Journal of Marine Systems xxx (2014) xxx–xxx
MARSYS-02536; No of Pages 15
Contents lists available at ScienceDirect
Journal of Marine Systems
j ourna l homepage: www.e lsev ie r .com/ locate / jmarsysComparative biogeochemistry–ecosystem–human interactions on
dynamic continental marginsLisa A. Levin a,⁎, Kon-Kee Liu b, Kay-Christian Emeis c, Denise L. Breitburg d, James Cloern e, Curtis Deutsch f,
Michele Giani g, Anne Goffart h, Eileen E. Hofmann i, Zouhair Lachkar j, Karin Limburg k, Su-Mei Liu l,
Enrique Montes m, Wajih Naqvi n, Olivier Ragueneau o, Christophe Rabouille p, Santosh Kumar Sarkar q,
Dennis P. Swaney r, Paul Wassman s, Karen F. Wishner t
a Center for Marine Biodiversity and Conservation, Scripps Institution of Oceanography, 9500 Gilman Dr., La Jolla, CA 92093-0218, USA
b Institute of Hydrological and Oceanic Sciences, National Central University, Chungli 320, Taiwan
c Helmholtz-Zentrum Geesthacht, Institute of Coastal Research, Max-Planck-Str. 1, 21502 Geesthacht, Germany
d Smithsonian Environmental Research Center, PO Box 28, 647, Edgewater, MD 20676, USA
e United States Geological Survey, 345 Middlefield Rd., Menlo Park, CA 94025, USA
f School of Oceanography, University of Washington, Seattle, WA 98195, USA
g Istituto di Oceanografia e Geofisica Sperimentale (OGS), Via A. Piccard 54, 34151 Trieste, Italy
h Laboratoire d'Océanologie, Université de Liège, B6c, B 4000 Liège, Belgium & STARESO, F 20260 Calvi, France
i Center for Coastal Physical Oceanography, Old Dominion University, Norfolk, VA 23508, USA
j Environmental Physics, Institute of Biogeochemistry and Pollutant Dynamics, ETH Zurich, CHN E 23.1, Universitätstrasse 16, 8092 Zürich, Switzerland
k Department of Environmental and Forest Biology, State University of New York College of Environmental Science and Forestry, Syracuse, NY 13210, USA
l Key Laboratory of Marine Chemistry Theory and Technology Ministry of Education, Ocean University of China, Qingdao 266100, PR China
m College of Marine Science, University of South Florida, St. Petersburg, FL, USA
n National Institute of Oceanography, Goa, India
o Laboratoire des Sciences de l'Environnement Marin, Institut Universitaire Européen de la Mer, Technopôle Brest-Iroise, 29280 Plouzané, France
p Laboratoire des Sciences du Climat et de l'Environnement, Gif sur Yvette, France
q Department of Marine Science, University of Calcutta, 35 Ballygunge Circular Road, Calcutta 700019, India
r Department of Ecology and Evolutionary Biology, Cornell University, Ithaca, NY 14853, USA
s Dept. of Arctic and Marine Biology, Faculty of Bioscience, Fishery and Economy, University of Tromsø, 9037 Tromsø, Norway
t University of Rhode Island, 215 S Ferry Rd., Narragansett, RI 02882, USA⁎ Corresponding author. Tel.: +1 858 534 3579.
E-mail addresses: llevin@ucsd.edu (L.A. Levin), kkliu@
cdeutsch@uw.edu (C. Deutsch), mgiani@inogs.it (M. Gian
klimburg@esf.edu (K. Limburg), sumeiliu@ouc.edu.cn (S.-
christophe.rabouille@lsce.ipsl.fr (C. Rabouille), sarkar.sant
(K.F. Wishner).
http://dx.doi.org/10.1016/j.jmarsys.2014.04.016
0924-7963/© 2014 Elsevier B.V. All rights reserved.
Please cite this article as: Levin, L.A., et al., Com
Syst. (2014), http://dx.doi.org/10.1016/j.jmaa b s t r a c ta r t i c l e i n f oArticle history:
Received 4 January 2014
Received in revised form 22 April 2014
Accepted 24 April 2014
Available online xxxx
Regional terms:
Continental margins
Europe
North Atlantic
North Pacific
ArcticThe oceans' continental margins face strong and rapid change, forced by a combination of direct human activity,
anthropogenic CO2-induced climate change, and natural variability. Stimulated by discussions in Goa, India at the
IMBER IMBIZO III, we (1) provide an overview of the drivers of biogeochemical variation and change onmargins,
(2) compare temporal trends in hydrographic and biogeochemical data across different margins, (3) review eco-
system responses to these changes, (4) highlight the importance of margin time series for detecting and attrib-
uting change and (5) examine societal responses to changing margin biogeochemistry and ecosystems. We
synthesize information over a wide range of margin settings in order to identify the commonalities and distinc-
tions among continental margin ecosystems. Key drivers of biogeochemical variation include long-term climate
cycles, CO2-induced warming, acidification, and deoxygenation, as well as sea level rise, eutrophication, hydro-
logic and water cycle alteration, changing land use, fishing, and species invasion. Ecosystem responses are com-
plex and impact major margin services. These include primary production, fisheries production, nutrient cycling,
shoreline protection, chemical buffering, and biodiversity. Despite regional differences, the societal consequencesncu.edu.tw (K.-K. Liu), kay.emeis@hzg.de (K.-C. Emeis), breitburgd@si.edu (D.L. Breitburg), jecloern@usgs.gov (J. Cloern),
i), a.goffart@ulg.ac.be (A. Goffart), hofmann@ccpo.odu.edu (E.E. Hofmann), zouhair.lachkar@env.ethz.ch (Z. Lachkar),
M. Liu), emontesh@mail.usf.edu (E. Montes), naqvi@nio.org (W. Naqvi), olivier.ragueneau@univ-brest.fr (O. Ragueneau),
osh@gmail.com (S.K. Sarkar), dps1@cornell.edu (D.P. Swaney), paul.wassmann@uit.no (P. Wassman), kwishner@gso.uri.edu
parative biogeochemistry–ecosystem–human interactions on dynamic continentalmargins, J. Mar.
rsys.2014.04.016
2 L.A. Levin et al. / Journal of Marine Systems xxx (2014) xxx–xxxKeywords:
Anthropogenic factors
Coastal biogeochemistry
Climate change
Eutrophication
Ecosystem services
Time seriesPlease cite this article as: Levin, L.A., et al., Com
Syst. (2014), http://dx.doi.org/10.1016/j.jmaof these changes are unarguably large and mandate coherent actions to reduce, mitigate and adapt to multiple
stressors on continental margins.
© 2014 Elsevier B.V. All rights reserved.1. Introduction to dynamic margin ecosystems
The oceans' continental margins extend for some 150,600 km
(Jahnke, 2010) and encompass estuarine, open coast, shelf, canyon,
slope, and enclosed sea ecosystems. They are both gateway andwindow
to the open ocean, where water, nutrients, energy, sediments, contam-
inants and organisms meet and are transferred through land-margin
andmargin-open ocean interactions (Levin et al., 2001). The continental
margins include proximal estuaries, bays, lagoons and banks, and distal
shelves, slopes and marginal seas. These are susceptible to changes in
biodiversity, water quality, and productivity and have been increasingly
perturbed by human activities.
Margin ecosystems include hard and soft-substrate habitats ranging
from structurally complexwetlands, kelp forests, coral reefs, rocky reefs
and sand beaches, to sedimented estuaries, slopes and canyons. Most of
the habitat volume, however, occurs in the overlying water column,
with variation linked to water masses, circulation, and land and atmo-
spheric interactions. As one crosses depth contours from estuaries
across the shelf to the continental slope, steep gradients in nutrient con-
centrations, temperature, salinity, oxygen, pH and suspended matter
are found that impact the productivity, composition, diversity, and
abundance of organisms (Cloern, 1996; Hofmann et al., 2011; Levin
and Sibuet, 2012). Relative to their area, the margins account for a
disproportionately large fraction of the global primary production (10–
15%), nutrient recycling, carbon burial (N60% of total settling organic car-
bon), and fisheries production (Muller-Karger et al., 2005; Walsh et al.,
1988). They also are exceptionally dynamic systemswith ecosystemstruc-
tures that can oscillate slowly or shift abruptly, but rarely remain static.
The current continental margin seascape has been shaped exten-
sively by climate change and human activities, yielding altered ecosys-
tem services. Margin ecosystems provide key services in the form of
physical protection from waves, storms, and floods, chemical buffering,
food provisioning, nursery support, nutrient cycling, habitat fostering
biodiversity, carbon sequestration, recreation, and aesthetic value. Fine-
ly tuned biogeochemical interactions drive these functions. Because
human populations are disproportionately concentrated in coastal
cities, there is heterogeneity in the human effects on margins, creating
mosaics of heavily impacted and relatively pristine systems. Nutrient in-
puts, freshwater extraction, fishing, construction, species introductions,
and contamination are but a few of themanyways humans alter coastal
ecosystems. Also, the steady increase of anthropogenic CO2 inputs to the
atmosphere will result in significant changes inwater column tempera-
ture, oxygenation, pH, and productivity by 2100, with major conse-
quences for margin ecosystems and the over 1 billion people that
depend on them for food, employment and revenue (FAO, 2012; Mora
et al., 2013).
