6.0
RESEARCH NEEDS
6.1
Environmental Research
6.1.1. Sustaining ecosystem services
The key emphasis should be on a shift from the management of one service at a time, to focus
instead on the conservation of several services simultaneously through protection of natural
biodiversity. Consistent management across management bodies and policy makers to sustain
biodiversity – via conservation of species richness, genetic diversity, species composition and
habitat diversity- will promote ecosystem integrity and stability. The range of services in marine
systems can create conflicts if different managers have different priorities (Fig. X). Thus, a focus
on one service at a time might compromise the multifunctionality of the ecosystem.
Figure X. (a) Complex positive and negative correlations among marine ecosystem services
create an intricate web of relationships that will be difficult for managers to simultaneously
optimize. Environmental changes that affect any one service (e.g. water quality) will probably
impact on others as well, making exosystem wide decisions difficult to achieve. (b) Likely
relationships between each ecosystem service and the biodiversity of marine habitats. Positive
effects of diversity on services may make it easier to enhance or maintain multiple services at the
same time, providing a basis for a coordinated regulatory framework. NOAA = National Oceanic
and Atmospheric Administration; EPA = Environmental Protection Agency; FWS = US Fish and
Wildlife Service; MMS = Minerals Management Service (After Palumbi et al., 2009).
6.1.2 Linking biodiversity and ecosystem function
Priorities should include an approach that focuses on the link between diversity and ecosystem
function, which in turn will require experimental studies exploring the association between
increased biodiversity on the level and stability of ecosystem functioning (Dully et al., 2003;
Worm et al., 2006). It will also be vital that appropriate and standardized approaches are applied
in the measurement of biodiversity, thus enabling a reference base-line that can be employed in a
comparative way.
The recommendation would be to measure biodiversity in accordance with its key constituent
components (see section…X; Fig. X). First, fundamental measurement can take place at the
seascape level by mapping distinct biological habitats across regions. Second, identification of
species within habitats will provide a baseline for estimates of richness and diversity measures.
Finally, con-specific diversity estimators, including genetic variability, physiological or life
history diversity provides an index of biological options for adaptation to environmental change
and stress. It is the last of these levels, and the linkages between genetic and ecologicallyrelevant phenotypic diversity that remains in general the level that is most under-studied, and
which will drive the higher level response to environmental variation. An outstanding challenge
is to relate the nature and magnitude of marine services to the biodiversity of habitats and
communities and the levels, speed and nature of disturbance that they can sustain. It is the
interplay among these factors that increasing effort should be expended.
Figure X. Measurement of biodiversity must occur at several levels: the lower level includes
different habitat types within a region- in this case, the rocky intertidal zone, sea grass beds and
kelp forests along the Californian coast. The middle level focuses on species diversity, here
illustrated as a set of macroinvertebrates of the rocky intertidal zone. The upper level represents
the diversity within each species, here shown by different DNA types within the intertidal. (After
Palumbi et al., 2009).Molecular techniques can in fact be employed at all levels, from
community to species and within species levels, though there will typically remain a requirement
for integration with traditional taxonomic approaches in many cases.
In terms of improving our ability to place our understanding of ecosystem function into a
predictive framework for forecasting resilience and recovery to environmental change, there is a
need to identify thresholds and to design studies that allows hypothesis testing from theory using
empirical data on key processes and rates that control how communities and ecosystems respond
to various stressors. Such studies might focus on the interactions of species and processes that
serve to drive the dynamics in the face of environmental change (Table XXX), by for example
the use of exploring variation in response across an environmental gradient (Figure XXX).
Figure XXX. Experimental design with sites randomly allocated to strata across a
“landscape”. The landscape could represent a stress or disturbance gradient or spatial
structure in the density or size of key species or diversity within a functional group. The
design, and more generally, the construction of gradients facilitate the use of co-variables
to tease apart the effects of different factors on experimental processes and multi-scale
analysis. (After Thrush et al., 2009).
Experimentalists and theoreticians need to work together to develop the ability to predict when
cumulative effects exceed ecological thresholds beyond which recovery is limitd and ecosystem
services compromised. Among the approaches that hold most promise include: (1) experimental
tests of hypotheses about putative factors generating thresholds in community dynamics (Table
XXX); (2) adaptation of disturbance-recovery experiments along gradients and across scales; (3)
recognition and potential for different outcomes driven by key species vs. weak interactions, and
degraded vs. diverse systems. Empirical studies will not be sufficient alone because resilience
will be relative and context dependent (Boyer et al., 2009). Moreover, interactions among
different human-induced stressors can generate non-linear responses of ecosystems to change
and limit their resilience (Ling et al., 2009). The need for the development, testing and
verification of models that incorporate empirical data and identify the positive feedbacks that
drive systems to rapiod change are required.
