Award: OCE-1041678

The primary outcomes of this research are: (1) an expanded and enhanced global database of open access information on fish population dynamics; (2) a better understanding of the role of regime shifts in driving changes in fish populations; (3) identification of the factors that determine how rapidly fish populations recover from depletion. The RAM Legacy Stock Assessment Database is a global repository of information on fish population dynamics. Since the earliest version of the database was released in 2009, it has supported 23 peer-reviewed publications. An updated version of the database was developed as part of this NSF CAMEO project and is freely available at: http://ramlegacy.org/ The RAM Legacy database is rapidly becoming a critical resource for researchers hoping to understand fish population changes or the effectiveness of different fishery management strategies through a data-driven comparison of multiple fish populations. Use of the database has already broadened well beyond our own research group. There is already one paper in revision and several others in preparation that are based on the RAM Legacy Database, but do not include any of our group as co-authors. It has long been known that fish populations, even in the absence of fishing, do not stay at a constant equilibrium population size. Changes in productivity (essentially the amount a population grows or shrinks in the absence of fishing) from year to year were known to occur, but generally believed to be small compared to the changes in productivity that result when fishing reduces the population size. Our research conducted under this NSF CAMEO grant and published in the Proceedings of the National Academy of Sciences (Vert-pre et al. 2013) has established that changes in fish productivity come in alternating multi-year periods of high and low productivity. In fact, these "productivity regime shifts" better explain fluctuations in fish populations than do the mathematical models typically used by fishery management organizations. As a consequence, the predicted increase in fish productivity from reducing fishing rates and allowing populations to rebuild is far from guaranteed. Perhaps more importantly, fishing rates that proved to be sustainable during a period of high productivity can may be unsustainably high during periods of low productivity. Detecting these productivity regime shifts in time to adjust fishing rates remains a critical scientific challenge. Analysis of fish populations in the RAM Legacy database has also shed light on the process of recovery for depleted fish populations. In paper published in Science (Neubauer et al. 2013), we showed that marine fish populations are surprisingly resilient to overfishing and can generally rebuild to sustainable levels within a decade or so, if fishing is substantially reduced at the first signs of overexploitation. Unfortunately, globally, we don't have a good track record of making necessary fishing cuts when depletion is first recognized. Of 62 currently depleted stocks, less than a quarter are fished below rates needed for rebuilding. The findings show that if we don't detect depleted fish populations early and respond quickly with appropriate reductions in catch, then our options become very poor. We're left with either drastic reductions in catch that have severe economic and social consequences or slow and uncertain recovery. Last Modified: 02/07/2014 Submitted by: Olaf P Jensen