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SEAMANCORE: A spatially explicit simulation model for assisting the local MANagement of COral REefs. Ecol Modell 2018. [DOI: 10.1016/j.ecolmodel.2018.05.026] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
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Bumbeer J, da Rocha RM, Bornatowski H, Robert MDC, Ainsworth C. Predicting impacts of lionfish (Pterois volitans) invasion in a coastal ecosystem of southern Brazil. Biol Invasions 2017. [DOI: 10.1007/s10530-017-1625-8] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
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Weijerman M, Fulton EA, Kaplan IC, Gorton R, Leemans R, Mooij WM, Brainard RE. An Integrated Coral Reef Ecosystem Model to Support Resource Management under a Changing Climate. PLoS One 2015; 10:e0144165. [PMID: 26672983 PMCID: PMC4682628 DOI: 10.1371/journal.pone.0144165] [Citation(s) in RCA: 32] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2015] [Accepted: 11/13/2015] [Indexed: 11/19/2022] Open
Abstract
Millions of people rely on the ecosystem services provided by coral reefs, but sustaining these benefits requires an understanding of how reefs and their biotic communities are affected by local human-induced disturbances and global climate change. Ecosystem-based management that explicitly considers the indirect and cumulative effects of multiple disturbances has been recommended and adopted in policies in many places around the globe. Ecosystem models give insight into complex reef dynamics and their responses to multiple disturbances and are useful tools to support planning and implementation of ecosystem-based management. We adapted the Atlantis Ecosystem Model to incorporate key dynamics for a coral reef ecosystem around Guam in the tropical western Pacific. We used this model to quantify the effects of predicted climate and ocean changes and current levels of current land-based sources of pollution (LBSP) and fishing. We used the following six ecosystem metrics as indicators of ecosystem state, resilience and harvest potential: 1) ratio of calcifying to non-calcifying benthic groups, 2) trophic level of the community, 3) biomass of apex predators, 4) biomass of herbivorous fishes, 5) total biomass of living groups and 6) the end-to-start ratio of exploited fish groups. Simulation tests of the effects of each of the three drivers separately suggest that by mid-century climate change will have the largest overall effect on this suite of ecosystem metrics due to substantial negative effects on coral cover. The effects of fishing were also important, negatively influencing five out of the six metrics. Moreover, LBSP exacerbates this effect for all metrics but not quite as badly as would be expected under additive assumptions, although the magnitude of the effects of LBSP are sensitive to uncertainty associated with primary productivity. Over longer time spans (i.e., 65 year simulations), climate change impacts have a slight positive interaction with other drivers, generally meaning that declines in ecosystem metrics are not as steep as the sum of individual effects of the drivers. These analyses offer one way to quantify impacts and interactions of particular stressors in an ecosystem context and so provide guidance to managers. For example, the model showed that improving water quality, rather than prohibiting fishing, extended the timescales over which corals can maintain high abundance by at least 5–8 years. This result, in turn, provides more scope for corals to adapt or for resilient species to become established and for local and global management efforts to reduce or reverse stressors.
