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Stock A, Murray CC, Gregr EJ, Steenbeek J, Woodburn E, Micheli F, Christensen V, Chan KMA. Exploring multiple stressor effects with Ecopath, Ecosim, and Ecospace: Research designs, modeling techniques, and future directions. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 869:161719. [PMID: 36693571 DOI: 10.1016/j.scitotenv.2023.161719] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/26/2022] [Revised: 01/04/2023] [Accepted: 01/15/2023] [Indexed: 06/17/2023]
Abstract
Understanding the cumulative effects of multiple stressors is a research priority in environmental science. Ecological models are a key component of tackling this challenge because they can simulate interactions between the components of an ecosystem. Here, we ask, how has the popular modeling platform Ecopath with Ecosim (EwE) been used to model human impacts related to climate change, land and sea use, pollution, and invasive species? We conducted a literature review encompassing 166 studies covering stressors other than fishing mostly in aquatic ecosystems. The most modeled stressors were physical climate change (60 studies), species introductions (22), habitat loss (21), and eutrophication (20), using a range of modeling techniques. Despite this comprehensive coverage, we identified four gaps that must be filled to harness the potential of EwE for studying multiple stressor effects. First, only 12% of studies investigated three or more stressors, with most studies focusing on single stressors. Furthermore, many studies modeled only one of many pathways through which each stressor is known to affect ecosystems. Second, various methods have been applied to define environmental response functions representing the effects of single stressors on species groups. These functions can have a large effect on the simulated ecological changes, but best practices for deriving them are yet to emerge. Third, human dimensions of environmental change - except for fisheries - were rarely considered. Fourth, only 3% of studies used statistical research designs that allow attribution of simulated ecosystem changes to stressors' direct effects and interactions, such as factorial (computational) experiments. None made full use of the statistical possibilities that arise when simulations can be repeated many times with controlled changes to the inputs. We argue that all four gaps are feasibly filled by integrating ecological modeling with advances in other subfields of environmental science and in computational statistics.
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Affiliation(s)
- A Stock
- Institute for Resources, Environment and Sustainability, University of British Columbia, AERL Building, 429-2202 Main Mall, Vancouver V6T 1Z4, BC, Canada.
| | - C C Murray
- Fisheries and Oceans Canada, Institute of Ocean Sciences, 9860 West Saanich Road, Sidney, BC V8L 5T5, Canada
| | - E J Gregr
- Institute for Resources, Environment and Sustainability, University of British Columbia, AERL Building, 429-2202 Main Mall, Vancouver V6T 1Z4, BC, Canada; SciTech Environmental Consulting, Vancouver, BC, Canada
| | - J Steenbeek
- Ecopath International Initiative (EII) Research Association, Barcelona, Spain
| | - E Woodburn
- Institute for Resources, Environment and Sustainability, University of British Columbia, AERL Building, 429-2202 Main Mall, Vancouver V6T 1Z4, BC, Canada
| | - F Micheli
- Hopkins Marine Station, Oceans Department, Stanford University, Pacific Grove, CA 93950, USA; Stanford Center for Ocean Solutions, Pacific Grove, CA 93950, USA
| | - V Christensen
- Ecopath International Initiative (EII) Research Association, Barcelona, Spain; Institute for the Oceans and Fisheries, University of British Columbia, Vancouver, BC, Canada
| | - K M A Chan
- Institute for Resources, Environment and Sustainability, University of British Columbia, AERL Building, 429-2202 Main Mall, Vancouver V6T 1Z4, BC, Canada; Institute for the Oceans and Fisheries, University of British Columbia, Vancouver, BC, Canada
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Environmental assessment of proposed areas for offshore wind farms areas off southern Brazil based on ecological niche modeling and a species richness index for albatrosses and petrels. Glob Ecol Conserv 2022. [DOI: 10.1016/j.gecco.2022.e02360] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022] Open
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A Review of Modeling Approaches for Understanding and Monitoring the Environmental Effects of Marine Renewable Energy. JOURNAL OF MARINE SCIENCE AND ENGINEERING 2022. [DOI: 10.3390/jmse10010094] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
Understanding the environmental effects of marine energy (ME) devices is fundamental for their sustainable development and efficient regulation. However, measuring effects is difficult given the limited number of operational devices currently deployed. Numerical modeling is a powerful tool for estimating environmental effects and quantifying risks. It is most effective when informed by empirical data and coordinated with the development and implementation of monitoring protocols. We reviewed modeling techniques and information needs for six environmental stressor–receptor interactions related to ME: changes in oceanographic systems, underwater noise, electromagnetic fields (EMFs), changes in habitat, collision risk, and displacement of marine animals. This review considers the effects of tidal, wave, and ocean current energy converters. We summarized the availability and maturity of models for each stressor–receptor interaction and provide examples involving ME devices when available and analogous examples otherwise. Models for oceanographic systems and underwater noise were widely available and sometimes applied to ME, but need validation in real-world settings. Many methods are available for modeling habitat change and displacement of marine animals, but few examples related to ME exist. Models of collision risk and species response to EMFs are still in stages of theory development and need more observational data, particularly about species behavior near devices, to be effective. We conclude by synthesizing model status, commonalities between models, and overlapping monitoring needs that can be exploited to develop a coordinated and efficient set of protocols for predicting and monitoring the environmental effects of ME.
