2009 NORTHEASTERN NATURALIST 16(2):255–268 Environmental Variability Affects Distributions of Coastal Fish Species (Maryland) Joseph W. Love1,*, Paulinus Chigbu1, and Eric B. May1 Abstract - We determined how environmental variability affected distributions of seasonally recruiting fishes (i.e., transient species) in coastal lagoons of Maryland from May–October during 1996, 1997, and 1999. A total of 241 monthly sampling events were conducted in the coastal lagoons at 40 sampling stations. Fluctuations in salinity resulting from variation in stream discharge were negatively correlated with intra-annual stability of fish assemblages. Transient, or non-resident species (e.g., recruiting species), were more frequent in habitats where salinity was less variable. When stream discharge lessened during dry years, transient species were more common throughout the coastal lagoons. Thus, environmental variability influenced distributions of young-of-year fishes in coastal estuaries. Introduction Documenting relationships between environmental variability and habitat use by fishes builds knowledge on the functional role of coastal estuaries as nursery habitat, and the conditions under which they serve that role. Interannual differences in coastal conditions occur as precipitation and stream discharge levels vary because of large-scale climatic patterns (e.g., El Niño/ La Niña events). Variation in stream discharge affects the first year of life of fishes (Hare and Able 2007, Rogers et al. 1984, Searcy et al. 2007) and invertebrates (Hofmann and Powell 1998, Hofstetter 1983) by influencing salinity levels and nutrient addition (Rabalais et al. 2002). Nutrient addition may result in lower dissolved oxygen (DO), which can adversely influence behavior and survivorship of fishes (Eby et al. 2005, Kramer 1987, Love and Rees 2002). However, fish species respond differently to variation in stream discharge (Rogers et al. 1984). Some species may emigrate from habitats that vary considerably in salinity when stream discharge is high, resulting in greater variability of those assemblages. Thus, more stable environments may provide greater stability of fish assemblages, as well as higher diversity, higher biomass, and suitable habitat for larger-bodied predators (Kushlan 1976). We used a multi-species approach to explore the role of environmental variability in salinity and DO on dynamics of fish assemblages. The research was conducted in coastal lagoons of the lower eastern shore of Maryland (Fig. 1) during 1996, 1997, and 1999. In 1996, the average mean monthly stream discharge on the lower eastern shore from May–October (≈1.62 m3/sec) was about four times that observed for 1997 (0.39 m3/sec) and 1Department of Natural Sciences, NOAA Living Marine Resources Cooperative Science Center, University of Maryland Eastern Shore, Princess Anne, MD 21853. *Corresponding author - jlove@umes.edu. 256 Northeastern Naturalist Vol. 16, No. 2 double that observed for 1999 (0.85 m3/sec), as measured for Nassawango Creek (Snow Hill, MD; USGS Gauge 01485500). While Nassawango Creek is part of the Chesapeake Bay watershed, it is the only stream gauge on the lower eastern shore of Maryland with data from 1996–1999. Notably, data from 2 gauges in the coastal bays watershed (USGS 0148471320, Showell, MD; USGS 01484719, Ironshire, MD) were highly correlated to stream discharge from Nassawango Creek (r > 0.80) for 2000–2007. Interannual variation in stream discharge was likely related to interannual variation in precipitation, which was higher from May–October in 1996 (12.0 cm) than 1997 (2.6 cm) and 1999 (7.8 cm) (data from Remote Automated Weather Stations, Assateague Island, www.raws.dri.edu/wraws/de_mdF.html). The coastal lagoons of Maryland lie behind Assateague and Fenwick Islands (Fig. 1), and two inlets provide access to the Atlantic Ocean. Ocean City Inlet (OCI) was formed during a 1933 storm and may be an important dispersal corridor for marine and estuarine fishes (Schwartz 1961, 