Benefits and risks of diversification for individual fishers

Abstract

Individuals relying on natural resource extraction for their livelihood face high income variability driven by a mix of environmental, biological, management, and economic factors. Key to managing these industries is identifying how regulatory actions and individual behavior affect income variability, financial risk, and, by extension, the economic stability and the sustainable use of natural resources. In commercial fisheries, communities and vessels fishing a greater diversity of species have less revenue variability than those fishing fewer species. However, it is unclear whether these benefits extend to the actions of individual fishers and how year-to-year changes in diversification affect revenue and revenue variability. Here, we evaluate two axes by which fishers in Alaska can diversify fishing activities. We show that, despite increasing specialization over the last 30 years, fishing a set of permits with higher species diversity reduces individual revenue variability, and fishing an additional permit is associated with higher revenue and lower variability. However, increasing species diversity within the constraints of existing permits has a fishery-dependent effect on revenue and is usually (87% probability) associated with increased revenue uncertainty the following year. Our results demonstrate that the most effective option for individuals to decrease revenue variability is to participate in additional or more diverse fisheries. However, this option is expensive, often limited by regulations such as catch share programs, and consequently unavailable to many individuals. With increasing climatic variability, it will be particularly important that individuals relying on natural resources for their livelihood have effective strategies to reduce financial risk.

Keywords: Bayesian variance function regression; diversity-stability relationship; ecological portfolio effects; income variability; natural resource management.

Fig. 1.

Trends in revenue and diversification over time. (A) Map of major fishing areas in Alaska. (B) Total revenue in billions of USD from 1986 to 2014 for multiple-permit (gray) and single-permit (blue) holders. (C) Proportion of single-permit holders for all fisheries (thick black line) and with permit holders omitted each year who fished any of the nine top species groups (thin lines). (D) Mean effective diversity of species fished (Simpson’s diversity index) for all fisheries (thick black line) and with permit holders omitted each year who fished any of the nine top species groups (thin lines).

Fig. 2.

Individuals who fish permits and permit combinations (permit strategies) with higher species diversity have lower expected revenue variability. On the y axis, dots, thick lines, and thin lines represent posterior medians, 50%, and 95% credible intervals, respectively, for the 34 most common permit strategies. Thick black line and dark- and light-gray shaded regions indicate median, 50%, and 95% credible intervals, respectively, of strategy-level regression built into the hierarchical model. Estimated variability represents expected SD for a permit holder who does not change species diversity or days fished from year to year. Species groups: Dun C, dungeness crab; Fin, finfish; Hal, halibut; Herr, herring; King C, king crab; S, salmon; Sab, sablefish; Sea cuc, sea cucumber; sock, sockeye salmon; Tan C, tanner crab. Gears: drift, drift gillnet; gill, gillnet for herring; ll, longline; otter, otter trawl; set, setnet. Regions: AP, Alaska Peninsula; BB, Bristol Bay; CH, Chignik; CI, Cook Inlet; K, Kodiak; KU, Kuskokwim; NS, Norton Sound; PWS, Prince William Sound; SE, Southeast Alaska; YAK, Yakutat.

Fig. 3.

Diversifying permits reduces revenue variability and usually increases revenue. Two examples of expected revenue variability and median revenue for owners of individual (A) halibut and (B) gillnet herring roe permits (dark blue) compared with owners of the same permit plus one more (medium blue) or two more (light blue) permits. On the y axis, dots and lines represent posterior median and 95% credible intervals, respectively, of expected standard deviations of year-to-year revenue rates of return. Angled lines connect permit sets that differ by one permit. Species groups: Hal, halibut; Herr, herring; S, salmon; Sab, sablefish; sock, sockeye salmon. Gear types: drift, drift gillnet; gill, gillnet for herring; ll, longline. Regions: AP, Alaska Peninsula; BB, Bristol Bay; CI, Cook Inlet; K, Kodiak; NS, Norton Sound; PWS, Prince William Sound; SE, Southeast Alaska.

Fig. S1.

The effect of adding a permit to one’s strategy on estimated revenue variability and median revenue. This is an extended version of Fig. 2 that includes all major strategy combinations. Species groups: Dun C, dungeness crab; Fin, finfish; Hal, halibut; Herr, herring; King C, king crab; S, salmon; Sab, sablefish; Sea cuc, sea cucumber; sock, sockeye salmon; Tan C, tanner crab. Gears: drift, drift gillnet; gill, gillnet for herring; ll, longline; otter, otter trawl; set, setnet. Regions: AP, Alaska Peninsula; BB, Bristol Bay; CH, Chignik; CI, Cook Inlet; K, Kodiak; KU, Kuskokwim; NS, Norton Sound; PWS, Prince William Sound; SE, Southeast Alaska; YAK, Yakutat.

