GHOL 23 0.1165 I 1 9/9/2012 WB4 PLAT 49 1.9637 F 1 9/9/2012 WB4 PLAT 51 2.0795 M 1 151 ?