Predatory Impacts of Crayfish on Juvenile Apple Snails

PREDATORY IMPACTS OF CRAYFISH ON JUVENILE APPLE SNAILS

(POMACEA PALUDOSA AND P. MACULATA)

Andrew Davidson

A Thesis Submitted to the Faculty of

The Charles E. Schmidt College of Science

In Partial Fulfillment of the Requirements for the Degree of

Master of Science

Florida Atlantic University

Boca Raton, FL

December 2016

ACKNOWLEDGEMENTS

Nathan Dorn provided crucial guidance, insight, editing, and a patient and helpful hand throughout this thesis, as did committee members Erik Noonburg and Brian

Benscoter. Several people provided invaluable assistance with the process of bringing down the mesocosms and collecting data, including Hannah Campbell, Michelle Finn,

Juan Molero, and Estevao Santos. Jacob Dombrowski assisted by facilitating trips to the field and helped with collecting specimens. Erin Binkley and Sergio Gonzalez provided helpful feedback on the manuscript and defense. The author’s parents, Debbie and Clyde

Davidson, provided support and encouragement; lastly, the author’s wife, Jennifer

Davidson, provided helpful proofreading of the manuscript and impeccable amounts of patience and support, helping facilitate the entire process.

ABSTRACT

Author: Andrew Davidson

Title: Predatory Impacts of Crayfish on Apple Snails (Pomacea paludosa and P. maculata)

Institution: Florida Atlantic University

Thesis Advisor: Dr. Nathan Dorn

Degree: Master of Science

Year: 2016

Theory predicts that when prey can reach a size refuge from predation, prey vulnerability to predation is a function of hatchling size, growth rate, and the handling limitations of its predator, which collectively influence the amount of time prey spend vulnerable. I examined the mechanistic role of prey size for the predator-prey interaction between predatory crayfish (Procambarus fallax) and apple snail prey (Pomacea paludosa and P. maculata) and found that crayfish feeding rates decreased with snail size, such that smaller hatchling P. maculata were more than twenty times more vulnerable than hatchling P. paludosa. Experimental manipulations of productivity increased apple snail growth rates, reducing the effects of predatory crayfish on P. maculata survivorship, but not P. paludosa survivorship. My results indicate that when prey can reach a size refuge from predation, increased system productivity decreases predator limitation of that prey.

v PREDATORY IMPACTS OF CRAYFISH ON JUVENILE APPLE SNAILS

(POMACEA PALUDOSA AND P. MACULATA)

List of Tables ...... viii

List of Figures ...... ix

Introduction ...... 1

Effects of Life History Traits on Apple Snail Vulnerability to Crayfish ...... 6

Introduction ...... 6

Methods ...... 10

Effects of Predator Size, Prey Size, and Prey Species ...... 10

Selectivity ...... 12

Antipredator Defenses ...... 12

Effects of Prey Life History Traits on Prey Vulnerability ...... 14

Results ...... 15

Effects of Predator Size, Prey Size, and Prey Defensive Traits ...... 15

Selectivity ...... 16

Antipredator Defenses ...... 16

Effects of Prey Life History Traits on Prey Vulnerability ...... 17

Discussion ...... 18

vi Effects of Productivity on Crayfish Predation of Apple Snails ...... 28

Introduction ...... 28

Methods ...... 33

Experimental Design ...... 33

Data Collection ...... 36

Data Analysis ...... 37

Results ...... 41

Prey and Predator Growth Rates ...... 41

Prey Survival and Biomass ...... 41

Predator Sorting Effects ...... 42

Productivity Effects on Predation Strength ...... 43

Vegetation and Planorbid Snails ...... 44

Discussion ...... 45

Appendices ...... 58

References ...... 64

vii TABLES

Table 1. Summary of survival rates of juvenile apple snails and projected survival of

full clutches over 49 days under four experimental scenarios ...... 57

viii FIGURES

Figure 1. Crayfish kill and consumption rates on hatchling and juvenile P. maculata

as a function of crayfish length ...... 23

Figure 2. Crayfish kill and consumption rates on size-matched juvenile P. maculata

and P. paludosa as a function of crayfish length ...... 24

Figure 3. Crayfish feeding selectivity when offered size-matched juvenile P.

maculata and P. paludosa ...... 25

Figure 4. Shell masses of size-matched juvenile P. maculata and P. paludosa ...... 26

Figure 5. Shell masses of juvenile P. maculata reared in the absence of presence of

crayfish ...... 27

Figure 6. Apple snail growth rates at low and high productivity...... 52

Figure 7. Effects of productivity and crayfish on survival of apple snails ...... 53

Figure 8. Effects of productivity and crayfish on the assemblage of apple snails ..... 54

Figure 9. Effect sizes of crayfish predators on apple snail survival at varying

productivity levels ...... 55

Figure 10. Effect sizes of crayfish predators on apple snail total biomass at varying

productivity levels ...... 56

ix I. INTRODUCTION

Determining and understanding the importance of predation for structuring communities is a long-standing area of research in ecology (Paine 1966, Connell 1970).

Predators vary widely in size and morphology, but all predators must consume prey and therefore the consumer-resource interaction starts with the result of encounters between capable predators and vulnerable prey. The sizes of both predators and their prey can strongly impact the success of predator-prey interactions. Predator size directly influences which prey that predator can successfully and efficiently handle (Evans 1976,

Sousa 1993), and prey typically become less vulnerable to predation as they grow by exceeding the handling capabilities of their predators (Paine 1976, Werner and Gilliam

1984, Connell 1985). Thus, unless predators have difficulty detecting smaller prey, hatchling prey are often the most vulnerable to predators, and size-specific predation theory predicts that prey survival rates directly relate to the hatchling size and growth rate of the prey, and the handling capabilities of its predator (Werner and Gilliam 1984,

McCoy et al 2011), because these factors collectively influence the amount of time that the prey spends in a vulnerable state (e.g., Vonesh and Bolker 2005, Urban 2007).

Attempts to model and experimentally assess how predation strength varies with system productivity (e.g., Oksanen et al 1981, Borer et al 2006) frequently overlook the fact that prey can vary widely in size and thus vulnerability to predators across ontogeny, sometimes by orders of magnitude, and typically conclude that productivity will either

(1) increase predation strength, because higher productivity systems yield more predator biomass, which holds down prey biomass; or (2) have no effect, because higher productivity systems do not reliably produce more prey or predator biomass. For prey that can reach a size refuge from predation, increasing system productivity may provide higher quantity or quality resources, increasing prey growth rates and decreasing the amount of time prey spend at vulnerable sizes. Thus, if prey can reach a size refuge, predation may weaken at higher productivity (Chase 1999).

Gastropods are common herbivores in freshwater benthic communities. Two large-bodied apple snails (Pomacea spp.) inhabit freshwaters in Florida, including the

Everglades, and natural limits to their populations have been poorly studied. Pomacea maculata is native to South America, but has been present in Florida since at least 2002

(Rawlings et al 2007), and is one of the largest species in the genus with adult sizes at >

80 mm shell length (SL). It is known to be a voracious macrophyte herbivore and is widely considered a pest in its invaded range (Hayes et al 2012, Horgan et al 2014). The

Florida apple snail (P. paludosa) is the only native apple snail inhabiting wetlands in the southeastern U.S and has a considerably smaller adult size (25-40 mm SL). Both species consume a variety of foods including algae, detritus, and native macrophyte vegetation, and lab studies suggest that P. maculata may be a superior competitor; P. maculata inhibits the growth of juvenile P. paludosa (Conner et al 2007, Posch et al 2013). As adults both species are important prey for the endangered snail kite, Rostrhamus sociabilis, but it is unclear whether one species provides a superior food source (Cattau et al 2010).

2 Despite their large adult sizes, both species of apple snails produce small hatchlings (<4 mm SL). Pomacea paludosa produces 20-40 egg clutches of large, >3.5 mm diameter, white eggs that yield 3-4 mm SL hatchlings (Dorn and Hafsadi 2016), whereas P. maculata produces significantly larger clutches (300-4000 eggs, avg. = 2100) of small, <2 mm diameter, pink eggs that produce 1.5-2 mm SL hatchlings (Barnes et al

2008). Pomacea paludosa is reproductively active from spring through early fall, laying its eggs out of water on emergent vegetation (Hanning 1979, Turner 1996). Adults typically die after the reproductive season, and young hatch during the summer and autumn as adult densities decline (Hanning 1979, Darby et al 2008). Pomacea maculata has similar reproductive seasonality, but in south Florida, reproduction and egg-laying can continue later into the autumn, with egg masses observable as late as November (AD personal observations). Juvenile stage mortality may be a critical factor limiting adult apple snail densities. Despite the fact that Florida apple snails can produce over 400 eggs per year per individual and have hatching success exceeding 75% (Posch et al 2012), adult snail populations typically do not exceed 1 m-2 (Cattau et al 2014). Adult apple snail densities may be limited by several factors affecting juvenile snail survivorship.

Gastropod densities might be limited in oligotrophic wetlands like the Everglades by low availability of high quality food (Ruehl and Trexler 2011, Ruehl and Trexler 2015).

Hatchling and juvenile sized apple snails are also vulnerable to a host of predators including small turtles, aquatic insects, and crayfish (Procambarus spp.; Snyder and

Snyder 1971; Valentine-Darby et al 2015; Dorn and Hafsadi 2016).

Crayfish are ubiquitous in the Everglades, frequently reaching densities between

1-8 m-2 and can exceed 20 m-2 depending on season and location (Turner et al 1999, Dorn

3 and Trexler 2007, Dorn and Volin 2009, Hagerthey et al 2014). Crayfish are opportunistic omnivores, participating in several trophic levels from primary consumer to apex predator and consuming a variety of food sources such as detritus, algae, macrophyte vegetation, small aquatic invertebrates, and even fish (Nyström and Strand

1996, Hobbs 2001, Dorn and Wojdak 2004). The slough crayfish, Procambarus fallax, is the dominant crayfish species in wetlands with longer hydroperiods and less frequent drying (Hendrix and Loftus 2000). Procambarus fallax is a medium-bodied crayfish

(most < 25 mm carapace length; CL; van der Heiden 2012) and has been implicated as an important predator of juvenile apple snails in the Everglades (Dorn and Hafsadi 2016), and the relative risk P. fallax poses to apple snails is 8 X higher for juvenile P. maculata than for juvenile P. paludosa; this differential vulnerability is hypothesized to be due to differences in hatchling size (Dorn and Hafsadi 2016). Juvenile apple snail vulnerability is size-dependent; larger snails are less vulnerable, and juvenile P. paludosa reach a size refuge from P. fallax at approximately 11 mm SL (Valentine-Darby et al. 2015).

In this thesis, I tested the effects of hatchling size, crayfish size, and productivity on the vulnerability of both species of apple snails to a shared crayfish predator. In chapter 2 I investigated the importance of crayfish size, hatchling size, and antipredator defenses to the vulnerability of juvenile apple snails to crayfish. My objective was to mechanistically assess factors and apple snail life history traits that lead to the differential vulnerability faced by P. paludosa and P. maculata. In chapter 3, I examined how productivity affects the strength of crayfish predation on apple snails and tested the predictions of Chase (1999) and Werner and Gilliam (1984), which state that increased

4 prey growth rates at high productivity should decrease predation strength when prey can reach a size refuge.

