Biol Invasions (2010) 12:1305–1318 DOI 10.1007/s10530-009-9548-7
ORIGINAL PAPER
Reconstructing the range expansion and subsequent invasion of introduced European green crab along the west coast of the United States Kevin E. See Æ Blake E. Feist
Received: 5 August 2008 / Accepted: 23 July 2009 / Published online: 8 August 2009 ! Springer Science+Business Media B.V. 2009
Abstract The European green crab, Carcinus maenas, was first documented in San Francisco Bay in 1989, and has since spread north along the west coast of North America. The spread of this invasion has not been a smooth expansion, which has raised questions about the underlying causes of variation in recruitment. We modeled larval development and transport along the West Coast by employing an individual-based model that incorporated oceanographic model output of water temperature and ocean currents at fine spatial and temporal scales. The distance that larvae were advected depended primarily on the timing of larval release. However, the effect of seasonal ocean currents varied across latitude and years. Our results imply that the furthest northern transport from California occurs when larvae are released from Humboldt Bay during the fall of an El Nin˜o year, making this a particularly risky time for invasion to Oregon and Washington estuaries. To precisely predict future spread and
K. E. See (&) University of Washington, Box 352182, Seattle, WA 98195, USA e-mail:
[email protected] B. E. Feist Watershed Program, Environmental Conservation Division, Northwest Fisheries Science Center, National Marine Fisheries Service, NOAA, Seattle, WA 98112, USA
potential impacts of green crab, we recommend further empirical research to determine the precise timing of larval release and seasonal abundance of green crab larvae from North American west coast populations. Keywords Carcinus maenas ! Larval dispersal ! European green crab ! Invasive species ! ROMS ! Individual-based model Introduction The pelagic larval stage of many marine species often provides the best opportunity for populations to disperse and potentially extend their range (Eckman 1996). For some marine invasive species, larval dispersal is the sole means of natural range expansion (Kinlan et al. 2005). Scientists and managers need to identify source and sink populations and understand the limits of dispersal to effectively prevent or contain the spread of invasives. Models of dispersal can help address these questions (Hastings et al. 2005; Shanks et al. 2003). However, modeling the spread of some marine invasive species can be difficult, primarily due to the variability of ocean transport during the pelagic larval stage (Grosholz 1996; Kinlan and Gaines 2003). We attempted to incorporate that spatial and temporal variability of ocean conditions by constructing an individual-based model (IBM) to simulate the spread of one recently
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introduced species along the west coast of North America. The European green crab, Carcinus maenas, is listed as one of the world’s worst invasive alien species by Invasive Species Specialist Group (Lowe et al. 2000), and it has proved to be a very successful invader worldwide. From its native range in Europe and North Africa, it has spread to the east coast of North America (Glude 1955), southern Australia (Carlton and Cohen 2003), South Africa (Le Roux et al. 1990), Japan (Carlton and Cohen 2003), South America (Hidalgo et al. 2005), and to the Pacific coast of North America, from Morro Bay, California, to as far north as Vancouver Island, British Columbia (Carlton and Cohen 2003). Although green crabs utilize a variety of habitats in their native range and on the east coast of North America, their predominant habitat on the west coast of North America is currently limited to the high intertidal zone in protected estuaries, perhaps due to biotic resistance from native crabs (Cohen et al. 1995; Grosholz and Ruiz 1996; Jamieson et al. 1998; Hunt and Yamada 2003; McDonald et al. 2006; Jensen et al. 2007). The past and potential impacts of green crabs have been well documented in the literature. Their arrival in the Gulf of Maine coincided with a drastic decrease in the annual catch of soft-shell clams from 1948 to 1953 (Glude 1955). Green crabs have also been reported to negatively impact scallop, quahog and other bivalve species on the East Coast (Walne and Dean 1972; Lake et al. 1987; Grosholz and Ruiz 2002), and they may outcompete the native rock crab Cancer irroratus (Miron et al. 2005). On the West Coast, green crabs could have severe impacts on native bivalves and native crabs. Grosholz et al. (2000) found a local 90–95% decline in the abundance of the native clams Nutricola tantilla and Nutricola confusa, as well as the native shore crab Hemigrapsus oregonensis, at sites in Bodega Bay within 3 years of the first arrival of green crabs in the bay (Grosholz et al. 2000). Lab experiments have also revealed that green crabs prefer the Olympia oyster, Ostreola conchaphila, over several other bivalve species (Palacios and Ferraro 2003), which could impact the efforts to restore Olympia oyster populations in the Pacific Northwest. There is also the potential for negative impacts upon populations of Dungeness crab, Cancer magister, on the West Coast through competition and predation upon Dungeness