1964). Chincoteague Inlet, VA is larger and has been in place for at least 200 years, providing access for migratory and recruiting fishes (Hall et al. 2005). Environmental variability was expected to differ between OCI and lagoon areas closer to rivers. There are over 100 species of fish that utilize coastal lagoons of Maryland; the distributions of some of these species have been documented (Love and May 2007; Murphy and Secor 2006; Schwartz 1961, 1964; Slacum et al. 2000). The influence of environmental variability on fish distribution has not been addressed in this system. Figure 1. Map of surveyed sites from the coastal lagoons of Maryland and Virginia. Ocean City Inlet (OCI) lies at 38°N and 75°W. 2009 J.W. Love, P. Chigbu, and E.B. May 257 Our objectives were to: 1) determine whether environmental variability in salinity and DO was high at points of stream discharge, and compare those patterns between a climatically wet (1996) and dry (1997) year, with additional comparisons to an intermediate year (1999); and 2) determine if environmental variability of salinity and DO explained variability in fish assemblages. We predicted that more environmentally stable habitats would have greater proportions of transient fishes. Methods We used environmental and fish survey data from Slacum et al. (2000) for 1996 (7 sites), 1997 (11 sites), and 1999 (22 sites) (Fig. 1). All sites were surveyed monthly between May and October. Temperature, DO, and salinity were measured using a Hydrolab H20 and Surveyor 3 (Hydrolab Corporation). Dissolved oxygen minima were not measured because sampling occurred after dawn. Fishes were sampled using a 4.9-m semi-balloon otter trawl with 5-mm mesh at the cod-end (Slacum et al. 2000). Trawling was conducted at approximately 4 knots in water more than 1 m deep and for 6 minutes. Two trawls were conducted at each site. For each trawl, all fish were identified and enumerated, and data were pooled between trawls for each site. We pooled data because trawl events did not constitute replicate surveys and yielded a more robust sample for each site. Species were identified in the field, but voucher specimens were preserved in 10% formalin for later verification. Species were considered rare if they constituted less than 0.01% of the sample (low abundance) for less than 0.01% of all sites (low frequency). Rare species were excluded from the dataset. Abundance data were square-root transformed prior to analysis to help normalize variance (McCune and Grace 2002). All data were entered into spreadsheets twice by different people and cross-checked for errors. We quantified the level of monthly variability in temperature, salinity, and DO at a site for each year using coefficients of variation (CV). We used linear regression to determine if average temperature, salinity, and DO, or their respective CVs, differed with increasing distance from OCI to habitats closer to a stream mouth. The OCI is strongly influenced by tidal flushing, but may provide more stable and higher salinities. We used separate regressions for each month and year of study to determine how environmental variability (dependent variables) differed as distance from OCI increased (independent variable). Environmental data were log10 transformed prior to analysis, and CVs were transformed by an arcsine square root. The least distance from each site to OCI was measured using ArcView (Version 3.3, Environmental Systems Research Institute, Inc.) and log10 transformed prior to analyses. We determined if within-year stability of salinity and DO explained variability of a fish assemblage. Our approach was to: 1) assign similarity scores to an assemblage sampled at a site, 2) quantify the variability of those scores for each site across time, and 3) relate variability in those scores to environmental variability (i.e., CVs). To assign scores to an assemblage, we 258 Northeastern Naturalist Vol. 16, No. 2 used an indirect gradient, multivariate analysis (non-metric multidimensional