Oecologia (2012) 168:977–988 DOI 10.1007/s00442-011-2158-y
P O P U L A T IO N E CO L O G Y - O R I G I N A L P A PE R
Incidental nest predation in freshwater turtles: inter- and intraspeciWc diVerences in vulnerability are explained by relative crypsis Aaron J. Wirsing · Julia R. Phillips · Martyn E. Obbard · Dennis L. Murray
Received: 27 April 2011 / Accepted: 28 September 2011 / Published online: 19 October 2011 © Springer-Verlag 2011
Abstract There has long been interest in the inXuence of predators on prey populations, although most predator–prey studies have focused on prey species that are targets of directed predator searching. Conversely, few have addressed depredation that occurs after incidental encounters with predators. We tested two predictions stemming from the hypothesis that nest predation on two sympatric freshwater turtle species whose nests are diVerentially prone to opportunistic detection—painted turtles (Chrysemys picta) and snapping turtles (Chelydra serpentina)—is incidental: (1) predation rates should be density independent, and (2) individual predators should not alter their foraging behavior after encountering nests. After monitoring nest survival and predator behavior following nest depredation over 2 years, we conWrmed that predation by raccoons (Procyon lotor), the primary nest predators in our study area, matched both predictions. Furthermore, cryptic C. picta nests were victimized with lower frequency than more detectable C. serpentina nests, and nests of both species were more vulnerable in human-modiWed areas where
Communicated by Joel Trexler. A. J. Wirsing (&) School of Forest Resources, University of Washington, Box 352100, Seattle, WA 98103, USA e-mail:
[email protected] J. R. Phillips · D. L. Murray Department of Biology, Trent University, 1600 West Bank Drive, Peterborough, ON K9J 7B8, Canada M. E. Obbard Wildlife Research and Development Section, Ontario Ministry of Natural Resources, Trent University, 2140 East Bank Drive, Peterborough, ON K9J 7B8, Canada
opportunistic nest discovery is facilitated. Despite apparently being incidental, predation on nests of both species was intensive (57% for painted turtles, 84% for snapping turtles), and most depredations occurred within 1 day of nest establishment. By implication, predation need not be directed to aVect prey demography, and factors inXuencing prey crypsis are drivers of the impact of incidental predation on prey. Our results also imply that eVorts to conserve imperiled turtle populations in human-modiWed landscapes should include restoration of undisturbed conditions that are less likely to expose nests to incidental predators. Keywords Chelydra serpentina · Chrysemys picta · Density-dependent predation · Human disturbance · Incidental predation
Introduction There is considerable and longstanding interest in the inXuence of predators on the dynamics and persistence of prey populations (Hairston et al. 1960; Sinclair 1989; Sinclair et al. 1998; Korpimäki et al. 2004). Most studies of predator–prey interactions have focused on prey species that are targets of directed predator searching and comprise a major portion of a predator’s annual or seasonal diet (Salo et al. 2010). Yet, generalist predators may also consume some prey items that are encountered unexpectedly and do not elicit directed searching behavior (Vickery et al. 1992; Schmidt et al. 2001). These incidental predation events are usually of limited importance to the predator, but under certain conditions they can depress and even locally extirpate prey populations (Vickery et al. 1992; Yanes and Suárez 1996; Wilson et al. 1998). Thus, additional scrutiny of the mechanisms underlying incidental predation can enhance
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our understanding of the potential impact of predators on prey population dynamics and help to explain numerical declines in prey. To date, studies of incidental predation have focused primarily on songbirds (e.g., Vickery et al. 1992; Yanes and Suárez 1996; Schmidt and Ostfeld 2003), leading to calls for broader taxonomic examination of this phenomenon (e.g., Schmidt et al. 2001; Schmidt 2004). Moreover, few past studies have contrasted patterns of incidental predation on sympatric prey with a shared opportunistic predator (but see Schmidt and Whelan 1998 for an example), slowing the formulation of a general framework for explaining diVerences in vulnerability to incidental predators in ecological communities. Accordingly, we asked whether, and to what extent, two sympatric freshwater turtle species—the painted turtle (Chrysemys picta) and the common snapping turtle (Chelydra serpentina)—experience incidental nest predation by raccoons (Procyon lotor). Species whose nests