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Affiliation(s)
- Mariska Weijerman
- Joint Institute for Marine and Atmospheric Research, University of Hawaii at Manoa, Honolulu, Hawaii, United States of America
- Environmental Systems Analysis Group, Wageningen University, Wageningen, Netherlands
- Pacific Island Fisheries Science Centre, NOAA Fisheries, Honolulu, Hawaii, United States of America
- * E-mail:
| | | | - Isaac C. Kaplan
- Northwest Fisheries Science Centre, NOAA Fisheries, Seattle, Washington, United States of America
| | - Rebecca Gorton
- Oceans and Atmosphere Flagship, CSIRO, Hobart, Tasmania, Australia
| | - Rik Leemans
- Environmental Systems Analysis Group, Wageningen University, Wageningen, Netherlands
| | - Wolf M. Mooij
- Department of Aquatic Ecology, Netherlands Institute of Ecology (NIOO-KNAW), Wageningen, Netherlands
- Aquatic Ecology and Water Quality Management Group, Wageningen University, Wageningen, Netherlands
| | - Russell E. Brainard
- Pacific Island Fisheries Science Centre, NOAA Fisheries, Honolulu, Hawaii, United States of America
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Suprenand PM, Drexler M, Jones DL, Ainsworth CH. Strategic assessment of fisheries independent monitoring programs in the gulf of Mexico. PLoS One 2015; 10:e0120929. [PMID: 25835742 PMCID: PMC4383601 DOI: 10.1371/journal.pone.0120929] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2014] [Accepted: 02/09/2015] [Indexed: 11/19/2022] Open
Abstract
This study evaluates information produced from 14 fisheries independent monitoring programs (FIM) in the Gulf of Mexico. We consider the uniqueness of information from each program and its usefulness in estimating fisheries management indices. Biomass values of 35 functional groups are extracted from an operating model (Ecospace) with a method that replicates the patterns of historic FIM samplings. Observation error is added to these data in order to create a set of pseudo data that replicate the type and quality of information obtained from FIM programs. The pseudo data were put into a separate fishery assessment model (Pella-Tomlinson) to determine management indices of each functional group (maximum sustainable yield (MSY), biomass at MSY, and fishing mortality at MSY). These indices are compared against values in Ecospace, and against previously published single-species stock assessments. We also evaluate the full suite of information derived from FIM within an ecosystem context, considering whether functional roles are over- or under-sampled, and whether sampling effort is proportional to the value of fish stocks. Results reveal that model derived fishery indices closely matched published indices for the majority of the functional groups, economic and ecological evaluation suggests that several piscivorous functional groups are under-sampled include forage base species that are likely to indirectly support fisheries for piscivores, and sampling efforts are not proportional to the value of some fish stocks. Following ecological modelling we performed statistical analyses on historic FIM catch data to identify optimal species-specific sampling months and gear-types that can be used to refine future FIM sampling efforts.
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Affiliation(s)
- Paul Mark Suprenand
- University of South Florida—College of Marine Science, 140 7 Ave S, St. Petersburg, Florida, 33701, United States of America
- Mote Marine Laboratory, 1600 Ken Thompson Parkway, Sarasota, Florida, 34236, United States of America
- * E-mail:
| | - Michael Drexler
- University of South Florida—College of Marine Science, 140 7 Ave S, St. Petersburg, Florida, 33701, United States of America
| | - David L. Jones
- University of South Florida—College of Marine Science, 140 7 Ave S, St. Petersburg, Florida, 33701, United States of America
| | - Cameron H. Ainsworth
- University of South Florida—College of Marine Science, 140 7 Ave S, St. Petersburg, Florida, 33701, United States of America
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Ainsworth CH, Mumby PJ. Coral-algal phase shifts alter fish communities and reduce fisheries production. GLOBAL CHANGE BIOLOGY 2015; 21:165-172. [PMID: 24953835 PMCID: PMC4310290 DOI: 10.1111/gcb.12667] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/18/2014] [Revised: 06/12/2014] [Accepted: 06/13/2014] [Indexed: 06/03/2023]
Abstract
Anthropogenic stress has been shown to reduce coral coverage in ecosystems all over the world. A phase shift towards an algae-dominated system may accompany coral loss. In this case, the composition of the reef-associated fish assemblage will change and human communities relying on reef fisheries for income and food security may be negatively impacted. We present a case study based on the Raja Ampat Archipelago in Eastern Indonesia. Using a dynamic food web model, we simulate the loss of coral reefs with accompanied transition towards an algae-dominated state and quantify the likely change in fish populations and fisheries productivity. One set of simulations represents extreme scenarios, including 100% loss of coral. In this experiment, ecosystem changes are driven by coral loss itself and a degree of habitat dependency by reef fish is assumed. An alternative simulation is presented without assumed habitat dependency, where changes to the ecosystem are driven by historical observations of reef fish communities when coral is lost. The coral-algal phase shift results in reduced biodiversity and ecosystem maturity. Relative increases in the biomass of small-bodied fish species mean higher productivity on reefs overall, but much reduced landings of traditionally targeted species.