II. EFFECTS OF LIFE HISTORY TRAITS ON APPLE SNAIL VULNERABILITY TO CRAYFISH

1. Introduction

Both predator and prey sizes play a crucial and often overlooked role in the mechanics of predation. Predators must be large enough to successfully capture and consume their prey (Cohen et al 2003), and prey capture efficiency and handling time both directly relate to the size of both the predator and its prey (Evans 1976, Sousa 1993), with smaller prey most often being easier and faster to handle. As prey grow, they typically become less vulnerable to predation by exceeding the handling capabilities of their predators (e.g., Paine 1976, Werner and Gilliam 1984, Connell 1985, Murdoch et al

1987, Miller et al 1988). Unless a predator fails to detect or value small-sized prey (e.g.,

Peters 1983, Persson and Leonardsson 1998, Brose 2010), hatchling and juvenile prey are generally the stages most vulnerable to predation. Therefore, size-specific predation theory predicts that the survival of a prey cohort directly relates to its hatchling size, growth rate, and the handling capabilities of its predator (Werner and Gilliam 1984,

McCoy et al 2011), because these factors collectively influence both organism size and the amount of time that the prey spends in a vulnerable state (e.g., Vonesh and Bolker

2005, Urban 2007). Differences in the vulnerability of different prey species to a shared predator should be related to interspecific differences in the same traits plus differences

6 in defensive traits (e.g., escape speed, spines, etc.) yet the contributions of multiple different life history traits to relative vulnerability have not been quantitatively decomposed for any known predator-prey pairs. Size-selective predators can have strong impacts on prey populations by reducing their abundance (Paine 1976, Tonn et al 1992) and shifting the size structure of prey populations through selective foraging on preferred prey sizes (Kerfoot and Peterson 1980, Claessen et al 2000, de Roos et al 2003).

Two large-bodied Ampullariid apple snails (Pomacea spp.) with important life history differences inhabit the freshwater wetlands in Florida: the native P. paludosa, and the non-native P. maculata. As adults, both snails attain large (>40 mm shell length) sizes and become important prey for large vertebrate predators, but they hatch at small and dramatically different sizes. Pomacea maculata produces large clutches of small eggs that hatch into 1.5-2 mm (SL) hatchlings, while P. paludosa produces smaller clutches of larger eggs that hatch into snails that are ~2 X longer (3.75-4.25 mm SL) and ~8 X heavier.

Fish, crayfish, and insect predators feed on juvenile apple snails, but only crayfish are common wetland predators. Slough crayfish (Procambarus fallax) inhabit many wetlands in Florida and can be important apple snail predators, but can only feed on snails at smaller juvenile sizes (< 11 mm SL; Valentine-Darby et al 2015). Crayfish feed on apple snails by either crushing the shells of the smallest hatchlings (e.g., hatchling P. maculata) or by chipping back the aperture edge of larger snails (e.g., juvenile P. maculata or hatchling P. paludosa) until the soft tissue can be extracted (Davidson pers. obs.). Dorn and Hafsadi (2016) observed that in wetland mescosm experiments, crayfish consumed approximately 7.1 X more hatchling P. maculata per hour than hatchling P.

7 paludosa and hypothesized that this difference could be attributed to differences in hatchling size. I tested this hypothesis and extended it across an ecologically relevant range of juvenile sizes, predicting that apple snail vulnerability to crayfish predation is mediated by both snail size and crayfish size, and that maximum kill rates (kills/h) and consumption rates (mg snail soft tissue · h-1) would be higher for larger crayfish, but lower on larger snails because of handling time differences. Furthermore, I decomposed the total instantaneous vulnerability of juvenile apple snails to crayfish predators as a function of hatchling size.

Shell-crushing predators like crayfish and fish often prefer smaller, thinner shelled snail prey (Osenberg and Mittelbach 1989, Alexander and Covich 1991, Brown

1998, Nystrӧm et al 1999). Snails may differ interspecifically in shell characteristics, and some gastropods grow thicker/heavier shells when reared in the presence of predators

(e.g., DeWitt 1998, Trussell and Smith 2000). Additionally, aquatic snails may exhibit other inducible defenses such as higher growth rates at the cost of delayed reproduction

(e.g., Crowl and Covich 1990). Werner and Gilliam (1984) predicted that the survival of a prey cohort directly relates to its hatchling size, growth rate, and the handling capabilities of its predator. In addition to these three factors, I predicted that the presence of any innate interspecific differences in shell thickness or inducible defenses (e.g., the induction of faster growth rates or the growth of a thicker shell in the presence of a predator) would also be important in assessing interspecific differences in predator vulnerability.

To test these hypotheses and decompose the importance of snail hatchling size and other defensive traits to instantaneous vulnerability to crayfish I conducted several

8 lab studies in which groups of snails were exposed to individual crayfish. The experiments included replicated feeding trials to quantify the effects of predator and prey size on vulnerability of cohorts of juvenile P. maculata to crayfish as well as cohorts of hatchling P. paludosa. A selection assay was performed to determine whether crayfish fed selectively on one species when size was held constant. Morphological traits related to defense were compared by measuring shell weights of each species, and the potential for induced shell defenses was tested by rearing P. maculata in the presence and absence of crayfish. The combination of feeding trials on two sizes of P. maculata (hatchling and juvenile) and hatchling P. paludosa allowed me to compare the relative contributions of size and antipredator defenses to the overall vulnerability of cohorts of apple snails.

2. Methods

2.1 Effects of Predator Size, Prey Size, and Prey Species

I conducted a series of feeding assays to examine how the vulnerability of snail cohorts scales with both snail and crayfish size, and how cohort vulnerability differs between P. paludosa and P. maculata when size is held constant. If hatchling size is the primary reason why P. maculata hatchlings are more vulnerable to crayfish predators than P. paludosa (i.e., no other life history differences are important), hatchling P. maculata should be more vulnerable than larger juvenile P. maculata and P. paludosa, and size-matched P. paludosa and P. maculata should exhibit similar vulnerability to crayfish predators. Multiple P. maculata and P. paludosa egg masses as well as crayfish were collected from Water Conservation Area 3A (26.0702° N, 80.6771° W), and the hatchling snails were reared in the greenhouse on a diet of mixed macrophytes

(Najas guadalupensis and Chara vulgaris), periphyton, and romaine lettuce. The feeding assays were conducted in the greenhouse on FAU's Davie campus using small plastic experimental arenas (42.5 x 30.2cm; 1283 cm2). I filled each arena with approximately 3-

4 cm of pond water and a small (7-10 cm) length of PVC pipe as shelter for the crayfish.

The water level in the tanks was intentionally kept low so that snails would not be able to climb above the reach of the crayfish. Some climbing behavior was observed, but snails did not climb any higher than the surface of the water.

I measured crayfish maximum feeding rates on three size classes of snails: hatchling P. maculata (1.5-2 mm SL), juvenile P. maculata that had been size-matched with hatchling P. paludosa (3.75-4.25 mm SL; hereafter referred to as “juvenile P. maculata”), and hatchling P. paludosa (3.75-4.25 mm SL). To test the extent to which

10 snail mortality scales with snail size and crayfish size, I compared crayfish feeding rates on hatchling P. maculata to feeding rates on juvenile P. maculata. I contrasted the vulnerability of cohorts of P. paludosa to juvenile P. maculata when size is held constant by comparing crayfish feeding rates on juvenile P. maculata to feeding rates on hatchling

P. paludosa. Individual crayfish (23 males and 25 females; total n = 48) between 8.5-25 mm carapace length (CL) were starved for 24 hours and allowed to feed for 16 hours overnight. In each trial, crayfish foraged on either 150 hatchling P. maculata (1.69 ± 0.02 mm SL, n = 18; mean ± SE), 25 juvenile P. maculata (3.97 ± 0.07 mm SL, n = 18), or 25 hatchling P. paludosa (3.96 ± 0.06 mm SL, n = 22).

I recorded the number of snails consumed by each crayfish and calculated the kill rate (snails consumed · h-1) and consumption rate (mg dry soft tissue mass · h-1). I modeled both rates as a function of crayfish size (mm CL) and compared the rates for a) hatchling P. maculata vs. juvenile P. maculata, and b) hatchling P. paludosa vs. juvenile

P. maculata using analysis of covariance. Crayfish below 12.2 mm CL consumed zero juvenile P. maculata, and crayfish below 13.8 mm CL consumed zero hatchling P. paludosa. Thus, these replicates were excluded from their respective analyses. Kill and consumption rates were natural logarithm transformed to meet the assumption of normality, but the model residuals for both kill and consumption rates when comparing juvenile P. maculata to hatchling P. paludosa were still non-normal (Shapiro-Wilk: kill rates p = 0.010; consumption rates p = 0.030). All data were tested for and met the assumption of homogeneity of variance using Levene’s test.

2.2 Selectivity

If crayfish consumption rates on juvenile P. maculata differ from consumption rates on size-matched hatchling P. paludosa, crayfish should selectively feed more on whichever species is more energetically favorable. I conducted a second feeding assay in the greenhouse using the same experimental arenas to examine whether crayfish feed selectively among equally sized individuals of both species. Fifteen adult crayfish at 18-

25 mm CL (mean ± SE = 21.34 ± 0.63) were starved for 24 hours (n = 15 replicates) and offered a mixed assemblage of size-matched snails; 15 hatchling P. paludosa (3.96 ± 0.06 mm SL) and 15 juvenile P. maculata (3.97 ± 0.07 mm SL). Crayfish fed for 16 hours overnight, after which the survivors were recovered. Surviving snails were identified by species by measuring the length of the spire (see Appendix I). Pomacea maculata typically possesses a longer spire length proportional to the rest of their shell length than

P. paludosa (see Appendix I); at 4 mm SL this means that snails with spires longer than

10% of the total shell length of the animal were identified as P. maculata.

To determine whether or not crayfish display preference, I calculated Chesson’s selectivity (α with depletion; Chesson 1983) such that indices < 0.5 indicated preference for P. maculata. I then used a two-tailed t-test for the mean to test for deviation from 0.5.

Two replicates were excluded from the analysis because the crayfish consumed only one snail each, for a final n = 13.

2.3 Antipredator Defenses

To investigate whether the two species have similar shell defensive structures, I dissected twelve greenhouse-reared snails of each species between 3.5-4.25 mm SL. I separated the soft tissue, shell and operculum, dried all three components in a drying

12 oven for 24 h at 60 °C, and compared the weight of the shell, used as a proxy for shell thickness, in two analyses with total length and soft tissue mass as alternate covariates.

To investigate whether P. maculata exhibit inducible antipredator defenses (e.g., the development of a thicker shell as in Crowl and Covich 1990; or faster growth rates as in DeWitt 1998, Trussell and Smith 2000), I reared P. maculata from hatchling sizes

(1.69 ± 0.02 mm SL; n = 144) in the presence or absence of predators. Pomacea maculata were reared in twelve plastic tubs (42.5 x 30.2cm; 1283 cm2) in pond water (pH

= 7.3; Glass and Darby 2009) on a diet of mixed macrophytes (Chara vulgaris, Naja guadalupensis), periphyton, and romaine lettuce. Each tub received six hatchling P. maculata and was randomly assigned a cup that was either empty or contained one crayfish between 15-20 mm CL (n = 6 each; total n = 12). Cups were pre-drilled with approximately 50 small (<1.5 mm) holes to allow chemical cues from the crayfish to pass outside of the cup and be detected by the snails. Crayfish were fed every other day on a diet of 20 hatchling P. maculata (approx. 1.5-2 mm SL).

Snails were reared to sizes between 4-6 mm SL (mean ± SE = 5.24 ± 0.12 mm

SL), collected, dissected, and dried in a drying oven at 60°C for 24 hours. I weighed the soft tissue mass and shell mass, used as a proxy for shell thickness, separately and calculated the growth rate of the snails (as mg soft tissue · day-1). I averaged these values across the six snails used in each replicate and compared the shell weight and growth rates in the presence and absence of crayfish predators using analysis of covariance, with final shell length as the covariate.

