Download Pacific Ocean observation programs_ Gaps in ecological time series

Marine Policy 51 (2015) 408–414
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Marine Policy
journal homepage: www.elsevier.com/locate/marpol
Pacific Ocean observation programs: Gaps in ecological time series
J. Anthony Koslow n, Jennifer Couture 1
Scripps Institution of Oceanography, 9500 Gilman Drive, University of California, SD, La Jolla, CA 92093-0218, USA
art ic l e i nf o
a b s t r a c t
Article history:
Received 27 May 2014
Received in revised form
25 August 2014
Accepted 1 September 2014
Available online 24 October 2014
How well do existing ocean observation programs monitor the oceans through space and time? A metaanalysis of ocean observation programs in the Pacific Ocean was carried out to determine where and
how key parameters defining the physics, chemistry, and biology of the oceans were measured. The
analysis indicates that although the chemistry and physics of the Pacific Ocean are reasonably well
monitored, ecological monitoring remains largely ad hoc, patchy, unsystematic, and inconsistent. The
California Cooperative Oceanic Fisheries Investigations (CalCOFI), for example, is the only Pacific Ocean
program in which the zooplankton and micronekton are resolved to species with consistent time series
of greater than 20 years duration. Several studies now indicate massive changes to nearshore,
mesopelagic and other fish communities of the southern California Current but available time series
do not allow these potential changes to be examined more widely. Firm commitment from the global
community to sustained, representative, quantitative marine observations at the species level is required
to adequately assess the ecological status of the oceans.
& 2014 Elsevier Ltd. All rights reserved.
Keywords:
Micronekton
Ocean observation programs
Pacific Ocean
Time series
Zooplankton
Ichthyoplankton
1. Introduction
Bishop Berkeley is reputed to have asked, “If a tree falls in the
forest and there is no one around to hear it, did it make a sound?”
However, if a fallen tree is encountered in the forest, one can be
confident that once it stood upright and even surmise from where
it fell. Photographs of a forest taken from the same vantage years
apart allow growth, death and other forms of change in the forest
to be evaluated, even without observations of each tree fall.
Observing and understanding change in the ocean present
greater challenges. How is it known if a species declines or
increases? Sub-surface ecological observations remain difficult
and costly and therefore relatively scarce. Isolated observations or
“snapshots” of local conditions, unlike photographs of the forest,
often prove to be of little value in assessing change, because the
ocean is a dynamic environment. The abundance of its ever-shifting,
patchily-distributed populations may vary daily, seasonally, interannually, and from decade to decade in relation to naturally varying
conditions, as well as in response to human influences. Isolated
observations may therefore be aliased and of little value in
evaluating change. The consistent systematic time series of observations that are required to evaluate change across this range of
time scales and to distinguish natural variability from secular
climate change must be maintained for a very long time, well
n
Corresponding author. Tel.: þ 1 858 534 7284.
E-mail address: [email protected] (J.A. Koslow).
1
Present address: Bren School of Environmental Science and Management,
University of California, SB, Santa Barbara, CA 93106-5131, USA.
http://dx.doi.org/10.1016/j.marpol.2014.09.003
0308-597X/& 2014 Elsevier Ltd. All rights reserved.
beyond the time scale of any single government's tenure in office or
scientist's career: a very long time, indeed, on the human scale. It is
no wonder that such time series are scarce.
Despite the inherent difficulties of achieving long-term ocean
time series, they are nonetheless essential, given that the oceans
are not at equilibrium, as once believed, but rather continuously
varying in response to a poorly-understood array of natural and
anthropogenic pressures. Multi-decadal ocean time series are a
sine qua non to distinguish natural variability from secular trends
induced by climate change and other anthropogenic stressors.
Ocean time series are therefore also fundamental to effective
ocean management, since without these, the need for management may be missed and the effectiveness of management
measures, such as instituting marine protected areas (MPAs),
cannot be evaluated.
