The Seascapes

The Seascapes

Saturday, November 13, 2010

“Now where are all those kids I left by the side of the road?” I. Summer flounder life history & some observations of broad scale patterns.

Figure 1. Summer flounder range from Cape Canaveral,
 Florida to George's Bank off the Coast of Massachusetts. 
Subpopulations North and South of Cape Hattaras, North 
Carolina have different ecologies which are summarized 
in detail by Packer et al., 1999. Mapped data is available 
from Fishbase.
One of the things we have been trying to do is to link our discoveries in the adaptive plankton and bottom surveys of the seascapes with our understanding of the dynamics of fish and invertebrates important in the Mid-Atlantic Bight Ecosystem. The birth and death rates that underlie population dynamics occur to individuals with specific traits in habitats defined by sets of environmental factors affecting those rates (e.g. growth is dependent on temperatures; predation mortality is affected by the availability of hidey holes as well as other things such as body size). I am sure this is blindingly obvious to anyone who is not a marine biologist. But often we seem to ignore this because making the connection between local habitat effects on individuals and the emergent dynamics of populations at regional scales in a quantitative way is so hard. Somehow “information” is translated across scales and levels of biological organization in both directions, from local to regional scales (e.g. effects of individual births and deaths related to habitat quality within subpopulations), and from regional to local scales (e.g. connectivity among subpopulations provided by dispersing larvae and migrating adults that can supplement, rescue, or even found new subpopulations). Sometimes science is thinking out loud, and I am going try to amble through some data on summer flounder (AKA “fluke”) to try to understand these connections better.

Figure 2. Summer flounder life cycle in the mid-Atlantic Bight.
Adults spawn as they migrate in the autumn from nearshore 
coastal feeding grounds to deep overwintering habitats on 
the edge of the continental shelf. Fertilized eggs hatch larvae 
that live in the water column in the coastal ocean for a month
 or more before moving into estuaries and transforming into 
small juveniles. The juveniles overwinter in the estuaries.
Why choose summer flounder or “fluke” as a model species? One reason is that fluke integrate a particularly broad spectrum of habitats throughout the mid-Atlantic Bight (Fig. 2). During their complex life history which includes eggs and larvae that live in the water column as well as adults and juveniles strongly associated with the seabed, they use habitats ranging from marsh creeks in estuaries, to pelagic & seabed habitats in the coastal ocean, to deep habitats on the seabed at the edge of the continental shelf. From late spring through the summer, adults and juveniles are important predators in shallow estuaries and the near-shore coastal ocean. In early autumn they begin to migrate from these nearshore feeding habitats to deep overwintering grounds near the edge of the continental shelf. Adults two or more years old spawn as they migrate across the inner continental shelf. Each ripe female carries between ½ million to over 4 million eggs depending on her body size. The females release these eggs directly into the sea where they are externally fertilized by males. The fertilized eggs hatch in less than about 4 days. The larvae which are shaped like a regular fish (fusiform or laterally compressed) develop in the water column for 1 to 3 months depending on the temperature, availability of food, and their "ability" to avoid predators. Late stage larvae then move into estuaries during the winter. As they do, they metamorphose into small juvenile flatfish. Metamorphosis involves the “migration” of their eyes to the left side of their heads, and the twisting of their spinal cord into loop as they flatten into a flatfish. They are 10-20 millimeters long when they “settle” out of the water column to become more strongly associated with the bottom habitats in estuaries.

With the exception of fishing, we believe most of the important processes affecting birth and death rates occur from spawning through the early juvenile phase. Unfortunately for field ecologists working in the northern part of summer flounders range, the interesting habitat specific processes influencing summer flounder population dynamics happen during the autumn, winter, and spring when it's cold. Who named this fish? Why would a fish spawn in the autumn and float around in the plankton to settle in estuaries in the winter when its so cold? Our guess is that larvae and juveniles are probably exposed to fewer predators in the ocean and estuaries during the fall and winter than they would during the spring and summer. By growing slowly over the winter they achieve a size advantage when spring rolls around that makes them less vulnerable to predators but capable of eating larvae and early juveniles of other animals colonizing estuaries later in the spring. This is the expression of an important rarely violated ecological theorem: “You can't eat anything bigger than your head”.  However, the tradeoff for overwintering in the coastal ocean and estuaries for this subtropical flatfish is that it exposes larvae and small juveniles to cold winter temperatures in the northern part of the species range. Small juveniles die when exposed to temperatures below about 2 or 3 degrees Celsius in the laboratory (Keefe & Able 1993, Szedlemeyer et al., Malloy & Target, 1991, 1994 ).

