Connectivity of lobster (Homarus americanus) populations in the coastal Gulf of Maine: part II....

Connectivity of lobster (Homarus americanus) populations inthe coastal Gulf of Maine: part II. Coupled biophysicaldynamics

LEWIS INCZE,1,*HUIJIE XUE,2 NICHOLASWOLFF,1 DANYA XU,2 CARL WILSON,3

ROBERT STENECK,2 RICHARD WAHLE,4

PETER LAWTON,5 NEAL PETTIGREW2 ANDYONG CHEN2

1Aquatic Systems Group, University of Southern Maine,Portland, ME 04101, USA2School of Marine Sciences, University of Maine, Orono, ME

04469-5741, USA3Maine Deparment of Marine Resources, West BoothbayHarbor, ME 04538, USA4Bigelow Laboratory for Ocean Sciences, West Boothbay

Harbor, ME 04538, USA5St Andrews Biological Station, Department of Fisheries andOceans, St Andrews, NB E5B 2L9, Canada

ABSTRACT

We used a coupled biophysical model to investigatelarval transport and connectivity patterns in the Gulfof Maine lobster (Homarus americanus) population.Biological ‘particles’ were released at over 21 000locations every 10 days over a 4-month hatchingperiod, and were followed from hatching through latepostlarval stage. In addition to circulation and dis-persion, model calculations included spatial patternsof egg production, temporal patterns of hatching,temperature-dependent development, vertical distri-bution and mortality. We ran the model for threelarval production seasons using the same hatchingpatterns and individual-based modeling parametersbut different flow patterns in the coastal current sys-tem. Model results gave distribution and abundancepatterns of competent postlarvae that closely resem-bled observed, alongshore patterns of lobster settle-ment density. We evaluated the relative contributionof all source regions to the total number of competentpostlarvae in a series of medium-size zones along thecoastal shelf, many of which are used in lobster

management. Connectivity depended on many factors,including patterns of egg production and transport,and the location and size of the receiving zones. Selfrecruitment ranged from a few percent to >90% ofcompetent postlarvae. Although it was common forpostlarvae to come from many, often distant, sources,most of the competent postlarvae in a zone originatedwithin one to two zones in the prevailing ‘up-stream’direction, forming shorter connections along the coastthan the energetic currents might otherwise suggest.Inshore migrations during summer hatching maycontribute to these shorter patterns of connectivity.Transport in the prevailing ‘upstream’ direction wasalso indicated.

Key words: advection, coastal current, connectivity,coupled biophysical model, egg production, hatching,Homarus americanus, individual-based model, larvae,lobster, mortality, postlarvae, transport

INTRODUCTION

Coupled biophysical models that embed ‘biological’particles into simulated model flow fields provideimportant insights into potential patterns of transportand connectivity in populations of marine organismswith planktonic life stages (Cowen et al., 2006; Miller,2007; Briones-Fourzan et al., 2008). As these modelsimprove in resolution and realism (Fiksen et al., 2007;Paris et al., 2007) they can be used to address a growingnumber of questions concerning the conservation ofmarine biodiversity and development of sustainablefisheries practices. For example, larval development andmortality rates can be coupled with variability of oceanforcing to understand the spatial distribution of repro-duction needed to sustain populations over their naturalranges (Botsford et al., 2001; Shanks et al., 2003).Although the study of the drivers of mortality in the seaand their variability form an inherently interesting andinformative part of ecological and population studies(Gallego et al., 2007), such specific, process-relatedestimates are usually not available over large areas andmultiple years. In such cases, estimates of average

*Correspondence. e-mail: [email protected]

Received 20 October 2008

Revised version accepted 21 July 2009

FISHERIES OCEANOGRAPHY Fish. Oceanogr. 19:1, 1–20, 2010

� 2009 The Authors. doi:10.1111/j.1365-2419.2009.00522.x 1

mortality serve to constrain estimates of connectivityover large scales (Cowen et al., 2006).

In this study we used the circulation model ofthe Gulf of Maine Ocean Observing System (Xueet al., 2005) to quantitatively examine connectivity oflobster (Homarus americanus) populations in the Gulfof Maine (Fig. 1). The operational nature of the modelhas led to extensive performance evaluation in allseasons and over several years, and has revealed dis-tinct interannual differences in the summer residualcirculation (Xue et al., 2008). The objective of thepresent study was to understand the degree to whichsettlement (benthic recruitment) along different sec-tions of the coast was driven by distant versus local eggproduction under these varying summer circulationpatterns. Adjusting the model results of postlarvalabundance to fit field observations of abundance pro-vided estimates of average planktonic mortality thatwere higher than originally assumed.

The lobster fishery has become the most lucrativefishery in the coastal Gulf of Maine over the past twodecades, due to an apparent increase in the abundanceof lobsters as well as a decline in other historicallyimportant species (Incze et al., 2006). Reproductivefemale lobsters carry their eggs attached to the ventralsurface of the abdomen for 9–10 months, during whichthey may undertake seasonal movements into deeperwater in fall and winter and shallower water duringspring and summer (Lawton and Lavalli, 1995; Cowanet al., 2007). Eggs hatch in late spring and summer(Ennis, 1995) to produce pelagic larvae (three stages)and postlarvae that remain in the water column for 2 ormore weeks, depending on temperature (MacKenzie,1988; Annis et al., 2007). Approximately halfwaythrough postlarval development, lobsters becomecompetent to settle and can begin recruiting to the

bottom (Cobb et al., 1989). Along the central coast ofMaine, settlement begins in mid-July and lasts 6–8 ormore weeks (Incze and Wahle, 1991; Incze et al.,2000b). Settlement densities are positively correlatedwith postlarval abundance (Wahle and Incze, 1997;Incze et al., 2000b) and can show large variationsbetween years (Incze et al., 2006). In addition, somesections of the coast have characteristically highersettlement densities than others (Incze et al., 2006),although several factors may be involved, such aspostlarval supply, predators, and environmental con-ditions (Wahle and Steneck, 1992; Steneck and Wil-son, 2001). The total amount of settlement in an area isa function of habitat abundance and distribution, andis beyond the scope of this paper (but see Incze et al.,2003 and Drew and Eggleston, 2006 for discussions).

Harding and Trites (1988) and Incze and Naimie(2000) demonstrated the potential for long-distancetransport of lobster larvae in the cyclonic coastalcurrent system that flows at speeds of 5–30 cm s)1

around the Gulf of Maine during summer months(Pettigrew et al., 2005). However, the quantitativeaspects of transport and recruitment dynamics of lob-sters are complex, and depend on numerous hetero-geneous and variable aspects of the system and thebehavior of the organisms themselves. These includespatial differences in egg production, spatial andtemporal differences in the flow field and water tem-perature, the protracted period of hatching, stochasticprocesses, dispersion and mortality of the planktonicstages, and ontogenetic and environmentally stimu-lated changes in the vertical distribution of theplanktonic life stages and their propensity to settle.

In an earlier paper (Xue et al., 2008) we modeledthe transport of particles released at 21 740 locations(approximately 4-km spacing) every 10 days

Figure 1. Gulf of Maine study area,showing 100 m isobath and zones used inthe analyses. Abbreviations are: BB(Browns Bank); SWNS (SouthwestNova Scotia); DGBY (Digby); LBF andUBF (lower and upper Bay of Fundy);GMI (Grand Manan Island); A-G(Maine Lobster Management ZonesA–G); NH (New Hampshire); MB(Massachusetts Bay and Cape Cod Bay);OCC (Outer Cape Cod); BIS (BlockIsland Sound); FC (Fippinnes andCashes Ledges).