2.4 Effects of Prey Life History Traits on Prey Vulnerability

In order to decompose the relative importance of hatchling size and interspecific differences in antipredator defenses to predator vulnerability, I used regressions of crayfish kill rates for hatchling P. maculata, juvenile P. maculata, and hatchling P. paludosa to calculate kill rates for a 15 mm CL crayfish on each of the three snail classes.

In order to estimate the influence of hatchling size on predator vulnerability, I compared kill rates on hatchling and juvenile P. maculata. The influence of antipredator defenses was calculated as the proportional difference in kill rates on juvenile P. maculata as compared to hatchling P. paludosa where size was held constant, and the total difference

(i.e., factoring in both hatchling size and antipredator defenses) in predator vulnerability was calculated by comparing kill rates on hatchling P. maculata to kill rates on hatchling

P. paludosa.

3. Results

3.1 Effects of Predator Size, Prey Size, and Prey Defensive Traits

In every replicate, there was still a substantial number of snails remaining at the end of the trial. Crayfish consumed on average 25.8% ± 6.1% of the 150 available hatchling P. maculata, 12.9% ± 4.4% of the 25 available hatchling P. paludosa, and 30%

± 6.0% of the 25 available juvenile P. maculata. Thus, crayfish feeding rates were maximal and not likely limited by search times for any category of snail.

Crayfish kill rates scaled with snail size and were higher on hatchling P. maculata than on juvenile P. maculata (F1,30 = 74.96, p < 0.001). Crayfish kill rate was positively related to crayfish size (F1,30 = 60.093, p < 0.001) and the effect of snail size was greater for larger crayfish (interaction: F1,30 = 4.36, p = 0.040; Fig. 1a), such that small crayfish

(10 mm CL) consumed approximately the same amount of P. maculata regardless of snail size, but large crayfish (20 mm CL) consumed approximately 5.8 X more hatchling

P. maculata than juvenile P. maculata.

Crayfish consumed the same amount of P. maculata soft tissue regardless of snail size (F1,30 = 0.010, p = 0.921), but larger crayfish consumed more snail soft tissue (F1,30 =

41.199, p < 0.001). There was no interaction between snail and crayfish size (F1,30 =

0.069, p = 0.367; Fig. 1b) on soft tissue consumption rate. When offered hatchling P. maculata, crayfish may have also consumed portions of the shell, because when handling smaller snails, crayfish typically crushed the shell and consumed the snail whole. When fed larger snails, crayfish were observed leaving the shell behind after peeling away at the aperture wall of the snail and removing the soft tissue directly.

When crayfish were fed hatchling P. paludosa or juvenile P. maculata, despite the fact that snails were size-matched, crayfish killed P. maculata at a faster rate than P. paludosa (F1,29 = 8.467, p = 0.006), such that medium-sized crayfish (15 mm CL) consumed approximately 2.2 times more juvenile P. maculata than hatchling P. paludosa

(Fig. 2a). Crayfish kill rate was positively related to crayfish size (F1,29 = 17.658, p <

0.001), and there was no interaction between crayfish size and snail species (F1,29 =

1.190, p = 0.284). Crayfish below 13.8 mm CL consumed zero hatchling P. paludosa, whereas crayfish of sizes as low as 12.2 mm CL were able to consume juvenile P. maculata. Crayfish consumption of snail soft tissue was faster when feeding on juvenile

P. maculata than when feeding on P. paludosa (F1,29 = 8.039, p = 0.008). Larger crayfish consumed snail soft tissue faster than small crayfish (F1,29 = 18.696, p < 0.001), and there was no interaction between crayfish size and snail species (F1,29 = 0.837, p = 0.368; Fig.

2b).

3.2 Selectivity

Crayfish fed selectively when presented with a choice between size-matched apple snails of the two species. Crayfish consumed approximately 2.4 X more non-native

P. maculata than native P. paludosa (mean Chesson’s α ± std. error = 0.740 ± 0.052; t12 =

4.5609, p < 0.001; Fig. 3).

3.3 Antipredator Defenses

Juvenile P. maculata and P. paludosa differed significantly in shell weight whether using shell length (F1,20 = 19.210, p < 0.001) or dry soft tissue mass (F1,20 =

19.863, p < 0.001) as a covariate, such that native P. paludosa shells were 1.8 X heavier than those of size-matched P. maculata (Fig. 4). There was no effect of dry soft tissue

16 mass on shell mass (F1,20 = 0.499, p = 0.488), however, shell mass did vary with shell length (F1,20 = 19.210, p = 0.002). There was no interaction between snail species and either shell length (F1,20 = 1.689, p = 0.208) or dry soft tissue mass (F1,20 = 0.083, p =

0.776).

Pomacea maculata grown with crayfish cues did not exhibit heavier shells (F1,8 =

0.31, p = 0.590; Fig. 5a). Pomacea maculata shell weights increased with shell length

(F1,8 = 39.248, p < 0.001), but there was no interaction between shell length and predator presence (F1,8 = 0.128, p = 0.730). The presence of crayfish did not affect the growth rate of juvenile P. maculata, expressed as the growth of soft tissue mass per day (F1,8 = 0.945, p = 0.359; Fig. 5b). Growth rates increased with shell length (F1,8 = 10.450, p = 0.012), but there was no interaction between shell length and predator presence (F1,8 = 0.988, p =

0.349).

3.4 Effects of Prey Life History Traits on Vulnerability

Taken together, differences in both hatchling size and antipredator defenses meant that crayfish instantaneous kill rates were 20.8 X higher on hatchling P. maculata than on hatchling P. paludosa. When faced with an average-sized crayfish (15 mm CL), differences in snail size resulted in crayfish kill rates that were 6.9 X higher on hatchling

P. maculata than on juvenile P. maculata. By comparison, differences in antipredator defenses led to crayfish kill rates that were 3 X higher on juvenile P. maculata than on size-matched hatchling P. paludosa. Hatchling size contributed 2.3 X more to the overall differences in instantaneous kill rates between hatchling P. maculata and hatchling P. paludosa.

4. Discussion

Regardless of the size or species of apple snail prey, crayfish kill and consumption rates increased with crayfish size. This result is intuitive given that larger predators will necessarily have a stronger effect on food resources than smaller ones

(Paine 1976, Peters 1983) because of their higher metabolic demands (Brown et al 2004).

Larger predators are also less likely to be limited by factors like the ability to successfully handle prey (Paine 1976, Werner and Gilliam 1984, Connell 1985, Miller et al 1988).

Crayfish consumed P. maculata soft tissue at similar rates regardless of the size of snail prey, suggesting that consumption rates were maximal in all assays where predation occurred. Thus, kill rates on P. maculata from 1.5-4.25 mm SL were a function of crayfish metabolic rates; while crayfish handling times were longer on larger snails, the extra time required to remove a larger snail shell was proportionally offset by the amount of soft tissue yielded. Because juvenile P. maculata constitute approximately 6.2 X as much soft tissue as hatchling P. maculata, crayfish needed to consume fewer juveniles than hatchlings to reach satiation and thus the threat crayfish pose to cohorts of snails was lower for juveniles than hatchlings. For P. maculata, the benefits of being a larger snail had a somewhat greater effect when encountering larger crayfish.

While it is possible that differences in crayfish kill rates on juvenile and hatchling

P. maculata may have been due to differences in stocking densities (either 150 hatchlings or 25 juveniles were used), a considerable amount of snails (>70%) survived until the end of each trial. Crayfish are tactile foragers, and the experimental arenas were small; thus, it is unlikely that crayfish had difficulty searching for and locating snail prey where stocking densities were low.

Previous theoretical and experimental work predicts that both large and small prey may have refuge from predation because larger prey are often too large for their predators to successfully handle (e.g., Werner and Gilliam 1984, Miller et al 1988) while smaller prey are more difficult for predators to detect (e.g., Aljetlawi et al 2004, Vonesh and Bolker 2005). This produces a hump-shaped relationship between predation rates and prey size. Within the context of my experiment, crayfish did not have difficulty foraging on the smallest snails. Size-specific predation theory predicts that the survival of a prey cohort directly relates to its hatchling size, growth rate, and the handling limitations of its predator (Werner and Gilliam 1984, McCoy et al 2011), because these factors collectively influence both organism size and the amount of time that the prey spends in vulnerable size classes (e.g., Vonesh and Bolker 2005, Urban 2007). I quantified the influence of hatchling size and the handling limitations of the predator by comparing the mortality of hatchling P. maculata to the mortality of juvenile P. maculata that had been size-matched to hatchling P. paludosa across a range of crayfish sizes. When faced with a

15 mm CL crayfish, kill rates on hatchling P. maculata were 6.9 X higher than those on juvenile P. maculata. My results indicate that, for both species of apple snails, hatchling size and predator size play a crucial role in the mortality that snail cohorts face when exposed to crayfish predators.

In addition to hatchling size, comparisons between size-matched juvenile P. maculata and P. paludosa indicate that interspecific differences in defensive traits are important determinants of the mortality of cohorts of apple snails when exposed to crayfish. 15 mm CL crayfish killed juvenile P. maculata 3 X faster than hatchling P. paludosa even though size was equal. Selective foraging on P. maculata was

19 qualitatively consistent with the kill and consumption rate differences. Faster kill rates and selectivity for P. maculata were consistent with differences in shell masses; at similar sizes, P. paludosa hatchlings had shells that were 1.8 X heavier than P. maculata. Thus, hatchling P. paludosa are likely better defended against crayfish predators than P. maculata and thus require longer to handle, and this is consistent with observed differences in the size range of crayfish that could successfully handle hatchling P. paludosa as compared to juvenile P. maculata. Crayfish smaller than 13.8 mm CL could not handle P. paludosa, but crayfish as small as 12.2 mm CL were able to consume juvenile P. maculata of the same size. Additionally, I found no evidence that P. maculata respond physiologically to the presence of crayfish predators feeding on snails by either growing faster or growing a heavier shell.

When the impact of both hatchling size and antipredator defenses on prey vulnerability are considered together, average-sized crayfish (15 mm CL) killed hatchling

P. maculata at rates 20.8 X faster than they killed hatchling P. paludosa. Hatchling size was responsible for the majority of this overall difference; the impact of hatchling size on snail mortality when faced with a 15 mm CL crayfish was approximately 2.3 X higher than the impact of antipredator defenses.

Werner and Gilliam (1984) also identified prey growth rate as being an important factor in assessing the vulnerability of a prey to a size-specific predator, because it directly influences how much time prey spend at vulnerable sizes. My results estimate the maximum short term kill rates of crayfish on apple snails and thus represent instantaneous mortality rates. Overall measures of mortality through early life stages would require an estimate of the amount of time spent in that condition (i.e., snail growth

20 rates). Because P. maculata will spend many days growing from hatchling to juvenile while P. paludosa hatches at a relatively invulnerable, large and heavy-shelled, condition, the vulnerability of a cohort of P. maculata will be more than 20.8 X higher than P. paludosa. While I did not directly address the role of growth rate in measures of apple snail vulnerability, I found no evidence that P. maculata is capable of modulating its growth rate when exposed to crayfish predators. The presence of high quality food in eutrophic conditions may bolster P. maculata growth rates and thus may be important in mediating the vulnerability of P. maculata to crayfish and other size-limited predators.

Slough crayfish (Procambarus fallax) are nearly ubiquitous in south Florida wetlands, with densities commonly between 1-8 m-2 and sometimes exceeding 20 m-2 depending on season and location (Turner et al 1999, Dorn and Trexler 2007, Dorn and

Volin 2009, Hagerthey et al 2014). There is considerable variation in crayfish body size with some individuals reaching up to 40 mm CL, however most individuals are below 25 mm CL (Van der Heiden 2012). Thus, apple snails encounter crayfish often, and the risk that such an encounter poses can vary greatly depending on the size of the crayfish and the life history traits associated with the species of the apple snail. Because P. maculata spends a greater amount of time at significantly more vulnerable sizes than P. paludosa and remains more vulnerable even after reaching similar sizes the potential for control by crayfish may be stronger (see Dorn and Hafsadi 2016). Invasive Pomacea spp. are a global problem, and there is a considerable amount of interest in any methods that could help reduce their densities. My results highlight the importance of evaluating differences in life history traits between seemingly similar native and non-native taxa when

21 investigating predators that may provide biotic resistance or filters of prey community structure.