Figure 3. Estimated trends in summer flounder population
size and age class diversity in the mid-Atlantic Bight. 
The population size was low and dominated by a few 
young age classes in the late 1980s early 1990 when a 
Fisheries Management Plan (FMP) was implemented. 
This plan was amended (Amend 2) in the early 1990s. In the
1990s and 2000s the population increased in size and older
fish became more abundant increasing the age class diversity. 

Another reason “fluke” are an interesting fish is that the mid-Atlantic bight population has been getting healthier over the past two decades. The estimated size of the population decreased from a peak in the early 1980s to a low about 1990 (Fig.3). During this time it was dominated by young fish and had a low age diversity. In response to this decline a fisheries management plan was established in late 1980s and amended in 1990s to restrict the amount of summer flounder that could be caught and the gear used to catch them. In the early 1990s the population began to rebound and older larger individuals became more common. The increased survival of older age classes is particularly important because higher age class diversity makes populations more resilient to environmental shocks. In part this is just simple bet hedging. But there is also evidence that older females produce more, higher quality eggs over a longer spawning periods than younger fish.  They are thought to produce kids more likely to survive the dangers of early life. This is the BOFFF hypothesis (Big, Old, Fat, Fecund, Females) . The summer flounder population is doing well enough that the current precautionary fishing regulations have become pretty contentious.

Figure 4. Estimated centers of summer flounder biomass 
during the autumn shifted toward the north east nearly
250 kilometers between 1973 and 2006. Centers of biomass
were calculated by fitting sample coordinates to year in a
generalized additive model that weighted the observations
by the standardized biomass of summer flounder collected
in North East Fisheries Center Bottom trawl surveys.  
But was the rebound of the summer flounder population entirely due to fisheries management and the reduction in predation by human predators? As the population increased the distribution of the animals also changed. The center of distribution of summer flounder in the Autumn seems to have shifted from an area offshore of Cape May, New Jersey in the 1970s, to one off the eastern end of Long Island, New York by the mid-2000s (Fig. 4). The velocity of this shift  was approximately 11 km per year from 1991 to 2005 (also see Janet Nye's work). These patterns suggest that changes in climate along with fishing may have affected the summer flounder population. Nineteen ninety one has been identified as the year in which the ecological dynamics of a number of marine populations changed. The summer flounder species range shift could have occurred because warmer temperatures allowed summer flounder to remain inshore on northern feeding grounds later in the autumn. However such a change in the timing of fall migration wouldn't necessarily result in an increase in population size. Alternatively, more early juvenile summer flounder may have survived more winters in northern estuarine nurseries because winter temperatures have been warmer in recent years. If this is the case summer flounder may be extending their species range to the north by coupling their life cycle and affecting affect the entire suite of habitats/ecosystems they use during their life history (Fig. 2). There is some evidence that the survival of young juveniles has increased in northern estuaries. Indices of Age-0 summer flounder abundance are have been higher in Massachusetts, Rhode Island and Connecticut (Fig. 5) than they have been in the past.  Furthermore winters have been warmer with fewer subfreezing degree days since the early 1990s (Fig. 5).  This is interesting since the survival of winter flounder juveniles on mid-Atlantic Bight estuarine nursery grounds has been poor since the 1990s apparently as a result of the high frequency of warm springs (Manderson, 2008).  Unlike summer flounder which are subtropical, winter flounder are a cold temperate flatfish.   

Figure 5. Standardized trends in age-0 summer flounder abundance estimated in surveys conducted in states ranging from Massachusetts (MA) to North Carolina (NC).  Abundance in Massachusetts, Rhode Island (RI), and Connecticut (CT) has been relatively high during the last decade (data from 47th SAW). This may have resulted from higher overwintering survival. Winters have been mild with fewer subfreezing degree days in the mid-Atlantic regions since the late 1980s based on analysis of daily temperature records compiled by the Academy of Natural Sciences in Philadelphia. New Jersey (NJ), Delaware (DE), Maryland(MD), Virginia (VA).

The effects of fishing regulations, and climate on migratory patterns and/or the survival of early juveniles summer flounder are alternative hypothesis of mechanisms that have could have different impacts on the mid-Atlantic ecosystem and implications for ecosystem and fisheries management. They are not necessary mutually exclusive, but may effect the population dynamics of summer flounder and the other animals they interact with simultaneously.   How can we find a method to estimate the relative contribution of fishing and changing climate on the habitat specific processes affecting the summer flounder population in the Mid-Atlantic Bight?