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� 2009 The Authors, Fish. Oceanogr., 19:1, 1–20.

throughout the lobster hatching season, June throughSeptember, 2002–2004, in water depths £100 m. Theparticles occupied specific depths in the water columnand ‘developed’ according to ambient temperatures atrates similar to lobster larvae, but there was no simu-lation of spatial or temporal differences in reproduc-tive output and the particles experienced no mortality.The results provided an overview of potential trans-port patterns during summer months in 3 yrs in whichthe continuity of flow along the western margin of theGulf of Maine varied significantly. The years werecharacterized as ‘blocked’ (low connectivity from eastto west, 2002), ‘flow-through’ (2003), and intermedi-ate (2004). In the present paper, we estimated thespatial and temporal patterns of egg hatching andweighted the particles according to these estimates ateach place and time of release. We assigned a tenta-tive, fixed mortality rate based on prior work (Inczeet al., 2003) and calculated connectivity based onpatterns of larval production and transport coupledwith dispersion and mortality. We compared theresulting postlarval abundances with field observationsand adjusted the mortality rate to bring model andfield data into agreement.

MATERIALS AND METHODS

Individual-based, coupled biophysical model

We used the operational circulation model of the Gulfof Maine Ocean Observing System [GoMOOS (http://www.gomoos.org); Xue et al., 2005; ] which is based onthe Princeton Ocean Model (Mellor, 2003). Themodel uses an orthogonal curvilinear grid with 22

sigma-levels in the vertical and a horizontal resolutionthat varies from 3 to 5 km; it includes the ScotianShelf, Gulf of Maine, Georges Bank, part of theSouthern New England Shelf and the adjacent sloperegion (Fig. 2). The open boundaries are forced withdaily ‘nowcasts’ from the Regional Ocean ForecastSystem (http://polar.ncep.noaa.gov/cofs/). Surfaceforcing within the model domain is obtained from theNational Center for Environmental Prediction(NCEP) NAM 221 AWIPS Grid (http://www.nco.ncep.noaa.gov/pmb/products/nam/), and daily fresh-water inputs from the Gulf’s six major rivers areobtained from the US Geological Survey. A particle-tracking subroutine (Bernsten et al., 1994) is embed-ded in the circulation model to simulate transport anddispersion of particles in the water. A random walkterm was used to approximate the effects of sub-gridscale processes on particle trajectories (Xue et al.,2008). To simulate the development and transport oflarvae and postlarvae, we used an individual-basedmodel approach in which modeled ‘particles’ developat temperature-dependent rates and follow simpleontogenetic changes in depth (see below).

In the first part of this study (Xue et al., 2008) weestablished 15 analysis grids for summarizing particledistributions. Seven of these grids are formal LobsterManagement Zones (LMZs) used in the state ofMaine. The others – we added three more for a total of18 in this study – are geographical units that we cre-ated for analysis (Fig. 1). For simplicity we refer to allof these as ‘zones’. These zones provide a practicalscale for aggregating model results in geographic termsuseful to the industry and management, and this step

Figure 2. Model grid. Egg release pointsare shaded black and are inside the100 m isobath.

Connectivity of lobster populations: part II 3


avoids too much focus on small-scale patterns orresults where prediction bears a high degree ofuncertainty.

Larval production and timing

The spatial and temporal pattern of production(n km)2) of newly hatched Stage I larvae was derivedfrom field data for each Maine LMZ and for the zonereferred to as NH. No comparable data exist in theother zones. A series of calculations was required,beginning with the estimated abundance and sizedistribution of female lobsters. The base estimatescame from 312 trawl samples collected at bottomdepths of 8–97 m by the Maine Department ofMarine Resources during September and October,2000–2003. Abundance, sex, size, presence ⁄ absenceof eggs, and egg development stage (Perkins, 1972)were recorded. The swept area of the trawl was usedto estimate abundance (n km)2). This likely is anunderestimate because trawling is conducted on rel-atively open bottom (thus missing rocky habitat) andbecause trawls probably fail to catch (because theyover-ride) some individuals in the trawl path. Wecompared trawl-generated abundance estimates oflarge lobsters (carapace length, CL, ‡90 mm) withvisual counts from ROV (remotely operated vehicle)and research submarine (‘sub’) surveys (a total of 102dives for the two platforms). ROV and sub data werecollected mostly over open bottom, sampling from138 m2 to 3516 m2 per sample at depths from8–122 m in July, August and September 1997, 1999and 2001. We also compared trawl estimates of lob-ster abundance with SCUBA surveys (N = 70 dives)conducted at depths <14 m in July and August, 1999.Comparisons were made only for lobsters with CL‡90 mm. Comparisons were pooled across years andgrouped by depth, proximity to each other, and zone.Although size (from all survey methods) and otherbiological data (from SCUBA) were available, samplesizes were too small to warrant further partitioning ofthe data.

To estimate the temporal and spatial patterns ofhatching, we used data collected in collaboration withlobstermen during normal commercial fishing (trap-ping) operations. Data came from 45 309 trap haulsmade during July and August, 1998–2002. Traps werelocated throughout the Maine coastal shelf to depthsapproaching 100 m, though most were in depths<50 m. The timing of hatching was calculated fromthe proportion of lobsters carrying newly extrudedversus late-stage eggs (Perkins, 1972). We binned thedata over 10-day periods to compensate for generallylow catch rates of ovigerous females. We first looked

for a difference in timing between eastern and westernareas of Maine (Zones A–C and D–G, respectively:Fig. 1), and took the mean of the two polynomial fitswhen differences between the two areas were found tobe small (£6 days). The mean hatch curve was nor-malized to one (total hatch) to calculate the propor-tion of eggs hatched each day. To determine thespatial distribution of hatching, we examined thedistribution of female lobsters with late-stage eggs orsigns of recent hatching (remains of egg stalks on theventral surface of the abdomen). Data were expressedas catch per trap haul (CPTH) and entered into ageographical information system (GIS) for analysis.CPTH was binned over 10-m-depth intervals afterstratifying each zone for large-scale patterns such asthe decreased abundance of ovigerous females in themiddle and upper reaches of large bays and estuaries.The product of this analysis was a map of the spatialand temporal distribution of hatching within eachzone. Potential sources of bias in the trap catches(Miller, 1990; Fogarty and Addison, 1997) could notbe evaluated critically and are discussed later.

The numbers of Stage I (SI) larvae produced peryear in NH and in each Maine LMZ were calculated bymultiplying adult female lobster abundance per zone bythe size distribution (CL) of lobsters, appropriatematurity ogives, a size–fecundity relationship, aspawning frequency, and an egg mortality rate. Sizedistribution was specific to each zone and maturityogives varied from west to east. Maturity, defined as theproportion of females at size that are sexually mature, isgiven by the relationship M = 1 ⁄ [1 + e(a+b*CL)] wherea and b have the following values: 14.898635 and0.1738515 for zones NH, F and G; 23.28458085 and)0.264004712 for zones D and E, and 31.6769441and )0.3444601 for zones A, B and C (AtlanticStates Marine Fisheries Commission, 2000). Fecundity(N eggs per female) is given as F = (6.06*10)4)*CL 3.7227 (Estrella and Cadrin, 1995). The spawningfrequency is determined by the intermolt period. Theminimum intermolt period for a sexually maturefemale lobster is 2 yrs, and this gradually increases to7 yrs at 130 mm CL (we used real numbers instead ofwhole integers: Atlantic States Marine FisheriesCommission [ASMFC], 2000). We assumed an eggmortality rate of 0.40 from extrusion (when ‘F’ is cal-culated) to hatching (cf. Perkins, 1971; Campbell andBratty, 1986).

