ARTICLE

Contrasting decadal trends in mortality between large and smallindividuals in skate populations in Atlantic CanadaDouglas P. Swain, Ian D. Jonsen, James E. Simon, and Trevor D. Davies

Abstract:Mature thorny (Amblyraja radiata), winter (Leucoraja ocellata), and smooth (Malacoraja senta) skates have declined to verylow abundance in the southern Gulf of St. Lawrence (SGSL) and on the eastern Scotian Shelf (ESS). We used stage-structuredstate-space models to examine decadal patterns in mortality rates in these skates. Mortality at early life stages (embryos in eggcases, hatchlings, and (or) small juveniles) appeared to decrease between the 1970s and the 2000s. In contrast, estimatedmortality rates increased for larger individuals over this period. Although potentially confounded in models with effects of anychanges in juvenile growth, the estimated increases in mortality could not instead be attributed solely to changes in growth.Increases in themortality of large individuals appeared to reflect increases in naturalmortality, possibly due to predation by greyseals. Increases in natural mortality were not evident for skates on the neighbouring western Scotian Shelf, where grey sealabundance has remained lower. Even in the absence of fishing, recovery of skates is unlikely under current ecosystem conditionsin the SGSL and on the ESS.

Résumé : Les raies épineuses (Amblyraja radiata), tachetées (Leucoraja ocellata) et a queue de velours (Malacoraja senta) matures sontdevenues très peu abondantes dans le sud du golfe du Saint-Laurent (SGSL) et l'est du plateau néo-écossais (ESS). Nous avonsutilisé des modèles d'espaces d'états structurés selon les étapes du cycle de vie afin d'examiner les patrons décennaux des tauxde mortalité chez ces raies. La mortalité durant les premières étapes du cycle de vie (embryons dans les capsules d'œufs, alevinsvésiculés et petits juvéniles) semble diminuer entre les années 1970 et les années 2000. En revanche, pour les individus plusgrands, les taux de mortalité estimés ont augmenté au cours de cette période. Si, dans les modèles, les augmentations estiméesde la mortalité peuvent potentiellement se confondre avec les effets de changements de la croissance des juvéniles, elles nepeuvent toutefois être entièrement attribuées a de tels changements. Les augmentations de la mortalité des grands individussemblent refléter des augmentations de la mortalité naturelle possiblement dues a la prédation par les phoques gris. Aucuneaugmentation claire de la mortalité naturelle n'a été notée pour les raies de la partie ouest du plateau néo-écossais, oùl'abondance des phoques gris est demeurée plus faible. Même en l'absence de pêche, un rétablissement des raies est peu probabledans les conditions écosystémiques actuelles dans le SGSL et le ESS. [Traduit par la Rédaction]

IntroductionElasmobranch fishes, especially the larger species, are considered

to be among the most vulnerable fishes to exploitation because oftheir life-history characteristics, in particular late maturation, largeadult size, long life span, and slow growth (e.g., Stevens et al. 2000;Dulvy and Reynolds 2002). Rapid declines in the abundance oflarge sharks have occurred in the Northwest Atlantic and in otherareas in recent decades (Baum et al. 2003; Ferretti et al. 2010), anda high proportion of oceanic pelagic sharks and rays are consid-ered to be at a heightened risk of extinction (Dulvy et al. 2008).Likewise, in the Northeast Atlantic, three of the largest skates(common skate, Dipturus batis; longnose skate, Dipturus oxyrhinchus;and white skate, Rostroraja alba) have become locally extinct, andother large-bodied skate species are declining in abundance(Brander 1981; Walker and Hislop 1998; Dulvy et al. 2000). Thesedeclines are attributed to overexploitation. In contrast, small-bodied elasmobranch species have recently increased in abun-dance off the eastern seaboard of the United States (Myers et al.2007), in deeper waters of the Gulf of Mexico (Shepherd andMyers2005), and off South Africa (Ferretti et al. 2010). These increases inthe abundance of small-bodied elasmobranchsmay reflect releasefrom predation by large sharks (Shepherd and Myers 2005; Myers

et al. 2007; Ferretti et al. 2010). Similarly, small-bodied skate spe-cies have increased in abundance in regions of the Northeast At-lantic, possibly because of competitive release as the larger skatesdeclined (Dulvy et al. 2000), reduced competition with depletedteleost fishes (Walker and Heesen 1996; Walker and Hislop 1998),or increased food supplies due to high levels of fishery discards(Walker and Heesen 1996; Walker and Hislop 1998).

In many ecosystems of the Northwest Atlantic, the biomass ofdemersal fishes, notably Atlantic cod (Gadus morhua), collapsed inthe early 1990s because of overfishing (Sinclair and Murawski1997) combined in some cases with a decline in productivity(Hilborn and Litzinger 2009). Following these collapses, moratoriaon directed cod fisheries were established and overall fishing ef-fort for groundfish declined sharply. Most of these depleted codpopulations have failed to recover, primarily because of reducedproductivity (Shelton et al. 2006). This reduction in productivitywas particularly severe in two of these ecosystems, the southernGulf of St. Lawrence and the eastern Scotian Shelf.

Although attention has focussed on the declines in the biomassof cod and other commercially important teleost fishes in North-west Atlantic ecosystems, skate biomass has also declined to verylow levels in the the southern Gulf of St. Lawrence and on theeastern Scotian Shelf (Swain et al. 2005; McPhie and Campana

Received 19 April 2012. Accepted 10 October 2012.

Paper handled by Associate Editor Ray Hilborn.

D.P. Swain. Gulf Fisheries Centre, Fisheries and Oceans Canada, P.O. Box 5030, Moncton, NB E1C 9B6, Canada.I.D. Jonsen and T.D. Davies. Department of Biology, Dalhousie University, Box 15000, 1355 Oxford Street, Halifax, NS B3H 4J1, Canada.J.E. Simon. Bedford Institute of Oceanography, Fisheries and Oceans Canada, P.O. Box 1006, Dartmouth, NS B2Y 4A2, Canada.

Corresponding author: Douglas P. Swain (e-mail: doug.swain@dfo-mpo.gc.ca).

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Can. J. Fish. Aquat. Sci. 70: 74–89 (2013) dx.doi.org/10.1139/cjfas-2012-0179 Published at www.nrcresearchpress.com/cjfas on 6 November 2012.

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2009a). The most common skates in these two ecosystems arethorny skate (Amblyraja radiata), winter skate (Leucoraja ocellata),and smooth skate (Malacoraja senta). On the eastern Scotian Shelf,the abundance ofmature individuals declined by greater than 90%between 1970 and 2006 for all three species (McPhie and Campana2009a). In the southern Gulf, mature abundance of these skateshas also decreased sharply since the early 1970s, by 80%–90% overthe 1971–2002 period for thorny and winter skates and to a lesserdegree for smooth skate (Swain et al. 2005). The causes of thesedeclines are unclear. Except for a fishery targetingwinter skate onthe eastern Scotian Shelf from 1994 to 2006, skates in these areashave been caught as bycatch in fisheries directed at other ground-fish and are typically discarded at sea. The declines between the1970s and the early 1990s may reflect overexploitation by thesefisheries directed at other species (Swain et al. 2005; McPhie andCampana 2009a). However, fishing effort in these areas droppedsharply in the early 1990s, and this was reflected in sharp declinesin indices of fishing mortality to very low levels for thorny andsmooth skates on the eastern Scotian Shelf (Simon et al. 2012) andfor winter skate in the southern Gulf (Swain et al. 2009). Lowproductivity is associated with slow recovery from overexploita-tion in marine fishes (Hutchings and Reynolds 2004), and McPhieand Campana (2009a) suggested that given their life-history char-acteristics, recovery of these skate populations can be expected tobe slow even following reductions in fishing effort.