Fig. 4.

Effect of specializing on year-to-year changes in revenue and revenue variability for individual permit holders within the 34 most common strategies. Changing species diversity from year to year is associated with higher variability for individuals within the strategies above the zero line. Specializing is associated with greater expected revenue ratios to the right of the zero line and lower expected revenue ratios to the left of the zero line. For example, individuals with setnet permits for salmon in Prince William Sound, Cook Inlet, Kodiak, Bristol Bay, or the Alaska Peninsula (second purple dot from right) target primarily sockeye salmon and experience a ∼1.5% increase in their year-to-year revenue ratio (horizontal axis) and a ∼0.5% increase in their revenue variability (vertical axis) for a 1% decrease in their ratio of year-to-year species diversity. These effects are estimated holding fishing season length constant from year to year. Dots and line segments represent medians and 50% credible intervals, respectively, of posteriors. In other words, the axes represent coefficient values from the strategy-level slopes. Moving along an axis (say from left to right on the horizontal axis) represents an increase in how steep the slope is between specialization and the year-to-year revenue ratio. The effect of generalizing (increasing species diversity) is similar (Fig. S4). Species groups: Dun C, dungeness crab; Fin, finfish; Hal, halibut; Herr, herring; King C, king crab; S, salmon; Sab, sablefish; Sea cuc, sea cucumber; sock, sockeye salmon; Tan C, tanner crab. Gears: drift, drift gillnet; gill, gillnet for herring; ll, longline; otter, otter trawl; set, setnet. Regions: AP, Alaska Peninsula; BB, Bristol Bay; CH, Chignik; CI, Cook Inlet; K, Kodiak; KU, Kuskokwim; NS, Norton Sound; PWS, Prince William Sound; SE, Southeast Alaska; YAK, Yakutat.

Fig. S2.

Main effects from the hierarchical model predicting revenue ($\beta$) and variability ($\gamma$) in revenue. The $\eta$ coefficients represent strategy-level predictors relating mean species diversity and mean days fished within a strategy (both centered by their means and divided by 2 times their standard deviations) to the magnitude of residual error. Note that ${\mu }_{{\beta }_1}$, ${\beta }_4$, ${\mu }_{{\gamma }_1}$, and ${\gamma }_4$ have been multiplied by $-1$ to make these coefficients interpretable as effects of increasing specialization (as opposed to decreasing specialization).

Fig. S3.

Estimates of within-strategy effects from the hierarchical model. Panels refer to parameters in Eqs. 3 and 7. Shown are medians (dots) and 50% and 95% credible intervals (thick and thin line segments). Strategies are ordered from high to low mean species diversity from top to bottom. Note that ${\gamma }_{1\text{,}j}$ and ${\beta }_{1\text{,}j}$ have been multiplied by $-1$ to make these coefficients interpretable as effects of increasing specialization (as opposed to decreasing specialization). Species groups: Dun C, dungeness crab; Fin, finfish; Hal, halibut; Herr, herring; King C, king crab; S, salmon; Sab, sablefish; Sea cuc, sea cucumber; sock, sockeye salmon; Tan C, tanner crab. Gears: drift, drift gillnet; gill, gillnet for herring; ll, longline; otter, otter trawl; set, setnet. Regions: AP, Alaska Peninsula; BB, Bristol Bay; CH, Chignik; CI, Cook Inlet; K, Kodiak; KU, Kuskokwim; NS, Norton Sound; PWS, Prince William Sound; SE, Southeast Alaska; YAK, Yakutat.

Fig. S4.

Effects of (A) generalizing and (B) specializing from year to year for individual permit holders within the 34 most common strategies. Changing species diversity from year to year is associated with higher variability for individuals within the strategies above the zero line. Generalizing (A) or specializing (B) is associated with greater expected revenue ratios to the right of the zero line and lower expected revenue ratios to the left of the zero line. These effects are estimated holding fishing season length constant from year to year. Dots and line segments represent medians and 50% credible intervals of posteriors. B and Fig. 4 are the same. This is a bivariate display of the ${\gamma }_{1\text{,}j}$, ${\gamma }_{2\text{,}j}$, ${\beta }_{1\text{,}j}$, and ${\beta }_{2\text{,}j}$ coefficient estimates displayed in Fig. S3. Note that ${\gamma }_{1\text{,}j}$ (B vertical axis) and ${\beta }_{1\text{,}j}$ (B horizontal axis) have been multiplied by $-1$ to make these coefficients interpretable as effects of increasing specialization (as opposed to decreasing specialization). Species groups: Dun C, dungeness crab; Fin, finfish; Hal, halibut; Herr, herring; King C, king crab; S, salmon; Sab, sablefish; Sea cuc, sea cucumber; sock, sockeye salmon; Tan C, tanner crab. Gears: drift, drift gillnet; gill, gillnet for herring; ll, longline; otter, otter trawl; set, setnet. Regions: AP, Alaska Peninsula; BB, Bristol Bay; CH, Chignik; CI, Cook Inlet; K, Kodiak; KU, Kuskokwim; NS, Norton Sound; PWS, Prince William Sound; SE, Southeast Alaska; YAK, Yakutat.