6.1.3 Measuring the genetic basis of biodiversity
The benefits of the DNA barcoding approach include:
1. Standardisation of the technique and method of data acquisition
2. A global reference data base accessible to everybody;
3. High level of quality assurance
4. Associated biological and voucher specimen information required, so allowing accurate
cross-referencing and rapid specimen retrieval;
5. The same approach can be applied to many different taxa, even if a different reference
gene is to be employed. For example, bacterial and microbial communities can be
surveyed using ribosomal genes- the aim is not to employ a single standard gene, though
CO1 works well in many diverse animal taxa, but rather to limit and standardise the most
appropriate genes for specific taxa.
6. In addition to exploring individual species, the approach can be applied to survey entire
communities (e.g. marine meiofauna; zooplankton assemblages: see below).
7. The high throughout nature of the technique can be enhanced by employing state of the
art new sequencing methodologies such as so-called second generation sequencing (see:
Carvalho GR, Creer S, Allen M, et al., (In Press) Genomics in the discovery and
monitoring of marine biodiversity. In: An Introduction to Marine Genomics, (ed.) Boyen
C & Cock, M. Springer-Verlag; Creer, S.*, Fonseca, V.G.*, Porazinska D.L., GiblinDavies, R.M., Sung, W., POwer, D.M., Packer, M., Carvalho, G.R., Blaxter, M.L.,
Lambshead, P.J.D. and Thomas, W.K. 2010. Ultrasequencing of the meiofaunal
biosphere: practice, pitfalls and promises. Molecular Ecology, Molecular Ecology (2010),
19 (Suppl. 1), 4–20.
8. Once the species richness and diversity of samples, habitats and communities has been
described, the data can be used as a platform to explore the functional role of specific
taxa, including trophic interactions and dynamics, the contributions to ecosystem
services, and the role of novel marine products in situ and for exploitation.
9. The robustness of DNA tools means that information can be accessed from a diversity of
sources, including archived materials (e.g. otoliths, resting eggs, fish scales), recovered
material from the gut contents, and even material from processed products to allow
traceability of specific products back to species origin.
There is a need to enhance capacity in the marine community to describe and monitor species
richness and dynamics- thus, an opportunity to engage in the global movement using DNA-based
standardised tools. For example, recent work to examine the diversity of zooplankton
communities (Machida, R et al., (2009) Zooplankton diversity analysis through single-gene
sequencing of a community sample. BMC Genomics 10:438 doi:10.1186/1471-2164-10-438)
illustrates the potential well.
It is well established that among the components of the ocean ecosystem, zooplankton
play vital roles in energy and matter transfer through the system. Despite their importance,
understanding of zooplankton biodiversity is limited because of their fragile nature, small body
size, and the large number of species and diversity of life history stages and taxonomic phyla.
The authors applied single-gene zooplankton community analysis using mitochondrial COI gene
sequences from a bulk zooplankton sample, allowing them to derive an estimate of species
richness of almost the entire zooplankton community. Results from a depth of 721 m to the
surface in the western equatorial Pacific off Pohnpei Island, Micronesia, detected a total of 189
species of zooplankton. In conjunction with the Census of Marine Zooplankton
(http://www.cmarz.org/) and Barcode of Life projects, such single-gene zooplankton community
analyses can provide a powerful and robust tool for estimating the species richness of
zooplankton communities. A similar approach can be employed for communities that are critical
to the structure and functioning of marine communities, but are typically intractable, such as the
marine benthos (eg. Creer et al., 2010).
Additional illustration can be obtained by considering the case of DNA barcoding of fish and
fish products (Fish-Bol: http://www.fishbol.org/). See Costa and Carvalho: Costa, FO &
Carvalho, GR (2007) The Barcode of Life Initiative: synopsis and prospective societal impacts of
DNA barcoding of Fish. Genomics, Society and Policy 3, 29-40 (available on line at
www.gspjournal.com./). More details can be provided if required.
6.1.4 Using other analytical tools
Numerous new analytical methods have been developed, significantly improving geographical
resolution (Ruzzante et al., 2000b) and statistical power (Kalinowski, 2002, Kalinowski, 2005),
while enhancing speed of detection and reducing cost. New tools have been developed such as
otolith microchemistry, where the chemical composition of a fish otolith can be matched with
composition of seawater to provide data on the geographical origin of individual fish (Thorrold
et al., 2001). Likewise, recent revolutions in molecular biology have facilitated the development
of powerful tools for genetic analysis of population structure in marine fishes (Kochzius, in
press), with significant additional data on population structure originating in the last decade. In
addition to enhanced opportunities in the description of population structure and connectivity,
the application of genomic tools to explore directly the extent and dynamics of adaptive variation
and coupling of genetic variation to phenotypic responses, provides a new range of opportunities.