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Affiliation(s)
- Cameron H Ainsworth
- College of Marine Science, University of South Florida, 140 7th, St. Petersburg, FL, 33701, USA
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Vulnerability of Coral Reef Fisheries to a Loss of Structural Complexity. Curr Biol 2014; 24:1000-5. [DOI: 10.1016/j.cub.2014.03.026] [Citation(s) in RCA: 205] [Impact Index Per Article: 20.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2013] [Revised: 01/30/2014] [Accepted: 03/10/2014] [Indexed: 11/24/2022]
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Arbault D, Rivière M, Rugani B, Benetto E, Tiruta-Barna L. Integrated earth system dynamic modeling for life cycle impact assessment of ecosystem services. THE SCIENCE OF THE TOTAL ENVIRONMENT 2014; 472:262-72. [PMID: 24291626 DOI: 10.1016/j.scitotenv.2013.10.099] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/01/2013] [Revised: 10/24/2013] [Accepted: 10/27/2013] [Indexed: 04/13/2023]
Abstract
Despite the increasing awareness of our dependence on Ecosystem Services (ES), Life Cycle Impact Assessment (LCIA) does not explicitly and fully assess the damages caused by human activities on ES generation. Recent improvements in LCIA focus on specific cause-effect chains, mainly related to land use changes, leading to Characterization Factors (CFs) at the midpoint assessment level. However, despite the complexity and temporal dynamics of ES, current LCIA approaches consider the environmental mechanisms underneath ES to be independent from each other and devoid of dynamic character, leading to constant CFs whose representativeness is debatable. This paper takes a step forward and is aimed at demonstrating the feasibility of using an integrated earth system dynamic modeling perspective to retrieve time- and scenario-dependent CFs that consider the complex interlinkages between natural processes delivering ES. The GUMBO (Global Unified Metamodel of the Biosphere) model is used to quantify changes in ES production in physical terms - leading to midpoint CFs - and changes in human welfare indicators, which are considered here as endpoint CFs. The interpretation of the obtained results highlights the key methodological challenges to be solved to consider this approach as a robust alternative to the mainstream rationale currently adopted in LCIA. Further research should focus on increasing the granularity of environmental interventions in the modeling tools to match current standards in LCA and on adapting the conceptual approach to a spatially-explicit integrated model.
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Affiliation(s)
- Damien Arbault
- Public Research Centre Henri Tudor/Resource Centre for Environmental Technologies, 6A avenue des Hauts-Fourneaux, L-4362 Esch-sur-Alzette, Luxembourg; Université de Toulouse, INSA, UPS, INP, LISBP, 135 Avenue de Rangueil, F-31077 Toulouse, France; INRA, UMR792, Laboratoire d'Ingénierie des Systèmes Biologiques et des Procédés, F-31400 Toulouse, France; CNRS, UMR5504, F-31400 Toulouse, France
| | - Mylène Rivière
- Public Research Centre Henri Tudor/Resource Centre for Environmental Technologies, 6A avenue des Hauts-Fourneaux, L-4362 Esch-sur-Alzette, Luxembourg; Université de Toulouse, INSA, UPS, INP, LISBP, 135 Avenue de Rangueil, F-31077 Toulouse, France; INRA, UMR792, Laboratoire d'Ingénierie des Systèmes Biologiques et des Procédés, F-31400 Toulouse, France; CNRS, UMR5504, F-31400 Toulouse, France
| | - Benedetto Rugani
- Public Research Centre Henri Tudor/Resource Centre for Environmental Technologies, 6A avenue des Hauts-Fourneaux, L-4362 Esch-sur-Alzette, Luxembourg
| | - Enrico Benetto
- Public Research Centre Henri Tudor/Resource Centre for Environmental Technologies, 6A avenue des Hauts-Fourneaux, L-4362 Esch-sur-Alzette, Luxembourg.