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juveniles (Cohen et al. 1995; Grosholz and Ruiz 1995; McDonald et al. 2001). In addition to their effects on oysters, other bivalves and native crabs, green crabs may also negatively impact shorebird populations and sediment characteristics (Grosholz and Ruiz 2002). However, the realized effects of green crabs on the West Coast may be less than originally feared because of biotic resistance from large native crabs, which interact via predation and competition (Hunt and Yamada 2003; McDonald et al. 2006; Jensen et al. 2007). This potentially explains why green crabs are only found in areas on the West Coast that lack large adult native crabs such as the high intertidal zone of protected estuaries. The first confirmed sighting of C. maenas on the West Coast was in San Francisco Bay in 1989. The size and circulation patterns of that bay probably led most larvae that hatched there to become entrained in the bay and to settle within that estuary, promoting the growth of the population in San Francisco Bay (Cohen et al. 1995). By 1993, C. maenas was found in Bodega Bay, 120 kilometers (km) north of San Francisco (Cohen et al. 1995; Grosholz and Ruiz 1995). In 1995, several individuals were captured in Humboldt Bay (Miller 1996), 330 km north of San Francisco. The size of those crabs suggested they had arrived in Humboldt Bay in 1994. In 1997, green crabs were discovered in Coos Bay, Oregon (Yamada et al. 1999), 665 km north of the original population. The strong El Nin˜o event in the winter of 1997–1998 was correlated with that year class of green crab being distributed to estuaries in Oregon, Washington and as far north as the west coast of Vancouver Island, British Columbia (Jamieson et al. 2002; Carlton and Cohen 2003). In only a decade, green crabs have spread over 1,200 km north from San Francisco Bay (Fig. 1). Although it is important to consider the possibility of multiple invasions (Roman 2006), there is genetic evidence that the west coast of North America has been invaded only once, from the east coast of North America (Bagley and Geller 1999; Darling et al. 2008). The spatial and temporal pattern of sightings indicates that their dispersal north of San Francisco is most likely due to natural rather than anthropogenic causes, namely pelagic larvae drifting in ocean currents and settling in new locations (Carlton and Cohen 2003; Yamada et al. 2005). The pelagic larvae can take from 20 to 80 days to become competent to
Reconstructing the range expansion and subsequent invasion of European green crab
Fig. 1 Dates of first arrival of green crabs in West Coast estuaries, based on first confirmed sightings
settle, depending on temperature (Dawirs 1985; Mohamedeen and Hartnoll 1989; Nagaraj 1993; deRivera et al. 2007), during which time they may exit their source estuary and be advected by nearshore currents to a new estuary. However, closer examination of the crabs found in various estuaries indicates that new larvae are not entering estuaries at a constant annual rate. Rather, in the northern part of the green crab’s range, the size frequencies are dominated by specific year classes, indicating that some years were very good recruitment years whereas others were not (Yamada et al. 2005). Inter-annual shifts in oceanographic patterns, such as El Nin˜o events, have been suggested as one possible mechanism that drives the success of a particular year class in reaching northern estuaries (Jamieson et al. 2002). El Nin˜o years are characterized by stronger and more persistent northern currents along the West Coast (Huyer et al. 2002), which
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could advect green crab larvae further north than in non-El Nin˜o years. Because C. maenas habitat on the West Coast is limited to estuaries, and there are relatively few large protected estuaries on the West Coast, green crab range expansion and population dynamics will be depend to some degree on how the spatial and temporal variability of oceanographic currents affect the connectivity of estuaries on the West Coast. To explore the drivers of green crab settlement patterns, we focused on several factors that are related to the oceanographic variability. How much of the variation in green crab settlement patterns is due to how far offshore the larvae may travel, the specific bay where they are released, or the month or year in which they may be released? Under what conditions can green crab larvae be advected from known sources to potential new habitat? We approach these questions by employing an individual-based model (IBM) of larval movement and development that incorporates spatially and temporally specific information about ocean currents and temperatures from the Regional Ocean Model System (ROMS). Individual-based modeling is a tool that has been developed in ecology over the past several decades and can be used to explore the underlying mechanisms of how organisms interact with their environment to produce the observed patterns that emerge in the world (Grimm and Railsback 2005). Given the lack of data related to C. maenas larval distribution and abundance in the northeastern Pacific, the construction of an IBM is an appropriate method for testing potential factors influencing where green crab settlement may be occurring on the West Coast. It is also an opportunity to determine whether oceanographic models such as ROMS can help predict range expansion of invasive species with a pelagic larval stage.
