To bid or not to bid: An investigation into economic incentives underling auction participation

This dissertation investigates the individual characteristics correlated with auction participation decisions using data from two commercial fishing license buybacks. I use the joint empirical analysis of stated and revealed preferences, with two major findings emerging. First, the results of my analysis suggest that individuals with relatively low willingness to accept values and low engagement in the fishery faced problems with the participation decision which prevented them from tendering bids in the auction. This has serious policy implications given that the efficiency of reverse auctions relies on buying goods back from individuals who value them the least. The low participation rate suggests that the licenses bought back represent between 47 - 64 percent of the maximum achievable with the same funds under a first best outcome. Second, fishermen are frequently modeled as strict profit maximizers and harvest histories are often assumed to serve as a good proxy for expected future profits in many circumstances. I find evidence against both of these assumptions. Indicators for bequest and enjoyment values are associated with an increased bid equivalent to that of a $6,500 -$20,000 increase in annual profits. Indicators of bequest and enjoyment values are also significantly correlated with the decision of whether to tender a bid at all. Expected future usage patterns are an important consideration in the participation decisions, and the expected usage can differ significantly from past usage patterns. These results suggest that market experience plays an important role in auction participation decisions, and the problems which develop from inexperience should be addressed explicitly through the auction design

Applying portfolio management to implement Ecosystem-Based Fishery Management (EBFM)

Author Posting. © The Author(s), 2016. This is the author's version of the work. It is posted here by permission of Taylor & Francis for personal use, not for redistribution. The definitive version was published in North American Journal of Fisheries Management 36 (2016): 652-669, doi:10.1080/02755947.2016.1146180.Portfolio management has been suggested as a tool to help implement ecosystem-based fisheries management (EBFM). The portfolio approach involves the application of financial portfolio theory to multispecies fishery management to account for species interdependencies, uncertainty, and sustainability constraints. By considering covariance among species, this approach allows economic risks and returns to be calculated across varying combinations of stock sizes. Tradeoffs between expected aggregate returns and portfolio risk can thus be assessed. We develop a procedure for constructing portfolio models to help implement EBFM in the northeastern United States, using harvest data from the National Marine Fisheries Service. Extending the work of Sanchirico et al. (2008), we propose a measure of excessive risk taking, which may be used by managers to monitor signals of non-optimal harvests. In addition, we conduct portfolio assessments of historical commercial fishing performance at different accounting stances: the large marine ecosystem, the New England region, and the community (fishing ports). We show that portfolio analysis could inform management at each level. Results of the study suggest that excessive risk taking is associated with overfishing, and risk management is therefore important for ensuring sustainability.This article was prepared under award numbers NA09OAR4320129 (Cooperative Institute for the North Atlantic Region) from the National Oceanic and Atmospheric Administration, US Department of Commerce and with additional support from the J. Seward Johnson Fund in Support of the WHOI Marine Policy Center.2017-06-0

How to Assess the Spatial Representation of Fishery's Revenues? A Method Comparison

Maps of fishing locations are important in assessing fishery exposure to management alternatives and facilitates stakeholder outreach (e.g. the New England Fishery Management Council’s Omnibus Habitat Amendment 2, http://www.nefmc.org/library/omnibus-habitat-amendment-2 and the Mid-Atlantic Fishery Management Council’s Amendment 16 to the Atlantic Mackerel, Squid, and Butterfish Fishery Management Plan, https://www.greateratlantic.fisheries.noaa.gov/regs/2016/September/16msbamend16ea.pdf). Fishing location data is also a primary input into behavioral location choice models. Issues of fishing location accuracy and precision thus affect both a manager’s ability to govern effectively and a researcher’s ability to model welfare changes. Using data from the limited access scallop fishery in the Northeastern US, this study compares revenue maps created by different approaches for the fishing years 2000-2015. Besides the commonly used aggregation approach of logbook data into statistical areas and ten-minutes-square grids, two probability models will be employed. One of the probability models is based on the work of DePiper (2014) and employs statistical representations of logbook point data, while the second approach follows the approach of Münch/DePiper/Demarest (2017) and incorporates a kernel smoother on Vessel Monitoring System track data. This works aims to highlight the differences in the spatial distribution of revenue between the method applied and to discuss the drawbacks of simply aggregating logbook data into standardized grids, which serves as the most common approach to its spatial representation. This research indicates that statistical models can substantially improve the ability to define fishing locations when compared to traditional point aggregation methods

