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An adjoint data assimilation approach to diagnosis of physical and biological controls on Pseudocalanus spp. in the Gulf of Maine–Georges Bank region

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Abstract:

The underlying scientific objective here is to determine the mechanisms that control seasonal variations in the abundance of Pseudocalanus spp. in the Georges Bank–Gulf of Maine region. It is postulated that the observed distributions result from the interaction of the population dynamics with the climatological circulation. The problem is posed mathematically as a 2-D advection–diffusion–reaction equation for a scalar variable. Given an initial distribution of animals, we seek the population dynamics source term R(x,y) such that integration of the forward model will result in predictions3 that minimize the sum of squares of differences with observed concentrations at a later time. An adjoint data assimilation technique has been designed for these purposes.

This approach has been used to invert for the population dynamics associated with the transition between bimonthly (i.e. for 2 months) climatological Pseudocalanus spp. distributions derived from MARMAP data. Vertically averaged velocity and diffusivity fields diagnosed from hydrodynamical simulations of the climatological flow are specified. Solutions converge rapidly, and the procedure reduces the cost function by an order of magnitude within 50 iterations. The resulting population dynamics vary considerably in space and time, as does the balance between local tendency, physical transport and biological source terms. Generally speaking, the patterns in population dynamics are not inconsistent with current knowledge concerning potential controls such as predation and food limitation. Analysis of the solutions indicates that the Pseudocalanus spp. population centres located in the western Gulf of Maine and on Georges Bank may be self-sustaining, in contrast to prior studies which characterize the former as a source region for the latter.

Keywords: Georges Bank; Gulf of Maine; Pseudocalanus; adjoint method; data assimilation; population dynamics; zooplankton

Document Type: Original Article

DOI: https://doi.org/10.1046/j.1365-2419.1998.00066.x

Affiliations: 1: Department of Applied Ocean Physics and Engineering, Woods Hole Oceanographic Institution, Woods Hole, MA 02543, USA, 2: Thayer School of Engineering, Dartmouth College, Hanover, NH 03755, USA, 3: Program in Atmospheric and Oceanic Sciences, University of Colorado at Boulder, Boulder, CO 80309, USA, 4: Biology Department, Woods Hole Oceanographic Institution, Woods Hole, MA 02543, USA, 5: NOAA, Northeast Fisheries Science Center, 74 McGruder Road, Highlands, NJ 07732, USA

Publication date: 1998-12-01

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