Keefe, M & KW Able, (1993) Patterns of metamorphosis in summer flounder, Paralichthys dentatus. Journal of Fish Biology 42(5): 1095-8649

Keefe M. & KW. Able (1994) Contributions of Abiotic and Biotic Factors to Settlement in Summer Flounder, Paralichthys dentatus. Copeia 1994 (2) 458-465 

Malloy, K. D., and T. E. Targett (1991) Feeding, growth and survival of juvenile summer flounder Paralichthys dentatus: experimental analysis of the effects of temperature and salinity. Mar. Ecol. Prog. Ser. 72:213-223.

Malloy, KD, and TE Targett. (1994) Effects of ration limitation and low temperature on growth, biochemical condition, and survival of juvenile summer flounder from two Atlantic Coast nurseries.
Trans. Am. Fish. Soc. 123:182–193.

Manderson. JP  (2008) The spatial scale of phase synchrony in winter flounder (Pseudopleuronectes americanus) production increased among southern New England nurseries in the 1990's. Canadian Journal of Fisheries and Aquatic Sciences 65:340-351.

Nye JA, Link JS, Hare JA, Overholtz WJ (2009) Changing spatial distribution of fish stocks in relation to climate and population size on the Northeast United States continental shelf. Mar Ecol Prog Ser 393:111-129

Szedlmayer, S. T., K. W. Able, and R. A. Roun-tree. 1992. Growth and ,temperature-induced mortality of young-of-the-year summer flounder (Paralichthys dentatus) in southern New Jersey. Copeia 1:120-128.

Sunday, September 19, 2010

Scales of variation in the coastal ocean fish and invertebrate community: An analysis in progress

Figure 1. Spawning longfin inshore squid.  We caught many 
small juveniles in trawls and saw their egg mops in 
underwater video in the seascapes.  Age-0 Juveniles labeled 
as LOLPEA_0 in figures 3 & 4 below. 
The design of our bottom sampling which we described in detail earlier was pretty simplistic.  We used depth and sediment characteristics to divide up the New York and New Jersey seascapes into bottom habitat patch types. Using a patch model to classify habitat based on bottom features is usually flawed in the sea particularly in the temperate coastal ocean where dynamic water column features like temperature and currents affect everything from the physiology to the movements of cold blooded and often nearly neutrally buoyant animals. But you have to start sampling systematically based on the questions you want to ask and what little you know about the system in the beginning. The information we had to design our field study with was sonar measurements of depth and sediment type and an intensive study of oceanography (Chant et al.2008, Schofield et al., 2008,  Moline et al.2008).

Figure 2. Estimates of the percent variance (total 
inertia =5.18) in the fish & invertebrate community
 associated with beam trawl survey design factors 
made using partial redundancy analysis (pRDA). 
The design factors explained ~38% of the species 
variance while 62% remained unexplained. About 
15% occurred over time and much of this was 
seasonal changes in species dominating the 
community (see fig 4). Most of the spatial 
variability (23%) occurred at the finest scale among 
patches (within depth strata within seascapes). 
 Two percent of the species variance occurred 
simultaneously in space and time and these spatial 
dynamics also contributed to the variance ascribed 
to patches. All of the variance components that could
 be tested were significant in permutation tests at a 
P<0.01 level (see Borchard and Legendre 1994 
for basic method)

Our big questions in the ECOS research program are: What are the dominant physical and biological processes controlling the abundance and health of animals and their assembly into communities in the coastal ocean? What are the relative importances and scales of operation of those dominant processes? And finally, how can we use information about those processes to identify sweet spots in the ocean likely to sustain healthy marine communities which should therefor be conserved?

