How does fishing help the economy

This analysis extended many typical fisheries bioeconomic modeling approaches by considering industry sectors that support or are influenced by changes in fishery production, such as industry suppliers, employment, or even household spending. The Northeast United States large marine ecosystem LME has supported economically important fisheries for hundreds of years Link et al. Bioeconomic analyses for the region have rarely focused on system-level objectives.

Most models estimating the economic effects of fisheries management strategies in the Northeast United States have focused on a particular fishery and the direct impact of policy on fishermen.

Examples include models for scallops Harksever et al. Although some papers look at multiple species simultaneously, they tend to consider a subset of species of commercial and conservation interest and most have not taken an overall perspective of the effects of changes in fishery production on the larger economy in the Northeast United States e.

Hoagland et al. Consideration of marine sectors as a portfolio of economic activities, as well as risk related to variance of expected returns from a set of individual fish stocks via portfolio analysis, also offers opportunity for integrating economic considerations into marine management and evaluation of risk e.

Dynamically interacting models of economic and ecological processes might best account for feedbacks and interactions between changes in fishery production, ecosystem state, and economic variables. Constructing such models is, however, time and data-intensive, requiring parameterization of behavioral models that include relationships between economic variables and human decision processes and necessitate a substantially reduced number of economic sectors for modeling purposes e.

In a simpler approach, input—output models allow for coupling of ecological and economic models by quantifying both the direct and indirect economic impacts of changes in harvest rates derived from the ecological model.

Input—output models for fisheries have been used at the single species e. When applied at the ecosystem level, this approach can be used to evaluate system-wide tradeoffs across ecological, economic, and social management objectives.

Here we link the harvest from a marine ecosystem model for the Northeast United States continental shelf to an input—output regional economic model for the Northeast United States. We calculate changes in socio-economic indicators such as jobs and earnings and compare these changes to values of ecological indicators from the ecosystem model. We use the coupled models to explore the ecological and economic consequences of three simple fishing effort scenarios initialized to the historical range of these data with variable fishing scenarios projected over a 10 year period.

A baseline scenario reflects historical conditions where fishing effort during this period was substantially lower than in previos years. This is compared with two alternative scenarios where a change in effort was implemented. In particular, we wanted to quantify the effects of changes in fishing fleet sector landings associated with these effort changes on the regional economy.

This section briefly summarizes both the ecosystem and economic models, describes model coupling, and outlines the fishing scenarios tested. Rather than provide full details of model descriptions which are referenced elsewhere , we focus on relevant details for the model coupling.

Atlantis is an end-to-end marine ecosystem model that has been applied to multiple marine systems globally Fulton et al. Atlantis consists of biophysical, fishing dynamics, management, and assessment sub-models, and is intended to be a strategic tool for comparing the performance of management strategies under alternative scenarios i.

Physical parameters and flows in the system are modeled in Atlantis-NEUS using output from a regional ocean model. The biogeochemical-based ecological model of Atlantis-NEUS consists of 45 functional groups, 24 of which are vertebrates. The exploitation sub-model of Atlantis-NEUS consists of 18 fishing fleets that are combinations of fishing gears and target species. Model runs to using the predictive scenario capability of Atlantis have been compared to data from — documenting model skill for those species groups that formed the focus of model calibration Olsen et al.

Figure 1. The input—output economic model Northeast Region input—output model NERIOM; Steinback and Thunberg, was used to quantify the regional economic effects of changes in commercial fishing landings. Commercial fishing activities are grouped into 18 distinct gear sectors Table 1. Changes in output e. The estimated direct changes in gross revenues for harvesters are then tracked backward to bait and ice suppliers, gear and vessel repair shops, gas stations, and the host of other service and goods providers servicing fishermen through the NERIOM multipliers.

We acknowledge the assumptions of this approach regarding fixed inputs. However, recent years of data used to inform the parameterization of NERIOM matching the scenario period , and the scenarios we examine are from the same time period, rather than some long-term future projection during which assumptions about prices and inputs would be more tenuous, may make this less of a concern.

Table 1. Linking the ecosystem and economic models required mapping fisheries landings by Atlantis fleets and spatial regions to NERIOM fleets and regions. These delineations are made to reflect the substantially different economic production functions associated with each type of vessel.