SI production was distributed spatially and tempo-rally according to our analysis of the commercial trapdata (see above), and the spatial pattern was trans-ferred to a ‘grid’ of polygons constructed about thenodes in the circulation model. Polygons were defined

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by the midpoints along all possible lines connectingneighboring nodes, and thus were octagonal in shapeand approximately 16 km2 each. Trap and trawl datawere not very abundant in the middle and upperportions of most bays, but these data and otherobservations showed that a reduction in larval pro-duction estimates was warranted for these areas. Wereduced larval production to 50% of the nearestcoastal values in the middle sections of large coastalembayments, and to 1% of coastal values in the upperreaches of these bays and in estuaries.

We did not have the full complement of dataneeded to calculate SI production for other areas ofthe Gulf of Maine. Consequently, for Canada, we usedthe Maine-wide average of the annual SI productionfor each depth interval (0–10, 10–20 m, etc.). For MBand OCC we used SI production data from zone F,which was better sampled than zone G. The effect ofthese estimations on model results is discussed later.Hatching, once initiated, was assumed to follow thesame temporal curve as in Maine. The beginning datefor hatching in NH was assumed to be the same asMaine (first appreciable SI on YD 152). Beginningdates were adjusted 10 days earlier in the south (forMB and OCC) and up to 40 days later in the north, asfollows: YD 172 for Browns Bank; 182 for SouthwestNova Scotia and the Upper Bay of Fundy; and 192 forGrand Manan Island, Digby and Lower Bay of Fundy(Fig. 1). The northern (Canadian) adjustments werebased on egg conditions from 101 792 trap hauls inCanadian lobster management districts (Lobster Fish-ing Areas) from May through November, 1977–1989.

Larval IBM and model runs

Larval development, vertical position in the watercolumn and mortality were represented by a simpleindividual-based model (IBM, Table 1) coupled withthe operational circulation model of the Gulf of Maine

Ocean Observing System, which has an average hor-izontal resolution of about 4 km (Xue et al., 2005).Transport and dispersion were simulated using a par-ticle-tracking subroutine with a random walk term(Xue et al., 2008). Ten ‘super-particles’ (henceforth‘particles’) were released at each model node wherewater depth was £100 m (Fig. 2), resulting in 21 740particles per release. Particles were released on the 1st,11th and 21st day of each month from 1 June throughSeptember, were independently subjected to the ran-dom walk term, and were followed for 60 days afterrelease. Each particle represented a large number ofindividual larvae (see below), and developed throughtime according to the rate specified by the IBM andthe ambient temperature. The model kept track of theproportion of accumulated development per stage, andthe particle (representing a group of larvae) advancedto the next stage when the accumulated developmentequaled 1.0 (Xue et al., 2008). In this study, particlesrepresenting stage I–III larvae were maintained at afixed depth of 15 m. The depth immediately changedto 1 m when larvae advanced to stage IV (postlarvae,see Table 1).

The model was run with all particles being of equalrank and experiencing no mortality. Results (time,location and larval development within stage) werestored and post-processed to (1) weight the particlesat the time of their release according to the spatialand temporal (seasonal) patterns of SI production(n km)2 day)1), and (2) apply the mortality term.Each release included SI production for that date andthe following 9 days (in some cases 10 days) toaccount for all hatching during a season. Model flowfields show strong consistency over this time intervalduring summer months. Converting from particlesback to population estimates that were applicable tomodel polygons was technically easy (particle weightswere originally defined by the number of larvae per

Table 1. Biological values used in the initial larval and postlarval individual-based model.

Property Stages Value Source ⁄ explanation

V SI-SIII 15 m Incze, unpubl. field dataPL 1 m Annis (2005)

z SI 0.3 This paperSII-PL 0.06 Incze et al. (2003), adjusted for

faster development ratesD SI 0.4[851(T)0.84))1.91] Annis et al., 2007

SII 0.4[200(T)4.88))1.47] Annis et al., 2007SIII 0.4[252(T)5.3))1.54] Annis et al., 2007PL 0.4[0.358833T2 ) 14.316T + 156.895] Annis et al., 2007

V, vertical distribution (a single depth); z is the specific mortality rate, z = )ln(Nt)N0), where N = number of larvae at thebeginning (N0) and end (Nt) of the stage, and t is measured in days; D = stage duration, in days; T is temperature (�C).



unit area), but could be unreliable if only a fewparticles were present. To avoid this, we binned theparticles over 5-day periods, which gave large numbersof particles per polygon except for a few of the mostoffshore locations.

The model time-step was 216 s, but post-processingused daily time-steps beginning with the mid-nightreleases (hatching). The model was run for the egghatching and larval transport seasons during 2002,2003 and 2004, which offered the following con-trasting flow conditions in the Coastal Current Sys-tem along the Maine coast: a strong discontinuitybetween east and west; high flow-through from east towest; and intermediate conditions, respectively (Xueet al., 2008). All runs used the same egg productionpatterns (the 2000–2003 average) and identical IBMproperties.

Our analyses focused on the distribution andabundance of postlarvae – information carried by thelocation and biological ‘properties’ of individual par-ticles. We calculated the average daily concentrationof postlarvae (n km)2) in each model polygon(16 km2) and summed the daily averages for eachpolygon over the season. Plots of the resulting datashowed the spatial distribution of postlarvae (PL) inunits PL-days km)2 yr)1, which we compared withfield data (see Incze et al., 2006 and later discussion).We examined within-year patterns of timing and peakabundance of postlarvae in Zone E, where we haveextensive field data for comparison.

Postlarvae that were competent to settle weredefined as stage 4.5 (halfway through postlarvaldevelopment, Cobb et al., 1989). The seasonal stand-ing stock of competent postlarvae was tabulated foreach zone after dividing into the following depthareas: £50 m, 51–100 m, and >100 m. Using the his-tories of each particle, we constructed connectivitymatrices for the above zone and depth areas toexamine the relationships between source (egghatching) and sink regions, where the sink was definedas the zone where the resulting postlarvae becamecompetent to settle. Specifically, we were interested inthe degree of self-recruitment versus allochthonoussupply, or subsidy, in various zones. We also quantifiedexchanges between the inner (0–50 m) and outer(50–100 m) shelf regions, and ‘losses’ of reproductiveeffort to areas >100 m deep. We examined interannualdifferences in patterns of supply through an inverseanalysis of release points contributing to zone E.Finally, we examined the effect of various mortalityrates on the seasonal abundance patterns.

We used GIS tools to measure the area of each zoneand the width (along-shelf direction) of each zone

from A to NH, using a straight line or simple curveapproximating the 50-m isobath.

RESULTS

Based on trawl data, the size frequency distribution offemale lobsters ‡60 mm CL (minimum size at sexualmaturity) varied little along the coast of Maine andNew Hampshire except that zone C had a greaterproportion of lobsters >85 mm CL. The density(n km)2) of all female lobsters ‡60 mm CL, as well asthe density of ovigerous lobsters and annual egg pro-duction, was greatest in zone D and declined both tothe north and south (Fig. 3). The proportion of femalelobsters ‡60 mm CL that were ovigerous, based onmaturity ogives and molting frequency calculations,was minimum (0.05) in zone A and maximum (0.18)in zone C, with the other zones ranging from 0.09 to0.15.

The mean density (n km)2) of large lobsters(‡90 mm CL) from ROV and sub transects showed anincreasing trend with increasing trawl densities, andaveraged approximately 30% higher. However, theregression was not statistically significant and could

Figure 3. Characteristics of female lobster populations andegg production in Zones A–NH, 2000–2003.