Thus, there is a need to:
1. Increase the resolution and robustness of estimates of population structure and
connectivity by applying advanced high throughput tools (e.g. single nucleotide
polymorphisms, SNPs);
2. To increase investment from predominantly descriptive studies that provide the spatial
and temporal framework of patterns of genetic variability in the wild, to increasingly
mechanistic approaches that empirically explore some of the biological (e.g. life history,
population demography and connectivity) and environmental factors (e.g. oceanic
hydrography, environmental stress, harvesting) shaping such patterns. Importantly, such
efforts not only inform our understanding of the distribution and dynamics of species, but
also provide a range of tools and conceptual platform for the design and implementation
of management and conservation strategies. The key to future developments will continue
to depend upon the integration of principles and practice, and the acknowledgement that
fundamental features of a species biology (recruitment, migration and mortality) depend
upon the nature, pace and extent of interactions between the genotypic composition of
populations and their environment.
3. To explore the linkages between genetic and phenotypic diversity in relation to
identifiable selective forces. Even where this is not directly possible, approaches based on
covariance between environmental factors and patterns of genetic structuring as in
landscape genetics (or so-called “seascape genetics”), can generate hypotheses for
subsequent testing.
4. To enhance the use of traditional ecological approaches for direct estimates of fitness
variation in the wild, by the design of appropriate meso- or microcosm manipulation
studies, reciprocal transplant experiments, and the use of common greenhouse studies
where the response of individuals and populations can be explored under natural or seminatural conditions. A major approach in fisheries for example would be to utilise the
facilities, biological information (e.g. pedigree data) and genetic and genomic approaches
of aquaculture to derive direct estimates of adaptive variation.
5. To incorporate empirically-derived estimates of adaptive variation into environmental
and climate-change scenarios, so that the capacity and nature of responses can be
incorporated into meaningful predictive frameworks.
6.1.5 Differentiating evolutionary and ecological time scales
A key question underpinning much recent activity in marine biodiversity and a necessary
corollary for assessing the impact of environmental change is to examine whether the current
trends in marine biodiversity differ from historical trends. It becomes necessary to employ an
historical perspective to compare rates of change across evolutionary and ecological timescales
in the absence of human disturbance.
The evolutionary timescale provides a baseline for estimating the extremes of changes
in planetary marine diversity against which anthropogenic effects can be scaled: ecological
timescales are relevant for examining the role that human-induced drivers have on recent
biodiversity change. On the evolutionary scale it is important to understand the drivers of mass
extinctions: although the impact of human drivers is yet to approach the 98% species extinction
level that occurred during the Permian- it is important to know how threshold effects could result
in rapid collapses with apparently little warning. Indeed, the study of past global warming events
and their impact on biodiversity can be highly informative in generating predictions based on
current trends (Kennet & Stott, 1991; Crouch et al., 2001).
For example a marked oxygen and carbon isotope excursion occurred in Antarctic waters at the
end of the Palaeocene (~ 57.33 Myr ago; Kennet & Stott, 1991), indicative of global warming
and associated oceanographic changes. The event resulted in one of the largest deep-sea benthic
extinctions of the past 90 million years (35-50% species reduction of benthic foraminiferal taxa),
though oceanic plankton were largely unaffected, suggesting an uncoupling between deep and
shallow marine ecosystems. A key feature here is that the extinctions were driven by processes
that were surprisingly rapid (< 3Kyr), indicating that vast volumes of deep oceanic waters were
affected rapidly. Hypotheses proposed included: (1) rapid warming of the deep ocean waters and
a change in bottom water sources; (2) a deep sea oxygen deficiency caused by sudden warming
and alterations in circulation of deep waters; (3) a marked decline in surface oceanic productivity
that reduced trophic resources available for deep ocean biota.
Modeling studies indicate that option (2) was most likely based on knowledge of temperature
changes at the Palaeocene/Eocene boundary and predicted complex modifications to
oceanographic circulation. The significance of the above example is several-fold: (1) it
demonstrates the value of studying past patterns of marine biodiversity and environmental
change; (2) it demonstrates the speed and global extent of changes that can generate threshold
effects impacting on discrete but wide-ranging components of marine ecosystems; (3) it assists in
our understanding of the nature and dynamics of interactions between climate and abiotic and
biotic drivers of biodiversity; (4) it allows such data to develop predictive climate models based
on recent and current trends of environmental change.