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Castles R, Woods F, Hughes P, Arnott J, MacCallum L, Marley S. Increasing numbers of harbour seals and grey seals in the Solent. Ecol Evol 2021; 11:16524-16536. [PMID: 34938454 PMCID: PMC8668788 DOI: 10.1002/ece3.8167] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2021] [Revised: 08/31/2021] [Accepted: 09/06/2021] [Indexed: 12/02/2022] Open
Abstract
Harbour seals (Phoca vitulina) and grey seals (Halichoerus grypus) both occur within the UK, but display regional contrasting population trends. While grey seals are typically increasing in number, harbour seals have shown varying trends in recent decades following repeated pandemics. There is a need for monitoring of regional and local populations to understand overall trends. This study utilized a 20-year dataset of seal counts from two neighboring harbours in the Solent region of south England. Generalized additive models showed a significant increase in the numbers of harbour (mean 5.3-30.5) and grey (mean 0-12.0) seals utilizing Chichester Harbour. Conversely, in Langstone Harbour there has been a slight decrease in the number of harbour seals (mean 5.3-4.0). Accompanying photographic data from 2016 to 18 supports the increase in seal numbers within Chichester Harbour, with a total of 68 harbour and 8 grey seals identified. These data also show evidence of site fidelity of harbour seals in this area, with almost a quarter of animals resighted within the past three years. Overall, this long-term study indicates an increasing number of both harbour and grey seals within the Solent. However, more research is required to identify the drivers of this trend.
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Affiliation(s)
- Robyne Castles
- Institute of Marine SciencesUniversity of PortsmouthPortsmouthUK
| | - Fiona Woods
- Institute of Marine SciencesUniversity of PortsmouthPortsmouthUK
| | | | | | | | - Sarah Marley
- Institute of Marine SciencesUniversity of PortsmouthPortsmouthUK
- Scotland's Rural College (SRUC), Craibstone EstateAberdeenScotland
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Coles D, Angeloudis A, Greaves D, Hastie G, Lewis M, Mackie L, McNaughton J, Miles J, Neill S, Piggott M, Risch D, Scott B, Sparling C, Stallard T, Thies P, Walker S, White D, Willden R, Williamson B. A review of the UK and British Channel Islands practical tidal stream energy resource. Proc Math Phys Eng Sci 2021; 477:20210469. [PMID: 35153596 PMCID: PMC8564615 DOI: 10.1098/rspa.2021.0469] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2021] [Accepted: 10/06/2021] [Indexed: 11/12/2022] Open
Abstract
This review provides a critical, multi-faceted assessment of the practical contribution tidal stream energy can make to the UK and British Channel Islands future energy mix. Evidence is presented that broadly supports the latest national-scale practical resource estimate, of 34 TWh/year, equivalent to 11% of the UK's current annual electricity demand. The size of the practical resource depends in part on the economic competitiveness of projects. In the UK, 124 MW of prospective tidal stream capacity is currently eligible to bid for subsidy support (MeyGen 1C, 80 MW; PTEC, 30 MW; and Morlais, 14 MW). It is estimated that the installation of this 124 MW would serve to drive down the levelized cost of energy (LCoE), through learning, from its current level of around 240 £ / MWh to below 150 £ / MWh , based on a mid-range technology learning rate of 17%. Doing so would make tidal stream cost competitive with technologies such as combined cycle gas turbines, biomass and anaerobic digestion. Installing this 124 MW by 2031 would put tidal stream on a trajectory to install the estimated 11.5 GW needed to generate 34 TWh/year by 2050. The cyclic, predictable nature of tidal stream power shows potential to provide additional, whole-system cost benefits. These include reductions in balancing expenditure that are not considered in conventional LCoE estimates. The practical resource is also dependent on environmental constraints. To date, no collisions between animals and turbines have been detected, and only small changes in habitat have been measured. The impacts of large arrays on stratification and predator-prey interaction are projected to be an order of magnitude less than those from climate change, highlighting opportunities for risk retirement. Ongoing field measurements will be important as arrays scale up, given the uncertainty in some environmental and ecological impact models. Based on the findings presented in this review, we recommend that an updated national-scale practical resource study is undertaken that implements high-fidelity, site-specific modelling, with improved model validation from the wide range of field measurements that are now available from the major sites. Quantifying the sensitivity of the practical resource to constraints will be important to establish opportunities for constraint retirement. Quantification of whole-system benefits is necessary to fully understand the value of tidal stream in the energy system.