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not be used to adjust the trawl estimates. Likewise,SCUBA data were too variable to distinguish statis-tically between lobster abundance values over openareas (sampled by trawls, ROV and sub) comparedwith rocky bottom. Thus, we could not derive a hab-itat ‘correction’ for the trawl estimates of abundance.The autumn trawl data showed the same alongshorepattern of abundance as the traps (top panel in Fig. 3),and became the sole basis for estimating total eggproduction in each zone.

From the trap sampling, egg condition was recordedfor 15 117 ovigerous lobsters, 4455 of which haddeveloping eggs that would hatch that year. Anadditional 1597 lobsters had recently shed eggs. Theaverage of the egg condition data indicates a hatchingseason extending from approximately YD 140 to YD280 (mid May to early October) in Maine, with themajority of hatching taking place within a period of80–90 days (Fig. 4). Data indicated a possibly laterbeginning to the hatching season in 1998, but thesmaller sample size had negligible effect on the overallaverage. The polynomial fits to the hatching data(proportion of present-year eggs that had alreadyhatched) were significant for both eastern (A–D) andwestern (E–G) zones: r2 = 0.88 and 0.89, P = 0.005and 0.002, respectively. Canadian data likewiseshowed that most hatching took place over a period of90 days or less. The catch per trap haul of females withmature eggs in Maine indicates a strong tendency

toward inner shelf locations at the time of hatching(Fig. 5).

Each model year generated more than 7 millionrecords of date, larval stage with fractional proportionof within-stage development, and geographical loca-tion. Results for the yearly distribution and abundanceof postlarvae on their first day of competence to settle(stage 4.5) are shown in Fig. 6, and for cumulativeyearly postlarval days of all postlarvae (regardless ofdevelopment) in Fig. 7. The abundances illustrated inFig. 6 use a GIS classification scheme known as ‘nat-ural breaks’ (Jenks), which divides classes at bound-aries where there are relatively large jumps in datavalues. We added a zero to this scheme. Maps of sea-sonal abundance of postlarvae 10 days after attainingcompetence show patterns similar to Fig. 6 and are notshown here. Particularly high postlarval abundances,both competent and total, appear in the Upper Bay ofFundy, along the mid-coast of Maine, and in CapeCod Bay. Chronically and conspicuously low abun-dance areas include zones A–C and NH. Other lowvalues, for BB, SWNS, and OCC, should be consid-ered only partial results because we did not modelpotential upstream sources of larvae for BB andSWNS, and did not model local egg production forOCC (Fig. 2). BIS did not receive any competentpostlarvae from the modeled egg production zones andwas dropped from further consideration.

Differences between the ‘blocked’ year (2002) andthe ‘flow-through’ year (2003) occurred primarily inmid-coast Maine (zones D and E) and in Massachu-setts ⁄ Cape Cod Bays (zone MB), with the ‘blocked’year yielding higher total postlarval days (Fig. 7) andgreater abundances of competent postlarvae (Fig. 8) inall three zones. Connectivity between all zones in themodel domain is shown as a matrix of values inTable 2, emphasizing the perspective from therecipient zones (‘sinks’). Of the zones where we canreasonably account for all the plausible significantsources of SI production, the majority experiencedsubstantial amounts of self-recruitment, wherein alarge proportion of competent postlarvae originatedfrom eggs within the zone. This was not true for zonesLBF, A, E and G, which depended on upstream sourcesfor most of their postlarvae.

We examined zone E more closely because it is thebest-studied zone with respect to lobster early lifehistories (Incze et al., 2006 and references therein).The majority of competent postlarvae in zone E camefrom its nearest upstream neighbor, zone D, in theblocked and intermediate years (Table 2), with a moreinshore distribution of sources in the former (Fig. 9).In the flow-through year, the majority came from

Figure 4. Proportion of lobsters that have released eggs(post-hatch) compared to the total of pre- and post-hatchfemales in traps, binned over 10 days intervals, 1998–2002.East data are from zones A–C, and west from zones D–G.Solid line is the mean of the polynomial equations describingthe two data sets.



zone C, two zones away (Table 2). The maximum self-recruitment in zone E (10%) occurred in the blockedcirculation of 2002. The pattern of contributions fromzones other than C and D varied between years.Competent postlarvae in zone E came from as far awayas Browns Bank to the north (Fig. 9B) and Cape Annto the south (Fig. 9A,C). However, contributions fromzones other than C and D were always small (Table 2).

The predicted temporal patterns of postlarvae inthe inner coastal shelf (<50 m) of zone E show con-siderable within-year fluctuations and different inter-annual patterns (Fig. 10), with seasonal maximamostly in the range of 20–35 PL 1000 m)2 (note thatthe area units have been reduced here for convenienceto match prior published results). Both in the model

Figure 5. Stage I larval production pre-dicted from the egg production esti-mates. Estimates in the upper bays werefurther reduced in model runs (seeMaterials and methods). Data for zonesA–G (black outline, cf. Fig. 1) are basedon trawl and trap data from the coastalshelf in each zone for the years 2000–2003. Values for areas to the north andthe offshore banks and ledges wereextrapolated from the mean depth-spe-cific values for zones A–G; values to thesouth were extended from zone F.

Figure 7. Integrated annual postlarval abundance (all molt-cycle stages) for areas £50 m: 2002 (black), 2003 (gray) and2004 (white).

Figure 6. Annual postlarval-days (PL-d) for competentpostlarvae, summing daily average abundance in each16 km2 polygon. All runs used the SI larval production inFig. 5.

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and in field studies, the same postlarvae are countedon numerous succeeding days, except where mortalityand ⁄ or advection intervene. This is knowable in themodel, but not in the field; hence our use of PL-daysfor any summation over time. The seasonal postlarvalabundance in zone E averaged approximately 1000PL-days 1000 m)2 yr)1. The maximum and totalabundances are all high compared with field observa-tions.

The across-shelf transport of larvae hatched in zonesA–G (Maine) is summarized in Table 3. Of the SIlarvae, 81% originated inside the 50-m isobath. Ofthose that survived to become competent postlarvae,42–56% remained within the 50-m isobath somewherein the Maine zones. A total of 22–37% had beentransported to the outer coastal shelf (50–100 m) butremained in Maine, and 14–18% had been transportedbeyond the 100-m isobath. Losses to regions outsidezones A–G totaled 6% or less. SI larvae produced inshelf depths 50–100 m deep in zones A–G accountedfor 19% of SI hatched in Maine. Of the resultingpostlarvae, 26–33% were still in that depth zone whenthey became competent to settle; 26-30% had beentransported to areas inside the 50-m isobath; and 28–38% had been transported beyond the 100-m isobath.Losses to regions outside Maine ranged from 5 to 12%over the 3 yrs. A small number had ‘collided’ with thelandward boundary of the model and were removedfrom the calculations (Xue et al., 2008). Physicaldimensions of the zones and areas are given in Table 4.

DISCUSSION

This paper is the first spatially explicit populationmodel to cover the early life history from egg pro-duction through postlarval development for American

lobsters. We divide our discussion into three parts: anassessment of model inputs; a comparison of modelpredictions with field data; and a summary of transportpatterns and connectivity in the Gulf of Maine pop-ulation.

Model inputs

For the core of our calculations, we were fortunate tohave inshore trawl surveys and collaborations withcommercial lobstermen during the summer fishingseason when eggs hatch. The extension of averagesouthern Maine and average Maine and NH egg pro-duction values and depth patterns to areas south andnorth of these zones was of unknown accuracy, but byincluding these estimates we could follow the poten-tial patterns of influence of sources throughout theregion. Thus, while the magnitude of influence amongthese zones remains open to debate, the basic patternsof influence were captured and could be scaled up ordown in the future. Based on the tentative Canadianegg production numbers, the influences of Canadiansources (mostly from UBF and GMI) appear to besignificant as far south as zone D (generally ‡10%), butthen diminish rapidly (<2%). Although we thoughtthis would overestimate egg production because theBay of Fundy lobster catch is approximately 10% thatof Maine (Incze et al., 2006), some Canadian expertopinions suggest it might be close.