are subject to incidental predation by opportunistic feeders should exhibit two key characteristics. First, the rate at which nests are attacked should be density independent, given that predators should not be actively targeting speciWc areas where nest density is elevated (Best 1978; Martin and Roper 1988; Schmidt and Whelan 1998; Schmidt 2004). Second, nest encounters should not alter subsequent foraging behavior of individual predators [e.g., by inducing predators to return to predation sites in search of more nests (Vickery et al. 1992; Schmidt 2004; Pelech et al. 2010)]. Most previous tests for incidental nest predation have addressed only the Wrst prediction (Pelech et al. 2010). We addressed both by quantifying predation rates on painted and snapping turtle nests in relation to nest density and monitoring the behavior of individual predators following nest predation events. Painted and snapping turtles are both regular victims of nest predation (Tinkle et al. 1981; Christens and Bider 1987; Congdon et al. 1987; Robinson and Bider 1988). However, snapping turtle nests are likely more susceptible to predation for several reasons. One, snapping turtles tend to nest closer to the water’s edge (Congdon et al. 1987; Congdon and Gatten 1989), where the substrate is sandy and nest visibility and predation risk should be higher (Kolbe and Janzen 2002; Marchand and Litvaitis 2004). Two, snapping turtles disturb the soil surface at nests to a greater extent than painted turtles, leaving more visual cues for nest detection (Strickland et al. 2010). Three, snapping turtles often nest at twilight or at night, meaning that attractive olfactory cues emitted by their fresh nests are most potent when many nest predators are more active (Legler 1954; Burger 1977; Tinkle et al. 1981; Christens and Bider 1987), whereas painted turtles nest mainly diurnally (Congdon and Gatten 1989). Four, snapping turtle egg numbers and corresponding nest sizes are substantially larger than those for painted turtles (Robinson and Bider 1988), imply-
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Oecologia (2012) 168:977–988
ing that snapping turtle nests likely represent a more detectable visual and olfactory target for predators. Thus, we predicted that painted turtle nests would be attacked by predators with lower frequency than snapping turtle nests because they are more cryptic (Schmidt and Whelan 1998; Schmidt 2004). Given that the vulnerability of any particular nest to predation should correlate positively with its detectability (Wilhoft et al. 1979; Robinson and Bider 1988; Schmidt 1999, 2004), we also predicted that nests of both species in locations facilitating opportunistic discovery (e.g., highly visible locations) or characterized by relatively heavy predator traYc would be most likely to be depredated.
Materials and methods Study site The study was conducted during May–October 2004 and 2005 in Point Pelee National Park (PPNP), near Leamington, Ontario, Canada (41°57⬘N, 82°31⬘W). The park is a 15-km2 peninsula that functions as a closed system, with roughly 80% of its perimeter surrounded by Lake Erie and the remainder bordered by agricultural land (Browne 2003; Fig. 1). The park contains coastal marsh (68% of total park area), dry land forest (12%), savannah (9%), beach (5%), swamp thicket (4%), and swamp forest (2%). A 20-km beach surrounds the park and the northern and western sides are subject to high levels of anthropogenic disturbance; these areas experience heavy visitor Xow (up to 500,000 visitors/yea; Browne and Hecnar 2007), frequent automobile traYc, and routine habitat maintenance (e.g., mowing, tree trimming, etc.). Additionally, all anthropogenic structures (e.g., roads, trails, buildings, garbage cans, etc.) and human-deWned habitat edges are located in these areas. In comparison, the eastern side of the park experiences relatively little human disturbance. Thus, for the purposes of this study, we assumed that turtle nesting sites on the northern and western sides of the park were subject to human disturbance, and that those on the eastern side experienced negligible disturbance. Six species of turtles occur in PPNP (Browne and Hecnar 2007). Four are of conservation concern: spiny softshell (Apalone spinifera), Blanding’s turtle (Emydoidea blandingii), and eastern musk turtle (Sternotherus odoratus) are classiWed as Threatened and the northern map turtle (Graptemys geographica) is classiWed as Special Concern (Ontario Ministry of Natural Resources 2011). We protected all detected nests of these four species using wire predator exclusion devices (Yerli et al. 1997), such that only nests of the other two species—painted and snapping turtles—functionally were exposed to predation risk.