scaling [NMDS]). Monthly assemblages were scored based on assemblage dissimilarity (Sörensen or Bray-Curtis distances) following McCune and Mefford (1999: 114). The NMDS analysis performed an iterative search to rank and place these scores on k-axes in a manner to minimize the stress of the k-dimensional configuration (McCune and Grace 2002, McCune and Mefford 1999). Stress of each axis for each run measures the departure from monotonicity in the relationship between distance in the p-dimensional matrix (calculated using the original data matrix with p-columns) and distance in the reduced k-dimensional configuration. The standard deviation in stress divided by the number of iterations is the instability criterion and should be less than 0.001 for acceptable NMDS ordinations (McCune and Grace 2002). We began with a six-dimensional solution and stepped down to a onedimensional solution using 500 iterations and 10 runs of the data set. The final number of k-axes was estimated using Scree plots. For each axis, we used 20 runs with randomized data to assess the significance of obtaining a stress value less than or equal to the observed stress using Monte Carlo simulation (McCune and Mefford 1999). For the final number of k-axes, we generated two-dimensional plots of scores for NMDS axes that represented the largest proportions of variance from the original data matrix. To quantify variability of NMDS scores at a site, the coordinates for scores for each axis were plotted in a new view using ArcView. Each coordinate in the new view represented sitei for monthj. Scores for sitei were connected by a polygon that represented the maximum area possible for the points (i.e., Maximum Area Polygon or MAP). Thus, a polygon represented by 6 vertices (i.e., six months) was drawn for each site surveyed in 1996, 1997, and 1999. The area of the polygon was calculated using ArcView. The area of the polygon represented the maximum level of assemblage change for sitei from May until October. To relate assemblage variability to environmental variability, we used linear regressions of MAP values (dependent variable) and CV salinity and CV DO (independent variables). MAP values were log10 transformed. We determined if environmental variability affected distribution of transient species by comparing the number of transient species between habitats near OCI and habitats further from OCI, which are more influenced by stream discharge. For these analyses, we used a subset of each of the 1996, 1997, and 1999 datasets and included 3 sites that occurred near OCI (average distance = 6 km) and 3 sites that occurred farther from OCI (average distance = 25 km). We defined a habitat near OCI using an 8-km radius or 200-km area (Fig. 1; Slacum et al. 2000). For each species collected, we categorized it as either resident or transient based on life history (Table 1). Transient species included species that recruit to coastal estuaries and species that strayed into the estuary as adults. Most species collected were not strays, but recruiting juveniles. The categorization of transience and residence is imperfect because of complex life histories represented by the diversity of species collected here. Life-history characteristics were determined using Murdy et 2009 J.W. Love, P. Chigbu, and E.B. May 259 al. (1997), Able and Fahay (1998), and Carpenter (2002). Anguilla rostrata (American Eel), a catadromous species, was considered a resident because individuals that were collected were not glass eels (larval stage of ingress) and the majority of adult life is spent in freshwater and estuary habitats. We used two methods to determine if the number of transient species differed between habitats near OCI and farther from OCI. First, we tabulated the number of species that were proportionately abundant (>50% relative abundance) in each habitat for each year. For example, if the abundance of a species was higher near OCI than farther from OCI, it was tallied for habitats near OCI. Second, we also