While margin research has a long history among oceanographers
(Antia et al., 2001; Banner et al., 1980; Biscaye et al., 1994; Duarte
et al., 1999; Liu et al., 2010; Walsh et al., 1988), a synoptic view of
dynamic coupled margin systems has emerged more slowly and the
linkages between human and natural biogeochemical variations, eco-
system response and human social structures are only now being ex-
plored. The interactive effects of remote forcing from distant inland
activities, from atmospheric processes, and from physical processes far
out to sea are becoming more apparent. There are, however, gaps in
our understanding of the combined effects ofmultiple drivers on coastalparative biogeochemistry–e
rsys.2014.04.016biogeochemistry and ecosystems across all continentalmargins. The ob-
jectives of this paper are to provide an overview of sources of biogeo-
chemical variation on margins, associated ecosystem responses, and
the societal and policy implications, with a focus on lessons frommulti-
ple continental margin time series (Fig. 1).
This paper reflects the themes and discussions of the continentalmar-
gins working group of IMBER IMBIZO III (Goa, India in January 2013). In
this paper we examine drivers of biogeochemical variation on margins,
distinguishing natural from CO2-based climate variability, and more di-
rect human drivers. We next compare temporal trends for multiple
physical and biogeochemical parameters at geographically contrasting
locations. We then discuss the complex ecosystem responses to biogeo-
chemical variation and trends on margins, in particular those related to
warming, deoxygenation, acidification and hydrologic alterations. We
subsequently identify the key roles played by continental margin time-
series stations (Fig. 1) in identifying and attributing drivers of change
and in understanding the associated ecosystem responses. Finally, we
examine societal responses to changing margin biogeochemistry and
ecosystems, highlighting areas where social and natural scientists must
work together. Case studies (expanded in Supplementary material B)
are synthesized to provide insights into the sensitivity of margins to nat-
ural and human perturbations, the ecological, social and economic con-
sequences that stem from these perturbations, and the policy actions
needed to mitigate impacts on coastal ecosystems and their resources.
2. Natural and human-induced drivers of biogeochemical variation
on margins
Controls on biogeochemistry of margins are complex and dynamic. In
this paper we distinguish drivers associated with natural variability, an-
thropogenic CO2-driven climate change anddirect human (anthropogenic)
impacts. It is oftendifficult to disentangle these three forcingmechanisms,
as well as to distinguish local change from regional to global-scale pres-
sures. Multiple factors act together — exerting top-down (often human)
and bottom-up (natural or human) controls on ecosystem structure
simultaneously.
2.1. Natural sources of variability
Natural variation in biogeochemical features affecting margin eco-
systems occurs on a vast range of time scales, from millions of years to
hours. Directmeasurements during the past century inmany of the sys-
tems discussed here have revealed large, abrupt, persistent changes in
the structure and function (or state) of an ecosystem,whichwere some-
times interpreted as regime shifts (Barnosky et al., 2012; deYoung et al.,
2008; Mumby et al., 2007). These may be manifested as simultaneous
changes in phytoplankton, dominant consumer species, and trophic
structure. Regime shifts often yield major consequences for fisheries
and human livelihood (McFarlane et al., 2002; Zhang and Gong, 2005).
Examples can be found in the North Pacific-Pacific Decadal Oscillation
(Wooster and Zhang, 2004), North Atlantic (Alheit et al., 2014),
Caribbean coral reefs (Hughes, 1994), Mediterranean Sea (Conversi
et al., 2010), Northern Adriatic Sea (Conversi et al., 2009) and North
Sea (Beaugrand, 2004). In the Northern Hemisphere, major ecosystem
shifts were observed in the late 1980s to early 1990s, with synchronous
shifts following an overall period of high variability. These ecosystemcosystem–human interactions on dynamic continentalmargins, J. Mar.
Fig. 1.Map showing locations of time-series observations that exemplify the interplay of natural variability, CO2-driven climate change and human activities to shapemargin ecosystems.
Each area is discussed in themanuscript or summarized in Table 1 and the supplementarymaterial. 1. Arctic Sea; Americanmargins: 2. Cariaco Basin, 3. Chesapeake Bay, 4. Gulf of Mexico
off Louisiana, 5. San FranciscoBay, 6. Southern California Bight; Africanmargins: 7. Canary Current System, 8. Congo River Submarine Canyon; Asian seas: 9. Bay of Bengal, 10. Bohai Sea, 11.
East China Sea; European seas: 12. Baltic Sea, 13. Black Sea, 14. Mediterranean— Corsica (Liguran Sea), 15. Mediterranean — N. Adriatic Sea, 16. North Sea.
3L.A. Levin et al. / Journal of Marine Systems xxx (2014) xxx–xxxregime shifts were linked to changes in global-scale climate indices
(Chavez et al., 2011; Conversi et al., 2010; Möllmann et al., 2011). It is
cautioned that these abrupt changes are sometimes difficult to distin-
guish from random fluctuations or overfishing effects and their true
nature often remains unclear (e.g., Hsieh et al., 2005).
Margins may also be subject to basin-specific and regional influ-
ences. For example, the California Cooperative Oceanic Fisheries Investi-
gations (CalCOFI), one of the longest existing oceanographic time series
(63 years), reveals major natural variations in water column tempera-
ture, oxygen, pH and current strength that are associated with changes
in the regional hydrography of the California Current Ecosystem over
multiple time and space scales (Checkley and Barth, 2009; McClatchie
et al., 2010; Nam et al., 2011; Send and Nam, 2012). In addition to the
Pacific Decadal Oscillation, there are decadal scale ENSO cycles, seasonal
and week-long upwelling events that alter productivity and/or ocean
biogeochemistry withmarked shifts in oxygen and pH (Fig. 2). Variabil-
ity in these environmental parameters results in changes in the regional
biodiversity and ecosystem structure with significant impacts on
ecosystem services we depend on (Doney et al., 2012).
Much natural climate variability and somemanifestations of climate
change occur abruptly over short time and space scales. Most margins
experience episodic, extreme events that shape their ecosystems,
often through biogeochemical modification. For example the Rhone
River carries 80% of its solid flux during 5% of the time (Antonelli
et al., 2008) with large biogeochemical consequences (Cathalot et al.,
2010). Extreme storm events can reshape coastal systems with short-
lived, dramatic changes in salinity and flushing rates and through
more persistent alterations of channel openings (Paerl et al., 2001). At-
mospheric deposition of nutrients associated with air mass outflow
from the Indo-Gangetic Plain to the northern Bay of Bengal is significant
andmost can occur over 4 months in association with the NEmonsoon,
highlighting the temporal nature of these atmospheric drivers (Srinivas
et al., this volume). These are likely to have direct consequences for eu-
trophication in Bay of Bengal surface waters, triggering profuse algal
blooms in the adjacent Sundarban wetland (Naha Biswas et al., 2013).
Heatwaves that last for a fewweeks can inducemassmortality in coast-
al ecosystems of theMediterranean Sea, either directly (Garrabou et al.,
2009; Marba and Duarte, 2010) or through the spread of disease and
invasive species (Lejeusne et al., 2010).Please cite this article as: Levin, L.A., et al., Comparative biogeochemistry–e
Syst. (2014), http://dx.doi.org/10.1016/j.jmarsys.2014.04.016As with short time scales, small areas of the ocean can play key roles
in global biogeochemical fluxes on margins. For example, 1% of the
ocean's water volume accounts for 50% of N removal throughwater col-
umn denitrification and anammox in oxygen deficient zones (Deutsch
et al., 2011), and 60–70% of the annual denitrification rate occurs in
shelf sediments (Codispoti, 2007). Submarine canyons carry 80–90% of
the sediment and organic matter fluxes to the open seafloor sediments,
with transport affected by climate-driven stratification, wind regime
and winter cooling (Canals et al., 2006; Rabouille et al., 2013). It is
proposed that the Congo River, with the second largest discharge in
the world, carries 50% of the river's silica through an 800-km long sub-
marine canyon to a 3000 km2 deep-sea fan (Raimonet et al., this
volume). The functions of submarine canyons as key removal agents
via deep-sea fans and deltas may be diminished by climate change-
driven reduction of dense water formation with less cascading and
deep export (Herrmann et al., 2008; Rabouille et al., 2013).
