The Effects of Flow and Stream Characteristics on the Variation in Freshwater Mussel Growth in a Southeast US River Basin

The effects of flow and stream characteristics on the variation in freshwater mussel growth in a Southeast US river basin

Dycus, J. C., Wisniewski, J. M. and Peterson, J. T. (2015). The effects of flow and stream characteristics on the variation in freshwater mussel growth in a Southeast US river basin. Freshwater Biology, 60, 395-409. doi:10.1111/fwb.12504

10.1111/fwb.12504 John Wiley & Sons Ltd.

Version of Record http://cdss.library.oregonstate.edu/sa-termsofuse Freshwater Biology (2014) doi:10.1111/fwb.12504

The effects of ﬂow and stream characteristics on the variation in freshwater mussel growth in a Southeast US river basin

† ‡ JUSTIN C. DYCUS*,1, JASON M. WISNIEWSKI AND JAMES T. PETERSON *Warnell School of Forestry and Natural Resources, University of Georgia, Athens, GA, U.S.A. † Georgia Department of Natural Resources, Wildlife Resources Division, Nongame Conservation Section, Social Circle, GA, U.S.A. ‡ U.S. Geological Survey, Georgia Cooperative Fish and Wildlife Research Unit, Warnell School of Forestry and Natural Resources, University of Georgia, Athens, GA, U.S.A.

SUMMARY

1. The evaluation of the age and growth of animal populations is essential for understanding and predicting how populations will respond to changes in environmental conditions and anthropogenic stressors. 2. We used a novel, von Bertalanffy hierarchical modelling approach to quantify relationships between the growth of three freshwater mussel species and various site- and watershed-level factors including seasonal discharge, land cover and stream size in the lower Flint River Basin, Georgia, U.S.A. 3. Our modelling approach quantified the mussel-to-mussel variation in the von Bertalanffy parameters and accounted for biases associated with multiple measurements made on each mussel specimen, which are generally not accounted for as sources of bias in age and growth studies. 4. Modelling results suggested that maximum shell size parameter and the Brody growth coefficient varied across species, on average, 19 and 33%, respectively, among individual mussels within sample sites. The variation was related to short-term high streamflows during the spring season, stream size, channel geomorphology and land cover in the watershed. 5. This study provides insight to the factors affecting the growth of stream-dwelling freshwater mussels. Although hierarchical von Bertalanffy growth models are rarely used for freshwater mussel age and growth studies, this approach can provide important information regarding the ecology of freshwater mussels.

Keywords: annuli, hierarchical model, thin section

Although rarely assessed in freshwater mussel (Unioni- Introduction formes) studies, similar approaches to using age and Age and growth determination is an essential compo- growth metrics may be useful for identifying factors and nent of effectively managing animal populations. This is mechanisms affecting these highly imperilled species. best exemplified in fisheries management, in which age Various methods have been used to determine age and growth data are frequently used to investigate the and growth of freshwater mussels including examina- influence of various environmental factors on fish popu- tion of external annuli counts (Negus, 1966; Hanson, lation dynamics. For instance, fish growth reportedly Mackay & Prepas, 1988), repeated measurements from varies in response to stream discharge (Paragamian & mark–recapture studies (Anthony et al., 2001; Tang, Jiao Wiley, 1987) and other physical habitat characteristics, & Jones, 2013) and examination of internal annuli counts such as substrate or structure (Quist & Guy, 2001). through thin sectioning (Neves & Moyer, 1988; Haag &

Correspondence: James T. Peterson, U.S. Geological Survey, Oregon Cooperative Fish and Wildlife Research Unit, 104 Nash Hall, Oregon State University, Corvallis, OR 97331-3803, U.S.A. E-mail: [email protected] 1Present address: North Carolina Wildlife Resources Commission, 8370 Broadway Road, Sanford, NC 27332, U.S.A.