Estimation of Commercial Fishing Trip Costs Using Sea Sampling Data

Accurate cost estimation is crucial in fisheries economic analyses, but is often the least known component of many studies. For the past two decades, a systematic approach to collecting fishing cost data has been employed by the Northeast Fisheries Science Center through the sea sampling program, i.e., onboard observers collecting economic information in addition to bycatch information. However, the selection of trips to be observed is driven by biological concerns rather than cost assessment. The primary driver is the Standardized Bycatch Reporting Methodology which dictates what types of vessels (gear, species, area of operation, etc.) participating in various fisheries should be sampled and at what rate. There are other factors (weather and the condition of the vessel) that may introduce biases in terms of choice of vessels observed within a given time frame. This is compounded by the fact that both the optimal stratification and sampling rates for estimating bycatch discards are different from those for estimating vessel trip costs. We investigate the effects of sampling bias on trip cost model estimations through the estimation of weighted and unweighted least squares models, as well as Heckman Sample Selection Models, using a data set including both the subsample of fishing trips observed in the sea sampling program and unobserved trips. Results indicate that sampling bias is an issue that cannot be ignored, given that the uncorrected estimates have the potential to lead to erroneous conclusions, which in turn may negatively affect management decisions and regulatory outcomes.Proceedings of the Eighteenth Biennial Conference of the International Institute of Fisheries Economics and Trade, held July 11-15, 2016 at Aberdeen Exhibition and Conference Center (AECC), Aberdeen, Scotland, UK

Economic and Ecosystem Effects of Fishing on the Northeast US Shelf

Modeling tools that can demonstrate possible consequences of strategies designed to operationalize ecosystem-based fisheries management (EBFM) should be able to address tradeoffs over a wide suite of considerations representing the scope of marine management objectives. Coupled ecological-economic modeling, where models for ecological and economic subsystems are linked through their inputs and outputs, allows for quantification of such tradeoffs. Here, we link the harvest output from fishery management scenarios implemented in an end-to-end ecosystem model (Atlantis) to an input–output regional economic model for the Northeast United States to calculate changes in socio-economic indicators, including the consequences of management action for regional sales, wages, and employment. We implement three simple scenarios (maintain, decrease, or increase current fishing effort), and compare model-projected values for systematic and sector-specific indicators. Systematic indicators revealed different ecological and economic outcomes, with large ecological responses and clear tradeoffs among the catch and biomass of species groups. Economic indicators for the region responded similarly to fishery yield; however, changes in total sales did not match those in landed catch. Under increased fishing effort, a lower proportional increase in sales relative to total landed catch arose due to increased yield from lower value species groups. Average fisheries income changed little among scenarios, but was highest when effort was maintained at current levels, likely a reflection of fleet and catch stability. Our results serve to demonstrate that consequences of management may be felt disproportionately among species through the region and across different fisheries sectors. With our coupled modeling approach of passing Atlantis ecosystem model outputs to an input–output economic model, we were able to assess effects of fisheries management across a broader suite of indicators that have relevance for policymakers across multiple objectives

The Impact of Catch Shares on Fishing Income Diversification and Variation in Annual Revenue

Many fishermen diversify their income by fishing in more than one fishery which can significantly reduce year-to-year variation in income. However, opportunities to diversify have become more limited as access to fisheries has become more restricted. The implementation of catch share systems could further reduce diversification if those who remain in a fishery consolidate catch privileges and specialize, and those who exit lose a component of their fishing portfolio. However, catch shares, particularly in the form of IFQs, offer individuals who had not been part of fishery the opportunity to enter by purchasing or leasing quota. Thus the net effect of catch shares on diversification is uncertain. Furthermore, for fishermen that remain in the catch share fishery, the secure privilege to harvest a set share of the TAC may provide opportunities to reduce variation in income offsetting increased risk associated with reduced diversification. Thus it remains an empirical question whether and how catch shares affect diversification and variation in income. We present an empirical study of diversification in 14 catch share fisheries with a diversity of species from different regions of the US, including both IFQs and cooperative-based catch share systems. For each of these fisheries we test whether diversification levels and trends in diversification changed after implementation of IFQs both for fishermen that remained in the catch share system and for those that exited but remained active in other fisheries. We also test whether variation in fishing revenues changed for fishermen in these groups.Proceedings of the Eighteenth Biennial Conference of the International Institute of Fisheries Economics and Trade, held July 11-15, 2016 at Aberdeen Exhibition and Conference Center (AECC), Aberdeen, Scotland, UK

