Informing the management of multiple stressors on estuarine ecosystems using an expert-based Bayesian Network model

Allison, 2018, Dilemmas of modelling and decision-making in environmental research, Environ. Model. Software, 99, 147, 10.1016/j.envsoft.2017.09.015 Belanger, 2017, Future needs and recommendations in the development of species sensitivity distributions: estimating toxicity thresholds for aquatic ecological communities and assessing impacts of chemical exposures, Integrated Environ. Assess. Manag., 13, 664, 10.1002/ieam.1841 Bremner, 2003, Assessing functional diversity in marine benthic ecosystems: a comparison of approaches, Mar. Ecol. Prog. Ser., 254, 11, 10.3354/meps254011 Choy, 2009, Elicitation by design in ecology: using expert opinion to inform priors for Bayesian statistical models, Ecology, 90, 265, 10.1890/07-1886.1 Clark, 2019, The development of a national approach to monitoring estuarine health based on multivariate analysis, Mar. Pollut. Bull., 110602 Cloern, 2010, Biological communities in san francisco Bay track large-scale climate forcing over the North pacific, Geophys. Res. Lett., 37, 10.1029/2010GL044774 Côté, 2016, Interactions among ecosystem stressors and their importance in conservation, Proc. Biol. Sci., 283, 20152592 Dambacher, 2003, Qualitative predictions in model ecosystems, Ecol. Model., 161, 79, 10.1016/S0304-3800(02)00295-8 Davies, 2020, Trans-Tasman cumulative effects management: a comparative study, Frontiers in Marine Science, 7, 10.3389/fmars.2020.00025 de Juan, 2009, Defining ecological indicators of trawling disturbance when everywhere that can be fished is fished: a Mediterranean case study, Mar. Pol., 33, 472, 10.1016/j.marpol.2008.11.005 Duarte, 2009, Return to neverland: shifting baselines affect eutrophication restoration targets, Estuar. Coast, 32, 29, 10.1007/s12237-008-9111-2 Dudley, 2017 Foley, 2019, The implications of uncertainty on cumulative effects management, Resource Management Journal, November, 22 Foley, 2015, Using ecological thresholds to inform resource management: current options and future possibilities, Frontiers in Marine Science, 2, 10.3389/fmars.2015.00095 Gladstone-Gallagher, 2019, Old tools, new ways of using them: harnessing expert opinions to plan for surprise in marine socio-ecological systems, Frontiers in Marine Science, 6, 10.3389/fmars.2019.00696 Grimm, 2005, Pattern-oriented modeling of agent-based complex systems: lessons from ecology, Science, 310, 987, 10.1126/science.1116681 Gunderson, 2016, Multiple stressors in a changing qorld: the need for an improved perspective on physiological responses to the dynamic marine environment, Annual Review of Marine Science, 8, 357, 10.1146/annurev-marine-122414-033953 Hewitt, 2017 Hewitt, 2009, Enhancing the ecological significance of sediment contamination guidelines through integration with community analysis, Environ. Sci. Technol., 43, 2118, 10.1021/es802175k Hume, 2018 Hewitt, 2016, Multiple stressors, nonlinear effects and the implications of climate change impacts on marine coastal ecosystems, Global Change Biol., 22, 2665, 10.1111/gcb.13176 Hewitt, 2007, Incorporating temporal variability of stressors into studies: an example using suspension-feeding bivalves and elevated suspended sediment concentrations, J. Exp. Mar. Biol. Ecol., 341, 131, 10.1016/j.jembe.2006.09.021 Hicks, 2019 Hillebrand, 2020, Thresholds for ecological responses to global change do not emerge from empirical data, Nature Ecology & Evolution, 4, 1502, 10.1038/s41559-020-1256-9 James, 2001, Our evolving