© 2014 John Wiley & Sons Ltd 1 2 J. C. Dycus et al. Commens-Carson, 2008; Rypel, Haag & Findlay, 2008; understanding of the response of mussel populations to Black et al., 2010; Haag & Rypel, 2011). Comparisons of these disturbances may greatly aid the development of counts of external annuli versus internal annuli indi- successful conservation strategies for these species. There- cated that age often was underestimated when using fore, we evaluated factors affecting the growth rate and external annuli counts, particularly in older individuals maximum size of three freshwater mussel species in the (Neves & Moyer, 1988). Further, Haag (2009) suggested lower Flint River Basin. We first validated internal shell that inferences drawn from repeated measurements dur- annuli production and developed hierarchical von Berta- ing mark–recapture studies regarding age and growth of lanffy growth models to estimate the variation of growth freshwater mussels are inaccurate due to handling parameters among individual mussels. We then modelled effects that reduced growth, thus systematically overesti- variation in growth parameters as functions of individual mating age and underestimating growth. Therefore, and environmental covariates that included species, flow internal annuli counts using mussel shell thin sections regime components, stream size, stream channel mor- appear to provide a more accurate approach to ageing phology and watershed land use. and measuring growth of these species. However, due to the sensitivity of freshwater mussels to disturbances, validation of internal shell annuli should be included in Methods mussel age and growth studies utilising internal annuli Study area counts (Haag & Commens-Carson, 2008). Freshwater mussels are generally considered long- We studied the age and growth of freshwater mussels in lived, slow-growing animals (Bauer, 1992; Ziuganov the lower Flint River Basin (LFRB) in southwest Georgia et al., 2000) based on limited information from few spe- (Fig. 1). The LFRB contains the Fall Line Hills and cies throughout a relatively narrow distribution. How- Dougherty Plain districts of the Coastal Plain physio- ever, studies suggest that growth and longevity of these graphic province. Streams located within the Fall Line animals varies with species (Haag & Commens-Carson, Hills receive most of their water contribution from sur- 2008; Haag & Rypel, 2011), sex (Haag & Rypel, 2011), face water runoff and are characterised by sandy-mud population (Bauer, 1992; Haag & Rypel, 2011), climatic substrate with elevated turbidity levels. Streams within conditions (Black et al., 2010) and streamflow (Black the Dougherty Plain receive substantial amounts of et al., 2010). Therefore, examination of age and growth water input from the underlying Floridan aquifer and chronologies of freshwater mussels may provide valu- have greater amounts of coarse substrates and low tur- able insight into the relative influence of environmental bidity (Mosner, 2002; Peterson et al., 2009). We grouped factors affecting these species because variation in annu- streams within the LFRB into strata based on stream lus width may reflect responses of individual mussels to size, physiographic province and the abundance of the environmental conditions during the growing season three focal species (defined below) determined during (Rypel et al., 2008; Black et al., 2010). previous research (Shea, 2011). To minimise the effects The effects of natural and anthropogenic disturbances of mussel sampling on local populations, we randomly on freshwater mussel growth are largely unstudied. How- selected a minimum of four sample sites within each ever, the range of threats to freshwater mussels posed by stratum that contained relatively large numbers of the climatic and anthropogenic disturbances are typified in three focal species, resulting in 20 sample sites (Fig. 1). the Flint River Basin, Georgia. The upper portion of the basin is extensively altered by urbanisation, whereas Focal species lower portions of the basin are largely dominated by heavily irrigated row-crop agriculture, which has sub- We studied age and growth of three mussel species: Vill- stantially altered stream flows (McDowell, 2006; Rugel osa vibex (Southern Rainbow), Villosa lienosa (Little Spec- et al., 2012). The basin was historically occupied by 33 taclecase) and Elliptio crassidens (Elephantear) because freshwater mussel species with 29 species believed extant their populations were relatively stable and locally abun- (Brim Box & Williams, 2000; Shea et al., 2013; Wisniewski dant throughout the LFRB, and they each were relatively et al., 2014). Previous studies in the Flint River Basin iden- easy to identify (Williams, Bogan & Garner, 2008; Shea tified several mechanisms influencing the decline of et al., 2011). Villosa vibex and V. lienosa are thin-shelled mussel populations including severe drought, agricul- mussel species that occupy a variety of stream sizes tural water use and impoundment (Golladay et al., 2004; from small creeks to large rivers and occur in sand and Peterson et al., 2011; Shea et al., 2013). However, further gravel substrates (Williams et al., 2008; Wisniewski et al.,

SC GA

Fig. 1 Regional map (left) and locations of 20 study sites sampled in the lower Flint River Basin, Georgia. Triangles represent the location of the eight U.S. FL Geological Survey gages used to model site-speciﬁc seasonal discharges. Open circles represent the location of 11 sites within the Fall Line Hills and ﬁlled circles represent the location of 9 sites within the Dougherty Plain.

2014). Both species are long-term brooders that are Field crews sampled sites with no notched specimens gravid from late summer or autumn until the following between November 2009 and August 2010. Sites contain- summer (Williams et al., 2008). Elliptio crassidens is a ing notched specimens were sampled between June and thick-shelled species found primarily in large streams August 2010. Crews sampled each site for c. 1 h and with substrates composed of sand, gravel and cobble then examined collected specimens. In sites where mus- (Williams et al., 2008; Wisniewski et al., 2014). Elliptio sel populations appeared abundant, crews collected 20– crassidens is a short-term brooder, brooding from April 30 individuals of each focal species that represented all until August, depending on geographic location (Wil- size classes detected. In sites where insufficient numbers liams et al., 2008). of focal species were collected, the crews conducted additional sampling to increase the number of focal species specimens. If the focal species’ population numbers Mussel sampling and ageing appeared to be very low in a sample site (i.e. <10 mus- To confirm that presumed annuli corresponded to sels collected), mussel specimens were returned to the annual growth checks in LFRB mussels, we collected stream to prevent further population decline. All col- individual mussels of two focal species V. lienosa and lected mussels were identified to species by field person- V. vibex during June and July 2009 and notched each nel and measured (i.e. length, width, height) to the along the ventral margin directly below the umbo using nearest millimetre with dial calipers. We recorded tag the triangular edge of a file to a depth of 1–2 mm. We numbers of recaptured mussels tagged during a previ- tagged all notched mussels with 8 mm 9 4 mm oval ous study (Shea, 2011) and used these mussels to assess Hallprint shellfish tags (Hallprint Pty Ltd, Victor Har- the potential effects of handling and tagging on growth bor, SA, Australia), hand placed them in the stream sub- (see Definitions and analysis, below). We euthanised strate and did not disturb them for a minimum of specimens by separating the valves at the hingeline, 1 year. Tagged and recaptured mussels provided known assigned a unique identifier to the matching valves and age and growth since first capture, while notching dem- placed specimens with labels in individual plastic bags. onstrated visual signs of both external and internal We thin sectioned the right valve of each mussel using growth. Recapture of previously notched individuals a Buehler Isomet low speed saw (Buehler Ltd., Evans- provided visual evidence of external annual growth, and ton, IL, U.S.A.), with a Series 15HC diamond impreg- production of an internal annulus was evident after nated blade (Buehler Ltd.). Each thin section was examining thin sections that included the notch. sanded and polished using a five step polishing process