Oecologia (2012) 168:977–988
Fig. 1 Kaplan–Meier survival estimates for painted turtle (Chrysemys picta) and common snapping turtle (Chelydra serpentina) nests in Point Pelee National Park, Ontario, Canada, during 2004–2005 relative to days since being laid. Species’ survival estimates are not proportional over time
Because >78% (n = 371) of nests we detected were deposited by painted and snapping turtles (the species of interest), we assumed that protecting the remainder did not have appreciable eVects on observed patterns of nest predation. Importantly, we found most nests (241 out of 292, 83%) of painted and snapping turtles in PPNP to be along the shoreline (i.e., within 100 m of water), and nest density for PPNP (131 nests/km2 in 2004, 191 nests/km2 in 2005) along the shoreline to be within the normal range for freshwater chelonians in central North America (e.g., Kolbe and Janzen 2002: 74–259 nests/km2 in national wildlife refuge habitat). Turtle nests in PPNP are potentially subject to predation by a variety of species including coyote (Canis latrans), red fox (Vulpes vulpes), striped skunk (Mephitis mephitis), and Virginia opossum (Didelphis virginiana). However, the primary predators of turtle nests in PPNP are raccoons (Browne and Hecnar 2007), which are generalist feeders known to forage intensively along freshwater shorelines (Llewellyn and Uhler 1952) and that commonly attack nests of a variety of freshwater chelonians (e.g., Petokas and Alexander 1980; Congdon et al. 1987; Marchand and Litvaitis 2004) and ground-nesting birds (e.g., Zoellick et al. 2004; Ellis et al. 2007). Raccoon densities in PPNP are higher than those that typify rural Ontario (Browne and Hecnar 2007). Nest searching and monitoring We conducted turtle nest searches twice daily throughout the nesting season (late-May to mid-July) in each year of study. Nests were located either by (1) monitoring nesting females encountered opportunistically (Bowen and Janzen 2005;
979
Rowe et al. 2005), (2) following turtle tracks in the nesting substrate (Butler et al. 2004), or (3) investigating disturbed soil in nesting areas (Doody et al. 2003). We conWrmed the presence of eggs by excavating nest substrate while wearing latex gloves, and returned substrate to its original condition immediately upon detecting eggs (Butler et al. 2004). Nest location was recorded using a GPS unit and marked using plastic Xagging tape placed »50 cm from each nest (Burke et al. 2005). Importantly, the presence of Xagging tape does not appear to increase the probability of nest predation by raccoons (Burke et al. 2005). All work was approved annually by the Trent University Animal Care Committee and conforms to standard guidelines for animal care. We estimate that intensity of daily searches allowed us to detect >85% of nests deposited during the study (based on Burger’s 1977 proportionality equation), and that our success at detecting nests 0 nests/m2 = 1
Broad-scale capture–recapture methods were used to estimate raccoon population densities within PPNP. Two distinct capture–recapture capture sessions (mid-spring, late-summer) were conducted each year, with 50 live traps distributed evenly throughout the park and separated by »500 m. Trapping intervals spanned 9 days with 4 days rest in between. We ear-tagged captured animals and released them at the point of capture. Trap distribution and density ensured that all resident mesopredators were potentially exposed to traps. Variable classiWcation We geo-referenced all nest locations and classiWed them according to habitat type (lawn, savannah, beach, dry forest, swamp forest, swamp thicket, marshland, and marsh water) from a 1:15,000 land cover vector for PPNP. Additional digitized features (roads, trails, buildings and parking lots) were superimposed on the land cover layer. We characterized each nest according to 14 independent variables (Table 1). First, we chose two temporal variables—year and date of oviposition (DATELAID)—because turtle nest predation rates have been shown to be time-sensitive (e.g., Kolbe and Janzen 2002; Bowen and Janzen 2005). The inXuence of nest density on predation was assessed using two density variables: DENSITY1 [density of nests within a given radius of the focal nest (nests/m2)], and DENSITY2 (density of nests depredated within the past three nights within the given radius). Nest densities were integrated daily within each nest buVer (buVer radii: 5 m, 25 m). Additionally, Moran’s I correlograms (with Bonferroni correction) served to assess scale-sensitive autocorrelation in nest predation dates, with nest pairs divided among 10-m intervals successively increasing to 100 m. Each successive distance interval represented the maximum Euclidean