Methods Individual-based model The simulated larvae were affected by two separate processes: the ocean temperature regulated their development, and the ocean velocity determined their position. The IBM required spatially and temporally explicit input of ocean currents and temperature.
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A series of one-dimensional environments at various offshore distances parallel to the West Coast were constructed from ROMS output. Simulated larvae were released from latitudes corresponding to San Francisco, Bodega Bay and Humboldt Bay in each of these environments, and the currents and temperatures were used to track their position and govern their development. When the simulated larvae were 100% developed, their final latitude was recorded as the settlement location. The model was written, run and analyzed using the R statistical software program. The ocean environment in this IBM was constructed using hindcast output from the Regional Ocean Model System (ROMS) (Shchepetkin and McWilliams 2003, 2005; Moore et al. 2004). ROMS is a well established ocean circulation model that receives broad use by the scientific community for a variety of physical oceanographic purposes (Haidvogel et al. 2000; Marchesiello et al. 2003; Warner et al. 2005; Blaas et al. 2007; Di Lorenzo et al. 2007; Vikebo et al. 2007; Centurioni et al. 2008). ROMS has also been used to study the population dynamics of juvenile anchovy, Engraulis capensis/encrasicolus (Mullon et al. 2003; Brochier et al. 2008; Parada et al. 2008); juvenile lobster, Nephrops norvegicus (Marta-Almeida et al. 2008), juvenile cod, Gadus morhua (Svendsen et al. 2007; Vikebo et al. 2007); and ichthyoplankton dynamics in general (Kone et al. 2005; Lett et al. 2008). For this study, ROMS output of ocean temperatures and northern velocity vectors from January 1997 until June 2003 was obtained (NOAA 2006), including the El Nin˜o event of 1997– 1998. This output was provided in time-steps of three days, on an approximately 10 9 10 km spatial grid, from 34.5 to 48"N latitude. This area covers the geographical range from north of Point Conception to approximately the northern tip of Washington State. We generated each offshore scenario by grouping the ROMS grid cells that were a specific distance offshore (e.g., 15 km) to create a series of onedimensional environments. Marchesiello et al. (2003) examined ROMS output off the West Coast for the period 1994–1999 and found that it matched many of the observed ocean conditions during that time. They did find that on a smaller spatial scale (*100 km), there were some discrepancies in sea surface height between observations and ROMS predictions, and that ROMS could miss some of the more extreme sea
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surface height anomalies, particularly near the coast and near the capes. There were more of these discrepancies south of Cape Mendocino; ROMS correlated better with observed conditions north of that point. As one of the few regional oceanographic models that describes the West Coast, we felt ROMS would provide reliable insight into larval advection patterns. A new cohort of simulated larvae was released from the latitude of a particular bay (e.g., San Francisco Bay) at each time-step, and tracked until settlement. We used a three-day time-step, which corresponded to the ROMS output. The northern velocity and temperature for each cohort of larvae at each time-step were determined by a weighted average of the two ROMS output points closest to the larvae’s present latitude. The northern velocity determined their movement for the next three days, and the temperature determined the percentage of development that occurred over that same time period. Once each cohort of larvae had completed megalopae development, the latitude at that point was recorded as that cohort’s settlement location. Cohorts were tracked by release dates, so development time and settlement locations could be attributed to specific release dates. In all, a total of 18,331 cohorts of larvae were simulated, representing releases every three days over seven years from three different bays at eight offshore distances. Both Dawirs (1985) and deRivera et al. (2007) have performed laboratory experiments to determine development durations of the various larval stages of C. maenas based on temperature. We used the results presented in deRivera et al. (2007) for two reasons. First, deRivera et al. (2007) used larvae that were obtained in California, as opposed to the North Sea in Europe. Second, the predictions of larval duration were greater using the equations in deRivera et al. (2007) for temperatures greater than 11"C, which corresponded to the majority of the ROMS output, providing a potential maximum estimate of advection. The greater the larval duration, the longer the larvae are exposed to the ocean currents and the further they could potentially be advected. The equations from deRivera et al. (2007) were used to compute a percentage of development for each timestep, based on the temperature experienced by the larvae in a given ROMS grid cell. One equation was used while the larvae were in any of the zoeal stages,