conceptual model of the coastal eutrophication problem, Mar. Ecol. Prog. Ser., 210, 223, 10.3354/meps210223 Jarre, 2008, Knowledge-based systems as decision support tools in an ecosystem approach to fisheries: comparing a fuzzy-logic and a rule-based approach, Prog. Oceanogr., 79, 390, 10.1016/j.pocean.2008.10.010 Jones, 2020, Bridging the gap: a strategic framework for implementing best practice guidelines in environmental modelling, Environ. Sci. Pol., 114, 533, 10.1016/j.envsci.2020.09.030 Landuyt, 2013, A review of Bayesian belief networks in ecosystem service modelling, Environ. Model. Software, 46, 1, 10.1016/j.envsoft.2013.03.011 Le Heron, 2016, Non-sectarian scenario experiments in socio-ecological knowledge building for multi-use marine environments: insights from New Zealand's Marine Futures project, Mar. Pol., 67, 10, 10.1016/j.marpol.2016.01.022 Lek, 1999, Artificial neural networks as a tool in ecological modelling, an introduction, Ecol. Model., 120, 65, 10.1016/S0304-3800(99)00092-7 Little, 2017, Unbounded boundaries and shifting baselines: estuaries and coastal seas in a rapidly changing world, Estuar. Coast Shelf Sci., 198, 311, 10.1016/j.ecss.2017.10.010 Litzow, 2016, Early warning signals, nonlinearity, and signs of hysteresis in real ecosystems, Ecosphere, 7, 10.1002/ecs2.1614 Liu, 2015, Using fuzzy logic to generate conditional probabilities in Bayesian belief networks: a case study of ecological assessment, Int. J. Environ. Sci. Technol., 12, 871, 10.1007/s13762-013-0459-x Lohrer, 2004, Bioturbators enhance ecosystem function through complex biogeochemical interactions, Nature, 431, 1092, 10.1038/nature03042 Lundquist, 2016, Science and societal partnerships to address cumulative impacts, Frontiers in Marine Science, 3, 10.3389/fmars.2016.00002 MacDiarmid, 2016, Taking Stock – the changes to New Zealand marine ecosystems since first human settlement: synthesis of major findings, and policy and management implications, New Zealand Aquatic Environment and Biodiversity Report No, 170, 48 MacIntyre, 1996, Microphytobenthos: the ecological role of the “secret garden” of unvegetated, shallow-water marine habitats. I. Distribution, abundance and primary production, Estuaries, 19, 186, 10.2307/1352224 Madarasz-Smith, 2020 Mangan, 2020, Shady business: the darkening of estuaries constrains benthic ecosystem function, Mar. Ecol. Prog. Ser., 647, 33, 10.3354/meps13410 Marcot, 2012, Metrics for evaluating performance and uncertainty of Bayesian network models, Ecol. Model., 230, 50, 10.1016/j.ecolmodel.2012.01.013 Marcot, 2001, Using Bayesian belief networks to evaluate fish and wildlife population viability under land management alternatives from an environmental impact statement, For. Ecol. Manag., 153, 29, 10.1016/S0378-1127(01)00452-2 Marcot, 2006, Guidelines for developing and updating Bayesian belief networks applied to ecological modeling and conservation, Can. J. For. Res., 36, 3063, 10.1139/x06-135 Mascaro, 2020 McGlathery, 2007, Eutrophication in shallow coastal bays and lagoons: the role of plants in the coastal filter, Mar. Ecol. Prog. Ser., 348, 1, 10.3354/meps07132 Moon, 2019, Mental models for conservation research and practice, Conservation Letters, 12, 10.1111/conl.12642 Murray, 2007, Reducing model complexity for explanation and prediction, Geomorphology, 90, 178, 10.1016/j.geomorph.2006.10.020 O'Brien, 2019, After decades of stressor research in urban estuarine ecosystems the focus is still on single stressors: a systematic literature review and meta-analysis, Sci. Total Environ., 684, 