Draft - University of Toronto T-Space · Draft Do diets vary over large spatial or temporal ranges? A test using inter-annual and inter-population data on Diamondback Terrapins (Malaclemys

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Do diets vary over large spatial or temporal ranges? A test using inter-annual and inter-population data on

Diamondback Terrapins (Malaclemys terrapin) diets

Journal: Canadian Journal of Zoology

Manuscript ID cjz-2018-0211.R2

Manuscript Type: Article

Date Submitted by the Author: 13-Sep-2018

Complete List of Authors: Erazmus, Kayleigh; Hofstra University, Biology; Sacred Heart University College of Arts and Sciences, BiologyFigueras, Miranda; Hofstra University, BiologyLuiselli, Luca; Environmental Studies Centre DemetraBurke, Russell; Hofstra University, Biology

Is your manuscript invited for consideration in a Special

Issue?:Not applicable (regular submission)

Keyword: FEEDING < Discipline, COMPARATIVE < Discipline, REPTILIA < Taxon, FORAGING < Discipline, TESTUDINES < Taxon, Habitat

https://mc06.manuscriptcentral.com/cjz-pubs

Canadian Journal of Zoology

Draft

Do diets vary over large spatial or temporal ranges?

A test using inter-annual and inter-population data

on Diamondback Terrapins (Malaclemys terrapin) diets

KAYLEIGH ROSE ERAZMUS1,2, MIRANDA FIGUERAS1, LUCA LUISELLI3,4,5, AND RUSSELL L. BURKE1,6

1: Department of Biology, Hofstra University, Hempstead, New York, USA

2: Biology Department, Sacred Heart University, Fairfield, Connecticut, USA

3. Institute for Development, Ecology, Conservation and Cooperation, via G. Tomasi di

Lampedusa 33, I-00144 Rome, Italy

4. Department of Applied and Environmental Biology, Rivers State University of Science and

Technology, P.M.B. 5080, Port Harcourt, Nigeria

5. Department of Zoology, University of Lomé, Lomé, Togo. Email: [email protected]

6: Corresponding author: [email protected]

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1 ABSTRACT.— Animal diets may vary spatially or temporally as resource availability vary. Diets of

2 species with extensive geographic ranges often span multiple habitats, thus their diets may vary

3 accordingly. Temporal diet variation is rarely explored because most diet studies are short-

4 term; this is problematic for long-lived species where individuals may persist as prey availability

5 changes. We analyzed diet variation in Malaclemys terrapin (Diamondback Terrapins Schoepf

6 1793), which inhabits nearly 70,000 km of United States Atlantic coastline, spanning 16.5o

7 latitude, 27.4o longitude, and 4 Köppen climatic zones, and Bermuda. We explored spatially or

8 temporally terrapin diet variation; including populations from Atlantic salt marshes, an

9 Everglades mangrove swamp, the Texas Gulf Coast, and a Caribbean golf course pond. We

10 found remarkably high levels of similarity indicating that although diets vary according to local

11 prey availability, at lower taxonomic resolution they are broadly similar. Even short-term

12 studies may be sufficient to accurately characterize diets of Diamondback Terrapins. These

13 results are surprising considering the geographic range sampled in this study, and indicate that

14 diamondback terrapin diets are conservative, reflecting local prey availability. Such diets

15 apparently allow terrapins to exploit their extensive range and may allow terrapin populations

16 to persist as local prey species wax and wane.

17 Keywords: Malaclemys terrapin, Diamondback Terrapins, feeding, comparative, Reptilia,

18 foraging, testudines, habitat.

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19 Diets of members of a population may vary temporally or spatially due to different

20 nutritional needs or availability of resources. Species with large geographic ranges typically

21 have different diets in different parts of their ranges, if only because prey availability varies

22 within the range (e.g., Iriarte et al. 1990; Simpfendorfer et al. 2001; Lozano et al. 2006; Rulison

23 et al. 2012). If the diet of a predator species is inflexible, its diet may not differ even between

24 spatially distant populations, and prey availability may limit its distribution. Inflexible diets may

25 also lead to local population reductions if the required prey species availability declines.

26 Conversely, flexible diets can allow predators to exploit more diverse habitats over wide ranges,

27 and also allow specific populations to persist as local prey species wax and wane.

28 We explored temporal and spatial diet variation in Diamondback terrapins (Malaclemys

29 terrapin Schoepf 1793), which comprise a monotypic emydid turtle genus within the relatively

30 speciose (approximately 41 species) Deirochelyinae subfamily (TTWG 2017). Most members of

31 the subfamily inhabit primarily freshwater. While at least 8 species are known to inhabit

32 brackish water regularly (Ernst and Lovich 2009), Malaclemys is a habitat specialist and the only

33 member of Deirochelyinae that specializes in brackish-water environments. Adult diets vary

34 both between and within Deirochelyinae, ranging from nearly strictly carnivorous (e.g.,

35 Deirochelys reticularia Latreille in Sonnini and Latreille 1801) to nearly herbivorous (e.g.,

36 Pseudemys rubiventris Le Conte 1830). Many species in genera Trachemys (sliders) and

37 Pseudemys (cooters) tend to undergo an ontogenetic shift from carnivory to herbivory as they

38 mature (Hart 1983; Parmenter and Avery 1990; Bouchard and Bjorndal 2006) associated with a

39 habitat shift (Hart 1983; Congdon et al. 1992) and changes in digestive physiology (Whelan et

40 al. 2000; Bouchard and Bjorndal 2006). Therefore, there is reason to hypothesize that a

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41 Deirochelyinae species with a large range, such as Diamondback terrapins, (nearly 70,000 km of

42 United States Atlantic coastline, spanning 16.5 latitude degrees, 27.4 longitude degrees, and 4

43 Köppen climatic zones, Roosenburg and Kennedy 2018) will exhibit wide diet diversity. Even

44 their sister taxon (Graptemys) includes species with diets ranging from primarily sponges and

45 bryozoans (e.g., G. flavimaculata Cagle 1954 and G. nigrinoda Cagle 1954) to primarily molluscs

46 (e.g., female G. barbouri Carr and Marchand 1942 and G. pulchra Baur, 1893), Lindeman 2013),

47 and no Graptemys species distribution matches the latitudinal or longitudinal range of

48 Malaclemys.

49 Diamondback terrapin diets have recently been studied in many parts of their range,

50 including the westernmost populations (Alleman and Guillen 2017), the southernmost

51 population (Denton et al. 2016), northern populations (Erazmus 2012), the Bermuda population

52 (Outerbridge et al. 2017) as well as several other locations (reviewed by Tucker et al. 2018).

