Brazilian fishery stock assessment and management: current status and challenges

Flávia Lucena Frédou – Universidade Federal Rural de Pernambuco (Recife – Brazil)

November 5th, 2019 9:00 AM (PST): FSH 203

There is a large diversity of species and fishing gear/methods in Brazilian marine waters, given the long coast (more than 7000 km long), with different environments and a multispecies and multifleet fishery. Most of the industrial fishing fleet is concentrated in Southern Brazil, while most of the small-scale fisheries (SSF) is concentrated in the north and northeast regions (Bertrand et al., 2018), where the activity is extremely important in terms of food security and employment (over 90% of jobs in the fishery sector concentrates). Based on a multi-year Brazilian research Program REVIZEE (Avaliação do Potencial Sustentável da Zona Econômica Exclusiva do Brasil), created by the Brazilian Government in compliance with the United Nations Convention of the Law of the Sea, by the early 2000s, Brazilian fisheries far exceeded sustainable target levels in the main portion and the majority of stocks were either fully (23%) or over-exploited (33%) (MMA, 2006). Moreover, Brazilian Fisheries Statistics have not been reported since 2007, when the existing system was gradually dismantled and not replaced. Hence, the assessment and the management of the Brazilian fishery resources have been a great challenge for scientists and government.  After the Program REVIZEE ended, stocks have never been re-assessed at a national level. However, specific initiatives were established in order to assess the sustainability and conservation of some fishery resources. More recently (2010 – 2014), Brazilian aquatic resources have  been evaluated according to the IUCN Red List categories at a regional scale, in a process  leaded by the ICMBio (Instituto Chico Mendes de Conservação da Biodiversidade, Ministério do Meio Ambiente, Brazil). The red list, published in 2014 (Portaria 445), enumerated 475 aquatic species as threatened. Moreover, research initiatives funded by the Fishery and Aquaculture Secretary (Ministry of Agriculture) and CNPq (National Research Council) are in place in order to evaluate the main fishery resources of the country. This talk will review the initiatives of the Brazilian Government in assessing its stocks and the current challenge given the diversity and the data-limited nature of the national fisheries.

Quantifying Sablefish Movement and its Consequences for Fishery Management in the Northeast Pacific

Luke Rogers^1,2, Maia Kapur³, Sean Anderson¹, Brendan Connors¹, Sean Cox², Melissa Haltuch⁴, Dana Hanselman⁴

¹Fisheries and Oceans Canada

²Resource and Environmental Management, Simon Fraser University

³School of Aquatic and Fishery Sciences, University of Washington

⁴National Oceanic and Atmospheric Administration

October 22nd, 2019 9:00 AM (PST): FSH 203

The consequences of spatial mismatch between fish stocks and the scale of management often remain unknown because stock structure is difficult to observe. For transboundary stocks, the difficulty is compounded because spatial mismatch may occur at political as well as ecological boundaries. Sablefish (Anoplopoma fimbria) are a highly mobile species that support valuable commercial fisheries. While their range spans the North Pacific continental margin, Sablefish are managed as independent stocks in Alaska, British Columbia, and the US West Coast. Although differences in growth rates and size-at-maturity occur across their range, low genetic differentiation suggests Sablefish constitute a single panmictic population in the northeast Pacific. To inform Sablefish stock structure, we ask: with what annual probabilities do Sablefish move among Alaska, British Columbia, and the US West Coast; have these probabilities changed over time; and do movement patterns suggest natural divisions between stock components? We estimate average and time-varying annual Sablefish movement probabilities among management regions using a Markov movement model and four decades of mark-recapture data. We then ask, does Sablefish movement undermine the performance of current management practices in these regions; and could alternative spatial management perform better? We plan to simulate Sablefish dynamics with harvest from a delay-difference operating model under contrasting assumptions about the underlying number of stocks (1–3), number of independent management regions (1–3), degree of juvenile movement between regions (low–high), and degree of adult movement between regions (low–high). This project is ongoing—we welcome feedback particularly to make inference from the simulation analysis management-relevant.