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Day of oviposition (Julian date)
distance allowed between nest pairs in the interval, and each interval contained a minimum of 20 nest pairs. Because preliminary analyses did not reveal speciWc spatial trends with respect to nest predation (see “Results”), we tested density covariates at two spatial scales (buVer radii: 5 m, 25 m) that were potentially relevant in the context of turtle nest predation (see Burke et al. 1998; Marchand and Litavitis 2004). By assessing the eVect of nest density on predation in this way, we were able to discriminate between the distinct possibilities that (1) nest predation risk increases with density of depredated and living neighboring nests, and (2) nest predation risk increases with density of recently-depredated nests (deWned as nests that were destroyed within the past three nights). Three weather variables were selected because of their potential to inXuence nest detectability: mean daily temperature (TEMP; Bergin et al. 1997), rainfall on the day of nest deposition (RAINLAID; Bergin et al. 1997; Bowen and Janzen 2005), and daily rainfall amount (RAIN; Bergin et al. 1997; Bowen and Janzen 2005). We also considered Wve landscape variables with the potential to aVect rates of nest discovery: putative amount of local predator traYc (CORRIDOR; Fleury and Brown 1997), degree of human disturbance (DISTURBANCE; MarzluV et al. 1998; Schmidt and Whelan 1998, 1999), distance to water (WATERDIST), distance to vegetation edge (VEGDIST, Robinson and Bider 1988), and the amount of edge habitat near each nest (EDGEAMT; Vigallon and MarzluV 2005). We deWned predator travel corridors as unobstructed strips of land 0.375; mean condition number = 2.986), so all were used in the model building process. All predation analyses were conducted using STATA (www.stata.com). We used information theoretic methods to develop a set of best-Wt models for the species-speciWc and pooled analyses of nest predation. For both analyses, we Wrst individually modeled the relationships between each of the 14 independent variables and nest predation risk; all possible combinations of the signiWcant variables (P values 10.0 were considered to have no support (Anderson et al. 2000). Akaike weights (w) quantiWed the relative strength of selected models, and the strength of individual variables was indicated by cumulative weight
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(w). Model-averaged hazard ratios and unconditional standard errors also were calculated (Anderson et al. 2000). Nest age may be an important determinant of turtle nest predation risk (e.g., Burger 1977). We sought to model nest age by including it as a covariate in hazard models but, because most nests were detected within 24 h of being laid, inclusion of such a covariate was largely equivalent to our time variable (DATELAID). Accordingly, we examined the eVect of nest age graphically. We used the Lincoln–Petersen estimator in program MARK (White and Burnham 1999) to estimate raccoon population sizes (population sizes of other predators were not estimated because they contributed minimally to observed rates of nest depredation; see “Results”). Due to the short length of trapping intervals, we assumed population closure during each 22-day trapping session. Population size estimates §95% CI within the park were divided by 4.9 km2 (area of dry land in PPNP) and 15.0 km2 (total area of PPNP including wetlands) to provide a range of population densities. Finally, the amount of anthropogenic disturbance was found to inXuence nest predation risk (see “Results”). Thus, we used Chi-square analyses to compare (1) the proportion of nests depredated by raccoons (vs. other predators), (2) estimates of raccoon abundance (prior to, during, and after the turtle nesting season), and (3) the proportion of raccoon recaptures at depredated nest sites relative to the proportion of recaptures during capture– recapture sessions in disturbed and undisturbed portions of the study system.
Results We monitored 94 painted turtle nests (2004: 44; 2005: 50) and 198 snapping turtle nests (2004: 81; 2005: 117) during the course of the study. Predation was the primary cause of nest mortality (98%; n = 225). Nest age had a strong inXuence on nest predation risk; most (74% painted turtle; 82% snapping turtle) nest predation occurred within 1 day of nest deposition, with 98% of all depredated nests being destroyed within 5 days of deposition. Baseline nest survival rates decreased by approximately 55 and 78% within the Wrst 5 days post-laying for painted turtles and snapping turtles, respectively, but were relatively stable thereafter (Fig. 1). Raccoons were the principal predator of turtle nests in PPNP, with 64.8% (n = 54) of painted turtle nest predation events being attributable to raccoons, compared to 7.4% for coyotes, 1.8% for skunks, and 26.0% for unknown predators. At snapping turtle nests, raccoons were apparently responsible for 74.1% (n = 166) of predation events, compared to 1.2% for coyotes, 2.4% for skunks, 1.2% for opossums and 21.1% for unknown predators. We suspect that a
