JT (2023) The performance of model-based indices given alternative sampling strategies in a clima... more JT (2023) The performance of model-based indices given alternative sampling strategies in a climate-adaptive survey design.
Implementation of the United Nations Sustainable Development Goals requires assessments of the gl... more Implementation of the United Nations Sustainable Development Goals requires assessments of the global state of fish populations. While we have reliable estimates of stock status for fish populations accounting for approximately half of recent global catch, our knowledge of the state of the majority of the world's “unassessed” fish stocks remains highly uncertain. Numerous publications have produced estimates of the global status of these unassessed fisheries, but limited quantity and quality of data along with methodological differences have produced counterintuitive and conflicting results. Here, we show that despite numerous efforts, our understanding of the status of global fish stocks remains incomplete, even when new sources of broadly available data are added. Estimates of fish populations based primarily on catch histories on average performed 25% better than a random guess. But, on average, these methods assigned fisheries to the wrong FAO status category 57% of the time...
Canadian Journal of Fisheries and Aquatic Sciences, 2017
Estimating trends in abundance from fishery catch rates is one of the oldest endeavors in fisheri... more Estimating trends in abundance from fishery catch rates is one of the oldest endeavors in fisheries science. However, many jurisdictions do not analyze fishery catch rates due to concerns that these data confound changes in fishing behavior (adjustments in fishing location or gear operation) with trends in abundance. In response, we developed a spatial dynamic factor analysis (SDFA) model that decomposes covariation in multispecies catch rates into components representing spatial variation and fishing behavior. SDFA estimates spatiotemporal variation in fish density for multiple species and accounts for fisher behavior at large spatial scales (i.e., choice of fishing location) while controlling for fisher behavior at fine spatial scales (e.g., daily timing of fishing activity). We first use a multispecies simulation experiment to show that SDFA decreases bias in abundance indices relative to ignoring spatial adjustments and fishing tactics. We then present results for a case study i...
Canadian Journal of Fisheries and Aquatic Sciences, 2018
Stock assessment models are fitted to abundance-index, fishery catch, and age–length–sex composit... more Stock assessment models are fitted to abundance-index, fishery catch, and age–length–sex composition data that are estimated from survey and fishery records. Research has developed spatiotemporal methods to estimate abundance indices, but there is little research regarding model-based methods to generate age–length–sex composition data. We demonstrate a spatiotemporal approach to generate composition data and a multinomial sample size that approximates the estimated imprecision. A simulation experiment comparing spatiotemporal and design-based methods demonstrates a 32% increase in input sample size for the spatiotemporal estimator. A Stock Synthesis assessment used to manage lingcod (Ophiodon elongatus) in the California Current also shows a 17% increase in sample size and better model fit using the spatiotemporal estimator, resulting in smaller standard errors when estimating spawning biomass. We conclude that spatiotemporal approaches are feasible for estimating both abundance-in...
JT (2023) The performance of model-based indices given alternative sampling strategies in a clima... more JT (2023) The performance of model-based indices given alternative sampling strategies in a climate-adaptive survey design.
Implementation of the United Nations Sustainable Development Goals requires assessments of the gl... more Implementation of the United Nations Sustainable Development Goals requires assessments of the global state of fish populations. While we have reliable estimates of stock status for fish populations accounting for approximately half of recent global catch, our knowledge of the state of the majority of the world's “unassessed” fish stocks remains highly uncertain. Numerous publications have produced estimates of the global status of these unassessed fisheries, but limited quantity and quality of data along with methodological differences have produced counterintuitive and conflicting results. Here, we show that despite numerous efforts, our understanding of the status of global fish stocks remains incomplete, even when new sources of broadly available data are added. Estimates of fish populations based primarily on catch histories on average performed 25% better than a random guess. But, on average, these methods assigned fisheries to the wrong FAO status category 57% of the time...
Canadian Journal of Fisheries and Aquatic Sciences, 2017
Estimating trends in abundance from fishery catch rates is one of the oldest endeavors in fisheri... more Estimating trends in abundance from fishery catch rates is one of the oldest endeavors in fisheries science. However, many jurisdictions do not analyze fishery catch rates due to concerns that these data confound changes in fishing behavior (adjustments in fishing location or gear operation) with trends in abundance. In response, we developed a spatial dynamic factor analysis (SDFA) model that decomposes covariation in multispecies catch rates into components representing spatial variation and fishing behavior. SDFA estimates spatiotemporal variation in fish density for multiple species and accounts for fisher behavior at large spatial scales (i.e., choice of fishing location) while controlling for fisher behavior at fine spatial scales (e.g., daily timing of fishing activity). We first use a multispecies simulation experiment to show that SDFA decreases bias in abundance indices relative to ignoring spatial adjustments and fishing tactics. We then present results for a case study i...
Canadian Journal of Fisheries and Aquatic Sciences, 2018
Stock assessment models are fitted to abundance-index, fishery catch, and age–length–sex composit... more Stock assessment models are fitted to abundance-index, fishery catch, and age–length–sex composition data that are estimated from survey and fishery records. Research has developed spatiotemporal methods to estimate abundance indices, but there is little research regarding model-based methods to generate age–length–sex composition data. We demonstrate a spatiotemporal approach to generate composition data and a multinomial sample size that approximates the estimated imprecision. A simulation experiment comparing spatiotemporal and design-based methods demonstrates a 32% increase in input sample size for the spatiotemporal estimator. A Stock Synthesis assessment used to manage lingcod (Ophiodon elongatus) in the California Current also shows a 17% increase in sample size and better model fit using the spatiotemporal estimator, resulting in smaller standard errors when estimating spawning biomass. We conclude that spatiotemporal approaches are feasible for estimating both abundance-in...
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