An important question to emerge iswhether natural variability asso-
ciated with exposure to stressful conditions (such as hypoxia or hyper-
capnia) confers evolutionary pre-adaptation to further stress from
climate change or direct human activities. Evidence suggests that ani-
mals inmargin settings subject to upwelled, low-pHwaters are resilient
to such conditions (e.g., Hofmann et al., 2014; Thomsen et al., 2010; Yu
et al., 2011). In other coastal regions where hydrographic variability is
also intense and there are multiple controls from land, detection of
trends, sources and biological responses including adaptation can be
difficult (Duarte et al., 2013). Whether hydrographic stressors that
vary naturally (oxygen, acidification and warming) elicit more adapta-
tion than ‘unnatural’ (man-made) trace organic or metal/metalloid
contaminants remains an open question.2.2. CO2-driven climate drivers
Rising CO2 in the atmosphere is reshapingmargin ecosystems by in-
creasing sea level, ocean warming, ocean acidification and ocean deox-
ygenation (Doney et al., 2012). There are also climate shifts that alter
patterns of heat, drought, precipitation, and flooding that modify mar-
gins directly and indirectly through changes in land use, runoff, and
human activities.cosystem–human interactions on dynamic continentalmargins, J. Mar.
Fig. 2. Data plots of O2 and pH illustrating time scales of natural hydrographic variability in the nearshore southern California Bight, USA. (a) Decadal scale suggesting regime shifts
(modified fromMcClatchie et al., 2010). (b) Interannual scale illustrating effects of ENSOat a site 6 km fromDelMar (modified fromNamet al., 2011), (c) seasonal scale combining CalCOFI
data at line 93 and continuousmooringmeasurements (modified from Send andNam, 2012), (d) event (week) scale illustrating upwelling (blue) and relaxation (green) phases (modified
from Send and Nam, 2012), and (e) semi-diurnal and diurnal scale variations in the La Jolla Kelp Forest during upwelling phase (blue) when there are strong semidiurnal signals and re-
laxation phase (green) when kelp influences the oxygen and pH variability (Frieder et al., unpublished).
4 L.A. Levin et al. / Journal of Marine Systems xxx (2014) xxx–xxxCO2-induced warming and enhanced stratification have been linked
to declining oxygen concentrations on the southern California shelf and
upper slope (Bograd et al., 2008) as well as increased seasonal hypoxia
on the innerOregon shelf (Chan et al., 2008). These changes also involve
lowered pH and high pCO2 (Alin et al., 2012; Frieder et al., 2012), with
consequences for biogeochemical cycling and ecosystem structure in
the California Current (CC) system (Doney et al., 2012). Upwelling is in-
tensifying and low pH (which promotes aragonite undersaturation) is
spreading in the northeast Pacific (Feely et al., 2008; Gruber et al.,
2012). The observed low pH conditions in the CC system are shaping
characteristics of this ecosystem by affecting calcifying species and
have resulted in the decline of cultured bivalves (Barton et al., 2012).
Whether the oxygen and pH changes reflect a continuous, secular
trend resulting from CO2-driven climate changes or are part of a larger
(50 years) natural cycle remains controversial (Deutsch et al., 2011;
McClatchie et al., 2010). These changes are occurring in an ecosystem
already subject to high natural variability (Fig. 2). Clear understanding
of this complexity is needed for forecasting future conditions.
Beyond upwelling regions, perhaps the greatest manifestations of
climate change are found on the shelves of the Arctic Ocean. Among
the most massive of inputs, a full 10% of the freshwater reaching the
oceans occurs in the Arctic, which has only 4 million people livingPlease cite this article as: Levin, L.A., et al., Comparative biogeochemistry–e
Syst. (2014), http://dx.doi.org/10.1016/j.jmarsys.2014.04.016there. Thawing of permafrost due to warming yields increased inputs
of soil organic carbon andmethane to the coastal ocean and atmosphere
(Schuur, 2013), and will influence many aspects of the Arctic coastal
ecosystem (Whiteman et al., 2013). The freshwater from melting sea
ice combined with degradation of released organic matter is causing
major perturbation of low pH in the Arctic. Baseline monitoring of the
W. Arctic Ocean reveals that 20% of the Canada Basin surface waters
exhibit aragonite undersaturation (Robbins et al., 2013).
As temperatures continue to increase (Behrenfeld et al., 2006),
warming is expected to reduce productivity over much of the ocean
(Mora et al., 2013). It is uncertain whether lowered production will
reduce oxygen depletion in midwater (from decomposition of sinking
phytoplankton and respiration of vertical migrators), counteracting
the deoxygenation effects of global warming (from increased stratifica-
tion and reduced mixing). Alternatively, intensified upwelling in a
warmer world may pump more nutrients into surface waters, increase
primary production and subsequent respiration of microbes and other
organisms, and increase the rate of deoxygenation. As a direct effect or
through changes in currents such as the Gulf Stream,warmingmight in-
crease methane emissions via dissociation of gas hydrates on continen-
tal margins (Phrampus and Hornbach, 2012). Massive gas hydrate
deposits in the shallow Arctic Ocean are particularly susceptible andcosystem–human interactions on dynamic continentalmargins, J. Mar.
5L.A. Levin et al. / Journal of Marine Systems xxx (2014) xxx–xxxtheir releasemay exacerbate acidification and oxygen depletion via aer-
obic methane oxidation in the water column (Biastoch et al., 2011).
There has yet to be exploration of modern biological responses to
long-term increases inmethanefluxes onmargins, although the geolog-
ic past may hold lessons in this regard (Kennett et al., 2003).
2.3. Direct human drivers
Rivers are a primary conduit of nutrient loading to the shelf from ter-
restrial sources of nutrients. Since the development in the early 20th
century of the Haber–Bosch process for fixing nitrogen for use in fertil-
izers, the global nitrogen cycle has become increasingly affected by
anthropogenic inputs. The net anthropogenic nitrogen inputs (NANI)
to a region include fertilizer application, atmospheric deposition, agri-
cultural N fixation by leguminous crops, and the nitrogen associated
with food and livestock feed crossing regional boundaries. Nitrogen
flux in rivers is often highly correlated to the NANI of their drainage ba-
sins (e.g., Han and Allan, 2008; Howarth et al., 1996; Swaney et al.,
2012). In areas of high population densities (e.g., coastal cities) or
regions of industrial-scale livestock production, as is increasingly seen in
India and China, the nitrogen associated with the trade of food and feed
commodities may be very significant. In areas of high crop production,
synthetic N fertilizer is typically the dominant source of N (e.g., Yan
et al., 2010). In India, use of synthetic fertilizer has grown exponentially
over the last fifty years,making Indian agriculture one of themost intense
consumers of fertilizer in theworld (Swaney et al., in this issue). Between
1970 and2000, the coastal Bay of Bengal has experiencedmassiveNandP
loading (50% and 35% increase, respectively) causing eutrophication;
70–80% of the loading is from agricultural sources (Sattar et al., 2014).
Margins play a key role in filtering nutrients and contaminants that
enter the ocean via runoff and rivers. Productive estuarine ecosystems,
particularly wetlands, are able to remove nutrients by denitrification,
uptake by vascular plant, phytoplankton, and microbes, by promoting
flocculation and enhancing deposition and burial (Dähnke et al., 2008;
Howarth et al., 2006, 2012; Kennedy, 1984; Lassaletta et al., 2012).
Intensive filter feeding by bivalves such as oysters and mussels can
also remove particulate nutrients and control eutrophication (Cloern,
1982; Dame, 2012). The filtering functions ofmargins have been greatly
affected by massive wetland loss over the past century, due largely to
changing land use and sea level rise. Globally, overfishing (of oysters)
and species introductions (of invasive bivalves) have also had a major
influence on water filtration functions (Dame, 2011).
Human acceleration of nutrient cycles and eutrophication is among
the best studied of the anthropogenic forcing factors and causes the
most conspicuous adverse effects upon continentalmargins aswitnessed
by diverse case studies (Table 1, Fig. 1). Intensified nitrogen loading is
widespread in coastal ecosystems receiving effluents from catchments
with dense human populations (Glavovic et al., submitted for
publication; Rabalais, 2004). This yields continental margin dead
zones (coastal hypoxic areas resulting from eutrophication), which
number over 475 and are on the rise (Diaz and Rosenberg, 2008;
World Resources Institute, 2013). The largest of these occur in the Baltic
Sea, the Black Sea, the northern Gulf of Mexico and the East China Sea
(Rabouille et al., 2008; Zhu et al., 2011), where historical hypoxia in-
duced by natural climate conditions and circulation has been exacerbat-
ed by human nutrient input (Liu et al., in this issue; Rabalais et al., 2010;
Zillén et al., 2008). The relative importance of natural and human
(nutrient) drivers and efficacy of nutrient legislation have been under
debate in recent years (e.g., Bianchi et al., 2008). For example, shrinking
of hypoxic areas in the Black Sea appears to have resulted from reduc-
tions in human agricultural nutrient inputs, though the extent of the
human impacts on this ecosystem is still not clear (Mee et al., 2005).