© 2014 John Wiley & Sons Ltd, Freshwater Biology, doi: 10.1111/fwb.12504 4 J. C. Dycus et al. detailed in Dycus (2011). Mounted thin sections were simultaneously by all three observers (Dycus, 2011). photographed using a Leica MZ6 modular stereomicro- During the concert read, consensus annuli were identi- scope with 6.3 : 1 zoom lens equipped with a Leica fied and marked on the thin-section images, and mussel DFC295 (Leica Microsystems Inc., Buffalo Grove Illinois, ages were estimated as the total number of consensus USA) digital microscope colour camera. Thin-section annuli. Specimens were removed from the study if images were captured at 0.639 magnification and analy- observers failed to reach consensus on annuli location. sed using Image-Pro Plus (version 7.0; Media Cybernet- During the concert read, observers collectively identified ics, Inc., Bethesda, MD, U.S.A.). Mussel thin sections too and marked reference points used to measure annual large for capture in a single image were captured using height-at-age for each thin section. The reference point Image Pro’s tiling procedure that consisted of taking a was placed at the highest arch of the umbo (Fig. 2) and series of photographs along a common axis and combin- corresponded to the maximum umbo to ventral margin ing them into a single image based on spatially autocor- distance (i.e. mussel shell height) measured using dial related similarities (R. Bunn, Vashaw Scientific Inc., calipers. The amount of shell erosion from the umbo to pers. comm.). the ventral margin was visually estimated by consensus Personnel estimated mussel age by identifying and as the percentage of external shell of each thin section counting the number of annuli present in each thin-sec- eroded (Fig. 2). Shell height-at-age was estimated by tion image using a multiple-observer method. Before measuring the distance from the reference point to each mussels were aged, all three observers were trained to annulus on the ventral margin (Fig. 2) to the nearest identify internal annuli by two mussel-ageing experts. 0.00001 mm. To ensure accurate measurements, Image- True annuli were those that originated at the umbo of Pro was calibrated using a DR-867 2-mm stage microme- the thin section and were traceable to the margin of the ter (Klarmann Ruling, Inc., Litchfield, NH, U.S.A.). shell (Neves & Moyer, 1988; Haag & Commens-Carson, 2008). True annuli often were accompanied by a corre- Verification of annuli sponding halo that surrounded the annulus as it joined the periostracum of the thin section which assisted clas- Previously notched V. lienosa and V. vibex aided in dis- sification of annuli exhibiting faint lines (Haag & Com- tinctions between true and pseudo-annulus production. mens-Carson, 2008; Rypel et al., 2008). Verification of annulus production required observers to We initially used an independent, multiple-observer agree that notched thin sections only had one true annu- method to evaluate the relative precision of annuli-based lus post-notching. Notched thin-section photographs age estimates and found that initial observer agreement were mixed with non-notched thin sections and ran- on mussel age was >50% for each focal species (Dycus, domly placed in the ageing sets. The independent 2011). During the initial assessment, the average differ- observers then aged all individuals. During the concert ences in estimated ages among observers were relatively read, notched thin sections were identified and annuli low (i.e. <20% of final age). The final annuli used to esti- placement was compared relative to the notch. We con- mate mussel age and growth were determined during a sidered annuli production validated for a specimen if all concert read in which thin-section images were viewed three observers marked an annulus in the same location

Fig. 2 Thin section of an estimated 5- year-old Villosa lienosa collected from Kinchafoonee Creek showing the (a) shell wear present on the thin section estimated to be 20%, (b) the reference point used to measure annual growth and the (c) marks for each of the ﬁve annuli on the ventral margin of the shell. Measure- ment of height-at-age from the reference point to an annulus is shown with a broken line.

© 2014 John Wiley & Sons Ltd, Freshwater Biology, doi: 10.1111/fwb.12504 Factors affecting mussel growth 5 post-notching for a specimen. If observers marked in the winter months with little or no growth (Haag & multiple annuli or one annulus in multiple locations Commens-Carson, 2008; Rypel et al., 2008; Versteegh post-notching, observers discussed the discrepancy and et al., 2010), and our annulus validation (discussed attempted to reach a consensus. Annuli production of a below) indicated that winter was the period of slow specimen lacked validation when observers failed to growth and annuli deposition. All flow regime compo- reach a consensus or agreement on a single annulus nents were standardised by the contributing upstream post-notching. We assumed focal species had valid ann- watershed area of each site to allow comparisons of the uli production when more than 50% of notched speci- effects of stream flows across different sized streams. mens had validated annulus production and none (zero) We used predicted probability distributions for the had multiple annuli post-notching. model-estimated flow regime components (i.e. rather than single values) assuming a gamma distribution to incorporate prediction error. Definitions and analysis We characterised each sample site based on physio- We used average daily discharge data at each study graphic province (i.e. Dougherty Plain or Fall Line site to identify flow regime components having the Hills), stream size (link magnitude, following Shreve, greatest influence on mussel growth. We downloaded 1966), gross channel morphology (confined or an uncon- daily discharge data for sample sites that were located fined channel, following Peterson et al., 2009) and land immediately up or downstream (<5 km) of a U.S. Geo- cover. We classified land cover as urban, agricultural logical Survey stream gage (USGS, 2011). We estimated and other by combining classes in the 2001 National discharge for ungaged streams using published dis- Land Cover Dataset (USGS, 2001). Urban land cover was charge models (McCargo & Peterson, 2010) and used a combination of developed open space, and developed linear regression (Sokal & Rohlf, 1995) to develop site- low, medium and high intensity urban space. Agricul- specific models relating measured discharge at ungaged ture land cover was a combination of grasslands/herba- sites to average daily discharge data where models ceous, pasture/hay and cultivated crops classes. The were not available. Here, we used data from eight other category consisted of the remaining classes. Per- long-term USGS gaging stations in the LFRB (Fig. 1). centage land cover represented the percentage of urban The best approximating model for each study site was and agricultural land cover in the contributing that with the largest coefficient of determination (r2). watershed upstream of a site. We diagnosed linear regression residuals to ensure that We modelled growth rate of individual mussels using regression assumptions regarding normality and homo- the von Bertalanffy (1938) equation: geneity of variance were met for each model and log- Kðt t Þ l ¼ l1½1 e 0 transformed discharge measurements when necessary. t