Using stage-structured population models, Swain et al. (2009)estimated decadal patterns in mortality rates of winter skate inthe southern Gulf of St. Lawrence and on the eastern ScotianShelf. In this paper, we extend their analysis, estimating trends inmortality over a 40-year period (1970–2009) for thorny, smooth,and winter skates in these two ecosystems. We also compare re-sults between these areas and the western Scotian Shelf, an eco-system where water temperatures are warmer, demersal fishdeclines have been less severe, and directed fisheries for cod andother demersal teleosts are ongoing. Our results suggest that in-creased natural mortality of large individuals is preventing therecovery of all three species in the southern Gulf of St. Lawrenceand on the eastern Scotian Shelf. In contrast, no increases innatural mortality are evident for these species on the westernScotian Shelf.

Material and methods

Study areas and populationsWe examined the thorny, smooth, and winter skate popula-

tions (or subpopulations) in three ecosystems of Atlantic Canada(Fig. 1): the southern Gulf of St. Lawrence, comprising NorthwestAtlantic Fishery Organization (NAFO) Division 4T; the eastern Sco-tian Shelf, NAFO Divisions 4VW; and the western Scotian Shelfand Bay of Fundy, NAFO Division 4X. The southern Gulf ofSt. Lawrence consists of the Magdalen Shallows, with depthsmostly less than 100 m, bordered by the Laurentian Channel withdepths up to 500 m. The eastern Scotian Shelf consists of a num-ber of offshore banks and inner basins separated by gullies andchannels. The 4X area comprises a number of offshore banks andthe Bay of Fundy (depths < 100 m) and is bordered on the west bythe Fundian Channel with depths greater than 200 m.

In summer, three water layers form in the Gulf and on theScotian Shelf: a warm surface layer 30–40 m thick, a cold inter-mediate layer (CIL), and a warm deep layer at depths greater thanabout 150 m (Drinkwater and Gilbert 2004). The CIL covers thebottom over most of the southern Gulf and the offshore banks onthe Scotian Shelf. Bottom temperatures are coldest in the south-ern Gulf and warmest on the western Scotian Shelf and in the Bayof Fundy, where vertical gradients are weak because of intensetidalmixing. Inwinter, the surface layer cools and becomesmixedwith the CIL waters. The 4T area is typically ice-covered in winter,

but ice cover generally does not extend far beyond the 4Vn area onthe Scotian Shelf.

The three skate species show a degree of segregation by depthin the 4T area in summer. Winter skate are restricted to shallowinshore waters (<50 m), whereas smooth skate occur in deeperwater (100–300 m) along the slope of the Laurentian Channel(Swain et al. 2005). Thorny skate were widely distributed over theMagdalen Shallows in the 1970s and 1980s but are now concen-trated in deeper water with highest densities between 100 and200 m (Swain and Benoît 2006). Smooth skate do not appear toundertake seasonal movements in 4T, while thorny skate moveinto deep water along the slope of the Laurentian Channel inwinter and up onto the Shallows in summer (Clay 1991; Darbysonand Benoît 2003). Winter skate appear to move out of shallowinshore waters and become widely dispersed over the MagdalenShallows in winter (Clay 1991; Darbyson and Benoît 2003).

In the 4VWX area, winter skate tend to occur in the shallowwaters of the Bay of Fundy and on the offshore banks, moving uponto the banks in summer and into deeper water along the slopesof the banks in winter (Swain et al. 2006). Like in 4T, smooth skatein 4VWX occupy the deeper water along the slopes of channelsand banks, with concentrations in the 4Vn area and in the Gully inDivisions 4VWandnorth of Brown's Bank and in theGulf ofMainein Division 4X (Simon et al. 2012). As reported for 4T, no strongseasonal movements are evident for smooth skate in the 4VWXarea (Simon et al. 2012). Thorny skate were widespread through-out the 4VWX area in the 1970s but now are found primarily in the4V area and the Bay of Fundy (Simon et al. 2012).

Population structureIn these analyses, we assumed that individuals in each of the

three ecosystems represented separate populations, though weexamined the sensitivity of results to this assumption (see below).This assumption is clearly valid for 4T winter skate, which aredistinct from winter skate elsewhere in terms of morphology andlife history (McEachran and Martin 1977; Swain et al. 2009). How-ever, little is known about spatial population structure of theother stocks examined here. Tagging studies of thorny skate(Templeman 1984) and other small skates (see references inTempleman 1984) indicate that these skates generally do not un-dertake large-scale movements. This and the absence of a disper-sive pelagic stage in their life cycle make the formation of localpopulations likely. The distribution of adult-sized skates is dis-junct between ecosystems for each of the three species; this ismost clearly evident during the low abundance period in the1990s and 2000s (Figs. 1b–1d). For thorny and smooth skates, dis-tributions are less disjunct between the 4T and 4VW areas thanbetween areas 4VW and 4X (Figs. 1b, 1c). The distributions ofthorny and smooth skates in 4X are continuous with their distri-bution in US waters of the Gulf of Maine (Simon et al. 2012).

Data sourcesData on relative abundance at length are from bottom-trawl

surveys conducted by Fisheries and Oceans Canada each Septem-ber since 1971 in Division 4T and each July since 1970 in Divisions4VWX. These surveys followed a stratified random design withstratification based on depth and geographic area. For both sur-veys, the target fishing procedure was a 30 min tow at 3.5 knots(1 knot = 1.853 km·h–1). The stratified mean catch per 1.75 nauticalmile (1 n.mi. = 1.853 km) tow was used to construct time series ofrelative abundance for the period ending in 2009. Zero valueswere replaced by half theminimumnonzero value for a particularspecies and stage (length class) for population modelling.

Several research vessels have been used to conduct the Septem-ber survey: the E.E. Prince (1971–1985), Lady Hammond (1985–1991),Alfred Needler (1992–2002, 2004, 2005), Wilfred Templeman (2003),and Teleost (2004–2009). Tows conducted by the E.E. Prince used aYankee 36 trawl; all other vessels used a Western IIA trawl. Rela-

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tive fishing efficiency between these vessels and gears was esti-mated from comparative fishing experiments conducted duringor shortly before the September survey in 1985, 1992, and 2004–2005 (Benoît and Swain 2003; Benoît 2006). Based on the results ofthese experiments, catches of thorny skate were adjusted for thechange in survey vessel in 1992, but no other adjustments wererequired for changes in vessel or gear.

The July survey was conducted by the A.T. Cameron (1970–1981),Lady Hammond (1982), Alfred Needler (1983–2003, 2005, 2006, 2009),

Wilfred Templeman (2008), and Teleost (2004, 2005, 2007). Tows con-ducted by the A.T. Cameron used a Yankee 36 trawl; all other ves-sels used a Western IIA trawl. Estimates of relative fishingefficiency for skates between these vessels and gears are not avail-able for the July survey, but any differences are expected to beslight based on the results of the comparative fishing experimentsin 4T.