The United Nations (UN) is conducting its first World Ocean
Assessment (WOA) to be completed in 2014, a process intended to
parallel the periodic reporting of the UN Intergovernmental Panel
on Climate Change. The need for a periodic WOA is clear, given the
large number of anthropogenic stressors to which the ocean
environment is subjected: overfishing, the impacts of marine
industries from fishing and mariculture to mining and energy
development, eutrophication due to nutrient runoff, pollution,
invasive species, coastal development, warming, acidification,
and deoxygenation. The impacts of these stressors are generally
poorly understood in isolation from each other, much less in
concert with the potential for synergistic interactions. Without
time series, it is impossible even to know that there is change in
marine ecosystems. And because there are a number of more or
J.A. Koslow, J. Couture / Marine Policy 51 (2015) 408–414
Fig. 1. The distribution of the 3525 Argo floats that currently profile the temperature and salinity of the world oceans from the surface to 2000 m depth.
Source: Argo web-site, http://www.argo.ucsd.edu/.
less distinct biogeographic provinces or large marine ecosystems
(LMEs) within the global ocean [41,30], a system of representative,
consistently sampled ocean observation programs is required to
achieve an effective global ocean assessment.
Recent decades have seen dramatic advances in observation
systems for the physics and chemistry of the global ocean, with further
improvements on the horizon, based on advances in sensor technology.
Satellites now provide global coverage of sea surface temperature,
altimetry, and chlorophyll a (chl), which is commonly used as an index
for phytoplankton abundance. The Argo float program, operational
since the early 2000s, today has approximately 3600 floats deployed to
sample ocean temperature and salinity to 2000 m depth (Fig. 1).
Dissolved oxygen measurements are currently being obtained from a
limited number of floats, with plans to add sensors to measure chl,
nutrients, and pH. The Argo program monitors the open ocean, and the
physical state of the coastal ocean is monitored by the Global Ocean
Observing System (GOOS) coastal program.
However, observing the physical state of the ocean is the lowhanging fruit. Measurements of temperature and salinity (and chl)
are well-standardized and can be readily and consistently measured to a high level of precision. On the other hand, as a former
GOOS director once observed, the critical lack of ecological ocean
time series remains an “embarrassing gap” more than 25 years
after GOOS was formed [2]. The only possible exception to this
gloomy overview is fishery time series. Fishery statistics based on
catch and effort have been maintained in parts of the world for on
the order of 100 years. However, fishery statistics are generally
limited to commercially-exploited species and are influenced by
changes in market conditions, technological change, and the
effects of over-exploitation itself; fishery-independent time series
are generally more limited in duration as well as in the number of
species and regions covered.
Several recent issues highlight the need for improved ecological
time series for the ocean. These involve ecological groups – gelatinous zooplankton and midwater fishes – that are immensely
important in pelagic ecosystems but that have been poorly monitored to date. As a result, potential changes in these groups remain
controversial and uncertain, although these groups may be responding to anthropogenic influences and changes in these groups could
have profound implications for global marine ecosystems.
The first issue is the uncertainty whether jellies are increasing
globally in response to overfishing, eutrophication, and deoxygenation, particularly in degraded coastal ecosystems. Blooms of
gelatinous plankton (jellyfishes and salps) have been widely
observed in recent years, with implications for marine industries,
including fisheries and power plants, and potentially signaling a
regime shift in the structure of marine food webs (reviewed in
Refs. [34,35,8,19]). However, lack of adequate time series has led a
number of leading experts to conclude that it is not possible at
present to distinguish natural cycles from a secular increase in
409
their abundance [11]. Indeed, there are no existing quantitative
time series in the Pacific Ocean for gelatinous zooplankton [11].
A second issue is the potential impact of deoxygenation on
mesopelagic fishes in regions with oxygen minimum zones.