Reconstructing the range expansion and subsequent invasion of European green crab
DurationðdaysÞ ¼ 122:96 % 34:47 & lnðTÞ; and one equation was used for the megalopal stage, Duration ðdaysÞ ¼ 77:76 % 21:72 & lnðTÞ: Once the larvae had completed development, they were forced by the model to settle at their present latitude. There is evidence that megalopae search for suitable habitat and can settle during a window of several days, but because we did not incorporate probabilities of settlement based on habitat into this IBM, we fixed the moment of settlement at 100% megalopal development. Because the simulated larvae were traveling only north or south, their advection was governed by the northern velocity vector provided by ROMS. Given the shape of the west coast of the United States, this is a reasonable assumption, and provides a good first approximation of the alongshore distance larvae may travel. Because ocean conditions could change as one moves offshore, simulations were carried out at eight distinct distances offshore (10, 15, 20, 25, 30, 35, 40 and 45 km). Although no larval trawl surveys have been conducted off the west coast of North America, surveys off the coast of Portugal indicate that C. maenas larvae were primarily found 15–20 km offshore, with larvae found up to a maximum of 45 km offshore (Queiroga 1996). The availability of ocean model output constrained the traveling depth of simulated larvae to 10 meters (m). The same trawl surveys off Portugal found most C. maenas larvae in the top of the water column (0–30 m) with older larvae found progressively deeper, down to 60 m (Queiroga 1996). The larval behavior of green crabs, especially on the west coast of North America, is not well known. Studies from the North Sea and off the west coast of Portugal suggest that C. maenas larvae may migrate vertically to take advantage of tides to advect them out to sea during the first zoeal stage and back into estuaries during the megalopae stage (Queiroga 1996, 1998; Queiroga et al. 2006). (However, Queiroga et al. (2002) suggests vertical migration may be related to light levels, not tides.) However, no such studies have been carried out in the eastern Pacific. This type of behavior could enhance the probability of reaching strong offshore currents and being advected great distances, or it could enhance the probability of settlement within an estuary. Incorporating this sort of larval behavior into our model was beyond the scope of this study for two
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reasons. First, the lack of larval behavior studies in the northeastern Pacific makes behavior assumptions problematic. Second, if vertical migration takes place, it occurs on a daily, or twice daily cycle, but the ROMS output was available in three day timesteps, making the temporal scales incompatible. Therefore, it was assumed that the simulated larvae maintained a constant depth of 10 m. Besides a constant depth, it was also assumed that the simulated larvae maintained the same distance offshore during their entire development. It was also assumed the larvae could reach that offshore distance immediately after being hatched, and that they could move onshore across that distance once they were competent to settle. This study was primarily concerned with alongshore dispersal. Because ROMS does not provide reliable estimates of on- and offshore currents extremely close to the coast, where larvae would actually be released, this period of pelagic drift was bypassed by releasing our simulated larvae offshore. Ignoring the time to be advected from and return to an estuary means that this IBM allows the simulated larvae to drift for a longer time period than they might in reality, leading to a potential upward bias in advection distance. Some of this bias may be offset by the fact that the simulated larvae were forced to settle as soon as they had completed the megalopae stage when in reality they may drift for several days at that point, searching for suitable habitat to settle. Although these assumptions are not a perfect approximation of the actual larval transport process, they do lead to a simple model that can be used to analyze the potential extent of C. maenas pelagic dispersal on the West Coast. Statistical analysis The central question of this study was to understand how larval transport varies with source location, offshore distance, month and year of release. A standard sensitivity analysis would adjust the various inputs and determine how the results were affected. This was not appropriate because most of these inputs were categorical factors, so they could not be adjusted. The only exception to this was offshore distance. For this particular factor, we ran simulations across a range of eight different offshore distances. Therefore, instead of a sensitivity analysis, we examined the contribution of each factor to the
