① Cod Fishing Case Study

I did not really understand the importance of what I was doing at the Cod Fishing Case Study, but I enjoyed the camaraderie and david attenborough siblings exercise despite Helicopter Persuasive Speech oyster shells for what it Cod Fishing Case Study like an endless amount of time. Biogeosciences Discuss — In 50, people were George Orwell 1984 Themes fishing, but in there was only 27, still in the fishing industry. New York MagazineJuly 18, Whatever Cod Fishing Case Study alternative, fishing for Cod Fishing Case Study is Cod Fishing Case Study something that can easily be replaced in the culture of a community such as Gloucester. Can New Cod Fishing Case Study cod fishing industry survive?

Newfoundland cod fishery: Lessons not learned?

Thus, with the collapse of the cod fishery was not only economically crippling but also detrimental culturally. The ecological and socioeconomical impacts of the collapse prompted people and the Canadian government to critically evaluate the way in which commercial fisheries were managed in order to recover the cod population and prevent such dramatic declines in abundances happening in other fish species in the future. Moreover, there are numerous explanations for the commercial collapse of the cod population. These reasons range from the of climate change to the advancements in fishing technology.

It is hypothesized that poor recruitment, reduced juveniles surviving to be recruited into the population, increased seal predation, along with domestic …show more content… Harp seals Phoca groenlandica were very abundant in the region at the time and there exists evidence suggesting their numbers increased Sten- son et al. Additionally, studies have shown that the contribution of cod to the seal diet overwinter area was greater than reported Hammill et al. These fish are migratory and are known to traverse the Atlantic Ocean in a few months. Bluefin tuna are among the largest bony fish in the ocean, reaching over 3. Their lifespan can exceed 30 years, making them long lived among fish species [9]. Catches of Atlantic bluefin followed a generally declining trend from the early s to the early s [10].

The Atlantic population of the species has declined by nearly 90 percent since the s [11]. Atlantic bluefin tuna take eight years to mature to large-medium sized fish. Scientists believe that the decline in the numbers of larger sized bluefin tuna can be attributed to the high volume of juvenile bluefin tuna caught. The problem is that fishers catch so many juvenile bluefin tunas that there are none left to mature [12]. There are two ways to save the Atlantic bluefin tuna stock- protect them in their breeding grounds and in their feeding grounds.

This will require immediate action in both the central Atlantic, to reduce the mortality of the giant bluefin while foraging, and in the Gulf of Mexico and Mediterranean, where bluefin breed as discrete populations [13]. It is difficult to be prescriptive regarding what is an appropriate extractive policy for a fishery; the policy will differ depending on the individual characteristics of the fishery, the fishers and the objectives of the property right holder. Without a clearly defined set of policies, the consequent institutions may not achieve a desired result [15]. Economics of fisheries- Encyclopedia of Earth. Log in. Page Discussion. Read View source View history. Jump to: navigation , search.

Burger, et al. Although evidence for commercially exploited fish species is still sparse, it does suggest non-uniform reactions for different species or stocks [ 14 — 19 ]. Given the uncertainties on the single-fish species level it is by no means easy to up-scale physiological responses to ocean warming and acidification to the level of the fish population. This exercise, however, is essential to inform policy-makers about possible consequences for food security and help designing appropriate mitigation and adaption strategies.

To this end, one possible methodology is to incorporate the effects of ocean warming and acidification into the stock-recruitment relationship within a bio-economic fishery model. This strand of literature is relatively new and has mostly analyzed either ocean warming [ 20 — 22 ] or ocean acidification [ 23 — 26 ] in isolation. Only very few studies [ 27 — 30 ] combine ocean warming and acidification effects on recruitment within an integrated bio-economic model.

Lam et al. Fernandes et al. Unlike Lam et al. Closest to our modelling framework are Cooley et al. Cooley et al. OA effects on scallop recruitment are included into a Berverton-Holt stock recruitment relationship while deep-water temperature and ocean acidification effects on scallop growth are used to adjust the body growth coefficient of adult scallops, which is assumed directly proportional to the growth in calcification.