Koslow et al. (2011) [25] reported a 63% decline in a broad
assemblage of mesopelagic fishes in the California Current (CC),
apparently linked to declining oxygen concentrations at midwater
depths (200–400 m). Declining oxygen is now reported over much
of the global ocean [20] apparently a consequence of global
climate change, and global climate models predict continued
deoxygenation of the deep ocean as increased warming and
stratification of the upper mixed layer leads to decreased ventilation of the deep ocean [39,40]. Mesopelagic fishes are dominant
zooplankton consumers in the global oceans; as such, they are key
vectors for the transfer of energy to higher trophic levels and for
the sequestration of carbon into the deep ocean [13,22]. A
significant decline in their abundance could have profound consequences for global marine food webs and biogeochemistry.
However, at this time there do not appear to be time series to
examine changes in the midwater micronekton in other regions
with well-developed oxygen minimum zones [24].
This study examines the availability of ecological time series for
pelagic ecosystems in the Pacific Ocean based on a meta-analysis of
ocean observation programs. The study concludes with a modest
proposal to enhance ecological time series for the global ocean.
2. Methods
This study comprises a meta-analysis of sustained Pacific Ocean
observation programs leading to ocean time series based on
parameters measured consistently over time in the same geographic region. Short-term projects, surveys, cruises, and expeditions were therefore not considered. The analysis is also restricted
to non-proprietary programs and data sets, so military or industrial
data sets to which there is no public access were not considered,
along with geological data sets (for example, seafloor mapping) that
are not, properly speaking, time series observations. For each
program, we noted the start and end dates of the program,
geographic location (latitude and longitude) of routine data collection, sampling frequency, sampling months and the physical,
chemical and biological variables measured, although the focus of
the study is on biological observations and time series. Information
was obtained from web sites and the scientific literature.
For each variable, sampling methodology and depth range of
sampling were noted. Methodology included the oceanographic
instrument used for collection at sea (including the net types and
mesh sizes) and the method of analysis. For programs with
biological time series, the taxonomic resolution or grouping was
noted. For zooplankton samples in particular, there is a variety of
methods for sample analysis: bulk biomass measurement (displacement volume, settled volume, or wet or dry mass), analysis to
functional groups, or species-level enumeration. For surveys of
fishes, sampling methods range from sampling with a variety of
nets, ichthyoplankton sampling (sampling the fishes during the
planktonic phase in their early life history), and acoustic-trawl
surveys. The availability of long (Z 20 years) and short (o 20
years) time series for zooplankton (both bulk biomass and specieslevel resolution) and micronekton were mapped using online
mapping software, HamsterMap (http://www.hamstermap.com).
3. Results
Pacific Ocean biological observation programs were found in
Australia, Canada, Chile, Japan, Korea, Russia, Mexico, Panama, Peru,
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J.A. Koslow, J. Couture / Marine Policy 51 (2015) 408–414
Fig. 2. Locations of current Pacific Ocean biological observation programs. Counter-clockwise: COPAS (Chile), IMARPE (Peru), reef monitoring program (Panama), HOT
(Hawaii, USA), IMECOCAL (Mexico), CalCOFI and Station M (deep-sea benthic observatory) (USA), MBARI and PISCO (USA), Newport line (USA), Station Papa (Canada), NOAA
Gulf of Alaska, Bering Sea programs (USA), Russian pelagic trawl surveys (Russia), A-line (Japan), NFRDI/KORDI (South Korea), including joint China Sea program with China,
TaiCOFI (Taiwan), Port Hacking (Australia), Maria Is and Hobart-Antarctic CPR line (Australia). New Continuous Plankton Recorder lines shown in Fig. 3.
Taiwan, and the United States (Fig. 2). However, ocean observation
programs exhibit a wide range of capabilities from well-integrated,
multi-disciplinary programs to programs whose biological observations remain mostly aspirational. For example, within the USA, there
are a number of monitoring programs, including five so-called
Integrated Ocean Observing Systems (IOOS): AOOS (Alaska Ocean
Observing System), CeNCOOS (Central and Northern California Ocean
Observing System), NANOOS (Northwest Association of Networked
Ocean Observing Systems), PaCIOOS (Pacific Islands Ocean Observing
System), and SCCOOS (Southern California Coastal Ocean Observing
System). However, the IOOS programs, with limited funding, have
focused on shore-based observations and issues related to water
quality, marine operations, coastal hazards, and marine spatial
planning. The IOOS programs provide infrastructure and the potential for a representative biological observation program focused on
the large marine ecosystems in US waters, but at this time virtually
no biological observations are collected, other than data related to
harmful algal blooms. Further ecological data are obtained from
ongoing state and federal programs and offered on IOOS web-sites
but are not consistent across IOOS programs. The IOOS programs
were therefore not included in Fig. 2.