tabulated the exclusive occurrence of a species in either habitat for each year. We used contingency tables and Fisher exact tests (twotailed) to determine if the number of proportionately abundant or exclusively occurring transient species differed between habitats near OCI and further from OCI, and compared those patterns for 1996, 1997, and 1999. Multivariate analyses were performed using PC-ORD (Version 4.01, MjM Software, Gleneden Beach, OR; McCune and Mefford, 1999). All other analyses were performed with SYSTAT (Version 11, SYSTAT Software Inc., Port Richmond, CA). Results Sites were polyhaline (20–30 ppt) and typically shallow (<2 m), but ranged from 1.1 m–5.2 m. Salinity was highest near OCI, and decreased with increasing distance from OCI in October for 1996, and in June and August for 1997, but never for 1999 (Table 1). Monthly variability in salinity was significantly higher further from OCI in 1996 (m = 7.48, r2 = 0.78, P = 0.008) and 1997 (m = 14.4, r 2 = 0.62, P = 0.004), but not 1999 (m = 0.008, r 2 = 0.03, P = 0.474). Thus, during the wet conditions of 1996 and the dry conditions Table 1. Summary of environmental data collected monthly from sampling sites within the coastal lagoons of Maryland from 1996 (7 sites), 1997 (11 sites), and 1999 (22 sites). Means with standard deviations in parentheses are given. Variables are salinity (Sal, ppt), dissolved oxygen (DO, mg/L), and temperature (Temp, °C). The coefficient of variation (CV, %) was generated across months for each site. The CV and monthly means of temperature, salinity, and DO were regressed against distance of the site from Ocean City Inlet in Maryland (*P < 0.05). May June July August September October CV (%) 1996 Sal 25.4 (2.4) 28.0 (1.0) 28.4 (0.9) 26.9 (1.1) 24.6 (2.5) 25.4 (3.6)* 6.0* DO 5.6 (1.7)* 6.7 (1.1) 6.9 (1.0) 6.8 (0.7) 6.5 (0.8) 8.7 (0.8) 16.0* Temp 19.5 (3.5) 26.3 (2.3)* 24.6 (1.4)* 24.8 (1.9)* 21.8 (0.9) 15.1 (1.8) 21.0 1997 Sal 25.2 (2.6) 25.9 (1.7)* 26.9 (1.4) 26.5 (1.2) 28.0 (1.3) 27.8 (0.9) 7.0* DO 7.9 (1.0)* 9.9 (0.7) 6.5 (0.6) 6.0 (0.8) 7.6 (1.0) 9.0 (0.8) 19.0 Temp 18.3 (2.6) 24.7 (1.9)* 25.7 (3.1)* 26.2 (2.4) 20.5 (0.5) 13.8 (1.1) 22.0 1999 Sal 27.6 (1.1) 28.4 (0.7) 29.6 (0.8) 30.2 (0.4) 27.9 (1.3) 27.3 (1.3) 5.1 DO 6.7 (0.4) 6.8 (1.0) 6.0 (0.8) 6.9 (1.1) 7.9 (0.9) 8.0 (1.0) 16.3 Temp 19.8 (1.7) 23.1 (2.3) 27.8 (1.8) 26.1 (1.3) 19.7 (1.6) 15.8 (2.0) 20.7 260 Northeastern Naturalist Vol. 16, No. 2 Table 2. Species collected in the coastal lagoons of Maryland (May to October) for 1996 (7 sites), 1997 (11 sites), and 1999 (22 sites) at sampling locations depicted in Figure 1. Relative percentage of species (%N) collected in 1996, 1997, and 1999 are given. Species are denoted as transient (T), resident (R), or information not available (N/A). Sources of information are Murdy et al. (1997), Able and Fahay (1998), and Carpenter (2002). %N Species 1996 1999 1997 T/R Alosa aestivalis (Mitchill) (Blueback Herring) 0.00 0.66 - T Anchoa hepsetus (Linnaeus) (Striped Anchovy) 5.76 1.28 0.77 T Anchoa mitchilli (Cuvier and Valenciennes) (Bay Anchovy) 39.96 34.76 30.05 R Anguilla rostrata (Lesuer) (American Eel) 0.00 0.24 0.34 R Apeltes quadracus (Mitchill) (Fourspine Stickleback) 0.00 0.19 0.4 R Archosargus probatocephalus (Walbaum) (Sheepshead) 0.00 0.05 0.00 T Astroscopus guttatus Abbott (Northern Stargazer) 0.42 0.05 0.06 R Bairdiella chrysoura (Lacepède) (Silver Perch) 9.95 7.54 4.3 T Brevoortia tyrannus (Latrobe) (Atlantic Menhaden) 2.62 0.43 0.57 T of 1997, a significant salinity gradient formed in the coastal bays watershed during some months of summer, and variability in salinity was higher farther from OCI. In contrast, during the moderately dry year of 1999, no salinity gradients formed, and monthly salinity was generally higher, on average, than during the same months in 1996 and 1997 (Table 1). Dissolved oxygen across sites ranged from 5.6 mg/L (May 1996) to 9.0 mg/L (October 1997), and monthly averages among sites did not fall to hypoxic levels (i.e., 2 