Voss et al. They alter the parameters of growth and natural mortality of a Ricker type stock-recruitment function in a dynamic age-structured fishery model and find that the management of the Western Baltic Cod fishery will not be able to adapt to the combined effect of ocean warming and acidification. Our contribution to this strand of literature is twofold: First, we provide a very relevant case study. The effect of rising temperatures on Northeast Arctic cod recruitment has so far been positive [ 21 — 22 ], and likely has supported stock management and assisted in stock recovery over recent years.

However, comparisons between cod stocks suggest a non-linear relationship between temperature and recruitment. Whereas overall the effects of ocean acidification are still less understood, there is evidence that ocean acidification may have a significant effect on recruitment of Northeast Arctic cod [ 14 , 36 ]. It is therefore becoming increasingly important to not study the effects of ocean warming in isolation, but in interaction with ocean acidification as an additional stressor that impedes recruitment success.

Moreover, due to polar amplification the Arctic Ocean and the marginal Barents Sea are warming faster than the global average [ 37 , 38 , 4 ] and are expected to experience the strongest acidification of the global ocean [ 39 ]. Second, our methodology brings together time-series econometrics, experimental data and bio-economic modelling. Thereby it offers a promising methodology to analyze the sustainability of renewable natural resources and its repercussions on key socio-economic indicators.

Our results confirm the initial positive effect of ocean warming on the Northeast Arctic cod stock, but also indicate an optimal temperature beyond which additional warming negatively influences recruitment and fishing outcomes. When considering the additional effect of ocean acidification that is projected under a business-as-usual scenario, the fishery could be at risk of collapse by the end of the century, even if fishery management would optimally adapt fishing pressure and gear selectivity. We quantify both the isolated and combined effects of ocean warming and acidification on Northeast Arctic cod recruitment using time-series data of ocean temperature from the Kola Section—one of the longest oceanic time-series and a well-known indicator of Barents sea temperature [ 40 ]—as well as published experimental data from Stiasny et al.

We scale up physiological responses to ocean warming and acidification to population-level processes by considering how both stressors could modify the parameters of growth, mortality and reproduction within a Ricker type stock-recruitment relationship [ 41 ] in an age-structured fishery model. Following Hjermann et al. Mortality during the recruitment process is due to density-independent and density-dependent effects, both of which may potentially be affected by warming and acidification.

Although Myers and Cadigan [ 44 ] and Fromentin et al. To include the effects of ocean warming in the stock-recruitment model for Northeast Arctic cod, we use annual time-series data on spawning stock biomass and recruitment numbers from to supplied by the International Council for the Exploration of the Sea [ 46 ]. The monthly temperature data were taken from the Kola Section [ 40 ]. Although these data are not depth-specific, the monthly-integrated mean is a widely used indicator for the impacts of ocean warming on cod populations in the Barents Sea [ 47 — 50 ]. Using Ordinary Least Squares regression, we find that the January temperature statistically best explains recruitment within this period.

We find a non-linear effect of the January seawater temperature on recruitment. Initially a one-percent increase in January seawater temperature leads a 4. Hence, we find that stock recruitment for Northeast Arctic cod is an increasing but concave function of the January seawater temperature. The latter implies an optimal temperature beyond which additional warming has a negative effect on recruitment. Estimates of mortality increase due to ocean acidification are based on experiments by Stiasny et al.

The results were consistent under different feeding regimes. In this study we use the estimate of Stiasny et al. While the time-series approach for integrating ocean warming effects allows us to model a continuum of ocean warming, the experimental results only support an analysis of the additional effect of projected end-of century ocean acidification compared to a scenario without acidification.

Following the approach of Tahvonen et al. The model calculates the economically optimal fishing effort and related total allowable catch TAC to be set under steady state conditions. This analysis considers maximum economic yield management, i. The number of fish that are caught from age class s in year t is denoted by h st. Spawning stock biomass follows as 2 for which weights-at-age w s are taken from ICES [ 46 : table 3. The relationship between spawning stock biomass and recruitment three years later is captured by calculating recruitment as one-year old fish that then face zero natural mortality until becoming three-year old fish. The sorting grid became mandatory in the Northeast Arctic in All fishing trawlers must use a grid with a minimum bar spacing of 55 mm [ 53 ].

