Widespread coral reef decline, including decline in reef fish populations upon which many coastal human populations depend, have led to phase-shifts from the coral-dominated systems, found desirable by humans, to algal-dominated systems that provide less ecosystem services, and the loss of functionally important species. Marine resource managers are challenged with providing strategies that can mitigate or prevent such phase shifts and losses and promote the sustainable use of marine resources. Additionally, managers need to take into account the impacts of these strategies on the socioeconomic conditions of the many resource users. To respond to these challenges scientists, managers and policy makers have advocated for an ecosystem-based approach instead of the traditional focus on individual (economically important) species. Ecosystem-based management includes the various dynamic processes that influence an ecosystem, such as hydrology, ecology, biogeochemistry, and human activities. The management strategy evaluation (MSE) tool commonly used in single species stock assessments for evaluating socioeconomic and ecological tradeoffs of alternative management strategies, has now become more widely applied in multi-species or ecosystem assessments. Ecosystem modelling can include more of the key dynamic processes that drive ecosystems and by using that in an MSE framework provides a better understanding of the socio-ecological consequences of management options and quantifies these tradeoffs. In this thesis, I review the use of minimal, intermediate and complex coral reef ecosystem models for their suitability of MSE applications. I conclude that complex models can integrate the myriad dynamic processes that govern coral reef ecosystems and are most suitable for MSE, but that minimal and intermediate models are needed to provide the relationships relevant to these dynamics. The main objective of this thesis was to develop a complex model and quantify the effects of watershed management and fishery regulations on coral reef ecosystem services against a backdrop of climate change impacts. For this model development, I selected the Atlantis ecosystem model framework and applied it to a case study of the coral reef ecosystems around Guam to evaluate the performance of alternative management strategies against identified ecosystem metrics. Following the step-wise approach recommended for Integrated Ecosystem Assessments, I started with a workshop involving local stakeholders (including resource managers and other coral reef users) to identify the (1) overarching goal of coral reef management, (2) ecological indicators of reef status, and (3) socioeconomic indicators of reef users. Using an Ecopath model I identified additional ecosystem indicators of fishing impacts that could also be used as performance metrics in the ecosystem modelling of alternative strategies. Published relationships for key coral reef dynamics were used to apply the Atlantis framework to coral reef ecosystems. I then developed and parameterized the Guam Atlantis model including 42 functional species groups and the system impacts of eutrophication, sedimentation, fishing and ocean warming and acidification. I validated the model simulations of no local or global stressors, a ‘control run’, following common guidelines for Atlantis development and I validated the added dynamics with published and empirical data or with expert judgement. Due to the absence of time series, model skill assessment was difficult but I could compare biomass of included fish groups after a 1985–2015 simulation with observational data in 2011. These results showed that the model is biased and overestimates various fish groups. However, because the origin of the bias is unknown, rectifying the bias at this point was not possible. Despite this, based on the model validations I concluded that the model was ‘scenario ready’ and suitable for use as a basis of <em>relative </em>comparisons of management strategies, allowing for evaluations to be conducted in an internally consistent context. I applied the model to evaluate the relative performance of management strategies against a set of criteria based on the overall goals identified by local resource managers. These included: (1) improved water quality, (2) increased reef resilience, (3) enhanced fish biomass, and (4) similar or improved fishery landings. Comparing tradeoffs across the selected scenarios showed that each scenario performed ‘best’ for at least one of the performance indicators. The integrated ‘full regulation’ scenario (size and bag limits, marine preserves and no land-based sources of pollution) outperformed other scenarios with two thirds of the performance metrics approaching the criteria at the cost of reef-fish landings. When the effects of climate change were taken into account, the selected scenarios performed fairly equally, but none could prevent a collapse in coral biomass by mid-century under a business-as-usual greenhouse gas emission scenario. To get a better understanding of how these same management scenarios influence the economically important tourism sector and the socially important reef-fishing sector, I coupled the Guam Atlantis model to two human behavior models, one representing divers and the other fishers. Ecosystem modelling also allows for the comparison of cumulative impacts. Assessments of individual and cumulative impacts of three stressors to reef ecosystems: land-based sources of pollution, fishing and climate change, showed that, to-date, fishing has had the most negative influence on ecosystem metrics that represent reef status, resilience and functioning, and climate change will have the most negative effect in the future most noticeably on the benthic community structure. Cumulative simulations generally showed that the actual effect was slightly less than could be expected based on the sum of their individual effects, keeping in mind that the actual effect size was negative. With this model now developed, it provides a tool for assessing and quantifying a range of questions in support for EBM for coral reef ecosystems.
|Award date||16 Sep 2015|
|Publication status||Published - 16 Sep 2015|