mg/L). Dissolved oxygen decreased with increasing distance from OCI in May of 1996 (m = -0.477, r 2 = 0.82, P = 0.005), but increased with increasing distance from OCI in May of 1997 (m = 0.089, r 2 = 0.39, P = 0.40). Dissolved oxygen also increased with increasing distance from OCI in October 1996 (m = 0.046, r 2 = 0.68, P = 0.023; Table 1). During the wet conditions of 1996, monthly variability in DO increased with increasing distance from OCI (m = 0.25, r 2 = 0.84, P = 0.004). However, during the drier years of 1997 and 1999, there was no relationship between distance from OCI and variability in DO. Distributions of 38, 45, and 52 species of fish (Class: Actinopterygii) were analyzed for 1996 (43 sampling efforts), 1997 (66 sampling efforts), and 1999 (132 sampling efforts), respectively. Anchoa mitchilli (Bay Anchovy) constituted the highest percentage of the collection for all years (Table 2). The Sciaenidae represented a large proportion of the sample, with Leiostomus xanthurus (Spot), Bairdiella chyrosoura (Silver Perch), and Cynoscion regalis (Weakfish) among the most abundant. With the exception of Bay Anchovy, open-water species, such as Menidia menidia (Atlantic Silverside) and Clupeidae (herrings) were less common, likely because of sampling gear bias. Assemblage similarities among sites were represented in multivariate plots along NMDS axes (Fig. 2). For 1996 and 1997, the 1st NMDS axis explained relatively less variance (r 2 = 0.18) than the 2nd and 3rd axes (r2 = 0.29 and 0.36, respectively). In 1999, the 2nd NMDS axis explained less 2009 J.W. Love, P. Chigbu, and E.B. May 261 Table 2, continued. %N Species 1996 1999 1997 T/R Centropristis striata (Linnaeus) (Black Sea Bass) 0.14 1.76 3.93 T Chaetodon ocellatus Bloch (Spotfin Butterflyfish) 0.00 0.08 0.08 T Chasmodes bosquianus Lacepède (Striped Blenny) 0.00 0.40 0.18 R Chilomycterus schoepfi(Walbaum) (Striped Burrfish) 0.00 0.00 0.51 T Clupea harengus Linnaeus (Atlantic Herring) 3.74 0.76 1.10 T Cynoscion regalis (Bloch and Schneider) (Weakfish) 4.04 6.55 7.59 T Cyprinodon variegatus Lacepède (Sheepshead Minnow) 0.14 0.00 0.26 R Diplodus holbrooki (Bean) (Spottail Pinfish) 0.00 0.00 0.04 T Etropus microstomus (Gill) (Smallmouth Flounder) 1.49 0.55 2.87 T Eucinostomus gula (Quoy and Gaimard) (Silver Jenny) 0.00 0.00 0.12 N/A Fistularia tabacaria Linnaeus (Bluespotted Cornetfish) 0.00 0.00 0.15 T Fundulus heteroclitus (Linnaeus) (Mummichog) 0.00 0.08 0.16 R Fundulus majalis (Walbaum) (Striped Killifish) 0.00 0.00 0.32 R Gobiosoma bosc Lacepède (Naked Goby) 0.71 0.57 0.53 R Gobiesox strumosus Cope (Skilletfish) 0.00 0.00 0.00 R Hippocampus erectus Perry (Lined Seahorse) 1.28 0.54 1.15 R Hypsoblennius hentz (Lesuer) (Feather Blenny) 0.00 0.00 0.13 R Lagodon rhomboides (Linnaeus) (Pinfish) 0.00 0.00 0.52 T Leiostomus xanthurus Lacepède (Spot) 2.36 23.9 7.07 T Lucania parva (Baird and Girard) (Rainwater Killifish) 0.31 0.43 0.68 R Menidia menidia (Linnaeus) (Atlantic Silverside) 8.19 0.87 1.42 R Menticirrhus saxatilis (Bloch and Schneider) (Northern Kingfish) 0.56 0.16 0.57 T Microgobius thalassinus (Jordan and Gilbert) (Green Goby) 0.56 0.65 0.61 R Micropogonias undulatus (Linnaeus) (Atlantic Croaker) 2.29 4.52 4.62 T Monocanthus hispidus (Linnaeus) (Planehead Filefish) 0.14 0.05 0.00 T Morone saxatilis (Walbaum) (Striped Bass) 0.14 0.00 0.00 T Mycteroperca microlepis (Goode and Bean) (Gag) 0.14 0.00 0.00 T Ophidion marginatum DeKay (Striped Cusk-eel) 0.14 0.2 0.19 T Opsanus tau (Linnaeus) (Oyster Toadfish) 0.56 0.55 1.29 R Orthopristis chrysoptera (Linnaeus) (Pigfish) 0.14 0.35 1.24 T Paralichthys dentatus (Linnaeus) (Summer Flounder) 3.48 3.56 7.00 T Peprilus triacanthus (Peck) (Butterfish) 0.79 0.21 0.20 T Pogonias chromis (Linnaeus) (Black Drum) 0.14 0.13 0.10 T Pomatomus saltatrix (Linnaeus) (Bluefish) 0.96 0.11 0.16 T Prionotus carolinus (Linnaeus) (Northern Searobin) 0.91 0.8 2.67 T Prionotus evolans (Linnaeus) (Striped Searobin) 0.28 0.23 0.69 T Pseudopleuronectes americanus (Walbaum) (Winter Flounder) 1.01 1.31 2.73 R Scomberomorus maculatus (Mitchell) (Spanish Mackerel) 0.00 0.05 0.00 T Scophthalmus aquosus (Mitchill) (Windowpane) 0.97 0.53 0.64 T Selene vomer (Linnaeus) (Lookdown) 0.14 0.00 0.10 T Sphoeroides maculatus (Bloch and Schneider) (Northern Puffer) 2.57 1.00 3.49 T Sphyraena borealis Dekay (Northern Sennet) 0.14 0.05 0.00 T Stenotomus chrysops (Linnaeus) (Scup) 0.28 0.00 3.00 T Symphurus plagiusa (Linnaeus) (Blackcheek Tonguefish) 0.00 0.00 1.65 R Syngnathus floridae (Jordan and Gilbert) (Dusky Pipefish) 0.42 0.48 0.55 R Syngnathus fuscus Storer (Northern Pipefish) 2.07 1.74 2.39 R Synodus foetens (Linnaeus) (Inshore Lizardfish) 0.00 0.18 1.61 T Tautoga onitis (Linnaeus) (Tautog) 0.00 0.15 0.07 T Trinectes maculatus (Bloch and Schneider) (Hogchoker) 0.34 0.64 0.76 R Urophycis regia (Walbaum) (Spotted Hake) 0.14 0.68 0.44 T 262 Northeastern Naturalist Vol. 16, No. 2 variance (r2 = 0.20) than the 1st (r 2 = 0.32) or 3rd (r 2 = 0.27). For each time period, we plotted the two axes explaining the greatest level of variance in assemblage structure. Stress values for 1996 and 1997, and 1999 suggest that plots were interpretable (Fig. 2), but may be less useful for detailed analysis Figure 2. Results from a n o n - m e t r i c m u l t i d i m e n - sional scaling (NMDS) analysis of fish community data taken monthly from the coastal lagoons of Maryland. Scores for ordination axes that explain the greatest variance in the original community data matrix have been plotted for 1996 and 1997 (by location and by year) and 1999 (by location). Points represent a site near Ocean City Inlet (N) or farther in the estuary (F). Polygons help visualize clusters of N’s and F’s for 1996 and 1997, when clear differences in assemblage structure were more evident. 2009 J.W. Love, P. Chigbu, and E.B. May 263 (McCune and Grace 2002). Accordingly, we limited our interpretations to general patterns of assemblage structure. During the wet year of 1996, assemblages near OCI and further from OCI differed more in composition than during the dry year of 1997 (Fig. 2). The NMDS scores were more distant from one another for 1996 between habitats near OCI and farther from OCI, than they were for 1997. In 1999, assemblage composition also differed less between sites near and farther from OCI, but a well-defined assemblage near OCI did occur. In 1996, sites with highly variable salinity and DO levels generally had the least variable assemblages (Table 3). During the drier year of 1997, but not 1999, sites with highly variable salinity levels also had the least variable assemblages. During 1999, but not 1997, sites with highly variable DO had the least variable assemblages (Table 3). Thus, monthly variation in assemblage composition at a site can be explained by annual differences in climatic variability, and associated spatial gradients of environmental variability in salinity and DO. We determined if transient species were more frequently collected near OCI or farther from OCI, in more environmentally variable habitats. Transient species were more frequently collected near OCI than farther from OCI during 1996 (Table 4), when environmental variability was also lower near OCI than farther from OCI (see Table 1). However, during 1997 and especially 1999, transient species were more frequently collected farther from OCI than in 1996. The ratio of transient to resident species farther from OCI in 1996 was lower (proportionately abundant = 0.4, and exclusively collected = 0.2) than in 1997 (proportionately abundant = 1.0, and exclusively collected = 0.2) or 1999 (proportionately abundant = 1.0, and exclusively collected = 2.5). This result indicates that transient species were more frequently collected and abundant farther in the estuary during moderately dry to dry years, but Table 3. Results from linear regressions between monthly variability (May–October) in salinity and dissolved oxygen (DO) (predictors) and fish assemblage variability (response variable