Although we had an abundance of data fromzones A–NH on which to base our estimates of eggand larval production, it is important to recognizethat both trawl and trap data have biases in theirrepresentation of the lobster population. Trawl sam-pling was conducted over open bottom in theautumn, thus missing edge or rocky habitat, butsampling at a time when many lobsters were

Figure 8. The difference in annualabundance of competent postlarvaebetween the ‘blocked’ and ‘flow-through’years, 2002 and 2003, respectively. Onlydifferences > ±250 000 km)2 are shown.The best accounting of all stages is in thecentral coastal portion of the study area(Fig. 5).



Tab

le2.

Co

nn

ecti

vit

yb

etw

een

egg

pro

du

ctio

n(s

ou

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es,

ho

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ent

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(sin

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cal

axes

)b

ased

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each

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that

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add

up

too

ne

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ver

tica

lly)

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es<

0.0

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a‘+

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dze

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esar

ele

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lan

k.

Dia

gon

alli

nes

un

der

sco

rese

lf-r

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ues

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es‡0

.20

are

shad

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tw

her

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reg

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and

lik

ely

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com

ple

te(z

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few

com

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gp

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and

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on

esar

esh

ow

nin

Fig

.1

.

Yea

r⁄s

ink

So

urc

e

20

02

BB

SW

NS

DG

BY

UB

FL

BF

GM

IA

BC

DE

FG

NH

MB

FC

OC

CB

B1

.00

SW

NS

+1

.00

DG

BY

0.8

60

.13

+U

BF

0.0

70

.09

0.8

3+

LB

F0

.84

0.1

20

.03

0.0

1G

MI

+0

.08

0.3

90

.11

0.4

10

.02

A+

0.6

10

.19

0.1

00

.07

0.0

3B

0.0

5+

0.1

00

.06

0.7

90

.01

C+

+0

.02

0.0

10

.01

0.0

30

.04

0.8

50

.04

D+

++

0.0

50

.01

+0

.21

0.7

00

.03

+E

+0

.02

0.0

40

.33

0.4

90

.10

0.0

1F

+0

.01

0.1

20

.36

0.1

00

.42

+G

0.1

00

.31

0.2

00

.31

0.0

70

.01

+N

H0

.01

0.0

40

.18

0.1

70

.60

+M

B+

0.0

20

.98

FC

0.7

90

.02

0.1

9+

OC

C+

++

0.6

6+

0.3

3

10 L. Incze et al.


Tab

le2.

(Con

tin

ued

)

Yea

r⁄s

ink

So

urc

e

20

03

BB

SW

NS

DG

BY

UB

FL

BF

GM

IA

BC

DE

FG

NH

MB

FC

OC

CB

B1

.00

SW

NS

1.0

0D

GB

Y0

.84

0.1

6U

BF

0.0

40

.05

0.9

0+

LB

F0

.64

0.1

60

.14

0.0

7+

+G

MI

0.1

10

.03

0.3

80

.06

0.4

10

.01

A0

.17

0.0

10

.56

0.1

30

.10

0.0

2+

B+

+0

.05

0.0

50

.03

0.0

80

.79

+C

++

+0

.01

0.1

40

.05

0.1

10

.50

0.1

9D

++

++

0.1

10

.02

0.0

30

.15

0.6

9E

0.0

20

.01

+0

.80

0.1

30

.03

F+

0.0

10

.15

0.4

00

.12

0.3

3G

++

0.1

80

.24

0.1

70

.34

0.0

7N

H+

0.1

30

.03

0.1

10

.10

0.0

80

.55

+M

B+

++

++

+0

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0.9

6F

C0

.01

0.0

50

.94

OC

C+

++

++

0.0

10

.62

0.3

7

20

04

BB

SW

NS

DG

BY

UB

FL

BF

GM

IA

BC

DE

FG

NH

MB

FC

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CB

B0

.96

0.0

4S

WN

S+

1.0

0D

GB

Y0

.03

0.8

80

.09

+U

BF

0.0

50

.02

0.9

20

.01

+L

BF

0.6

50

.15

0.1

50

.05

++

GM

I0

.02

0.0

30

.44

0.1

50

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0.0

1A

0.1

00

.08

0.3

90

.17

0.1

90

.07

+B

0.0

10

.07

0.0

1+

0.0

60

.13

0.7

2+

C+

++

+0

.11

0.0

30

.05

0.5

00

.29

D+

++

0.0

50

.04

0.1

00

.14

0.6

6+

E+

+0

.01

0.0

10

.31

0.6

30

.02

0.0

2+

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.01

0.0

20

.10

0.2

60

.12

0.5

0+

G+

++

0.0

1+

0.1

20

.30

0.2

30

.28

0.0

50

.01

NH

++

0.0

80

.62

0.0

10

.03

0.0

20

.23

0.0

1M

B+

++

0.0

1+

++

0.0

10

.97

+F

C1

.00

OC

C+

+0

.01

0.5

6+

0.4

3



migrating to deeper water. We assume that these twofactors led to an underestimate of abundance overall,but we do not know by how much. Rocky habitat,especially boulders, has higher abundances of largelobsters (sampled by SCUBA during summer: Ste-neck and Wilson, 2001), but there is less of thishabitat than there is open bottom. Over open bot-tom the trawls almost certainly under-sample lob-sters, but we do not know the sampling efficiency forthe large lobsters of interest at this time of year. Weshould note that another source of uncertainty is theestimate of area swept, which could be off in eitherdirection. Importantly, patterns of abundance (dis-tribution) of large lobsters along the coast are similar

in the SCUBA (mostly summer) and trawl analyses,so the trawl data reflect regional population densitypatterns even if the absolute abundance estimatesremain in question.

In Zones A–G, we distributed the calculated zonalegg production according to the trap catch rates(CPTH) of ovigerous females during the hatchingseason. We have no reason to doubt the dominance ofinshore regions in terms of the overall pattern ofhatching, but we caution that traps, trap density,lobster abundance, lobster behavior and commercialfishing practices present many sources of potential biasfor this estimate (Miller 1995, Fogarty and Addison,1997; Jury et al., 2001), even though we focused on

Figure 9. Source locations for larvaethat became competent postlarvae insidethe 50 m isobath in Zone E (gray poly-gon). The area with the best-resolvedlarval production (Zones A–G) is out-lined in black.

12 L. Incze et al.


relative, rather than absolute, abundance. With somuch fishing effort concentrated inshore during sum-mer months (though not directed at ovigerous females,which cannot be kept), it is possible that we overes-timated the proportion of hatching taking place inwater £50 m (81%: Table 3), but other factors (seeabove) might have biased the estimate in the otherdirection. Of less concern, the binning of the oviger-ous female density estimates by zones, sub-areas, anddepth intervals led to artificially sharp boundaries inlobster distributions (Fig. 5). These artifacts probablyhad negligible impacts on the outcomes since plank-tonic stages drifted and dispersed for two or moreweeks before they were reassessed as postlarvae, andabundances were averaged over large zones.