Fig. S5.

Same as Fig. 4 but without the effort (days fished) predictor and without its interaction with species diversity. Species groups: Dun C, dungeness crab; Fin, finfish; Hal, halibut; Herr, herring; King C, king crab; S, salmon; sock, sockeye salmon; Sab, sablefish; Sea cuc, sea cucumber; Tan C, tanner crab. Gears: drift, drift gillnet; gill, gillnet for herring; ll, longline; otter, otter trawl; set, setnet. Regions: AP, Alaska Peninsula; BB, Bristol Bay; CH, Chignik; CI, Cook Inlet; K, Kodiak; KU, Kuskokwim; NS, Norton Sound; PWS, Prince William Sound; SE, Southeast Alaska; YAK, Yakutat.

Fig. S6.

The effect of IFQs on model estimates. (A) Posterior density of the ratio between strategy-level estimates of standardized revenue variability (${\gamma }_{0j}$) after the introduction of IFQs vs. before the introduction of IFQs. (B) Estimates (medians) of the effect of generalizing (increasing species diversity) on variability (${\gamma }_{1j}$) for the full model (“Grouped”) compared with a model where separate effects are estimated before and after IFQs were introduced (“IFQ split”). Pattern looks similar for the effect of specializing on variability (${\gamma }_{2j}$) and is not shown. Species groups: Hal, halibut; S, salmon; Sab, sablefish; sock, sockeye salmon. Gears: drift, drift gillnet; ll, longline. Regions: AP, Alaska Peninsula; BB, Bristol Bay; CH, Chignik; CI, Cook Inlet; K, Kodiak; KU, Kuskokwim; NS, Norton Sound; PWS, Prince William Sound; SE, Southeast Alaska; YAK, Yakutat.

Fig. S7.

Strategy–year intercept estimates (${\beta }_{0\text{,}j\text{,}t}$ in Eq. 3) from the hierarchical model. Shown are 40 samples from the posterior distribution. Species groups: Dun C, dungeness crab; Fin, finfish; Hal, halibut; Herr, herring; King C, king crab; S, salmon; Sab, sablefish; Sea cuc, sea cucumber; sock, sockeye salmon; Tan C, tanner crab. Gears: drift, drift gillnet; gill, gillnet for herring; ll, longline; otter, otter trawl; set, setnet. Regions: AP, Alaska Peninsula; BB, Bristol Bay; CH, Chignik; CI, Cook Inlet; K, Kodiak; KU, Kuskokwim; NS, Norton Sound; PWS, Prince William Sound; SE, Southeast Alaska; YAK, Yakutat.

Fig. S8.

The log absolute value residuals from the mean component model (Eq. 3). These residuals are modeled in the variance component model (Eq. 7). Breakpoint linear regression fits are overlaid in red for visual interpretation. Species groups: Dun C, dungeness crab; Fin, finfish; Hal, halibut; Herr, herring; King C, king crab; S, salmon; Sab, sablefish; Sea cuc, sea cucumber; sock, sockeye salmon; Tan C, tanner crab. Gears: drift, drift gillnet; gill, gillnet for herring; ll, longline; otter, otter trawl; set, setnet. Regions: AP, Alaska Peninsula; BB, Bristol Bay; CH, Chignik; CI, Cook Inlet; K, Kodiak; KU, Kuskokwim; NS, Norton Sound; PWS, Prince William Sound; SE, Southeast Alaska; YAK, Yakutat.

Fig. S9.

The log absolute value of downside (negative) residuals from the main component model. Figure looks qualitatively the same as Fig. S8 and so justifies using variability (positive and negative residuals) as a measure of risk. Species groups: Dun C, dungeness crab; Fin, finfish; Hal, halibut; Herr, herring; King C, king crab; S, salmon; Sab, sablefish; Sea cuc, sea cucumber; sock, sockeye salmon; Tan C, tanner crab. Gears: drift, drift gillnet; gill, gillnet for herring; ll, longline; otter, otter trawl; set, setnet. Regions: AP, Alaska Peninsula; BB, Bristol Bay; CH, Chignik; CI, Cook Inlet; K, Kodiak; KU, Kuskokwim; NS, Norton Sound; PWS, Prince William Sound; SE, Southeast Alaska; YAK, Yakutat.