Download Estimating dispersal in marine fish to improve resilience to

Estimating dispersal in marine fish to improve
resilience to climate change
Malin L. Pinsky, [email protected], Stanford University, Pacific Grove, CA,
USA.
Humberto R. Montes, Jr., Visayas State University, Leyte, Philippines
Malin Pinsky
Maintaining the movement of organisms between
populations (connectivity) is one of the most
commonly advocated conservation strategies in
response to climate change (Opdam & Wascher
2004). However, robust estimates of dispersal are
required to design effective connectivity conservation,
and there is substantial uncertainty about whether
marine species have short or long-distance dispersal.
In the ocean, marine currents and long pelagic larval
stages for most organisms create a high potential for
long-distance dispersal (Roberts 1997). However,
recent studies have found populations that are largely
replenished by local offspring, suggesting local
dispersal (Swearer et al. 1999; Almany et al. 2007). To
address this problem and improve our ability to plan
for the impacts of climate change, we developed an
approach using population genetics to measure the
distances traveled by marine larvae (Pinsky et al.
2010).
Calculating
organisms
dispersal
distances
in
marine
Figure 1: Isolation-by-distance genetic patterns
for A. clarkii along two islands (Cebu and Leyte)
in the central Philippines. The y-axis is a
Population genetics provides a useful tool for studying measure of genetic distance.
dispersal because it uses the natural tags present in
every organism’s DNA. In particular, when the genetic
distance between populations increases with the
geographic distance between them (Figure 1), the
slope of the relationship can be used to calculate the
typical distance traveled by an organism (Rousset
1997). This pattern is called “isolation-by-distance.”
We demonstrated how to use this method with
Amphiprion clarkii, a common clownfish on tropical
coral reefs. As a fish with a short larval duration (7 to
11 days) and therefore a species likely to have lower
dispersal abilities, adaptation strategies sufficient to
maintain connectivity for this species will likely
maintain connectivity for a wide range of fishes.
To apply isolation-by-distance methods, we sampled
17-34 fish at 18 sites across 450km of coastline on
two islands in the central Philippines. Samples were
collected from both adults and juveniles to allow us to
estimate density from the strength of genetic drift
(see Pinsky et al. 2010 for explanation of these
methods). We also estimated adult density from
visual transects. This sampling strategy is simple to
apply, and therefore should be applicable to a wide
range of species.
We then measured genetic distance between each
sampled population with 13 microsatellite loci, and
we regressed this against geographic distance
(Figure 1). Finally, we used the slope of the
regression and our estimate of density to estimate
that typical dispersal distances in A. clarkii are 11 km
(4-27 km) (see Pinsky et al. 2010 for details).
Interestingly, this distance is two orders of magnitude
larger than has recently been suggested (Shanks
2009), likely because some previous methods have
difficulty detecting long-distance dispersers. The
dispersal distance we calculated can then be used to
design conservation measures and climate
adaptation strategies for clownfish and other marine
fish.
Using dispersal knowledge to improve resilience Figure 2. Map of a marine protected area (MPA)
to climate change
network on the island of Cebu, Philippines. The
red rectangles are MPAs. The arrow indicates a
When attempting to improve climate change gap in the network that may impede connectivity.
resilience in marine fish, there are two primary Map courtesy of the Coastal Conservation and
considerations:
improving
the
resilience
of Education
Foundation
(CCEF,
Cebu,
populations in situ, and allowing populations to move Philippines).
in search of more favorable conditions. Reducing
exposure to non-climate-related stressors can
strengthen population resilience, and marine
protected areas (MPAs) have been one especially
effective approach (Lester et al. 2009). MPAs are
areas of the ocean where fishing, habitat destruction,
and other extractive activities are limited. To sustain a
viable population, however, a substantial fraction of
the dispersing offspring must stay within the MPA. An
isolated MPA for A. clarkii would have to be about
20km wide, or twice the typical dispersal distance
(Lockwood et al. 2002).
An alternative is to design networks of much smaller MPAs, each connected to the other by dispersing
larvae (Figure 2). MPA networks also have a number of benefits for climate adaptation. In many
species, some populations are already adapted to high temperatures and other conditions predicted
under climate change (Balanyá et al. 2006). When designed in networks, MPAs create stepping-stones
that allow beneficial genes to flow to those populations experiencing climatic extremes for the first time.
This process would aid local adaptation to climate change. Without a network of MPAs, habitat
destruction and overfishing could create large gaps that would impede beneficial gene flow. MPA
networks can also allow populations to move to more favorable conditions by providing the necessary
stepping-stones. If local conditions become too extreme, this may be the only survival strategy.
Because clownfish, and most coastal marine species, are site-attached as adults, migration will take
place primarily during the larval stage. Given what we now know about dispersal in A. clarkii, spacing
between MPAs would need to be about 10-20 km to facilitate this movement (Figure 2).
In conclusion, estimates of dispersal are important for designing effective conservation strategies that
improve the climate resilience of marine populations. While dispersal distances in marine organisms
have been highly uncertain, we have shown how dispersal can be estimated with a genetic method
that will be applicable to a wide range of species.
References
Almany G.R., Berumen M.L., Thorrold S.R., Planes S. & Jones G.P. (2007). Local replenishment
of coral reef fish populations in a marine reserve. Science, 316, 742-744.
Balanyá J., Oller J.M., Huey R.B., Gilchrist G.W. & Serra L. (2006). Global genetic change tracks
global climate warming in Drosophila subobscura. Science, 313, 1773-5.
Lester S.E., Halpern B.S., Grorud-Colvert K., Lubchenco J., Ruttenberg B.I., Gaines S.D.,
Airamé S. & Warner R.R. (2009). Biological effects within no-take marine reserves: a global
synthesis. Mar. Ecol. Prog. Ser., 384, 33-46.
Lockwood D.R., Hastings A. & Botsford L.W. (2002). The effects of dispersal patterns on
marine reserves: does the tail wag the dog? Theor. Popul. Biol., 61, 297-309.
Opdam P. & Wascher D. (2004). Climate change meets habitat fragmentation: linking
landscape and biogeographical scale levels in research and conservation. Biol. Conserv., 117,
285-297.
Pinsky M., Montes H.R., Jr. & Palumbi S.R. (2010). Using isolation by distance and effective
density to estimate dispersal scales in anemonefish. Evolution, 64, 2688-2700.
doi:10.1111/j.1558-5646.2010.01003.x
Roberts C.M. (1997). Connectivity and management of Caribbean coral reefs. Science, 278,
1454-1457.
Rousset F. (1997). Genetic differentiation and estimation of gene flow from F-statistics under
isolation by distance. Genetics, 145, 1219-1228.
Shanks A.L. (2009). Pelagic larval duration and dispersal distance revisited. Biological Bulletin,
216, 373-385.
Swearer S.E., Caselle J.E., Lea D.W. & Warner R.R. (1999). Larval retention and recruitment in
an island population of a coral-reef fish. Nature, 402, 799-802.