The single depth (15 m) assigned to larval stagesI–III in the IBM is an oversimplification with some

consequences. We have found all three stages at bothdeeper and shallower depths, but ontogenetic andenvironmental patterns of vertical distribution of thevarious stages are not well resolved and may be quitevariable. Our data, for example, indicate that SIprobably has a shallower mean depth in regions wherethe water column is stratified, but turbulence, lightlevel and other factors may cause this to change. SIlasts a relatively short time, but SII and SIII havelonger development times. Although the residual flowfrom 5 to 15 m does not have a strong vertical gradientin most locations, the net effect of varying vertical

Table 3. Transport fate of planktonicstages of larvae originating in zonesA–G. The depth region and year of ori-gin (hatching) are listed on the left. Theother columns show where the resultingpostlarvae were found at the time theybecame competent to settle.

Depth of originProportion of resulting competent postlarvae found inZones A–G or elsewhere, by depth

Year Zones A–G Elsewhere

0–50 m 50–100 m >100 m 0–50 m 50–100 m >100 m

0–50 m2002 0.56 0.22 0.18 0.02 0.01 02003 0.5 0.3 0.17 0.01 0.01 0.012004 0.42 0.37 0.14 0.04 0.01 0.01

50–100 m2002 0.3 0.26 0.38 0.01 0.01 0.032003 0.29 0.31 0.29 0.03 0.03 0.062004 0.26 0.33 0.29 0.04 0.02 0.07

Figure 10. Modeled seasonal pattern of postlarval abun-dance (all molt-cycle stages) for Zone E inside the 50 misobath, years 2002–2004. Data shown are 5-days averages.

Table 4. Zone areas and dimensions. The shelf areas inside50 m and inside 100 m are given for each zone. Alongshoredistances are given for Zones A–NH using a simple curve ora straight line at approximately 50 m depth.

ZoneArea £50 m(km2 · 100)

Area £100 m(km2 · 100)

Alongshoredistance (km)

BB 0.4 29.2SWNS 27.5 61.7DGBY 7.2 19.2UBF 28.9 57.9LBF 3.8 17.6GMI 6.9 14.1A 9.4 26.2 108B 5.3 13 44C 8.3 17 49D 7.3 17.6 49E 2.8 6.3 32F 5.5 9.6 32G 7.8 19.3 69NH 5.8 13.4 36MB 30.9 52.6FIPCSH 0.1 1.8OCC 110.3 126.3BIS 35.8 36.2



distribution on the end distributions of long-livedlarvae cannot be ignored (Paris et al., 2007), and thevertical distributions need to be better known. Weselected one depth to maintain clarity through theanalysis of outcomes, but larvae near the surface wouldprobably experience more offshore transport, seen inextreme in the shallow postlarvae. An unintendedconsequence of the selected depth is that the coolertemperatures at 15 m probably led to slower develop-ment than larvae experience in stratified parts of theGulf of Maine. We will return to this point later. Theassignment of 1-m depth for postlarvae is reasonable(Annis 2005), and here the wind has a significanteffect on transport, which can be seen in model results(Xue et al., 2008).

Finally, neither the wind nor the circulation isproperly resolved near shore. Our analysis of coastalwind data from buoys and offshore islands along thecoast of Maine (unpublished data) shows an averagediel rotation and acceleration of the dominant,southwesterly geostrophic wind during summermonths (a diurnal sea breeze, Simpson, 1994). Theshoreward rotation and intensification of the windshould favor transport to, and settlement in, shallowcoastal waters at the end of the postlarval stage(Wahle and Incze, 1997; Incze and Naimie, 2000), butwe do not deal here with this final step in the linkbetween pelagic and early benthic life stages. Instead,‘background’ coastal abundances of postlarvae gener-ated by the present model can be used to estimatesettlement potential in shallow subtidal habitat, withwind and other transport mechanisms (Wahle andIncze, 1997; Shanks et al., 2000; Keafer et al., 2005),biological processes (Incze and Wahle, 1991; Inczeet al., 2000b) and habitat distributions (Incze et al.,2003, 2006) affecting realized settlement densities andfiner-scale spatial patterns. Larger-scale wind-drivenprocesses such as coastal divergence or convergenceare captured by the model and may affect on- and off-shore distributions and interactions with the along-shore flow field (Geyer et al., 2004; Keafer et al., 2005,and discussion below).

Comparisons with field data

In Fig. 6 and Table 2, we counted postlarvae that werein their first day of competence to settle, rather thanmapping all competent postlarvae. We used a singledevelopmental reference point for clarity, but addingolder competent postlarvae (age 10 days post-compe-tence) altered the results little because mortalityreduced the numbers quickly relative to the influenceof additional transport. In Fig. 7 we summed the dailycounts of all postlarvae over the entire postlarval

season because this tabulation can be compared withfield data, which generally do not have information onmolt-cycle stage (for exceptions, see Incze et al., 1997;Juinio and Cobb, 1994; James-Pirri and Cobb, 1997,Annis 2006).

Patterns of annual postlarval abundance shown inFig. 7 qualitatively agree with patterns shown by fielddata collected from 1989–2003 in Zones A–NH:comparatively low abundances in zones A and Bincreased to a maximum in zone E and declined farthersouth (Incze et al., 2006). Only a few zones weresampled after 2000, but some useful comparisons exist.In 2001, Annis et al. (2007) recorded 229 Pl-days1000 m)2 in the top 0.5 m in zones D and E, and Inczeet al. (unpublished data) measured 222, 207, 269 and215 PL-days 1000 m)2 in zone NH in 2001–2004,respectively. Field data show similar abundances inzones E and NH in most years (2001 and earlier: Inczeet al., 2000a), which does not agree with model pre-dictions for the 3 yrs of this study. This outcomesuggests that the model may underestimate transportinto the coastal bight in zone NH, which warrantsfurther scrutiny. The high values for MB are notunexpected based on earlier data for postlarvae(Fogarty and Lawton, 1983) and high settler densities(Incze et al., 2006, and next paragraph), but the highvalues in the Bay of Fundy need to be corroboratedwith field data. We offer a reminder that the eggproduction and distribution estimates for Canadianwaters were extrapolated from the Maine-wide averageand warrant future examination.

We compared model results with contemporaneoussettlement data using a time-series of settler densities,which are highly correlated with postlarval abundance(Wahle and Incze, 1997; Incze et al., 2000b). Averagesettler densities in zones GMI, A, B, C, E, F, G andMB from 2002 to 2004 (Incze et al., 2006) show apattern similar to the average model-predicted annualpostlarval abundances (Table 5). The agreement issurprisingly good, with a coefficient of determination(r2) of 0.60 for the full dataset and 0.91 for datawithout GMI. In zone GMI, observed settlement isconsiderably higher than predicted by modeled post-larval abundance. Possible explanations are (1) sourcesof egg ⁄ larval production for this settlement region aregreater than we used in the model, and ⁄ or (2) localconditions around the settlement sites are exception-ally favorable to postlarval delivery and do not rep-resent the zonal average (see Incze and Wahle, 1991;Wahle and Incze, 1997).

The model predicted first appearance of postlarvaein zone E between YD 195 and YD 210, depending onthe year (Fig. 10). We do not have field observations

14 L. Incze et al.


from Zone E in the modeled years, but data fromearlier years are only slightly earlier, in the range YD182–206 (Incze et al., 1997; Annis et al., 2007). Inzone NH in the same years as the model runs, the firstday of postlarvae was again slightly earlier in the field(YD 198, 190, and 194) than the model, but only by afew days (the two zones have similar first days).Because the model does not have sampling thresholds,whereas field sampling does, we might expect theopposite. However, the relatively small differencesbetween model predictions and reality could beaccounted for by small variations in the beginning ofhatching, water temperature, vertical distributions oflarvae, and the development rate equations. Thetemperature effect of the relatively deep modeledposition of the larvae could by itself explain thesedifferences (see earlier discussion).