Fig. 1: Crayfish a) kill rates (snails · h-1) and b) consumption rates (mg soft tissue · h-1) on P. maculata as a function of crayfish length (mm carapace length; CL) when fed 1.5-2 mm SL hatchling P. maculata (solid line; snails · h-1 = 0.396(crayfish length in mm CL) –

4.182; mg soft tissue · h-1 = 0.175(crayfish length in mm CL) – 1.843) or 3.75-4.25 mm

SL juvenile P. maculata (dashed line; snails · h-1 = 0.0786(crayfish length in mm CL) –

0.925; soft tissue · h-1 = 0.215(crayfish length in mm CL) – 2.522).

Fig. 2: Crayfish a) kill rates (snails · h-1) and b) consumption rates (mg soft tissue · h-1) as a function of crayfish length (mm carapace length; CL) when fed P. paludosa (solid line; snails · h-1 = 0.0446(crayfish length in mm CL) – 0.585; soft tissue · h-1 = 0.127(crayfish length in mm CL) – 1.663) or juvenile P. maculata (dashed line; snails · h-1 =

0.0786(crayfish length in mm CL) – 0.925; soft tissue · h-1 = 0.215(crayfish length in mm

CL) – 2.522) of equal sizes.

Fig. 3: Mean numbers of P. paludosa and P. maculata consumed by crayfish when offered a mixed assemblage of equally sized snails. Error bars represent one standard error.

Fig. 4: Pomacea paludosa and P. maculata mean dry shell mass (mg). Snails were approximately the hatchling sizes of P. paludosa (3.98 ± .05 mm SL). Error bars represent one standard error.

Fig. 5: Pomacea maculata a) mean shell weights in mg and b) mean growth rates in mg soft tissue · day-1 when reared in the absence or presence of predatory crayfish. Error bars represent one standard error.

III. EFFECTS OF PRODUCTIVITY ON CRAYFISH PREDATION OF APPLE SNAILS

1. Introduction

The study of the interactive effects of top-down and bottom-up processes on community structure and trophic level biomass have been a focal point in ecology for decades (Oksanen et al 1981, Polis & Strong 1996, Menge 2000), and models of the interactions can come to opposing conclusions based on their assumptions about prey vulnerability (Chase 2003). The simplest models assume that all prey are equally vulnerable (e.g., modified Lotka-Volterra models such as Oksanen et al 1981), and thus predict that, for three-level food webs, as productivity increases predator effects on prey biomass should increase and hold prey biomass down. Other models incorporate variability in the vulnerability of different prey (e.g., Leibold 1989, Leibold 1996, Holt et al 1994), by assigning a static level of vulnerability to each prey item. These models generally predict that as productivity increases, predator effects on total prey biomass weakens, because even as predators sort the assemblages by selectively consuming prey that are most vulnerable, invulnerable prey are free to grow. Thus, the relative abundance of the most vulnerable prey will decrease, shifting the community towards being dominated by less vulnerable prey.

By holding down prey biomass, predators indirectly benefit plant biomass via trophic cascade. Results of a recent meta-analysis of experimental studies challenges these predictions, asserting that the predators controlled prey biomass similarly regardless of system productivity; there was no effect of productivity on predator effect size (Borer et al 2006). Additionally, Borer et al (2006) found no effect of productivity on the biomass of prey even where predators were absent, despite improved plant biomass and thus concluded that bottom-up effects attenuate faster than top-down effects.

Many theoretical food web models (e.g., Oksanen et al 1981, Abrams 1993, Holt et al 1994, Leibold 1996) overlook the fact that prey vulnerability can vary with ontogeny. Most animals increase in body size across ontogeny – sometimes by several orders of magnitude – and their vulnerability to predators decreases with size as they outgrow the handling capabilities of their predators (Werner and Gilliam 1984, Miller et al 1988). Therefore, when predation mortality is limited by prey size, the survival of a cohort of prey depends on its hatchling size, the handling limitations of the predator, and prey growth rate, because these factors collectively influence the amount of time that prey are vulnerable to their predators (Werner and Gilliam 1984, McCoy et al 2011). A model by Chase (1999) included variability in prey vulnerability as a function of body size such that juveniles were vulnerable to predators while adults were invulnerable and predicted that, because productivity influences prey growth rates, predation strength would be strong at low productivity and weaker at high productivity. The strength of predator control on prey biomass in turn led to either strong or weak cascading effects on plant biomass, respectively (Chase 1999), and these predictions were consistent with experimental results in pond food webs (Chase 2003). Thus, theoretical and experimental

29 attempts to quantify productivity’s effects on predation come to largely conflicting conclusions based on the vulnerability of prey to their predators; predator effects such as control of total prey biomass or sorting of a prey community may be enhanced, weakened, or unaffected by increasing productivity depending on how prey vulnerability differs – or fails to differ – interspecifically or throughout ontogeny.

Body size is critical to the vulnerability of many invertebrates to their predators

(Paine 1976, Connell 1985, Sousa 1993). Two large-bodied apple snails (Pomacea spp.) inhabit freshwaters in Florida, including the Everglades, the invasive P. maculata and the native P. paludosa. The two species differ in several life history traits, most notably the size of their hatchlings. Despite their large adult sizes (>25 mm shell length; SL), both species of apple snails produce small hatchlings (<4 mm shell length). Pomacea paludosa produces clutches of 20-40 large eggs that yield 3-4 mm SL hatchlings (Dorn and Hafsadi

2016), whereas P. maculata produces significantly larger clutches (300-4000 eggs, avg. =

2100) of smaller eggs that produce 1.5-2 mm SL hatchlings (Barnes et al 2008). Factors driving adult apple snail densities are poorly studied, and adult populations may be limited by juvenile survival. In oligotrophic wetlands like those present in southern

Florida, gastropod survival and growth might be limited by the availability of high quality food (Ruehl and Trexler 2011). Hatchling and juvenile-sized apple snails are also vulnerable to a host of predators including small turtles, aquatic insects, and crayfish

(Procambarus spp.; Snyder and Snyder 1971, Valentine-Darby et al 2015, Dorn and

Hafsadi 2016), but juvenile apple snail vulnerability to these early-life stage predators decreases with size (Chapter 2; Valentine-Darby et al 2015).

Crayfish are common predators in wetlands in south Florida (Turner et al. 1999,

Dorn and Trexler 2007, Dorn and Volin 2009, Hagerthey et al 2014) and are opportunistic omnivores, consuming a variety of food sources such as detritus, algae, macrophyte vegetation, small aquatic invertebrates, and even fish (Nyström and Strand

1996, Hobbs 2001, Dorn and Wojdak 2004, Dorn 2013). The slough crayfish,

Procambarus fallax, is the dominant crayfish species in wetlands with longer hydroperiods and less frequent drying (Hendrix and Loftus 2000). Procambarus fallax has been implicated as an important predator of snails in the Everglades (Dorn 2013,

Ruehl and Trexler 2015, Dorn and Hafsadi 2016), and the relative risk P. fallax poses to individual apple snails varies both with snail size and crayfish size (Chapter 2; Valentine-

Darby et al 2015). Apple snails eventually reach a size refuge from crayfish predation; even large adult P. fallax (>25 mm carapace length; CL), cannot consume apple snails above approximately 11 mm shell length (SL; Valentine-Darby et al 2015).

Because P. maculata produces smaller hatchlings that stay vulnerable to crayfish predators for a longer period of time, results from mesocosm studies suggest that the six- week cumulative vulnerability of juvenile P. maculata is 8 X greater than the vulnerability of juvenile P. paludosa (Dorn and Hafsadi 2016), and feeding trials estimate that instantaneous crayfish kill rates on hatchling P. maculata are >20 X higher than those on hatchling P. paludosa (Chapter 2). Dorn and Hafsadi (2016) predicted that the presence or absence of crayfish predators in wetlands will mediate the relative success of the two species; P. paludosa should be relatively favored (i.e., the overall assemblage of apple snails will contain a higher proportional density and/or biomass of P. paludosa) when crayfish are present, but P. maculata should be favored in their absence by their

31 larger clutch sizes (Barnes et al 2008) and competitive interactions (Conner et al 2007,

Posch et al 2013). Dorn and Hafsadi’s (2016) predictions may be context dependent.

Natural wetlands in Florida can vary widely in productivity and nutrient availability

(from 130-600 mg P/kg soil; see Reddy et al 2011). In highly productive wetlands, apple snail growth rates could be accelerated, reducing the amount of time that both species spend vulnerable to crayfish. If apple snail vulnerability scales with size such that the smaller snails are disproportionately more vulnerable than larger juveniles, increased growth rates may more strongly benefit the smaller hatchlings produced by P. maculata.

The objective of this study was to test how wetland productivity influences the strength of predation for prey that can grow to a size refuge. I predicted that higher productivity may limit predator control of apple snail abundance and reduce prey sorting by crayfish by promoting growth to size refuge, and weaken the cascading effects of crayfish predators on plant biomass (consistent with Chase 1999). I tested all three predictions by manipulating crayfish predators across two productivity levels in experimental wetland communities.

2. Methods

2.1 Experimental Design

To assess how the strength of crayfish predation on juvenile apple snails varies under differing productivities, I conducted a mesocosm experiment manipulating both predator presence and primary productivity in a factorial design by crossing crayfish presence and absence with low and high productivity conditions. The four treatments were interspersed in 24 1.1 m2 x 50 cm deep round mesocosms (n = 6 replicates). The array was located outdoors behind the greenhouse on FAU's Davie campus (Broward

County, FL). Each mesocosm was filled with a five cm layer of Everglades peat soil. I established two different productivity levels in the mesocosms in August 2015 by adding a pellet fertilizer (Osmocote, © The Scotts Company) to bring nutrient levels up to 400 mg P/kg soil in half of the mesocosms (high productivity) and 100 mg P · kg-1 in the other half (low productivity). While manipulating nutrient availability does not necessarily represent a direct manipulation of primary productivity, nutrient availability is correlated with the production of plant biomass. Thus, for this experiment, nutrient availability was treated as a proxy for primary productivity. Wetland productivity naturally varies in Florida; soil nutrient levels in Florida’s nutrient-enriched stormwater treatment areas (large nutrient remediation wetlands) have average phosphorus concentrations of 615 ± 396 mg P · kg-1 (mean ± std. error; Reddy et al 2011). Natural

Everglades soils without nutrient enrichment are typically much lower in phosphorous

(218 ± 46 mg P · kg-1; mean ± std. error; Hagerthey et al 2014). While the pellet fertilizer also introduced nitrogen and trace amounts of other micronutrients (e.g., iron,

33 magnesium) to the mesocosms, the primary goal was to elevate phosphorous levels to mimic eutrophication in Florida wetlands.

Water was added from a nearby pond with relatively low nutrient content (total phosphorus < 10 ppm). To simulate natural assemblages that could be found in shallow freshwater marshes in Florida, I added both coastal spikerush (Eleocharis cellulosa) in small pots (942.48 cm3) and six 30 cm strands of the macroalgae Chara vulgaris. Large apple snails have been documented feeding on C. vulgaris (Sharfstein and Steinman

2001, Baker et al 2010, Morrison and Hay 2011), but small juveniles presumably feed on periphytic algae (Rich 1990, Shuford et al 2005). I seeded populations of mosquitofish

(Gambusia holbrooki) and one species of smaller gastropod (Planorbella duryi) in each of the mesocosms. These species are common in Florida wetlands and the presence of mosquitofish also helps limit colonization by insects like dragonflies (Knorp and Dorn

2016) that can potentially prey on juvenile apple snails (Pyke 2005, Yusa et al 2006).

