A global movement toward an ecosystem approach to management of marine resources

Sherman, Kenneth; Sissenwine, Michael P.; Christensen, Villy; Duda, Alfred M.; Hempel, Gotthilf; Ibe, Chidi A.; Levin, Simon A.; Lluch-Belda, Daniel; Matishov, Gennady G; McGlade, Jacqueline; O'Toole, Malcolm; Seitzinger, Sybil P.; Serra, Rodolfo; Skjoldal, Hein Rune; Tang, Qisheng; Thulin, Jan; Vandeweerd, Veerle; Zwanenburg, Kees C.T.

doi:10.3354/meps300275

Cited by 82 publications

(45 citation statements)

References 16 publications

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“…Catch and PP data were obtained for 14 out of the 66 LMEs defined by Sherman et al (2005). Selected LMEs belong to boreal temperate shelves and major upwelling systems (i.e.…”

Section: Methodsmentioning

confidence: 99%

“…It is within the boundaries of the 66 LMEs that major efforts are presently under way to meet the World Summit on 234 Conti & Scardi: Fisheries yield and primary productivity Sustainable Development (WSSD) deadlines, namely: (1) introducing an ecosystem approach to marine resource assessment and management by 2010, and (2) maintaining fish stock maximum sustainable yield levels by 2015. While these standards are still far from being reached, there is a general agreement on the reference space-based ecosystem unit of LMEs, for which a 5-modules strategy of assessment (productivity, fish and fisheries, pollution and ecosystem health, socioeconomics and governance) has been developed (Sherman et al 2005). In this context, the present paper proposes a focus on the first 2 modules, productivity and fisheries, even though any attempt to better understand ecosystem functioning has important outcomes on all LME strategy components.…”

Section: Resale or Republication Not Permitted Without Written Consenmentioning

confidence: 99%

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Fisheries yield and primary productivity in large marine ecosystems

Conti¹,

Scardi²

2010

Mar. Ecol. Prog. Ser.

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Primary productivity (PP) and fisheries yield were analysed in 14 large marine ecosystems (LMEs), which encompassed temperate boreal shelves and the Eastern Boundary Currents (EBCs), from 1998 to 2002. PP was estimated by means of a depth-integrated neural network model based on Sea-viewing Wide Field-of-view Sensor (SeaWiFS) data and aimed at providing conservative PP estimates. Landings records were extracted from the global spatial database provided by the Sea Around Us Project (SAUP). Correspondence analysis performed on yield data outlined the role played by different trophic levels (TLs) in LME catches. PP temporal variability was significantly and positively correlated to average trophic level of catches (TL c ) so that higher yields in less variable ecosystems were characterised by a lower TL c . From a functional perspective, high PP temporal variability was associated preferentially with demersal fishes and lower yields, while pelagic-dominated catches were harvested in conditions with lower PP variability. Primary production required (PPR) to sustain fisheries in each LME showed that the highest yield occurred in combination with moderate fishing pressure especially when TL c was intermediate to low. High fishing pressures were associated with intermediate total yields and high TL c , a condition which seemed to occur in high-latitude boreal LMEs. The %PPR and TL c were used to assess fisheries impact on ecosystems. PP model choice affects the assessment of exploitation levels, in that a more conservative estimation of PP could contribute to a more precautionary approach to fisheries management where high levels of exploitation are more easily attained. KEY WORDS: Primary productivity · Fisheries yield · Large marine ecosystems · PPR · Overexploitation Resale or republication not permitted without written consent of the publisherMar Ecol Prog Ser 410: [233][234][235][236][237][238][239][240][241][242][243][244] 2010 Pace et al. , Cury et al. 2001. Several studies pointed out that both systems act locally (e.g. Ware & Thomson 2005, Mueter et al. 2006, Mackinson et al. 2008.The shift from local to regional and global spatial scales, added to the potential effects of climate change and regime shifts, highlights the complexity that underlies marine food webs. Cyclic and punctual events, both environmental and anthropogenic, influence the structure and functioning of marine ecosystems, hindering the identification of the relative role of each driving force. Landings statistics are the main source of data for these kinds of studies, representing the only spatial and temporal large-scale data sets available for the detection of different sources of variation. Recently, Perry & Schweigert (2008) suggested that these highly aggregated data and large (often global) spatial domains may have played a key role in the identification of the general relationship between PP and fisheries yields. The primary criticism about large-scale fisheries studies is their reliance on poor quality of data: landings m...

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“…Catch and PP data were obtained for 14 out of the 66 LMEs defined by Sherman et al (2005). Selected LMEs belong to boreal temperate shelves and major upwelling systems (i.e.…”

Section: Methodsmentioning

confidence: 99%

Section: Resale or Republication Not Permitted Without Written Consenmentioning

confidence: 99%

Fisheries yield and primary productivity in large marine ecosystems

Conti¹,

Scardi²

2010

Mar. Ecol. Prog. Ser.

