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Comment on "A Global Map of Human Impact on Marine Ecosystems"
Michael R. Heath
Halpern et al. (Reports, 15 February 2008, p. 948) integratedspatial data on 17 drivers of change in the oceans to map theglobal distribution of human impact. Although fishery catchesare a dominant driver, the data reflect activity while impactsoccur at different space and time scales. Failure to accountfor this spatial disconnection could lead to potentially misleadingconclusions.
Fisheries Research Services, Marine Laboratory, 375 Victoria Road, Aberdeen AB11 9DB, UK. E-mail: heathmr{at}marlab.ac.uk
As spatial planning and legislation, which has long been appliedto human activity on land, extends out into the marine environment,the need for a synthesis of the human impacts on the seas andoceans becomes ever more urgent. Thus, the initiative reportedby Halpern et al. (1) is extremely timely and welcome. However,the task is a formidable one, and the results highlight someof the challenges that still need to be overcome.
Halpern et al. (1) estimated impacts on the oceans from a rangeof human activities, including various methods of fishing thatare among the most important factors affecting the ecologicalstate of many large marine ecosystems (2, 3). Spatial disaggregations(° latitude by ° longitude) of 1999 to 2003 regionallandings data from the United Nations Food and Agriculture Organization(FAO) (4) were used as measures of fishing activity. Spatialdisaggregation was performed by the Sea Around Us Project [SAUP(5)] on the basis of various covariates of fish distribution(temperature, depth, and primary production), together witha rule-based system defining the cells accessible to nationalfishing fleets (6). The ecological pressure caused by fisherieswas assumed to be confined to catch locations, and the intensitywas measured by dividing the catch density of landed fish (tonneskm–2 in 1 km by 1 km cells) by estimates of annual primaryproduction (PP) derived from satellite remote sensing (7). Thelogic was that higher catch rates in lower productivity areasof the ocean should have a higher impact than similar catchrates in higher productivity areas. Location-specific vulnerabilityscores were then applied to translate activity measures intoimpacts.
One may worry about the precision with which the SAUP disaggregationmethod represents the spatial distributions of where the fishlanded from a region were actually caught (8) but, regardlessof any such concerns, the key problem is that the spatial footprintof the impacts may differ from the distribution of catches andaffect different ecosystems from those in which the catchingactivity occurred. Clearly, the physically destructive impactsof certain fishing gear and some of the impacts of discardedbycatch occur local to the activity. However, other major ecologicalconsequences occur at locations far removed in space and timefrom catches, depending on the biology and migratory behaviorof the species concerned. Almost all open water pelagic anddemersal fish exhibit spatial and ecosystem segregation of lifestages (larvae, juveniles, and adults) over scales ranging fromtens to thousands of kilometers, with life-cycle connectivitythrough active migration by juveniles and adults and passivetransport of eggs and larvae by ocean currents. In contrast,fisheries are generally targeted at the most commercially valuablelife stages, which are usually the adults. Removal of maturefish affects the supply of juveniles elsewhere in the system,with consequences for species richness and diversity, marinepredator populations, and food web functionality (9–11)that extend over a far greater area and range of ecosystemsthan the fishing activity itself.
The northeast Atlantic mackerel fishery (Fig. 1) provides anillustration of the generic problem. Most of the food consumptionby mackerel caught around the north of the United Kingdom occurs1000 km away in the Norwegian Sea rather than in the localityof the catches, whereas the consequences of removing matureadults will be realized far to the south in the spawning areaand in inshore waters that form the habitat for juvenile offspring.Hence, the impact of the mackerel fishery is too localized inthe analysis of Halpern et al., leading to exaggeration of thecumulative human impact on waters around the northern UnitedKingdom.
Fig. 1. Quarterly distributions (° latitude by 1° longitude) of catches from the northeast Atlantic mackerel stock for 2006 [data from (14)]. Total annual catch was 472,700 tonnes, exceeded in the northeast Atlantic only by catches of Norwegian Sea herring. Surveys of planktonic eggs show that the majority of spawning activity occurs in Q2 west and southwest of Ireland (14, 15). Tagging studies (16) show that after spawning, the majority of fish migrate 2000 km northward into the Norwegian Sea to feed during Q3, with a southward return migration during Q4 and Q1. The stock is only lightly exploited during Q2 when fish are close to the sea surface and difficult to catch. Most of the catch is taken during Q4 and Q1 when the fish are aggregated into very large schools. In 2006, 300,000 tonnes (63% of the annual total) were taken from an area of 5000 km2 off the northern United Kingdom. Although there must be local impacts due to bycatch and slippage from nets (4% of catch), the principal ecological impacts on an annual time scale must be distributed over the spatial envelope of the stock as a whole, which exceeds 250,000 km2.