Seasonal stream flow statistics were then calculated where lt is the shell height at age t, l∞ is the asymptotic using daily discharge estimated for ungaged study sites or maximum shell height, and K is the Brody growth for the entire record of mussel growth. coefficient. We assumed that shell height at birth (t0) A primary objective of our study was to evaluate the was zero. Traditionally, the parameters l∞ and K are esti- relative influence of streamflows on freshwater mussel mated by rearranging the formula and regressing lt +1 growth. Previous studies suggest that the influence of versus lt or using nonlinear estimation procedures (Hil- flow regime components on physical and ecological pro- born & Walters, 1992). These approaches, however, gen- cesses varies seasonally (Craven et al., 2010; McCargo & erally assume no individual variability, which can result Peterson, 2010; Peterson et al., 2011). Thus, we character- in biased estimates and standard errors (Hart & Chute, ised the flow regime for each season using three compo- 2009). To incorporate individual variation, we modelled nents: short-term low flows (10-day minimum l∞ and K hierarchically as: discharge); short-term high flows (10-day maximum dis- l1; i ¼ b þ u1; i charge); and long-term average flow conditions (median discharge for each season of recorded mussel growth). Ki ¼ c þ uK; i We only considered the effect of streamflows during growing seasons defined as spring (March–June) and where b and c are the mean asymptotic/maximum shell summer (July–October) following Peterson et al. (2011). height (henceforth, maximum shell size) and mean Bro- Remaining months were excluded because previous dy growth coefficient (henceforth, growth coefficient), studies report that freshwater mussels become dormant respectively, and associated random effects (u) that were

© 2014 John Wiley & Sons Ltd, Freshwater Biology, doi: 10.1111/fwb.12504 6 J. C. Dycus et al. assumed to be normally distributed among individual day high discharge or no discharge (i.e. model did not s s mussels (i) with a mean of zero and variance ∞ and K, contain discharge) and systematically excluded stream respectively. We also added a residual term (e) to the reach characteristics (e.g. channel conﬁnement) and von Bertalanffy (1938) equation: anthropogenic land use to identify those that were useful

K in explaining variability in growth. We also fit maximum l ; ¼ l1; ½1 e i þe ; t i i t i shell size models by systematically excluding stream that was assumed normally distributed with a mean of reach characteristics (e.g. channel confinement) and zero and variance r2. We initially fit the model to each anthropogenic land use. Species, tagging and percentage species individually to estimate the predictable variation shell wear were included in every candidate model in l∞ and K among individuals. We then evaluated the because these predictors were previously documented to influence of seasonal flow regime components and site- affect estimates of freshwater mussel growth (Haag & specific stream characteristics on l∞ and K by modelling Commens-Carson, 2008; Rypel et al., 2008) and were not each as a linear function of predictor variables in a sin- the primary focus of our study. Two-way interactions gle model. All models were fit using Markov Chain were only included in models that contained the main Monte Carlo (MCMC) as implemented in BUGS soft- effects. For example, a two-way interaction between link ware, version 1.4 (Lunn et al., 2000) with 650 000 itera- magnitude and a flow component was only included tions, 20 000 burn in, thinning at 25 and diffuse priors. when the candidate model contained both variables. The These values were determined by fitting the global (all relative fit of models with and without quadratic terms parameters) model with 100 000 iterations and evaluat- for each flow regime component were evaluated prior to ing the output with the Raftery & Lewis (1995) diagnos- model selection using the global model for each flow tic as implemented in the R package Coda (Plummer regime component. We also evaluated the relative fit of et al., 2006). The BUGS code used for this analysis can models that did and did not include a covariance s s be obtained from the corresponding author. between the random components, ∞ and K and that Prior to constructing candidate models, we calculated modelled that variance as differing or equal among spe- Pearson correlation coefficients for all pairs of potential cies using the global model for each flow regime compo- predictor variables. To avoid multicollinearity, we only nent. The same best approximating variance structure included uncorrelated predictor variables (r2 < 0.45) was used for all model selection. together in candidate models. We also created binary To assess the fit of each candidate model, we calcu- indicator variables (i.e. 0 or 1) for the following categori- lated Deviance Information Criterion (DIC; Spiegelhalter cal variables: species, with V. vibex coded as 1 when the et al., 2002), with the best approximating model having species was V. vibex and 0 otherwise and E. crassidens the lowest DIC. The relative plausibility of each candi- coded as 1 when the species was E. crassidens and 0 date model was assessed by calculating model weights otherwise (i.e. V. lienosa served as the statistical baseline w using the DIC values (Link & Barker, 2010). These species); channel confinement, with unconfined channels weights can range from 0 to 1, with the most plausible coded as 1 and 0 otherwise; tagged and notched speci- candidate model having the highest weight. The ratio of mens, coded as 1 for year following tagging and notch- model weights for two candidate models can be used to ing and 0 otherwise; and physiographic province, with assess the degree of evidence for one model over Dougherty Plain sites coded as 1 and 0 otherwise. another (Anderson, Burnham & Thompson, 2000). We used an information-theoretic approach, described Therefore, we created a confidence set of models that by Burnham & Anderson (2002), to evaluate the relative included only those candidate models with model plausibility of models relating seasonal streamflows, site- weights that were within 10% of the largest weight, specific stream characteristics and species characteristics which is similar to the general rule of thumb (i.e. 1/8 or to the annual growth of the three focal mussel species. 12%) suggested by Royall (1997) for evaluating strength Our primary hypotheses of interest were to evaluate the of evidence. We estimated the precision of each fixed relative influence of streamflow regime components on and random effect by computing 95% credibility inter- the growth coefficient (K). Secondarily, we sought to vals (Congdon, 2001), which are analogous to 95% confi- determine the influence of stream characteristics and dence intervals. Credibility intervals that contained 0 anthropogenic land use on mussel growth coefficient and indicated inconclusive results because we could not maximum shell size (l∞). Thus, we contrasted four sets of determine the nature of the relationship (i.e. whether growth coefficient models that included either 10-day positive or negative). Goodness-of-fit was assessed for seasonal low discharge, median seasonal discharge, 10-