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“…To date, despite mandates to establish global MPA networks and large marine ecosystem management systems (Sherman et al 2005), and rapidly growing interest in EBM (McLeod & Leslie 2005;CEQ 2009), the evaluative efforts are commonly ad hoc and inappropriately scaled. Evaluation began with useful case studies of management effectiveness of MPAs (see for example White et al 2002) and LMEs (for example Cochrane et al 2009;Fanning et al 2009).…”

Section: Reassessing the Starting Point And Disciplinary Balance Of Kmentioning

confidence: 99%

“…Management recommendations are focused on maintaining large-scale ecological processes and maintaining ecosystem integrity through a consideration of connectivity of ecosystems and marine species populations. The large marine ecosystem (Sherman et al 2005) and biodiversity hotspots planning models (Conservation International 2010) are examples of management scales reliant on EBM conceptualizations. Ecological analyses of large-scale global change processes promote such scaling (Pauly et al 1998;Pandolfi et al 2003;Mora et al 2006;Worm et al 2006;Halpern et al 2008).…”

Section: Assessing Management Framework Assumptions and Tendenciesmentioning

confidence: 99%

Creating space for interdisciplinary marine and coastal research: five dilemmas and suggested resolutions

Christie

2011

Envir. Conserv.

102

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SUMMARYImportant changes are needed to disciplinary theories and methods to support interdisciplinary and integrated ocean and coastal management policies and implementation. This review argues that theories and methods should conform to a perspective that ocean management is a societal activity with diverse goals ideally informed by interdisciplinary information. The review focuses on the integrated coastal management (ICM) and marine ecosystem-based management (EBM) frameworks and the marine protected areas (MPA) management tool. It begins by suggesting that at present there is a notable imbalance in the degree of effort allocated to monitoring the ecological and social dimensions of ocean resource use and policy processes. Based on how Western society and an influential epistemic community construct 'the environment' and society's relation to the environment, natural sciences play an inordinately important role in the description of the problem and policy recommendations. The discourse advocating for a global networks of marine protected areas, without adequate consideration of society impacts and responses, represents an example of this imbalance. Rebalancing the contributions of scientific disciplines encounters various dilemmas with epistemological, methodological and sociological dimensions. The analysis concludes with suggestions for balancing ocean and coastal interdisciplinary research and reframing key issues, creating self reflexive and multidisciplinary research teams, and reworking educational programmes.

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“…While physical conditions partly explain plankton distributions, nutrient limitation, shading, competition, grazing and predation appear to also influence their distribution as they do in benthic and terrestrial environments (Vinogradov 1997, Longhurst 1998. Large Marine Ecosystems (LMEs) are a network of some 64 coastal areas selected due to their importance for resource management (Sherman et al 2005). The MEOW classification is also coastal, and it encompasses LMEs, countries' Exclusive Economic Zones (EEZ) and earlier national regions such as bioregions and ecoregions.…”

Section: Regionsmentioning

confidence: 99%

Distinguishing marine habitat classification concepts for ecological data management

Costello¹

2009

Mar. Ecol. Prog. Ser.

105

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Including ecology in biodiversity data management systems requires classifications of habitat terms that provide standard definitions and indicate their relationships. In addition to databases, a wide range of intergovernmental, conservation and fishery organizations require classifications of habitats and ecosystems to enable comparisons between areas and organize information in maps and reports. However, all of the terms used to describe habitats are concepts whose definition is context-dependent. This paper reviews the key concepts and ecological perspectives involved in classifying marine 'habitats' and 'biotopes' (habitat plus its associated species) so as to advise how they may be used in data management systems. Classifications of biotopes provide practical measures of biodiversity at the ecosystem level. As an example the habitat of a benthic invertebrate is very different in spatial scale to that of a parasite, plankton, tuna or whale. Habitats can be geophysical and/or biogenic, and may operate at different spatial scales. For example, aggregations of deepsea coral colonies <1 m in diameter may form km-scale reefs which contain other habitats (e.g. sediments, sponges). An ecosystem can be physiographically defined as a lagoon, seamount, estuary, abyssal plain or entire ocean. Different sampling methods will define different regions, such as satellite images of ocean colour, acoustic maps of the seabed, in situ sampling of water or sediment cores and maps derived from analyses of species distributions that may define biogeographic regions. Because they are sampled (and thus defined) by different methods and can operate at different spatial scales, separate classifications are recommended for (1) nekton, plankton and benthos and (2) regions (defined to suit political, geographic or management areas), seascapes (defined by topography or water mass), biotopes and guilds (e.g. based on body size, diet or sampling method). Furthermore, it is recommended to record the measurable features used to describe biotopes (e.g. depth, dominant species, substratum) and to avoid imposing a classification hierarchy where the concepts and methods of defining them are different. Indeed, one can let users create the most parsimonious classification for their purposes.KEY WORDS: Methods · Biogeography · Ocean · Biotope · Seascape · Eco-informatics · Biodiversity Resale or republication not permitted without written consent of the publisher Contribution to the Theme Section 'Conservation and management of deep-sea corals and coral reefs'OPEN PEN ACCESS CCESS

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A global movement toward an ecosystem approach to management of marine resources

Cited by 82 publications

References 16 publications

Fisheries yield and primary productivity in large marine ecosystems

Fisheries yield and primary productivity in large marine ecosystems

Creating space for interdisciplinary marine and coastal research: five dilemmas and suggested resolutions

Distinguishing marine habitat classification concepts for ecological data management

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