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Affiliation(s)
- Daniel Coles
- School of Engineering, Computing and Mathematics, University of Plymouth, Plymouth PL4 8AA, UK
| | - Athanasios Angeloudis
- School of Engineering, Institute for Infrastructure and the Environment, The University of Edinburgh, Edinburgh EH8 9YL, UK
| | - Deborah Greaves
- School of Engineering, Computing and Mathematics, University of Plymouth, Plymouth PL4 8AA, UK
| | - Gordon Hastie
- Sea Mammal Research Unit, Scottish Oceans Institute, University of St Andrews, St Andrews KY16 8LB, UK
| | - Matthew Lewis
- School of Ocean Sciences, Bangor University, Menai Bridge LL59 5AB, UK
| | - Lucas Mackie
- Department of Earth Science and Engineering, Imperial College London, London SW7 2AZ, UK
| | - James McNaughton
- Department of Engineering Science, University of Oxford, Oxford OX1 3PJ, UK
| | - Jon Miles
- School of Engineering, Computing and Mathematics, University of Plymouth, Plymouth PL4 8AA, UK
| | - Simon Neill
- School of Ocean Sciences, Bangor University, Menai Bridge LL59 5AB, UK
| | - Matthew Piggott
- Department of Earth Science and Engineering, Imperial College London, London SW7 2AZ, UK
| | - Denise Risch
- The Scottish Association for Marine Science, Oban PA37 1QA, UK
| | - Beth Scott
- School of Biological Sciences, University of Aberdeen, Aberdeen AB24 2TZ, UK
| | - Carol Sparling
- Sea Mammal Research Unit, Scottish Oceans Institute, University of St Andrews, St Andrews KY16 8LB, UK
| | - Tim Stallard
- Department of Mechanical, Civil and Aerospace Engineering, University of Manchester, Manchester M1 3BB, UK
| | - Philipp Thies
- Renewable Energy Group, CEMPS, University of Exeter, Penryn Campus, Penryn TR10 9FE, UK
| | - Stuart Walker
- Renewable Energy Group, CEMPS, University of Exeter, Penryn Campus, Penryn TR10 9FE, UK
| | - David White
- School of Engineering, University of Southampton, Southampton SO17 1BJ, UK
| | - Richard Willden
- Department of Engineering Science, University of Oxford, Oxford OX1 3PJ, UK
| | - Benjamin Williamson
- Environmental Research Institute, North Highland College, University of the Highlands and Islands, Thurso KW14 7EE, UK
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Potential Environmental Effects of Marine Renewable Energy Development—The State of the Science. JOURNAL OF MARINE SCIENCE AND ENGINEERING 2020. [DOI: 10.3390/jmse8110879] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Marine renewable energy (MRE) harnesses energy from the ocean and provides a low-carbon sustainable energy source for national grids and remote uses. The international MRE industry is in the early stages of development, focused largely on tidal and riverine turbines, and wave energy converters (WECs), to harness energy from tides, rivers, and waves, respectively. Although MRE supports climate change mitigation, there are concerns that MRE devices and systems could affect portions of the marine and river environments. The greatest concern for tidal and river turbines is the potential for animals to be injured or killed by collision with rotating blades. Other risks associated with MRE device operation include the potential for turbines and WECs to cause disruption from underwater noise emissions, generation of electromagnetic fields, changes in benthic and pelagic habitats, changes in oceanographic processes, and entanglement of large marine animals. The accumulated knowledge of interactions of MRE devices with animals and habitats to date is summarized here, along with a discussion of preferred management methods for encouraging MRE development in an environmentally responsible manner. As there are few devices in the water, understanding is gained largely from examining one to three MRE devices. This information indicates that there will be no significant effects on marine animals and habitats due to underwater noise from MRE devices or emissions of electromagnetic fields from cables, nor changes in benthic and pelagic habitats, or oceanographic systems. Ongoing research to understand potential collision risk of animals with turbine blades still shows significant uncertainty. There has been no significant field research undertaken on entanglement of large animals with mooring lines and cables associated with MRE devices.