In Atlantis, fleets are based on gear type and target species groups. Table 1 summarizes the proportional amount of landed catch for each Atlantis fleet that was transferred to each of the NERIOM fleets using this approach. The mapping differs substantially depending on the species and gear being considered. Our mapping explicitly accounts for such differences. Fishing effort within Atlantis-NEUS is not directly associated with ports because a distance-to-port-based fleet dynamics model is not implemented in the effort scenarios used.

The distribution of fishing effort for each fleet is allocated spatially in the Atlantis-NEUS model according to prescribed distributions that can change over time to be characteristic of the historical data. We allocated landings to ports within Atlantis by assuming that the landings of each fleet by spatial box could be assigned to ports based on the distance of the centroid of the box to the ports.

We tested the sensitivity of the assumption for this relationship by also calculating landings by port assuming inverse distance rather than inverse squared distance. While the values for the landings by port changed slightly, these did not impact results qualitatively. The ports defined within Atlantis and the regions modeled in NERIOM differ, meaning that landings were again mapped between the two models.

Port to region mapping was conducted through a hierarchical assignment algorithm. The first step assigned ports to the region of the Northeast coast in which they fell based off the original county definitions used to classify regions in the NERIOM model.

The second step in the algorithm then attributed landings to regions within the NERIOM model that had no corresponding port of landing in Atlantis. For example, landings to the port of Atlantic City were allocated to New York. Although this allocation may in some instances be questionable, the inverse distance squared function that allocated landings from Atlantis boxes to ports is also an approximation.

At the Northeast Region level, sub-regional differences between observed and modeled landings are not large enough to have measurable effect on the NERIOM estimates of economic impacts. To better reflect recent patterns of landings, the final step of the port to region mapping re-allocated landings from regions with no recent history of specific fleet activity to nearby regions that have had landings from that fleet. We use the coupled models to explore the ecological and economic consequences of three simple fishing effort scenarios initialized to cover the historical range of these data — We then started variable fishing scenarios projected for the period —, and focused our reporting on results for the final 5 years of that time period.

Three fisheries management scenarios were considered in Atlantis to evaluate the effects of changes in landings on the regional economy: 1 a base scenario of fishing effort for — fixed at levels consistent with observed data for the Northeast United States from —, 2 a reduced effort scenario where the fishing effort for — was halved for all Atlantis fleets compared to the base scenario values, and 3 an increased effort scenario where fishing effort for — was twice that in the base scenario again, for all fleets.

We selected the fixed effort scenario described in Link et al. We chose the multiplicative, cross-fleet effort scenarios as alternatives to the base to quantify economic effects that bracket common and reasonable large-scale changes in fisheries operations which have been observed. While more complicated fisheries management scenarios could be envisaged, these simple scenarios provide an easy way to demonstrate economic impacts at the regional level.

Scenarios where the magnitude of the effect size on fishing effort was even greater e. As NERIOM is a static model, this provided one way to moderate some of the inter-annual variability in landings within the analysis. For each of the three Atlantis scenarios, biomass and landings by species group were recorded, in addition to a set of ecological indicators that capture fundamental features of marine ecosystems related to fishery exploitation e.

Output from NERIOM is summarized in terms of effects on sales, income, and employment, both at the regional level and by individual sector. In our analyses, we focus on the changes in quantities of interest under the reduced and increased fishing effort scenarios relative to those obtained from the base scenario rather than the absolute values for metrics.

Decreases in catch under the reduced effort scenario were not necessarily associated with increases in biomass, with very small changes in biomass in some cases decreases for lower trophic level groups, mainly as a result of increased predation pressure from the increased biomass of other piscivores Figure 2. Catch declined under this scenario for a few species notably cod and silver hake. In general, species groups that showed large increases in biomass under the reduced effort scenario compared to the base showed large decreases in biomass under the increased effort scenario Figure 2A ; e.

Figure 2. Changes to the A biomass and B catch of individual Atlantis species groups for the reduced and increased fishing effort scenarios compared to the baseline. Species groups are arranged vertically by trophic level with lower trophic level groups at the bottom. Figure 3. Levels of response for ecological and economic indicators to the three fishing effort scenarios.

