Marine reserve effects on fishery profits : a comment on White et al. (2008)

This paper is not subject to U.S. copyright. The definitive version was published in Ecology Letters 12 (2009): E9-E11, doi:10.1111/j.1461-0248.2008.01272.x.A recent study (White et al. 2008) claimed that fishery profits will often be higher with management that employs no-take marine reserves than conventional fisheries management alone. However, this conclusion was based on the erroneous assumption that all landed fish have equal value regardless of size, and questionable assumptions regarding density-dependence. Examination of an age-structured version of the White et al. (2008) model demonstrates that their results are not robust to these assumptions. Models with more realistic assumptions generally do not indicate increased fishery yield or profits from marine reserves except for overfished stocks

William (Bill) Peterson's contributions to ocean science, management, and policy

© The Author(s), 2020. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Schwing, F. B., Sissenwine, M. J., Batchelder, H., Dam, H. G., Gomez-Gutierrez, J., Keister, J. E., Liu, H., & Peterson, J. O. William (Bill) Peterson's contributions to ocean science, management, and policy. Progress in Oceanography, 182, (2020): 102241, doi:10.1016/j.pocean.2019.102241.In addition to being an esteemed marine ecologist and oceanographer, William T. (Bill) Peterson was a dedicated public servant, a leader in the ocean science community, and a mentor to a generation of scientists. Bill recognized the importance of applied science and the need for integrated “big science” programs to advance our understanding of ecosystems and to guide their management. As the first US GLOBEC program manager, he was pivotal in transitioning the concept of understanding how climate change impacts marine ecosystems to an operational national research program. The scientific insight and knowledge generated by US GLOBEC informed and advanced the ecosystem-based management approaches now being implemented for fishery management in the US. Bill held significant leadership roles in numerous international efforts to understand global and regional ecological processes, and organized and chaired a number of influential scientific conferences and their proceedings. He was passionate about working with and training young researchers. Bill’s academic affiliations, notably at Stony Brook and Oregon State Universities, enabled him to advise, train, and mentor a host of students, post-doctoral researchers, and laboratory technicians. Under his collegial guidance they became critical independent thinkers and diligent investigators. His former students and colleagues carry on Bill Peterson’s legacy of research that helps us understand marine ecosystems and informs more effective resource stewardship and conservation

Why compare marine ecosystems?

This paper is not subject to U.S. copyright. The definitive version was published in ICES Journal of Marine Science: Journal du Conseil 67 (2010): 1-9, doi:10.1093/icesjms/fsp221.Effective marine ecosystem-based management (EBM) requires understanding the key processes and relationships controlling the aspects of biodiversity, productivity, and resilience to perturbations. Unfortunately, the scales, complexity, and non-linear dynamics that characterize marine ecosystems often confound managing for these properties. Nevertheless, scientifically derived decision-support tools (DSTs) are needed to account for impacts resulting from a variety of simultaneous human activities. Three possible methodologies for revealing mechanisms necessary to develop DSTs for EBM are: (i) controlled experimentation, (ii) iterative programmes of observation and modelling ("learning by doing"), and (iii) comparative ecosystem analysis. We have seen that controlled experiments are limited in capturing the complexity necessary to develop models of marine ecosystem dynamics with sufficient realism at appropriate scales. Iterative programmes of observation, model building, and assessment are useful for specific ecosystem issues but rarely lead to generally transferable products. Comparative ecosystem analyses may be the most effective, building on the first two by inferring ecosystem processes based on comparisons and contrasts of ecosystem response to human-induced factors. We propose a hierarchical system of ecosystem comparisons to include within-ecosystem comparisons (utilizing temporal and spatial changes in relation to human activities), within-ecosystem-type comparisons (e.g. coral reefs, temperate continental shelves, upwelling areas), and cross-ecosystem-type comparisons (e.g. coral reefs vs. boreal, terrestrial vs. marine ecosystems). Such a hierarchical comparative approach should lead to better understanding of the processes controlling biodiversity, productivity, and the resilience of marine ecosystems. In turn, better understanding of these processes will lead to the development of increasingly general laws, hypotheses, functional forms, governing equations, and broad interpretations of ecosystem responses to human activities, ultimately improving DSTs in support of EBM

Predicting Crappie Recruitment in Ohio Reservoirs with Spawning Stock Size, Larval Density, and Chlorophyll Concentrations