In addition, as indicated above, the balance between N, P and Si is
being modified by many factors that affect coastal production, both
qualitatively and quantitatively (Ragueneau et al., 2005). CO2-driven
changes inwarming, winds, upwelling, and precipitationwill inevitablyPlease cite this article as: Levin, L.A., et al., Comparative biogeochemistry–e
Syst. (2014), http://dx.doi.org/10.1016/j.jmarsys.2014.04.016influence both the intensity and areal cover of hypoxia in many dead
zones (Giani et al., 2012; Rabalais et al., 2010, 2014).
3. Comparisons across continental margins
To gain a broader sense of how shelf systems are responding to cli-
matic forcing and direct human activities we have compared multiple
physical and biogeochemical observations collected at geographically
contrasting locations (Fig. 3, Table 2). Consistent with the global
warming trend, multiple margins (the Cariaco Basin, East China Sea,
North Adriatic Sea, and North Sea) have shown increasing temperatures
over the last four decades (slope = ~0.03 °C yr−1; p b 0.01); in the
San Francisco Bay (slope = −0.029 °C yr−1; p = 0.07) a
cooling trendhas been detected. (Formore detail on SST trends see Sup-
plementary material A and Djakovac et al., this issue.) The cooling trend
observed in San Francisco Bay is attributed to an increase in upwelling
intensity across the entire California Current system resulting from in-
creasing northerly wind stress along the western coast of the US
(Chavez et al., 2011). The warming trend in the Cariaco Basin, in turn,
is the result of theweakening of the TradeWinds, and thus of upwelling
intensity, along the southern Caribbean Sea (Astor et al., 2013; Taylor
et al., 2012).
No significant trends in sea surface salinity (SSS) are observed at the
Cariaco Basin or the North Sea. SSS in the Bohai Sea, however, shows a
positive trend (0.0632 yr−1) (Fig. 3b). The increasing salinity of the
Bohai Sea is thought to be caused by decreasing freshwater discharge
from the Yellow River (Fig. 3d).
The load of dissolved inorganic nitrogen (DIN) in Changjiang (aka
the Yangtze River), which empties into the East China Sea, has increased
by over two-fold (Liu et al., in this issue) between 1970 and 2002
(Fig. 3c), while this river's freshwater discharge has only increased
slightly (Fig. 3d). This suggests that rising DIN concentrations in the
Changjiang River ismainly due to the intensive use of chemical fertilizer
(Yan et al., 2010). By contrast, and due to EU policy change, the DIN load
discharged to the North Sea has decreased by 50% since 1977. Dissolved
inorganic phosphorus (DIP) shows a similar decreasing trend at this
location (Pätsch and Lenhart, 2011).
The sea surface chlorophyll-a concentrations in SF Bay have
increased in the last two decades (Fig. 3e), which is consistent with
the observed decreasing trend in SST. Simultaneously, however,
chlorophyll-a in the Cariaco Basin shows a decreasing trend since the
late 90s due toweaker upwelling events and stronger thermal stratifica-
tion (Taylor et al., 2012). Themonthlymean sea surface chlorophyll-a in
the East China Sea derived from ocean color products by NASA's Sea-
viewingWide Field-of-view Sensor (SeaWiFS) also exhibits a significant
increasing trend since 1998, which is thought to result from increased
DIN loads from the Changjiang River (Fig. 3c) (Liu et al., in this issue).
In response to increasing phytoplankton growth, bottomwater oxy-
gen saturation in SF Bay and the East China Sea has shown a significant
decline (Fig. 3f). Oxygen saturation shows aweak decline in the upper 3
m at the Cariaco Station (Fig. 3f), probably due to warming and possibly
to lower oxygen production by phytoplaknton (Fig. 3e).
Different margins show markedly different responses to local
stressors and to global-scale change. Variations in availability and
temporal coverage of different environmental parameters highlight
the need for comprehensive and sustained time-series observations
on continental margins. These are required in order to understand eco-
system responses to natural, CO2 climate-driven and direct human
perturbations.
4. Ecosystem responses to biogeochemical change on
continental margins
Some of the most apparent environmental and ecosystem conse-
quences due to the common climate and human stressors discussed in
this special issue are summarized in Table 1 and discussed below.cosystem–human interactions on dynamic continentalmargins, J. Mar.
Table 1
Environmental drivers and ecosystem responses on continental margins: Case studies.
Consequences
& regional
responses
(supplementsa)
Drivers of environmental change on continental margins from regional to global scale Actions taken
Land use
change
Damming, diking,
water diversion
Alien
species
Anthropogenic
nutrients &
pollutants
Energy &
mineral
extractions
from the sea
Overfishing Changes in
water cycle
Rising sea
level
Warming Climate change &
oscillation
General
consequences
Changes
in soil
qual. &
erosion in
watershed
Sed. retention,
decr. runoff
Change in
ecosystem
structure
Eutrophication,
change in nutrient
ratios & plankton
community, HAB,
hypoxia
Change in
seascape &
marine
environments
Decr. fish
stock, trophic
cascades
Extreme
weather,
flooding,
drought
Lowland
flooding,
salt water
intrusion
Incr. stratification,
drop in O2, incr.
vulnerability
Change in ocean
circulation,
upwelling
American margins
Cariaco Basin (B1) Collapse of
Spanish sardine
(Sardinella
aurita)
Freshening of
surface waters
due to higher
regional
precip.
N1 °C incr. since
1995
Decr. upwelling,
PP and phytoplankton
biomass; incr.
N-fix.,
change in ecosystem
structure; incr. zooplank-
ton biomass
Chesapeake
Bay (B2)
Degrading
water
qual.
& clarity
Blocked
migratory
pathways for
anadromous fish
Decreased
oyster
populations
and
increased
piscivory
Seasonal hypoxia,
decline of SAV, fish
advisories
Extirpation of
sturgeon,
collapse
of oyster fishery
Salinity drop
following
tropical storm
Agnes
Rate of sea
level rise much
higher
than average
Change in water
exchange rate
Acts for
reducing
nutrients &
restoring SAV,
oysters; re-
moving
blockages to
fish
San Francisco
Bay (B3)
Decreased
sediment supply,
shrinking
mudflats, incr.
salinity
Decreased
phytopl. PP
due
to Asian
clams
Degrading water
quality
Drought and
water diversion
trigger invasion
Change in
bio-community
1972 Clean
Water
Act
Asian margins
Bohai Sea (B4) Changes
in tidal
regime
Massive drop in
water discharge
and sediment
load, fishery
collapse in 1990s
High N, low P and Si,
decr. diatom/
dinoflagellate ratio
Decr. fish
biomass;
dominant fish
species changed
from bottom to
pelagic fish
0.011 °C per year
increase during the
1960s–1990s
Artificially
controlled
water
discharge in
the
Yellow River
European margins
Mediterranean— N.
Adriatic Sea (B5)
Reduced minor
river flow
Introduction
of alien
species
P decrease, N/P
increase, anoxic
events (1970s–1980s),
loss of macrobenthos;
chl decrease, trend
reversed in the last two
decades
Loss of demersal
fish, small
pelagic
fish and top
predators
Drought period
in 2000s,
salinity incr.
Incr. sea surface
temperature
Changes in
bio-community, incr.
salinity of southern
water inflow
Mandates of
reduction in P
loading
North Sea (B6) Altered mudflats Massive coastal
environment
deterioration in 1980s
Massive wind
farming
Temporally and
regionally faster
than global mean,
provoked
ecosystem shift
NAO state determines
circulation mode and
nutrient inventories
EU-wide
mitigation,
Marine
Strategy
Framework
Directive
Increase in Na. Whether this is due to increased N fixation is being explored.
a Note: More descriptions and references about the case studies are presented in electronic supplements listed under each case heading. SAV: Submerged Aquatic Vegetation; HAB: Harmful Algal Blooms; PP: Primary Production
6
L.A
.Levin
etal./JournalofM
arine
System
s
xxx
(2014)
xxx–xxx
Please
cite
this
article
as:Levin,L.A
.,etal.,Com
parative
biogeochem
istry
–ecosystem
–hum
an
interactions
on
dynam
ic
continentalm
argins,J.M
ar.
Syst.(2014),http://dx.doi.org/10.1016/j.jm
arsys.2014.04.016
a) b)
c) d)
e) f)
Fig. 3. Time series of sea surface temperature (SST) (a), sea surface salinity (SSS) (b), nutrient loads (c), riverine discharge (d), chlorophyll-a (e), and saturation of dissolved oxygen
(f) from the Cariaco Basin and San Francisco Bay (SF Bay) in the Americas, the East China Sea (ECS) and Bohai Sea (BH) in Asia, and the North Sea (NS) in Europe (See Fig. 1 for location
of time-series stations). SST time series include values obtained from satellite remote sensing monthly composites (lines without symbols) from NOAA's National Climatic Data Center
(See Supplementary material A), and in situ observations (lines with symbols). Statistically significant regression (p b 0.1) results are shown as solid straight lines; insignificant ones
are shown as dashed lines (see text).