© 2014 John Wiley & Sons Ltd, Freshwater Biology, doi: 10.1111/fwb.12504 Factors affecting mussel growth 7 the global model for each flow component using a sim- whereas four notched mussels (i.e. 19% of total) had lit- ple discrepancy measure (Gelman, Meng & Stern, 1996). tle growth post-notching, presumably because they were older than other notched individuals. All observers agreed that 14 notched V. lienosa and V. vibex displayed Results a disturbance ring (i.e. response to notching) at the bot- Fifty-three of the 830 total thin-sectioned mussels were tom of the notch followed by one true annulus post- omitted from the data set due to excessive erosion or notching (Fig. 3). No thin section had multiple annuli failure to reach age consensus. The remaining 777 mus- post-notching. sel thin sections were included in the analysis, although Of the focal species, E. crassidens had the oldest and not all species were collected at all 20 sites. In total, field largest individuals in the study that averaged 15 years crews collected 402 V. lienosa, 282 V. vibex and 93 old and 45 mm height, respectively. Twelve per cent of E. crassidens at 18, 17 and 3 sites, respectively. Elliptio E. crassidens were estimated as older than 25 years, and crassidens was only found at the two mainstem Flint the oldest specimen collected was estimated at 46 years. River sites and at one site in Chickasawhatchee Creek. Villosa lienosa and V. vibex were younger and smaller Villosa lienosa, V. vibex and E. crassidens represented 52, than E. crassidens with average ages of six and seven, 36 and 12% of the total number of mussels analysed, respectively. Shell heights for these species averaged 27 respectively. Fifty-six specimens were previously tagged, and 30 mm, respectively. and 16 V. lienosa and 5 V. vibex were tagged and notched for annuli validation and age verification. Site-specific stream characteristics

Five sample sites were located near a USGS gage and Annuli validation published models were available for estimating dis- Annulus production was present in 67% of notched Vill- charge at seven sites (Table 1). Discharge models created osa species. Thin-section photographs of three notched to estimate discharge at the remaining eight ungaged mussels (i.e. 14% of total) failed to capture the notch, sites ﬁt well (r2 > 0.95). Seasonal discharges in the LFRB

(a)

(b) 1 3

2 Fig. 3 Thin-section photographs of a notched (a) Villosa vibex and (b) Villosa lienosa with (1) the notch created by the rectangular ﬁle, (2) the disturbance ring in response to notching and (3) the ﬁrst true annulus post-notching.

© 2014 John Wiley & Sons Ltd, Freshwater Biology, doi: 10.1111/fwb.12504 8 J. C. Dycus et al. varied substantially during the lifespan of mussels used growth among individuals and sites. On average, maxi- in this study. During an average 6 year lifespan of mum shell size (l∞) variedpffiffiffiffiffiffiffiffiffi among individual mussels V. lienosa and V. vibex, the flows experienced by mussels from a low of 13% ( 38:1=47:1) for E. crassidens to a included above average flows during 3 years (2005, high of 23% for V. vibex (Table 2). Mussel growth coef- 2009–2010) and below average flows during 3 years ficients (K) were similarly variable among individuals (2006–2008; Fig. 4). Stream discharges at sampled sites and sites and ranged from a low of 24% for V. lienosa also included observed flow cessation (zero discharge) to a high of 45% for E. crassidens. The best approximat- events. ing model for predicting the mussel growth parameters explained, on average, 75% of the variation in maximum shell size and 32% of the variation in the growth Mussel growth models coefficient. The best approximating von Bertalanffy The hierarchical von Bertalanffy growth models fit with growth models included: maximum shell size modelled no predictor variables indicated substantial variation in as a function of species, link magnitude, unconfined stream channel and link magnitude by species interaction; and the growth coefficient modelled as a function Table 1 A summary of flow regime components and the characteristics of the 20 study sites that were used to model the growth of of species, tagging, percentage shell erosion, link mag- mussels in the lower Flint River Basin, Georgia nitude, urban and agriculture land cover, spring 10-day high discharge and associated quadratic term and Flow regime component Mean (SD) Minimum Maximum spring 10-day high discharge by link magnitude inter- Spring action (Table 3). Model weights (w) indicated that the Long-term average 0.010 (0.014) 0 0.12 best approximating model was 8.6 times more likely discharge 10-day low discharge 0.007 (0.007) 0 0.04 than the second-best approximating model, which con- 10-day high discharge 0.071 (0.112) 0.01 0.98 tained the same predictor variables with agriculture Summer land cover replacing unconfined channel morphology Long-term average 0.007 (0.007) 0 0.04 in the maximum shell size model. The three best discharge 10-day low discharge 0.004 (0.004) 0 0.02 approximating models represented our confidence set 10-day high discharge 0.039 (0.113) 0 1.84 of models (Table 3). Site characteristics Maximum shell size (i.e. shell height) differed among ² Watershed area (km ) 1228 (2567.3) 39 7989 species and was related to stream size and stream chan- Link magnitude 964.1 (2385.43) 11 8104 nel confinement. Maximum shell size was greatest for Percentage agriculture 36.9 (17.01) 3 58 land cover E. crassidens and least for V. lienosa, with the difference Percentage urban 8.5 (11.68) 2 45 in maximum shell size between the two species averag- land cover ing 18.4 mm (Table 4). Maximum shell size was posi- Site-specific flow regime components were standardised (divided) tively but weakly related to stream size for both by watershed area. E. crassidens and V. vibex, but not V. lienosa (Fig. 5).