Figure 3. Ordination of species (blue) and temporal 
factors (year and season in red) along the first two 
axes from non-metric multidimensional scaling of 
the ecological distance between beam trawl samples
collected in the seascapes in 2008 & 2009. Changes 
in community structure over time were captured on 
NMDS axis 1 while spatial differences were captured 
on NMDS 2 (see fig. 5). Species abundances often 
increase in direction of the arrows (see fig. 4 below).
Species diversity (simpson's index) and evenness 
were higher at stations with high scores on both 
NMDS 1 &2. Many of these samples were collected 
at deep sites during the Fall, particularly in 2009. 
 Species codes: SCOAQU = windowpane flounder, 
PLEAME= winter flounder, PARDEN=summer 
flounder, ETRMIC =Smallmouth flounder, CITARC 
= Gulf stream flounder, PAROBL =Fourspot flounder,
LEUOCE= Winter skate, LEUERI=Little skate, 
MERBIL=Silver hake, PRICAR =Northern searobin, 
PRIEVO=striped searobin, AMMAME=american sand 
lance, STECHR= scup, PEPTRI =Butterfish, ANCMIT
=Bay anchovy, CENSTR= black seabass, LOLPEA = 
lonfin inshore squid, CANIRR=Rock crab age, 
CRASEP= sand shrimp, DICLEP=Bristled longbeak
shrimp, ASTSPP=Seastar asterias, ECHPAR=Sand 
dollar, PLAMAG=sea scallop. Codes followed by _0 
are age-0 individuals, _1 older animals.

In our inshore surveys we sampled at two time scales (year and season) and three spatial scales (seascapes [10s kms] , depth strata within seascapes [3-5 kms], patches of sediment within depth strata within seascapes [100s of m]). We assume that scales of community variation match the scales of operation of the important physical and biological processes causing the variation 1. So we can use the nested survey design to identify scales of community variation falling within the limits of the study resolution and get clues about the operational scales some of the driving processes. (Our study resolution doesn't include variation on time scales of hours to weeks or decades, or over spatial scales more than a few10s of kilometers. We can identify meter to sub-meter scale spatial changes in the distributions and habitats of some animals visible in imagery we collected with the underwater video sled. There are other longer and larger scale surveys we can turn to to define the context for our study). Once we identify the dominant scales of community variation we can use our scale matching assumption and measurements of water column and bottom features made with satellites and radar by MARCOOS and with water quality sensors, acoustics, and underwater video by us to winnow down the likely candidate processes.

More specifically we can use our nested beam trawl survey to ask:

-Are dissimilarities in the fish and invertebrate community bigger in time or in space?

-Is the species turnover bigger between years or between seasons?

-How dissimilar are the communities in the two seascapes?

-Are differences in the communities in the two seascapes bigger than those in depth strata within the seascapes or sediment patches within depth strata within seascapes.

-Does the community vary simultaneously in space and time and at what scales do those spatial dynamics occur?

Figure 4. Abundance trends of selected species along 
the first NMDS axis which primarily captured changes 
in the biological community sampled with beam trawls 
in the two seascapes over time (see Fig 2). Much of 
this temporal variation was seasonal. Age 1+ northern 
searobin, sand shrimp and butterfish were most 
abundant during the spring surveys and had low scores
on NMDS1, while early juvenile (age-0) northern 
searobin, age-0 squid and scup were more common in 
the seascapes in the Fall and had high scores on NMDS1.
The curves are generalized additive model (GAM) 
smoothing spline fits of proportions of maximum 
abundance for each species to station scores on NMDS1
(Fig. 5 below). Two standard error confidence bands 
are shown in blue. Rare species and those that did not 
show significant trends on the axis are not shown. Titles 
above plots are species common names while y-axes are
labeled with the species codes used in Figure 3

Answering the last question should give us clues about the nature of dynamic water column features strongly affecting the distributions and abundances of the animals.

To answer these questions I used the vegan library in R software to calculate ecological distances between samples and to visualize the relationships between community structure and the survey design factors (year, season, seascape, depth strata, patches of fine or medium sand) using non metric multidimensional scaling (metaMDS; e.g. Figs 3 & 4). I then used partial redundancy analysis (pRDA) to estimate proportions of the variation in the fish and invertebrate community to the nested factors we used to design the study (Fig. 2).

Before running these analyses I removed species occurring in less than 3 samples from the data and standardized abundances by dividing numbers of the remaining fish and invertebrates by the number of meters of bottom trawled to collect each sample. I then double square root transformed these standardized abundances to shrink the range and make the analyses sensitive to the rare as well as common species. Finally I used the bray-curtis index of similarity (%) in species composition as the index of ecological distance between the samples for the multidimensional scaling.

Before running these analyses I removed species occurring in less than 3 samples from the data and standardized abundances by dividing numbers of the remaining fish and invertebrates by the number of meters of bottom trawled to collect each sample. I then double square root transformed these standardized abundances to shrink the range and make the analyses sensitive to the rare as well as common species. Finally I used the bray-curtis index of similarity (%) in species composition as the index of ecological distance between the samples.