The waters around Asia appear to be largely deficient in
systematic biological ocean observation programs, with the exception of the waters around Japan, South Korea, and Taiwan. The lack
of ecological monitoring in Chinese waters (e.g. the Yellow Sea,
East China Sea, and South China Sea) is particularly notable, since
these coastal ecosystems appear to be among the most severely
impacted by overfishing, pollution, and eutrophication, with
increasing deoxygenation and massive algal and jellyfish blooms
(reviewed in Ref. [45]). Although a Yellow Sea LME adaptive
management project has been approved, which is to include
monitoring activities by both China and South Korea [42], no
information on ecological monitoring activities was available for
Chinese waters, and it was not clear that these are yet operational.
The Indonesian GOOS program was also not included because it
does not yet appear to be operational [17]. Although the Russian
pelagic trawl survey program was included, it is designed primarily to survey salmon in the northwest Pacific and is not systematic.
Lack of systematic survey design has also limited the time series
that can be obtained from US waters in the Bering Sea, Gulf of
Alaska and off Washington and Oregon, despite the considerable
research effort expended in those regions.
Although this study focuses on water-column observations,
three predominantly benthic observation programs were included
in Fig. 2: the reef observation program in Panama, the PISCO project
in central California, which focuses on the kelp bed environment,
and the Station M deep-sea observations in the CCE [43].
Zooplankton is sampled relatively frequently around the Pacific
(Fig. 3). However, methods of sample analysis vary considerably,
which greatly limits the usefulness of some time series and their
comparability. Several programs limit sample analysis to some form
of bulk biomass measurement (e.g. displacement or settling
volume, wet or dry weight) or to functional groups, which are of
limited utility in detecting and interpreting ecological change.
Regime shifts in the ocean often involves shifts in water masses
and species composition but not in functional groups [5,33,26].
Zooplankton bulk biomass measurements are extremely coarse, and
changes in these measures related to changes in functional groups
J.A. Koslow, J. Couture / Marine Policy 51 (2015) 408–414
411
Fig. 3. Zooplankton observation programs. Red crosses: Zooplankton bulk measurements only; red circles: analysis to species-level resolution, time series o 20 years; yellow
diamonds: zooplankton time series to species level, o20 years; lines: CPR transects. (For interpretation of the references to color in this figure legend, the reader is referred
to the web version of this article.)
(e.g. between crustacean and gelatinous zooplankton) may be
misinterpreted as changes due to productivity (cf [36,28]). It is a
positive development that several observation programs that once
restricted zooplankton sample analysis to bulk biomass, such as
CalCOFI and the A-line off Japan, now carry out species-level
analyses. Although zooplankton coverage for the Pacific now
appears reasonably good, there are only five long-term (420 year)
zooplankton time series with species-level resolution (Fig. 3). There
are nine more recent (o20 years duration) Pacific zooplankton
time series with species-level resolution, including several Continuous Plankton Recorder transects that cover significant sectors of
the open North Pacific and the waters around Australia.
Sampling of the micronekton and fishes (other than those that
are commercially exploited) is far more limited (Fig. 4). Only
CalCOFI in the CCE has maintained long-term systematic observations of the region's fishes to species level based on ichthyoplankton
surveys, which are used to obtain indices of species' spawning stock
biomass. Russian trawl surveys for salmon in the upper 50 m of the
northwest Pacific and Bering Sea have been carried out since about
1980, providing data about micronekton that vertically migrate into
near surface water [27]. Ichthyoplankton surveys carried out since
the 1970s in the Gulf of Alaska and Bering Sea also provide time
series on the micronekton, but the sampling design is not consistent
from year to year and is generally limited to the spring spawning
period of the Alaska pollock [15]. The Taiwan Cooperative Oceanic
Fisheries Investigations (TaiCOFI) program carried out around
Taiwan for approximately 10 years may provide a further speciesresolution ichthyoplankton time series, but sample analyses to date
are limited to isolated cruises [29]. Since about 2000, there have
been trans-Tasman ship of opportunity (SOOP) lines between
Australia and New Zealand based on acoustics and limited trawling,
which provides limited species resolution [18].