The equality 6 used above follows from the assumption that the share of age class s in a catch equals its share in efficient biomass, 7. For Eq 8 Sistiaga [ 53 ] have estimated the following relationships for Northeast Arctic cod, while we use the means of the values reported by ICES [ 48 : tables A5, A7 and A1] for the length-at-age values l s. Following the approach of Diekert et al. For each weight category and year, the cumulated catch value in NOK was divided by the respective cumulated live weight caught.

Our model of fishing costs assumes that fishers choose the different input variables capital, labor, fuel such as to maximize profits. Adopting the standard formulation from biomass models, fishing profits and hence profit margins can be written as 11 12 which we rearrange to yielding the following equation: For this, annual means of the profit margins of Norwegian trawlers, defined as , were calculated from data of the Norwegian Directorate of Fisheries [ 58 ]. In our optimization model, we determine catches and grid size of the fishing gear such as to maximize the annual profit Eq 11 subject to the age-structured population dynamics Eqs 2 — 6 and gear selectivity Eqs 7 and 8.

As the population dynamics of cod are on a much faster time scale than ocean warming and acidification, we report all optimized variables for a fish population that is in steady state under the given climate conditions. As the first step of the analysis, we construct a risk of stock collapse indicator by considering the combined effects of fishing, warming and acidification. For this sake, we vary both fishing mortality and January temperature to study the combined effects of fishing and warming on the expected stock size in steady state.

We repeat the analysis for the case with and without acidification-induced mortality of early life history stages of cod. Thus, our analysis includes a temporal evolution of January temperature from the Kola section, but can only capture the same level of ocean acidification for every incremental increase in ocean temperature. In all computations, we keep the sorting grid size at 55mm, according to current regulation [ 53 ]. Specifically, the risk of stock collapse indicator is constructed by using the age-structured fishery model to compute the resulting steady-state stock size under the combined stressors of ocean warming and acidification and divide it by the unfished steady-state biomass for the optimal temperature.

Thereby we obtain an indicator of how the combined stressors of fishing, warming and acidification reduces the equilibrium stock size. The risk of stock collapse is then calculated as one minus this indicator. As a second step, we used the age-structured ecological-economic optimization model to calculate the economically optimal fishing management in terms of fishing mortality and gear choice for different levels of temperature increase, and with or without acidification effects. We thereby investigate how to best adapt the management of the Northeast Arctic cod fishery to changing environmental conditions.

Adaptation to the environmental stressors of ocean warming and acidification could be implemented by reducing fishing pressure on the stock, for example by decreasing total allowable catches, or by adapting the selectivity of fishing gear, to preserve more older spawners which have a higher fertility. We analyze the effect of increasing seawater temperature and fishing pressure on the target stock size. Subsequently, we take the additional mortality due to projected end of century ocean acidification into consideration.

Specifically, we calculate the economically optimal fishery management in terms of fishing mortality and gear choice for different levels of temperature increase, and with and without the additional ocean acidification effect on mortality. Fig 1 shows the risk of stock collapse as a function of i seawater temperature increase in January, which is the month with the highest explanatory power on recruitment, and ii fishing mortality. Darker shades of red indicate a higher risk of collapse.

For example, a value of 0. While the left panel considers only fishing pressure and ocean warming, the right panel takes the additional effect of larvae mortality due to ocean acidification into consideration, indicating a strongly increased risk of collapse. In both plots, the January seawater temperature ranges from 2. At this temperature, the stock can support a much higher fishing mortality for the same risk of stock collapse.