inferred from comparing two axes of the non-metric multidimensional scaling analysis) for three years (1996, 1997, 1999) in the coastal lagoons of Maryland. Enviromental Year variable Axes Slope r2 P-value 1996 Salinity 2 vs. 3 -8.3 0.58 0.045 1 vs. 2 -3.8 0.33 0.177 DO 2 vs. 3 -3.9 0.69 0.022 1 vs. 3 -2.0 0.46 0.093 1997 Salinity 2 vs. 3 -14.2 0.44 0.026 1 vs. 2 -13.5 0.82 0.001 DO 2 vs. 3 2.2 0.04 0.552 1 vs. 2 -1.5 0.04 0.569 1999 Salinity 2 vs. 3 -0.2 0.00 0.950 1 vs. 2 -3.6 0.06 0.290 DO 2 vs. 3 -1.5 0.12 0.110 1 vs. 2 -1.9 0.22 0.030 264 Northeastern Naturalist Vol. 16, No. 2 particularly so during 1999 when salinity levels were slightly higher and varied more similarly among sites than in previous years (see Table 1). Discussion Environmental conditions in estuaries may influence the first year of life of fishes and also alter population structure for some coastal fishes by enhancing year-class strength of younger age classes (Hare and Able 2007). Stream discharge and freshwater input was higher at sites in 1996, and the distributions of many fishes spending their first year of life in estuaries were more restricted to more environmentally stable habitats near OCI. Environmental gradients in the coastal lagoons varied among years, however, and the distributions of fishes likewise changed among years. Thus, the spatial extent of essential fish habitat may differ among years for some species. Distributions of fishes in coastal estuaries have traditionally been explained by spatial gradients, such as those for salinity (Able et al. 2001, Martino and Able 2003), DO (Eby et al. 2005), and habitat (Bell and Westoby 1986, Heck and Orth 1980, Hovel and Lipcius 2001). Here, we suggest that monthly and interannual changes in an environment’s water quality also play an important role in distribution of fishes. In our study, when environmental variability was low, assemblage variability was high, which is different than that expected from ecological theory (Grossman et al. 1982, Oberdoff et al. 2001, Schlosser 1982). High variability in fish assemblages in environmentally variable aquatic habitats is expected because of higher levels of mortality or emigration (Eby et al. 2005, Grossman et al. 1982, Palmer et al. 1997, Schaefer 2001, Schlosser 1982, Taylor and Warren 2001, Taylor et al. 2006). We explain our results by highlighting the dominance of transient species in coastal lagoons, particularly in environmentally stable habitats. Marine transient (or migrant) species are those that spend less of their lifetime in coastal estuaries than residents, and may form assemblages distinct from resident species in coastal estuaries (Koutrakis et al. 2005, Mariani 2001). The distinctness of such assemblages may explain higher levels of species turnover (i.e., beta diversity) at tidal freshwater interfaces in coastal estuaries (Wagner 1999). Transient species may be physiologically Table 4. Numbers of proportionately abundant (>50% of the sample) resident and transient species collected near Ocean City Inlet (<8 km) and farther from Ocean City Inlet (>8 km) in Maryland for 1996, 1997, and 1999. The numbers of resident (Res) and transient (Trans) species exclusively collected in habitats near (N) and farther (F) from Ocean City Inlet were also tallied. We tested the null hypothesis that the number of transient species did not differ between habitats near or farther from Ocean City Inlet using chi-square (χ2) tests of significance (* signifies P < 0.05). Abundant Exclusive Year NRes NTrans FRes FTrans χ2 NRes NTrans FRes FTrans χ2 1996 3 19 9 4 8.9* 2 11 5 1 5.5* 1997 2 15 11 11 4.7* 2 10 6 1 6.0* 1999 3 17 10 10 4.1* 2 7 2 5 0.1 2009 J.W. Love, P. Chigbu, and E.B. May 265 intolerant to fluctuating salinity (i.e., stenohaline marine). Resident species such as Fundulus spp. (killifishes) may persist in environmentally variable habitats because of morphological or physiological adaptations (Kirby-Smith et al. 2003, Kramer 1987, Lewis 1970, Love and Rees 2002, Nordlie 