Coral Reef Dynamics as Complex Ecological Networks: Linking Structure to
Resilience for Conservation
Coral reefs are complex systems that vary in structure, species diversity, and ecological
processes across spatial and temporal scales. Systemic function of the ecosystem as a
whole can be disrupted by single or cumulative stressors, by direct or indirect effects, and
by feedbacks within the system (Hatcher 1997, Hughes and Connell 1999, Hughes et al.
2005). Coral reefs throughout the world are declining in coral cover (Gardner et al. 2003;
Bruno & Selig 2007), have reduced function and resilience (Nystrom et al. 2000), and
individual coral colonies are suffering degraded health where intensive human influence
is present (Richardson 1998; Hughes et al. 2003). At the global scale, reefs are
considered to be at high risk of continued losses, however, at local and regional scales,
some reefs are not exhibiting stress responses or are able to recover from disturbance
where others are not. Given the heterogeneity of reefs and their response to stress,
effective conservation of coral reef ecosystems under regimes of natural and
anthropogenic disturbance requires that resilience parameters, those factors that either
encourage or inhibit resistance to and recovery from disturbance (Mumby et al. 2007),
are identified and targeted for conservation action. Historically, coral reef science has
focused on a small number of species and stress responses in a single location, such as
effects of temperature on one species growth, or in larger studies, the effects of several
stressors on a few variables. Of necessity, this approach ignores much of the physical and
ecological complexity of reefs, including the environmental context of the response, the
effects of the excluded variables and relationships in the system, as well as feedbacks and
other non-linear dynamics that structure the system. One of the great challenges in
conservation biology is predicting the effects of human activity on a complicated web of
interacting parts, particularly in a system where the individual components exhibit highly
variable responses to stress in space and time.
My research will use probabilistic graphical models to study the relationships (of species
and environmental factors) that constitute a coral reef ecosystem. This approach views
coral reefs as a set of interrelated, hierarchically-organized processes that exhibit
complex, non-linear dynamics (Folke et al. 2004). An example of this network-oriented
approach is a food web comprised of organisms that act as nodes (e.g. an algal species
and an herbivorous fish) connected by an interaction (e.g. energy consumption). In coral
reef systems, some of these nodes and links are known (e.g. Dulvy et al. 2004) but others
are poorly understood. Nevertheless, their influence on the overall system could be nontrivial, as relatively minor seeming influences can exhibit feedbacks that propagate
through the network structure (Sole and Montoya, 2001). Probabilistic graphical models
are a promising approach to studying problems of this type because they can be used to
model both known and latent structural relationships, even under uncertainty about the
nature of those relationships (Koller and Friedman, 2009). Network analysis leads to
results that could not be determined from the interaction of a single species with the
environment, and that more accurately reflect a disturbance regime that includes
cumulative stressors, feedbacks, and cascading effects through the system network. In a
traditional approach, a strong interaction between two variables is assumed to be
important systemically, but as an example, indirect and stabilizing effects from weak
interactions can have a strong effect on system maintenance (Berlow 1999) that would go
undetected by traditional analyses. These influential nodes and links may not be
intuitively identified from their interaction strengths, but are most responsible for the
maintenance of the network structure and function (Berlow et al. 2009), and are therefore
critical indicators of resilience and the most important targets for management action.
Strong examples of ecological networks in marine, terrestrial and economic systems have
successfully predicted the whole ecosystem response to a changing environment
(Williams and Martinez 2000), and these powerful methods have not yet been applied to
system ecology of coral reefs.
In my PhD research, I propose to investigate the following research questions using
complex ecological network analysis:
1. Which interactions in a coral reef ecosystem have the greatest influence on
maintaining its structure, function, and service provision?
2. Do influential interactions gain or lose influence at different spatial scales and
if so, what types of interactions are influential at what scales?
3. How do interactions gain or lose influence on the whole system under different
disturbance or stressor regimes?
The final chapter of my PhD thesis will assess the potential for engaging recreational
divers in scientific network analysis of coral reefs, which is described in greater detail
below.