Figure 5. Ordination of samples along the first two axes
derived from the multidimensional scaling of ecological 
distances. Distances between points approximate 
differences in species composition and abundance between 
the samples. Samples collected in the New Jersey 
seascape are represented by circles while those collected 
in New York are squares. Open symbols represent shallow 
sites 10-20 meters deep whole deep sites (20-30m) are 
indicated by closed symbols. Red symbols are samples 
collected in patches of fine sand while blue symbols 
represent the samples from patches of medium to coarse 
sand. (still under construction).

1 Is the scale matching assumption always valid? Just as the variability of the atmosphere is buffered  as it it translated across the oceans surface, don't the organisms use their physiologies and behaviors to lower “pitch” of the ocean?

Friday, September 3, 2010

Seascapes, Landscapes & Marine Habitat Dynamics

Because the density and viscosity of water are higher than air, the structures in the ocean span shorter distances and last longer than similar structures in the atmosphere. The space-time diagram above shows that the speed of the ocean is about 100 times slower than the atmosphere. This difference in the speed of the environment on land and in the sea has allowed marine animals to remain more tightly coupled to the oceans “weather” than land organisms are to the atmospheres weather. In the diagram V1-V5 are lines of equal velocity at 103, 30, 0.3 , 3x10-3 & 3x10-5 centimeters per second. The red lines and blue lines are characteristic velocities of the atmospheric and ocean structures that are labeled in the same colors. The approximate space-time scales of forests on land and phytoplankton in the sea are also in the plot. Phytoplankton live and die fast like cavalier poets. The darker dotted line at the bottom is the threshold where laminar flow becomes turbulent flow. Life happens in turbulent flows. The diagram combines information from those in Mamayev (1996) and Steele & Henderson (1994)

One of the really interesting things to think about as a marine scientist is how different from landscapes, seascapes must be from an organisms perspective. Wrestling with this is central to our research program which is concerned with understanding why some parts of the ocean are essential to the survival of marine organisms and the resilience of marine ecosystems. Understanding the nature of the seascape is not easy because we come at the problem with terrestrial bias's; biological and ecological bias's that are even harder to overcome than cultural biases. Understanding differences between marine and terrestrial animals and the environments they occupy is also difficult because it requires a deep understanding of differences in the rates of change in space and time of the external environmental characteristics that affect survival and which therefor have guided the evolution of the animals in the sea. This is a problem of scaling. The space-time diagram above tries to identify the differences in the length-time scales of important dynamic features of the ocean and atmosphere.

Variations in wind, temperature, and precipitation associated with atmospheric storms, fronts, cyclones and long fronts are translated across the surface of the sea to create the waves, fronts, eddies, gyres, and deep ocean circulation which are the “weather” of the ocean. The high density and viscosity of water, its capacity to retain heat and dissolve salts, and its huge volume in the sea, causes the variability in atmosphere to be dampened and slowed down as it is translated across the sea surface. In the plot above, the turbulent structures of the oceans (in blue) are connected by the dotted blue line that is parallel to, but shifted to the right of the structures making the weather of the atmosphere. That rightward shift indicates that it takes much longer for similar structures move over a given distance in the sea. The take away message for me is that while life happens everywhere in turbulent flows and the speed of the ocean and its habitats is about 100 times slower than the speed of the atmosphere.

Because the variability of the atmosphere is slowed down and dampened in the sea, most marine organisms have not evolved the elaborate mechanisms of metabolic and physiological regulation required of terrestrial organisms to maintain homeostasis while in contact with a fast, extremely variable atmosphere. This means that most marine animals are more tightly coupled to the dynamics of the ocean's weather than terrestrial organisms are to the atmosphere's. The properties and dynamics of the water in the ocean are therefor critical to defining the habitats of marine organisms; even those strongly associated with the bottom. There are all sorts of interesting ramifications to this for marine animals who usually start out floating about in the ocean as fertilized eggs a few millimeters long, but grow in spatially dynamic universe made of structured water with 3 spatial dimensions over a huge range of body sizes. The habitat of a baby fish is probably not even perceived by a juvenile or adult. This is not the case for terrestrial organisms.

However there may be some bad ramifications to all this too. Below is a figure made from Sorte et al. (2010) who demonstrated that recent poleward shifts in distributions of marine organisms have occurred at 10 times the speed of the poleward shifts of land animals. These fast species range shifts in the sea may have to do with the tight physiological coupling of marine animals with oceans "weather:. They might also be related to the fact that the dominant force controlling movements in the sea is viscosity instead of gravity which controls the movements of organisms on land. The flows of materials and thus the connections between distant parts of seascapes are greater than for landscapes. Its generally easier to disperse faster over longer distances in the sea. The range shifts of marine and land animals depicted in the graph are probably the result of global climate change.