53 Most diet studies show that despite variation in the availability of prey species, Diamondback

54 terrapins exhibit moderate to high levels of molluscivory (Tucker et al. 2018), much like many

55 Graptemys. Studies based on observations of feeding in the wild, fecal samples, and stomach

56 dissections have found that Diamondback terrapins consume primarily eastern mudsnails

57 (Nassarius obsoletus Say 1822) in New York (Petrochic 2009), soft-shelled clams (Mya arenaria

58 Linnaeus 1758) in Maryland (Roosenburg et al. 1999), Atlantic blue crabs (Callinectes sapidus M.

59 J. Rathbun 1896) in North Carolina (Spivey 1998), marsh periwinkles (Littoraria irrorate Say

60 1822) in South Carolina (Tucker et al. 1995), and dwarf surfclams (Mulinia lateralis Say 1822) in

61 northern Florida (Butler et al. 2012). Studies of captive Diamondback terrapins of all ages found

62 they willingly ate blue crabs, fish, oysters, clams, fiddler crabs, canned fish, liver, beef and small

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63 mollusks (Hildebrand 1928; Allen and Littleford 1955). Beyond these general observations,

64 there has been no overall quantitative analysis of Malaclemys diets (Tucker et al. 2018).

65 Our study addressed 2 general concerns. First, although there have been more than 20

66 Diamondback terrapin diet studies (Tucker et al. 2018), these were mostly short-term studies

67 and/or involved small numbers of turtles. The diet study with the largest sample size (N = 294)

68 was limited to a single nesting season (Tucker et al. 1995); in fact, very few studies have

69 included data from more than 1 year, thus the possibility of inter-annual variation has not been

70 explored. These studies have been insufficient to test for temporal variation over timescales

71 relevant to a species where individuals are typically long-lived. Second, while several studies

72 have explicitly compared their results to the results of other studies (e.g., Denton et al. 2016;

73 Tucker et al. 2018), thus far no inter-populational studies have used quantitative diet overlap

74 methods, and previous comparisons were strictly qualitative. Thus, previous authors have been

75 tested for spatial variation using statistically robust methods.

76 Our goals were to address these concerns by collecting multiple years of diet data from

77 a substantial number of Diamondback terrapins from a single population and measure inter-

78 annual variability using standard quantitative diet overlap measures. Second, using the same

79 methods, we compared the diets from our well-studied population to the results from all other

80 substantial Diamondback terrapin diet studies and thus assess intra-specific variability. We

81 limited our comparison to the 6 other studies that had data similar to ours: fecal samples

82 collected from adult females primarily in the middle of the activity season.

83 METHODS

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84 Jamaica Bay Study Site.— Jamaica Bay (JB) is a polyhaline embayment at the extreme

85 southwestern end of Long Island NY, part of the boroughs of Brooklyn and Queens NY, and

86 connected to the Atlantic Ocean through Rockaway Inlet. The salinity varies from 28-32 parts

87 per thousand near the Rockaway Inlet to 16-27 ppt near the Bergen Basin outfall (Ringenary,

88 unpub. data). Northern quahogs (Mercenaria mercenaria Linnaeus 1758), soft-shelled clams,

89 and blue mussels (Mytilus edulis Linnaeus 1758) are abundant in JB mud flats and deep waters.

90 Atlantic ribbed mussel (Geukensia demissa Dillwyn 1817) and northern rock barnacles

91 (Semibalanus balanoides Linnaeus 1767) are common in the upper half of the inter-tidal zone,

92 and both eastern mudsnails and common Atlantic slippersnails (Crepidula fornicate Linnaeus

93 1758) dominate tidal creeks. Additionally, sea lettuce (Ulva latuca Linnaeus) and smooth

94 cordgrass (Spartina alterniflora Muhl. ex Elliott) are abundant, especially in the summer.

95 Although late in the 19th century Eastern oysters (Crassostrea virginica (Gmelin 1791) were

96 abundant in JB, currently there are few or no oysters in JB due to overharvesting and pollution.

97 The loss of oyster populations can result in hypoxic conditions and greatly reduced water

98 filtration rates (Rothschild et al. 1994; Kemp and Boynton 1984), causing a shift in dominant

99 macrofaunal species in deep muddy sediments from larger, older bivalves to short-lived

100 opportunistic species (Holland et al. 1987). A similar shift may have occurred in Jamaica Bay,

101 thus altering the prey species available to Diamondback terrapins, but historical records are

102 insufficient to test this.

103 Fecal Sample Collections. — In June and July of 2008-2014 we collected adult female

104 Diamondback terrapins that had nested on the western half of Ruler’s Bar, an island centrally

105 located within JB. We induced defecation by soaking them in fresh water (Tucker et al. 1995) in

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106 individual containers with approximately 23 liters of freshwater each, allowing for full coverage

107 of their carapaces. We soaked each Diamondback terrapin for 2 days in 2008, for 5 days in 2009

108 and 2010, and 3 days in subsequent years. We released the Diamondback terrapins back into JB

109 after fecal collection. Feces were condensed by pouring the water into a sieve (1 mm standard

110 size mesh) and preserving the solid material in formalin or 70% ethanol. Prey pieces were

111 separated using forceps and a dissecting microscope, then air-dried in a hood and identified to

112 the highest taxonomic level possible. Molluscan and crustacean pieces were compared to live

113 specimens collected from JB and to Gosner (1978). Items we could not identify to species were

114 placed into more general categories.

115 Fecal Sample Analyses.— We classified prey items into the following groups: Plantae

116 (leaves/stems, seeds, grass); Algae (sea lettuce and algae other than sea lettuce); Bivalvia (soft-

117 shelled clams, Atlantic ribbed mussels, and amethyst gem clams (Gemma gemma Totten

118 1834)); Crustacea (crabs and ostracods); Gastopoda (eastern mudsnails, rough periwinkles,

119 convex slippersnails (Crepidula convexa Say 1822)); Bryozoa; Insecta; Annelids (polychaete

120 tubes); invertebrate eggs (Atlantic horseshoe crab (Limulus Polyphemus Linnaeus 1758) eggs,

121 and Invertebrate egg masses); Unidentifiable animal tissue/detritus and Sand (Table 1). We

122 calculated the percent frequency of occurrence (PFO) by summing the number of times each

123 prey species was identified in any fecal sample in a particular year and dividing that number by

124 the total number of individuals whose feces were collected that year. PFOs were calculated for

125 each year and for all 7 years combined.

126 We did not attempt to count the number of individuals of each prey species or to

127 estimate the volume eaten of any prey species because in most cases we could not confidently

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128 estimate these parameters. For example, clam shell fragments could have been the remains of

129 1 or multiple clams. Estimating the number of individuals or volume eaten would have been

130 especially problematic for Ulva or plant remains. Thus, we consider our estimates of prey

131 consumption to be appropriately conservative.

132 Comparisons with Published Diet Data. — We searched the available literature for

133 published Malaclemys diet data from other populations that met the following criteria: 1) Fecal

134 analysis was the primary method of sample collection, 2) During fecal collection, individuals

135 were housed in separate containers so PFO could be calculated for each individual’s prey, and

136 3) Diet data were obtained primarily from adult females collected in the summer. We included

137 data from Denton et al. (2016) even though 11 of the 30 adult females they sampled were

138 collected in either January or September. We re-categorized samples into major taxonomic

139 groups (Plantae, Bivalvia, Gastropoda, Crustacea, Algae, Insecta, Gnathostomata, Annelida,

140 Bryozoa/Porifera, and Invertebrate eggs) as necessary to facilitate inter-populational

141 comparisons. For example, 4 studies (Butler et al. 2012; Tulipani 2013; Denton et al. 2016;

142 Herrel et al. 2018) lumped Plants and Algae into a single category, and only 1 other

143 (Outerbridge et al. 2017) reported sediment, as we did. We assume that sediment and sand

144 were ignored in the other studies.

