Northern Shortfin Squid (Illex illecebrosus) Fishery Footprint on the Northeast US Continental Shelf

Northern shortfin squid (Illex illecebrosus) have presented a challenge for US fishery management because of their life history traits and broad population distribution. They are characterized by a short semelparous lifespan and high interannual variability in recruitment. Much of the stock resides outside of the boundaries of existing US fisheries surveys and US fishing effort. Based on the annual migration pattern and broad geographic distribution of shortfin squid, it is believed that the US squid fishery in the Mid-Atlantic has not had a substantial impact on the stock; however, recent catches are viewed as tightly constrained by quotas. To better estimate the potential impact of fishing on the resource, we worked with industry representatives, scientists, and managers to estimate the availability of the northern shortfin squid stock on the US continental shelf to the US fishery. Taking a novel analytical approach, we combine a model-based estimate of the area occupied by northern shortfin squid with the empirical US commercial shortfin squid fishery footprint to produce estimates of the area of overlap. Because our method overestimates the fishery footprint and underestimates the full distribution of the stock, we suggest that our estimates of the overlap between the area occupied by the squid and the fishery footprint is a way to develop a conservative estimate of the potential fishery impact on the stock. Our findings suggest a limited degree of overlap between the US fishery and the modeled area occupied by the squid on the US continental shelf, with a range of 1.4–36.3%. The work demonstrates the value of using high-resolution, spatially explicit catch and effort data in a species distribution model to inform management of short-lived and broadly distributed species, such as the northern shortfin squid.

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Catch shares drive fleet consolidation and increased targeting but not spatial effort concentration nor changes in location choice in a multispecies trawl fishery

Canadian Journal of Fisheries and Aquatic Sciences ◽

10.1139/cjfas-2019-0005 ◽

2019 ◽

Vol 76 (12) ◽

pp. 2377-2389 ◽

Cited By ~ 2

Author(s):

Peter T. Kuriyama ◽

Daniel S. Holland ◽

Lewis A.K. Barnett ◽

Trevor A. Branch ◽

Robert L. Hicks ◽

...

Keyword(s):

Fishery Management ◽

Location Choice ◽

Fishing Effort ◽

Fishing Activity ◽

Catch Shares ◽

Capital Costs ◽

Trawl Fishery ◽

Management Objectives ◽

The Us ◽

Fisher Behavior

Catch share systems are generally expected to increase economic rents in fisheries by increasing harvest efficiency, reducing capital costs through consolidation, and increasing the value of landed catch. However, these benefits may have costs, as consolidation and the potential for associated change in spatial distribution in landings can hinder social objectives such as maintaining access for fishery-dependent communities and small owner-operators. Achievement of such fishery management objectives are determined by changes in fisher behavior, which may be complex and difficult to predict. Predicting fisher behavior is particularly challenging in multispecies fisheries, in which the mix of species is a determinant of where and when fishing effort and landings occur. We evaluate changes in overall fishing effort, species targeting, and determinants of fishing location choice in response to catch shares in the US West Coast Groundfish Trawl Fishery. We found reductions in total fishing effort, increased targeting of some species, and no evidence of spatial effort concentration. Key determinants of location choice (distance, expected revenue, and recently fished locations) were similar among time periods, but after catch shares there was more avoidance of areas that lacked recent fishing activity or associated information with which to develop expectations of catch and bycatch. Additionally, location choice remained constant with up to 100-fold financial penalties on bycatch species.

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Comparing predictions of fisheries bycatch using multiple spatiotemporal species distribution model frameworks

Canadian Journal of Fisheries and Aquatic Sciences ◽

10.1139/cjfas-2018-0281 ◽

2020 ◽

Vol 77 (1) ◽

pp. 146-163 ◽

Cited By ~ 4

Author(s):

Brian C. Stock ◽

Eric J. Ward ◽

Tomoharu Eguchi ◽

Jason E. Jannot ◽

James T. Thorson ◽

...

Keyword(s):

Random Forests ◽

Species Distribution ◽

Markov Random Fields ◽

Fishery Management ◽

Species Distribution Model ◽

Additive Models ◽

Distribution Model ◽

Range Of Movement ◽

Distribution Models ◽

Model Framework

Spatiotemporal predictions of bycatch (i.e., catch of nontargeted species) have shown promise as dynamic ocean management tools for reducing bycatch. However, which spatiotemporal model framework to use for generating these predictions is unclear. We evaluated a relatively new method, Gaussian Markov random fields (GMRFs), with two other frameworks, generalized additive models (GAMs) and random forests. We fit geostatistical delta-models to fisheries observer bycatch data for six species with a broad range of movement patterns (e.g., highly migratory sea turtles versus sedentary rockfish) and bycatch rates (percentage of observations with nonzero catch, 0.3%–96.2%). Random forests had better interpolation performance than the GMRF and GAM models for all six species, but random forests performance was more sensitive when predicting data at the edge of the fishery (i.e., spatial extrapolation). Using random forests to identify and remove the 5% highest bycatch risk fishing events reduced the bycatch-to-target species catch ratio by 34% on average. All models considerably reduced the bycatch-to-target ratio, demonstrating the clear potential of species distribution models to support spatial fishery management.