| | - Ligia Tiruta-Barna
- Université de Toulouse, INSA, UPS, INP, LISBP, 135 Avenue de Rangueil, F-31077 Toulouse, France; INRA, UMR792, Laboratoire d'Ingénierie des Systèmes Biologiques et des Procédés, F-31400 Toulouse, France; CNRS, UMR5504, F-31400 Toulouse, France
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Varkey DA, Pitcher TJ, McAllister MK, Sumaila RS. Bayesian decision-network modeling of multiple stakeholders for reef ecosystem restoration in the coral triangle. CONSERVATION BIOLOGY : THE JOURNAL OF THE SOCIETY FOR CONSERVATION BIOLOGY 2013; 27:459-469. [PMID: 23530881 DOI: 10.1111/cobi.12036] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/19/2011] [Accepted: 08/28/2012] [Indexed: 06/02/2023]
Abstract
Proposals for marine conservation measures have proliferated in the last 2 decades due to increased reports of fishery declines and interest in conservation. Fishers and fisheries managers have often disagreed strongly when discussing controls on fisheries. In such situations, ecosystem-based models and fisheries-stock assessment models can help resolve disagreements by highlighting the trade-offs that would be made under alternative management scenarios. We extended the analytical framework for modeling such trade-offs by including additional stakeholders whose livelihoods and the value they place on conservation depend on the condition of the marine ecosystem. To do so, we used Bayesian decision-network models (BDNs) in a case study of an Indonesian coral reef fishery. Our model included interests of the fishers and fishery managers; individuals in the tourism industry; conservation interests of the state, nongovernmental organizations, and the local public; and uncertainties in ecosystem status, projections of fisheries revenues, tourism growth, and levels of interest in conservation. We calculated the total utility (i.e., value) of a range of restoration scenarios. Restricting net fisheries and live-fish fisheries appeared to be the best compromise solutions under several combinations of settings of modeled variables. Results of our case study highlight the implications of alternate formulations for coral reef stakeholder utility functions and discount rates for the calculation of the net benefits of alternative fisheries management options. This case study may also serve as a useful example for other decision analyses with multiple stakeholders.
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Affiliation(s)
- Divya A Varkey
- Fisheries Centre, University of British Columbia, Vancouver, V6T1Z4, Canada.
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Weijerman M, Fulton EA, Parrish FA. Comparison of coral reef ecosystems along a fishing pressure gradient. PLoS One 2013; 8:e63797. [PMID: 23737951 PMCID: PMC3667803 DOI: 10.1371/journal.pone.0063797] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2013] [Accepted: 04/05/2013] [Indexed: 11/18/2022] Open
Abstract
Three trophic mass-balance models representing coral reef ecosystems along a fishery gradient were compared to evaluate ecosystem effects of fishing. The majority of the biomass estimates came directly from a large-scale visual survey program; therefore, data were collected in the same way for all three models, enhancing comparability. Model outputs–such as net system production, size structure of the community, total throughput, production, consumption, production-to-respiration ratio, and Finn’s cycling index and mean path length–indicate that the systems around the unpopulated French Frigate Shoals and along the relatively lightly populated Kona Coast of Hawai’i Island are mature, stable systems with a high efficiency in recycling of biomass. In contrast, model results show that the reef system around the most populated island in the State of Hawai’i, O’ahu, is in a transitional state with reduced ecosystem resilience and appears to be shifting to an algal-dominated system. Evaluation of the candidate indicators for fishing pressure showed that indicators at the community level (e.g., total biomass, community size structure, trophic level of the community) were most robust (i.e., showed the clearest trend) and that multiple indicators are necessary to identify fishing perturbations. These indicators could be used as performance indicators when compared to a baseline for management purposes. This study shows that ecosystem models can be valuable tools in identification of the system state in terms of complexity, stability, and resilience and, therefore, can complement biological metrics currently used by monitoring programs as indicators for coral reef status. Moreover, ecosystem models can improve our understanding of a system’s internal structure that can be used to support management in identification of approaches to reverse unfavorable states.
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Affiliation(s)
- Mariska Weijerman
- Joint Institute for Marine and Atmospheric Research, University of Hawai'i at Manoa, Honolulu, Hawaii, USA.
