How much does a longline fishing trip cost?

Since 2004, the PIFSC Socioeconomics Program – in collaboration with the NOAA Observer Program managed by the Pacific Islands Regional Office (PIRO) – has maintained an ongoing trip-level economic data collection program for Hawaii longline fisheries. The establishment of this routine economic data collection program provides timely information to support management of these fisheries. Economic data collected are used for (but not limited to): 1) Assessing the economic viability and stability of the fisheries; 2) Measuring the economic importance to local economies and the value of fisheries; and 3) Analyzing the economic impacts of various policy options.

Trip costs for Hawaii longline tuna fishing trips, 2004-2015

An average tuna trip cost about $25,500 in 2015, excluding labor costs. Over the period 2004-2015, the average trip cost in the Hawaii tuna longline fishery nearly doubled (in nominal value), from $13,800 per trip to $25,500 per trip, due primarily to increases in fuel prices. In 2004, fuel costs made up about 46% of total trip costs, whereas it comprised 54% in 2015. Average tuna trip costs have increased gradually over time, peaking in 2012. In 2012, the average yearly fuel price as reported by fishermen reached a high of $3.90 per gallon (average consumer prices as reported by AAA was $4.78/gallon at the time), which comprised nearly 58% of the non-labor trip costs. The recent drop in fuel prices during 2015 resulted in decreased overall fishing costs in 2015 relative to prior years (16% lower than the 2012 peak).

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Trip costs for Hawaii longline swordfish fishing trips, 2005-2015

Swordfish fishing trips are usually more expensive than tuna fishing trips, even when trips are carried out by the same vessel, mostly due to longer trip length and subsequently a higher proportion of fuel cost in its trip expenditures. On average, the cost of a swordfish trip is approximately double that of a tuna fishing trip. In 2015, the average swordfish trips cost $42,200. In 2012 when the average yearly fuel price was at its peak, an average swordfish trip cost over $57,600, while a tuna trip cost about $30,700 during the same year. Similar to tuna trips, with the substantial drop of fuel price in 2015, the average trip costs for swordfish fishing decreased relative to recent years (27% less than the peak costs in 2012).

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More data products based the data collection program led Dr. Minling Pan, can be found on the PIFSC website, click for:

Hawaii longline

American Samoa longline

For more information about this research or to comment on survey results, feel free to contact us: pifsc.socioeconomics@noaa.gov

For more information about other research from the PIFSC Socioeconomics Program visit our website or browse recent blog posts.

How Much Does it Cost a Fishery to Save a Single Sea Turtle?

by Minling Pan

If you ever wondered how much it costs a fishery to save a sea turtle, check out this new study conducted by Dr. Minling Pan of the Pacific Islands Fisheries Science Center (PIFSC) Socioeconomic program and Dr. Shichao Li, formerly of the Joint Institute for Marine and Atmospheric Research of the University of Hawaiʻi.

According to their study, the answer to this question is quite straightforward: a fishery’s cost of saving a turtle depends on the rate of sea turtle bycatch (unintended and unwanted catch) in the fishery. In short, the higher the bycatch rate, the lower the cost to save one sea turtle (through regulating the fishery to reduce sea turtle interactions).

This finding suggests that it would be more cost effective if sea turtle conservation efforts or regulations — such as seasonal or area closures, sea turtle caps, or effort caps — take place in fisheries where bycatch rates are high. Given the transboundary nature of sea turtle and swordfish populations, these results provide insights into opportunities for fishery managers to explore win-win solutions in promoting sea turtle conservation while maintaining sustainable fisheries.

Measuring the cost of saving sea turtles

To measure the cost of saving one sea turtle in a fishery, Drs. Pan and Li developed a spatial and temporal model of sea turtle interactions the Hawaiʻi swordfish fishery. This model enables prediction of sea turtle interaction rates associated with each unit of swordfish fishing effort and the economic returns of the fishing effort by area and time.