[View Larger Version of this Image (48K GIF file)]
Incorporating the spatial disconnect between fishing activityand its ecological impact into integrated assessments couldbe done at a regional scale for some species using spatiallyresolved population demography models (12) to diagnose the spatialimpact of a given pattern of catches. However, more generally,there needs to be some consideration of the spatial graininessat which it is meaningful to represent the impact of fisherieson marine ecosystems, given the oceanography of a region andthe biology of species inhabiting it.
Halpern et al. (1) have assembled global data on human activityin the oceans, which is an achievement in itself, and initiateda diagnosis of cumulative impact. However, it is clear thatmore needs to be done to realistically equate the spatial characteristicsof activity to impact, especially in the case of fisheries.Although activity can, theoretically, be resolved to fine geographicscales, there are serious scientific issues regarding the thresholdof graininess below which assessments of impact are legitimate.
2. S. Jennings, M. J. Kaiser, Adv. Mar. Biol.34, 201 (1998). [CrossRef]
3. S. J. Hall, The Effects of Fishing on Marine Ecosystems and Communities (Blackwell Science, Oxford, 1999).
4. Food and Agriculture Organization, FishStat Plus: Universal software for fishery statistical time series; www.fao.org/fishery/topic/16073.
5. The Sea Around Us Project, University of British Columbia, www.seaaroundus.org.
6. R. Watson, A. Gelchu, D. Pauly, in Fisheries Impact on North Atlantic Marine Ecosystems: Catch, Effort and National and Regional Data Sets, D. Zeller, R. Watson, D. Pauly, Eds.. Fisheries Centre Research Reports 9 (2001), pp. 1–11.
7. M. J. Behrenfeld, P. G. Falkowski, Limnol. Oceanogr.42, 1 (1997).
8. The SAUP methodology (6) disaggregates regional annual fishery landings to ° spatial resolution. This is a bold attempt at a difficult task and there will always be discrepancies from reality, so the results should be used with caution. For example, the SAUP estimate of the spatial distribution of Atlantic mackerel catches since 2000 (13) fails to reflect the annually recurrent component of the fishery that occurs in the Norwegian Sea and misrepresents the distribution of catches from the northern North Sea.
14. International Council for the Exploration of the Sea, Report of the Working Group on the Assessment of Mackerel, Horse Mackerel, Sardine and Anchovy (WGMHSA) (ICES CM 2007/ACFM:31); www.ices.dk/reports/ACOM/2007/WGMHSA/WGMHSA07.pdf.
16. A. Uriarte, P. Lucio, Fish. Res.50, 129 (2001). [CrossRef]
Received for publication 5 March 2008. Accepted for publication 18 August 2008.
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Kimberly A. Selkoe, Carrie V. Kappel, Benjamin S. Halpern, Fiorenza Micheli, Caterina D'Agrosa, John Bruno, Kenneth S. Casey, Colin Ebert, Helen E. Fox, Rod Fujita, Dennis Heinemann, Hunter S. Lenihan, Elizabeth M. P. Madin, Matt Perry, Elizabeth R. Selig, Mark Spalding, Robert Steneck, Shaun Walbridge, and Reg Watson (12 September 2008) Science321 (5895), 1446c.
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REPORTS
Benjamin S. Halpern, Shaun Walbridge, Kimberly A. Selkoe, Carrie V. Kappel, Fiorenza Micheli, Caterina D'Agrosa, John F. Bruno, Kenneth S. Casey, Colin Ebert, Helen E. Fox, Rod Fujita, Dennis Heinemann, Hunter S. Lenihan, Elizabeth M. P. Madin, Matthew T. Perry, Elizabeth R. Selig, Mark Spalding, Robert Steneck, and Reg Watson (15 February 2008) Science319 (5865), 948.
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