Steele JH & EW Henderson (1994) Coupling between physical and biological scales. Phil. Trans. R. Soc. Lond. B. 343: 55-9

Mamayev OI (1996) On space time scales of oceanic and atmospheric processes. Oceanology 35(6) 731-734

Sorte et al. (2010)  Marine range shifts and specie introductions: comparative spread rates and community impacts.  Global Ecology and Biogeography.  19: 303-316

Friday, August 27, 2010

General patterns in the bottom communities in the seascapes

Length frequencies of spotted hake collected in beam trawl surveys of the New York & New Jersey seascapes in 2008 & 2009.  Fish less than 1 year in age (age-0) were represented by individuals less than 70 millimeters in length.  These age-0 fish were only collected in New Jersey.
Shell height frequencies for sea scallops collected in beam trawls towed in the New York & New Jersey seascapes in 2008 & 2009.  At least 2 height/age classes of scallops were represented in our collections and scallops were consistently more abundant off New York.

Fancy statistics are useful but if a data summary and simple graphs don't reveal a few intriguing trends, no amount of statistical hokus pocus will make the data interesting.  So in an effort not to lose the forest for the trees below is a general summary table that I admit is a little difficult to read (The fancy statistics will come later). The table lists the percent occurrence and mean abundance of species we collected in 2 meter beam trawls in the two seascapes during 2008 and 2009 using the methods described earlier

Species richness and patterns of age & size
Over the two years we collected 34 fish species and 19 invertebrates. Based on the animals lengths, 5 fish and 3 invertebrates were represented by more than one age class including an early juveniles less than a year old. Animals less than 1 year old are labeled age 0 in the table. For example age 0 spotted hake were represented in our trawl collections by fish less than 70 millimeters (mm) long. We collected at least two age classes of sea scallops; the youngest less than 40 mm in shell height. In addition northern sea robin, four spot flounder, black sea bass, windowpane flounder as well as rock crabs and long fin inshore squid used habitats in at least one of the seascapes as early juvenile nurseries.

The dominant fish species we collected were little skate, age 1+ spotted hake, butterfish, smallmouth flounder and gulf stream flounder. These last two species were among the 7 flatfishes occurring in our trawl samples. The butterfish we collected were all young juveniles. The most common invertebrates were seven-spine bay shrimp, sea stars, age 0 rock crabs, sand dollars, and spider crabs.

General differences between Seascapes

A number of fish species appeared to be more common in the New Jersey seascape.  These included little skate, age 1+ spotted hake, bay anchovy were more common in New Jersey than New York while age-0 spotted hake collected exclusively in New Jersey over the two years. This suggests that larval delivery mechanisms and/or survival rates of newly settled spotted hake might make the New Jersey habitats more suitable nurseries. Butterfish and sand lance were also more abundant in New Jersey. Sand lance were rare in beam trawls, but these skinny little fish that live in sandy burrows were commonly captured on our underwater video and were dominant prey of the skates we collected in New Jersey during the early summer survey of 2008. The predators are always better samplers than we are. Gulfstream flounder, Red hake, age-0 searobin and striped searobin were more abundant in 2009. During that year the gulfstream flounder and red hake were more common in New York.


Among invertebrates sevenspine bay shrimp and spider crabs were more common in the New York seascape. Age-0 rock crabs, which were very important prey for many of the animals we collected, were also slightly more common in New York. Sand dollars were more abundant in New Jersey in 2008 while age-0 longfin inshore squid were more abundant in that seascape in 2009.

Sea stars were consistently more abundant in our New Jersey collections. These animals are important predators of young sea scallops.   In the plot above of scallop shell heights, the smallest year class in 2008 is visible as a strong second size mode in 2009.  All year classes of sea scallops were more abundant in New York than New Jersey.  This might indicate that the settlement and survival of this 2008 cohort was high in New York. Differences in encounter rates of sea star predators with sea scallop prey in the two seascapes may be partially responsible for the differences in scallop abundance we observe.  This is just the kind of hypothesis we can test in field experiments to identify the seascape characteristics that effect the dispersal, growth and survival of animals that use the areas as nurseries. (Thanks to Jessica Lajoie for helping to get this information together)