753, 10.1016/j.scitotenv.2019.02.131 Pratt, 2014, Changes in ecosystem function across sedimentary gradients in estuaries, Ecosystems, 17, 182, 10.1007/s10021-013-9716-6 Pratt, 2014, Changes in ecosystem function across sedimentary gradients in estuaries, Ecosystems, 17, 182, 10.1007/s10021-013-9716-6 Pratt, 2014, The effects of short-term increases in turbidity on sandflat microphytobenthic productivity and nutrient fluxes, J. Sea Res., 92, 170, 10.1016/j.seares.2013.07.009 Schiel, 2015, Controlling inputs from the land to sea: limit-setting, cumulative impacts and ki uta ki tai, Mar. Freshw. Res., 67, 57, 10.1071/MF14295 Siwicka, 2020, Advancing approaches for understanding the nature-people link, Ecol. Complex., 44, 100877, 10.1016/j.ecocom.2020.100877 Snelder, 2020, Nitrogen loads to New Zealand aquatic receiving environments: comparison with regulatory criteria, N. Z. J. Mar. Freshw. Res., 54, 527, 10.1080/00288330.2020.1758168 Sponaugle, 2002, Predicting self-recruitment in marine populations: biophysical correlates and mechanisms, Bull. Mar. Sci., 70, 341 Stephenson, 2018, Socio-economic, technological and environmental drivers of spatio-temporal changes in fishing pressure, Mar. Pol., 88, 189, 10.1016/j.marpol.2017.11.029 Tepolt, 2020, Strong genetic structure in a widespread estuarine crab: a test of potential versus realized dispersal, J. Biogeogr., 47, 2532, 10.1111/jbi.13919 Thrush, 2003, Habitat change in estuaries: predicting broad-scale responses of intertidal macrofauna to sediment mud content, Mar. Ecol. Prog. Ser., 263, 101, 10.3354/meps263101 Thrush, 2004, Muddy waters: elevating sediment input to coastal and estuarine habitats, Front. Ecol. Environ., 2, 299, 10.1890/1540-9295(2004)002[0299:MWESIT]2.0.CO;2 Thrush, 2008, Multiple stressor effects identified from species abundance distributions: interactions between urban contaminants and species habitat relationships, J. Exp. Mar. Biol. Ecol., 366, 160, 10.1016/j.jembe.2008.07.020 Thrush, 2012, Interaction networks in coastal soft-sediments highlight the potential for change in ecological resilience, Ecol. Appl., 22, 1213, 10.1890/11-1403.1 Thrush, 2014, Experimenting with ecosystem interaction networks in search of threshold potentials in real-world marine ecosystems, Ecology, 95, 1451, 10.1890/13-1879.1 Thrush, 2016, Addressing surprise and uncertain futures in marine science, marine governance, and society, Ecol. Soc., 21, 10.5751/ES-08574-210244 Thrush, 2021, vol. 31 Uusitalo, 2007, Advantages and challenges of Bayesian networks in environmental modelling, Ecol. Model., 203, 312, 10.1016/j.ecolmodel.2006.11.033 Uusitalo, 2016, Exploring methods for predicting multiple pressures on ecosystem recovery: a case study on marine eutrophication and fisheries, Continent. Shelf Res., 121, 48, 10.1016/j.csr.2015.11.002 Villnäs, 2011, Benthic diversity gradients and shifting baselines: implications for assessing environmental status, Ecol. Appl., 21, 2172, 10.1890/10-1473.1 Wu, 2018, Managing seagrass resilience under cumulative dredging affecting light: predicting risk using dynamic Bayesian networks, J. Appl. Ecol., 55, 1339, 10.1111/1365-2664.13037 Zadeh, 2008, Is there a need for fuzzy logic?, Inf. Sci., 178, 2751, 10.1016/j.ins.2008.02.012 Zhang, 2014, Effects of sediment geochemical properties on heavy metal bioavailability, Environ. Int., 73, 270, 10.1016/j.envint.2014.08.010 zu Ermgassen, 2013, Quantifying the loss of a marine ecosystem service: filtration by the eastern oyster in US estuaries, Estuar. Coast, 36, 36, 10.1007/s12237-012-9559-y