To address these questions, I will develop a probabilistic niche model (Williams and
Martinez 2000) of the linkage structure of each reef, and will include up to three
interacting components that relate physical and chemical links in addition to biological.
Model nodes are any variables that interact, including species and stressors. To develop a
dynamical model of bioenergetics, I will determine interactions and their relative
strengths from existing data and estimates that are derived from known relationships
between organism size and metabolic requirements. These two component models will be
hybridized to integrate the structural and dynamical properties of the reef. I will then
analyze each network’s structural properties (e.g. density, size, path length, clustering,
connectedness, etc.) and dynamical properties (e.g. stability, multistability, persistence,
resilience, feedbacks, nonlinearity, etc.), and will perform probabilistic simulations given
different scenarios. Ground-truthing and simulating future scenarios are performed in the
model similarly by adding and removing structural elements, altering interaction
strengths and then comparing the resulting network properties to each other and to realworld examples (Pascual and Dunne 2006).
For my program collaboration with the Dr. Nancy Foster scholarship, I would like to
address my research questions using the Florida Keys National Marine Sanctuary
(FKNMS) as a study system. The FKNMS is uniquely suited to investigate these
questions because: a. its relatively low ecosystem diversity allows for a simpler network
structure, b. its islands vary in their proximity to and use by human populations for
comparison of disturbance regimes, and c. because of the availability of long-term data.
The large management effort in the area and different zones of extraction regulations also
offer real-world examples to ground-truth the effects of altering reef network structure of
reefs (e.g. fishing removes targeted fish from the network and alters interaction strengths
with other species). Network analysis of the FKNMS will yield three scientific outcomes:
1. Identifying the factors that control ecosystem structure, which is critical knowledge for
how best to conserve ecosystem function with limited resources, 2. Understanding
variability in network properties between reefs, which is essential to estimating
vulnerability to human impacts, and 3. Predicting the ecosystem response to specific
disturbance regimes that are simulated in the network model, which allows managers to
assess the sensitivity of a reef to natural or anthropogenic disturbance. The models and
visualization tools produced from this study will be provided to resource managers
working specifically in the FKNMS, and will be published online as a template that can
be applied to all marine systems for identifying the most efficient conservation targets.
In order to engage the public with my work, I am developing a citizen science training
program that encourages recreational divers to participate in the scientific process.
Recreational divers log more underwater observation hours in more locations than
scientists can, are often highly engaged in the natural history of dive sites and have
enormous potential for meaningful scientific collaboration. As an example, species
interactions on reefs are poorly known in part due to limited observation time, and our
ability to model reef dynamics will improve substantially with increased records of
interactions. The benefit of these collaborations is three-fold: science benefits from more
data and new ideas, divers are enriched by making valuable contributions to protecting
their resources, and management efforts benefit from receiving better scientific
information as well as deeper and broader engagement in conservation by resource
stakeholders. In order to facilitate these collaborations, I have partnered with a software
engineer and a website is currently under construction that will teach divers how to
collect data, make observations and form hypotheses. The site will be open to all and will
allow users to upload, crowd-analyze and visualize data that they collect, as well as
provide a community forum where users can ask questions and discuss the project.
I will implement a pilot version of this citizen science program at multiple dive shops in
the Florida Keys in order to identify opportunities for improving public engagement,
training curriculum and website functionality. Following this pilot, I will develop a model
that has been improved by adding citizen observations to the network structure, and
compare this to a previous network model in the same area so as to statistically estimate
the potential information gain by citizen scientist participation.
This study will be the first to use a complex network approach for coral reef ecological
dynamics and will also be innovative within the field of complexity science by
incorporating non-trophic interactions among network components. This research has the
potential to substantially improve evidence-based coral reef conservation by deepening
our understanding of the interdependence among reef components and by revealing the
most influential mechanisms in the system, which will directly inform management
action. Therefore, this project aligns perfectly with both my and NOAA’s missions to
improve our knowledge and ability to predict complex ocean ecosystem dynamics, to
share this knowledge openly, and to use it to conserve our valuable resources.