André Punt, Margaret Siple and Tessa Francis
October 15th, 2019 2:30 PM (PST): FSH 213

Progress on evaluating approaches for determining whether bycatch levels of marine mammals are sustainable

The US National Oceanic and Atmospheric Administration’s National Marine Fisheries Service (NMFS), which administers the portions of the Marine Mammal Protection Act (MMPA) pertaining to cetaceans and most pinnipeds, evaluates the status of stocks and issues regulations for reducing incidental take (bycatch) in US commercial fisheries. Within this regulatory framework, the Potential Biological Removal (PBR) level is a reference point for managing bycatch. NMFS regulations implementing the Fish and Fish Product Import Provisions of the MMPA require that imported fish and fish products be evaluated with respect to US standards. The regulations require foreign fisheries that export fish and fish products to the US, and are identified by NOAA as having fisheries that may incur marine mammal bycatch, to adhere to bycatch monitoring and mitigation standards “comparable” to those applied to US fisheries. An Ocean Modeling Forum working group has been established to develop a set of tools to aid countries in assessing marine mammal stocks, estimating bycatch, calculating bycatch limits, and reducing total bycatch to comply with the US marine mammal bycatch standards. As part of this effort, modelling frameworks have been developed to (a) examine the performance of the PBR approach in situations that are more broad than those used in its original formulation, (b) explore how well PBR-based management will perform for the case of harbor porpoises, harbor seals and gray seals in the Icelandic bottom gillnet fishery, and (c) estimate population trajectories for South American sea lions and fur seals in the trawl and purse seine fisheries for small pelagics off Chile, given uncertainties in bycatch levels and population size. This think tank will outline progress on each of these modelling efforts.

Ingrid Spies^1
1NOAA
May 7th, 2019 10:00 (PST): FSH 203

Genetic evidence of a northward range expansion in the Eastern Bering Sea stock of Pacific cod

Abstract: Poleward species range shifts have been predicted to result from climate change, and many observations have confirmed such movement. The abundant center hypothesis predicts that range shifts will take place by movement of individuals from core habitat to marginal habitat. However, poleward shifts may also represent a homogeneous shift in distribution, northward movement of specific populations, or colonization processes at the poleward edge of the distribution. The ecosystem of the Bering Sea has been changing along with the climate, moving from an arctic to a subarctic system. Several fish species have been observed further north than previously and in increasing abundances. We examined one of these fish species, Pacific cod, in the northern Bering Sea to assess whether they migrated from another stock in the eastern Bering Sea, Gulf of Alaska, or Aleutian Islands, or whether they represent separate populations. Genetic analyses using 3,457 SNP markers indicated that non-spawning cod collected in August 2017 in the northern Bering Sea were similar to spawning stocks of cod in the eastern Bering Sea. This result suggests escalating northward movement of the large eastern Bering Sea stock of Pacific cod that may be consistent with the abundant center hypothesis.

Merrill Rudd¹ Jim Thorson^2
1Scaleability LLC
²NOAA
April 2nd, 2019 9:00 (PST): FSH 203