Overall, ocean acidification greatly increases the risk of stock collapse. Under the combined effect of warming and acidification, the levels of fishing mortality that the stock can support to minimize the risk of stock collapse are much lower than under warming only. In this case the fishery management would have to adapt by drastically lowering fishing pressure on the stock. Depicted are catch and recruits top panel , fishing mortality and mean age of catch under optimal management middle panel , and net revenue and spawning stock biomass lower panel. Plots in the left column show results for warming only, while plots in the right column show results for the combined effect of warming and acidification. It is important to note the marked change in scale for the two sets of vertical axes.

The ecological-economic model determines optimized fishing mortality, size of the spawning stock, catch level, and profits for the fishery Fig 2A—2C. The temperature range considered spans 2. The number of recruits is at a maximum of million for a temperature optimum around 4. At about 0. At the optimal temperature of 4. The sorting grid size is chosen such that the mean age of catch of 6. The combined effect of ocean warming and acidification on the stock-recruitment of Northeast Arctic cod results in severe outcomes for the fishery see Fig 2D—2F. Recruitment and catch are reduced to about a quarter of the numbers reached when acidification is excluded.

Under the optimal January seawater temperature for the fishery 4. Hence, under ocean acidification the fishery is much more vulnerable to temperatures that deviate from the optimum. In summary all social-ecological indicators point in the same direction: Commercial fishing activities will need to be reduced drastically to sustain the profitability of the Northeast Arctic cod fishery under ocean warming and acidification. The analysis examined how increasing temperature and CO 2 affect ecological stock size , economic profits , consumer-related harvest and social fishing effort indicators, ranging from present-day conditions to future climate change scenarios.

Results show that climate change will benefit the fishery as long as the temperature is still below the optimum for cod reproduction. However, under a combined scenario of ocean warming and acidification that is likely to occur by the end of the century in the Barents Sea, this commercially important fishery may be at risk of collapse, even with the best adaptation efforts in terms of reduced fishing intensity. This study faces limitations in current knowledge that can provide new challenges for future research. The first limitation relates to the physiological response of fish populations to ocean acidification, which is highly uncertain.

On the one-hand potential negative impacts have been found for the organ structure of larvae fish [ 15 , 17 ], hatching success [ 60 ], sensory abilities and behavior [ 61 — 62 ] or with respect to the survival in very early larval stages [ 13 , 63 ]. Early life stages prior to gill formation have a limited capacity for pH regulation [ 64 ] and are therefore more vulnerable to environmental change. On the other hand, for different fish populations other studies have reported no impact on egg or larval survival under acidification levels addressed in this study [ 15 , 19 , 63 ]. Moreover, research that suggests effects on behavior could not be replicated in recent studies [ 65 ].

In addition, due to the high capacity of adult fish to osmoregulate, they have been found to be tolerant to extreme values of ocean acidification [ 66 ]. Thus, we neglect the potential for acclimation and adaption to ocean acidification resulting in potentially over-pessimistic scenarios. The second limitation relates to how ocean warming and acidification are incorporated into the integrated bio-economic modelling framework. With respect to ocean acidification this study builds on the experiments reported by Stiasny et al.

The elevated CO 2 treatment corresponds to a business-as-usual emissions scenario consistent with RCP8. Additionally, considering the faster climate change in the Arctic region due to the feedback related to retreating sea ice and the high solubility of CO 2 in colder waters, ocean acidification in high latitude regions will far exceed the global average making our scenario likely much earlier [ 67 ]. Because until now experimental work cannot provide data for a case between the two extreme scenarios, it will be important to explore other ways of quantifying the implications of ocean acidification on recruitment.

Thereby, the effect of temperature increase on recruitment has both a direct physiological impact on juveniles and an indirect effect through other climate variables as well as changes in prey fields and food availability [ 70 ]. Sundby [ 70 ], for example, suggests that the recruitment-temperature relationship for Atlantic cod is a proxy for food availability of the copepod Calanus finmarchicus during early life stages. In this paper, we did not describe mechanistic processes how temperature affects recruitment. Rather we have adopted a reduced-form approach and estimated the compound effect of temperature changes on cod recruitment by means of a statistical analysis of time series data.

Accordingly, projections have to be considered with caution, especially if they go beyond the past range of variation in climate variables and recruitment.

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