Unlike the generally close agreement above, themodeled peak period of postlarval abundance in ZoneE (Fig. 10) was longer and the end dates later thanshown by earlier field data. For example, field datafrom 1989–1995 showed that postlarvae declined tovery low levels by YD 240 and were rarely found afterYD 260 (Incze et al., 2006). There may have been ashift in the season length over time. In 2001, the fieldend date in Zones D and E was YD 275 (Annis et al.,2007), and in Zone NH from 2001–2004 the end dateswere YD 276, 275, 286 and 265, respectively (Inczeet al., unpublished data). These are still earlier thanmodel results (cf. Fig. 10), but closer. We suspect thatthe model produced longer (later) seasons becauselarvae were developing at cooler temperatures in themodel than in nature due to the single, 15-m, depthwhere we placed them (see earlier discussion of thelarval IBM). Because the temperature differencebetween 15 m and shallower depths increases as theseason progresses, the difference between model resultsand observations would be larger at the end of theseason.

The temperature-dependent rates of larval devel-opment in our IBM were based on recent field data(Annis et al., 2007) that shortened development rel-ative to earlier laboratory results. These rates arealways difficult to establish from field data and areinevitably imprecise, but they appear to work reason-ably well. Possible explanations for faster developmentin the field include better nutrition, and biasing due tohigher rates of survival of fast growers (Juinio andCobb, 1994, Castro and Cobb 2005, James-Pirri andCobb, 1997; Gonzalez-Gordillo and Rodriguez, 2000).Even after correcting for the probable temperatureeffect discussed above, the revised development ratesdo not appear to be too rapid.

The final comparisons we make with field data areabundance estimates for postlarvae in zone E. Ouroriginal estimates of mortality (Table 1) gave modelpredictions of �20–35 1000 m)2 over the inner shelfduring the peak of the postlarval season (Fig. 10).Such densities are occasionally sampled in the field,but the daily averages over many samples are almostalways lower. In 2001, we observed averages of�5 1000 m)2 from YD 200–240 (Annis et al., 2007),and about the same or only slightly higher in otheryears (Incze et al., 1997, 2006). Field data came fromthe top 0.5 m of the ocean. Correcting for the fractionof postlarvae below this depth (Annis 2006) givesestimated field averages �8 1000 m)2. The differencebetween model and field results thus appears to be onthe order of 3· or more.

It may be better to compare model and field datausing the integrated seasonal abundances because theyaverage over the high-frequency variations. Themodeled seasonal postlarval abundance in Zone E(Fig. 7), at ‡1000 postlarval-days 1000 m)2 yr)1, is alittle more than three times greater than the field datawhen corrected for depth. From 1989 to 1995 therewere �200 PL-days 1000 m)2 yr)1 in the upper 0.5 min this zone (Incze et al., 2000b); in 2001, there were

Table 5. Comparison of 2002–2004 average observed settler density (n m)2 yr)1) in subtidal cobble substrate, (Inczeet al., 2006) and model predictions of postlarval abundance for the same period (this study, Fig. 7, units converted toPL-days m)2 yr)1). Data are means ± 1 SE for settlers and ±1 SD for postlarvae. Settler data for zones GMI-G are the same asshown in Fig. 6 of Incze et al. (2006); MBB is an average of data from two sites in Massachusetts Bay and one in Cape CodBay. Linear regression for all zones: Settlers = 1.5032* (Postlarvae)0.109) (r2 = 0.60); for zones A–MB, Settlers = 1.5594 *(Postlarvae)0.2703) (r2 = 0.91). The increase in concentration from postlarval to settler stages is due to time, advection andsettling behavior (Incze et al., 2000b).

Zone GMI A B C E F G MB

Observed settlers Mean 1.68 0.18 0.18 0.37 1.63 1.26 0.78 0.85(n m)2 yr)1) SE 0.72 0.05 0.12 0.09 0.21 0.56 0.4 0.53Modeled postlarvae Mean 0.61 0.23 0.4 0.54 1.18 1 0.49 0.74(PL-days m)2 yr)1) SD 0.07 0.05 0.08 0.13 0.28 0.17 0.15 0.32



229 (Annis et al., 2007). Using the depth correction,both sets of estimates give values from 307 to <350PL-days 1000 m)2 yr)1. The 2002–2004 averagedepth-corrected field abundance in Zone NH (usuallysimilar to Zone E) was 350 PL-days 1000 m)2. As withthe values from the middle of the postlarval season,the model estimates of seasonal abundance exceedfield estimates by �3· or more. We assume that thisoverestimation is typical, and the values used inTable 5 and shown in various figures should beadjusted accordingly.

The most likely source of error in our calculations islarval mortality. Egg mortality (already high), hatchingdistributions and advective losses are other possibili-ties, but it is difficult for these to account for themagnitude of difference in abundance between modeland field data results. Our sensitivity analyses show thataverage speed (and the potential for advective losses)would be slightly greater if the larval stages had beenlocated at 5 m rather than 15 m, but the potential forgreater advective losses would have been opposed byfaster development times at the warmer temperaturesthat exist near the surface. These findings suggest thatthe initial mortality rate estimates must be adjustedupward to bring model predictions and field data intoalignment. All other things being equal, the dailymortality rate required to reduce model estimates to300–350 PL-days 1000 m)2 yr)1 was in the range 0.11–0.12 for Stages II–IV (Fig. 11). The mortality rate forSI may be higher than the 0.03 we used, which would

reduce the estimate for subsequent stages. At the timewe developed the initial larval IBM, we had field datasuggesting that the mortality rate was as high as 0.5 forthe first stage, but the data were limited and we choseto remain with a more conservative number. This rateneeds to be more firmly established before any furtheradjustments of the SII–SIV rates can be justified.A higher SI mortality rate would reduce our estimatesfor remaining stages, which might also not be equalamong stages or over time. Other factors also have tobe considered. If larvae develop a little faster (seeearlier discussion), it would imply higher mortalityrates; likewise if egg production was underestimated.Thus, the range of 0.11–0.12 is a rough approximationand an overall average, useful for broad comparativepurposes only. A more important focus would be thefactors that might cause such rates to vary significantlyover space and time.

Transport patterns and connectivity

The different circulation patterns of the 3 yrs resultedin generally small differences in patterns of source :sink relationships, except for the influence of zones Cand D on downstream zones. These two zones cur-rently have high egg production and are located in thetransition area between eastern and western coastalcurrents. It is therefore not surprising that the degreeof continuity of flow between the two segments of thecoastal current system would have an impact on thedistribution of resultant postlarvae. In general,the amount of self-recruitment throughout the studyarea was higher than we expected, and the amount ofvariation in lobster connectivity from year to year wasless than might have been imagined from the strikingdifferences in circulation among the 3 yrs. Both find-ings might be explained by the fact that most hatch-ing, according to our analysis of the trap data, occurredinside the 50-m isobath, where patterns of flow aregenerally more complicated than in more offshoreportions of the coastal current system. The inshoremigration of lobsters in the spring is thus consequen-tial in terms of increasing the chances for larvalretention close to areas of reproduction, as well asproducing larvae that remain relatively closer to shore,where settlement might be favored (Incze et al., 2006).The blocked flow characteristic of summer 2002 pro-duced a more variable temporal pattern of postlarvalabundance in zone E than the other 2 yrs, possibly theresult of greater variability in supply routes (Fig. 9).The suite of patterns, including the range of variationsfrom week to week and the differences between years,are reminiscent of field observations (Incze et al.,2000a).

Figure 11. Effects of daily mortality rate (z) for Stages II-IVon modeled seasonal abundance of postlarvae inside the50 m isobath in zone E. The baseline of 1 · 106 postlarvae atz = 0.06 was chosen for simplicity from Fig. 7. Light graybox highlights the range of observed annual PL-d in zone Eafter depth corrections (see text).