Fig. 4 Estimated discharge for Ichaway- nochaway Creek, Georgia, at U.S. Geo- logical Survey gage number 02353500 for 1995 through 2011 (grey line) in comparison to mean estimated discharge based on 106 year of data (black line).

Table 2 Estimates of the mean and standard deviation (in paren- effect of flows decreased with stream size (Table 4). The thesis) of von Bertalanffy growth parameters without covariates for mussel growth parameter also was related to stream the three mussel species collected in the Flint River Basin, GA characteristics and land use in the watershed. Parameter l∞ K estimates indicated that mussel growth was positively associated with the amount of agricultural land cover Species Mean s Mean s and urban land cover within corresponding watersheds. Villosa 23.4 (0.158) 21.3 (1.00) 0.722 (0.012) 0.031 (0.0018) Of these factors, agricultural land cover appeared to lienosa have the greatest effect on mussel growth (Fig. 6). Villosa 26.6 (0.398) 38.9 (3.50) 0.749 (0.017) 0.051 (0.0032) vibex Elliptio 47.1 (0.679) 38.1 (1.76) 0.335 (0.011) 0.022 (0.00147) crassidens Discussion s is an estimate of the predictable variability of the parameter Growth chronologies recorded in freshwater mussel among individuals and sites. shells can provide valuable insight into biotic and abi- otic factors influencing these highly imperilled organ- isms. Despite their widely recognised conservation Parameter estimates also indicated that maximum shell status, comprehensive mussel age and growth analyses size was, on average, 2.6 mm smaller in streams with are largely unpublished and have only recently gained unconfined channels for all species (Table 4). attention in North American freshwater mussel research The growth of freshwater mussels, as indexed by the (Haag & Commens-Carson, 2008; Rypel et al., 2008; growth coefficient (K), differed among species. Parame- Haag, 2009; Rypel, Haag & Findlay, 2009; Black et al., ter estimates indicated that the growth coefficient of 2010; Haag & Rypel, 2011; Tang et al., 2013; Daniel & E. crassidens was substantially smaller than V. vibex and Brown, 2014). Nonetheless, validation of annulus forma- V. lienosa, respectively (Table 4). However, parameter tion during such studies is necessary to ensure accurate estimates for V. vibex were small and imprecise in all and meaningful results (Beamish & McFarlane, 1983). models in the confidence set suggesting that, on average, Shell notching of the ventral margin is among the most the growth of V. vibex was not biologically different than convenient and reliable annuli validation methods for V. lienosa (Fig. 5). Parameter estimates for tagging effect freshwater mussel field studies (Neves & Moyer, 1988) and percentage shell wear were small and relatively and was therefore our method of choice. We validated imprecise (Table 4). the formation of a single annulus post-notching in 67% The mussel growth parameter was strongly and posi- of notched V. lienosa and V. vibex, which falls between tively related to spring 10-day high discharge (Table 3). the 27% rate reported by Neves & Moyer (1988) and However, the flow component quadratic terms revealed 92% by Haag & Commens-Carson (2008). The lack of that growth decreased as the magnitude of these flows multiple annuli post-notching in any thin section also increased, suggesting a nonlinear relationship between verified annuli formation and assisted observers in dis- streamflow and growth (Fig. 6). Similarly, the interaction tinguishing between true and pseudo-annuli. Annulus between flow and link magnitude suggested that the production was most evident in young individuals that

Table 3 Parameters, effective number of parameters (pD), DIC, DDIC and weights (w) for conﬁdence set of mussel maximum shell size (l∞) and growth coefﬁcient (K)

Candidate model pD DIC DDIC w l∞(Elliptio crassidens, Villosa vibex, Link magnitude, Unconﬁned, Link magnitude*E. crassidens, 1101.74 23564.9 0 0.868 Link magnitude*V. vibex), K (E. crassidens, V. vibex, Tagging, Percentage shell wear, Link magnitude, Percentage Urban, Percentage Agriculture, Spring 10-day high discharge, Spring 10-day high discharge 2, Spring 10-day high discharge*link magnitude) l∞ (E. crassidens, V. vibex, Link magnitude, Percentage agriculture, Link magnitude*E. crassidens, 1101.48 23569.2 4.3 0.101 Link magnitude*V. vibex), K (E. crassidens, V. vibex, Tagging, Percentage shell wear, Link magnitude, Percentage Urban, Percentage Agriculture, Spring 10-day high discharge, Spring 10-day high discharge2, Spring 10-day high discharge*link magnitude) l∞(E. crassidens, V. vibex, Link magnitude, Unconﬁned, E. crassidens*Link magnitude, 1101.26 23571.6 6.7 0.030 V. vibex*Link magnitude), K (E. crassidens, V. vibex, Tagged, Shell wear, Link magnitude, Percentage Urban, Percentage Agriculture, Spring 10-day low discharge, Spring 10-day low discharge2)