Fishing was conducted during daylight hours only (0700–1900)by the E.E. Prince but 24 h per day by all other vessels used for the

Fig. 1. Study area (a) and the distribution of adult skates in the 1990s and 2000s (b–d). (a) Black lines and labels denote Northwest AtlanticFishery Organization divisions or subdivisions; grey lines denote bathymetry (solid: 100 m; dotted: 200 m). (b–d) Catches of adult-sized skatesin the September survey of 4T and the July survey of 4VWX (see details in text under data sources), averaged over 10= squares; circle size isproportional to the catch rate (fish per 1.75 nautical mile tow; 1 n.mi. = 1.852 km).

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July and September surveys. In the September survey, all threeskate species weremore catchable at night than in the day (Benoîtand Swain 2003). This effect was stronger at shorter lengths forthorny and winter skates, but appeared to be independent oflength for smooth skate. Catches in the September survey wereadjusted for this diel effect to maintain a consistent time series in4T. For winter skate in 4T, night catches were converted to day-time equivalents using the length-dependent correction factorsgiven by Benoît and Swain (2003). For some analyses, thorny andsmooth skate data from the July and September surveys werecombined to produce 4TVW or 4TVWX indices. Thus, time seriesconsistency was maintained for these two species by adjustingcatches by the E.E. Prince to a level intermediate between day andnight catchability, based on the diel effect for the Lady Hammond(whose fishing efficiency for skates did not differ from that of theE.E. Prince in comparative fishing experiments).

Population modelsFollowing Swain et al. (2009), we used stage-structured popula-

tion models to estimate mortality trends in these skates. Exceptfor 4T winter skate, we included two juvenile stages and an adultstage in models, with individuals assigned to stage based onlength (Table 1). The lower length limit for the adult stage wasbased on the length at 50%maturity (L50), constrained by the 3 cmintervals used to measure skates on the surveys in some years.Estimates of L50 were available for these species for 4T (Swainet al. 2009; Swain et al. 2012a, 2012b) and for 4VW (McPhie andCampana 2009a) based on data collected since themid 2000s. Datacollected prior to the mid 1970s, available for thorny skate in theGulf of St. Lawrence (NAFO area 4RST; Templeman 1987) and forwinter skate in 4T and 4VW (McEachran andMartin 1977), suggestthat lengths at maturity in earlier years were similar to the recentestimates. Although not available for 4X, estimates of L50 wereavailable for the western Gulf of Maine (wGoM), the area to thesouthwest of 4X. For winter skate, the estimates of L50 are similarbetween 4VWand thewGoM (Sulikowski et al. 2005). However, forsmooth and thorny skates, estimates of L50 for the wGoM aregreater than those for the 4VW area, particularly for thorny skate(Sulikowski et al. 2006, 2009). Application of the wGoM estimatesto 4X would imply that virtually all (99%) of the thorny skate in 4Xare juveniles.We chose to apply the 4VW estimates of L50 to 4X forthese analyses. For 4VW and 4X winter skate, juveniles consistedof one stage (36–59 cm) not yet vulnerable to the directed skatefishery in 4VW (1994–2006) and a second stage (60–74 cm) vulner-able to this fishery (Simon and Frank 1996). Winter skate smallerthan 36 cm in total length were excluded from the 4VW and 4Xanalyses because of difficulties in distinguishing between winterskate and little skate (Leucoraja erinacea) at these small sizes, butwere included in analyses for 4T where little skate do not occur.For thorny and smooth skates, the juvenile stage was divided intotwo length classes to reflect differences in the time trends inrelative abundance. A single juvenile stage was used for 4T winterskate because of the early age and small size at maturity for thispopulation.

For all populations except 4T winter skate, transitions fromyear t – 1 to year t were modeled as follows:

(1) N1,t � [N1,t�1(1 � �1) �12(rN3,t�a)] e

�Z1,t e�1,t

(2) N2,t � [N2,t�1(1 � �2) � N1,t�1�1] e�Z2,t e�2,t

(3) N3,t � (N3,t�1 � N2,t�1�2) e�Z3,t e�3,t

where Ni,t (i = 1, 2, 3) is abundance in year t for the ith life stage,�i is the transition probability to the next stage, a is the timebetween laying of egg cases and recruitment to juvenile stage 1(1–4 years depending on population), Zi,t is the stage-specificinstantaneous rate of total mortality in year t, and r is therecruitment rate (i.e., annual fecundity per female discountedby egg case mortality and mortality between hatching and re-cruitment). A sex ratio of 1:1 was assumed to compute recruitproduction. The probability of transition directly from the firstjuvenile stage to the adult stage in 1 year was assumed to bezero based on plausible growth rates for these skates. The �1,t,�2,t, and �3,t are independent normal random variables withmean 0 and variance �i

2, representing process stochasticity ineach of the three stages. The model for 4T winter skate had thesame form except that transition was directly from the firstjuvenile stage to the adult stage. These models assume thatrecruitment and transition between stages occur prior to mor-tality events. Zi was assumed to be constant over all years t orwas allowed to vary decadally.

Observation modelThe true abundance of each life stage Ni,t is not observed di-

rectly, rather survey catch rates provide observations of relativeabundance yi,t with some error. Survey catch rates can be relatedto Ni,t with the following observation model:

(4) yi,t � qiNi,te�i,t

where qi is the catchability coefficient of stage i that scales relativeabundance to Ni,t (i = 1, 2, 3), and �i,t are independent normalrandom variables with mean 0 and variance �i

2, representing ob-servation error in the abundance index for stage i.

In most fishery models, data on fishery catch and assump-tions about natural mortality are incorporated to help to scalerelative abundance to population abundance. In many of thecases examined here, reliable data on fishery catch and itslength composition were unavailable because almost all of theskate catch was discarded at sea. Likewise, assumptions aboutnatural mortality were problematic because natural mortalityappears to have changed dramatically over the past 40 years formany demersal fishes in these ecosystems (see Discussion).Thus, we did not attempt to scale Ni,t to true abundance. In-stead, survey catch rates were adjusted for size selectivity usingthe research-trawl selectivity curve estimated by Harley andMyers (2001) for flatfish. Small and large individuals were ad-justed to the same relative catchability, but not to 100% catchabil-ity, by setting the maximum catchability (= in Harley and Myers2001) to 1.

Bayesian analysisWe used a Bayesian approach to parameter estimation, placing

informative priors on a number of model parameters (Supple-

Table 1. Length-based stages (cm) used in population models for thorny skate, smooth skate, and winter skate in regions ofAtlantic Canada (denoted by their Northwest Atlantic Fishery Organization (NAFO) designation).

Species Population(s) Juvenile 1 Juvenile 2 Adult Source for size at maturity

Thorny skate 4T ≤32 33–50 ≥51 Swain et al. 2012a4VW, 4X ≤32 33–53 ≥54 McPhie and Campana 2009a

Smooth skate 4T, 4VW, 4X ≤32 33–47 ≥48 McPhie and Campana 2009a; Swain et al. 2012bWinter skate 4T 21–41 — ≥42 Swain et al. 2009

4VW, 4X 36–59 60–74 ≥75 McPhie and Campana 2009a

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mentary Appendix S11) for which little information was likely tobe available in the relative abundance at length data. In particu-lar, we made use of estimates of annual fecundity (Frisk et al.2002; Parent et al. 2008; McPhie and Campana 2009a), growth rate(McPhie and Campana 2009b; Swain et al. 2012a; D.P. Swain, un-published analyses), and mortality prior to recruitment (egg caseand early juvenile stages) (Lucifora and García 2004; Frisk et al.2002) to place informative priors on recruitment rates and transi-tion probabilities. Because we adjusted the relative abundancesfor size selectivity prior to model fitting, we placed highly infor-mative priors on the catchability q of each life stage. Except forjuvenile winter skate in 4T, we assumed that relative catchabilitywith the adjusted catch rates was 1 but allowed some variationabout this value. For 4T winter skate, the prior on relative catch-ability of juveniles was centered on 0.7 to account for the loweravailability of juveniles than adults to the survey (see Swain et al.2009 for details). Priors for initial population sizes were based onthe average survey catch rates in the 1970s and were also highlyinformative. Uniform priors were placed on the standard devia-tions of process and observation errors. Lower limits for the priorsfor observation error were based on the CVs of the survey data.Vague normal priors were used for the mortality parameters.