145 Statistical Analyses. — Percent Frequency of Occurrence of prey items from our inter-

146 annual data and from studies meeting all criteria were compared to our JB results using 2

147 quantitative methods for measuring niche overlap: Pianka’s (1973) symmetric equation and the

148 Morisita-Horn equation (Morisita 1959; Horn 1966). These 2 methods for measuring niche

149 overlap have been well explored elsewhere (i.e., Smith and Zaret 1982; Winemiller and Pianka

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150 1990; Cortés 1997; Barwell et al. 2015) and have been used successfully in studies of a wide

151 variety of taxa (i.e., Pianka’s equation: Driscoll and Miranda 1999; Bulté et al. 2008; Crawford et

152 al. 2009; Durso et al. 2013; Barwell et al. 2015; Bonato et al. 2018; Morisita-Horn: Bergman and

153 Krebs 1993; Young and Winn 2003; Jaquemet et al. 2011; Mablouké et al. 2013; Estupiñán-

154 Montaño et al. 2018). Although the overlap formula has been traditionally used for assessing

155 similarity in resource use by sympatric species, it is just a similarity index and therefore can also

156 be confidently used for assessing similarities in resource use of distinct species or populations

157 inhabiting different localities. Both approaches perform well with PFO data (references above),

158 and both are easily employed using modern software that performs randomized bootstrapping

159 techniques to produce artificial datasets that would be expected in the absence of underlying

160 structure, which facilitates statistical comparisons. The Morisita-Horn test is particularly suited

161 to small data sets, because rare species (whether missing or present) have a negligible effect on

162 test results (Jost et al. 2011; Barwell et al. 2015), whereas the Pianka equation with a

163 scrambled-zero algorithm is particularly successful at revealing underlying prey use patterns

164 (Winemiller and Pianka 1990). Therefore, we considered the use of the 2 methods as a

165 potential test of whether our sample sizes were adequate.

166 We used Pianka’s (1973) symmetric equation to calculate the overall similarity of the

167 prey consumption patterns between years and between our combined (all years) data and data

168 from other studies. Its formula is Ojk = ∑ni pijpik /sqrt(∑n

i pij2∑n

i pik2) where n is the number of prey

169 categories, pij is the proportion of prey item i in 1 year (or in 1 study when comparing 1 study to

170 another) and pik is the proportion of prey item i in another year (or in another study when

171 comparing 1 study to another). O values are non-parametric and vary between 0.0 (no overlap)

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172 and 1.0 (total overlap).

173 To test whether the different Pianka O values of dietary similarity were significantly

174 different, first we used the R package ecosimR to calculate Pianka’s overlap (O) value between

175 data from each year of the JB study, then for all years combined against each of the datasets

176 from the intra-specific studies we compared. We next calculated P values associated with each

177 pairwise comparison by creating 100,000 Monte Carlo simulations with a scrambled-zero

178 algorithm of each diet matrix with Lawlor’s (1980) random RA3 algorithms. The RA3 procedure

179 conserves niche breadth for each seasonal sample at each simulation but destroys the resource

180 use matrix’s zero structure (Gotelli and Graves 1996). A value of Pianka’s equation was

181 calculated for each of these simulated data matrices, and the observed value was compared to

182 this population of simulated overlap values with appropriate correction for multiple

183 comparisons. For each pair of populations compared, if the observed O value was greater than

184 95% of the population of O values from the Monte Carlo simulations, we concluded that the 2

185 populations were more similar in overall diet composition than expected by chance. If the

186 observed O value was less than 95% of the population of O values from the Monte Carlo

187 simulations, we concluded that the populations were more different in overall diet composition

188 than expected by chance. We used Bonferroni corrections to adjust for multiple comparisons.

189 We also calculated the Morisita-Horn’s Index (Morisita 1959; Horn 1966) for the

190 comparisons of our inter-annual data and our combined data to data from studies meeting our

191 criteria, as described above. Its formula is Cλ = 2(∑ni pxipyi /(∑n

i pxi2 + ∑n

i pyi2)) where Cλ is the

192 Morisita-Horn index between species x and y, Pxi is the proportion of prey i relative to the total

193 prey consumed by predator x, Pyi is the proportion of prey i relative to the total prey consumed

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194 by y, and n is the total number of prey. M-H values range from 0 to 1, as with Pianka’s equation

195 above: M-H values close to zero indicate large dietary differences while values close to 1

196 indicate complete diet overlap. We calculated M-H values using the mh function in the ‘divo’

197 package of R, calculating 100,000 bootstrap values. We interpreted the significance of output

198 as described above, except this routine generated confidence intervals, for which we used

199 Bonferroni corrections to adjust for multiple comparisons.

200 We compared the resulting Pianka O and M-H values indicating the degree of diet

201 overlap between the overall diet data from JB and the data from each of the other 6 published

202 Malaclemys diet studies data using 2 measures of distance from our Ruler’s Bar study site, to

203 measure whether dissimilarity increased with increasing geographic distance. Our first distance

204 measure was the straight-line distance between each site and Ruler’s Bar, in Jamaica Bay, New

205 York; our second measure was the distance as traced along the shore line from Jamaica Bay,

206 New York. We used standard linear regression to test for relationships between the diet

207 overlap measures and the geographic distance measures.

208 RESULTS

209 Fecal Analysis.— We collected 354 usable fecal samples from JB Diamondback terrapins

210 (Table 1). We assumed that all white shell fragments were soft-shelled clams even though

211 Baltic clams (Macoma baltica Linnaeus 1758) occur in JB and appear similar to soft-shelled

212 clams. However, all complete clam shells with the diagnostic hinge structures were identifiable

213 as soft-shelled clams, so we assumed that similar shells lacking a hinge fragment were soft-

214 shelled clams as well. We also lumped Crabs together because some fragments could not be

215 identified to species. Those that could be identified were flatback mud crabs (Eurypanopeus

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216 depressus S. I. Smith 1869), lady crabs (Ovalipes ocellatus J. F. W. Herbst 1799), Atlantic sand

217 fiddler crabs (Uca pugilator Bosc 1802), and European green crabs (Carcinus maenas Linnaeus

218 1758). We lumped insects into a single category Insecta, as many could not be identified to

219 species. Those that could be identified were from orders Coleoptera (family Dytiscidae) and

220 Hemiptera Heteroptera (family Saldidae). We found Atlantic horseshoe crab eggs and algae

221 containing invertebrate egg masses; these have not been reported in previous Diamondback

222 terrapin diet studies.

223 In 2008 Atlantic ribbed mussels and amethyst gem clams had the highest PFOs, but in

224 2009 and 2010, sea lettuce and soft-shelled clams occurred most frequently (Table 1). Plant

225 leaf/stems was the highest PFO category in the remaining years (2011-14). When all fecal

226 sample data were combined over the 7-year study, the prey items with the highest PFO were

227 Plant leaf/stems (57.6%) and grass (38.1%), and soft-shelled clams (44.19%) (Table 1). Thus, the

228 diets of these terrapins appear to be composed largely of plants and algae. Crabs and Bivalves

229 (Atlantic ribbed mussels, amethyst gem clams, and especially soft-shelled clams) are important

230 in some years, but generally animal prey did not have high PFO.