Ecological indicators are the average value from the terminal 5 years of the run, the period used to calculate the economic indicators. The effects of the changed effort scenarios are also seen at the system level. While the effect on total ecosystem biomass was much smaller than this, the fish community was impacted with a decrease in the ratio of demersal to pelagic fish under the doubled effort scenario and a concurrent increase in this indicator for the reduced effort scenario Figure 3.

Threatened and protected species were affected by the changes to fishing, with the biomass of seals and birds being reduced in the increased fishing effort scenario Figure 3. A larger number of species groups were observed to fall below commonly used management reference points in the increased fishing effort scenario.

The proportion of species groups deemed to be overfished i. As described at the species level, changes in catch were more prominent for pelagic groups than demersals, with total catch from pelagics having a higher magnitude of change than that of demersals under both increased and decreased effort scenarios.

In contrast, large increases e. Although the magnitude of the differences was small, average incomes under both the increased and decreased effort scenarios were lower than that in the baseline.

Figure 4. The number of jobs for some of the fishing sectors was more sensitive to the increased effort scenario than total sales e. There were distinct regional differences in the magnitudes of effects for the changed effort scenarios, reflecting the differences in species and fleets associated with the various ports. Most notably, the changes in sales and employment for the scallop dredge sectors that occurred during the changed effort scenarios were completely a result of changes to the New England economy, with very small changes to these sectors in the Mid-Atlantic Figures 5 , 6.

In contrast, decreases in total sales from the midwater trawl sector under the decreased effort scenario were driven by changes in New England, but increases in sales from this sector under the increased effort scenario were due to increases in the Mid-Atlantic Figures 5 , 6.

Because some of the nuances of these changes are associated with the assumptions made when mapping fleets to ports, we do not overly highlight these and instead focus on system-wide indicators that are more robust. However, these results serve to demonstrate that the consequences of management scenarios for individual sectors may be felt disproportionately through the region in addition to across sectors, an issue of importance to managers.

Figure 5. Figure 6. Under the decreased effort scenario, the reduction in total catch from the baseline scenario means there is less demand from seafood processors and traders for goods and services required to handle the catch. Similarly, the increase in total catch from the increased effort scenario provides more business for seafood processors and subsequently more demand for industries supplying these sectors.

Taking the fishing fleet sectors alone, the economic system consequences mirror those of the regional indicators shown in Figure 3 , even though individual sectors showed more varied responses to the scenarios and by region Figure 4.

We linked the output of a marine ecosystem model to a regional economic model for the Northeast United States, and estimated the impacts of simple management strategies on both ecological and economic indicators. The value of using a coupled modeling approach to quantify these effects is that it is possible a to make use of extant tools facilitating relatively rapid analysis and b to retain the detail associated with both the ecological and economic systems.

Such detail is often lost when using a single model approach that bridges across disciplines and spatial and temporal scales e. Coupling existing models, even in a one-way fashion as we did here, greatly facilitates the simultaneous consideration of multiple management objectives.

A key element of ecosystem-based management of marine resources is the development of analytical tools for quantifying tradeoffs associated with human activities Leslie and McLeod, ; Link, We quantified tradeoffs among ecological groups associated with alternative fishing scenarios, with shifts in ecosystem composition and resulting changes to both magnitude and composition of landed catch.

Under our increased effort scenario, the total amount of fisheries landings increased but not linearly with effort , leading to a higher proportion of species groups overfished compared to the baseline and reduced effort scenarios.

At the system level, our increased fishing effort scenario increased sales, income, and employment, yet there was very little change to the average income. This implies that the dynamics of the entire ecological and economic system may have some inherent stability despite individual taxa or fleet dynamics Link, Our analyses suggest that the economic impacts of fishing scenarios on individual industry sectors, particularly harvesting sectors, can be large and variable even though system level properties were predictable and robust.

These large, systemic effects were observed even during the relatively short time period for our model projections; consequences would potentially be amplified if viewing these scenarios over the long term.

Costello contends that such a comparison would provide fishermen and other stakeholders with the necessary information to better advocate for management approaches that reflect their diverse goals and promote the long-term prosperity of the U.

Former U. Treasury Secretary Robert E. Rubin will open the forum, followed by a roundtable discussion on the new proposal. Costello will be joined by Lee Crockett, Director of U. For the full agenda and to register for the forum, please click here. For updates on the event, follow hamiltonproj and join the conversation using CastTheNet.