Another issue that emerges when comparing ecological time
series is that not all observation programs sample ecological
variables with comparable oceanographic instrumentation and
sampling frequency. There are many zooplankton and midwater
net types, with various mouth openings, mesh sizes, and tow
characteristics, all of which influence the community that is
sampled and the portion that avoids or escapes the sampler
(Table 1). Tow depth and tow volume also vary substantially. As
a result the sample universe may vary dramatically from one
sampling program to another. In addition, the seasonality and
frequency of biological sampling may also dramatically influence
sample composition, depending upon the various species' seasonality and other life-history factors influencing distribution and
abundance. For example, the ichthyoplankton surveys carried out
by the Alaska Fisheries Science Center in the Gulf of Alaska and
Bering Sea concentrate on the spawning period of the Alaska
pollock and thus the time series only reflect the abundance of
fishes that spawn in the same period.
4. Discussion
Major advances in ocean observing have been achieved through
remote sensing and the Argo profiling-float program. Satellites
designed to observe the ocean now provide global coverage of seasurface temperature, sea-surface height, and ocean color, from which
sea-surface chlorophyll concentrations can be inferred; Argo floats
now routinely profile temperature and salinity in the upper 2000 m of
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J.A. Koslow, J. Couture / Marine Policy 51 (2015) 408–414
Fig. 4. Location of fish community and micronekton time series with species-level resolution. Red circle transect: o 20 years; yellow diamonds: 420 years. (For
interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
Table 1
Net types, mesh sizes (mm), and maximum tow depths (m) of zooplankton time series in the Pacific Ocean.
Observation Program
Net type
Mesh size (lm)
Maximum tow depth (m)
CalCOFI
MBARI
A-line
Australian CPR lines
Station Papa line
TaiCOFI
IMARPE
North Pacific CPR lines
Newport line
Bongo, manta, pairovet, MOCNESS
Bongo, dip net
Bongo, NORPAC, marutoku
CPR
NORPAC, white and dark SCOR, Miller
ORI (Ocean Research Institute) net
Bongo
CPR
Bongo, MOCNESS, ring net
150, 333, 505
333, 505
35, 183, 330
270
236, 350
330, 333
75, 300
270
150, 202, 240, 333, 505
210
210
150
10
250
200
300
7
100
the ocean, with the possibility that chlorophyll, oxygen, and nutrient
sensors may be added in future. These time series have proven
enormously useful, contributing to our understanding of global
primary production [6] and the production systems underlying
biogeography [30]. They are also critical to understanding processes
of global climate change, such as ocean warming dynamics [9].
Approximately 25 years ago, recognition of the need to monitor a
potentially changing ocean biogeochemistry led to development of
the Hawaii Ocean Time-series (HOT) and the Bermuda Atlantic Timeseries Study (BATS) in the North Pacific and North Atlantic subtropical gyres, respectively. These programs focused on characterizing the physical and biogeochemical pelagic environment based on
monthly sampling [23,44]. Consistent with these objectives, the
highest trophic level resolved was the zooplankton, whose overall
biomass and size structure were examined, but without resolution to
species level. However, species-level taxonomic resolution has generally proven necessary to assess changes in phenology, diversity, and
community structure, the most sensitive indicators of the ecological
impacts of climate variability and change in marine systems
[5,4,33,16].