231 Our analyses using Pianka’s O values to test for inter-annual diet overlap showed that

232 overall diet composition was significantly more similar than expected by chance in 5 of the 21

233 year-by-year comparisons (2009 vs. 2010, 2009 vs. 2014, 2010 vs. 2014, 2011 vs.2014, and 2013

234 vs. 2014, Table 2). The other 16 comparisons were not distinguishable from random levels of

235 similarity, and no pair-wise comparisons were significantly different by this measure. Our

236 analyses using the Morisita-Horn’s Index to test for inter-annual diet overlap showed that

237 overall diet compositions were not distinguishable from random levels of similarity in any of the

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238 21 year-to-year comparisons (Table 2).

239 Comparisons with Published Malaclemys Diet Data.— We located 6 studies that met our criteria

240 (see above) for comparison: Butler et al. (2012); Tulipani (2013); Denton et al. (2016); Alleman

241 and Guillen (2017); Outerbridge et al. (2017); and Herrel et al. (2018). Our analyses using

242 Pianka’s O values to test for inter-population diet overlap between JB and other Malaclemys

243 studies showed that diet composition was significantly more similar than expected by chance in

244 the 2 studies (Herrel et al. (2018): Long Island Sound, NY and Tulipani (2013): Chesapeake Bay,

245 VA) that were geographically closest to our site in Jamaica Bay. The comparisons of JB diet data

246 with similar data from 4 other sites were not significantly different from chance (Table 3). Our

247 analyses using the Morisita-Horn’s Index to test for inter-population diet overlap showed that

248 overall diet compositions were not different from values than expected by chance in any of the

249 6 site-by-site comparisons using this measure (Table 3).

250 We found no significant relationships between the diet overlap measures and the

251 geographic distance measures. Straight-line distance between each site and Ruler’s Bar (NY)

252 explained only 15.6% of the variance (R2 = 0.156, F(1,4) = 0.740, P = 0.438) in Pianka O values,

253 and only 12.4% of the variance (R2 = 0.124, F(1,4) = 0.566, P = 0.494) in M-H values. Shoreline

254 distance between each site and Ruler’s Bar (NY) explained only 0.9% of the variance (R2 = 0.009,

255 F(1,4) = 0.038, P = 0.856) in Pianka O values, and only 1.1% of the variance (R2 = 0.011, F(1,4) =

256 0.044, P = 0.844) in M-H values.

257 DISCUSSION

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258 We used our own long-term diet data from a single site in combination with diet studies

259 from 6 other widely-spaced populations to test for patterns of prey use in a turtle species with

260 an exceptionally large range. To our knowledge this is the first such tests for any turtle species.

261 Temporal variation in diet.— Our statistical tests found that despite some obvious inter-

262 annual fluctuations in consumption of particular prey species, Jamaica Bay Diamondback

263 terrapin diets were highly similar over 7 consecutive years. These findings indicate that single-

264 year studies may often be adequate to characterize Diamondback Terrapin diets, which is

265 reassuring given that so many diet studies are short-term.

266 Unfortunately, there are no data on prey species abundance during this time, so we

267 cannot speculate whether the minor fluctuations we observed were due to changes in prey

268 abundance or predator choice. However, JB may have undergone a recent ecosystem state

269 change influencing Diamondback terrapin prey abundance and distribution. Extirpation of

270 oysters in the past century, the shift from a hard-bottom substrate to a soft-bottom substrate,

271 and the dramatic loss of coastal and inner salt marshes (Hartig et al. 2002; Mackenzie Jr. 2005;

272 Campbell et al. 2017) likely caused changes to abundance and distribution of Diamondback

273 terrapin prey species that inhabited oyster beds. Studies from elsewhere in the Diamondback

274 terrapin range have shown that artificial or restored oyster reefs can be as successful as natural

275 reefs for providing habitats for high densities of Atlantic ribbed mussels, common mud crabs,

276 flatback mud crabs, soft-shelled clams, and amethyst gem clams (Meyer and Townsend 2000;

277 Rodney and Paynter 2006), all of which Diamondback terrapins consume in JB. Researchers are

278 investigating the potential for reintroduction of eastern oysters, bay scallop (Argopecten

279 irradians Lamarck 1819) and eelgrass (Zostera marina Linnaeus) beds to restore JB native plant

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280 and animal communities (Frame, pers. comm.); Diamondback terrapin diets should be

281 monitored during these restoration projects to explore whether diets change as available prey

282 diversity changes.

283 Diet analyses can be used to indicate the microhabitats in which Diamondback terrapins

284 feed, which are otherwise poorly known. JB Diamondback terrapins most commonly ate

285 Atlantic ribbed mussels, amethyst gem clams, soft-shelled clams and sea lettuce. Although

286 detailed invertebrate distributions have not been studied in JB, soft-shelled clams typically bury

287 themselves in soft coastal and marsh-edge sediments (Zwarts and Wanink 1989) and are found

288 throughout JB (Franz, pers. comm.). Atlantic ribbed mussels embedded themselves in and

289 amongst salt marsh sediments, often attached to smooth cordgrass stalks in the upper half of

290 the inter-tidal zone (Bertness 1980). Sea lettuce is abundant throughout JB (RLB, unpub. data).

291 Diamondback terrapins may feed on sea lettuce and soft-shelled clams throughout much of JB,

292 and may move into intertidal, smooth cordgrass-dominated habitats where Atlantic ribbed

293 mussels, amethyst gem clams, and crabs are found. Kumiga (2004) and Palmer and Cordes

294 (1988) also suggested that Diamondback terrapins move into intertidal areas to feed.

295 JB Diamondback terrapins eat far more plant material and algae than has generally been

296 reported for terrapins elsewhere; only Tulipani (2013) was comparable. This may be because JB

297 salt marshes, and therefore Diamondback terrapin prey availability, are affected by sea level

298 rise and pollution. Local sea level rise within JB is higher than the global average (Hartig et al.

299 2002) and urban pollution, specifically nitrogen loading, has also been linked to current salt

300 marsh loss and the growth of sea lettuce (Odum et al. 1984; Hanson and Lindh 1993; Mackenzie

301 2005; Ehrenfeld 2008). Areas of JB that once had dense stands of smooth cordgrass are now

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302 covered with sea lettuce (Hartig et al. 2002) and dense clusters of Atlantic ribbed mussel are

303 now common, attached to the bases of remaining smooth cordgrass stems (Hartig et al. 2002).