Spatiotemporal models of populations in stream networks

Abstract: Spatial and spatiotemporal models of stream networks are vital in the management and conservation of freshwater and anadromous fishes, often threated by terrestrial development along connected waters upstream. An ideal approach to modeling stream networks would 1) allow for spatial correlations over time or autocorrelations as a function of distance, 2) distinguish between process and observation error, and 3) overcome computational challenges to analyze large networks while estimating covariance structures. The latter two issues for estimating spatiotemporal densities are addressed using the Vector Autoregressive Spatio-Temporal (VAST) model. VAST has many features that make it an accessible and reproducible tool for single and multivariate spatiotemporal models with covariates. Previous applications have only used Gaussian Markov random fields to approximate spatial and spatiotemporal variation. We added a stream network spatial model that uses the Ornstein-Uhlenbeck process, a stochastic process that implies a child node is correlated with its parent node as a function of distance, where variation includes an exponential rate of decay in correlation between child and parent nodes and an asymptotic variance for two sites that are far apart. This presentation will provide an overview of updates to the VAST R package considering stream networks as a spatial model and preliminary results of its application for longfin eels in the Waitaki River catchment in New Zealand. The Waitaki River catchment has been heavily affected by dams, the largest of which was installed in 1948. Longfin eels are a cultural keystone species for Maori. In the face of increasing terrestrial development, impacts of dams, and continued harvest, spatiotemporal modeling including multiple types of information is vital for estimating longfin eel densities. This work will contribute to ongoing studies of New Zealand longfin eel populations and later other freshwater species. This modeling approach is also being applied to model juvenile and adult densities of coho salmon in Oregon. This study could benefit from the perspectives of scientists with stream network modeling experience or spatiotemporal modeling experience in other contexts.

Maia Kapur^1
1SAFS
April 2nd, 2019 9:00 (PST): FSH 203

Sneaking up on a well specified model

Abstract: The sustainable exploitation of marine resources requires management that is based on sound scientific guidance. One of the most important goals of stock assessment modelling is to accurately characterize the important systems model processes by either specifying the correct relationships and by estimating the parameters governing those processes. A well-designed approach to model structuring is needed to ensure good representation of the systems processes. Improper structuring of a model is the result of misspecification of either observation or systems processes. For this work, I plan to use simulation methods to evaluate improvement in assessment model performance (based on a recent Hake assessment) with sequential elimination of a series of known misspecifications of both observation and systems model processes. This talk will go through our proposed methodology and ask for feedback from the audience on how to best execute performance testing and present our findings.

Cole Monnahan^1
1SAFS
February 26th, 2019 9:00 (PST): FSH 203

Overcoming long Bayesian run times in integrated fisheries stock assessments

Abstract: Bayesian inference is an appealing alternative to maximum likelihood estimation, but estimation can be prohibitively long for integrated fisheries stock assessments. Here, we investigated potential causes of long run times for four U.S. assessments written in AD Model Builder (ADMB), both custom built and Stock Synthesis models. Between regularization, parallel chains, and the more efficient no-U-turn sampler we found models ran thousands of times faster. In this talk, I will go into detail about the causes of slow run times, the largest of which is the effect of over-parameterization on posterior geometry and how that interacts with MCMC sampler efficiency. I will also discuss the technical details of the default Metropolis and no-U-turn samplers in ADMB and how tuning parameters can dramatically increase efficiency, all in the context of real stock assessments. Finally, I will demonstrate the new R package adnuts which presents a convenient framework for running parallel chains and exploring convergence with the interactive tool ShinyStan. Throughout I will contrast ADMB’s (and TMB’s) Bayesian capabilities with the popular program Stan. The goal of this informal, hands-on talk will be for assessment scientists to leave with the knowledge and tools necessary to try Bayesian inference on their assessments. Participants wishing to follow along should have a model build with ADMB v12.0 and the github.com development branch of adnuts installed.

Grant Adams^1
1SAFS
January 29th, 2019 9:00 (PST): FSH 203

Sensitivity of multispecies statistical catch-at-age models to inclusion of annual recruitment deviations as random effects and diet estimation