Implementing Ecosystem Approaches to Fishery Management: Risk Assessment in the US Mid-Atlantic

Fishery managers worldwide are evaluating methods for incorporating climate, habitat, ecological, social, and economic factors into current operations in order to implement Ecosystem Approaches to Fishery Management (EAFM). While this can seem overwhelming, it is possible to take practical steps toward EAFM implementation that make use of existing information and provide managers with valuable strategic advice. Here, we describe the process used by the U.S. Mid-Atlantic Fishery Management Council (Council) to develop an ecosystem-level risk assessment, the initial step proposed in their recently adopted EAFM guidance document. The Council first defined five types of Risk Elements (ecological, economic, social, food production, management) and identified which management objectives aligned with each element. Based on an existing ecosystem status report for the region and other existing sources (including expert opinion), potential ecological, social, economic, and management indicators were identified for each risk element. Finally, low, low-moderate, moderate-high, and high risk criteria were defined for each indicator, and the indicator data were used to score each risk element using the criteria. The ultimate outcome is a ranked risk assessment in order to focus on the highest risk issues for further evaluation and mitigation. The risk assessment highlights certain species and certain management issues as posing higher cumulative risks to meeting Council management objectives when considering a broad range of ecological, social, and economic factors. Tabular color coded summaries of risk assessment results will be used by the Council to prioritize further EAFM analyses as well as research plans over the coming 5 years. As ecosystem reporting and operational EAFM continue to evolve in future years, the Council foresees integrating these efforts so that ecosystem indicators are refined to meet the needs of fishery managers in identifying and managing risks to achieving ecological, social, and economic fishery objectives. Overall, ecosystem indicator-based risk assessment is a method that can be adapted to a wide range of resource management systems and available information, and therefore represents a promising way forward in the implementation of EAFM

Joint ICES/EUROMARINE: Workshop on common conceptual mapping methodologies (WKCCMM; Outputs from 2021 meeting)

The Joint ICES/EUROMARINE Workshop on Common Conceptual Mapping Methodologies (WKCCMM) aimed to advance approaches to support inter- and transdisciplinary science via qualitative conceptual models to inform Integrated Ecosystem Assessment (IEA) throughout Eu-ropean seas and beyond. The workshop focused on developing a common understanding of conceptual mapping meth-odologies, their key uses and limitations, and processes for effective conceptual modelling with stakeholders for a variety of applications (e.g. developing food-webs, socio-ecological modelling, scoping exercises, rapid/initial management action and/or impact evaluations). Discussion in-volved presentation and discussion of a range of conceptual modelling approaches and contexts through the examination of case studies. These case studies gave rise to a suite of recommenda-tions, including the development of a workflow for IEA, and more generic guidelines and best practice advice for the use of conceptual modelling approaches with stakeholders. Although stakeholders were not able to be included in this workshop, they were very much at the heart of discussions, with the challenges and good practices of stakeholder inclusion addressed. WKCCMM also investigated how the methodologies can be best used to contribute to IEA, and may otherwise be applied throughout the ICES community, including identifying opportunities for cross-collaboration and knowledge transfer within the network.info:eu-repo/semantics/publishedVersio

On the precision of predicting fishing location using data from the Vessel Monitoring System (VMS)

Defining fishing grounds based on data from Vessel Monitoring System (VMS) has been a widely-researched topic in recent years. Much of the research has focused on filtering algorithms for identifying fishing locations from VMS point data, most often supplemented with either imputed or reported vessel speed information. This study compared the precision of categorizing fishing locations from VMS data either by the most wide-spread â speed ruleâ approach or a probability model. Using data from Northeast U.S. Fisheries for fishing years 2010-2014, we showed that the traditional representation of fishing activities as derived by speed rules leads to a severe misrepresentation of fishing grounds for gears other than bottom otter trawl. Predictions based on probability models outperformed gear-specific speed rules in classifying VMS polls for sink gillnet and scallop dredge trips, without adding substantial computational effort. The probability models thus provide the largest improvements in gears with complicated fishing patterns, while controlling for issues, such as fleet dynamics, that historically have not been dealt with in the static speed rules, but which can have significant impacts on the quality of predictions.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author