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total variation in distance advected. This approach is similar to an analysis of covariance (ANCOVA) in which different input combinations are treated as samples, and the residual variance is attributed to the daily variation of ocean conditions within each month. The results of the IBM were combined into one database where the dependent variable was the distance the simulated larvae were advected north. The variation of this variable was explored using an analysis of covariance (ANCOVA) to determine how much of the variation was due to offshore distance, starting location, month or year released. The method follows that of Edwards et al. (2007). There were eight possible offshore distances and three possible starting latitudes corresponding to San Francisco Bay, Bodega Bay and Humboldt Bay, all in California. Carcinus maenas had been found in all of those bays prior to 1997. When we released larvae from bays further north, the simulated larvae reached the northern limits of the available ROMS output. Therefore, release locations north of Humboldt Bay were excluded from this analysis. All twelve months, and each of the seven years were also considered to be factors. A linear model was fit that assumed the distance advected north was dependent on the offshore distance, starting estuary, month released and year released, as well as all two-way interaction terms. Higher-level interaction terms were omitted because of the difficulty in interpreting them biologically. An ANCOVA was then performed to determine what percentage of the variation in distance advected was attributed to each of those factors, including the interaction terms. The percent contribution of variance was based on the sum of squares for each term compared to the overall total sum of squares. Although this IBM is deterministic (which made it possible to explain all of the variance in this linear model by including a term for day released in the model), the smallest timeframe we were concerned with is one month. Therefore, the daily variation in ocean conditions over the course of a month was considered the residual variance in this analysis. El Nin˜o conditions increase the strength of northern currents, but also raise the water temperature. During these times, larvae drift north faster, but develop faster as well, potentially offsetting northern expansion due to increased current speeds. To
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examine this trade-off, we computed the standardized average velocity and standardized average temperature that larvae experienced, and then performed linear regression that assumed the distance advected depended on these two factors as well as their interaction. The coefficients for each of these standardized covariates could then be compared to assess their relative strength.
Results The ANCOVA showed all terms were significant to the a = 0.05 level. For the 7-year time-period that the IBM was run, over 6,000 cohorts of larvae were released from each of the three starting locations. The top contributors to overall variance were ‘‘Month’’ (29.6%), ‘‘Month 9 Release Location’’ (13.5%) and ‘‘Month 9 Year’’ (12.8%). No other term contributed more than 5% to the overall variance (Table 1). The residual variance was due to the daily variance in oceanographic conditions. The high contribution of the residuals to the overall variance (31.4%) suggests that there are a wide range of ocean conditions that pelagic larvae experience. Larvae released in January through May tended to move south, whereas those released in June through December generally traveled north (Fig. 2), leading to the large contribution of ‘‘Month’’ to the variation
Table 1 Results of the ANCOVA analysis of model that included all main effects (month, year, bay and offshore distance of release) and two-way interactions Variable
DF
Contribution to variance (%)
Month
11
29.6
Month 9 release location Month 9 year
22 58
13.5 12.8
Year
6
4.6
Release location 9 year
12
3.4
Offshore distance 9 month
11
3.0
Other Residuals
1.7 18,199
31.4
The factors that contributed at least 3% to overall variance are listed, as well as their degrees of freedom (DF). The contribution of all other factors were summed and listed as ‘‘other’’
Reconstructing the range expansion and subsequent invasion of European green crab
0
0
5
200
10
15
Humboldt Bay
−5 −10
ROMS Output J F M A M J
J A S O N D J F M A M J
J A S O N D J F M A M J
Mean Monthly Velocity (km / day)
Bodega Bay
400
San Francisco Bay
−200
Distance Advected (km)
600
Variation in Month and Location of Release
−400
Fig. 2 Advection distance by month of release and starting location. Box plots of advection distance show 5th, 25th, 50th, 75th and 95th quantiles. Lines show the average monthly ROMS output for 30 km offshore at each release bay latitude