We used the freely available software WinBUGS (Lunn et al.2000) to implement the state-space models. The software usesGibbs sampling (Gelman et al. 2005), a Markov chain Monte Carlo(MCMC) approach, to estimate the joint posterior distribution ofthemodel parameters. A total of 175 000 samples was generated ineach of two chains, the first 100 000 were discarded as a “burn-in”,and every 30th sample thereafter was retained to reduce autocor-relation, yielding 5000 samples from the joint posterior. We se-lected contrasting values within the range specified by each of theprior distributions to initialize the two chains. Convergence wasassessed by examining plots of Brooks–Gelman–Rubin conver-gence statistics and by comparing posterior density plots betweenthe first, middle, and last third of the saved samples for mortalityparameters (Supplementary appendices S2–S41). WinBUGS wasrun from R (R Development Core Team 2011) using theR2WinBUGS package (Sturtz et al. 2005). Gelman and Rubinshrink factors were calculated using the R package boa (Smith2007).

Sensitivity analysisWe expected the posterior distributions for mortality parame-

ters to be influenced by the ratios of abundances in adjacentstages, which are affected by the adjustment for size selectivity ofthe survey trawl. To examine the sensitivity ofmortality estimatesto our adjustments for size selectivity, we conducted two sensitiv-ity tests using the data for 4T thorny skate. In the first test, weused an adjustment for size selectivity that was half as strong asthat estimated by Harley and Myers (2001) for flatfish. In the sec-ond test, no adjustments for size selectivity were applied to thedata. Instead, an informative prior centered on 1 was used forcatchability to the adult stage, and uniformpriors extending from0.1 to 1.0 were used for each of the juvenile stages.

In our models, changes in productivity are modeled as changesin mortality rates. Effects attributed to changes in stage 1 mortal-ity could instead reflect changes in recruitment rate, and thoseattributed to changes in mortality during stages 2 and 3 couldinstead reflect changes in growth through stages 1 and 2 (mod-elled via �1 and �2), respectively. To examine whether estimatedchanges inmortality rates could instead reflect changes in rates ofrecruitment and (or) juvenile growth, sensitivity analyses wereconducted using models for 4T thorny skate. Changes in juvenilegrowth rates were simulated by allowing or imposing decadalvariation in �. A series of hierarchical models were examined in

which decadal variation in recruitment rate, growth rates, and(or) mortality rates was allowed and their goodness of fit wascompared using DIC (deviance information criterion; Spiegelhal-ter et al. 2002). Model names indicate the life-history parametersallowed to vary decadally; for example, in model Gr, �1 and �2(reflecting growth rates through stages 1 and 2) and the recruit-ment rate parameter r were allowed to vary decadally, whereasthe mortality parameters Zi were constrained to be constant overtime. Priors were the same as in the thorny skate models de-scribed above (Supplementary Appendix S11), except in modelsthat allowed decadal variation in recruitment rate or growth rate.In models allowing decadal variation in growth rate, uniformpriors were used for � in each decade, extending between 0.12 and0.25 for �1 and 0.15 and 0.3 for �2.We considered this range for � toexceed the range of plausible variation in growth rates, represent-ing growth rates varying between about 2.7 and 5.5 cm·year–1. Inmodels allowing decadal variation in recruitment rate, uniformpriors extending from 1 to 80were used for r in each decade. Againthis represents an extreme range for variation in recruitmentrate, corresponding to a fecundity of half the estimated currentlevel and 5% embryo survival in egg cases at one extreme andfecundity 1.75 times the current estimate and 95% embryo survivalat the other extreme. Three additional models were examined.Model Gr2was likemodel Gr except that the priors for �1 and �2spanned a range of 0.05 to 0.8, far in excess of plausible variationin growth, corresponding to stage durations varying between 20and 1.25 years, respectively. Model ZGr2 was like model ZGrexcept that decadal variation in both r and � was forced by usingdifferent informative priors for these parameters in different de-cades (Table 2), corresponding to growth rates in the 1970s thatwere about twice as fast as those in the 2000s and recruitmentrates that were 7.5 times greater in the 2000s than in the 1970s.Model Zr2 was like model Zr except that decadal variation wasnot allowed for Z1.

Finally, we examined the sensitivity of estimated trends inmor-tality to our assumptions about population structure. For thornyand smooth skates, we also fit models assuming that the individ-uals distributed in 4T and in 4VW represented a single populationor that individuals throughout the entire 4TVWX area compriseda single population. For winter skate, we examined the assump-tion that individuals throughout the 4VWX area comprised a sin-gle population. The abundance indices used for these analyseswere weighted averages of the indices for each zone, with weight-ing based on the relative survey areas of the zones.

1Supplementary data are available with the article through the journal Web site at http://nrcresearchpress.com/doi/suppl/dx.doi.org/10.1139/cjfas-2012-0179.

Table 2. Priors for recruitment rate (rd) and transition probabilities(�i,d) in model ZGr2.

Parameter Decade Prior Median

r1 1970s lognormal(1.568616, 1)I(0.01,1000) 4.8r2 1980s lognormal(2.772589, 2.56)I(0.01,1000) 16r3 1990s lognormal (3.295837, 8.163265)I(0.01,1000) 27r4 2000s lognormal (3.583519, 16)I(0.01,1000) 36�1,1 1970s beta(29,71)I(0.22,0.41) 0.291�1,2 1980s beta(29,71)I(0.22,0.41) 0.291�1,3 1990s beta(20,80)I(0.154,0.286) 0.203�1,4 2000s beta(15,85)I(0.11,0.20) 0.149�2,1 1970s beta(40,60)I(0.31,0.57) 0.402�2,2 1980s beta(40,60)I(0.31,0.57) 0.402�2,3 1990s beta(27,73)I(0.205,0.381) 0.272�2,4 2000s beta(30,120)I(0.154,0.286) 0.201

Note: The second parameter of the lognormal distribution is given as preci-sion (1/�2). The notation I (x,y) indicates that distributions are truncated at x andy so that values must be greater than x and less than y.

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Results

Trends in abundance

Thorny skateAdult-sized thorny skate declined sharply from the 1970s to the

2000s in all three ecosystems (Figs. 2a, 2d, 2g). Trends in the abun-dance of juvenile thorny skate differed among ecosystems. In 4T,the average abundance of small juveniles (stage 1) was relativelyhigh from the late 1980s to the late 1990s, returned to lower valuesin the early 2000s, and increased again to high values in recentyears. The abundance of larger juveniles (stage 2) showed littletrend in 4T until the late 1990s when their abundance began asharp decline to record-low levels (Fig. 2a). Abundance trendswere similar between the two juvenile stages in 4VW, with high-est average levels observed in the early to mid-1980s followed by agradual decline over the remainder of the time series (Fig. 2d). In4X, the abundance of stage 1 juveniles fluctuated with little trendover the 1970–2009 period, while stage 2 abundance declined overthe period, though not as sharply as observed for stage 3 abun-dance (Fig. 2g).

