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Oyster Population/Biomass/Variance Estimates for the Maryland Portion of Chesapeake Bay 1994 – 2006. Linda Barker Maryland DNR Fisheries Service November 29, 2007 AFS Conference. Chesapeake Bay 2000 Agreement. Baseline: 1994 level of abundance Goal: 10-fold increase by 2010
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Oyster Population/Biomass/Variance Estimates for theMaryland Portion of Chesapeake Bay 1994 – 2006 Linda Barker Maryland DNR Fisheries Service November 29, 2007 AFS Conference
Chesapeake Bay 2000 Agreement • Baseline: 1994 level of abundance • Goal: 10-fold increase by 2010 • Indicator: Annual biomass estimate of small & market size oysters
Indicator Timeline • Developed in: 2000 • Original estimates: 1994-2000 • Updated: 2001, 2002 • Documented: 2007 • Variance estimate: 2007 • 2007 update: 1994-2006 w/variance
Methods: Population/Biomass Calculations Area x Density = Oysters Oysters x Weight = Biomass
Methods: Area Spatial BasisTemporal Basis 8 basins values constant 1994-2006 Habitat Surveys Yates (1906-1911) MBBS (1976-1983) Md DNR COL (1999-2000) High Quality HabitatLow Quality Habitat 71% decline from MBBS 73% decline from MBBS 91% decline from Yates 89% decline from Yates Shell plantings < 5 years old 60 to 1,800 acres/basin 1,000 to 12,000 acres/basin
Methods: Density On High Quality Habitat From DNR Fall Survey (annual values) • Observed value: oysters/bushel • Transformed to: oysters/acre ( ~750x ) Hatchery seed plantings not included On Low Quality Habitat Basis is undocumented Value changed in 2002 (to reflect drought?) • 1994-2001 = 2.02 oysters/m2 • 2002-2006 = 0.36 oysters/m2
Methods: Biomass Biomass Biomass = Population x Weight (by size class) Total = sum for all size classes/basins Population by Size Group For 5-mm size classes Total population x rel. abundance From Md DNR Fall Survey Conversion to Biomass Jordan et al., 2002 log weight = -3.8 + 2.1 * log size
Methods: Variance For Population on HQ Habitat Density variance (oysters/bu)2 x (730 bu/ac)2 x (acres) 2 For Population on LQ Habitat none calculated
Conclusions • OPEs based on many critical assumptions • many contain error. • The data are not the problem • values at a very small spatial scale are inflated to create values at a much greater spatial scale • High variance • even so, these are underestimates! • insufficient precision to show change over time.
Recommendation • The use of an absolute estimate of abundance that has sufficient precision to show real trends in the bay-wide oyster population will require entirely different stock assessment methods, at orders of magnitude more cost. • A relative index of abundance based on observed densities may be useful.