304 These changes might be responsible for our finding that JB Diamondback terrapins consume

305 these 2 species far more heavily than do Diamondback terrapin populations elsewhere. The

306 expansion of sea lettuce also dramatically reduces the number of macroinvertebrates on

307 sediment surfaces in JB (Franz and Freidman 2002). Studies of nearby New Jersey estuaries

308 have found similar effects of sea lettuce mat expansion on populations of copepods,

309 polychaetes, amethyst gem clams, Eastern mudsnails, and soft-shelled clams (MacKenzie 2000;

310 MacKenzie and McLaughlin 2000), all of which are important prey items for Diamondback

311 terrapins. Because JB is rapidly losing salt marshes (Hartig et al. 2002; National Park Service

312 2007; Campbell et al. 2017), it is therefore likely that some Diamondback terrapin prey species

313 are decreasing in abundance. For example, rough periwinkles, which typically live in smooth

314 cordgrass marshes, and are consumed by Diamondback terrapins in nearby Oyster Bay NY

315 (Herrel et al. 2017) are not abundant in JB (G. Frame pers. comm., D. Franz pers. comm.).

316 Between population diet comparisons.— Although previous Diamondback terrapin diet

317 studies (e.g., Tucker et al. 1995; Spivey 1998; and Butler et al. 2006) provided valuable

318 information, they reported diet data from fecal and/or stomach content analyses as percent

319 volume and/or percent mass, which are highly variable according to prey type. This is especially

320 problematic with prey items such as sea lettuce, carrion, and hard-shelled clams and small

321 snails. Additionally, Tucker et al. (1995) and Spivey (1998) developed similarity indices with

322 arbitrary significance values which cannot be analyzed statistically. We were also unable to

323 directly compare our results to either Tucker et al. (1995) or Spivey (1998) because fecal

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324 collections from different individuals were pooled (Tucker, pers. comm.; Spivey, pers. comm.).

325 Using 2 traditional statistical techniques enhanced with bootstrapping to create null

326 models, we found a pattern of few significant comparisons among long-term inter-annual

327 (same population) and inter-populational diet comparisons. This is surprising because the

328 techniques we used have detected general inter-seasonal and intersexual diet differences

329 between and within other turtle species (Luiselli 2006a; 2008a; Del Vecchio et al. 2011; Luiselli

330 et al. 2011) as well as lizards (Lorenzo and Luiselli 2007; Luiselli 2008b) and snakes (Luiselli

331 2006b; Akani et al. 2008) and many other species (listed above). Although diamondback

332 terrapin diets vary at the specific levels according to local prey availability, we suspect our

333 findings of overall similarity are the result of the fact that at fairly high taxonomic levels (i.e.,

334 Gastropods), Diamondback Terrapin diets are conservative and reflect whatever prey is found

335 in their brackish-water habitats. This suggests that Diamondback Terrapins are diet generalists,

336 readily attempting novel prey (e.g., Bulte and Blouin-Demers 2008) and may be limited by

337 factors other than specific prey species availability. Future work exploring the factors that limit

338 their distribution into lower salinity environments, such as upstream into the many rivers

339 whose estuaries they inhabit, could indicate the factors that limit this wide-spread species.

340 Acknowledgements. —P. Lindeman was extraordinarily generous with his time and

341 advice. We thank D. Franz and W. Miller for help identifying prey species and C. Peterson, J.

342 Williams, D. Franz, and two anonomous reviewers for reviewing this manuscript. M. Denton,

343 and M. Outerbridge graciously answered important clarifying questions about their published

344 data. Special thanks go to National Park Service employees, especially J. Browning, G. Frame, J.

345 Gracey and P. Rafferty for supplying space and resources for this project. A. Kanonik, G.

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346 Mnkande, L. Peyer, and Y. Weiss provided valuable field and lab assistance. This work was

347 approved by Hofstra University’s Institutional Animal and Use Committee and conducted under

348 New York State License to Collect and Possess #383 and National Park Service permit #GATE-

349 0039.

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350 Literature Cited

351 Akani, G. C., Luiselli, L., Eniang, E. A., and Rugiero, L. 2008. Life in the tropical suburbs: food type

352 partitioning among sympatric African house snakes of the genus Lamprophis (Colubridae). Ital.

353 J. Zool. 75:395-399.

354 Alleman, B.J., and Guillen, G.J. 2017. Prey availability and diet analysis of Texas Diamond-

355 Backed Terrapin (Malaclemys terrapin littoralis). Chelonian Conserv. Biol. 16:52-61.

356 Allen, J. F., and Littleford, R. A. 1955. Observations on the feeding habits and growth of

357 immature diamondback terrapins. Herpetologica, 11:77-80.

358 Barwell, L. J., Isaac, N.J.B., and Kunin, W.E. 2015. Measuring β-diversity with species abundance

359 data. J. Anim. Ecol. 84.4: 1112-1122.

360 Bergman, C. M., and Krebs, C. J. 1993. Diet overlap of collared lemmings and tundra voles at

361 Pearce Point, Northwest Territories. Can. J. Zool. 71:1703-1709.

362 Bertness, M. D. 1980. Growth and mortality in the ribbed mussel Geukensia demissa. Veliger,

363 23:62-69.

364 Bonato, K. O., Burress, E. D., Fialho, C. B., and Armbruster, J.W. 2018. Resource partitioning

365 among syntopic Characidae corroborated by gut content and stable isotope analyses.

366 Hydrobiologia, 805:311-324.

367 Bouchard, S. S., and Bjorndal, K. A. 2006. Ontogenetic diet shifts and digestive constraints in the

368 omnivorous freshwater turtle Trachemys scripta. Physiol. Biochem. Zool. 79:150-158.

369 Bulté, G., Gravel, M-A., and Blouin-Demers, G. 2008. Intersexual niche divergence in northern

370 map turtles (Graptemys geographica): the roles of diet and habitat. Can. J. Zool. 86:1235-1243.

Page 19 of 34



Draft

371 Bulte, G., and Blouin-Demers, G. 2008. Northern map turtles (Graptemys geographica) derive

372 energy from the pelagic pathway through predation on zebra mussels (Dreissena polymorpha).

373 Freshw. Biol. 53.3: 497-508.

374 Butler, J. A., Seigel, R. A., and Mealey, B. K. 2006. Malaclemys terrapin - Diamondback

375 terrapin. In: Biology and Conservation of Florida Turtles. Edited by P. Meylan. Chelonian Res.

376 Monogr. 3:279-295.

377 Butler, J.A., Heinrich, G.L., and Mitchell M.L. 2012. Diet of the Carolina Diamondback Terrapin

378 (Malaclemys terrapin centrata) in Northeastern Florida. Chelonian Conserv. Biol. 11:124-128.

379 Campbell, W., A. Y., Christiano, M. and Stevens, S. 2017. Salt Marsh Monitoring in Jamaica Bay,

380 New York from 2003 to 2013: A Decade of Change from Restoration to Hurricane Sandy.

381 Remote Sens. 2017, 9:1-20 doi:10.3390/rs9020131.

382 Congdon, J. D., Gotte, S. W., and McDiarmid, R. W. 1992. Ontogenetic changes in habitat use by

383 juvenile turtles, Chelydra serpentina and Chrysemys picta. Can. Field-Nat. 106:241-248.

384 Cortés, E., 1997. A critical review of methods of studying fish feeding based on analysis of

385 stomach contents: application to elasmobranch fishes. Can. J. Fish. Aquat. Sci. 54:726-738.

386 Crawford, J. A., Shepard, D. B., and Conner, C. A. 2009. Diet composition and overlap between

387 recently metamorphosed Rana areolata and Rana sphenocephala: implications for a frog of

388 conservation concern. Copeia, 2009:642-646.