Table 4 Parameter estimates, standard deviation (SD) and 95% credible intervals of ﬁxed and random effects for best approximating model of the growth of three species of freshwater mussels in the lower Flint River Basin, Georgia

Parameter Estimate SD Lower Upper

Maximum shell size (l∞) Intercept 24.4700 0.2845 23.9100 25.0300 Elliptio crassidens 18.4300 1.3940 15.6700 21.1300 Villosa vibex 2.7610 0.3851 2.0080 3.5170 Link magnitude 1.45E-04 1.35E-04 4.09E-04 1.21E-04 Unconfined 2.5700 0.3747 3.3050 1.8380 Link magnitude 0.0007 0.0002 0.0002 0.0011 9E. crassidens Link magnitude 0.0011 0.0002 0.0006 0.0016 9V. vibex Random effect* 4.2640 0.1257 4.0260 4.5180 Growth coefficient (K) Intercept 0.4901 0.0238 0.4453 0.5391 E. crassidens 0.4422 0.0381 0.5182 0.3766 V. vibex 0.0003 0.0171 0.0344 0.0331 Tagging 0.0471 0.0410 0.0320 0.1281 Percentage 0.0812 0.0575 0.0334 0.1933 shell wear Link magnitude 9.39E-08 5.05E-06 9.40E-06 9.83E-06 Percentage Urban 0.0045 0.0005 0.0034 0.0055 Percentage 0.0053 0.0008 0.0038 0.0068 Agriculture Fig. 5 The estimated relation between stream link magnitude and Spring 10-day 0.1927 0.0521 0.0948 0.2982 maximum shell size (l∞) and the growth coefficient (K) for three high discharge freshwater mussel species in lower Flint River Basin, Georgia. Esti- Spring 10-day 0.2624 0.0630 0.3872 0.1406 mates were calculated with the best approximating model and high discharge2 assuming untagged mussels, an unconfined stream channel, and Spring 10-day high 2.00E-05 6.17E-06 3.23E-05 8.22E-06 average values for link magnitude and land cover observed during discharge9link the study. magnitude Random effect 0.1440 0.0074 0.1299 0.1588 American mussel species (Haag & Rypel, 2011) in that Residual error 1.6870 0.0183 1.6520 1.7230 E. crassidens attained greater size and age, but exhibited Species-specific estimates are interpreted relative to the baseline slower growth than V. lienosa and V. vibex which species, Villosa lienosa. exhibited similar growth rates and lower maximum ages. *Random effects and residual error are expressed as standard devi- ations. We estimate that it takes, on average, 4 years for Villosa species to reach 95% of their maximum size and 8 years had high annual growth. Previous mussel age and for E. crassidens, which is likely indicative of different growth studies attributed inabilities to distinguish annu- life-history strategies of these species. Villosa lienosa and li post-notching to minimal annual growth (Neves & V. vibex are long-term brooders that mature early and use Moyer, 1988; Haag & Commens-Carson, 2008; Rypel ubiquitous Centrarchid species as hosts (Keller & Ruess- et al., 2008). The lack of validated annuli production in ler, 1997; Haag 2012). In contrast, E. crassidens is a short- 33% of notched thin sections in our study was likely term brooder that presumably parasitises the genus Alosa due to our inability to distinguish annuli in slower (Howard, 1914), a group of fishes that is frequently char- growing and larger notched specimens. This, combined acterised by variable year class strength. Hence, Villosa with the observed annuli production in 67% of notched species have greater opportunities for successful repro- specimens, suggests that freshwater mussels in our duction over a short life, whereas E. crassidens may study consistently produced annuli. Therefore, we require more reproductive seasons as a compensatory believe that thin sectioning was an appropriate and response to annual variability in environmental condi- effective method for determining the age and annual tions and host fish populations. growth of freshwater mussels in the LFRB. The majority of recent bivalve age and growth studies Differences in growth and maximum size among spe- assume that maximum shell size and growth coefficients cies in our study are consistent with that of other North are constant among individuals within a population

© 2014 John Wiley & Sons Ltd, Freshwater Biology, doi: 10.1111/fwb.12504 Factors affecting mussel growth 11 (Hart & Chute, 2009; Tang et al., 2013). However, Haag & Rypel (2011) and Haag (2012) reported variation in growth between sexes within populations of several mussel species in the Sipsey River, Alabama. Using the hierarchical Bertalanffy growth models, we found that mussel growth coefficients and maximum shell sizes varied substantially among individuals within and among populations (i.e. study sites). We also found that some of the variation was related to differences among species, site-specific characteristics and stream flows. However, significant variation in the growth coefficient and maximum shell size remained after accounting for these factors. To our knowledge, this study is among the first to explicitly model variation in these parameters making it difficult to assess whether the variation is typical of stream-dwelling mussels. The variation in these two parameters represents predictable differences among study sites and mussels that were unaccounted for by the predictors in the best approximating models. Given the relatively large number of study site characteristics examined, we believe that much of this variation reflects differences among individual mussels due to behavioural or physiological differences. Sex may also explain some differences in maximum size and growth among mussels within a site (Haag & Rypel, 2011), but we did not include sex as a predictor because only V. lienosa exhibited consistently recognisable sexual dimorphism among our study species. Regardless of the source of the variation, our study suggests that variation in growth among mussels is relatively large and needs to be explicitly incorporated into evaluations of mussel growth. Failure to do so can lead to biased model estimates, standard errors and estimates of model fit, such as coefficients of determination (Hart & Chute, 2009). Variation in mussel growth was related to spring 10- day high discharge, which was among the most significant factors influencing mussel growth in our study. We also found a strong, quadratic relationship between spring 10-day high discharge and mussel growth, suggesting that the effect of flows on mussel growth is Fig. 6 Estimated relation between spring 10-day high discharge likely more complex than previously reported (Rypel and the Villosa lienosa growth coefficient (K) for three stream sizes et al., 2009; Black et al., 2010). Although the specific pro- (top), three levels of urban cover (middle) and three levels of cesses that caused this relationship are unclear, several agricultural land cover (bottom). The growth coefficient was esti- hypotheses may explain this pattern of growth in mated with the best approximating model and assuming untagged mussels, an unconfined stream channel, and median values response to stream flows. Because stream transport is for link magnitude and land cover as default values. The three dependent upon water velocity, particulate matter may levels contrasted in each plot represent the median and upper settle out of the water column and become unobtainable and lower quantiles observed during the study. Standardised to suspension-feeding mussels under very low flow con- flows are expressed in discharge (m3 s 1) per km2 watershed area. ditions (Vaughn & Hakenkamp, 2001) until resuspended