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Table 2 Cox proportional hazard models using one of 14 independent variables to predict predation risk of painted turtle (subjects = 94, depredations = 54) and snapping turtle (subjects = 198, depredations = 166) nests in Point Pelee National Park (2004–2005) Univariate model
Painted turtle Hazard ratio (SE)
Snapping turtle P value
Hazard ratio (SE)
P value
YEARa
0.902 (0.246)
0.706
0.971 (0.154)
0.852
TEMP
1.004 (0.003)
0.222
0.999 (0.004)
0.939
RAIN
1.006 (0.006)
0.329
0.999 (0.002)
0.973
DATELAID
1.042 (0.014)
0.003
1.009 (0.016)
0.554
RAINLAID
1.038 (0.051)
0.448
0.988 (0.012)
0.295
CORRIDORa
0.196 (0.102)
0.002
0.948 (0.156)
0.747
DISTURBEDa
1.611 (0.502)
0.126
1.926 (0.329)
0.000
WATERDIST
1.002 (0.002)
0.338
1.003 (0.002)
0.024
VEGDIST
1.014 (0.008)
0.083
1.011 (0.006)
0.068
EDGEAMT
0.998 (0.002)
0.426
1.001 (0.001)
0.259
DENSITY1 (5 m radius scale)a
0.986 (0.027)
0.619
1.037 (0.031)
0.218
DENSITY1 (25 m radius scale)a
0.987 (0.015)
0.397
1.046 (0.058)
0.418
0.849 (0.324)
0.452
1.036 (0.373)
0.923
0.855 (0.318)
0.673
0.522 (0.265)
0.200
DENSITY2 (5 m radius scale)
a
DENSITY2 (25 m radius scale)a
Bold text denotes signiWcant models (P < 0.10) a Discrete variable (refer to Table 1 for coding system)
large majority of “unknown” nest depredations in both turtle species were also attributable to raccoons. In total, 216 individual predators were captured at nest predation sites, including raccoons (62.0%), opossums (37.0%), skunks (0.5%), and domestic cats (0.5%), and during our Weld activities we incidentally recorded direct observations of raccoon (n = 18) and skunk (n = 1) depredations on turtle nests. The proportion of nests apparently depredated by raccoons (vs. other predators, based on track evidence) was similar between disturbed and undisturbed portions of the study area (painted turtle: 2 = 2.369, df = 1, P = 0.19; snapping turtle: 2 = 0.979, df = 1, P = 0.48). Overall, we captured a total of 151 and 168 individual raccoons during broad-scale capture–recapture sessions in 2004 and 2005, respectively. Spring densities in PPNP were estimated at 23.3 (95% CI: 19.9–29.8) and 25.3 (21.6–29.0) raccoons/km2 in 2004 and 2005, respectively, using the area of dry land in the park, and 7.6 (6.5–9.7) and 8.3 (7.1–9.5) raccoons/km2 for spring 2004 and 2005, respectively, when wetlands were included. Raccoon trapping success was higher in the disturbed portion of the park during spring capture–recapture trapping periods (May) (whole-period trap success; undisturbed: 9.7%; n = 360 trap nights; disturbed: 23.0%; n = 1440 trap nights; 2 = 25.927, df = 1, P < 0.001), during nest predation-site trapping (June–July) (3-night trap success; undisturbed: 13.3%; n = 225 trap nights; disturbed: 34.3%; n = 303 trap nights; 2 = 45.877, df = 1, P < 0.001), and during summer capture–recapture trapping periods (August) (whole-period
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trap success; undisturbed: 6.1%; n = 360 trap nights; disturbed: 16.0%; n = 1440 trap nights; 2 = 22.193, df = 1, P < 0.001). Thus, raccoon densities were higher in disturbed habitat before, during, and after the turtle-nesting season. Prediction 1: Relationship between nest density and depredation rate Overall, there was no evidence suggesting that nest depredation rates were dependent on nest density. Neither DENSITY1 (density of all nests, whether surviving or depredated) nor DENSITY2 (density of recently-depredated nests) was signiWcant in any of the predation analyses, regardless of the spatial scale at which they were tested [Table 2; species-combined CPH regression: DENSITY1 (5 m) HR = 1.009, SE = 0.014, P = 0.52; DENSITY1 (25 m) HR = 1.002, SE = 0.014, P = 0.91; DENSITY2 (5 m) HR = 1.018, SE = 0.332, P = 0.96; DENSITY2 (25 m) HR = 0.833, SE = 0.294, P = 0.61]. Inclusion of DENSITY1 or DENSITY2 in the best-Wt species-speciWc and species-combined models did not provide additional explanatory power (all painted turtle AICc > 7.592; all snapping turtle AICc > 2.007; all species-combined AICc > 24.998). In addition, Moran’s I correlograms revealed that depredation dates among neighboring nest pairs were not autocorrelated at any spatial scale up to 100 m (Fig. 2), suggesting that nest depredation events were spatially and temporally independent.
