are degrading the physical, chemical, and biological properties
of the marine environment; causing the collapse of many fisheries
worldwide (1). As a result, fishery managers and policy makers are
being tasked with developing policies and management techniques
that increase the sustainability of the global fishing industry.
Marine reserves (MR) are an emerging tool for protecting biodiversity,
sustaining productivity, and allowing for continued extractive uses
of the marine environment (1,2). Over the past decade, MRs have
gained rhetorical acceptance in fishery management plans as a means
of mitigating uncertainty and bet-hedging against management failure
while promoting marine habitat protection (3,4). Yet despite their
anticipated importance, MRs effectively protect less than 0.01%
of the world’s oceans (3).
The design of MRs rests on two critical principles: 1) spillover
(export of biomass via juvenile/adult emigration) from within a
reserve into adjacent waters; and 2) population connectivity on
a regional scale via pelagic egg/larval dispersal. Although there
is evidence that MRs provide spillover effects (see 1,4,5); the
degree to which population connectivity occurs is debatable (4),
and due to a lack of connectivity-model validation and conflicting
results from field trials using various stocks, much uncertainty
remains (4,6,7). Many regard larval dispersal in marine ecosystems
to be one of the “major unsolved problems of biological oceanography”
(8). However, accurate and robust estimates of well- defined larval
dispersal and well-defined local retention are essential prerequisites
to resolving marine colonization patterns and to design effective
marine reserves (9).
I propose to quantify the extent of larval dispersal and subsequent
benthic recruitment in the Strait of Georgia and then develop a
spatially-explicit population model that has sufficient predictive
capability to increase the effectiveness of marine reserve designs,
from a connectivity perspective.
To track larval dispersal, two complementary fish otolith tagging
techniques will be used; one natural and one artificial. The first
relies on the fact geochemical signatures of population origin reside
in the calcified structures of fish larvae (i.e. otoliths) and act
as a natural tag (9). Mass spectrometry (i.e. ICP-MS) will be used
to identify trace element signatures within the otolith created
by spatial differences in water chemistry (typical of coastal systems
in which this study will occur; 9,10,11). These natural tag data,
from a larger spatial and temporal scale, will be validated through
an independent mark-recapture study on a subset of individuals from
known source locations. In this second study, an artificial fluorescent
compound (i.e. oxytetracycline) will be used to tag the eggs of
the model fish species (cabezon, Scorpaenichthys marmoratus and
garibaldi, Hypsypops rubicundus). This compound creates an unambiguous
fluorescence signature during UV microscopy, is readily incorporated
into the calcified tissues of larvae, and has been successfully
used to mass-mark batches of fish eggs in the field (9,12). Furthermore,
research shows these tags are detectable for up to 3 years, exposure
does not impact larval growth or mortality, and a 100% marking efficiency
is possible over a range of immersion times and chemical concentrations;
making this technique ideally suited for the study in question.(9).
This project will yield the first unequivocal data set that realistically
describes larval dispersal on a regional scale. The findings will
be used to create an explicit population connectivity model that
will be invaluable to scientists, resource managers, and policy
makers involved in the planning process of marine reserve networks;
and will act to construct the blueprint for future marine reserves,
increasing the sustainability of marine fisheries while simultaneously
protecting marine biodiversity.
1. Lubchenco, J., et al. 2003. Plugging a hole in the ocean:
the emerging science of marine reserves. Ecological Applications 13:
2. Russ, G.R., and D.C. Zeller. 2003. From mare liberum to mare reservarum.
Marine Policy 27: 75-78.
3. Pauly, D., et al. 2002. Towards sustainability in world fisheries.
Nature 418: 689- 695.
4. Russ, G. R. 2002. Yet another review of marine reserves as reef
fishery management tools. in P.F. Sale, ed. Coral Reef Fishes: Dynamics
and Diversity in a Complex Ecosystem. Academic Press, San Diego, CA.
5. Palumbi, S. 2002. Marine Reserves: A tool for ecosystem management
and conservation. Report to the Pew Oceans Commission, Washington,
6. Botsford, L.W., et al. 2003. Principles for the design of marine
reserves. Ecological Applications 13: Supp. S25-S31.
7. Gerber, L.R., et al. 2003. Population models for marine reserve
design: a retrospective and prospective synthesis. Ecological Applications
13: Supp. S47-S64.
8. Palumbi, S.R. 1999. The prodigal fish. Nature 402: 733-735.
9. Thorrold, S.R., et al. 2002. Quantifying larval retention and connectivity
in marine populations with artificial and natural markers. Bulletin
of Marine Science 70: Supp. 291-308.
10. Gillanders, B.M., and M.J. Kingsford. 1996. Elements in otoliths
may elucidate the contribution of estuarine recruitment to sustaining
coast reef populations of a temperate fish. Marine Ecology Progress
Series 141: 13-20.
11. Thorrold, S.R., et al. 1998. Accurate classification of nursery
areas of juvenile weakfish (Cynoscion regalis) based on chemical signatures
in otoliths. Marine Ecology Progress Series 173: 253-265.
12. Jones, G.P., et al. 1999. Self-recruitment in a coral reef fish
population. Nature 402: 804-804.