The vegetation in the mesocosm established from August 2015 to April 2016

(approx. eight months), and the experiment was conducted over 49 days in the early wet season (late April to early June). At the start of the experiment E. cellulosa stem density was higher in the high productivity mesocosms (173.8 ± 12.8 stems · m-2) than in the low productivity mesocosms (84.2 ± 4.6 stems · m-2). This difference was consistent across the course of the experiment; there were 265.2 ± 31.8 E. cellulosa stems m-2 in the high productivity mesocosms and 92.3 ± 7.3 stems · m-2 in the low productivity mesocosms at the end of the experiment. Throughout the course of the 49-day experiment, I also added

10 mg P in the form of sodium phosphate weekly to the water in high productivity mesocosms to maintain higher nutrient availability for algae. I chose to use 10 mg

P/week to approximate the phosphorous loading rates observed in stormwater treatment areas in southern Florida in 2015 (Redfield and Efron 2015).

To establish predator treatments, I collected medium-sized juvenile male crayfish

(Procambarus fallax; 14.25 ± 0.32 mm CL, mean ± SE) from the wetlands in Water

Conservation Area 3A (26.0702° N, 80.6771° W). Two crayfish were added to half of the experimental mesocosms creating predator densities of 1.8 m-2. I added the crayfish five days before the addition of apple snails and crayfish were assigned to mesocosms such that the average size of the individuals was equal in all mesocosms. Natural crayfish densities in Florida wetlands can range from 1-10 m-2 depending on location, season, and year (Dorn and Trexler 2007, Dorn and Volin 2009) so the density used was on the low end of the range. While P. fallax can grow to sizes exceeding 40 mm CL in the lab (Dorn, unpublished data), large adults (> 25 mm CL) within Florida wetlands are not common

(van der Heiden 2012). Valentine-Darby et al (2015) suggested that crayfish ≤ 17 mm

CL could not handle hatchling P. paludosa; my lab observations indicated that crayfish as small as 14 mm CL will consume hatchling P. paludosa at low rates (0.06 snails · h-1;

Chapter 2).

Apple snail egg masses were also collected from the Water Conservation Area 3A wetlands and hatched out in trays in the greenhouse. Equal total biomasses of hatchlings

(mean sizes ± SE: P. maculata 1.69 ± 0.02 mm SL; P. paludosa 3.96 ± 0.06 mm SL) of both species were stocked into the mesocosms. A single P. paludosa hatchling is approximately 8 X more massive (mg total wet mass) than a P. maculata hatchling (Dorn and Hafsadi 2016), so mesocosms were stocked with 30 P. paludosa hatchlings (27.3 m-2;

~1 clutch m-2) and 240 P. maculata hatchlings (218.2 m-2, ~0.11 clutches m-2) in each

35 mesocosm. Both species were stocked in groups over the course of 10 days as the hatchlings became available but biomasses were matched for each species each day until the target stocking densities were reached.

2.2 Data Collection

The experiment ended when snails stocked on the median stocking date had been in the mesocosms for 49 days. All vegetation was removed from the mesocosms and systematically rinsed and snails were removed from the walls of the mesocosms, mosquitofish were collected via dip net, and all of the soil and water from the mesocosms was poured through a bar seine (2 mm mesh) to collect any remaining fish, crayfish, and snails. All of the animals were euthanized (MS-222 was used for fish) and preserved with solutions of formaldehyde followed by 70% ethanol.

To quantify the effects of productivity on apple snail food availability, I estimated the amount of periphyton present in each mesocosm by deploying two rope substrates

(157 cm2 each in surface area) in each mesocosm at the beginning of the experiment. At the end of the experiment, the rope substrates were collected and immediately brushed with a toothbrush for two minutes and rinsed to remove the periphyton. I filtered the periphyton and weighed it after drying it in a drying oven at 100°C for 2 hours. I calculated the ash-free dry mass (AFDM) of the periphyton by weighing the samples after placing them in an ashing furnace at 500°C for 1 hour. The volume of C. vulgaris was quantified with a 2 L graduated cylinder at the end of the study. Chara vulgaris volume was converted into dry mass using a conversion factor that I calculated using the mass of two samples of C. vulgaris of a known volume that had been dried in the oven at

60°C for 24 h.

Apple snails were counted and identified to species using morphological differences. Larger juvenile to adult snails (>15 mm SL) were identified using characteristics of the aperture. P. paludosa possess an aperture lip that meets the body of the shell at a right angle, while the aperture lip on P. maculata curves inward as it reaches the body of the shell (personal obs.). For smaller snails (<15 mm SL) I measured the length of the shell spire (Appendix I). Pomacea maculata possesses a longer spire length proportional to the rest of their shell length than P. paludosa (Appendix I); snails with spires longer than 10% of the total shell length of the animal were identified as P. maculata. Identifications of 48 (3%) of the surviving snails in the intermediate size range

(6-21 mm) were confirmed with genetic tests of the cytochrome c oxidase subunit I gene

(Dr. J. Baldwin, FAU, unpublished data). I recorded the shell length of all surviving apple snails and calculated growth rates (mm SL · day-1) as the difference in shell length from hatchling size. Total apple snail biomass was estimated in each mesocosm by species using a natural log-transformed regression of dry soft tissue mass to shell length

(Appendix II). Apple snail biomass was calculated for each snail individually and then summed to acquire the total apple snail biomass for each replicate. I recorded the final size of all crayfish and calculated crayfish growth rates (mm CL · day-1) in low and high productivity conditions.

2.3 Data Analysis

I hypothesized that snail growth rates would be important to survival by limiting the amount of time apple snails spend at vulnerable sizes. To determine whether my treatments created different growth environments for apple snails, growth rates and average final sizes (mm SL) were compared from the crayfish-free mesocosms using one-

37 way analysis of variance. In addition to prey growth rates, crayfish growth rates might also be enhanced by increased productivity. Crayfish kill rates increase with carapace length (Chapter 2); thus, if crayfish grew faster at high productivity, their per capita effects on apple snail survival might also have increased. Therefore, I calculated crayfish growth rates as the difference between the final carapace length and the average carapace length of crayfish stocked in each mesocosm divided by the amount of time the crayfish were in the mesocosms (59 days) and compared the effects of productivity on crayfish growth rates using a one-way analysis of variance.

To test for effects of productivity and crayfish presence on apple snail survival, I performed a multivariate analysis of variance on the logit transformed proportional survival (Warton and Hui 2011) of both P. paludosa and P. maculata with productivity and crayfish presence as factors. I contrasted the treatment effects on P. paludosa and P. maculata survival individually using two separate two-way analyses of variance with planned contrasts. I tested the effects of crayfish and productivity on total apple snail biomass by comparing the total apple snail biomass (g dry soft tissue mass) across treatments and contrasted it against effects on the biomass of each species individually using three separate two-way analyses of variance.

In order to examine how crayfish effects on apple snail survival differed with productivity, I also calculated the crayfish effect size on final apple snail density

(ln(Ncrayfish/Ncontrol)), where Ncontrol was the mean number of survivors where crayfish were absent, and compared it across productivity levels using one-way analyses of variance for each species of apple snails separately to contrast the effects on each species.

Borer et al (2006) demonstrated that productivity does not affect predator effect size on

38 total herbivore biomass, but did not explicitly mention stage-specific predators, so I compared effect sizes on total apple snail biomass (calculated as above) across productivity levels using one-way analysis of variance.

Dorn and Hafsadi (2016) demonstrated that crayfish had stronger effects on P. maculata survival than P. paludosa survival and suggested that the presence of crayfish may shift mixed assemblages of apple snails to favor P. paludosa. Leibold (1996) predicted that predator sorting of a community would strengthen with increased productivity, but assumed that each prey species had a fixed level of vulnerability. Apple snail vulnerability varies with ontogeny (Chapter 2), and if productivity weakens the effects of crayfish on P. maculata as predicted, then crayfish sorting at high productivity may also be weaker and snail assemblages might still be dominated by P. maculata regardless of crayfish presence. To test this hypothesis, I calculated the logit-transformed proportion of the apple snail assemblage that was composed of P. paludosa and compared it across treatments using two-way analysis of variance.

To consider effects on assemblages in natural wetlands I also made projections of survivors using the clutch size differences and empirical survival estimates. I equalized juvenile biomass in the experiment and could not simultaneously account for clutch size differences in the experiment, but P. maculata clutches average 2100 eggs (Barnes et al.

2008) whereas P. paludosa clutches average only 30 (Rogevich et al. 2009; Posch et al.

2012; Dorn and Hafsadi 2016). To make a heuristic projection, I used the survival rates from each experimental combination to estimate the effects of crayfish on a single clutch of eggs of either species by calculating the number of surviving juveniles after 49 days under each set of conditions.

Planorbella duryi were also included in the mesocosms and may serve as alternative herbivore prey for crayfish, so I tested for effects of productivity and crayfish on P. duryi using two-way analysis of variance. I tested for effects of productivity and crayfish presence (through either cascading effects or direct consumption) on the vegetation by comparing the final dry mass of C. vulgaris and the AFDM of periphyton removed from the rope substrates using separate two-way analyses of variance. The predictions for periphyton biomass were complicated by the omnivory of crayfish

(Nystrӧm and Strand 1996; Dorn and Wojdak 2004; Dorn 2013).

For all analyses, I tested for violations of model assumptions by visually assessing and testing the residuals using the Shapiro-Wilk test and checking for homogeneity of variance using Levene’s test. In some cases, the residuals were not normally distributed due to the presence of outliers in some treatments. Rerunning the analyses without these outliers caused the residuals to be normally distributed, but did not qualitatively change the model results (i.e., the effects that were declared significant, at α < 0.05, with the outliers were still significant without them) so I have included only the full analyses in the results.

3. Results

3.1 Prey and Predator Growth Rates

Productivity improved overall apple snail growth rates of both species in the controls (MANOVA: F1,10 = 27.60, p < 0.001; one-way ANOVAs: P. maculata F1,10 =

50.45, p < 0.001; P. paludosa F1,10 = 38.32, p < 0.001, Fig. 6). Pomacea maculata reared at low productivity grew to only 7.3 ± 0.5 mm SL, whereas at high productivity P. maculata grew 2.2 X faster, reaching 16.3 ± 1.2 mm SL. P. paludosa reared at low productivity reached sizes of 13.0 ± 0.6 mm SL; at high productivity, P. paludosa grew

1.6 X faster, reaching 18.6 ± 0.7 mm. Apple snail growth rates did not differ when crayfish treatments were included in the analyses (P. paludosa: F1,20 = 0.09, p = 0.763;

P. maculata: F1,20 = 2.57, p = 0.126) and there were no interactions between treatments

(P. paludosa: F1,20 = 0.85, p = 0.367; P. maculata: F1,20 = 3.00, p = 0.1). Crayfish grew to a mesocosm average of 30.35 ± 0.54 mm CL (mean ± SE), regardless of productivity

(F1,10 = 0, p = 0.994). While this is a larger size than crayfish typically reach in Florida wetlands (van der Heiden 2012), most crayfish predation likely occurred early within the experiment while crayfish were still small (<20 mm CL). Based on apple snail growth rate estimates, P. maculata took on average between 7-11 days depending on productivity to reach the size of P. paludosa hatchlings; at these sizes, crayfish kill rates on P. maculata are 85.5% lower than kill rates on hatchling P. maculata (as calculated using a

15mm CL crayfish; Chapter 2).