16 L. Incze et al.


Self-recruitment is the balance between retentionof locally hatched larvae through to competent post-larvae, and inputs from other zones. Self-recruitment isaffected by many factors: (1) development, mortalityand dispersion rates; (2) relative egg productionamong the various zones; (3) the size of a zone (it iseasier to have high self-recruitment in a large zone,other factors being equal); and (4) transport pathwaysaffecting losses and gains. The small size of Zone E andits location downstream of high egg production zonesC and D made outside sources of egg production par-ticularly important: ‡90% of competent postlarvae inZone E originated as SI larvae in other zones. Zone A,though one of the largest, also had low self-recruit-ment because of relatively low egg production, lowtemperature (slow larval development), and a partic-ularly strong coastal flow (Pettigrew et al., 1998,2005). Large zones such as UBF, B, C and D had highdegrees of self recruitment, but still received outsidesubsidies of 17–50% (Table 2). The values in theconnectivity matrix for the zones at the two ends ofthe model domain (BB, SWNS, OCC) are not truemeasures of connectivity because potential larvalinputs to these zones were not complete, but they canbe used to see which zones might interact throughtransport processes.

Variations in sources of larvae (egg hatching areas)contributing to the pool of competent postlarvae inZone E were consistent with our initial characteriza-tion of the years (larval transport seasons) as ‘blocked’,‘flow-through’ and ‘intermediate’ in terms of the gen-eral circulation (Fig. 9). In the ‘blocked’ year thereapparently was considerable net drift in the ‘upstream’direction, something that was nearly absent in the‘flow-through’ year. In all years, postlarvae arriving inZone E came from a large portion of the Gulf ofMaine. However, quantitatively, distant sources con-tributed only a small proportion of the competentpostlarvae to this zone in all 3 yrs. The largest con-tributors to zone E were the two large egg-producingareas one and two zones upstream, with changes inrelative contribution consistent with the flow regimes(Table 2). Relatively more of the postlarvae origi-nated from hatching locations closer to shore in theblocked season (Fig. 6), which is consistent with anenergized offshore branch point of the current at suchtimes (Pettigrew et al., 1998, 2005). An unintuitiveresult was that more postlarvae in Zone E came fromthe Bay of Fundy in the blocked conditions, althoughthese contributions were still small. This agrees withthe apparent importance of the nearshore flow (‘insidetrack’) described for the transport of harmful algalblooms (Keafer et al., 2005).

The blocked flow resulted in markedly higherPL-days per year in three zones: D (due to high self-recruitment), E (from zone D) and MB (self-recruit-ment; Fig. 7 and Table 2). The intermediate flowproduced the highest PL-days in BB and SWNScompared with other conditions. Contributions tothese two zones were not completely accounted forbecause they were at the upstream end of the studyarea, but it remains interesting that the differenceswere produced by circulation alone, since larval pro-duction and mortality were the same in all modeledscenarios. Zone FC received postlarvae mostly fromzones C and D due to transport in the offshore branchof the Eastern Maine Coastal Current, demonstratinga potential recruitment pathway to offshore banksfrom the coastal population. Postlarval abundance atFC was similar to some of the less abundant coastalzones.

Average temperatures experienced by the lar-vae decreased from 2002 to 2003 and 2004 andaccounted for an average 2 days’ longer larvaldevelopment in 2003 and another 2 days in 2004.The mortality associated with these differences indevelopment time does not account for the modeleddifferences in postlarval abundances in zones D, Eand MB. Interannual differences in PL-days in theother zones were generally small, which agreed withsmall between-year differences in observed settlementdensities over the same time period (Incze et al.,2006).

Of the larvae hatched in Maine (zones A–G), arelatively high proportion of those that survived tobecome competent postlarvae remained withinMaine and over the coastal shelf, defined as withinthe 100-m isobath. Nearly half (42–56%) of larvaehatched inside the 50-m isobath (inner shelf) thatsurvived to become competent postlarvae were stillin Maine and in this depth zone when they reachedcompetency (Table 3). Model results showed post-larvae broadly distributed across the shelf, a condi-tion confirmed by field observations for those zoneswhere the data exist (Incze et al., 2000a). In all, 22–37% of larvae hatched inside the 50-m isobath inMaine were transported to waters 51–100 m deep,and smaller but still significant portions (14–18%)were transported to waters >100 m deep (Table 3).The proportion of competent postlarvae that hadbeen transported outside of Maine was small (3–6%,Table 2), most drifting to MB. These had originatedas larvae in all Maine zones except in the blockedyear, when only F and G contributed to postlarvae inMB. Larvae were transported against the prevailingdirection of the coastal current system. While the



quantitative impact on the level of recruitment wassmall, the results agree with other studies suggestingthat gene flow and biological invasions can takeplace in an upstream direction (Shanks and Eckert,2005; Byers and Pringle, 2006). The scale and vari-ability of dispersal in our study was thus much greaterthan corresponding patterns of major recruitment.

From the outer shelf, 51–100 m deep, less than athird (26–30%) of survivors to competent postlarvaehad been transported to the inner shelf. About thesame proportion (26–33%) remained in the outershelf, and slightly more (29–38%) had been trans-ported to deeper water. Up to 13% of postlarvae weretransported to areas outside Maine. The greater lossesfrom the deeper portion of the shelf can be ascribed tothe fact that it has open boundaries on two sides, andthat the along-shelf transport is more rigorous therecompared to the inner shelf. According to these cal-culations, and considering only the inshore–offshoreexchange within zones A–G, about 12% of competentpostlarvae in the inner shelf originated offshore (from51 to 100 m deep). This is relevant to the question ofconserving offshore egg production as a managementoption (Fogarty, 1998). While modest at present, anoffshore source of larvae could prove more importantto the coastal fishery should the inshore component ofegg production be reduced through factors such asdisease, over-exploitation or a change in environ-mental conditions. To the extent that the trap dataled to an overestimate of inshore egg production, theoffshore contribution was correspondingly underesti-mated.

While we have focused on the life history oflobsters, our model results and calculations provideinsight into the general patterns of along-shelf andacross-shelf transport and connectivity in the Gulf ofMaine under two significantly different and oneintermediate transport regime. Consistent with earlierthinking, larvae can be transported over large dis-tances in the Gulf of Maine. However, quantita-tively, most competent postlarvae originated withintwo zones of the zone being considered, and self-recruitment was almost always important. This issimilar to findings by Cowen et al. (2006), but at asmaller scale. The inshore concentration of hatching,coupled with faster development, contributed to theslower transport along the coast compared to priorestimates and assumptions, which were influenced byobservations in the core of the coastal current.Anything that would change the distribution ofovigerous females at the time of hatching would haveconsequences for patterns of settlement and connec-tivity.

ACKNOWLEDGEMENTS

We thank F. Page, D. Greenberg, D. Townsend,D. Brooks, E. Annis, R. Strong and R. Losier forhelpful discussions about modeling approaches andresults; E. Annis for data; M. Strong, D. Robichaudand D. Pezzack for data mining; and S. Cousins formodel runs and data archiving. M. Fogarty, J. Idoineand S. Cobb provided helpful insights during numer-ous conversations about this work, and the MaineDepartment of Marine Resources and the CanadianDepartment of Fisheries and Oceans provided data forour analysis. This work was sponsored by NOAA’sCenter for Sponsored Coastal Ocean Research, Grant#NA03NOS4780003, and received additional supportfrom the Alfred P. Sloan Foundation (Gulf of MaineArea Program, Census of Marine Life) and the U.S.National Science Foundation (Grant 0709536). Allare gratefully acknowledged.

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