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Finding the accelerator and brake in an individual quota fishery: linking ecology, economics, and fleet dynamics of US West Coast trawl fisheries

ICES Journal of Marine Science ◽

10.1093/icesjms/fst114 ◽

2013 ◽

Vol 71 (2) ◽

pp. 308-319 ◽

Cited By ~ 16

Author(s):

Isaac C. Kaplan ◽

Daniel S. Holland ◽

Elizabeth A. Fulton

Keyword(s):

West Coast ◽

Fishery Management ◽

Fishing Effort ◽

Target Species ◽

The Pacific ◽

The Us ◽

Fleet Dynamics ◽

Us West ◽

Trawl Fisheries ◽

Management Council

Abstract Isaac C. Kaplan, Daniel S. Holland, and Elizabeth A. Fulton. 2014. Finding the accelerator and brake in an individual quota fishery: linking ecology, economics, and fleet dynamics of US West Coast trawl fisheries. – ICES Journal of Marine Science, 71: 308–319. In 2011, the Pacific Fisheries Management Council implemented an individual transferrable quota (ITQ) system for the US West Coast groundfish trawl fleet. Under the ITQ system, each vessel now receives transferrable annual allocations of quota for 29 groundfish species, including target and bycatch species. Here we develop an ecosystem and fleet dynamics model to identify which components of an ITQ system are likely to drive responses in effort, target species catch, bycatch, and overall profitability. In the absence of penalties for discarding over-quota fish, ITQs lead to large increases in fishing effort and bycatch. The penalties fishermen expect for exceeding quota have the largest effect on fleet behaviour, capping effort and total bycatch. Quota prices for target or bycatch species have lesser impacts on fishing dynamics, even up to bycatch quota prices of $50 kg−1. Ports that overlap less with bycatch species can increase effort under individual quotas, while other ports decrease effort. Relative to a prior management system, ITQs with penalties for exceeding quotas lead to increased target species landings and lower bycatch, but with strong variation among species. The model illustrates how alternative fishery management policies affect profitability, sustainability and the ecosystem.

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A Robust Prediction Model for Species Distribution Using Bagging Ensembles with Deep Neural Networks

Remote Sensing ◽

10.3390/rs13081495 ◽

2021 ◽

Vol 13 (8) ◽

pp. 1495

Author(s):

Jehyeok Rew ◽

Yongjang Cho ◽

Eenjun Hwang

Keyword(s):

Neural Networks ◽

Species Distribution ◽

Best Practice ◽

Deep Neural Networks ◽

Species Distribution Models ◽

Species Distribution Model ◽

Environmental Data ◽

Distribution Model ◽

Distribution Models ◽

Robust Prediction

Species distribution models have been used for various purposes, such as conserving species, discovering potential habitats, and obtaining evolutionary insights by predicting species occurrence. Many statistical and machine-learning-based approaches have been proposed to construct effective species distribution models, but with limited success due to spatial biases in presences and imbalanced presence-absences. We propose a novel species distribution model to address these problems based on bootstrap aggregating (bagging) ensembles of deep neural networks (DNNs). We first generate bootstraps considering presence-absence data on spatial balance to alleviate the bias problem. Then we construct DNNs using environmental data from presence and absence locations, and finally combine these into an ensemble model using three voting methods to improve prediction accuracy. Extensive experiments verified the proposed model’s effectiveness for species in South Korea using crowdsourced observations that have spatial biases. The proposed model achieved more accurate and robust prediction results than the current best practice models.

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Improving performance of species distribution model in mountainous areas with complex topography

Ecological Research ◽

10.1111/1440-1703.12227 ◽

2021 ◽

Author(s):

Chi‐Cheng Liao ◽

Yi‐Huey Chen

Keyword(s):

Species Distribution ◽

Species Distribution Model ◽

Distribution Model ◽

Complex Topography ◽

Mountainous Areas

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A Bioclimate-Based Maximum Entropy Model for Comperiella calauanica Barrion, Almarinez and Amalin (Hymenoptera: Encyrtidae) in the Philippines

Insects ◽

10.3390/insects12010026 ◽

2021 ◽

Vol 12 (1) ◽

pp. 26

Author(s):

Billy Joel M. Almarinez ◽

Mary Jane A. Fadri ◽

Richard Lasina ◽

Mary Angelique A. Tavera ◽

Thaddeus M. Carvajal ◽

...

Keyword(s):

Maximum Entropy ◽

Habitat Suitability ◽

Species Distribution Model ◽

Biological Control Agent ◽

The Philippines ◽

Distribution Model ◽

Field Surveys ◽

Probability Of Occurrence ◽

Precipitation Seasonality ◽

Bioclimatic Variables

Comperiella calauanica is a host-specific endoparasitoid and effective biological control agent of the diaspidid Aspidiotus rigidus, whose outbreak from 2010 to 2015 severely threatened the coconut industry in the Philippines. Using the maximum entropy (Maxent) algorithm, we developed a species distribution model (SDM) for C. calauanica based on 19 bioclimatic variables, using occurrence data obtained mostly from field surveys conducted in A. rigidus-infested areas in Luzon Island from 2014 to 2016. The calculated the area under the ROC curve (AUC) values for the model were very high (0.966, standard deviation = 0.005), indicating the model’s high predictive power. Precipitation seasonality was found to have the highest relative contribution to model development. Response curves produced by Maxent suggested the positive influence of mean temperature of the driest quarter, and negative influence of precipitation of the driest and coldest quarters on habitat suitability. Given that C. calauanica has been found to always occur with A. rigidus in Luzon Island due to high host-specificity, the SDM for the parasitoid may also be considered and used as a predictive model for its host. This was confirmed through field surveys conducted between late 2016 and early 2018, which found and confirmed the occurrence of A. rigidus in three areas predicted by the SDM to have moderate to high habitat suitability or probability of occurrence of C. calauanica: Zamboanga City in Mindanao; Isabela City in Basilan Island; and Tablas Island in Romblon. This validation in the field demonstrated the utility of the bioclimate-based SDM for C. calauanica in predicting habitat suitability or probability of occurrence of A. rigidus in the Philippines.

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