3.2 Prey Survival and Biomass:

Apple snail survival was significantly affected by crayfish (MANOVA: F1,20 =

25.74, p < 0.001) and productivity (F1,20 = 9.43, p < 0.001), and the effect of crayfish was

41 modified by productivity (F1,20 = 4.99, p = 0.018). Crayfish reduced P. maculata survival

(F1,20 = 49.03, p < 0.001; Fig. 7a), but productivity increased survival (F1,20 = 19.77, p <

0.001) such that high productivity diminished the effects of crayfish predators

(interaction: F1,20 = 34.37, p = 0.005, Fig. 7a). Crayfish reduced survival of P. maculata by an average of 96.6% at low productivity (p < 0.001) and 72.2% at high productivity (p

= 0.014). With crayfish, the number of surviving P. maculata increased from near zero (2

± 1.2 ind./mesocosm) at low productivity to an average of 27.2 ± 0.1 ind./mesocosm (p <

0.001) at high productivity. Productivity did not significantly affect P. maculata survivorship where crayfish were absent (p = 0.377). Because P. maculata growth rates increased with productivity and were unaffected by crayfish, the survival results were consistent when testing for the effects of crayfish and productivity on P. maculata biomass (analysis not shown).

Crayfish reduced P. paludosa survival (F1,20 = 8.58, p = 0.008; Fig. 7b), but there were no effects of productivity (F1,20 = 0.52, p = 0.48) nor was there an interaction between crayfish and productivity (F1,20 = 0.94, p = 0343). Crayfish reduced juvenile P. paludosa survival from an average of 86% to 71% across both productivity treatments.

Total P. paludosa biomass was greater at high productivity (F1,20 = 48.98, p < 0.001), was unaffected by crayfish (F1,20 = 0.55, p = 0.47), and there was no interaction between productivity and crayfish (F1,20 = 0.65, p = 0.43).

3.3 Predator Sorting Effects

The proportion of the final assemblage that was composed of P. paludosa was affected by crayfish (F1,20 = 41.57, p < 0.001) and productivity (F1,20 = 14.96, p < 0.001), and the effects of productivity modified the influence of crayfish (interaction: F1,20 = 5.80,

42 p = 0.026; Fig. 8). Background mortality of P. maculata reduced the relative density of P. maculata from 89% at initial stocking (240 P. maculata: 30 P. paludosa) to an average of

69.5% where crayfish were absent. Crayfish shifted the assemblage towards higher relative abundances of P. paludosa regardless of productivity level (p < 0.001; Fig. 8), but sorting effects were 1.8 X greater at low productivity (p < 0.001) than at high productivity (p = 0.01). At low productivity where crayfish were present, there were on average 13 X more P. paludosa than P. maculata. At high productivity the assemblage was almost evenly divided (mean = 48.3% P. paludosa) (Fig. 8). Productivity alone did not shift the assemblage (productivity contrast without crayfish: p = 0.314: Fig 8).

When clutch size differences were accounted for, projected survivors of each species over a 49-day period indicated that P. paludosa was only slightly favored over P. maculata in low productivity wetlands with crayfish (1.1 X more P. paludosa than P. maculata) and that P. maculata density would be higher than P. paludosa density under all other conditions (Table 1).

3.4 Productivity Effects on Predation Strength:

The effect size of crayfish on P. paludosa survival and biomass was unaffected by productivity (survival: F1,10 = 2.59, p = 0.138; Fig. 9; biomass: F1,10 = 2.65, p = 0.135).

Crayfish effect sizes were highly variable at low productivity for P. paludosa, but this variation was mostly driven by one replicate. Increased productivity decreased the negative effects of crayfish (i.e., effects became more positive) on P. maculata survival

(F1,10 = 35.71, p < 0.001; Fig. 9). Crayfish effect sizes were 3.4 X higher on P. maculata kept in low productivity mesocosms than in high productivity mesocosms. These results were consistent when comparing effect sizes on either survival or biomass, although the

43 presence of an outlier mesocosm caused the effect of productivity on crayfish effect sizes to be marginally nonsignificant for P. maculata biomass (F1,10 = 3.93, p = 0.076).

Without the outlier, effect sizes on P. maculata biomass were significantly affected by productivity (F1,10 = 11.68, p = 0.008).

By comparison, the effect size of crayfish on total apple snail biomass (i.e., both species) did not differ with productivity (F1,10 = 0.03, p = 0.869; Fig. 10). Total apple snail biomass was directly increased 5.5x by higher productivity (F1,20 = 23.99, p <

0.001) and decreased by 54.2% with crayfish (F1,20 = 6.87, p = 0.0164). There was no interaction between crayfish and productivity (F1,20 = 3.84, p = 0.064).

3.5 Vegetation and Planorbid Snails

There was 1.4 X more C. vulgaris by dry mass in mesocosms with high productivity (F1,20 = 4.68, p = 0.043), but C. vulgaris dry mass was unaffected by crayfish presence (F1,20 = 2.81, p = 0.109), and there was no interaction between productivity and crayfish presence (F1,20 = 0.79, p = 0.385). The AFDM of periphyton harvested from the rope substrates was not affected by productivity (F1,20 = 0.038, p = 0.846), crayfish presence (F1,20 = 0.004, p = 0.95), or the interaction between them (F1,26 = 0.72, p =

0.407). Planorbella duryi densities were increased by productivity (F1,20 = 10.62, p =

0.004), but unaffected by crayfish (F1,20 = 0.23, p = 0.637; interaction: F1,20 = 1.36, p =

0.257). More than 68% (± 4.5%) of the P. duryi recovered from mesocosms were larger than 11 mm SL; at these sizes, P. duryi vulnerability to crayfish predators is relatively low (Dorn 2013).

4. Discussion

Crayfish and productivity both independently affected survival and biomass of one or more of the prey in my experiment. Though overall crayfish effect sizes on total prey biomass were unaffected by productivity, high productivity weakened crayfish sorting because differences in prey vulnerability were reduced by increased prey growth rates. Based on survival the crayfish effect size on P. maculata was 3.4 X stronger at low productivity than at high productivity. Because crayfish predation on apple snails is size- limited, increased productivity that increased snail growth shortened the period of vulnerability to crayfish and decreased the overall effect of predatory crayfish, but only for juvenile P. maculata. Crayfish predation on P. paludosa was uniformly weak and was unaffected by productivity. My results provide tests of predictions about the effects of life history traits on cohort vulnerability and the effects of productivity on predator-mediated population limitation, biomass limitation, and assemblage sorting. My results also provide some instructional value about the conditions under which native (P. paludosa) apple snails may be favored over non-native (P. maculata) in natural wetlands.

Productivity increased growth of both species of apple snails, but only P. maculata realized survival benefits with crayfish predators.

Food web models vary in their assumptions about prey vulnerability. Simple food web models often assume that prey are equally vulnerable (Oksanen et al 1981) and predict that predator effects on prey abundance increase along a productivity gradient because predator biomass and per capita predator effects increase with productivity, allowing predators to more effectively hold down prey biomass. However, a meta- analysis by Borer et al (2006) demonstrated that predation strength is largely unaffected

45 by productivity, because bottom-up effects of productivity enhance plant biomass but do not consistently or strongly influence herbivore biomass or the biomass of any subsequent trophic level. Within the context of my study, productivity enhanced apple snail biomass, but crayfish control of total apple snail biomass did not differ with productivity, consistent with results in Borer et al (2006).

Predators also sort prey assemblages and neither Oksanen et al (1981) nor Borer et al (2006) directly consider prey that vary in predator vulnerability or those that eventually reach an adult size refuge (Chase 1999). My results indicate that predation strength was unaffected by productivity when examining total biomass because the relatively invulnerable prey, P. paludosa, was only weakly affected by crayfish and made up a large fraction of the prey biomass in all replicates. Crayfish control of population density decreased with productivity when considering the smaller, more vulnerable prey,

P. maculata.

Simple food web models such as Oksanen et al. (1981) also predict that by limiting herbivore biomass, the presence of predators should also indirectly benefit plant biomass via trophic cascade (Oksanen et al. 1981). While crayfish limited apple snail biomass, I observed no net cascading of crayfish on either the biomass of C. vulgaris or periphyton at either productivity level. This may have been for two reasons: crayfish are known omnivores and will reduce densities of periphyton and macroalgae (Nystrӧm and

Strand 1996; Hobbs 2001; Dorn and Wojdak 2004; Dorn 2013), thus potentially negating any positive indirect effects of crayfish on C. vulgaris or periphyton; additionally, the time course of our study was relatively short (49 days) and may not have allowed time for the apple snails to grow and have pronounced effects on C. vulgaris biomass in the

46 absence of crayfish. Periphyton biomass was highly variable and did not respond to productivity either. At high productivity, increased snail biomass may have suppressed periphyton biomass, or available nutrients may have been limited in the water column by

C. vulgaris.

In food web models that assume prey vary in vulnerability to predators (e.g.,

Leibold 1989, Leibold 1996, Holt et al 1994), predator effects on total prey biomass are expected to decrease along a productivity gradient, because with increasing productivity, predators will selectively reduce the density of more vulnerable prey. At the same time, the density of less vulnerable prey will be relatively unaffected by predators and is expected to increase with productivity. Thus, the effects of predators on overall prey biomass will weaken, but the effects of predators on more vulnerable prey will increase with productivity and the community will be sorted to favor higher densities of less vulnerable prey. This model assumes prey have intrinsic vulnerabilities unaffected by productivity. My results were opposed to this prediction because the differences in apple snail vulnerability were lessened with increasing productivity, thus decreasing the strength of predator sorting. The effects of predators on total prey biomass were also unaffected by productivity.

Chase (1999) included variability in prey vulnerability in his food web models, such that juvenile prey were vulnerable, whereas adult prey were not. Based on this assumption, Chase (1999) predicted that predator effects should be strong at low productivity where growth rates to invulnerable adult sizes are limited and weak at high productivity because high productivity conditions facilitate faster growth to invulnerable sizes. Crayfish effect sizes on apple snail density only decreased with productivity in my

47 study for P. maculata. Despite increased growth rates, the effects of crayfish on P. paludosa survival were unaffected by productivity. Pomacea paludosa is less vulnerable from the start of life as a hatchling (Chapter 2), and the presence of crayfish only reduced average survival by 18%. The effect size of crayfish predators on P. paludosa survival was uniform and relatively weaker across productivity levels compared to effect sizes on

P. maculata survival. Werner and Gilliam (1984) predicted that in addition to growth rates, larger hatchling sizes also decrease the effects of size-selective crayfish. By hatching at larger sizes, P. paludosa starts in a more predator-resistant condition (Chapter

2) and may gain less of an advantage from nutrient enrichment than P. maculata. Thus, model and experimental results by Chase (1999) and Werner and Gilliam’s (1984) predictions about the vulnerability of a cohort of prey to a size-limited predator may only apply where the vulnerability of juvenile and adult prey varies greatly. Alternatively, crayfish are known to feed selectively on P. maculata over P. paludosa when provided a choice between the two, even when snail size is held constant (Dorn and Hafsadi 2016,

Chapter 2). The effects of crayfish on P. paludosa survivorship may have thus been weakened by the presence of P. maculata; therefore, crayfish effects on P. paludosa may be stronger when P. maculata is not available as an alternative food source, and in these cases, productivity may weaken crayfish effects on P. paludosa.