They used a Generalized Additive Model approach, developed by PIFSC colleagues Kobayashi and Polovina (2005), to estimate sea turtle interactions associated with fishing effort in various seasons and locations. They added to the model economic returns associated with fishing effort by estimating a fishing trip cost function using ongoing trip cost data collected through a collaborative effort between the PIFSC Socioeconomics Program and the Pacific Islands Regional Office (PIRO) Observer Program.

courtesy: PIRO Observer Program

courtesy: PIRO Observer Program

The analysis compares the costs of saving one sea turtle across international fisheries with various sea turtle bycatch rates, and the team examined the trade-offs between saving one sea turtle and the economic returns of fishing operations in different seasons and different areas.

The study found that between 1994 and 2003, the Hawaiʻi swordfish fishery interacted with one loggerhead sea turtle for every 23,000 pounds of swordfish caught. This swordfish catch would be valued at approximately $50,000 in 2015 swordfish prices. After NOAA Fisheries imposed new regulations on gear and bait in April 2004, the sea turtle bycatch rate for the fishery dropped significantly.

Thus, in recent years, the fishery has interacted with one loggerhead for every 238,000 pounds of swordfish caught. This amount of catch is worth $520,000 in 2015 swordfish prices. Consequently, the marginal cost to a fishery, in terms of lost revenues, for saving an additional sea turtle is higher when the sea turtle bycatch rate is low, the researchers found.

If you are interested in finding out more detailed information, click the link below to read the newly published paper:

Evaluation of Fishing Opportunities under Sea Turtle Interaction Limits – A Decision Support Model for Hawaii-based Longline Swordfish, Xiphias gladius, Fishery Management.

For more information about this and other research from the PIFSC Socioeconomics Program visit our websitebrowse recent blog posts, or contact us by email:  pifsc.socioeconomics@noaa.gov

Researchers assess economic productivity for Hawaii longline fishery

image1 (1) (1)PIFSC Socioeconomics Program researcher Dr. Minling Pan, in collaboration with Northeast Fisheries Science Center economist Dr. John Walden, recently published a study measuring productivity changes in the Hawaii longline fishery in the journal Marine Policy. Fisheries productivity is the result of many factors, including exogenous and endogenous elements, such as regulation and stock condition. Understanding changes in productivity and the factors affecting that change is important to fishery management and a sustainable fishing industry. This work represents the first study to measure productivity change in the Hawaii longline fishery, the largest fresh bigeye tuna and swordfish producer in the United States.

A biomass quantity index is constructed to disentangle biomass impacts in a pelagic environment in order to arrive at an “unbiased” productivity metric. This is particularly important in the Hawaii longline fishery where catches rely mostly on transboundary (shared) stocks with little control on the total amount of extraction. As resource depletion of the transboundary stocks occurs, productivity losses may follow if less output is obtained from the same input usage, or more inputs are used to extract the same catch level from the fishery.

Using a Lowe productivity index, productivity change in the Hawaii longline fleet between 2000 and 2012 is measured in this study.Overall, unadjusted (“biased”) productivity in the Hawaii longline fishery showed a declining trend since 2005. However, once biomass change was used to adjust the index values, the negative productivity change turned positive (Figure 1).

Figure 1. Unbiased and biased Lowe index for tuna trips 2002 to 2012 (base year = 2005)

Figure 1. Unbiased and biased Lowe index for tuna trips 2002 to 2012 (base year = 2005)

While bigeye tuna biomass has trended down in recent years, fishing productivity has improved, as the unbiased productivity index (the adjusted Lowe index) went up steadily from 0.84 in 2009 to 1.36 in 2012. During the study time period, especially since 2010, analytical results show that tuna fishing became more productive in terms of endogenous productivity (e.g., fishing technology). Such an improvement of endogenous productivity has offset the negative impact of the bigeye stock depletion and kept the fishery stable in terms of output to input ratio. Without such an improvement in productivity, the tuna fishery would have had much poorer performance due to the depletion of the shared fish resources. Finally, the study compares productivity change under different fishing technologies and finds evidence that tuna fishing seems to be more efficient compared to swordfish fishing.