7L.A. Levin et al. / Journal of Marine Systems xxx (2014) xxx–xxxHuman alteration of hydrological processes such as damming and
water diversion (B3, B4), drives very noticeable physical changes in
margins causing loss of habitats due to coastal erosion or reduced
river discharge (e.g., Liu, in this issue). When combined with climate
effects, resulting salinity increases can lead to species invasions that
reshape coastal ecosystems. Following massive water diversion and
drought in San Francisco Bay, an invasion by Asian clams altered the
timing andmagnitude of phytoplankton availability, with cascading tro-
phic consequences (Cloern and Jassby, 2012, B3). In the Bay of Brest,Table 2
The temporal trends of the environmental variables presented in Fig. 3. All trends are statistica
regressions see Supplementary material A.)
Site SST (°C yr−1) SSS (yr−1) Q (km3 yr−1) DIN (K
Bohai Sea 0.0022 0.0632 −0.75a
Cariaco Basin 0.0895 −0.0097
East China Sea 0.0282 3.34 26.1
North Sea 0.0376b 0.0007 −7.44 −12.1
SF Bay −0.0290c 0.0427
a Water discharge of the Yellow River that empties into the Bohai Sea.
b The mean temperature of the top 10 m in the North Sea in winter months (DJF).
c The bottom temperature of the USGS Station 18 in the San Francisco Bay.
Please cite this article as: Levin, L.A., et al., Comparative biogeochemistry–e
Syst. (2014), http://dx.doi.org/10.1016/j.jmarsys.2014.04.016introduction of an invasive limpet changed the seasonality of primary
production, which in turn has changed benthic biodiversity and
completely modified the benthic–pelagic coupling over a 30-year
period (Grall and Chauvaud, 2002).
In a broad sense, land use change alters how rainfall interacts with
the landscape. Some land-use activities result in increased soil degrada-
tion and erosion (i.e., agriculture, mining), and in eutrophication of
rivers and continentalmargins through the use of fertilizers. The coastal
zone's high primary productivity and the abundant filter feeders (e.g.,lly significant except those shown in italics. (For more detailed information on the linear
t yr−1) DIP (Kt yr−1) Chl (mg m−3 yr−1) O2 saturation (% yr−1)
−0.0462 −0.105
0.0135 −0.536
−2.3
0.131 −0.290c
cosystem–human interactions on dynamic continentalmargins, J. Mar.
2.5 3.0 3.5 4.0 4.5 5.0
2.6
2.8
3.0
3.2
3.4
3.6
3.8
4.0
4.2
4.4
Total N loadings (log10 kg km-2 surface year-1)
La
nd
in
gs
 fi
sh
+ 
m
ob
ile
 in
ve
rte
br
at
es
(lo
g 1
0 
kg
 k
m
-
2  
su
rfa
ce
 a
re
a 
ye
ar
-
1 ) <2% hypoxia4-19% hypoxia
22-31% hypoxia
40-77% hypoxia
Fig. 4. The relationship between nitrogen loading and fisheries landings as a function of
hypoxic area for mobile species in estuaries and semi-enclosed seas.
Modified from Breitburg et al., 2009b.
8 L.A. Levin et al. / Journal of Marine Systems xxx (2014) xxx–xxxLotze et al., 2006) offset land-derived nutrient inputs to some extent,
but are tested by eutrophication and overfishing (B2). Moreover, rising
sea levels will lead to flooding of low-lying coastal regions like India and
Bangladesh, movement of seawater farther up estuaries, and intrusion
of seawater into groundwater reservoirs.
Eutrophication is among the most widespread of coastal insults
(Table 1; B2, B3, B4, B5, B6), but the outcomes, which include productiv-
ity enhancement and hypoxia, can be complex. For example, several
cross-system comparisons indicate that increased N enhances total
landings of fish and mobile shellfish even in systems with hypoxia
(Fig. 4), although individual speciesmay decline and the overall compo-
sition of the catch can be affected (Breitburg et al., 2009b; Nixon and
Buckley, 2002). On the downside, hypoxia – an endocrine disrupter in
fish that experience chronic exposure (Thomas et al., 2006) – can
favor gelatinous plankton and some bivalves (Breitburg et al., 2003)
and create and eliminate shallow water refuges for small and juvenile
fishes (Breitburg et al., 2009a).
Reversal of eutrophication trends have been observed in some areas
such as the Danish straits (Carstensen et al., 2006), the Scheldt Estuary
(Soetaert et al., 2006) and other continental European rivers discharging
into the North Sea (Emeis et al., this volume), the openNorthern Adriatic
(Giani et al., 2012;Mozetič et al., 2012; Solidoro et al., 2009), and theNW
Black Sea (McQuatter-Gollop et al., 2009). In some instances P reduction
has been considered to be a primary driver of these changes. In the areas
subject to oligotrophication, overfishingmayact synergistically to dimin-
ish the trophic chain and reduce seafood resources (B5). However, along
the Danish and Finnish coasts, dissolved oxygen in bottom waters con-
tinues to drop despite efforts to reduce nutrient discharge (Carstensen
et al., 2014). In the Baltic Sea, which hosts nearly 20% of theworld's iden-
tified coastal hypoxic sites, climate and nutrient drivers interact with re-
gional circulation patterns and wastewater treatment technologies to
produce a mosaic of faunal responses (Conley et al., 2011).
While eutrophication-induced hypoxia is spreading, warming also
causes the ocean to lose oxygen due to the synergistic effect of reduced
oxygen solubility and enhancedwater column stratification (Bopp et al.,
2002). This has been termed deoxygenation and contributes to global
expansion of oxygen minimum zones (Stramma et al., 2010). Recent
model results demonstrate the extreme sensitivity of the volume
of suboxic water in the open ocean to changing climate conditions
(Deutsch et al., 2011). Biological analyses suggest that equator-ward
species boundaries are highly sensitive to changes in ocean temperature
and oxygen content. Models predict a decline in metabolic scope of
species (energy available for maintenance and reproduction) and func-
tional habitat loss.Please cite this article as: Levin, L.A., et al., Comparative biogeochemistry–e
Syst. (2014), http://dx.doi.org/10.1016/j.jmarsys.2014.04.016On margins both eutrophication and intensified upwelling typically
increase production while drawing down oxygen and creating hypoxia
at deeper water levels. Animal avoidance of hypoxia acts to aggregate
species around or above hypoxic zones, and leads to habitat compres-
sion, both in estuarine settings and in open-ocean oxygen minimum
zones (OMZs). The resulting aggregations are susceptible to overfishing
(Breitburg et al., 2009b; Craig, 2012), but high catches may mask the
consequences of ecosystem stress,making detection of habitat degrada-
tion difficult (Breitburg et al., 2009b). Such conditions also induce
shoaling of the zooplankton biomass layer at the thermocline (upper
oxycline boundary) and concentration of midwater biomass in a layer
at the lower oxycline (Wishner et al., 2013). As oxygen declines and
oxygen minima shoal in both the Atlantic and Pacific, large billfish are
now found at shallower depths and are increasingly susceptible to
overfishing (Prince and Goodyear, 2006; Prince et al., 2010; Stramma
et al., 2011).
Upwelling margins, which host key world fisheries, exhibit strong
vertical gradients in temperature, oxygen and pH associated with
oxygen minimum zones (Paulmier et al., 2011). Across these gradients
bathyal benthic assemblages reveal shifts in diversity, body size, zona-
tion, carbon processing, bioturbation, colonization and resilience (Gilly
et al., 2013; Levin, 2003; Levin et al., 2009, 2013). Intensified upwelling
is predicted to result in changes in biodiversity and ecosystem function-
ing associated with the expansion of OMZs (Gilly et al., 2013; Stramma
et al., 2010). Recent onset of seasonal hypoxia on the Oregon inner shelf
now causes summer die-offs of fish and invertebrates (Grantham et al.,
2004). Responses to intensified upwelling winds and increased stratifi-
cation can also vary regionally. For example, comparative analyses of
the California and Canary systems reveal substantial differences in the
responses of biological production and air–sea CO2 fluxes to upwelling
intensification in these two systems (Lachkar and Gruber, 2013).
These differences have been attributed to various drivers such as the
contrasting shelf topography, eddy activity, coastal water residence
times and basin-scale forcing in the two regions (Marchesiello and
Estrade, 2009; Lachkar and Gruber, 2013). These differences also affect
the vulnerability of these ecosystems to global anthropogenic perturba-
tions such as ocean acidification (Lachkar, 2014). Other upwelling
regions have received less attention and could exhibit additional
(or alternative) response mechanisms.