2003), thereby resulting in lower assemblage variability in such habitats. In environmentally stable habitats, diversity may be high (Kushlan 1976), and food webs may be more complex (Paine 1966). If stream discharge lessens over time (Carpenter et al. 1992), diversity may increase in coastal estuaries. However, the impact of lessening stream discharge on signaling immigration of larval fishes, such as American Eel, may be dire, especially if precipitation plays an important role in larval ingress (Sullivan et al. 2006). Climatic conditions may also influence recruitment of fishes to seagrass habitats (Tuckey and Dehaven 2006), which may influence year-class strength by improving foraging opportunities. For a 72-year period, Hare and Able (2007) found that warm winters and concurrent warm estuarine waters were correlated with strong year-class strength for Micropogonias undulatus (Atlantic Croaker). We acknowledge several caveats to our interpretations. First, our characterization of residents and transients, while supported by literature (Able and Fahay 1998, Murdy et al. 1997), may change with continued study on the use of estuaries by marine and estuarine fish species. Secondly, while sites were selected randomly, patterns of transient distributions may have been spatially dependent if environments were spatially autocorrelated. Strong relationships between habitat type and fish assemblages may have accounted for variance not explained in our regression models. Nonetheless, variation in salinity and DO was useful for explaining changes in fish assemblages throughout the lagoons. These environmental variables were not, however, significantly related to both sets of MAP scores produced from NMDS axes. Because different axes resulting from multivariate analyses can represent different aspects of the community, it is not surprising that both sets of MAP scores were not related to environmental variables in the same manner. Another caveat to our study is that we ignored the larger, and geologically more stable, Chincoteague Inlet (CI), which also provides dispersal access to Maryland’s coastal lagoons. Several sampled sites occurred nearer CI than OCI, and transient species that occurred at these sites included Bay Anchovy and Spot. Largely, though, no sites were sampled near CI, making comparisons of fish assemblage structure between this inlet and other sites impossible. Our fourth caveat is related to gear bias. The use of a trawl, while effective for sampling water column and some benthic species, does not sample all species equally well, and did not well-represent intertidal resident fishes or larger, faster transient fishes (e.g., Carcharhinus plumbeus (Nardo) [Sandbar Shark]). Because patterns observed here were largely dependent on the species collected, the importance of environmental variability on a more thoroughly sampled assemblage needs further study. Finally, we acknowledge that our observations are limited to three years of 266 Northeastern Naturalist Vol. 16, No. 2 data. Two of these years may be considered dry years relative to a third year (1996). Thus, while we feel the patterns we have observed are meaningful, their prevalence in the coastal bays watershed and their generality for other coastal systems require additional years of study. Managing coastal ecosystems will require more insight into how climatic variability affects habitat connectivity between coastal lagoons and oceans, and how such relationships affect biomass and trophic interactions within coastal lagoons. These considerations will be useful for improving wellknown, ecosystem-based management practices (Christensen and Walters 2004; Christensen et al. 2002; Pauly et al. 1998, 2002) and modeling responses of populations to pending climatic change. Acknowledgments We gratefully acknowledge the efforts of Dr. Joseph Margraf and Mr. Ward Slacum in collecting and identifying species collected during this project. 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