Quantifying the impacts of multiple stressors on the production of marine benthic resources
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Schertenleib, Katrin Simone, Quantifying the impacts of multiple stressors on the production of marine benthic resources, Trinity College Dublin, School of Natural Sciences, Zoology, 2024Download Item:
Schertenleib_Katrin_PhD_2024.pdf (PDF) 5.685Mb
Abstract:
Coastal ecosystems are among the most heavily affected by climate change and anthropogenic activities, which impacts their diversity, productivity and functioning and puts many of the key ecosystem services they provide at risk. Although empirical studies have moved beyond single-stressor-single-species experiments with limited extrapolation potential and have increasingly investigated the cumulative effects of simultaneously occurring multiple stressors, consistent generalities have not yet been identified. Upscaling from controlled experiments to natural ecosystems, therefore, remains an unsolved challenge. Disentangling the independent and cumulative effects of multiple stressors across different levels of biological complexity, revealing the underlying mechanisms and understanding how coastal ecosystems may respond to predicted scenarios of global change is critical to manage and protect our natural capital.
In this thesis, I advance multiple stressor research by applying complementary approaches to quantify the impact of multiple stressors on marine benthic resources and thereby help predict the consequences of expected climate change for coastal habitats. First, I present the newly developed experimental platform QIMS (Quantifying the Impacts of Multiple Stressors) that overcomes some of the shortfalls of previous multiple stressor research (Chapter 2). Second, in a novel empirical study, I investigate the independent and combined effects of moderate ocean warming and acidification on the functioning and production of mussels and algae, considering the effects of interspecific interactions in the presence or absence of the respective other species (Chapter 3). Third, I synthesise monitoring data from Dublin Bay (representative of a typical metropolitan estuary) using conditional inference and a Bayesian Network model and provide alternative system trajectories according to different climate change scenarios. From this new model, I deepen the understanding of the complex linkages between environmental conditions and the diversity and functioning of Dublin Bay to support local decision making and management (Chapter 4).
Empirical tests of independent and cumulative multiple stressor effects require multi-factorial and multi-level designs, as well as high treatment replication to identify stressor interactions and their underlying mechanisms across multiple levels of biological organisation and enable robust data analyses. Many marine multiple stressor mesocosm-based studies to date included a low number of treatments or low replication of treatments or both. The new aquatic mesocosm-based experimental platform QIMS consist of 96 independent replicate units, in which up to three clearly separated factorial treatment levels of temperature and pCO2/pH each can be precisely manipulated and maintained randomly distributed across all mesocosms. QIMS complements a suite of permanently installed marine mesocosm facilities around the world that simulate ocean warming and/or acidification and facilitates multiple stressor research at an unprecedented level of statistical robustness and fully crossed, multi-level factor combinations.
To investigate the independent and combined effects of moderate ocean warming and acidification on the functioning and production of marine benthic resources, mussels and/or algae were exposed to three levels of temperature (ambient, +0.8 ?C, +2 ?C) and two levels of pCO2 (ambient at 450 ppm, elevated at 645 ppm) in a seven-week mesocosm experiment. Additionally, differences in responses according to the presence/absence of the respective other species were assessed (three levels: mussels, algae, mussels and algae). No interactions among any of the 18 experimental treatments (n = 5) were identified and no effects of pCO2 were found. Warming increased mussel mortality and clearance rates, while mussels and algae facilitated each other?s production (accumulated biomass, mussel condition index, algal photo physiology) when cultured together instead of separately. Overall mussel mortality was lower when algae were present. These results show the temperature sensitivity of the functioning of key benthic species, while there might be resilience towards moderate ocean acidification. Importantly, the ecological and potential economic benefits of increasing and conserving biodiversity in marine ecosystems is highlighted.
To identify links between environmental and biological variables, and to additionally predict the effects of climate change for Dublin Bay, Ireland, all available monitoring data was synthesised for the first time using conditional inference and a Bayesian Network. The model shows that when silica was limiting during the period from which monitoring data was available, phytoplankton biomass and abundance increased, while benthic invertebrate taxa indicated pristine conditions. When sediment organic content was high, invertebrate taxa richness was high, too, which allowed a greater abundance of wading birds. Having extrapolated warming, precipitation, ocean acidification and sea level rise according to climate change projections, I conclude from the model that climate change will degrade the ecological status of Dublin Bay, particularly affecting wader bird abundance through habitat loss, which emphasises the importance of protecting the remaining habitat.
Through methodological tool development, new empirical insights and a framework to synthesise existing monitoring information, this thesis adds to multiple stressor research opportunities, knowledge and accessibility, particularly in the light of expected climate change. Mesocosm experiments are important to test hypotheses and inform specific management questions, while models can inform holistic ecosystem management strategies or ecosystem maintenance in changing ocean conditions. Additionally, mesocosm experiments can inform or validate mathematical models, while models can highlight data gaps and identify system components that require prioritised management action. For best outcomes, empirical research and modelling should be applied as complementary tools to advance the scientific understanding of a system and thereby facilitate management and planning. Nevertheless, our planet is experiencing both a climate and a biodiversity crisis right now. Adding more detail to known tendencies may be a misleading priority and instead applying and implementing existing scientific knowledge to protect habitats and species, mitigating climate change effects, advancing adaptation to expected effects and making existing information readily available to managers and decision makers may be much more relevant.
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https://tcdlocalportal.tcd.ie/pls/EnterApex/f?p=800:71:0::::P71_USERNAME:SCHERTEKDescription:
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Author: Schertenleib, Katrin Simone
Advisor:
O'Connor, NessaPublisher:
Trinity College Dublin. School of Natural Sciences. Discipline of ZoologyType of material:
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