CO2-induced climate change is the predominant forcing on the eco-
system of the polar margins (B8). Warming of the Arctic is taking place
two to three times faster than global rates (Trenberth et al., 2007); as a
result sea-ice cover has been decreasing at a rate of N10% per decade
with ice-free summers expected in a few decades. Arctic ecosystems
are increasingly being challenged by tipping elements (Duarte et al.,
2012; Naam, 2012; Wassmann and Lenton, 2012). In the future
Norway may experience decreased primary productivity, while Russia
will show increased productivity. Nowhere will adaptation be a more
critical element of sustainability than in the Arctic, because the Arctic
shelves have inordinate importance in feeding the world population
(see B8 for more details).
Among the many effects of rising atmospheric CO2, the significant
decrease of ocean pH (ocean acidification) and shift in seawater carbon-
ate chemistry (Doney et al., 2009) may elicit some of the most econom-
ically significant responses frommargin ecosystems. Acidification alters
seawater chemical speciation, most notably the lowering of calcium
carbonate saturation states, which impacts shell-formingmarine organ-
isms from plankton to benthic molluscs, echinoderms, and corals, all of
which are abundant in continental margins. Ocean acidification is exac-
erbated in the coastal zone by increased land-derived nutrient inputs,
which enhance, in turn, productivity of organic matter and therefore
respiration and release of CO2 (e.g., Borges and Gypens, 2010; Cai
et al., 2011). A serious drop of aragonite saturation state has occurred
in some coastal seas, such as the North Yellow Sea, threatening the
aquaculture of shellfish (e.g., Zhai et al., 2013; 2014). Coral reef ecosys-
tems, which provide key fisheries, critical shoreline protection andcosystem–human interactions on dynamic continentalmargins, J. Mar.
9L.A. Levin et al. / Journal of Marine Systems xxx (2014) xxx–xxxhabitats for a large number of species, are highly susceptible (Andersson
and Gledhill, 2013). Due to ocean acidification, rates of coral calcifica-
tion may decrease, whereas rates of bioerosion and carbonate dissolu-
tion may increase, resulting in a transition from net accretion to net
erosion. Impairment of the calcifying capacity of marine organisms is
therefore expected to have negative impacts on coral reefs and other
calcifiers (e.g., bivalves) and on the ecosystem services they provide.
The complexity of ocean biogeochemical–ecosystem interactions on
margins means that some drivers will create responses that generate
feedback — further altering a system. One example occurs when
acidification-induced undersaturation of carbonate minerals adversely
affects shell growth and settlement success of bivalves and coral polyps
building reefs; this is predicted to ultimately reduce oyster, mussel and
clam populations and coral reef building. Locally, the presence of large
oyster populations buffers increasing CO2 and decreasing pH through
shell dissolution and alkalinity increase. So lowered pH ultimately
reduces local buffering capacity, leading to further reductions in pH
when the mineral buffer is exhausted. In addition, mass removal of
shellfish (by harvest) could contribute to a deficit in the carbonate
balance, as the shells form a dissolution buffer needed bymany animals
to survive (Waldbusser et al., 2013). Populationsmay be reduced to the
point of unsustainability leading to ‘recruitment overfishing’.
On some margins high-frequency climate oscillations are the domi-
nant driver of biogeochemical variation and consequently, ecosystem
structure. In the Bay of Calvi in the Ligurian Sea of the NWMediterra-
nean (Goffart et al., submitted for publication) the biogeochemical con-
dition is very oligotrophic during mild winters and mesotrophic during
moderate winters (B7). During severe winters, the Bay sustains a “high
nutrient–low chlorophyll” situation. With little human disturbances
this Bay may serve as the baseline, against which ecosystem changes
in the Mediterranean due to direct human impacts can be detected
(see B7 for more details). In the East Pacific Ocean, interannual varia-
tions linked to ENSO induce low productivity (well oxygenated) El
Niño and high productivity (low oxygen) La Niña conditions that affect
fisheries production in the Humboldt and California and Benguela
current ecosystems (Arntz et al., 2006).
5. Using time series to distinguish drivers of change
Hydrographic and ecological time series have provided data critical to
evaluating and interpreting change on margins. Koslow and Couture
(2013) have referred to ecological time series as the Cinderella (hard
working drudges) at the climate change ball. Beyond this they may pro-
vide the “Anthropocene's canary in a coal mine” for many other forms of
human disturbance. Below we address the approaches, benefits and
limitations of time series in attribution of change on margins.
Several multi-decadal oceanographic time series measurements
from a variety of coastal and pelagic systems have shown how lower
and intermediate trophic levels, and biogeochemical cycling react to cli-
mate oscillations regionally and globally (Black et al., 2011; Chavez
et al., 2003; Church et al., 2013) (Table 1). Multi-decadal time series of
phytoplankton have been generated for many regions including San
Francisco Bay (Cloern and Jassby, 2012), Chesapeake Bay (Lee et al.,
2013), Narragansett Bay (Borkman and Smayda, 2009), the Cariaco
Basin (Chavez et al., 2011; Muller-Karger et al., 2013), the North Sea
(Wiltshire et al., 2008) and areas of the Mediterranean Sea (e.g.
Goffart et al., 2002, submitted for publication; Ninčević Gladan et al.,
2010; Zingone et al., 2010) including the Northern Adriatic (Bernardi
Aubry et al., 2012; Cabrini et al., 2012; Marić et al., 2012; Mozetič
et al., 2012) and Gulf of Naples (Ribera d'Alcalà et al., 2004). There are
also Arctic time series in the Bering, Chukchi, and Barents Sea. Most of
these reveal oscillations associated with climate variability (Borkman
et al., 2009;Harrison et al., 2010). Indeed, such long-termocean time se-
ries have been fundamental for expanding our knowledge about the
sensitivity of marine biodiversity, ecosystems and biogeochemistry to
environmental change (Church et al., 2013; Koslow and Couture,Please cite this article as: Levin, L.A., et al., Comparative biogeochemistry–e
Syst. (2014), http://dx.doi.org/10.1016/j.jmarsys.2014.04.0162013). However, moving forward, an international network of time se-
ries is needed to evaluate regional linkages and interpret global changes.
There are some major gaps in time series monitoring. Whereas
models of nutrient fluxes from watersheds abound, monitoring data to
verify them do not. In the developing world, the scarcity of monitoring
data adequate to characterize riverine nutrient flows has impeded our
understanding of the relationships with human activities. Research
and development of monitoring in these regions, should be made a
priority, andwould improve ourmanagement of coastal waters. It is im-
portant to add that not only the N cycle should be monitored, but also
the changes in nutrient ratios delivered by rivers. In particular the Si:N
and Si:P ratios should be closely monitored as potential early warning
indicators of disturbances (Billen and Garnier, 2007). Indeed, they are
often decreasing due to excessive N and P inputs and decreasing Si
inputs due to damming (Humborg et al., 1997), with the proliferation
of invasive species (Ragueneau et al., 2005) causing replacement of dia-
toms by dinoflagellates. South East Asia, where anthropogenic factors
leading to decreasing Si:N and Si:P ratios combine, should be especially
targeted for monitoring (Ragueneau et al., 2006).
Modern time series gain added valuewhen used in conjunctionwith
paleoceanographic studies (Black et al., 2011) and models (see Church
et al., 2013); together these tools allow researchers to discern natural
sources of environmental change from variations induced by climate
change (warming, extreme flooding from river input or snow melt, or
heatwaves) and direct human drivers such as eutrophication, damming
and fishing (Koslow and Couture, 2013). In some margin settings sub-
ject to long bouts of habitation and industrialization (e.g., Chesapeake
Bay, the coastal SE North Sea, Northern Adriatic), natural variability is
a small signal relative to the influence of humans. In others (e.g., upwell-
ing margins) natural variability produces an exceedingly strong signal
and irrefutably detecting CO2-driven climate change or anthropogenic
forcing is difficult.
Sediment and glacial ice core climate records often provide the long
temporal perspective needed to identify climate oscillations prior to
high anthropogenic CO2 (N280 ppm) conditions or resulting from
long-term changes in human population density and land use practices
(Cooper and Brush, 1993; Emeis et al., 2000; Yasuhara et al., 2012).
Some of these geological climate records are now complemented by
oceanographic and biogeochemical time series observations, thus pro-
viding valuable insights into the effects of anthropogenic perturbations
on the marine environment (see Black et al., 2011).
5.1. Time series and coastal management
The motivation underlying the establishment of ecological time
series varies. In California, CalCOFI was developed in the 1950s to
understand the boom and bust cycles of the sardine (Bograd et al.,
2003; Chavez et al., 2003). At its inception, the CalCOFI concept of mon-
itoring the entire ecosystem, now widely accepted in the context of
ecosystem-based management, was visionary and somewhat heretical.