Smooth skateAdult-sized smooth skate declined in all three ecosystems be-

tween the 1970s and the early 1990s (Figs. 2b, 2e, 2h). These de-clines were greatest in 4X and least in 4T. Abundance of adultsmooth skate has shown some recovery from the low abundanceof the early 1990s in 4X but not in 4T or 4VW. In contrast withadult abundance, abundance of small (stage 1) juvenile smoothskate tended to be higher in the 1990s and 2000s than in the 1970sand 1980s. This pattern was most striking in 4T and weakest in4VW. Changes in the abundance of larger stage 2 juveniles dif-fered between ecosystems. In 4T, abundance of this length classincreased in the late 1980s to relatively high levels throughout the1990s and then declined back to low levels in the 2000s (Fig. 2b). In4VW, abundance of this length class was highest in the 1970s andthen declined to lower levels for the remainder of the time series,with the lowest average levels observed in the late 2000s (Fig. 2e).In 4X, trends in the abundance of stage 2 juveniles were similar tothe trends observed for adults, gradually decreasing from themid-1970s to very low levels in the late 1980s and early 1990s and thenincreasing throughout the 1990s and 2000s (Fig. 2h).

Winter skateAbundance of adult winter skate declined between the 1970s

and the 2000s, sharply in 4T and 4VW but only slightly in 4X (Figs.2c, 2f, 2i). Abundance of juvenile winter skate in 4T increased fromthe early 1970s to the mid-1980s and then declined, reaching verylow levels in the 2000s (Fig. 2c). In 4VW, abundance indices forsmall and larger juveniles (stages 1 and 2) showed similar patterns,increasing in the 1970s, fluctuating between medium and highlevels in the 1980s and early 1990s, and then declining to very lowlevels in the late 2000s (Fig. 2f). In 4X, though it fluctuated consid-erably, the index for small juveniles tended to be at a low levelfrom the early 1970s to the mid-1980s, a high level from the late1980s to the late 1990s, and an intermediate level in the 2000s(Fig. 2i). Little trend in the abundance of larger juveniles wasevident in 4X.

Trends in mortality

Thorny skateThorny skate models that constrained all life-history parame-

ters (i.e., r, �i, Zi) to be constant over time displayed severe tempo-ral patterns in observation and (or) process error (Fig. 3). Thesepatterns were most severe for stages 1 and 3 and indicate poormodel fits to the abundance index data. The models tended tooverestimate stage 1 abundance in the 1970s and underestimate itlater in the time series. Lack of fit to the stage 3 abundance indicesshowed the reverse pattern. These temporal patterns in the errors

indicate misspecification of the deterministic component of themodels. These patterns were eliminated by allowing decadal vari-ation in mortality (Fig. 4).

The estimatedmortality of small juvenile thorny skate declinedover time in all three ecosystems (Fig. 5a). This decline occurredbetween the 1970s and 1990s in 4T and 4VW and between the1980s and the 2000s in 4X. Mortality of larger juveniles increasedsharply from the 1980s to the 2000s in 4T. A weaker increase inadult mortality also appeared to occur in 4T from the 1970s to the1990s, with a decline in the 2000s. Little decadal variation in themortality of larger juveniles was evident in 4VW and 4X, thoughthere was a tendency in both areas for estimated mortality to besomewhat higher in the 2000s than in earlier decades. In 4VW,estimated adult mortality was low in the 1970s, high in the 1980sand 1990s, and intermediate in the 2000s. In 4X, estimated adultmortality was high in the 2000s compared with earlier decades.

Smooth skateSmooth skate models that constrained life-history parameters

to be constant over time also displayed temporal patterns in ob-servation and (or) process error that were similar to those de-scribed above for thorny skate, though they were not as severe asthose seen for thorny skate except at stage 1 (Supplementary Ap-pendix S51). Again, allowing decadal variation mortality elimi-nated these patterns (Supplementary Appendix S51).

The estimatedmortality of small juvenile smooth skate decreasedover the 1970–2009 period in all three ecosystems (Fig. 5b). The de-crease occurred from the 1970s to the 1990s in 4T and between the1980s and 1990s in 4VW and 4X. In contrast, estimated mortalityof larger juveniles increased from the 1980s to the 2000s in 4T and4VW but not in 4X. No strong decadal pattern in the mortality ofadult smooth skate was evident in any of the areas.

Winter skateWinter skate models assuming constant vital rates also displayed

temporal patterns in observation and process error, though theywere generally not as severe as seen for the other two species (Sup-plementary Appendix S51). Allowing decadal variation in mortalityeliminated these patterns (Supplementary Appendix S51).

Estimated mortality of small juvenile winter skate tended todecrease over the study period, though the changes were weakerthan those estimated for thorny and smooth skates, with consid-erable overlap between decades in the posterior distributions forjuvenile mortality (Fig. 5c). The decrease in mortality of smalljuveniles appeared to occur between the 1970s and the 1980s in 4T,from the 1970s to the 1990s in 4VW, and between the 1980s andthe 1990s in 4X. No changes in the mortality of larger juvenileswere evident in 4VW and 4X. In 4T, there was a strong increase inthe estimated mortality of adult winter skate from the 1970sto the 1990s. Adultmortality appeared to gradually increase fromthe1970s to the2000s in4VW.No strong changes in adultmortalitywereevident for winter skate in 4X, though the estimates tended to behigher in the 1990s and 2000s than in earlier decades.

Sensitivity analyses

Adjustment for gear selectivityAdjustment of the survey catch rates in an attempt to correct

for size selectivity of the survey gear affected the level of themortality estimates (Fig. 6). Data adjusted using the Harley–Myersselectivity curve for flatfish resulted in mortality estimates thatwere lower for stage 1 and higher for stages 2 and 3 than thosebased on an adjustment that was half as strong. Allowing themodel to estimate the catchability of stages 1 and 2 relative tostage 3 resulted in the highest estimates of mortality for stage 1and the lowest estimates for stages 2 and 3. However, the tempo-ral trends in mortality were the same regardless of the selectivityor catchability adjustment used.

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Fig. 2. Abundance indices for thorny skate, smooth skate, and winter skate in the annual surveys of the southern Gulf of St. Lawrence (4T, panels a–c), the eastern Scotian Shelf (4VW,panels d–f), and the western Scotian Shelf and Bay of Fundy (4X, panels g–i). Skates were classified into stages based on length (stage 1, grey lines; stage 2, thin lines and circles; stage 3,heavy black lines). Adult lengths correspond to stage 2 for 4T winter skate and stage 3 in other cases. 4T abundance indices were adjusted for diel and vessel–gear effects on catchabilityas described in the text.