The growing number of zooplankton time series that provide
species-level resolution is encouraging. However, our optimism is
tempered by recognition that many of these time series are based
on CPR sampling, which is inadequate to monitor the gelatinous
plankton, because they are too large, and the ichthyoplankton,
which are not sufficiently abundant: two groups which are in
particular need of adequate time series. We also note that new
time series (and old ones as well) are typically founded and
maintained based on the hope, hard work, and commitment of a
handful of scientists but lack the long-term funding and institutional backing required to maintain these in the long term. A
notable example is the Newport (Oregon) line: recent funding cuts
threaten its continuation despite its record of scientific excellence
and relevance to the fishing industry and management [37,38].
There is growing evidence of significant change in the ocean's
ecology, potentially related to anthropogenic forcing. Prominent
J.A. Koslow, J. Couture / Marine Policy 51 (2015) 408–414
examples include the impacts of global warming eutrophication,
overfishing, and acidification on coral reefs, which are iconic,
highly visible, and reasonably well-monitored [21], and the
impacts of deepwater trawling on deepwater reefs, which are
largely out of sight and poorly monitored [10].
However, other issues, potentially of global significance, remain
uncertain due to lack of sufficient evidence. Is a combination of
overfishing, eutrophication and deoxygenation leading to
increased blooms of gelatinous zooplankton ([35,12])? Is deoxygenation leading to a significant decline in mesopelagic fishes
([25])? Is the massive decline of nearshore and oceanic fishes
reported in the southern California Current, apparently related to
climate change, occurring more widely ([31], Koslow, Miller and
McGowan, unpublished results)? There are also pervasive but less
well-defined concerns about the state of the oceans, particularly in
coastal regions where burgeoning human populations put ocean
ecosystems under ever-increasing pressures from recreational and
commercial uses, runoff, power plants and waste recycling, habitat
modification, and so on.
The oceans contain remarkably complex and poorly-understood
ecosystems with diverse functional groups ranging from viruses to
whales. Not all groups are monitored adequately, and some not at
all. Unfortunately, there is evidence that some groups critical to the
ecology and biogeochemistry of the oceans are undergoing change
that we are only able to examine now as through a glass darkly.
There can be no responsible ocean stewardship without adequate ocean observations. An adequate global ocean observation
system should monitor a consistent set of ocean variables essential
to defining the health of ocean ecosystems at sites representative of
the ocean's 50 major biogeographic provinces [30]. As we have
seen in our survey, much of the Pacific Ocean is already covered by
biological observation programs that cover one set of variables or
another, and most of the ocean's biogeographic provinces already
have one or more active fishery and other ocean observation
programs (e.g. GOOS). However, they are generally too narrowly
focused, e.g. fisheries programs that do not monitor the oceanography or GOOS programs that do not encompass ecologically
relevant parameters. In addition, biological observation programs
are often not carried out consistently or fail to be adequately
integrated within or between biogeographic provinces. Critically,
almost none adequately observes the range of ecological variables
essential to define the status of key ecological communities.
However, there is often observational infrastructure in place; what
is required is to upgrade these systems to include key ecological
variables, in addition to fisheries or water quality variables.
Today, CalCOFI appears virtually unique in routinely observing
the physical, chemical, biogeochemical, and ecological state of the
ocean, with species-level resolution of the fish community (through
the ichthyoplankton), seabirds, marine mammals, and spring zooplankton. This has enabled studies of phenological shifts and of
community shifts in the California Current ecosystem associated
with the ENSO cycle, regime shifts (the Pacific Decadal Oscillation
[7] and North Pacific Gyre Oscillation [14]), and climate change
[25,26,3]. Although the program today carries out a broad range of
observations, it has a simple, proven and inexpensive technology at
its core to develop time series with species-level resolution of the
zooplankton and fish communities: plankton nets towed obliquely
through the upper 200 m of the water column.
Ichthyoplankton surveys are carried out in many parts of the
world to assess the stock size of commercial fish species, such as
anchovy, sardine, mackerel and others. Although many have an
underlying survey design similar to CalCOFI's, few examine the
abundance of fish eggs and larvae of non-commercial species.