In Chesapeake Bay, a long time series of young-of-year fish abundances
inMarylandwaterswas initiated in 1954 by the state fisheries agency to
aid management of several anadromous species (Durell and Weedon,
2011), a time series of jellyfish abundances was begun in 1960 by a
University of Maryland researcher in response to the ‘Jellyfish Nuisance
Act’ (Cargo and King, 1990), and bay-wide time series monitoring of
water quality parameters was begun in the 1980s with funding from
the States of Maryland and Virginia and the US EPA to aid management
efforts to improve water quality conditions (Boesch et al., 2001). Gov-
ernments of states bordering the western coasts of Europe (OSPAR)
and the Baltic Sea (HELCOM) initiated monitoring programs in the
1970s to protect the marine environment from all sources of pollution
through intergovernmental cooperation.
Although each time series is fixed in space and provides local infor-
mation, when data are combined across time series they can provide a
powerful synoptic understanding of the link between climate variabilitycosystem–human interactions on dynamic continentalmargins, J. Mar.
10 L.A. Levin et al. / Journal of Marine Systems xxx (2014) xxx–xxxand ocean biogeochemistry (Church et al., 2013). The ICES Phytoplank-
ton and Microbial Plankton Status Report 2009/2010 exemplifies this
for the North Atlantic (O'Brien et al., 2012). Records of sea ice cover
and tipping points in the Arctic provide another example (Carstensen
and Weydmann, 2012). Under optimal conditions, time series provide
data prior to catastrophe (e.g., fishery collapse) so that causes can be
discerned. It is important, however, to recognize the value of under-
standing regional differences and their forcing mechanisms.
5.2. Time series constraints
Spatially fixed time series may have limitations. Single-location
measurements typically do not reveal spatial expansions, contractions
or oscillations. They cannot recognize change due to relocation of organ-
isms or features,making it difficult in some cases to untangle spatial and
temporal change, although spatial comparisons can sometimes be used
as proxies of temporal change (e.g., Wishner et al., 2013). Satellite re-
mote sensing has typically been the tool of choice for extrapolating
fixed time series observations to broader spatial and temporal scales.
Some time-series stations (i.e., Hawaiian Ocean Time-series [HOT] and
the Bermuda Atlantic Time Series [BATS]) have been successful at
using autonomous samplers and sensors (e.g., gliders, drifting profilers)
for learning the regional significance of the measurements they collect.
These are especially important for hard-to-reach areas like the Arctic
and Antarctic, and can expand coverage for traditional time series in
other regions. Autonomous samplingplatforms, however, are expensive
to operate and thus are out of reach for time-series programs with lim-
ited resources. Another approach is to engage platforms of opportunity.
Industry with a presence on the ocean margins, such as offshore wind
and aquaculture, fishing, fossil fuel extraction and minerals, may have
a role to play in time series development in the future, and should be
broadly engaged to support monitoring efforts. Expansion of programs
like the World Ocean Council Smart Data/Smart Industries (http://
www.oceancouncil.org/site/smart_ocean.php) may be useful.
Time, funding and facilities constraints often limit time series to the
upper water column and basic hydrographic parameters. To link these
to key resource needs and sustainable management – including aqua-
culture, fisheries, energy and minerals – it will be necessary to incorpo-
rate the seafloor and its organisms into time-seriesmonitoring. Benthos
monitoring can also provide critical information about biogeochemical
feedbacks from the sea floor, processes often not included in large-
scale climate or ecosystem models.
Most margin time series are not of sufficient duration to detect
variation outside normal statistical variability (especially given
decadal-scale cycles emerging in the atmosphere-surface ocean sys-
tem). Often shifts and change are misattributed due to lack of knowl-
edge about natural variability and its sources. Paleoceanographic
records in ice cores, sediment cores or tree rings allow us to extend
understanding of margin processes back in time, prior to the estab-
lishment of in situ observations (Gooday et al., 2009). Innovative
analyses of scales, teeth, otoliths and ichnofacies may allow use of
such records to reconstruct complex changes in exposure histories
and food web dynamics (Gooday et al., 2009; Morat et al., 2014). Re-
cent development of geochemical proxies for detection of fish expo-
sure to hypoxia offers the promise of identifying past and present
trends in oxygen concentration using otoliths (Limburg et al., 2011,
2014); fish scales and other skeletal elements may also prove useful,
but require testing. Chronosequences from long-lived calcifying or-
ganisms (e.g., coldwater corals or bivalves) can provide excellent
time series of temperature or pH as a basis for chronometric analyses
similar to dendrochronology (e.g., Black et al., 2008; Chauvaud et al.,
2005, 2012). Novel functional gene microarrays may be used to eval-
uate the diversity and composition of the denitrifying microbial
community in hypoxic settings like OMZs, allowing us to better un-
derstand how microbial metabolism can impact the global climate
through the production of N2O, a bi-product of denitrification and aPlease cite this article as: Levin, L.A., et al., Comparative biogeochemistry–e
Syst. (2014), http://dx.doi.org/10.1016/j.jmarsys.2014.04.016powerful greenhouse gas (Jayakumar et al., 2013). We need to fur-
ther develop proxy variables for environmental reconstructions, ex-
pand the data bases for regional-scale hindcasts, and strive to detect
and interpret interannual variability from low-resolution archives.
While valuable in having fixed measurements, time series may also
need to have an adaptive observation component focused on (a) identi-
fying changes and their underlying causes and (b) monitoring parame-
ters tied to the ecosystem services we care about, in order to directly
address policy concerns for effective management of these services.
There is often a gap between what we can realistically measure, and
what we want to achieve. This highlights the importance of research
on basic processes and mechanisms that will identify indicators of
change and incorporate process-based knowledge into our models.
Often the early warning of degradation will come from land. For exam-
ple, agricultural inputs, nutrient concentrations, N:P, Si:P, Si:N ratios or
multiple nutrient concentration data together could be key indicators
(Billen and Garnier, 2007).
The burgeoning number of time series and rising volumes of data
highlight a need to engage more scientists in the analysis phase of
time series research. There is also a challenge of maintaining continuity
in the face of severe funding shortages; scientistsmust advocate for con-
tinuation of monitoring programs. Key to the successful continuation of
time series is concise presentation of insight gained and raising the
awareness of the public and policy makers of their value. It is here
that social scientists can help natural scientists learn how to make a
strong case without loss of integrity and accountability.
6. The continental margin in the Anthropocene: the convergence of
biogeochemistry, ecosystems and society
To be effective, economic models must be able to weigh the costs of
the unwanted impacts of stressors and forcings on ecosystem services
discussed above and associated consequences against gains for society,
and to attribute change to specific and controllable drivers. To date sci-
entists have failed to convey the message of the overriding importance
and societal consequences of CO2 emissions (as well as other green-
house gases) in the context of global warming. Investment in collabora-
tion efforts between social and natural scientists, development of
outreach and public communication skills, and advocacy about the im-
portance of individual actions are required tomanagemargins effective-
ly (Pidgeon and Fischhoff, 2011). A need to combine scientific with
traditional and local ecological knowledge, especially in settings such
as the Arctic, further argues for key social–natural science integration.
There is growing need for modeling of coupled human (social)–
biogeochemical systems on margins. A pioneering example can be
found for the surfclam fishery on the Middle Atlantic Bight (MAB) con-
tinental shelf (McCay et al., 2011). This million-dollar fishery has been
managed since the 1990s with transferable quotas, one of the first in
the US to do so. In recent decades the population has shifted to the
north and overall abundance has declined (Weinberg, 2005). Simula-
tions of surfclam growth that use 50-year hindcasts of bottom temper-
ature obtained froman implementation of the Regional OceanModeling
System for the MAB (Kang and Curchitser, 2013) show that episodic
warming events increase surfclam mortality and limit animal size in
the southern portion of its range (Narváez et al., this volume). The
resulting northward movement of the stock has negative economic
consequences for the fishing fleet and processing plants. These studies
point to a key role for natural scientists in assessment of the socio-
economic consequences of climate change (McCay et al., 2011).
6.1. Disasters can sometimes serve as catalysts for action
In the United States, several disaster events have caught the atten-
tion of the scientific community and policy makers, and have resulted
in the development of large-scale monitoring efforts that seek to mech-
anistically understand these events and mitigate their impacts bycosystem–human interactions on dynamic continentalmargins, J. Mar.
11L.A. Levin et al. / Journal of Marine Systems xxx (2014) xxx–xxximproving our predicting capabilities. One example is the unexpected
failure of the oyster aquaculture fishery on the US Pacific coast due to
upwelling of carbonate-undersaturated waters (Barton et al., 2012);
this stimulated state-sponsored research programs on ocean acidifica-
tion (Adelsman and Binder, 2012). Highly destructive Superstorm
Sandy stimulated sea level rise preparedness and massive fish kills
resulting from hurricane-induced release of hog waste and sewage in
North Carolina (Mallin et al., 1999), have engendered public support
for altered agricultural practices and backup treatment plants. These
types of events are not one-time occurrences, but are likely to become
more frequent. For example, low bottom-water aragonite saturation
values on shelves are expected to have negative effects on shellfish in
the Yellow Sea (Zhai et al., 2013; 2014) and off California (Gruber
et al., 2012). The costs required for building community, industry and
ecosystem resilience are now being weighed against the massive costs
of disaster damage and disaster relief.