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Changes in rates of recruitment or growthModels that allowed or forced decadal variation in r, �1, and �2

indicate that the patterns in the data that we attribute to decadalvariation in mortality rates cannot instead be entirely attributedto variation in rates of recruitment and growth (at least for thetest case, 4T thorny skate). Comparing models that allowed Zi, �i,and (or) r to vary decadally within plausible limits (Table 3), DICwas lowest for model Z, the model allowing decadal variation inZi only. DIC was only slightly greater in other models that alloweddecadal variation in Zi as well as in �i and (or) r. In these lattermodels, posterior distributions varied decadally only for the Zparameters (e.g., Fig. 7c), and decadal variation in Z was similar tothat estimated by the model with informative time-invariant pri-ors for �i and r (Fig. 5a). In models that did not allow the Z param-eters to vary decadally, posterior distributions for �i and (or) r didshowdecadal variation corresponding to higher recruitment ratesand slower growth in the 1990s and 2000s (e.g., Fig. 7a). However,these models were unable to fit the abundance trend for stage 1(Supplementary Appendix S61). Models that allowed decadal vari-ation in Zi were strongly favoured over models that allowed dec-adal variation in �i and (or) r only (DIC ≥ 10; Table 3).

Model Gr2, which allowed wider variation in �1 and �2, per-formed better than other models that did not allow the Z param-eters to vary decadally (DIC = 340.0; Supplementary AppendixS61), though models allowing decadal variation in the Z parame-ters were favoured over this model (DIC 332.0–334.9). Further-more, differences between the posterior distributions for �1 and �2estimated by model Gr2 (Fig. 7b) correspond to changes ingrowth rate that are far greater than is possible. For example, the

posterior medians for �1 correspond to growth through stage 1 in1.5 years in the 1970s (13.3 cm·year−1) and 15 years in the 2000s(1.3 cm·year−1).

In model ZGr2, variation in �i and r was imposed by informa-tive priors that differed between decades, whereas variation in Ziwas allowed by vague uniform priors that were the same for eachdecade. Despite the wide variation in rates of recruitment andgrowth (i.e., r and �i) imposed in this model, estimated mortalityrates for stage 2 were similar to those obtained from models inwhich �i and r were constant (or allowed, but not forced, to varydecadally), with Z2 increasing sharply from the 1980s to the 2000s(Fig. 7d). Decadal trends estimated for Z1 and Z3 were also similarto those estimated in these other models, though the decadalchanges were weaker, particularly for Z1.

Model Zr2 (DIC 333.7), which allowed decadal variation in re-cruitment rate but not inmortality for stage 1, fit the data about aswell as model Z (DIC 332.0), which allowed decadal variation inmortality for all three stages but not in recruitment rate (Supple-mentary Appendix S61). This indicates that variation in stage 1abundance of 4T thorny skate (relative to spawner abundance) canbe accounted for by decadal variation in either recruitment rate orstage 1 mortality rate. The decadal variation in recruitment rateestimated bymodel Zr2was extreme, corresponding to a recruit-ment rate 13 times greater in the 2000s than in the 1970s (Fig. 7e).Because of physiological and morphological constraints, it is notplausible that fecundity could vary this widely, so much of thiswide variation in recruitment rate would need to reflect variationin mortality (i.e., of embryos in egg cases or of hatchlings prior torecruitment to stage 1 in the survey catches).

Fig. 3. Observation and process error (stacked bars) for thorny skate models that assume that mortality rates do not change over time(shaded bars = observation error; open bars = process error). Heavy lines show a loess smooth to the sum of observation and process error ineach year. Error is calculated with indices and abundance on the loge scale.

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Population structureDecadal patterns in mortality estimates persisted assuming

that individuals comprised a single population over the 4TVW or4TVWX areas (thorny and smooth skates) or over the 4VWX area(winter skate). For thorny skate, decadal patterns inmortality rateaggregating over areas were similar to those observed treatingindividuals in 4T or 4VW as separate populations. Aggregatingover the 4TVW or the 4TVWX areas, estimated mortality declinedfrom the 1970s to the 1990s for stage 1, increased from the 1980s tothe 2000s for stage 2, and increased from the 1970s to the 1990s forstage 3 (Figs. 8a–8f). For smooth skate, estimated mortality de-creased between the 1980s and the 1990s for stage 1, increasedfrom the 1980s to the 2000s for stage 2, and changed little overtime for stage 3 aggregating over either 4TVW or 4TVWX (Figs.8g–8l). For winter skate, estimated mortality decreased from the1970s to the 1990s for stage 1, varied little for stage 2, and tendedto increase over time for stage 3 when individuals were aggre-gated over the 4VWX area (Figs. 8m–8o).

DiscussionFor all three skate species, the mortality rates estimated by our

models declined for small individuals and increased for largerindividuals between the 1970s and the 2000s in the 4T and 4VWareas. For thorny skate, increases in mortality were evident bothfor adult sizes and, particularly in 4T, for larger juveniles. In-creases in mortality appeared to be restricted to the larger juve-nile sizes for smooth skate and to the adult sizes for winter skate.Mortality of small individuals also appeared to decrease in 4X,

though the declines in mortality in this area tended to be firstevident later in the time series and were less distinct (i.e., theretended to be more overlap between posterior distributions formortality parameters). For the larger sizes, increases in mortalityin 4X were either not evident (smooth skate), less distinct (winterskate), or occurred later in the time series (thorny skate).

Declines in mortality rates of small individuals, estimated herefor skates, appear to be widespread throughout the marine fishcommunity in the 4T area. In this area, small-bodied species haveincreased in abundance since about themid-1980s, with the great-est increases in abundance generally occurring since the early tomid-1990s (Benoît and Swain 2008). Similarly, within large-bodiedspecies, abundance of small individuals generally increased torelatively high levels in the 1990s and 2000s (Benoît and Swain2011). Similar changes are evident in the marine fish communityof the 4VW area (Choi et al. 2004). In the 4T area, the biomass ofsmall fish is inversely related to an index of piscivory on thesefish, leading to the suggestion that the increased abundance ofsmall fish reflects a release from predation as the biomass of largedemersal fish collapsed in the late 1980s and early 1990s becauseof overfishing (Benoît and Swain 2008, 2011). In our analyses, esti-mated mortality rates of small juvenile skates reached the lowestlevels in the 1990s and 2000s, but declines in mortality of theseskates generally began in the 1980s, when overall demersal fishbiomass remained relatively high. This may reflect the loss of thelarger demersal fish (e.g., cod ≥ 60 cm in length), which beganearlier in the 1980s (e.g., Swain et al. 2009). Furthermore, changesin predation mortality may also reflect changes in the spatial

Fig. 4. Observation and process error (stacked bars) for thorny skate models that allow decadal variation in mortality rates (shaded bars =observation error; open bars = process error). Heavy lines show a loess smooth to the sum of observation and process error in each year. Erroris calculated with indices and abundance on the loge scale.

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distributions of predators and prey. For example, in the case of 4Twinter skate (which are restricted to shallow inshore waters duringthe feeding season), reduced juvenile mortality in the 1980s may bepartly due to an offshore shift in the distribution of cod in the late1970s and early 1980s (Swain 1999), resulting in reduced spatialoverlap between cod and winter skate. Finally, declines in fishingmortality (e.g., bycatch and discard mortality) likely also contrib-ute to declines in themortality rate of small individuals, followingincreases in mesh sizes and other measures to reduce the bycatchof small fish in the 1980s and the sharp declines in fishing effort inthe early 1990s (Benoît and Swain 2008, 2011; Choi et al. 2005).