Friday, August 20, 2010

A brief pelagic interlude

Densities measured with CTDs along the 4 transects on which we 
collected depth stratified plankton samples with a tucker trawl from 
August 9-12, 2010.   
I am trying hard to focus on the analysis of differences in fish and invertebrate bottom communities in the seascapes to follow up the last post about our bottom sampling methods.  But sometimes fun stuff happens.  First, Chip Haldeman from RUCOOL plotted up the density data we collected with CTDs during our plankton cruises last week. His waterfall plots are just too cool not to share.  Notice the highest density water (darkest red; cold & salty) in the head of the Hudson Shelf Valley in deep water off New Jersey.  The Steven's institute NYHOPs model showed a slug of cold salty water off the mouth of the estuary which could have welled up along the shelf valley. We had strong upwelling conditions all of last week. We tried to sample the plankton in the cold water on August 11th along the New York transect oriented southwest to northeast in the plot above. The positions of our tucker trawl tows on the NYHOPs model temperatures on the 11th are shown immediately below.
 Positions of the tucker trawls on NYHOPs forecast 
temperatures on August 11, 2010 showing the cool water
off the mouth of the estuary. This transect is also shown
stretching southwest to northeast in the plot above. 

RUCOOL used our CTD data to decide how to ballast a robot glider launched today off Sandy Hook.  The glider is to fly from Sandy Hook south to Cape May, New Jersey in a zigzag pattern from the near shore to 40 km offshore.  The glider will provide Steven's institute with temperature and salinity data to better tune the NYHOPs model for near shore forecasting.  It is also equipped with a dissolved oxygen and other optical sensors that will be used in the State of New Jersey's water quality monitoring program. This is exactly the kind of model tuning and habitat condition data we need to do our seascape work better.

At the last minute RUCOOL asked us if we could help with a vessel to launch the glider.  This was invitation for real fun.  Below are some pictures of the robot glider launch and a pod of porpoises that we saw on the way home. The mission of glider RU-16 over the next few weeks can be followed here.

Location where we launched the RU-16 glider on 8/20/2010 overlaid upon the surface salinity forecast from the NYHOPs model.  NYHOPs indicated that we launched the robot on the estuarine plume front which is why we may have had some buoyancy issues with the glider.

Launching the "bird" from the Research Vessel "The Torch".  Highlands New Jersey is in the back round on the right.

The "bird" at the surface.  The glider has a satellite telephone in its tail so the COOL room can upload instructions and download data to the robot anywhere in the world.

The pod of porpoises we saw on the way home about 1/2 mile off Sandy Hook.

Wednesday, August 18, 2010

Methods of sampling the bottom communities in the Seascapes

Egg capsules of longfin inshore squid captured on videotape
of the seabed in the New York seascape using the camera 
sled described below.   
Many of the larval fish, crabs and molluscs we collect in our tucker trawl on plankton cruises are probably just passing though the seascapes off Rockaway, New York and Seabright, New Jersey like all the ships traveling inbound and outbound from New York Harbor.  However some may settle out of the plankton to become small juveniles that use the seascapes and adjacent areas as nursery grounds.  Th­e New York Seascape is often supplied with water flowing from the east along the south shore of Long Island and Block Island Sound, while the New Jersey seascape usually receives surface water flowing out of the Hudson-Raritan river estuary, as well as deeper offshore water flowing inshore when winds from the south drive coastal upwelling.  Since the sources of water to the seascapes are often so different, the communities of animals occupying bottom habitats could reflect differences in larvae in the water masses.  If the bottom communities are different there are other plausible explanations too.  For example larvae settling as juveniles could suffer much higher predation mortality in one of the seascapes, while some older animals could be residents in one seascape rather than the other because oceanographic barriers restrict their movements.  Answering these questions requires that we measure differences in the rates animals are eaten by predators or the pathways over which they move in the ocean. These processes are very difficult to measure in the sea. Like all things ecological these and perhaps other processes are probably going on simultaneously to greater or lesser degrees.  In our study we chose to answer the easiest question first. Are there differences in the juvenile and adult communities in the seascapes that are related to the supply of baby fish and crabs to them? Knowing the answers to this questions should allow us to ask the more difficult ones more specifically and with more nuance in the future.