While continued and expanded time series measurements are es-
sential to monitor status and trends, scientists often know enough to
make strong policy recommendations regarding CO2, nutrients and
human activities. In many instances adaptation to change is required
and distinguishing among drivers is not essential for policy decisions.
Whether reduced sediment inputs to the coastal zone result from dam-
ming or from drought, it will still be necessary to prepare for climate-
related sea level rise and associated consequences of limited land-
building and net loss of coastal wetlands. For anadromous fishes, loss
of freshwater inputs from damming versus drought will have similar
consequences, aswill loss of river–sea connectivity from eutrophication
induced hypoxia versus upwelling-induced deoxygenation. For coastal
shellfish, the corrosive effects of acidification may result from atmo-
spheric CO2 inputs, intensified upwelling, increased stratification,
anthropogenic nutrient loads, precipitation or sea ice melting. Acting
to reduce CO2 emissions and limit the now-inevitable rise in ocean tem-
peratures, acidification, and deoxygenation is critical.
There is growing consensus that direct anthropogenic stressors such
as overexploitation of natural resources (fisheries, mining), habitat de-
struction, land use/cover change, alteration of river catchments, coastal
construction, damming, species invasion and pollution will lower the
resilience of populations, species and ecosystems and make them less
able to cope with climate-induced stress (Bijma et al., 2013). For exam-
ple, reducing fishing mortality in exploited populations can also reduce
total mortality and be protective of declining populations, even where
part of that totalmortality was due to hypoxia, disease or habitat degra-
dation (Breitburg et al., 2009b). Thus policy, law and management of
margins must consider and address climate and direct human stressors
together. Relevant lessons can be drawn from regional, time series and
case studies where different combinations of stressors interact and
their trends have been tracked over time. Understanding system
connectivities, seeking indicators of regime change, and promoting
adaptation-oriented policy to build functional resilience are lessons
from the Arctic (Carmack et al., 2012) that apply well to most margin
ecosystems. The recently released IPCC AR5 report emphasizes the
overwhelming need for societal adaptation tomultiple stressors associ-
ated with climate change, especially in countries where poverty will
exacerbate the consequences (Field et al., IPCC, 2014).
The recognition of the importance of natural capital and ecosystem
services to national wealth has come slowly to some nations. In the
USA this is now evidenced by the generation of a National Ocean Policy
(2004; http://ioc-unesco.org/images/stories/LawoftheSea/Documents/
NationalOceanPolicy/nop.usa.pdf). To a large extent this policy
addresses the continental margins, where most of the key services and
commercial resources are provided. The Marine Strategy Framework
Directive (Directive 2008/56/EC, http://ec.europa.eu/environment/
water/marine/ges.htm), adopted by the European Commission in
2008, marks an important milestone in the development of the EU's
marine environmental policy and is the first framework instrument
aimed expressly at protecting and preserving the marine environmentPlease cite this article as: Levin, L.A., et al., Comparative biogeochemistry–e
Syst. (2014), http://dx.doi.org/10.1016/j.jmarsys.2014.04.016with a holistic approach. In 2012 The EU launched its Blue Growth ini-
tiative (http://ec.europa.eu/maritimeaffairs/policy/blue_growth/) that
addresses three crucial components of sustainable development of ma-
rine resources: gathering and channelingmarine knowledge to improve
access to information about the continental margins of Europe, mari-
time spatial planning to aid management of offshore resources, and
integrated maritime surveillance. Other nations have national ocean
policies in review (e.g., South Africa) or in early stages of formulation
(Namibia).
6.2. Margin management strategies must move from mono- to multiple
stressor considerations
Most policies and research programs address only one or two
factors— nutrients, oxygen, ocean acidification, fishing pressure, disease,
or invasive species (e.g., Crain et al., 2008). We know that T, O2 and CO2
are changing simultaneously and interacting (Bijma et al., 2013). There is
need for scientific consensus on a) what the multistressor questions are
and b) how to approach the issues. How to integrate laboratory studies,
field observations, monitoring, modeling, and use of proxies to address
these questions remains a major challenge.
To incorporate natural variability and climate change into our deci-
sion making and management activitieswe need research that identifies,
quantifies and confronts management tradeoffs. Stakeholder identifica-
tion and finding equitable solutions is critical as every decision has
winners and losers. We must quantify the economic costs of nutrient
reduction for agriculture, fishers, and ecosystem services. Margin re-
searchers have only just begun to tackle the larger question of valuing
ecosystem services and biodiversity on the continental slope beyond
the shelf — this is especially critical in deep waters where resource
extraction activities (energy, minerals and deep-water fishing) are on
the rise (Jobstvogt et al., 2013; Levin and Dayton, 2009).
As both top predators and guardians of the planet we face immense
ocean policy challenges over the next 10–50 years. The mentality of
many nations is of a land-based society.Managing a fluid-connected en-
vironment is fundamentally different than managing land use where
discrete boundaries between impacted and more pristine areas can be
maintained. There is a spatial disconnect between farm policies and
their effects on the coastal ocean and our margins. Even international
climate negotiations (Conference of Parties) involve remarkably little
consideration of ocean processes, despite the large role the ocean
plays in regulating climate. The concepts underlying sustainability in
ocean margins must involve an educational thrust that starts early, as
well as strategies to communicate at national and international levels.
We need to better understand the process by which science is introduced
to policy, and target and fast track scientific approaches that meet those
needs. End-to-end efforts are needed thatfirst bring together the natural
and human component of socio-ecosystems; and then work with
stakeholders and policy makers towards finding and implementing
solutions.
This article focuses on the impacts of the 20th century;we recognize
that the 21st century may involve a different suite of primary stressors,
some of which are as yet unknown. The continental margins of the
future will undergo further changes as the system is continuously
perturbed. As human populations grow, needs for fresh water, energy,
space, and food will create new demands of the coastal ocean including
coastal aquaculture, wind farms,wave energy stations and desalinization
plants, intensified shipping activities, and seabed mineral exploration.
Holistic consideration of margins facing the confluence of human,
climate and natural stressors highlights the need to integrate science
with societal needs. Building on work of others (e.g., Islam and
Tanaka, 2004), we identify the need to:
• Formulate a clear understanding of the environmental, ecological and
economic value of margin ecosystems and how these vary under dif-
ferent climate regimes.cosystem–human interactions on dynamic continentalmargins, J. Mar.
12 L.A. Levin et al. / Journal of Marine Systems xxx (2014) xxx–xxx• Enact water quality management that recognizes land–ocean–
atmosphere exchanges controlled by climate and humans.
• Enact comprehensive monitoring to link policy-based changes in
drivers to ecosystem responses.
• Improve cooperation of stakeholders, regulators, scientists and civil
society.
• Scale and coordinate local, regional, national and international activi-
ties to maximize knowledge and promote modeling efforts.
• Protect key services via ecosystem-based management.
• Developmechanisms to translate scientific knowledge into regulation
and legislation, and the political realities needed to achieve action.
Ultimately, we will need to set priorities, accept tradeoffs and moti-
vate creative solutions. These goals are very much in line with the ap-
proach of the Future Earth Initiative to meet the grand challenge of
global sustainability (Reid et al., 2010). Interactions among social and
natural scientists are nascent, but a growing number of national and in-
ternational programs recognize their importance. Achieving sufficient
energy, water, food and healthy margin ecosystems is a tall order, but
a challenge that natural and social scientists must work together to
meet head on.
Acknowledgments
We are grateful for the hospitality of the National Institute of Ocean-
ography, Goa, India, which hosted the IMBIZO III. Support for the work-
shopwas providedby IMBER (a core project of IGBP), SCORand a host of
co-sponsors. We thank two anonymous reviewers for their comments
which have improved the manuscript. L. Levin's and D. Breitburg's at-
tendance was supported by the US Ocean Carbon Biogeochemistry pro-
gram and IMBER. Levin's research support is from NOAA — California
Sea Grant College Program Project # R/CC-04 and NSF OCE 0927445
and 1041062. Support for E. Hofmann was provided by NSF grant
GEO-0908939. Support for K.-K. Liu was provided by the Ministry of
Science and Technology (grant NSC 102-2611-M-008-002), Taiwan
and SCOR. C. Rabouille would like to thank Mermex/MISTRALS pro-
gramme for funding. M. Giani’s attendance was supported by the PER-
SEUS (Policy-oriented marine Environmental Research in the
SouthernEUropean Seas) FP7 Project n. 287600.
Appendix A. Supplementary data
Supplementary data to this article can be found online at http://dx.
doi.org/10.1016/j.jmarsys.2014.04.016.
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