In the 4T and 4VW areas, estimates of mortality increased tohigh levels in the 1990s and 2000s for large skates (either adults,

large juveniles, or both). In both these areas, groundfishing effortdeclined sharply to very low levels in the early 1990s following theimposition of moratoria on directed fishing for cod, the maintarget of demersal fishing effort in these areas (Benoît and Swain2008; Choi et al. 2005). This suggests that the high mortality oflarge skates in these areas in the 1990s and 2000s reflects increasesin naturalmortality. This suggestion is confirmed for winter skatein both areas based on analyses that disentangle fishing and nat-ural mortality (Swain et al. 2009) and for thorny and smoothskates in 4VWwhere indices of fishingmortality are available anddeclined to very low levels for both species since the mid-1990s(Simon et al. 2012). Furthermore, given the declines in fishingmortality in these areas in the 1990s and 2000s, natural mortality

Fig. 5. Decadal estimates of mortality rate by size class for thorny skate (a), smooth skate (b) and winter skate (c) in Northwest AtlanticFishery Organization divisions 4T, 4VW, and 4X. For 4T winter skate, stage 1 represents juveniles and stage 2 represents adults. In other cases,stages 1 and 2 comprise small and large juvenile skates, and stage 3 comprises adult skates. Heavy horizontal lines are the medians of theposterior distributions for mortality parameters, boxes delimit the 25th and 75th percentiles of these distributions, and vertical lines delimitthe 2.5th and 97.5th percentiles.

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of large skates has likely increased even more than the increasesin total mortality rates reported here. For example, given thesharp decline in estimates of relative fishing mortality of smoothskate in 4VW in the early 1990s (Simon et al. 2012), the lack of aconcurrent decline in total mortality of adult smooth skate in thisarea suggests that natural mortality has also increased for theseskates. Elevated naturalmortality has also been reported for otherlarge demersal fishes in the 4T and 4VW ecosystems, i.e., 4VsWcod (Mohn and Rowe 2012), 4T cod (Swain et al. 2012c), 4T whitehake (Urophycis tenuis; Swain et al. 2012d), and 4T American plaice(Hippoglossoides platessoides; Morin et al. 2008). In all these cases,estimated natural mortality increased to unusually high levels inthe 1990s and 2000s, particularly for large individuals (Mohn andRowe 2012; Swain et al. 2012c).

Causes of these increases in natural mortality of large demersalfishes in 4T and 4VW are a matter of debate (e.g., Trzcinski et al.

Fig. 6. Decadal patterns in estimated mortality rate of three length classes (stages) of 4T thorny skate based on data with differentadjustments for size-selectivity of the survey gear: (a–c) qadj1, adjustment based on the size-selectivity curve for flatfish from Harley and Myers(2001); (d–f) qadj2,based on an adjustment half as strong as in panels a–c; (g–i) qno_adj, no adjustment for size-selectivity, catchability of stages 1and 2 relative to stage 3 estimated by the model. Insets show prior (dashed line) and posterior (solid lines) distributions for catchabilityparameters.

Table 3. Comparison ofmodels for 4T thorny skate that allow decadalvariation in one or more of the following sets of life-history parame-ters: Zi (i = 1,2,3), �i (i = 1,2), and r.

Model

Decadalvariationallowed

Decadalvariationestimated DIC

0 None None 369.9Z Zi Zi 332.0G �i �i 370.7r r r 344.6ZG Zi, �i Zi 334.9Zr Zi, r Zi 332.5Gr �i, r �i, r 355.6ZGr Zi, �i, r Zi 334.1

Note: In model 0, all life-history parameters are constrained to be constantover time. Bold font indicates lowest deviance information criterion (DIC) value.

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Fig. 7. Posterior distributions for parameters allowed to vary decadally in selected models from the sensitivity analysis of effects of possiblevariation in rates of growth and recruitment on estimated mortality rates. Models shown are Gr (a), Gr2 (b), ZGr (c), ZGr2 (d), andZr2 (e). See text for model details. Heavy horizontal lines are the medians of the posterior distributions for parameters, boxes delimit the25th and 75th percentiles of these distributions, and vertical lines delimit the 2.5th and 97.5th percentiles.

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2009; O'Boyle and Sinclair 2012). Abundance of these fishes haddeclined to a low level by the early to mid-1990s, and one possibil-ity is that these increases in natural mortality reflect a “predatorpit” or predation-driven Allee effect (Gascoigne and Lipcius 2004).The grey seal (Halichoerus grypus) is an important fish predator inthe 4T and 4VW areas. Grey seal abundance has increased dramat-ically in these areas, from about 10 000 animals in 1960 to 400 000in 2010 (Hammill and Stenson 2011). Chouinard et al. (2005) re-ported that the estimated rate of natural mortality of 4T cod co-varied with grey seal abundance and suggested that predation bygrey seals may be a cause of the elevated natural mortality in thisstock. Likewise, Swain et al. (2011) examined a comprehensivesuite of hypotheses for causes of the increased natural mortalityof 4T cod and concluded that the hypothesis with the most sup-port was that predation by grey seals is an important componentof the current high level of natural mortality.

Increased predation by grey seals may also contribute to ele-vated naturalmortality of thorny, smooth, andwinter skates in 4Tand 4VW. Skates are known to be a component of grey seal diets inthese areas (Benoit and Bowen 1990; Beck et al. 2007). Assumingcommon forms of functional response (e.g., Gascoigne and Lipcius2004) for grey seals preying on skates, an increase in themortalityrate of skates due to predation by grey seals would be expectedgiven the dramatic increase in seal abundance and the declines inabundance of large skates in these ecosystems. Taking into ac-count the seasonal distributions ofwinter skate and grey seals andthe energetic requirements of grey seals, Benoît et al. (2011b) con-cluded that predation by grey seals could account for all of theelevated mortality of adult 4T winter skate even if they comprisea negligible (<0.1%) percentage of the grey seal diet. Given therelatively low biomass of other skates in these ecosystems and thehigh energetic demands of the large grey seal herd in these areas,an important contribution of predation by grey seals to the ele-vatedmortality of large individuals in the other skate populationsin 4T and 4VW seems plausible.

If increased predation by grey seals has resulted in increasedmortality of large individuals in these skate populations, why hasmortality not also increased for small juveniles in these popula-tions? One possibility is that reduced predation by collapsed de-mersal fishes more than compensates for any increase in

predation on small fish by grey seals. For example, the estimateddecline in consumption by predatory fish between the mid-1980sand the mid-1990s in the 4T ecosystem greatly exceeds the esti-mated increase in consumption by grey seals over this period(Savenkoff et al. 2007). Moreover, grey seals may selectively preyon fish larger than small juvenile skates (Benoît et al. 2011a).

Unlike in the 4T and 4VW areas, there is little evidence forincreases in the mortality of large skates in the 4X area, despiteongoing fisheries for demersal fish in this area. Only thorny skateshowed evidence of increased mortality of large individuals inrecent years in 4X. Unlike in the other areas, this can be attributedto a recent increase in fishing mortality (Simon et al. 2012). Thisdifference between areas is consistent with geographic differ-ences in grey seal abundance. In contrast with the 4T and 4VWareas, grey seal abundance has remained relatively low in the 4Xarea (Trzcinski et al. 2009).