For more information about this and other research from the PIFSC Socioeconomics Program visit our websitebrowse recent blog posts, or contact us by email:  pifsc.socioeconomics@noaa.gov

Visualizing the market for ahi tuna in Hawaii: tracking supply and demand characteristics over time

By Kolter Kalberg and Dawn Kotowicz

The majority of commercial landings for domestically caught ahi (bigeye and yellowfin tuna) sold in Hawaii go through the United Fishing Agency (UFA) auction. An auction setting, such as UFA, is often an effective means of quickly reaching short-term price equilibrium in a market characterized by volatile supply and varying degrees of quality for a perishable product – both of which typify the Hawaii ahi market.

In this post, a time-lapse week over day snapshot of the market is presented to depict certain market characteristics  and dynamics that exist between commercial ahi fishers, ‘the supply’, and wholesale buyers, ‘the demand’. Besides the total quantity landed, there are many other market drivers that influence the ex-vessel price of ahi that are difficult to capture independently. Such factors include the quality of ahi, individual fish size, and buyers’ proclivity, just to name a few.

By clicking on the video link below, the relationship among some of these factors can be observed through a graphical visualization of Hawaii’s ahi market using daily data between 2010-2014.

Key notes regarding the animated video

  • The top half of the animated graph is a calculated using a moving sum of a seven day period.
  • The bottom portion animates the average daily price for the four fish size groups and the average daily price (black line) of all fish along with a trend (red line) accounting for the variations of several statistically significant cycles, such as seasonality and lunar effects (for smoothing resolution of the line, weekly variations were not included in the trend.)
  • The Weight by Price density graph has a y-axis that is approximately linear from zero to 15,000 lbs. and then increases in a geometrically declining rate. The scale was modified to include the full range of the data without periodic adjustment to the scale.
  • Prices are represented as the price per unit of weight (lbs.) and not per fish, since individual fish weights varies significantly. However, average price per pound (bottom graph) is the weighted average by number of fish for comparison.

Social science research on the Hawaii tuna market provides evidence that fish dealers buying fish from the auction show preferences for different size and quality, depending on a dealers’ market niche. Related research has found that demand fluctuates with the seasons and certain holidays. These variations occur not only in the total market quantity but also the quality and size per individual fish landed. While average supplies over the course of a week or month are relatively stable, day-to-day supplies are quite variable as is price.

For more information about other research from the PIFSC Socioeconomics Program visit our website or browse recent blog posts

Economic and social science engagement at Pier 38 – An ear to the ground

Economic researcher Kolter Kalberg (JIMAR) and Social Science researcher Dawn Kotowicz (JIMAR) visit the Honolulu Fish Auction weekly. They check in with fish dealers, auction staff, and longline fishermen during their early mornings at Pier 38. They check to see how much fish is being sold that day and which boats landed their catch the night before. Dealers discuss the prices for the day and whether they can fill their orders. Longline fishermen who landed that morning are likely to be nearby and are often willing to discuss how the fishing was on their most recent trip.

   

Continued engagement with these stakeholder groups associated with the Hawaii longline fishery has provided the opportunity to monitor changes in various aspects of the fishery overtime, such as when the Hawaii longline fleet reached its quota in the Eastern Pacific Ocean in November 2013

When issues of interest arise for managers or stakeholders of the fishery, changes can be investigated using regularly collected data along with observations. This approach to research with the Hawaii longline fleet has led to several research projects including:

  • Social and economic effects of the first extended closure of Hawaii Longline Fishery. This research is detailed in a previous blog post and on the PIFSC website.
  • Describing distribution channels for longline-caught fish in Hawaii using observations to create a typology of dealers at the auction and then maintaining close observation of dealers representing each category. Check out a research summary and download a research brochure
  • An exploration of imported tuna and its interactions with Hawaii’s locally landed tuna market.

To keep up with this and other research from the PIFSC Socioeconomics Program visit our website