This record describes, and links to a working paper produced through the Crawford School of Economics and Government at The Australian National University in Canberra. The paper analyses the economic payoffs from marine reserves using a stochastic optimal control model. The results show that even if the reserve and harvested populations face the same negative shocks, harvesting is optimal, the population is persistent and with no uncertainty over current stock size, a reserve can increase resource rents. Using actual fishery data we demonstrate that the payoffs from a reserve, and also optimum reserve size, increase the larger is the magnitude of the negative shock, the greater its frequency, and the larger its relative impact on the harvested population.

This record describes, and links to a working paper produced through the Crawford School of Economics and Government at The Australian National University in Canberra. Using data from what was once one of the world's largest capture fisheries the economic value of a marine reserve is calculated using a stochastic optimal control model with a jump diffusion process. The results show that with a stochastic environment an optimal-sized marine reserve can generate a triple payoff that (a), raises the resource rent even when harvesting is 'optimal', (b) decreases the recovery time for the biomass to return to its former state and smooths fishers' harvests and resource rents, and (c), lowers the chance of a catastrophic collapse following a negative shock.

A compilation of ocean water quality (temperature, salinity, and dissolved oxygen) data at ¼ degree spatial resolution for the entire United States Exclusive Economic Zone. The dataset is derived from the ESRI Ecological Marine Unit (EMU) dataset, which was assembled from non-supervised statistical clustering of over 52 million points from NOAA’s World Ocean Atlas (2013) WoA database, an authoritative 57 year archive of global water column data. This derived dataset is divided into three separate point shapefiles, each representing either temperature (degrees Celsius), salinity (practical salinity units), or dissolved oxygen (mg/L). Values represent a climatological average. Each shapefile is formatted such that a single point location (i.e., unique associated latitude and longitude) contains a unique column entry for a given depth interval. Depth intervals are variable from 5 m near the surface to 100 m in the deeper regions (> 2000 m) for a total of 102 depth levels. All disclaimers provided by the original dataset authors apply to this derived dataset. For detail on these disclaimers, please refer to the following reference: Sayre, R., J. Dangermond, D. Wright, S. Breyer, K. Butler, K. Van Graafeiland, M.J. Costello, P. Harris, K. Goodin, M. Kavanaugh, N. Cressie, J. Guinotte, Z. Basher, P. Halpin, M. Monaco, P. Aniello, C. Frye, D. Stephens, P. Valentine, J. Smith, R. Smith, D.P. VanSistine, J. Cress, H. Warner, C. Brown, J. Steffenson, D. Cribbs, B. Van Esch, D. Hopkins, G. Noll, S. Kopp, and C. Convis. 2017. A New Map of Global Ecological Marine Units – An Environmental Stratification Approach. Washington, DC: American Association of Geographers. 36 pages.

This record describes, and links to a working paper produced through the Crawford School of Economics and Government at The Australian National University in Canberra. Unpredictable environmental fluctuations are a major problem in fisheries. To mitigate these uncertainties, reserves are advocated to help ensure population persistence, reduce population and harvest variance and to provide a hedge against management failures. Using recent insights from the modelling of marine reserves that indicate that reserves can generate a win-win in terms of economic payoffs and ecological benefits, we propose a six-step process for managing reserves with uncertainty and argue in favour of initially establishing less than desirable reserve sizes where stakeholder resistance to reserves may be preventing their implementation.

The purpose of this project is to develop spatially discrete end-to-end models of the California Current LME, linking oceanography, biogeochemistry, food web interactions, habitat, fisheries, economics, monitoring, and management into a common model framework. This framework allows for thought experiments, including evaluation of alternate management strategies, identifying robust indicators, and assessing relative importance of different ecosystem drivers in regulating important processes. NMFS personnel are conducting this work in broad collaboration with other NOAA scientists, academics, and NGOs. The specific work entails model development, scoping issues with stakeholders and policy makers, running scenarios, and analyzing and writing up the results. Products will include peer-reviewed papers, presentations, and workshops with modelers and/or stakeholders. Management audiences include NMFS west coast regions and the PFMC. The project is an on-going, stand-alone project with no firm deadline for completion. Outputs of the ROMS model. Metadata and .nc datafile at https://www.nodc.noaa.gov/oceanacidification/data/0131198.xml Generated from Atlantis ecosystem model, version AtlantisTrunk5425. Model code from CSIRO Australia, available via SVN after contacting CSIRO staff at http://atlantis.cmar.csiro.au/.