The description of spatial patterns of global marine biodiversity can be informative indicators of
natural drivers: for example, the well documented gradient with latitude (higher diversity in
tropical waters), longitude (decreasing diversity from west to east in tropical Pacific and
Atlantic), and depth. While some relationship between species richness and the amount of energy
is well supported (Erwin, 2009), the relationship between energy, climate, latitude and diversity
is complex. Averaged across the year for example, the energy received in the tropics if only 4
times as great as the poles, though the seasonality and intensity of incident radiation varies
markedly. There are a variety of historical, ecological and evolutionary explanations for
latitudinal diversity gradients and the species-energy relationship (Evans et al., 2005; Table X).
Table X: Mechanisms promoting posituive species-energy relationships (after Erwin, 2009). The
summary of mechanisms promoting positive species-energy relationships is based primarily on
information from Evans et al., 2005. Mechanisms in bold have considerable empirical support,
the possible role of niche onstruction is new and has not yet been rigorously investigated.
Historical hypotheses focus on the fact that the tropics are older, but the persistence of
latitudinal gradients during the Phanerozoic restricts the generality of such claims. Most
ecological models are based on the higher productivity of the tropics, and the evolutionary
models propose higher evolutionary or speciation rates, or lower extinction rates in the tropics. It
is likely that a combination of such events are operative. In general, current evidence supports a
positive relationship between high energy climates and increased diversification rates , increased
diversity of niches due to increased metabolic scope, and more specialized niches possibly
because of “niche construction” (Table X). Data that indicates the tropics as a cradle of diversity
that pumps clade representatives into higher latitudes, as well as evidence for a higher rate of
ordinal origins in the tropics, suggest an asymmetric pattern of innovations in high energy
climate regimes. It is possible that diversity does not track climate, but rather increases during
warm intervals and fails to decline proportionally when climates become cooler. Thus, warmer
climates may drive evolutionary diversification, with higher diversity persisting, at least for a
time.
Statistical phylogeographic studies (Richards et al. 2007; J Biogeog. 34, 1833-1845)
provide a robust framework for testing the factors that influence population divergence and
speciation, and that ultimately generate biogeographic patterns. Use of coalescent modeling
provides a framework for statistically testing alternative hypotheses about the timing and pattern
of divergence. Biogeography – identifies processes structuring diversity at a variety of
geographic and taxonomic scales. The linking of GIS-based approaches to generating alternative
hypotheses, when coupled with genetic approaches to test them, has the potential to increase
profoundly the rigour of phyloegographic research. It is then possible to explore the likely
impacts of such factors as demographic events- population bottlenecks and expansions, as well
as various types of population divergence, ranging from vacariant events to differentiation with
migration.
Figure X. Distributional modeling and statistical phylogeogrtaphy (After Richards et al., 2007).
The approach allows for the generation of alternative biogeographic hypotheses using
palaeodistribution models, and subsequently testing with coalescent simulations and empirical
genetic data. In (e) and (f) the gradient from red to white differentiates areas with predicted high
to low suitability, respectively, for the species in question.
Despite the plethora of data (Sala & Knowlton 2006), there remains significant
controversy about the underlying causes of the observed patterns. An additional level of
uncertainty emerges when examining single-celled eukaryotes- Bacteria, Archaea and virusesglobal patterns in the species richness of microbial species remains a key task- and underpins key
aspects of ecosystem function and the attendant services. High throughput genomic technologies
(Carvalho et al., 2010) provide an insightful approach not only for the description of patterns of
microbial diversity across a range of spatial scales, but importantly also provide the necessary
framework for investigating key drivers.
6.2
Human Dimensions Research
[SH, SJ, OT, CB, JB, HL, JW]
6.2.1 Designing effective institutions
6.2.2 Demographic
6.2.3. Economic
6.2.4 Social
6.2.5 Cultural
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see version Gary 20 February
Establishing realistic estimates of the magnitude and direction of change in biodiversity under a
range of scenarios is constrained by the interplay between the ongoing unpredictable and
continuous alterations to marine ecosystems driven by natural and man-made change. For
example, species become locally extinct, others are introduced, the abiotic environment is
modified through inputs of chemicals or acidification, habitat alteration affects distribution and
abundance, and major extractive pressure is often imposed on most trophic levels. Moreover, the
speed of such drivers is many orders of magnitude higher than the evolutionary time that it has
taken to derive communities and ecosystem function. One key area that might prove especially
insightful is the merging of food web research and biodiversity research in enhancing our
understanding of resilience (Worm & Duffy, 2003).