New Jersey and New York seascapes.  Dark brown patches are
fine sand and mud, light brown patches are sandy based on
classified side scan sonar imagery.  Depth  contours are shown
in the closeup image of the New Jersey seascape.  Blank areas
in the seascapes are located where the rocky reef and other hard
structures prevented us from towing the video sled and two
meter beam trawl on the bottom.
Are there differences in the bottom communities of fish and invertebrates in the two seascapes?  We performed trawl and underwater video surveys of bottom habitats in 2008 and 2009 to answer that question.  We were careful to choose seascapes with similar bottom types on either side of the mouth of the Hudson Raritan river estuary.  Choosing similar bottom habitats allowed us to estimate the relative contributions of fine scale variation in the seabed characteristics as well as broader scale circulation patterns to making animal communities different between and within the seascapes. We used maps of bottom depth and sediment type based on sidescan sonar to divide up the bottom so that each seascapes had equal proportions of fine sand and mud, medium sand and hard bottom habitat patches in both  “shallow” and “deep” areas (Lathrop et al. 2006).   The surface area of the seabed in each of the seascapes was ~ 95 km^2 (~37 miles ^2).   Shallow areas ranged in depth from 10 to 20 meters. The deep areas ranged from 20 to 30 meters (~100 feet) which was as deep as we could sample using the boat and gear available to us.  Within the deep and shallow areas, fine and medium sand and hard bottom habitats made up about 1/3 of the surface area of the bottom.

The video camera sled with a low light Deep Sea power
and light camera (the black thing in the center) and a
conductivity temperature and depth probe mounted at the
top of the frame. The length of chain at the bottom of the sled
is a "tickler" that flushes the critters out into the field of view
of the video camera. (see the videos at the end of the post).
The two meter beam trawl which we towed immediately adjacent
to the track of the video sled to capture live animals for verifying
video imagery and to characterize the food webs in the seascapes
We towed a video camera sled and a 2 meter beam trawl to sample fish, invertebrates and bottom habitats in the seascapes.  We limited our sampling to the patches of fine and medium sand because we could not tow our gear over more complex hard bottom. We conducted the surveys during the late Spring (Late June), Mid Summer (Late July through early August) and the Autumn (late September through early October) to identify the seasonal changes in the habitat associations of fish and invertebrates. During each survey we randomly selected two patches in the two types of soft bottom habitat (fine and medium sand) in each depth zone (shallow and deep) within the seascapes (New York and New Jersey).  We randomly selected 2 sites within each "habitat patch" for towing the gears. Thus we sampled animals and their habitats at 32 locations in each survey (2 sites x 2 patches x 2 sediment types x 2 depth zones x 2 seascapes x 3 seasons x 2 years = 192 sites total).  After measuring the vertical structure of the water column at each site with a conductivity, temperature and depth profiler (CTD) we towed the video sled at speed of about 1 knot (0.51 meters per second) for 10 minutes over ~ 300 meters of bottom. Our sled which was designed after Spencer et al (2005) and equipped with a Deep Sea Power and Light low light video camera, allowed us to identify associations of fish and invertebrates with fine scale characteristics of the seabed, including sizes and wavelengths of sand waves and the presence and absence of burrows and pits made by animals (see video below).  We also attached a CTD probe that measured temperature, salinity, oxygen and PH to the sled, and used our ADCP to measure current speeds over the bottom during every second of tow. These instrument allowed us to relate the presence and absence of animals on video to changes in the characteristics of overlying bottom water as well as to the structure of the seabed itself.  After hauling back the video sled we immediately towed a two meter wide beam trawl (with a 3 mm mesh net) parallel to, but 10 to 20 meters to one side of, the sled track. We counted and measured all of the animals collected in these trawls.  The live animal samples allow us to confirm the identities and sizes of the animals we collected in the video sled images.  They also allowed us to perform dietary analysis to see whether the food webs in the seascapes were different. In the next few posts we will try to summarize some analyses of differences in the juvenile and adult bottom communities.

The video immediately below of the sea scallop swimming was collected in the deep portion of the New York Seascape, while the videos of lobster (middle video) and windowpane flounder (bottom video) were collected in the New Jersey Seascape.  There were many lobster burrows in the dredge spoils from the deepening of the port of New York that were deposited in the north east corner of the New Jersey seascape.  At the start of the middle video of the lobster the sled also passes over a large rock crab sitting in a burrow.




Spencer, M. L., A. W. Stoner, C. H. Ryer, and J. E. Munk. 2005. A towed camera sled for estimating abundance of juvenile flatfishes and habitat characteristics: Comparison with beam trawls and divers. Estuarine, Coastal and Shelf Science 64:497.

Lathrop, R. G., M. Cole, N. Senyk, and B. Butman. 2006. Seafloor habitat mapping of the New York Bight incorporating sidescan sonar data. Estuarine, Coastal and Shelf Science 68:221.