Dorn and Hafsadi (2016) predicted that due to differences in hatchling size, P. maculata were more vulnerable to crayfish and as such, assemblages of apple snails would be shifted to favor higher relative densities of P. paludosa than P. maculata where crayfish were present (avg. = 93% P. paludosa). At low productivity, my results demonstrated that assemblages of apple snails did indeed shift towards P. paludosa in the

48 presence of crayfish, however, Dorn and Hafsadi (2016) did not consider the potential effect of high productivity conditions on growth rates, and thus the vulnerability of P. maculata to crayfish. Where productivity was high, P. maculata vulnerability decreased, and thus so did crayfish sorting of the apple snail assemblage. Apple snail assemblages featured proportionally more P. maculata survivors at high productivity, resulting in a roughly even split (avg. = 48.3% P. paludosa) in assemblage structure where crayfish were present. Where crayfish were absent, P. maculata dominated regardless of productivity level (avg. = 69.5% P. maculata). When the effects of clutch size were included, the only conditions that favored higher relative abundances of P. paludosa than

P. maculata were low productivity wetlands with crayfish; in all other cases survival of juveniles over 49 days favors P. maculata, and there were 10.3 – 32.8 X more P. maculata than P. paludosa (Table 1). It is important to note, however, that these predictions are only valid when considering the survivorship of a single clutch of eggs of either species and thus do not account for potential interspecific differences in the rate at which egg clutches are produced or reproductive seasonality.

While neither this study nor Dorn and Hafsadi (2016) can directly demonstrate that crayfish constrain wetland invasion by P. maculata, my results show that crayfish dramatically affect P. maculata survival and may confer biotic resistance to invasion by

P. maculata under certain contexts. However, wetland eutrophication may limit the ability of crayfish to control P. maculata population density. Additionally, Dorn and

Hafsadi (2016) proposed that P. paludosa may be more tolerant of poor food quality present in oligotrophic interior marshes (Turner et al 1999, Ruehl and Trexler 2011). P. maculata survival improved under high productivity conditions, but only where crayfish

49 were present. Thus, my results suggest that eutrophic conditions may facilitate invasion by P. maculata by improving P. maculata survival in the presence of juvenile-stage predators such as crayfish.

My results represent short term estimates of how crayfish effects on juvenile apple snails vary with productivity, and thus predictions for long term effects on the density and biomass of apple snails may differ. Presumably, by weakening predator effects on juvenile apple snails, high productivity conditions will increase the number of apple snails that survive to adulthood and reproduce, thus increasing overall apple snail densities. However, my study did not allow for numerical responses of crayfish predators to productivity, because both crayfish were male, and the experiment was conducted over a short time scale. It is unknown how crayfish densities respond to high productivity conditions, but there is some evidence to suggest that high productivity wetlands may support higher densities of crayfish (Hagerthey et al 2014) presumably due to their broad diet and greater availability of food in eutrophic marshes. If crayfish densities increase with productivity, this might limit the advantage that apple snails gain under high productivity conditions. Thus, further study is necessary to determine how crayfish densities vary with productivity and how differences in crayfish density influence this interaction.

My results additionally highlight the importance of considering variation in prey vulnerability through ontogeny when examining productivity effects on predation strength. When prey vary substantially in predator vulnerability between juvenile and adult sizes, productivity may mitigate vulnerability by enhancing prey growth rates to a size refuge, which can have important consequences for community structure and

50 function. By facilitating juvenile survivorship, high productivity conditions may boost adult prey densities, and while there were no cascading effects on plant biomass within the context of my study, if predator control of prey biomass is weakened by productivity, indirect positive effects of predators on plant biomass may be weakened as well.

Fig. 6: Mean apple snail growth rates (mm SL · day-1) when reared at low and high productivity wetland mesocosms in the absence of predators. Errors bars represent the standard error of the mean. Mean growth rates were unaffected by crayfish presence when the crayfish treatments were included in the analysis (see Results).

Fig. 7: Effects of productivity and crayfish presence on mean proportional survival of juvenile a) P. maculata and b) P. paludosa presented on a logarithmic scale. Errors bars represent one standard error.

Fig. 8: Effects of productivity and predator presence on the proportion of the overall apple snail assemblage composed of P. paludosa. Errors bars represent one standard error.

Fig. 9: Effect sizes of crayfish predation on juvenile survival of P. paludosa and P. maculata at low and high productivity. Error bars represent one standard error.

Fig. 10: Effect sizes of crayfish predation on total apple snail biomass (g dry mass) at low and high productivity. Errors bars represent one standard error

Table 1: Comparison of P. maculata and P. paludosa life history traits, juvenile survival rates over 49 days in the presence and

absence of two crayfish (P. fallax) at low and high productivity, and projected number of survivors per egg clutch.

Scientific name P. maculata P. paludosa

Hatchling Size (mm SL) 1.7 4 Eggs per clutch 2100a 30b

Productivity Low High Low High

Survival rate without crayfish (mean ± SE) 0.244 ± 0.025 0.407 ± 0.092 0.872 ± 0.026 0.867 ± 0.031 Survival rate with crayfish (mean ± SE) 0.008 ± 0.005 0.113 ± 0.019 0.633 ± 0.103 0.789 ± 0.011

Survivors per clutch without crayfish 512 854 26 26 Survivors per clutch with crayfish 16 237 18 23

aBarnes et al. (2008). bRogevich et al. (2009) (28/clutch), Posch et al. (2012) (44/clutch), Dorn and Hafsadi (2015) (30/clutch).

APPENDICES

Appendix I: Apple Snail Size and Biomass

In order to convert apple snail shell lengths to biomass (measured as mg dry soft tissue mass), I dissected 58 P. maculata and 73 P. paludosa from 3.5 mm SL to 34.5 mm

SL and dried the soft tissue in a drying oven at 60°C for 24 h. I weighed the dried soft tissue and used two separate linear regressions to model dry soft tissue mass (mg) as a function of shell length (mm) for both species. I also modeled shell mass (mg) and total dry mass (mg) as a function of shell length for both species. All variables were natural logarithm transformed for linearity. Soft tissue mass increased linearly with shell length for both species (P. paludosa: slope p < 0.001, intercept p < 0.001; P. maculata: slope p

< 0.001, intercept p < 0.001; Appendix Fig. 1), as did shell mass (P. paludosa: slope p <

0.001, intercept p < 0.001; P. maculata: slope p < 0.001, intercept p < 0.001; Appendix

Table 1), and total mass (P. paludosa: slope p < 0.001, intercept p < 0.001; P. maculata: slope p < 0.001, intercept p < 0.001; Appendix Table 1).

Appendix Figure 1: Apple snail soft tissue mass in mg as a function of shell length in mm for P. paludosa and P. maculata. Both variables were natural logarithm transformed for linearity.

Appendix Table 1: Linear regression results for total dry mass, soft tissue mass, and shell mass as a function of shell length for both P. paludosa and P. maculata. All variables were transformed for linearity using the natural logarithm. Also listed are the total number of snails used for each regression and the range of shell lengths in mm.

Species n Range (mm SL) Variable Slope Intercept R2 P. paludosa 73 3.44 - 34.5 Total Dry Mass 2.64 -1.84 0.98 Soft Tissue Mass 2.25 -2.01 0.94 Shell Mass 2.77 -2.57 0.99 P. maculata 58 3.55 - 31.6 Total Dry Mass 2.7 -2.21 0.97 Soft Tissue Mass 2.46 -2.6 0.92 Shell Mass 2.78 -2.94 0.96

Appendix II: Apple Snail Identification

At juvenile sizes, it is difficult to discern between P. maculata and P. paludosa, but the shell morphology of both species varies subtly in several traits, the most obvious of which is the length of the spire. Pomcaea maculata possess a longer spire relative to the length of their shell than P. paludosa (personal obs.). I measured various aspects of the shell morphology (shell length and width, aperture length and width, and the length of the spire) of 113 P. paludosa from 3.46 to 14.6 mm SL and 86 P. maculata from 3.22 to

14.58 mm SL. Discriminant function analysis (DFA) was performed on the following shell morphological characteristics: the relative length of the spire and aperture relative to the total length of the shell, and the width of the aperture relative to the total width of the shell. The DFA was 96.5% accurate when identifying the species of juvenile apple snails and identified all three traits as important for distinguishing between the two species, with longer relative spire lengths and aperture widths being associated with P. maculata and longer relative aperture lengths being associated with P. paludosa (Table 1). Based on the analysis, I chose to identify apple snails below 15 mm SL based on spire length, such that mean relative spire lengths above 10% of the total length of the animal were identified as P. maculata.

Appendix Table 2: Discriminant function analysis results for apple snail identification between 3-15 mm SL. Listed are mean values for relative spire length, relative aperture width, and relative aperture length, as well as the coefficients of linear discriminants, where overall negative values were identified as P. maculata and overall positive values were identified as P. paludosa.

Relative Spire Length Relative Aperture Length Relative Aperture Width P. maculata 0.136 0.726 0.59 P. paludosa 0.045 0.856 0.549 Coefficient -7.38 18.8 -9.35

REFERENCES

Abrams, P. A. 1993. Effects of increased productivity on the abundances of trophic

levels. The American Naturalist 141(3):351-371.

Alexander, J. E., and A. P. Covich. 1991. Predation Risk and Avoidance Behavior in Two

Freshwater Snails. Biological Bulletins 180(3):387-393.

Baker, P., F. Zimmanck and S. M. Baker. 2010. Feeding rates of an introduced freshwater

gastropod Pomacea insularum on native and nonindigenous aquatic plants in

Florida. Journal of Molluscan Studies 76:138-143.

Barnes, M. A., R. K. Fordham, R. L. Burks and J. J. Hand. 2008. Fecundity of the exotic

apple snail, Pomacea insularum. Journal of the North American Benthological

Society 27:738-745.

Borer, E. T., B. S. Halpern and E. W. Seabloom. 2006. Asymmetry in community

regulation: effects of predators and productivity. Ecology 87:2813-2820.

Brose, U. 2010. Body-mass constraints on foraging behaviour determine population and

food-web dynamics. Functional Ecology 24(1):28-34.

Brown, J. H., J. F. Gillooly, A. P. Allen, V. M. Savage and G. B. West. 2004. Toward a

metabolic theory of ecology. Ecology 85:1771-1789.

Brown, K. M. 1998. The role of shell strength in selective foraging by crayfish for

gastropod prey. Freshwater Biology 40(2):255-260.

Cattau, C. E., P. C. Darby, R. J. Fletcher, W. M. Kitchens. 2014. Reproductive responses

of the endangered snail kite to variations in prey density. Journal of Wildlife

Management 78:620-631.

Chase, J. M. 1999. Food web effects of prey size refugia: variable interactions and

alternative stable equilibria. The American Naturalist 154:559-570.

Chase, J. M. 2003. Strong and weak trophic cascades along a productivity gradient. Oikos

101:187-195.

Chesson, J. 1983. The estimation and analysis of preference and its relationship to

foraging models. Ecology 64:1297-1304.

Claessen, D., A. M. de Roos and L. Persson. 2000. Dwarfs and giants: cannibalism and

competition in size‐structured populations. The American Naturalist 155(2):219-

237.

Cohen, J. E., T. Jonsson and S. R. Carpenter. 2002. Ecological community description

using the food web, species abundance, and size. Proceedings of the National

Academy of Sciences USA 100(4):1781-1786.

Connell, J. H. 1970. A predator-prey system in the marine intertidal region. I. Balanus

glandula and several predatory species of Thais. Ecological Monographs

40(1):49-78.

Connell, J. H. 1985. The consequences of variation in initial settlement vs. post-

settlement mortality in rocky intertidal communities. Journal of Experimental

Marine Biology and Ecology 93:11-45.

Conner, S. L., C. M. Pomoroy and P. C. Darby. 2007. Density effects of native and exotic

snails on growth in juvenile apple snails Pomacea paludosa (Gatropoda:

Ampullaridae): A laboratory experiment. Journal of Molluscan Studies 74:355-

362.