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J A S O N D
Month
in advection distance. Month of release contributed a total of 58.9% to the overall variation through main or interaction effects. The range of this monthly pattern differed depending on where larvae were released, which is reflected in the significant contribution of the ‘‘Month 9 Release Location’’ term. There was a latitudinal gradient in the magnitude of advection distances such that larvae were advected further, both north and south depending on month of release, when starting from Humboldt Bay compared to Bodega Bay and to San Francisco Bay (Figs. 2, 3). Yearly conditions amplified the monthly oceanographic patterns, leading to the significant contribution of the ‘‘Month 9 Year’’ factor. On average, larvae released in the spring (March through May) traveled twice as far south during El Nin˜o conditions compared to other years (105 km compared to 51 km) while those released in the fall (September through December) drifted 3.5 times further north during El Nin˜o conditions compared with other years (139 km compared to 37 km). These yearly effects were also more pronounced along the latitudinal gradient. This is not apparent from the ANCOVA analysis because we did not investigate three-way interaction terms. However, the visual patterns are clear from settlement maps (Fig. 4). The only scenario in which simulated larvae reached estuaries in Washington State was when they were released from Humboldt Bay during an El Nin˜o fall or winter (Fig. 4). The offshore distance at which larvae drifted made little impact on their trajectories. In the ANCOVA
analysis, the interaction term of ‘‘Offshore Distance 9 Month’’ contributed only 3% to the overall variance, and each additional term that included offshore distance did not contribute as much as 1%. For each bay, the settlement patterns were similar regardless of how far offshore larvae were drifting (Fig. 3). The time it took for larvae to reach the completed megalopae stage varied from 42 to 75 days, with the longer durations occurring in the winter months when the water was cooler (Fig. 5). To compare the relative strengths of the opposing forces of warmer temperatures and increased northern velocities, standardized values of the average velocities and temperatures experienced by the simulated larvae were calculated and used to predict advection distance. Changes in northern velocity had a substantially larger relative effect than changes in temperatures (Table 2).
Discussion We developed an individual-based model to hindcast the invasion of European green crabs on the West Coast and explore how it may be influenced by spatially- and temporally-variable conditions experienced by larvae. Similar larval transport models have been employed by Polovina et al. (1999), Kobayashi and Polovina (2006) and Kobayashi (2006) for other species. However, these models did not account for temperature-dependent development; they assumed a specific larval duration for all simulated larvae. In
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Fig. 3 Magnitude and latitude of simulated green crab larvae settlement for three release locations, and all eight offshore distances. SF San Francisco, BB Bodega Bay, HB Humboldt Bay
another approach, Rooper et al. (2006) averaged temperature over a 60-day period to compute larval duration for English sole, Pleuronectes vetulus, and extrapolated alongshore currents based on three current meters off the Oregon and Washington coast. Our IBM utilized temperature and velocity information at a much finer resolution, thereby providing more precise results. However, this model was not as complex as some of the biophysical coupled models that have been employed by Allain et al. (2007), Pedersen et al. (2006), and Hermann et al. (2001), as we made several simplifying assumptions. Some of
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Fig. 4 Magnitude and latitude of simulated larval settlement for 2 years, an El Nin˜o year (1997–1998) and a non-El Nin˜o year (2001–2002). It is further broken up into bay of release and season when larvae were released. The seasons are defined as Winter = December, January, February; Spring = March, April, May; Summer = June, July, August; Fall = September, October, November
these (e.g., one-dimensional movement) were aimed at merely simplifying the model. Others (e.g., continuous larval release, constant larval densities across space, etc.) were due to a current lack of knowledge about the ecology of C. maenas on the West Coast. The general pattern of larval recruitment along the West Coast reflects northern transport when larvae were released from June through December and southern transport when release occured from January through May. This pattern was amplified when larvae were released from northern sites in California compared to more central California sites (Fig. 2).