The development of analytical tools that address ecosystem based fisheries management (EBFM) needs is essential for rationally managing fisheries resources in the face of changing climate and ecological processes. Multispecies statistical catch-at-age (MSCAA) models are one tool of particular value for providing both tactical and strategic EBFM advice by accounting for trade-offs among fisheries for multiple species. MSCAA links multiple single-species age-structured models via predator-prey interactions conditioned on bioenergetics and diet information. Within MSCAA models, annual recruitment are commonly estimated as deviations away from a mean process and predator-prey interactions conditioned on predator-prey suitability. For most MSCAA models, penalized likelihood approaches have been used to constrain recruitment deviations away from zero and suitability assumed to be known. Such an approach requires the a priori selection of recruitment variance and limit uncertainty in predation mortality. However, this can limit our understanding of the variation in recruitment and extent of predation and may also have an impact on estimates of biological reference points. Alternatively, recruitment deviations can be treated as random effects and suitability estimated., allowing for the estimation of variance terms and annual predation mortality. Using a MSCAA developed for groundfish in the Bering Sea (CEATTLE for climate-enhanced, age-based model with temperature-specific trophic linkages and energetics), I evaluate the sensitivity of MSCAA models to the incorporation of annual recruitment deviations as random effects and suitability estimation. This research addresses the need for a greater understanding of parameter uncertainty in MSCAA models prior to further implementation in fisheries management.

Noble Hendrix¹ and Erica Fleishman²

¹QEDA Consulting
²Dept. of Fish, Wildlife and Conservation at Colorado State University
October 30, 2018 9:00 (PST): FSH 203

Modeling the spatio-temporal dynamics of one little bugger – delta smelt in the San Francisco Estuary

Delta smelt are an annual estuarine fish that complete their life-cycle in the San Francisco Estuary. They were listed as threatened under the Endangered Species Act in 1993 and have continued to decline since then. As a result, there is interest in determining how management of water flow through the estuary may affect the population dynamics of the species. Focus has turned to factors that affect survival and movement in the fall and in the spring, and here we are interested in evaluating the fall. We have constructed a spatially explicit model that estimates survival and movement as functions of covariates in four regions of the estuary. This framework allows an explicit examination of hypotheses regarding the role of environmental drivers on these processes. The model also includes the probability of capture for spatial replicates within each region. We have developed the model in Stan and have fit to simulated data with well-behaved statistical properties; however, the catch data are zero-inflated and over dispersed. We investigate several alternatives including zero inflated Poisson and zero inflated negative binomial for the likelihood and present the results of fitting several conceptual models developed from recovery plans. We are interested in evaluating approaches for model averaging and model goodness of fit. With respect to the latter, we are developing metrics that highlight spatio-temporal patterns in model weaknesses to help generate the next round of conceptual models.

Margaret Siple^1
1SAFS
October 16, 2018 9:00 (PST): FSH 203

Simulating marine mammal bycatch impacts in data-poor situations

Simulation can be used to explore the expected outcomes of management actions when data on marine mammal abundance and bycatch are sparse or unavailable. For governments interested in evaluating their marine mammal bycatch with respect to regulations or instituting new changes (e.g., gear modifications or new bycatch limits), simulation can be a useful tool for exploring how marine mammal populations might respond to these actions. One of the work products of the Ocean Modeling Forum’s Marine Mammal Bycatch Working Group will be a tool that allows users to visually explore the impacts of different bycatch management actions on marine mammal abundance, given limited information about the fishery or the marine mammal of interest (i.e., abundance, current bycatch rate, and productivity).

The tool allows users to compare outcomes among various bycatch and starting abundance scenarios. It operates at different levels of complexity, using inputs chosen by the user in an age-structured model that projects abundance into the future, given estimates for abundance and bycatch rates. Users can apply specific life history parameters or choose from a list of life history types (humpback whale, bottlenose dolphin, bowhead whale, pinniped, or the ‘generic’ life history type used in the original simulations for PBR). Outputs include abundance trajectories under different management scenarios, and performance with respect to management objectives.

In the future, the tool will also be able to be used to find the strategy most likely to meet certain management objectives and explore the impacts of additional mortality besides bycatch (e.g., ship strikes). This talk will demonstrate the tool’s current capabilities and discuss some of the expansions to the current model, including ways to incorporate non-bycatch mortality and how to “back-calculate” strategies based on management objectives. I would also like to solicit feedback on some of the options for visualizing outputs.