Benjamin H. Related Books. This umbrella multi-donor trust fund, administered by the World Bank, focuses on four key themes:. Active regional programs include support for the Pacific island region , South West Indian Ocean fisheries management, a partnership to build governance for migratory fish stocks in areas beyond and between national jurisdiction , as well as regional technical assistance to combat coastal erosion in West Africa.

The Blue Economy report discusses long-term benefits of the sustainable use of marine resources for small island developing states and coastal least developed countries. The What a Waste 2. In the past two years, the Bank has provided analytics to countries in all regions to advise on the way forward, as reflected in many countries in East Asia , South Asia and Africa. The Bank convenes partners and stakeholders to mobilize ocean investment, advocate for positive reforms and ensure that healthy oceans remain on the global development agenda.

The WACA program provides countries with access to technical expertise and finance to support the sustainable development of coastal zones, using the management of coastal erosion and hazardous flooding as entry point. The program consists of a series of coastal resilience investment projects ResIP and a scale-up Platform.

Preparations are underway to start projects in Ghana and Nigeria. The WACA Platform has three functions: to facilitate and increase access to knowledge, expertise, global good practices, and technical assistance; to leverage and crowd-in financing for coastal resilience investments; and to provide a forum for dialogue to facilitate the involvement of other key partners, including the private sector.

Also in West Africa, the West Africa Regional Fisheries Program aims to increase the economic contribution of marine resources through strengthened fisheries governance, reduced illegal fishing, and increased value-added to fish products. In Senegal, for instance, fisheries co-management structures were legally established in 12 communities which resulted in an increase in the size of fish caught in all communities targeted by the Project and more value for the communities as well as a 70 percent decrease in illegal fishing in several artisanal exclusive areas.

In addition, the introduction of cleaner smoking ovens reduced toxins by an estimated 73 percent — and generated a reduction in the amount of wood consumption while increasing the value of the fish.

Another example is Guinea, where the project allowed for curbing illegal fishing, better preserving the resources, sharing the benefits with communities, and transforming the livelihoods of 50, people, mainly women - a newly-constructed landing site and a smoking facility enabling the processing of fish under improved hygienic conditions formed part of this intervention. The WARFP program is now closing but has inspired a series of national fisheries projects along the coast of West Africa, including Cabo Verde under preparation , Senegal under preparation , and Liberia approved.

More than a thousand artisanal fisher households have already benefited from the project since its launch in February In Vietnam, the Coastal Resources for Sustainable Development Project aims to improve the sustainable management of coastal fisheries. It has successfully promoted integrated spatial planning ISP for coastal areas, the adoption of improved biosecurity in aquaculture, and co-management arrangements for near-shore capture fisheries.

For example, by the end of the project, 50 shrimp Good Aquaculture Practices GAP zones were established, and GAP groups formed with 9, shrimp households participating and covering an area of 12, ha. The GAP zones were designed to manage the problems of disease, water pollution, and low productivity which affected the shrimp farms before the project.

One of the key factors in improved shrimp farming was the monitoring of environmental risks caused by poor management of wastewater and solid waste from shrimp farms. In October , 86 percent of farms in GAP zones applied wastewater treatment that met the national standards for environmental management and 93 percent of the farms practiced proper pond sludge handling after harvest, compared to 9 percent before the project.

The project also funded additional laboratory equipment, upgraded station facilities, and provided training to better control and reduce disease infection and outbreaks in the project provinces. The response time from disease reporting to effective disease outbreak containment was reduced from more than 10 days before the project to less than 4 days after. Now in its third phase, the project is strengthening Indonesia's oceans research capacity by upgrading laboratories, training scientists, and undertaking nationwide ecosystem monitoring.

It is also improving management effectiveness in nationally-significant marine protected areas in Raja Ampat, West Papua and Sawu Sea, East Nusa Tenggara, through ecotourism initiatives, community-based surveillance against illegal fishing, and threatened species conservation. PROP is providing support in the Monitoring, Control and Surveillance MCS of fisheries to safeguard the livelihoods, nutrition sources and revenues of governments and communities.

The program has supported countries in training and expanding fisheries observer programs, including improving safety with designated equipment — a pressing need for the industry.