Oecologia (2012) 168:977–988
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Prediction 3: Relative vulnerability of painted and snapping turtle nests Ultimately, 57.4% of painted turtle nests (61 and 54% in 2004 and 2005, respectively) and 83.8% of snapping turtle nests (85 and 83% in 2004 and 2005, respectively) were depredated; this diVerence was statistically signiWcant (non-parametric log-rank test, 2 = 24.63, df = 1, P < 0.001). Overall, the proportion of nests surviving (i.e., hatching or remaining intact) to the end of the season was 36.4% (2004) and 44.0% (2005) for painted turtles, and 13.6% (2004) and 15.4% (2005) for snapping turtles. Prediction 4: Factors inXuencing nest predation
Fig. 2 Moran’s I spatial correlograms representing the degree of spatial autocorrelation in turtle nest predation dates (both species combined) in Point Pelee National Park during a 2004, and b 2005. Open squares represent coeYcient values for (Euclidean separation) distance lags that were not signiWcant following Bonferroni correction. Each 10-m distance lag represents a minimum of 20 nest pairs
Prediction 2: Individual predator behavior following nest predation events Individual raccoons did not have higher site Wdelity to recently depredated nests, implying that nest predation was unlikely to be primarily due to speciWc individuals foraging selectively. Same-site capture success of raccoons captured near depredated nest sites on night 1 was 10% for either habitat type (between 10 and 12% in undisturbed habitat, between 25 and 27% in disturbed habitat) (2nd night capture success: 2 = 26.093, df = 1, P < 0.001; 3rd night capture success: 2 = 29.755, df = 1, P < 0.001). Raccoons were not more likely to return to a given trap location during the nesting season (June–July) than they were during spring capture–recapture sessions (May); repeated captures of raccoons were comparable between these two time periods in both undisturbed habitat (2nd and 3rd night pooled capture success of previously-tagged individuals; 2 = 1.566, df = 1, P = 0.19) and disturbed habitat (2 = 2.648, df = 1, P = 0.13).
Preliminary CPH models for turtle nests and their corresponding hazard ratios revealed that, when analyzed individually, few variables were correlated with nest predation risk for either species (Table 2). Factors inXuencing nest predation risk diVered by species. For painted turtles, the variables CORRIDOR and DATELAID were most important; the model with both variables together had strong support (all other models AICc > 4.423), and a high level of certainty (w = 0.851; Table 3). The CORRIDOR variable had the strongest inXuence on painted turtle nest predation risk (w = 0.997), with 17.4% (n = 23) of nests within corridors versus 70.4% (n = 71) of nests outside of corridors being depredated. The modelaveraged hazard ratio for CORRIDOR indicated that predation risk decreased by 78.1% [(1¡0.219) £ 100] when nests were situated within a corridor (Fig. 3). The DATELAID variable also had a high weight of evidence (w = 0.947), with overall predation rates increasing from 35.8% (n = 32) for nests laid in the Wrst third of the nesting season (June 6–15), to 63.3% (n = 28) for those laid in the middle of the season (June 16–29), to 76.4% (n = 34) for those laid in the last third of the season (June 30–July 14). The VEGDIST variable had a modest inXuence on painted turtle nest predation (w = 0.107), with nest mortality increasing by 2.0% (|1¡1.002| £ 10 £ 100) for every 10 m increase in distance to vegetation edge. Twoway interaction terms were not related to nest predation risk (all P > 0.12, Table 3). For snapping turtles, the DISTURBED variable had a strong inXuence on nest predation risk (w = 0.996), although level of certainty for individual models was relatively low (Table 4). According to the model-averaged hazard ratio, nests located in disturbed habitat were 1.9 times more likely to be depredated than their counterparts in undisturbed habitat. Overall, 98.2% of snapping turtle nests in the disturbed portion of the park were depredated (total n = 111), compared to 65.5% (n = 87) of those in the undisturbed portion (Fig. 4). EVects of VEGDIST and
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984 Table 3 Cox proportional hazard regression models of factors inXuencing painted turtle nest predation in Point Pelee National Park (2004–2005), as ranked by AICc k number of parameters in the model, AICc change in AICc between the model and the “best” model (i.e., model with the lowest AICc), w Akaike weight
Oecologia (2012) 168:977–988
AICc
Model
k
Log likelihood
AICc
w
CORRIDOR + DATELAID
3
¡221.412
447.059
0.000
0.851
CORRIDOR + DATELAID + VEGDIST
4
¡221.333
451.482
4.423
0.093
CORRIDOR
2
¡224.479
453.193
6.134
0.040
CORRIDOR + VEGDIST
3
¡224.479
455.438
8.379
0.013
DATELAID
2
¡227.377
458.989
11.930
0.002
DATELAID + VEGDIST
3
¡226.893
460.266
13.207
0.001
VEGDIST
2
¡230.734
465.703
18.644
0.000
Fig. 3 Kaplan–Meier survival estimates for painted turtle nests situated within (dashed line) and outside of (solid line) mesopredator corridors in Point Pelee National Park (2004–2005)
Fig. 4 Kaplan–Meier survival estimates for snapping turtle nests located in undisturbed habitat (dashed line) and disturbed habitat (solid line) in Point Pelee National Park (2004–2005)
WATERDIST on snapping turtle nest predation risk were weak relative to the disturbance variable, with model-averaged hazard ratios indicating 6.0% (|1¡1.006| £ 10 £ 100) and 5.0% (|1¡1.001| £ 50 £ 100) increases in predation risk with every 10- and 50-m increase in distance from vegetation and water edge, respectively. Two-way interaction terms were not signiWcant (all P > 0.114, Table 4). We determined if nests from both turtle species were inXuenced by a common set of variables by using SPECIES
as stratum in a pooled CPH analysis. All individual explanatory variables that were signiWcant and used to build the candidate model sets in the species-speciWc analyses (CORRIDOR, DATELAID, DISTURBED, VEGDIST, WATERDIST) remained inXuential in the species-pooled analysis (all P < 0.052), along with the variable RAIN (P = 0.015). The best-Wt model of nest predation for both species contained the DISTURBED variable (HR = 1.847, SE = 0.273) and had a high weight of evidence (w = 0.981).