Crowl, T. A., and A. P. Covich. 1990. Predator induced life history shifts in a freshwater

snail. Science 247:949-951.

Darby, P. C., R. E. Bennetts and H. F. Percival. 2008. Dry down impacts on apple snail

(Pomacea paludosa) demography: implications for wetland water management.

Wetlands 28(1):204-214. de Roos, A. M., L. Persson and H. R. Thieme. 2003. Emergent Allee effects in top

predators feeding on structured prey populations. Proceedings of the Royal

Society of London 270:611-618.

DeWitt, T. J. 1998. Costs and limits of phenotypic plasticity: tests with predator-induced

morphology and life history in a freshwater snail. Journal of Evolutionary Biology

11:465–480.

Dorn, N. J. 2013. Consumptive effects of crayfish limit snail populations. Freshwater

Science 32:1298-1308.

Dorn, N. J. and M. Hafsadi. 2016. Native crayfish consume more exotic than native apple

snails. Biological Invasions 18:159-1679.

Dorn, N. J. and J. C. Trexler. 2007. Crayfish assemblage shifts in a large drought-prone

wetland: the roles of hydrology and competition. Freshwater Biology 52:2399-

2411.

Dorn, N. J. and J. C. Volin. 2009. Resistance of crayfish (Procambarus spp.) populations

to wetland drying depends on species and substrate. Journal of the North

American Benthological Society 28:766-777.

Dorn, N. J. and J. M. Wojdak. 2004. The role of omnivorous crayfish in littoral

communities. Oecologia 140:150-159.

Evans, H. F. 1976. The role of predator-prey size ratio in determining the efficiency of

capture by Anthocoris nemorum and the escape reactions of its prey,

Acyrthosiphon pisum. Ecological Entomology 1:85–90.

Glass, N. H. and P. C. Darby. 2009. The effect of calcium and pH on Florida apple snail,

Pomacea paludosa (Gastropoda: Ampullariidae), shell growth and crush weight.

Aquatic Ecology 43(4):1085-1093.

Hagerthey, S. E., M. I. Cook, R. M. Kobza, S. Newman and B. J. Bellinger. 2014.

Aquatic faunal responses to an induced regime shift in the phosphorus-impacted

Everglades. Freshwater Biology 59:1389-1405.

Hanning, G. W. 1979. Aspects of reproduction in Pomacea paludosa (Mesogastropoda:

Pilidae). Masters Thesis, Florida State University, Tallahassee, FL.

Hayes, K. A., R. H. Cowie, S. C. Thiengo and E. E. Strong. 2012. Comparing apples to

apples: clarifying the identities of two highly invasive Neotropical Ampullaridae

(Caenogastropoda). Zoological Journal of the Linnean Society 166:723-753.

Hendrix, A. N. and W. F. Loftus. 2001. Distribution and relative abundance of the

crayfishes Procambarus alleni (Faxon) and P. fallax (Hagen) in southern Florida.

Wetlands 20:194-199.

Hobbs, H. H. III. 2001. Decapoda In: Thorp, J. H. and A. P. Covich (Eds.), Ecology and

Classification of North American Freshwater Invertebrates. Academic Press, NY.

Holt, R. D., J. D. Grover and D. Tilman. 1994. Simple rules for interspecific dominance

in systems with exploitative and apparent competition. The American Naturalist

144:741–777.

Horgan, F. G., A. M. Stuart and E. P. Kudavidanage. 2014. Impact of invasive apple

snails on the functioning and services of natural and managed wetlands. Acta

Oecologica 54:90-100.

Kerfoot, W. C. and C. Peterson. 1980. Predatory copepods and bosmina: replacement

cycles and further influences of predation upon prey reproduction. Ecology

61:417–431.

Knorp, N. E. and N. J. Dorn. 2015. Mosquitofish predation and aquatic vegetation

determine emergence patterns of dragonfly assemblages. Freshwater Science

35(1):114-125.

Leibold, M. A. 1989. Resource edibility and the effects of predators and productivity on

the outcome of trophic interactions. The American Naturalist 134:922-949.

Leibold, M. A. 1996. A graphical model of keystone predators in food webs: trophic

regulation of abundance, incidence, and diversity patterns in communities. The

American Naturalist 147:784–812.

McCoy, M. W., B. M. Bolker, K. M. Warkentin and J. R. Vonesh. 2011. Predicting

predation through prey ontogeny using size-dependent functional response

models. The American Naturalist 177(6):752-766.

Menge, B. A. 2000. Top-down and bottom-up community regulation in marine rocky

intertidal habitats. Journal of Experimental Marine Biology and Ecology 250:257-

289.

Miller, T. J., L. B. Crowder, J. A. Rice and E. A. Marschall. 1988. Larval size and

recruitment mechanisms in fishes: towards a conceptual framework. Canadian

Journal of Aquatic Science 45:1657-1670.

Morrison, W. E. and M. E. Hay. 2011. Feeding and growth of native, invasive and non-

invasive alien apple snails (Ampullariidae) in the United States: Invasives eat

more and grow more. Biological Invasions 13:945-955.

Murdoch, W. W., R. M. Nisbet, S. P. Blythe, W. S. C. Gurney and J. D. Reeve. 1987. An

invulnerable age class in delay-differential parasitoid-host models. The American

Naturalist 129(2):263-282.

Nystrӧm, P., C. Bronmark and W. Graneli. 1999. Influence of an exotic and a native

crayfish species on a littoral benthic community. Oikos 85:545-553.

Nyström, P. and J. Strand. 1996. Grazing by native and an exotic crayfish on aquatic

macrophytes. Freshwater Biology 36:673-682.

Oksanen, L., S. D. Fretwell, J. Arruda and P. Niemela. 1981. Exploitation ecosystems in

gradients of primary productivity. The American Naturalist 118:240-261.

Osenberg, C. W. and G. G. Mittelbach. 1989. Effects of body size on the predator-prey

interaction between pumpkinseed sunfish and gastropods. Ecological

Monographs 59:405-432.

Paine, R. T. 1966. Food web complexity and species diversity. The American Naturalist

100(910):65-75.

Paine, R. T. 1976. Size-limited predation: an observational and experimental approach

with the Mytilus-Pisaster interaction. Ecology 57:858-873.

Persson, L. and K. Leonardsson. 1998. Ontogenetic scaling of foraging rates and the

dynamics of a size-structured consumer-resource model. Theoretical Population

Biology 54:270-293.

Peters, R. H. 1983. The Ecological Implications of Body Size. New York, NY: Cambridge

University Press.

Polis, G. A. and D. R. Strong. 1996. Food web complexity and community dynamics. The

American Naturalist 147:813-846.

Posch, H., A. L. Garr, R. Pierce and M. Davis. 2012. The effect of stocking density on

the reproductive output of hatchery-reared Florida apple snails, Pomacea

paludosa. Aquaculture 360-361:37-40.

Posch, H., A. L. Garr and E. Reynolds. 2013. The presence of an exotic snail, Pomacea

maculata, inhibits growth of juvenile Florida apple snails, Pomacea paludosa.

Journal of Molluscan Studies 1–3 doi:10.1093/mollus/eyt034.

Pyke, G. H. 2005. A review of the biology of Gambusia affinis and G. holbrooki.

Reviews in Fish Biology and Fisheries 15:339–365.

Rawlings, T. A., K. A. Hayes, R. H. Cowie and T. M. Collins TM. 2007. The identity,

distribution, and impacts of non-native apple snails in the continental United

States. Evolutionary Biology 7:97.

Reddy, K. R., S. Newman, T. Z. Osborne, J. R. White and H. C. Fitz. 2011. Phosphorous

cycling in the Greater Everglades ecosystem: legacy phosphorous implications for

management and restoration. Critical Reviews in Environmental Science and

Technology 41:149-186.

Redfield, G. W. and S. Efron. 2015. 2015 South Florida Environmental Report. West

Palm Beach, FL: South Florida Water Management District.

Rich, E. R. 1990. Observations on feeding by Pomacea paludosa. The Florida Scientist

53(Supplement):13.

Rogevich, E. C., T. C. Hoang and G. M. Rand. 2009. Effects of sublethal chronic copper

exposure on the growth and reproductive success of the Florida apple snail.

Archives of Environmental Contamination and Toxicology 56:450-458.

Ruehl, C. B. and J. C. Trexler. 2011. Comparison of snail density, standing stock, and

body size between Caribbean karst wetlands and other freshwater ecosystems.

Hydrobiologia 665:1-13.

Ruehl, C. B. and J. C. Trexler. 2015. Reciprocal transplant reveals trade-off of resource

quality and predation risk in the field. Oecologia 179(1):117-127.

Sharfstein, A. and A. D. Steinman. 2001. Growth and survival of the Florida apple snail

(Pomacea paludosa) fed 3 naturally occurring macrophyte assemblages. Florida

Scientist 20(1):84-95.

Shuford, R. B. E. III, P. V. McCormick and J. Magson. 2005. Habitat related growth of

juvenile Florida apple snails (Pomacea paludosa). Florida Scientist 68(1):11-19.

Snyder, N. F. R. and H. A. Snyder. 1971. Defenses of the Florida apple snail Pomacea

paludosa. Behavior 40:175–215.

Sousa, W. P. 1993. Size-dependent predation on the salt-marsh snail Cerithidea

californica Haldeman. Journal of Experimental Marine Biology and Ecology

166:19–37.

Tonn, W. M., C. A. Paszkowski and I. J. Holopainen. 1992. Piscivory and recruitment:

mechanisms structuring prey populations in small lakes. Ecology 73:951–958.

Trussell, G. C. and L. D. Smith. 2000. Induced defenses in response to an invading crab

predator: an explanation of historical and geographic phenotypic change.

Proceedings of the National Academy of Sciences USA 97:2123–2127.

Turner, A. M. 1997. Contrasting short-term and long-term effects of predation risk on

consumer habitat use and resources. Behavioral Ecology 8:120–125.

Turner, A. M., S. A. Fefferolf and R. J. Bernot. 1999. Predator identity and consumer

behavior: differential effects of fish and crayfish on the habitat use of a freshwater

snail. Oecologia 118:242-247.

Turner, R. L. 1996. Use of stems of emergent plants for oviposition by the Florida apple

snail, Pomacea paludosa, and implications for marsh management. Florida

Scientist 59:34-49.

Urban, M. C. 2007. Predator size and phenology shape prey survival in temporary ponds.

Oecologia 154(3):571-580.

Valentine-Darby, P. L., S. E. Kell and P. C. Darby. 2015. Predation on Florida apple

snails (Pomacea paludosa) by native and non-native aquatic fauna, and predator-

prey size relationships. Florida Scientist 78(1):48-56. van der Heiden, C. A. 2012. Population distribution, habitat selection, and life history of

the slough crayfish (Procambarus fallax) in the ridge-slough landscape of the

central Everglades. PhD dissertation, Florida Atlantic University, Boca Raton, FL.

Vonesh, J. R. and B. M. Bolker. 2005. Compensatory larval responses shift trade-offs

associated with predator-induced hatching plasticity. Ecology 86(6):1580-1591.

Warton, D. I. and F. K. C. Hui. 2011. The arcsine is asinine: the analysis of proportions

in ecology. Ecology 92:3-10.

Werner, E. E. and J. F. Gilliam. 1984. The Ontogenetic Niche and Species Interactions in

Size-Structured Populations. Annual Reviews in Ecology, Evolution, and

Systematics 15:393-425.

Yusa, Y., N. Sugiura and T. Wada. 2006. Predatory potential of freshwater animals on an

invasive agricultural pest, the apple snail Pomacea canaliculata (Gastropoda:

Ampullariidae), in southern Japan. Biological Invasions 8:137-147.