389 Del Vecchio, S., Burke, R. L., Rugiero, L., Capula, M., and Luiselli, L. 2011. Seasonal changes in

390 the diet of Testudo hermanni in central Italy. Herpetologica, 67:236-249.

Page 20 of 34



Draft

391 Denton, M.J., Hart, K.M., Demopoulos, A.W.J., Oleinik, A., and Baldwin, J.D. 2016. Diet of

392 Diamondback Terrapins (Malaclemys terrapin) in subtropical mangrove habitats in south

393 Florida. Chelonian Conserv. Biol. 15:54-61.

394 Driscoll, M. P., and Miranda, L. E. 1999. Diet ecology of yellow bass, Morone mississippiensis, in

395 an oxbow of the Mississippi River. J. Freshw. Ecol. 14:477-486.

396 Durso, A. M., Willson, J. D., and Winne, C. T. 2013. Habitat influences diet overlap in aquatic

397 snake assemblages. J. Zool. (Lond.) 291:185-193.

398 Ehrenfeld, J. E. 2008. Exotic invasive species in urban wetlands: environmental correlates and

399 implications for wetland management. J. Appl. Ecol. 45:1160-1169.

400 Erazmus, K.R. 2012. Diet and prey choice of female Diamond-backed Terrapins (Malaclemys

401 terrapin) in Jamaica bay, New York. M.S. thesis. Hofstra University, Hempstead, N.Y.

402 Ernst, C.H. and Lovich, J.E. 1989. Turtles of the United States and Canada. 2nd Ed. The John

403 Hopkins University Press. Baltimore, MD.

404 Estupiñán-Montaño, C., Pacheco-Triviño, F., Cedeño-Figueroa, L. G., Galván-Magaña, F., and

405 Estupiñán-Ortiz, J. F. 2018. Diet of three shark species in the Ecuadorian Pacific, Carcharhinus

406 falciformis, Carcharhinus limbatus and Nasolamia velox. J. Mar. Biol. Assoc. U. K. 98(4) 927-935

407 doi:10.1017/S002531541600179X.

408 Franz, D. R., and Friedman, I. 2002. Effects of a macroalgal mat (Ulva lactuca) on estuarine sand

409 flat copepods: an experimental study. J. Exp. Mar. Biol. Ecol. 271:209-226.

410 Gosner, K. L. 1978. A Field Guide to the Atlantic Seashore. Houghton Mifflin, Boston, MA.

411 Gotelli, N. J., and Graves, G. R. 1996. Null Models in Ecology. Smithsonian Institution,

412 Washington, DC.

Page 21 of 34



Draft

413 Hanson, H., and Lindh, G. 1993. Coastal erosion-An Escalating environmental threat. Ambio,

414 22:188-195.

415 Hart, D. R. 1983. Dietary and habitat shift with size of red-eared turtles (Pseudemys scripta) in a

416 southern Louisiana population. Herpetologica, 39:285-290.

417 Hartig, E. K., Gornitz, V., Kolker, A., Mushacke, F., and Fallon, D. 2002. Anthropogenic and

418 climate-change impacts on salt marshes of Jamaica Bay, New York City. Wetlands, 22:71-89.

419 Herrel, A., Petrochic, S., and Draud, M. 2018. Sexual dimorphism, bite force and diet in the

420 diamondback terrapin. J. Zool. (Lond.) 304:217-224.

421 Hildebrand, S. F. 1928. Review of the experiments on artificial culture of the diamond-back

422 terrapin. Bulletin of the United States Bureau of Fisheries, 45:25-70.

423 Holland, A. F., Shaughnessy, A. T., and Hiegel, M. H. 1987. Long-term variation in mesohaline

424 Chesapeake Bay macrobenthos: spatial and temporal patterns. Estuaries, 10:227-245.

425 Horn, H.S. 1966. Measurement of overlap in comparative ecological studies. Am. Nat. 100:419-

426 424.

427 Iriarte, J.A., Franklin, W.L., Johnson, W.E., and Redford, K. H. 1990. Biogeographic variation of

428 food habits and body size of the America puma. Oecologia, 85:185-190.

429 Jaquemet, S., Potier, M., and Ménard, F. 2011. Do drifting and anchored Fish Aggregating

430 Devices (FADs) similarly influence tuna feeding habits? A case study from the western Indian

431 Ocean. Fisheries Research, 107:283-290.

432 Jost, L., Chao, A., and Chazdon, R.L. 2011. Compositional similarity and β (beta) diversity. In

433 Biological Diversity. Edited by A.E. Magurran and B.J. McGill. Oxford University Press. pp.66-

434 84.

Page 22 of 34



Draft

435 Kemp, W. P., and Boynton, W. R. 1984. Spatial and temporal coupling of nutrients inputs to

436 estuarine primary production: the role of particulate transport and decomposition. Bull. Mar.

437 Sci. 35:242-247.

438 Kumiga, B. 2004. Tidal and seasonal movements of an intertidal tertiary consumer, the

439 diamondback terrapin (Malaclemys terrapin). M.Sc. thesis, Long Island University, Brookville,

440 N.Y.

441 Lawlor, L. R. 1980. Structure and stability in natural and randomly constructed competitive

442 communities. Am. Nat. 116:394-408.

443 Lindeman, P. V. 2013. The map turtle and sawback atlas: Ecology, evolution, and conservation.

444 University of Oklahoma Press. Norman, OK.

445 Lorenzo, R., and Luiselli, L. 2007. Null model analysis of lizard communities in five urban parks

446 of Rome. Amphibia-Reptilia, 28:547-553.

447 Lozano, J., Moleón, M., and Virgós, E. 2006. Biogeographical patterns in the diet of the wildcat,

448 Felis silvestris Schreber, in Eurasia: factors affecting the trophic diversity. J. Biogeogr. 33:1076-

449 1085.

450 Luiselli, L. 2006a. Resource partitioning in the communities of terrestrial turtles: a review of the

451 evidences. Revue d'Ecologie: la Terre et la Vie, 61:353-365.

452 Luiselli, L. 2006b. Resource partitioning and interspecific competition in snakes: the search for

453 general geographic and guild patterns. Oikos, 114:193-211.

454 Luiselli, L. 2008a. Resource partitioning in freshwater turtle communities: a null model meta-

455 analysis of available data. Acta Oecologia, 34:80-88.

Page 23 of 34



Draft

456 Luiselli, L. 2008b. Do lizard communities partition the trophic niche? A worldwide meta-analysis

457 using null models. Oikos, 117:321-330.

458 Luiselli, L., Akani, G.C., Ebere, N., Rugiero, L., Vignoli, L., Angelici, F. M., Eniang, E.A., and

459 Behangana, M. 2011. Food habits of a pelomedusid turtle, Pelomedusa subrufa, in tropical

460 Africa (Nigeria): The effects of sex, body size, season, and site. Chelonian Conserv. Biol. 10:138-

461 144.

462 Luiselli, L., Eniang, E. A., and Akani, G. C. 2007. Non-random structure of a guild of geckos in a

463 fragmented, human-altered, African rainforest. Ecol. Res. 22:593-603.

