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Thursday, May 23, 2019

S1: Applications of Network Analysis to Fisheries Management

Session Chairs: Yutaro Sakai, University of Tokyo; Kailin Kroetz, Resources for the Future;

13:20 – 13:38  |  3585426

Use of network analysis to visualise relationships within commercial marine fisheries

Monica Galligan1;
1California State University Monterey Bay, Seaside, California, USA;

This paper describes the application of network analysis in both ArcGIS and R to depict relationships between and among participants in California commercial marine fisheries. In the course of researching and applying tools to illustrate multiple aspects of the US West Coast groundfish fishery, including supply chains and agents participation, I explored topics including data structure and preparation, graphing, and statistics. I will discuss challenges and troubleshooting techniques, as well as strategies developed to apply network analysis to improve understanding of connections in commercial marine fisheries.

13:38 – 13:56  |  3579810

Network analysis of quota trading in Alaska fisheries

Adam Hayes1;
1University of Washington, Seattle, United States;

Catch shares are a common policy instrument to mitigate the common pool resource problem associated with fisheries while avoiding perverse incentives that lead to overcapitalization and inferior product quality. A key feature of many catch share programs is that holders of quota can transfer their catch share rights, either temporarily or permanently. While previous research has noted that fishery participation tends to decline as quota is consolidated over time, analysis of quota share trading patterns, and, in particular, the ways in which annual management decisions may affect transfer activity has been limited. As fishery participation decisions affect the revenue generated by the fishery, this is an important consideration. I focus here on the Pacific halibut and sablefish fisheries which came under a catch share policy beginning in 1995. While management decisions concerning total allowable catch (TAC) are made separately, many fishing vessels and quota owners are active in both fisheries. Setting management decisions jointly may increase economic stability at both the individual and community level over time. Using data on catch share trading in Alaska for the years 2000-2016, I model quota trading behavior in each fishery over time using a social network analysis approach to account for the segmentation of trades within the network. I use this network model to estimate how catch share prices and trading behavior in each fishery affect the flow of quota in the network both within and across fisheries, and estimate potential increase economic stability as a result of jointly setting the TAC for the two fisheries.

13:56 – 14:14  |  3587189

Network analysis of quota trading in the Gulf of Mexico IFQ Fisheries

Andrew Ropicki1; Sherry Larkin2;
1Texas A&M University, Corpus Christi, United States; 2University of Florida - IFAS, Gainesville, United States;

Understanding how fishers behave in quota and landings markets in catch share managed fisheries can provide information on fishing community structure, how fishing communities interact, and how quota in a fishery might be expected to move spatially and temporally in response to external stimuli. This research applies network analysis to both landings and quota trading data from the Gulf of Mexico commercial red snapper and grouper-tilefish IFQ programs to examine fishing community structure in the Gulf of Mexico reef fish fishery, quota trading within and between fishing communities, and changes associated with both fishing community structure and quota trading patterns as the IFQ programs have aged. Networks are constructed annually for both the landings market where network connections represent IFQ fishers selling their catch to registered dealers (fish houses) and the quota trading market where network connections are defined by quota (sale and lease) transactions between fishers. The landings networks are used to define fishing communities and a quadratic assignment procedure will be used to measure overlap between the two networks (landings and quota) to examine the extent to which quota trading is accomplished within fishing communities as opposed to between fishing communities. By examining annual networks, the analysis will provide information on temporal changes in fishing community structure and its role in quota trading are quota trading markets becoming less segmented as the market matures? The analysis will provide valuable insights on the role of fishing communities in quota trading markets and how that role has changed since IFQ implementation.

14:14 – 14:32  |  3567329

A comparison of individual and network level analyses in the fishery context

Yutaro Sakai1; Daniel Holland2; Joshua Abbott3;
1Graduate School of Agricultural and Life Sciences, the University of Tokyo, Tempe, AZ, United States; 2Northwest Fisheries Science Center, Seattle, WA, United States; 3Arizona State University, Tempe, AZ, United States;

The management of multi-species fisheries is challenging, as each fishery shares linkages through exposure to common environmental shocks as well as the movement of fishermen across fisheries and the seascape. Network analysis has attracted increasing attention as a potential means to make sense of this complexity. Proponents of network analysis argue that it can distill the complex structure of a multi-species fishery into a handful of informative network statistics of cross-fisheries connectivity, which can aid in forward-looking fisheries management policy design and evaluation questions. While the arguments are appealing, the usefulness of network statistics for capturing essential elements of the underlying structure has not been thoroughly investigated in the fishery context.

In this paper, we use longitudinal fish ticket data in the west coast of the United States to examine how structural changes in the fishery both at the individual level and at the network level compare to one another. Our dataset includes 4 million observations for 30,000 vessels during 1981 to 2016. This detailed dataset allows us to examine how cross-fishery diversification and revenue risk has evolved at the vessel level. We contrast these individual level result with the changes in the network statistics. To do so, we assign each fishing trip to one of 39 fisheries following the Thomson fishery codes provided by PacFIN. We consider both a network of participation (extensive margin) and a network of effort allocation (intensive margin) across these fisheries. After constructing these networks in each year, we calculate various network statistics, including edge density, between centrality, and closeness centrality, to investigate to what extent they map to the underlying changes in the participation pattern and effort allocation of vessels. We also examine how these network statistics have changed over time in response to a series of limited access privilege policies, which are known to have affected individual vessels participation behaviors and income risk.

14:32 – 14:50  |  3565884

Reconciling micro- and macro-scale indicators: Measuring socio-economic resilience for ecosystem-based management

Kailin Kroetz1; Matthew Reimer2; James Sanchirico3; Daniel Lew4; Jaime Ashander5; Matthew Ashenfarb5;
1Resources for the Future, Washington, United States; 2University of Alaska, Anchorage, Anchorage, U.S.; 3University of California, Davis, Davis, U.S.; 4NOAA Fisheries, Davis, U.S.; 5Resources for the Future, Washington, U.S.;

Many indicators of socio-environmental system resilience have been proposed for and applied to regional fisheries socioeconomic systems, both at the micro- and macro-scale. Micro-scale indicators include individual-, vessel-, and community-level diversification metrics, such as the HerfindahlHirschman Index (HHI). Macro-scale indicators include Gaos universal resilience metric, which requires representing regional fisheries as an inter-connected network. Until now however, these micro- and macro-scale indicators have never been calculated for the same system and compared. We show, both theoretically and empirically, that common micro- and macro-scale indicators of resilience can move in opposite directions over time in a regional fisheries system, suggesting the need for a deeper understanding of these indicators and the relationship between them. Using Alaska fisheries landings data, we show empirically that after catch share implementation, micro-scale indicators imply resilience decreases, whereas macro-scale indicators imply resilience increases. To reconcile these opposing findings across the two scales, we provide rationale for their divergence and a discussion of how both micro- and macro-scale measures should be used when designing and evaluating Ecosystem-Based Fisheries Management policies with goals that include system resilience to environmental change.

14:50 – 15:30


A panel discussion will follow oral presentations.


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