© 2014 John Wiley & Sons Ltd, Freshwater Biology, doi: 10.1111/fwb.12504 12 J. C. Dycus et al. during increasing stream flows. Rypel et al. (2009) and 2006). Mussels that inhabited small streams and those Black et al. (2010) speculated that increased total sus- with unconfined channels in the LFRB likely experi- pended solids (TSS) associated with high stream flows enced harsher and more variable environmental may increase processing cost, thus reducing growth of conditions. Therefore, we hypothesise that smaller maxi- mussels at high flows. However, TSS does not appear to mum size of mussels in small and unconfined streams affect mussel growth (Gascho Landis, Haag & Stoeckel, may represent a life-history trade-off in which mussels 2013), suggesting that other mechanisms influence mus- mature at younger ages and attain maximum sizes more sel growth at high stream flows. Alternatively, reduced quickly than those in non-disturbed streams, increasing growth at increased stream flows could represent inter- opportunities to reproduce in disturbed habitats. ruptions in feeding due to behavioural responses to The hierarchical von Bertalanffy growth models devel- evade scouring during increasing stream discharges. oped in our study broadened our understanding of Mussel growth and maximum size also were related to freshwater mussel ecology by accounting for variability several reach- and watershed-level variables measured in in growth and maximum size parameters among indi- our study, presumably because mussel growth and size vidual mussels. The model structure also allowed us to is a function of food quality and availability. Mussels relate the values of parameters to various site and occurring in eutrophic waterbodies frequently reach watershed characteristic in a single model, which is in greater lengths than those occurring in less productive sharp contrast to previous investigations (e.g. Rypel systems (Kesler & Van Tol, 2000; Anthony et al., 2001; et al., 2009; Black et al., 2010; Haag & Rypel, 2011). Kesler, Newton & Green, 2007). Increased maximum size Although our results are limited to three relatively com- of mussels with increasing stream size in our study is mon Flint River Basin species, this approach is directly consistent with the river continuum concept (Vannote applicable to other mussel species occurring across et al., 1980). Under this concept, small streams contain watersheds and has potential to increase our knowledge greater ratios of allochthonous rather than autochthonous of ecological processes affecting this imperilled fauna. materials generally found in larger streams. Because We were restricted to using only common species in our clearance rates are functions of mussel gill-surface mor- study because shell thin sectioning required sacrificing phology (Silverman et al., 1995; Galbraith et al., 2009) and live animals in the Flint River basin as insufficient shell algal flux (Vanden Byllaardt & Ackerman, 2014), large material is generally found in the basin. However, other allochthonous materials must undergo extensive process- basins having dense mussel populations with abundant ing before they are transported and ingested by mussels. middens may have greater opportunities to apply this However, large streams not only have high proportions analysis to additional and imperilled species, which will of autochthonous materials, which are generally small undoubtedly aid in their conservation and management. and can be readily utilised by mussels, but also allochthonous input, which could increase the amount and diver- Acknowledgments sity of food particles available for mussels. Hence, mussels occupying large waters likely have higher clear- This project was funded by a grant from the United ance rates than those in smaller waters because large States Fish and Wildlife Service and the Georgia Depart- waters have substantially higher flows but variable con- ment of Natural Resources, Wildlife Resources Division, centrations of food particles consumed by mussels which Nongame Conservation Section. This study was per- may also explain the decreasing influence of spring 10- formed under the auspices of University of Georgia ani- day discharge on mussel growth in large streams. mal use protocol # A2011 07-002-Y1-A0. A number of The growth and maximum size of mussels occupying people were instrumental in providing assistance with small streams and streams with unconfined channels this project. We are particularly indebted to the many were smaller that conspecifics occupying larger streams individuals who aided during field sampling, including or similar sized confined channel streams. Small streams Joseph Kirsch, Zachery DeWolfe, Andrea Fritts, Michael tend to experience more frequent and intense distur- Homer Jr., Michael Bednarski, Camille Beasley, Ben Car- bances (Resh et al., 1988; Reice, Wissmar & Naiman, swell, Nicole Rankin and Rod Bunn. The manuscript 1990). Similarly, diurnal fluctuations in temperatures was improved with suggestions from anonymous and dissolved oxygen in unconfined streams are greater reviewers. Any use of trade, firm or product names is than similar sized confined channel streams and maxi- for descriptive purposes only and does not imply mum temperatures tend to be higher and minimum dis- endorsement by the U.S. Government. The Georgia solved oxygen levels lower during the summer (Li, Cooperative Fish and Wildlife Research Unit is jointly

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