464 Mablouké, C., Kolasinski, J., Potier, M., Cuvillier, A., Potin, G., Bigot, L., Frouin, P. and Jaquemet,

465 S. 2013. Feeding habits and food partitioning between three commercial fish associated with

466 artificial reefs in a tropical coastal environment. Afr. J. Mar. Sci. 35:323-334.

467 MacKenzie Jr., C. L. 2000. The abundances of small invertebrates in relation to sea lettuce, Ulva

468 lactuca, mats. Bull. New Jersey Acad. Sci. 45:13-17.

469 MacKenzie Jr., C. L. 2005. Removal of sea lettuce, Ulva spp., in estuaries to improve the

470 environments for invertebrates, fish, wading birds, and eelgrass, Zostera marina. Mar. Fish. Rev.

471 67:1-8.

472 MacKenzie Jr., C. L., and McLaughlin, S. 2000. Life history and habitat observations of softshell

473 clams Mya arenaria in northeastern New Jersey. J. Shellfish Res. 19:35-41.

474 Meyer, D. L., and Townsend, E. C. 2000. Faunal utilization of created intertidal eastern oyster

475 (Crassostrea virginica) reefs in the southeastern United States. Estuar. Coast. 23:34-45.

476 Morisita, M. 1959. Measuring of the dispersion and analysis of distribution patterns. Memoires

477 of the Faculty of Science, Kyushu University, Series E. Biology, 2: 215–235.

Page 24 of 34



Draft

478 National Park Service. 2007. An update on the disappearing salt marshes of Jamaica Bay, New

479 York. Jamaica Bay Watershed Protection Advisory Committee. Available from http://nbii-

480 nin.ciesin.columbia.edu/jamaicabay/jbwppac/JBAC_NPS_SaltMarshReport_080207.pdf.

481 Accessed 7 July 2018.

482 Odum, W. E., Smith, T. J., Hoover, J. K. III, and McIvor, C. C. 1984. The ecology of tidal

483 freshwater marshes of the United States East Coast: a community profile. U.S. Fish and Wildlife

484 Service, Washington, DC.

485 Outerbridge M.E., O’Riordan, R., Quirke, T., and Davenport, J. 2017. Restricted diet in a

486 vulnerable native turtle, Malaclemys terrapin (Schoepff), on the oceanic islands of Bermuda.

487 Amphibian & Reptile Conservation, 11: 25–35 (e134).

488 Palmer, W. M., and Cordes, C. L. 1988. Habitat suitability index models: diamondback terrapin

489 (nesting) - Atlantic coast. U.S. Fish and Wildlife Service Department. Biological Report,

490 82(10.151).

491 Parmenter, R. R., and Avery, H. W. 1990. The feeding ecology of the slider turtle. In Life History

492 and Ecology of the Slider Turtle. Edited by J. W. Gibbons. Smithsonian Inst. Press, Washington,

493 DC. pp. 257-266.

494 Petrochic, S. L. 2009. Feeding ecology of the northern diamondback terrapin, Malaclemys

495 terrapin terrapin. M.Sc. thesis, Long Island University, Brookville, N.Y.

496 Pianka, E. R. 1973. The structure of lizard communities. Annu. Rev. Ecol. Syst. 4:53-74.

497 Rodney, W. S., and Paynter, K. T. 2006. Comparisons of macrofaunal assemblages on

498 restored and non-restored oyster reefs in mesohaline regions of Chesapeake Bay

499 in Maryland. J. Exp. Mar. Biol. Ecol. 335:39-51.

Page 25 of 34



http://nbii-nin.ciesin.columbia.edu/jamaicabay/jbwppac/JBAC_NPS_SaltMarshReport_080207.pdf

http://nbii-nin.ciesin.columbia.edu/jamaicabay/jbwppac/JBAC_NPS_SaltMarshReport_080207.pdf

Draft

500 Roosenburg, W. M. and Kennedy, V. S. (Editors). 2018. Ecology and Conservation of the

501 Diamondback Terrapin. Johns Hopkins University Press. In press.

502 Roosenburg, W. M., Haley, K. L., and McGuire, S. 1999. Habitat selection and movements of

503 diamondback terrapins, Malaclemys terrapin, in a Maryland estuary. Chelonian Conserv. Biol.

504 3:425-429.

505 Rothschild, B. J., Ault, J. S., Goulletquer, P., and Héral, M. 1994. Decline of the Chesapeake Bay

506 oyster population: a century of habitat destruction and overfishing. Mar. Ecol. Prog. Ser.

507 111:29-39.

508 Rulison, E.L., Luiselli, L., and Burke, R.L. 2012. Relative impacts of habitat and geography on

509 raccoon diets. Am. Midl. Nat. 168:231-246.

510 Simpfendorfer, C.A., Goodreid, A.B., and McAuley, R.B. 2001. Size, sex and geographic variation

511 in the diet of the tiger shark, Galeocerdo cuvier, from Western Australian waters. Environ. Biol.

512 Fishes, 61:37-46.

513 Smith, E.P. and Zaret, T.M. 1982. Bias in estimating niche overlap. Ecology, 63:1248-1253.

514 Spivey, P. B. 1998. Home range, habitat selection, and diet of the diamondback terrapin

515 (Malaclemys terrapin) in a North Carolina estuary. M.Sc. Thesis, Univ. of Georgia, Athens, GA.

516 TTWG (Turtle Taxonomy Working Group). Rhodin, A.G.J., Iverson, J.B., Bour, R. Fritz, U.,

517 Georges, A., Shaffer, H.B., and van Dijk, P.P. 2017. Turtles of the World: Annotated Checklist

518 and Atlas of Taxonomy, Synonymy, Distribution, and Conservation Status (8th Ed.). In

519 Conservation Biology of Freshwater Turtles and Tortoises: A Compilation Project of the

520 IUCN/SSC Tortoise and Freshwater Turtle Specialist Group. Edited by A.G.J. Rhodin, J.B. Iverson,

Page 26 of 34



Draft

521 P.P. van Dijk, R.A. Saumure, K.A. Buhlmann, P.C.H. Pritchard, and R.A. Mittermeier. Chelonian

522 Research Monographs, 7:1–292. doi: 10.3854/crm.7.checklist.atlas.v8.2017.

523 Tucker, A.D., Burke, R.L., and Tulipani, D.C. 2018. Foraging ecology and habitat choice. In

524 Ecology and Conservation of the Diamondback Terrapin. Edited by W.M. Roosenburg and V.S.

525 Kennedy. Johns Hopkins University Press. Chapter 11. In press.

526 Tucker, A. D., Fitzsimons, N. N., and Gibbons, J. W. 1995. Resource partitioning by the estuarine

527 turtle Malaclemys terrapin: trophic, spatial, and temporal foraging constraints. Herpetologica,

528 51:167-181.

529 Tulipani, D.C. 2013. Foraging ecology and habitat use of the northern diamondback terrapin

530 (Malaclemys terrapin terrapin) in southern Chesapeake Bay. Ph.D. dissertation. The College of

531 William and Mary in Virginia, Williamsburg, VA.

532 Whelan, C. J., Brown, J. S., Schmidt, K. A., Steele, B. B., and Willson, M.F. 2000. Linking

533 consumer-resource theory and digestive physiology: application to diet shifts. Evol. Ecol. Res.