Table 4 Cox proportional hazard regression models of factors inXuencing snapping turtle nest predation in Point Pelee National Park (2004–2005), as ranked by AICc k number of parameters in the model, AICc change in AICc between the model and the “best” model (i.e., model with the lowest AICc), w Akaike weight
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Log likelihood
AICc
AICc
Model
k
w
DISTURBED
2
¡820.729
1,645.5336
0.000
0.484
DISTURBED + VEGDIST
3
¡820.355
1,646.858
1.325
0.249
DISTURBED + WATERDIST
3
¡820.729
1,647.606
2.073
0.172
DISTURBED + VEGDIST + WATERDIST
4
¡820.313
1,648.874
3.341
0.091
WATERDIST
2
¡826.098
1,656.270
10.736
0.002
VEGDIST + WATERDIST
3
¡825.549
1,657.246
11.713
0.001
VEGDIST
2
¡826.941
1,657.956
12.422
0.001
Oecologia (2012) 168:977–988
Whether or not a nest was located within disturbed habitat had a marked inXuence on predation risk; the speciespooled nest predation rate was 95.3% (n = 129) in the disturbed portion of the park as opposed to 59.5% (n = 163) in the undisturbed portion. The only other model worthy of consideration (AICc < 10) contained the DATELAID variable (HR = 1.027, SE = 0.010), indicating that nests of both species laid during the latter stages of the nesting season were more vulnerable to predation.
Discussion We documented heavy predation on nests of both painted and snapping turtles in Point Pelee National Park. Yet, our results are generally consistent with the hypothesis that the nest predation experienced by these two turtle species is incidental. Namely, predation rates on nests of both species were density independent and, based on recapture rates of raccoons at nest predation sites, individual predators did not appear to alter their foraging behavior after encountering nests. Furthermore, cryptic painted turtle nests were attacked by predators with lower frequency than more obvious snapping turtle nests, and nests of both species were depredated more often in areas subject to anthropogenic disturbance, a factor known to facilitate discovery by opportunistic predators. By implication, predation need not be directed to aVect prey demography, and reduced crypsis is an important driver of susceptibility to incidental predation. Raccoons appeared to be responsible for at least 71.8% of observed nest predation events across both turtle species and likely perpetrated many of the attacks for which a nest predator was not conWrmed (22.2%). These common nest predators, along with other medium-sized generalists such as opossums and skunks, have been labeled as ecological “cream skimmers”, or species with large home ranges and the capacity to detect and rapidly shift their diet toward resource hotspots (see Schmidt and Whelan 1999 and references within). Thus, we might expect raccoons and other generalist mesocarnivores to often prey on nests in a density-dependent fashion. Yet, evidence for density-dependent nest predation by these species is mixed. Among avian studies, for example, Schmidt and Whelan (1999) observed a positive relationship between raccoon predation and density of artiWcial ground nests of woodland songbirds, whereas Ackerman et al. (2004) found no support for density dependent predation on either artiWcial or natural duck (Anas spp.) nests. Similar disparity exists among reptile nest predation studies. For instance, Marchand and Litvaitis (2004) found that predation by raccoons and other generalists was more intense when artiWcial nests of painted turtles were clumped than when they were scattered, whereas Burke et al. (1998) found both no relationship between pre-
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dation rate and nest density of three turtle species, and nest survivorship that was independent of the survivorship of neighboring nests. Our results strengthen the notion that nest predation by generalist mesocarnivores such as raccoons is not always density dependent. We found no support over the course of our investigation for an association between increased predation and density of either all nests or recently depredated nests at two spatial scales (5- and 25-m buVers around the focal nest). Moreover, few individual raccoons appeared to return to (i.e., were recaptured at) sites of nest predation on consecutive nights, and no spatial autocorrelation existed among depredated nests. Some nest predators, including raccoons and skunks, may restrict the size of their home range when confronted with nest density hotspots without altering their foraging rate at a Wne spatial scale (Ackerman et al. 2004). Though we note that density dependence was in fact not detected even with a buVer radius of 50 m (J. Phillips, unpublished), it is therefore possible that densitydependent predation by these species could have manifested at spatial scales larger than those explored in the present study. Alternatively, the absence of density dependence in our system may be a function of the relationship between turtle nests and other food for incidental nest predators. A relative abundance of primary prey for incidental predators in PPNP, for example, would reduce the energetic incentive for active nest searching (Zimmerman 1984; Ackerman