Because the larval fish are mostly sampled at a very early developmental stage, their abundance is proportional to adult spawning
stock biomass. With adequate technical training, ichthyoplankton
413
identification can be carried out routinely today in most parts of the
world, so with a modest increment of additional effort the broad
community of fishes with a pelagic larval phase may be surveyed,
not just the handful of species of commercial interest. (In the
CalCOFI ichthyoplankton data set, only 3% of the fish taxa are of
commercial interest [1]) The development of community-level time
series provides altogether new opportunities for research, assessment, and management at the ecosystem level.
We note that in regions where stock assessment is not an
objective and ichthyoplankton surveys are not carried out, there is
no need for the extensive sampling programs entailed in CalCOFI
and other stock assessment surveys: sampling the ichthyoplankton at a relatively few stations can serve to define shelf and
offshore fish communities [32]. Resampling the CalCOFI data set
indicates that the abundance of key species and multivariate
community abundance patterns tend to be well correlated
between the full and reasonably reduced data sets (Koslow and
Wright unpublished results).
Who is to pay for expanded ocean observations? Clearly, costs
should be met by those utilizing and placing pressure on the
marine environment: coastal communities reliant on the oceans
for recreation and waste disposal, offshore energy industries,
fisheries and aquaculture, shipping, and others. In many instances
water quality and HAB surveys are already undertaken; only a
modest expansion of these activities is required. It should be noted
that the offshore oil and gas industry, worth more than $1 trillion
annually and often the cause of spectacular marine environmental
disasters, is generally not required to pay for ongoing monitoring
of the ocean environment.
There is a global effort underway to develop sustainable management practices in the LMEs of 110 developing nations in Africa,
Asia, Latin America and eastern Europe, funded with $3.1 billion in
assistance from the Global Environmental Facility (GEF) and the
World Bank [42]. The approach of these programs to ocean observations is still to be defined but this initiative offers perhaps the
greatest hope to date for widespread adoption of systematic observations of ocean ecology. The development of comprehensive ocean
observation programs can also serve to underpin viable marine
science and management infrastructure.
The development of ocean science to underlie ecosystem-based
management of the oceans depends on a three-legged stool:
observations, experimentation, and modeling. Observations have
long been the poor neglected relation in this partnership, but the
oceans cannot be managed without improved ecological time
series. Models of ocean biogeochemistry and ecosystems are empty
if they cannot be developed with data from the field and tested
with relevant biogeochemical and ecological time series. Such time
series are similarly required to evaluate marine management
measures. Time series are the bricks and mortar with which World
Ocean Assessments must be built; without these, potentially
profound issues of biogeochemical and ecological concern in the
global ocean – whether jellies are overwhelming the coastal ocean
or mesopelagic fishes are declining in the face of declining oxygen
levels – will remain speculative and the potential for action mired
in uncertainty. If we fail to develop adequate time series, we fail as
responsible ocean stewards and condemn ourselves to continuing
to stumble along, deaf and blind to its state.
5. Conclusions
A meta-analysis of ocean observation programs in the Pacific
Ocean indicates that the ocean's chemistry and physics are reasonably well monitored, but ecological monitoring remains largely ad
hoc, patchy, unsystematic, and inconsistent. Only a single program,
CalCOFI, provides consistent zooplankton and micronekton time
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series of greater than 20 years duration and with species-level
resolution. Recent studies based on the CalCOFI and other time
series indicate profound changes to the fish communities of the
southern CC, including nearshore, mesopelagic and other habitats
related to declining oxygen concentrations at mesopelagic depths
and other aspects of climate change. It is unlikely such changes are
isolated to the CC but lack of adequate time series largely
precludes their assessment elsewhere. Firm commitment from
the global community to sustained, representative, quantitative
marine observations at the species level is required to adequately
assess the ecological status of the oceans.
Acknowledgments
We gratefully acknowledge CCE LTER support from NSF grant
OCE-1026607 for an undergraduate summer fellowship that supported Jennifer Couture and an anonymous gift that partially
supported J. Anthony Koslow.
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