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Harvey C, Good T, Pearson S. Top–down influence of resident and overwintering Bald Eagles (Haliaeetus leucocephalus) in a model marine ecosystem. CAN J ZOOL 2012. [DOI: 10.1139/z2012-059] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Abstract
Conservation of predators presents challenges when predators affect prey populations that provide ecosystem services. Near Puget Sound, resident and overwintering populations of Bald Eagle ( Haliaeetus leucocephalus (L., 1766)) have expanded in recent decades. We modeled the potential impact of Bald Eagles on marine food-web structure. Bald Eagles caused trophic cascade dynamics through mid-level predators (seabirds) to lower trophic levels (fishes, benthic invertebrates), particularly when seabirds were more abundant in eagle diets. Resident Bald Eagles affected food-web structure more than overwintering eagles, despite the latters’ greater abundance. Predator avoidance behavior by nearshore diving birds and herbivorous birds exacerbated trophic cascade effects, but only in a narrow range of species. Variability in the number of overwintering Bald Eagles, which come to the area to feed on salmon carcasses (primarily chum salmon, Oncorhynchus keta (Walbaum in Artedi, 1792)), had little effect on the food web. Our results indicate that Bald Eagles are important to marine food-web structure, owing to their high consumption rates and the high consumption rates of their seabird prey, but uncertainty about eagle diets limits our full understanding of their impact. In systems where Bald Eagles affect large seabird breeding colonies, their role in food-web structure is likely greater.
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Affiliation(s)
- C.J. Harvey
- Conservation Biology Division, Northwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, 2725 Montlake Boulevard East, Seattle, WA 98112, USA
| | - T.P. Good
- Conservation Biology Division, Northwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, 2725 Montlake Boulevard East, Seattle, WA 98112, USA
| | - S.F. Pearson
- Washington Department of Fish and Wildlife, Wildlife Science Division, 600 Capitol Way North, Olympia, WA 98501, USA
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Mapping Fish Community Variables by Integrating Field and Satellite Data, Object-Based Image Analysis and Modeling in a Traditional Fijian Fisheries Management Area. REMOTE SENSING 2011. [DOI: 10.3390/rs3030460] [Citation(s) in RCA: 39] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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Ainsworth CH, Kaplan IC, Levin PS, Mangel M. A statistical approach for estimating fish diet compositions from multiple, data sources: Gulf of California case study. ECOLOGICAL APPLICATIONS : A PUBLICATION OF THE ECOLOGICAL SOCIETY OF AMERICA 2010; 20:2188-2202. [PMID: 21265451 DOI: 10.1890/09-0611.1] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/30/2023]
Abstract
Trophic ecosystem models are one promising tool for providing ecosystem-based management advice. Diet and interaction rate parameters are critical in defining the behavior of these models, and will greatly influence any predictions made in response to management perturbations. However, most trophic ecosystem models must rely on a patchwork of data availability and must contend with knowledge gaps and poor quantification of uncertainty. Here we present a statistical method for combining diet information from field samples and literature to describe trophic relationships at the level of functional groups. In this example, original fieldwork in the northern Gulf of California, Mexico, provides gut content data for targeted and untargeted fish species. The field data are pooled with diet composition information from FishBase, an online data repository. Diet information is averaged across stomachs to represent an average predator, and then the data are bootstrapped to generate likelihood profiles. These are fit to a Dirichlet function, and from the resulting marginal distributions, maximum-likelihood estimates are generated with confidence intervals representing the likely contribution to diet for each predator-prey combination. We characterize trophic linkages into two broad feeding guilds, pelagic and demersal feeders, and explore differentiation within those guilds. We present an abbreviated food web for the northern Gulf of California based on the results of this study. This food web will form the basis of a trophic dynamic model. Compared to the common method of averaging diet compositions across predators, this statistical approach is less influenced by the presence of long tails in the distributions, which correspond to rare feeding events, and is therefore better suited to small data sets.
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Affiliation(s)
- Cameron H Ainsworth
- Marine Resources Assessment Group (MRAG) Americas Inc., Northwest Fisheries Science Center (NWFSC-NOAA), 2725 Montlake Blvd. E., Seattle, Washington 98112, USA.
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Guénette S, Hill RL. A trophic model of the coral reef ecosystem of La Parguera, Puerto Rico: synthesizing fisheries and ecological data. CARIBB J SCI 2009. [DOI: 10.18475/cjos.v45i2.a17] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
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Ainsworth C, Pitcher T, Heymans J, Vasconcellos M. Reconstructing historical marine ecosystems using food web models: Northern British Columbia from Pre-European contact to present. Ecol Modell 2008. [DOI: 10.1016/j.ecolmodel.2008.05.005] [Citation(s) in RCA: 34] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
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