et al. 2004). A spatial mismatch between turtle nests and primary prey for opportunistic predators could also help to explain our failure to detect density dependence (Schmidt and Whelan 1999). That is, raccoons and other generalists in PPNP may exploit turtle nests primarily when they are fortuitously encountered during transit between preferred foraging areas. In general, then, we suggest that studies considering a wide range of spatial scales and the availability of alternative foods for potential predators are most likely to yield an improved understanding of the relationship between nest density and rate of exploitation in particular systems. Notably, turtle nest predation rates rose sharply over the course of the nesting season (from roughly 36 to 76% between early June and mid-July), possibly indicating that at least some nest predation in the study system was directed. We suspect, however, that this trend stems more from increases in raccoon abundance that were observed over the course of both nesting seasons than from changes to individual raccoon foraging behavior. We also doubt that observed increases in raccoon abundance were a response to the availability of turtle nests; nest density was highest during the initial stages of the egg-laying period (June) and declined thereafter, yet raccoon abundance was higher in July than in June. We predicted that snapping turtle nests would be more susceptible to predation than painted turtle nests for several
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reasons: they tend to be located closer to shorelines where opportunists such as raccoons concentrate their foraging, are associated with more visual cues from soil disturbance, are created during crepuscular and nocturnal periods when nest predators that visual and olfactory cues from fresh nests might attract are more active, and feature greater egg mass. In accord with this prediction, the frequency with which snapping turtle nests succumbed to predation over both years of our investigation was markedly higher than that of painted turtle nests (84 vs. 57%). Distance to water (WATERDIST) and distance to vegetation (VEGDIST) were not included in the best survival models for either turtle species, indicating that nest position had little to do with this diVerence. Instead, we infer that the increased visual and olfactory detectability of snapping turtle nests renders them more likely to be encountered by opportunistic predators. Other Weld investigations have also shown that painted turtles experience lower nest predation rates [mean: »36% (range: 0–77%); Tinkle et al. 1981; Snow 1982; Lindeman 1991; Kolbe and Janzen 2002; Congdon et al. 2003; Bowen and Janzen 2005; Rowe et al. 2005] than snapping turtles [mean: »77% (range: 59–94%); Hammer 1969; Petokas and Alexander 1980; Congdon et al. 1987]. By implication, the putatively heightened crypsis of painted turtle nests apparently lowers their susceptibility to predation relative to snapping turtle nests across a broad range of conditions. Although painted turtle nests were apparently less obvious to opportunistic predators than those of snapping turtles, nests of both species shared the same temporal pattern of vulnerability. The large majority of nests of both species were victimized within 1 day of establishment, when olfactory and visual cues that could attract the attention of incidental predators are strongest. Moreover, nearly all nest predation events occurred within 5 days of nest creation, presumably because cues facilitating detection have largely disappeared. In general, then, our results show that features promoting detection by opportunistic predators are dominant drivers of both variation in the susceptibility of sympatric prey species to predation and the extent to which incidental predation is likely to aVect prey population dynamics. From an applied perspective, it is important to note that anthropogenic habitat modiWcation that reduces cover (e.g., shrub clearing), facilitates predator travel (e.g., creation of paths), or encourages predator aggregation (e.g., resource subsidies) can create conditions that are conducive to incidental nest discovery (MarzluV et al. 1998; Schmidt and Whelan 1998, 1999). Thus, in the disturbed portion of the park where landscaping eVorts reduce cover and park visitors leave food waste that is undoubtedly attractive to raccoons and other carnivores, we expected to observe elevated rates of nest predation. In accord with the expectation, the top model of nest predation in the species-pooled
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analysis included disturbance as its only explanatory variable, and the species-pooled nest predation rate in disturbed areas of PPNP (95%) greatly exceeded that characterizing undisturbed areas (60%). Human disturbance in PPNP may have increased incidental nest predation largely by encouraging predator aggregation rather than changing patterns of individual predator habitat use and foraging. First, we observed higher raccoon abundance (as measured by trapping success) in disturbed habitat, both overall and in association with past predation events, and