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Larval Duration
60 45
50
55
Days
65
70
75
Fig. 5 Larval durations for larvae released in each month. Box plots show 5th, 25th, 50th, 75th and 95th quantiles
jan
feb
mar
apr
may
jun
jul
aug
sep
oct
nov
dec
Month
Table 2 Coefficients for standardized predictor variables Predictor variable
Coefficient
Std. Error
P-value
V
132.4
0.01
\0.0001
T
-1.7
0.01
\0.0001
-14.0
0.01
\0.0001
V9T
V is the standardized average ocean velocity that larvae experienced, T is the standardized average ocean temperature that larvae experienced, and V 9 T is the velocity–temperature interaction
Interannual events, such as El Nin˜o conditions, also amplified that general pattern. In particular, larvae released during the fall months (September through December) were advected much further north during El Nin˜o conditions than non-El Nin˜o conditions. Northward traveling larvae are more likely to be deposited onshore due to Eckman transport compared with larvae drifting south during the late winter and spring months, which will be swept offshore. This is consistent with El Nin˜o conditions fueling the northward expansion of the green crab’s range. The seasonal variability of larval settlement patterns is most likely due to the annual shifts in the California Current System (CCS) flow. Near the surface the mean current flows south from early
spring to summer, and it flows north the rest of the year (Hickey and Banas 2003). Each spring, there is an abrupt shift from the northern flowing, warmer current to the southern flowing, cooler current. This shift is known as the spring transition (Strub et al. 1987a, b; Hickey and Banas 2003). Although larvae released during the winter usually begin traveling north, they may be caught in the spring transition and be forcefully advected south. The long larval duration during the winter means that even larvae released in January may experience this type of drift pattern. Because of the lag due to larval development, our results are consistent with the general CCS pattern of southern currents in the spring and early summer, with northern currents in late summer through the winter (Marchesiello et al. 2003; Hickey and Banas 2003). Yamada and Gillespie (2008) found that C. maenas females, when held in a laboratory, released eggs in November and early December. She also estimated that the majority of the 1998 year class settled in Oregon estuaries during the first four months of 1998 (Yamada et al. 2005), which corresponds to a release in late fall and early winter. Therefore, for the Pacific Northwest, the most relevant panels from Fig. 3 are when larvae are released in fall and winter. El Nin˜o
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conditions during these seasons make extensive northern transport especially likely, particularly from Bodega Bay and Humboldt Bay. El Nin˜o conditions on the West Coast are characterized by stronger currents, particularly the northern flowing Davidson current, and warmer temperatures (Huyer et al. 2002). We had expected the warmer temperatures to shorten larval duration and therefore offset some of the effect of stronger northern currents. However, the effect of current velocity was two orders of magnitude larger than the effect of temperature, easily overwhelming this potential mitigating factor (Table 2). Although the month, year and location of larval release influenced the settlement patterns of C. maenas, the offshore distance did not (Fig. 3). Further examination of the ROMS output revealed that although the estimated currents were not completely uniform between 10 and 45 km offshore, they did exhibit similar seasonal trends across that distance but there was no regular gradient in the magnitude of the current as one moves offshore within that narrow window. The model provides insight into two puzzling aspects of the green crab invasion on the West Coast. First, why was the invasion apparently contained to San Francisco Bay as the population built up? According to this IBM, even if larvae managed to exit San Francisco Bay, they had little chance of net longshore transport (Figs. 2, 3). Therefore there is a high probability they would recruit back into San Francisco Bay. This self-recruitment could also help explain the rapid growth of the population within that bay as noted by Cohen et al. (1995). Several drift card studies are consistent with our results. Blaskovich (1973) found the vast majority of drift cards released from Monterey Bay were recovered within the bay. During the El Nin˜o of 1972– 1973, three cards drifted as far north as Oregon and Washington, but two of these took over 120 days, far longer than C. maenas larvae would be in the water. The results from Howard et al. (2006) also show the vast majority of drift cards ([90%) released from San Francisco Bay in 2004 and 2005 drifted less than 50 km from their origin. The few cards that did reach Oregon from San Francisco did so when released in the fall, but they took 90 days to get there, which is approaching the upper limit of C. maenas larval development time. In another modeling study, Banas