Stock-recruit models typically use only spawning stock size as a predictor of recruitment to a fishery. In this paper, however, we used spawning stock size as well as larval density and key environmental variables to predict recruitment of white crappies Pomoxis annularis and black crappies P. nigromaculatus, a genus notorious for variable recruitment. We sampled adults and recruits from 11 Ohio reservoirs and larvae from 9 reservoirs during 1998-2001. We sampled chlorophyll as an index of reservoir productivity and obtained daily estimates of water elevation to determine the impact of hydrology on recruitment. Akaike's information criterion (AIC) revealed that Ricker and Beverton-Holt stock-recruit models that included chlorophyll best explained the variation in larval density and age-2 recruits. Specifically, spawning stock catch per effort (CPE) and chlorophyll explained 63-64% of the variation in larval density. In turn, larval density and chlorophyll explained 43-49% of the variation in age-2 recruit CPE. Finally, spawning stock CPE and chlorophyll were the best predictors of recruit CPE (i.e., 74-86%). Although larval density and recruitment increased with chlorophyll, neither was related to seasonal water elevation. Also, the AIC generally did not distinguish between Ricker and Beverton-Holt models. From these relationships, we concluded that crappie recruitment can be limited by spawning stock CPE and larval production when spawning stock sizes are low (i.e., CPE , 5 crappies/net-night). At higher levels of spawning stock sizes, spawning stock CPE and recruitment were less clearly related. To predict recruitment in Ohio reservoirs, managers should assess spawning stock CPE with trap nets and estimate chlorophyll concentrations. To increase crappie recruitment in reservoirs where recruitment is consistently poor, managers should use regulations to increase spawning stock size, which, in turn, should increase larval production and recruits to the fishery.This research was funded by Federal Aid in Sport Fish Restoration Project F-69-P, administered jointly by the U.S. Fish and Wildlife Service and Ohio Department of Natural Resources, Division of Wildlife, and the Department of Evolution, Ecology, and Organismal Biology at Ohio State University

Diel Variations in Survey Catch Rates and Survey Catchability of Spiny Dogfish and their Pelagic Prey in the Northeast US Continental Shelf Large Marine Ecosystem

This study examines the potential uncertainty in survey biomass estimates of Spiny Dogfish Squalus acanthias in the Northeast U.S. Continental Shelf Large Marine Ecosystem (NES LME). Diel catch-per-unit-effort (CPUE) estimates are examined from the Northeast Fisheries Science Center bottom trawl surveys conducted during autumn (1963-2009) and spring (1968-2009). Influential environmental variables on survey catchability are identified for Spiny Dogfish life history stages and five pelagic prey species: Butterfish Peprilus triacanthus, Atlantic Herring Clupea harengus, shortfin squid Illex spp., longfin squid Doryteuthis spp., and Atlantic Mackerel Scomber scombrus. Daytime survey catchability was significantly higher than nighttime catchability for most species during autumn and for mature male Spiny Dogfish, shortfin squid, and longfin squid during spring in the NES LME. For most stages and species examined, breakpoint analyses identified significant increases in CPUE in the morning, peak CPUE during the day, and significant declines in CPUE in the late afternoon. Seasonal probabilities of daytime catch were largely driven by solar zenith angle for most species, with stronger trends identified during autumn. Unadjusted CPUE estimates appear to overestimate absolute abundance, with adjustments resulting in reductions in absolute abundance ranging from 41% for Spiny Dogfish to 91% for shortfin and longfin squids. These findings have important implications for Spiny Dogfish regarding estimates of population consumption of key pelagic prey species and their ecological footprint within the NES LME

Report of the Fisheries Ecology Meeting, June 8-11, 1981

An Ad Hoc Group of the Ocean Sciences Board of the Assembly of Mathematical and Physical Sciences, National Research Council, was formed in 1980 to study the constraints that impede advances in the understanding of fisheries ecology. In order to continue the discussions of the Ad Hoc Group and plan strategies or actions that might be taken to resolve the critical questions of fisheries ecology, the Woods Hole Oceanographic Institution and the National Oceanic and Atmospheric Administration sponsored a Fisheries Ecology Meeting at Woods Hole, June 8-11, 1981. The Woods Hole meeting addressed various topics related to a) fisheries ecology: the point of view of management, b) regional experience, c) fish and their environment, d) population dynamics, e) socioeconomics, f) the national environment for conducting fisheries ecology research, and g) actions that need to be undertaken.Prepared for the National Oceanic and Atmospheric Administration~ the Andrew W. Mellon Foundation, and the Pew Memorial Trust