Like in the 4T and 4VW areas, the model estimates of mortalityof small juvenile skates also declined in the 4X area in recentyears. The biomass of large demersal fish has also declined in 4X(e.g., Clark and Emberley 2010), though a rapid collapse in thisbiomass like that observed in the 4T and 4VW areas in the early1990s did not occur in this area. Shackell et al. (2010) reportedincreases in the biomass of prey fish in this area in the 1990s and2000s, which they attributed to decreases in themean body size ofpiscivorous fish. Also, while important groundfisheries persist inthe 4X area, fishing effort has declined in the 1990s and 2000s(based on estimates of fishing mortality; e.g., Clark and Emberley2010; Mohn et al. 2010). Thus, the recent declines in estimatedmortality of small juvenile skates in 4X may also reflect declinesin predation by large piscivorous fish and in bycatch in fisheriesdirected at other demersal fish.

Patterns in the time series of relative abundance that our mod-els have interpreted as changes in mortality could instead reflectemigration or immigration (e.g., Frisk et al. 2010) or changes inavailability to the surveys. Our initial models assume that skatesin each of the 4T, 4VW, and 4X areas represent closed populations.This assumption is clearly valid for winter skate in 4T, which aredistinct from winter skate elsewhere (Swain et al. 2009). The rela-tivelyminor seasonalmovements indicated by seasonal surveys in4T (Clay 1991; Darbyson and Benoît 2003) and in 4VWX (Simon

Fig. 8. Mortality trends of thorny skate, smooth skate, and winter skate aggregating individuals over ecosystems. Heavy horizontal lines arethe medians of the posterior distributions for mortality parameters, boxes delimit the 25th and 75th percentiles of these distributions, andvertical lines delimit the 2.5th and 97.5th percentiles.

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et al. 2012) and the limited movements indicated by tagging ofthorny skate and other small skates (Templeman 1984) are alsoconsistent with the assumption that the skates in these areasrepresent local populations. Furthermore, the same basic pat-terns in mortality, decreasing mortality for small juveniles andincreasing mortality for larger individuals, persist after data havebeen aggregated over larger areas (4TVW and 4TVWX for thornyand smooth skates, 4VWX for winter skate). These patterns inmortality are consistent with the changes in natural mortalityobserved for other demersal fishes in these ecosystems, includingspecies such as Atlantic cod for which population structure is wellestablished (e.g., COSEWIC 2010).

The distribution of thorny skate is well covered by the summerand early fall surveys of the 4TVW area. This is particularly truefor the 4T area, where changes in the availability of thorny skateto the September survey do not appear likely despite shifts inthorny skate distribution (Swain and Benoît 2006). On the otherhand, 4T winter skate are distributed in inshore areas that are notentirely covered by the September survey, so that changes in theavailability of winter skate to this survey are possible, particularlyif winter skate distribution is density dependent (MacCall 1990).However, preliminary analyses suggest that effects of possiblechanges in availability on estimated trends in the abundance of 4Twinter skate appear to be slight (Swain et al. 2009). The areawherechanges in the availability of skates to the annual survey are mostlikely is the 4X area. Skate distributions in the 4X area appear tobe continuous with distributions in the adjoining western Gulf ofMaine (Simon et al. 2012). It is possible that changes in availabilityto the July survey contribute to apparent changes in mortality inthe 4X area (or conversely obscure changes in mortality in thisarea). However, this area where spurious estimates of mortalitychange are most likely is also the area where mortality is esti-mated to have changed the least.

The patterns in the data that we have attributed to changes inmortality cannot instead be attributed solely to changes ingrowth. In the sensitivity analyses with 4T thorny skate, good fitsto the abundance trends required decadal variation in mortalityparameters even if transition probabilities were allowed or as-sumed to vary decadally within plausible limits (corresponding toa halving of growth rate at juvenile stages between the 1970s andthe 2000s). Good fits to the data without allowing decadal varia-tion in mortality required decadal changes in transition probabil-ities that far exceeded physiologically plausible limits (i.e.,corresponding to changes in growth rates by an order of magni-tude). Swain et al. (2009) reported similar results in sensitivityanalyses using data for 4T winter skate. Furthermore, strong com-pensatory responses are not expected in elasmobranchs (e.g.,Stevens et al. 2000; Frisk et al. 2010), and density-dependentchanges in growth rate appear to be modest in these fishes (Smin-key andMusick 1995; Cassoff et al. 2007), again consistentwith theview that the patterns in the data reflect changes in mortalityrather than extreme changes in growth. Thus, while it is possiblethat declines in growth rates contribute to declines in the abun-dance of large juvenile and adult skates (relative to abundance atsmaller sizes), increases in mortality of large individuals are alsoneeded to account for these trends.

Increases in the abundance of small juvenile skates (relative toadult abundance) potentially reflect decreases in the mortalityrate of these skates (Z1), increases in recruitment rates (r), or both.In the sensitivity analyses with 4T thorny skate, models fit aboutequally well when either or both of these parameters were al-lowed to vary decadally. When decadal variation was allowed forboth parameters, variation was estimated for Z1 and not for r.Nonetheless, variation in either parameter could account for thetrends in the data. However, given thewide variation in r requiredto account for these trends and the morphological and physiolog-ical constraints on the extent of variation that is plausible forfecundity, much of this variation would need to reflect variation

in mortality of embryos and hatchlings. Thus, the stage-specificabundance data suggest declines inmortality of early life stages ofskates, either of small juveniles (juvenile stage 1 in Table 1) or ofembryos and hatchlings prior to recruitment to stage 1, or both.

Mortality estimates are affected by the catchability adjustmentsapplied to the data. However, while these adjustments affect theestimated level of mortality, they do not affect the decadal patternsestimated by the model (i.e., mortality increasing, decreasing, orwithout decadal trend). Thus, while the estimated levels ofmortalityreported here are likely to be biased owing to inaccuracies in thecatchability adjustments, the estimated decadal trends in mortalityappear to be robust to inaccuracies in these adjustments.

In many areas, small-bodied elasmobranch species are increas-ing in abundance, perhaps reflecting release from predation orcompetitive release following the depletion of large sharks andrays by overfishing (Dulvy et al. 2000; Myers et al. 2007; Ferrettiet al. 2010). The southern Gulf of St. Lawrence and the easternScotian Shelf in Atlantic Canada are exceptions to this pattern. Inthese ecosystems, the abundance of mature individuals has de-clined to very low levels for thorny, winter, and smooth skates,the three small-bodied skates common in these areas. Demersalfishing effort in these two ecosystems decreased sharply in theearly 1990s, following the imposition of moratoria on directedfishing for cod, the main target species, and fishing effort fordemersal fish has remained very low since then. Despite nearly 20years with severe reductions in fishing effort, the skate popula-tions in these areas have shown no signs of recovery and in somecases have continued to decline. This lack of recovery appears toresult from increases in the mortality of large individuals (thelarger juveniles and (or) adults). These increases in mortality, co-inciding with decreases in fishing effort, appear to reflect in-creases in natural mortality. Predation by grey seals, which haveincreased to record-high levels of abundance in these ecosystems,provides a possible explanation for these increases in naturalmortality. This explanation would be consistent with the lack ofevidence for increases in natural mortality of these skates on thewestern Scotian Shelf, an areawhere grey seal abundance remainsrelatively low. If this explanation is correct, recovery of theseskate populations is not likely under current ecosystem condi-tions, even in the absence of fishing.

AcknowledgementsWe thank Tobie Surette for developing the R functions used to

produce Figs. 3 and 4 and for other assistance related to graphicsin R. We also thank anonymous reviewers for helpful commentson this work.

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