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et al. (2009) suggest that for smaller estuaries with similar shape (e.g., Willapa Bay), there are significant opportunities for larval retention within that estuary. Second, was El Nin˜o the driving force behind the rapid northern expansion in the late 1990s? There is widespread consensus that the 1997–1998 El Nin˜o event brought C. maenas larvae to the Oregon and Washington coasts, as well as to Vancouver Island (Yamada et al. 2005). The assumption has been that they came from the large source population in San Francisco Bay. However, our results imply that larvae from San Francisco did not reach the border between California and Oregon, let alone Vancouver Island, even during El Nin˜o years, but that Humboldt Bay may have been the source for the rapid northern migration. The first confirmed green crabs settled in Humboldt Bay in 1994 (Miller 1996). Crabs of that year class would have been four years old in the summer and fall of 1997, near their reproductive peak and possibly capable of supplying many of the larvae that later settled in Oregon, Washington and Vancouver Island estuaries. These results also show that some of the larvae released from Humboldt Bay each year may settle back in the bay, so the green crab population in that bay probably expanded between 1994 and 1997. Although the population may not have expanded to large abundances until after the 1997–1998 El Nin˜o (Boyd et al. 2002), the female crabs living in Humboldt Bay were capable of releasing 185,000 larvae each (Broekhuysen 1936). If the timing of release coincided with favorable ocean conditions, even a small population in Humboldt Bay may have fueled the large recruitment class of 1998 in Oregon and Washington. Although simulations were not carried out beginning from Coos Bay, OR, one- or two-year-old green crabs had been found there in 1997 (Yamada et al. 1999). This population could have contributed larvae to the 1998 recruitment class as well. Our unpublished IBM results suggest that larvae from Oregon could have been advected as far as Vancouver Island. Because the ROMS output may not capture the most extreme currents, our IBM cannot rule out San Francisco as a source. Despite that, it is clear that as C. maenas populations expand north of San Francisco, more and more larvae will be advected into Washington and Oregon estuaries, and from there to Vancouver Island.
Reconstructing the range expansion and subsequent invasion of European green crab
This type of modeling effort can provide crucial suggestions about forecasting green crab larval dispersal and facilitate early detection and eradication. If models like this had been constructed years ago, managers could have identified Humboldt Bay as a potential larval source and focused their monitoring and control efforts there. As the green crab range frontier shifts to British Columbia, future analogous modeling exercises can help managers in northern British Columbia and southeast Alaska streamline their monitoring efforts in a topologically complex area. Given the current limited knowledge about C. maenas on the West Coast, these model results provide directions for future research. Because the month of release is crucial for determining where larvae will drift, further investigation is needed into when green crab larvae on the West Coast are present in the water. Carcinus maenas hatch eggs on different schedules depending on water temperature. In the southern portion of their range in Europe and eastern North America, the first zoeal stage larvae are generally found in the water year-round, with a peak between February and April (Queiroga 1996). Towards the northern edge of their range in Maine, females are restricted to hatching eggs between June and October, the warmer months (Berrill 1982). Recently, some studies have been conducted on the West Coast. Yamada et al. (2005) characterizes the life history of green crabs in Oregon estuaries, while Banas et al. (2009) found ovigerous female green craps in Willapa Bay, Washington between January and August. Further studies on the West Coast could build on this research and Yamada and Gillespie (2008) to determine when green crab larvae are released along the latitudinal gradient from San Francisco to Vancouver Island. Collecting data to test these model results should involve increased trapping, with a particular focus on determining when females extrude and release their eggs. The timing of larval release could also be inferred by conducting trawl surveys, on a monthly or seasonal time scale, in areas offshore of known green crab populations. These IBM results also demonstrate that release location plays a large role in determining how far larvae are advected. Therefore, to predict the continued spread of green crabs along the West Coast, accurate population densities should be calculated for
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bays with known green crab populations. Again, this might come from trapping data, mark-recapture studies or larval trawls at the mouth of an estuary. Until these kinds of data are gathered, models such as this one can provide speculation on how the invasion of C. maenas may advance in the future. The growing green crab populations on Vancouver Island coupled with another El Nin˜o event could drive the invasion into northern British Columbia and potentially southeast Alaska, where lab results and modeling exercises suggest they could survive (deRivera et al. 2006, 2007). As green crab populations spread north and release more larvae in the late summer and early fall, when the currents are flowing north quickly, their range expansion northward could accelerate. Acknowledgements The authors would like to thank Jennifer Ruesink, P. Sean McDonald and Neil Banas for their valuable ideas, reviews and input. We also thank Al Hermann for assistance with ROMS, and Phil Levin as well as the anonymous reviewers for their helpful comments on a previous draft of this manuscript. This research was funded by the Aquatic Invasive Species Program and the Northwest Fisheries Science Center, both with the National Oceanic and Atmospheric Administration. The ideas expressed in this manuscript are those of the authors and do not necessarily represent positions of their employers or funding agencies.
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