534 2:911-934.

535 Winemiller, K. O., and Pianka, E. R. 1990. Organization in natural assemblages of desert lizards

536 and tropical fishes. Ecol. Monogr. 60:27-55.

537 Young, R.F. and Winn, H.E.. 2003. Activity patterns, diet, and shelter site use for two species of

538 moray eels, Gymnothorax moringa and Gymnothorax vicinus, in Belize. Copeia, 2003:44-55.

539 Zwarts, L., and Wanink, J. 1989. Siphon size and burying depth in deposit- and

540 suspension-feeding benthic bivalves. Mar. Biol. 100:227-240.

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541 Table 1. Percent Frequency of Occurrence of Ruler’s Bar (NY) diamondback terrapin

542 (Malaclemys terrapin Schoepf 1793) prey species in 2008-2014.

2008 2009 2010 2011 2012 2013 2014 combined

N 50 43 36 74 44 51 56 354

Plantae

Leaf/Stem 30.6 18.6 32.0 70.8 79.5 95.9 85.7 57.6

Seeds 8.3 18.6 7.0 9.7 4.5 14.9 3.6 8.3

Grass 11.1 34.9 36.0 43.1 27.3 51.4 66.1 38.1

Algae

Sea Lettuce (Ulva

lactuca)19.4 74.4 42.0 22.2 6.8 0.0 53.6 27.3

Algae (other than

sea lettuce)5.6 2.3 0.0 0.0 54.5 0.0 0.0 7.1

Bivalvia

Soft-Shelled Clam

(Mya arenaria)27.8 62.8 40.0 8.3 20.5 39.2 33.9 27.0

Atlantic Ribbed

Mussel (Geukensia

demissa)

33.3 2.3 6.0 16.7 18.2 2.7 12.5 9.0

Amethyst Gem

Clam (Gemma

gemma)

33.3 0.0 0.0 0.0 0.0 0.0 0.0 0.0

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Crustacea

Crab sp. 30.6 7.0 10.0 18.1 13.6 12.2 0.0 9.1

Ostracods 5.6 2.3 0.0 0.0 0.0 0.0 0.0 0.3

Gastropoda

Eastern Mudsnail

(Ilyanassa

obsoleta)

0.0 4.7 2.0 2.8 2.3 0.0 0.0 1.6

Periwinkle

(Littorina sp.)0.0 4.7 0.0 0.0 0.0 0.0 0.0 0.6

Convex Slippersnail

(Crepidula convexa)0.0 0.0 2.0 4.2 0.0 0.0 16.1 3.6

Annelids

Polychaete tube 0.0 0.0 2.0 0.0 0.0 0.0 0.0 0.2

Invertebrate eggs

Horseshoe Crab

Eggs (Limulus

polyphemus)

2.8 4.7 0.0 0.0 0.0 0.0 17.9 3.4

Invertebrate egg

masses5.6 2.3 0.0 0.0 0.0 0.0 0.0 0.3

Bryozoan/Porifera

Bryozoans 2.8 0.0 0.0 0.0 0.0 0.0 0.0 0.0

Insecta

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Insects 0.0 11.6 16.0 1.4 4.5 6.8 5.4 5.7

Unidentifiable

animal tissue13.9 20.9 8.0 2.8 2.3 74.3 17.9 17.8

Sand 16.7 47.9 7.0 9.7 4.5 48.6 46.4 23.5

543

544

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Table 2. All possible comparisons of Ruler’s Bar (NY) diamondback terrapin (Malaclemys terrapin Schoepf 1793) diet data 2008-2014

calculated using Pianka’s O and the Morisita-Horn Index. Significant findings (after Bonferroni correction for multiple comparisons)

are indicated with *.

Pianka’s O Morisita-Horn Index

O Value P (obs<null) P (obs>null) M-H Index Value 95% Confidence Interval

2008 vs. 2009 0.612 0.921 0.079 0.661 0.508-0.774

2008 vs. 2010 0.605 0.924 0.076 0.730 0.567-0.831

2008 vs. 2011 0.623 0.934 0.066 0.746 0.592-0.849

2008 vs. 2012 0.503 0.803 0.197 0.648 0.486-0.770

2008 vs. 2013 0.514 0.847 0.153 0.643 0.497-0.755

2008 vs. 2014 0.551 0.846 0.154 0.694 0.549-0.796

2009 vs. 2010 0.911 0.999 <0.001* 0.890 0.767-0.952

2009 vs. 2011 0.677 0.967 0.033 0.595 0.447-0.722

2009 vs. 2012 0.418 0.777 0.223 0.452 0.318-0.580

2009 vs. 2013 0.103 0.547 0.453 0.624 0.488-0.738

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2009 vs. 2014 0.881 0.999 <0.001* 0.801 0.667-0.889

2010 vs. 2011 0.799 0.997 0.003 0.794 0.629-0.897

2010 vs. 2012 0.499 0.849 0.151 0.656 0.489-0.784

2010 vs. 2013 0.582 0.934 0.061 0.705 0.550-0.815

2010 vs.2014 0.856 0.999 0.001* 0.884 0.751-0.942

2011 vs. 2012 0.547 0.917 0.083 0.823 0.680-0.907

2011 vs. 2013 0.572 0.923 0.077 0.771 0.642-0.856

2011 vs. 2014 0.325 0.999 <0.001* 0.870 0.746-0.934

2012 vs. 2013 0.377 0.757 0.243 0.715 0.581-0.811

2012 vs. 2014 0.454 0.813 0.187 0.738 0.602-0.831

2013 vs. 2014 0.700 0.986 0.014* 0.836 0.726-0.900

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Table 3. Comparisons of comparable diamondback terrapin (Malaclemys terrapin Schoepf 1793) diets elsewhere in the range with

Ruler’s Bar (NY) diet data, all years combined. Significant findings (after Bonferroni correction for multiple comparisons) are

indicated with *.

Pianka’s O Morisita-Horn Index

O value7 P (Obs ≤ null) P (Obs ≥ null) M-H Index Value 95% Confidence Interval

Long Island, NY1 0.737 0.989 0.011* 0.569 0.339-0.764

Chesapeake Bay, VA2 0.759 0.968 0.032* 0.643 0.523-0.746

North FL3 0.103 0.547 0.453 0.213 0.118-0.331

South FL4 0.095 0.283 0.719 0.287 0.173-0.423

Galveston Bay, TX5 0.733 0.922 0.078 0.589 0.450-0.707

Bermuda6 0.581 0.756 0.245 0.570 0.431-0.695

1: Herrel et al. 2018

2: Tulipani 2013

3: Butler et al. 2012

4: Denton et al. 2016

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5: Alleman and Guillen 2017

6: Outerbridge et al. 2017

7: O values indicate degree of similarity to Ruler’s Bar (NY) all years combined diet data

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Draft - University of Toronto T-Space · Draft Do diets vary over large spatial or temporal ranges? A test using inter-annual and inter-population data on Diamondback Terrapins (Malaclemys