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Abhinav KA, Collu M, Benjamins S, Cai H, Hughes A, Jiang B, Jude S, Leithead W, Lin C, Liu H, Recalde-Camacho L, Serpetti N, Sun K, Wilson B, Yue H, Zhou BZ. Offshore multi-purpose platforms for a Blue Growth: A technological, environmental and socio-economic review. THE SCIENCE OF THE TOTAL ENVIRONMENT 2020; 734:138256. [PMID: 32470664 DOI: 10.1016/j.scitotenv.2020.138256] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/04/2020] [Revised: 03/25/2020] [Accepted: 03/25/2020] [Indexed: 06/11/2023]
Abstract
"Blue Growth" and "Blue Economy" is defined by the World Bank as: "the sustainable use of ocean resources for economic growth, improved livelihoods and jobs, while preserving the health of ocean ecosystem". Multi-purpose platforms (MPPs) can be defined as offshore platforms serving the needs of multiple offshore industries (energy and aquaculture), aim at exploiting the synergies and managing the tensions arising when closely co-locating systems from these industries. Despite a number of previous projects aimed at assessing, from a multidisciplinary point of view, the feasibility of multipurpose platforms, it is here shown that the state-of-the-art has focused mainly on single-purpose devices, and adopting a single discipline (either economic, or social, or technological, or environmental) approach. Therefore, the aim of the present study is to provide a multidisciplinary state of the art review on, whenever possible, multi-purpose platforms, complementing it with single-purpose and/or single discipline literature reviews when not possible. Synoptic tables are provided, giving an overview of the multi-purpose platform concepts investigated, the numerical approaches adopted, and a comprehensive snapshot classifying the references discussed by industry (offshore renewables, aquaculture, both) and by aspect (technological, environmental, socio-economic). The majority of the multi-purpose platform concepts proposed are integrating only multiple offshore renewable energy devices (e.g. hybrid wind-wave), with only few integrating also aquaculture systems. MPPs have significant potential in economizing CAPEX and operational costs for the offshore energy and aquaculture industry by means of concerted spatial planning and sharing of infrastructure.
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Affiliation(s)
- K A Abhinav
- Naval Architecture, Ocean & Marine Engineering, University of Strathclyde, Glasgow, UK
| | - Maurizio Collu
- Naval Architecture, Ocean & Marine Engineering, University of Strathclyde, Glasgow, UK.
| | - Steven Benjamins
- Scottish Association for Marine Science, Scottish Marine Institute, Oban PA37 1QA, UK
| | - Huiwen Cai
- Zhejiang Ocean University, Changzhi Island, Zhoushan, Zhejiang, China
| | - Adam Hughes
- Scottish Association for Marine Science, Scottish Marine Institute, Oban PA37 1QA, UK
| | - Bo Jiang
- National Ocean Technology Center, No. 219, West Jieyuan Road, Tianjin, China
| | | | - William Leithead
- Electronic and Electrical Engineering, University of Strathclyde, Glasgow, UK
| | - Cui Lin
- National Ocean Technology Center, No. 219, West Jieyuan Road, Tianjin, China
| | - Hongda Liu
- College of Automation, Harbin Engineering University, Harbin 150001, China
| | | | - Natalia Serpetti
- Scottish Association for Marine Science, Scottish Marine Institute, Oban PA37 1QA, UK
| | - Ke Sun
- College of Shipbuilding Engineering, Harbin Engineering University, Harbin 150001, China
| | - Ben Wilson
- Scottish Association for Marine Science, Scottish Marine Institute, Oban PA37 1QA, UK
| | - Hong Yue
- Electronic and Electrical Engineering, University of Strathclyde, Glasgow, UK
| | - Bin-Zhen Zhou
- College of Shipbuilding Engineering, Harbin Engineering University, Harbin 150001, China
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Püts M, Taylor M, Núñez-Riboni I, Steenbeek J, Stäbler M, Möllmann C, Kempf A. Insights on integrating habitat preferences in process-oriented ecological models – a case study of the southern North Sea. Ecol Modell 2020. [DOI: 10.1016/j.ecolmodel.2020.109189] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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Di Tullio GR, Mariani P, Benassai G, Di Luccio D, Grieco L. Sustainable use of marine resources through offshore wind and mussel farm co-location. Ecol Modell 2018. [DOI: 10.1016/j.ecolmodel.2017.10.012] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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Villasante S, Arreguín-Sánchez F, Heymans J, Libralato S, Piroddi C, Christensen V, Coll M. Modelling marine ecosystems using the Ecopath with Ecosim food web approach: New insights to address complex dynamics after 30 years of developments. Ecol Modell 2016. [DOI: 10.1016/j.ecolmodel.2016.04.017] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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