Some of the greatest successes—and most formidable remaining challenges—in environmental governance center on common pool resources such as forests and fisheries. Early thinking about managing common pool resources to avoid overuse focused on establishing centralized government control or private property rights (Scott 1955, Hardin 1968). More recently, researchers have demonstrated that local resource users can take voluntary collective action to sustainably manage these resources (Berkes et al. 1989, Ostrom 1990). This local collective action, set within broader polycentric governance arrangements, can promote social-ecological resilience to resource collapse (Feeny et al. 1990, Dietz et al. 2003, Carpenter and Brock 2004, Gutiérrez et al. 2011).
Under limited access, users may have incentives to invest in improving or maintaining the resource when those investments yield benefits greater than those that would result from not investing (Ostrom 1998). Under open access, in contrast, incentives for investment are reduced or eliminated because any returns are dissipated as improvements in the resource draw more users into the system (Smith 1968). For this reason, previous work on enabling conditions for collective action has focused on cases where resource users hold the property right of exclusion, via either government- or community-defined rules, and so can limit access (Berkes et al. 1989, Feeny et al. 1990, Ostrom 1990, McGinnis 1999, Dietz et al. 2003).
Most recreational fisheries in North America are open access common pool resources because the license fee for recreational anglers is low and the number of licenses available is unlimited (Post 2013, Arlinghaus et al. 2019). Yet investments in voluntary fish stocking by local anglers occurs widely throughout North America and in open access fisheries around the world (Korth and Klessig 1990, Lorenzen et al. 1998, Johnson et al. 2009). This observation, other recent empirical evidence that shared resources can sometimes be governed successfully without limited access or clear boundary rules (Baggio et al. 2016, Moritz et al. 2018), and the imperiled state of recreational fisheries globally (Post 2013, Arlinghaus et al. 2019) all suggest a need to re-examine theory about investments in open access common pool resources.
To explore investments in open access common pool resources, we adapted a classic model of fishery dynamics (Smith 1968), which we parameterized and tested with empirical data. We demonstrate a previously unrecognized mechanism that can create incentives for investments in common pool resources, even under the widespread open access conditions that were previously thought to eliminate such incentives.
We adapted a classic open access fishery model (Smith 1968) to describe a lake recreational fishery in which either a local or a centralized manager seeks to maximize welfare to individuals in their purview by choosing the rate at which to invest in stocking fish through time. The local manager is a collective action organization composed of lakeshore residents, and focuses on maximizing welfare only for resident anglers. The centralized manager is a state fisheries agency, and so its definition of welfare includes resident anglers but also roving anglers who reside elsewhere and visit the lake to fish. We focused on the conditions that incentivize investments in a common pool resource by local and centralized managers under open access; we did not explore the emergence of local collective action, which has been addressed extensively elsewhere (Ostrom 1990). We provide a complete description of the model including equations and parameter values in Appendix 1, and solve analytically for the optimal stocking rate in Appendix 2.
Resident and rover fishing effort in our model respond positively and sluggishly to fishing quality (Smith 1968), defined separately for residents and rovers as the current average net benefits of catch less the access costs. Access costs influence effort allocation in fisheries, and are an important axis of heterogeneity between angler groups in our model because residents have lower marginal access costs than rovers (Clawson 1959, Brown and Mendelsohn 1984). Our effort model follows bioeconomic theory for open access fisheries, which assumes that effort responds myopically to current average net benefits (Gordon 1954, Smith 1968, McConnell and Sutinen 1979, Anderson 1993). Although myopic behavior is a standard assumption in models of aggregate fishing effort in open access, alternative models of capital investments in open access have been developed based on the assumption that resource users have rational expectations and make participation decisions based on the entire future path of net benefits (e.g., Berck and Perloff 1984, McKelvey 1985). However, our setting is characterized by relatively low capital requirements for participation, which suggests that the assumption of myopic behavior is a better representation of the participation decision. Sluggishness in models of fishing effort is typically understood to represent delays in response times due to the need to divest capital out of one fishery and invest that capital in an alternative use. For recreational angling where investments in participation are minimal, a better motivator for sluggishness is the difference between expected and realized utility. For example, with a model of adaptive expectations, where individuals formulate their expectations based on information from the past, anglers will systematically over-predict their utility from fishing if the fish stock level is declining over time, leading to a sluggish exit even when utility is negative. Adaptive expectations is a reasonable assumption in our scenario where the fish stock levels are unobservable by anglers, and is the most commonly employed assumption in empirical models of fishing location choice where backward rolling averages of revenue are used to define expected revenues from fishing (Smith and Wilen 2003). In keeping with the open access nature of most recreational fisheries in North America, we assume that there are no formal or informal institutions that limit effort.
Our model is generalizable to any harvest-oriented recreational fishery, but in this analysis we parameterized it from the literature to represent the open access fishery for walleye (Sander vitreus) in lakes of northern Wisconsin, USA. In this region, recreational fisheries are socially, economically, and ecologically important and have been studied extensively (Liu et al. 2007). Walleye is the most commonly fished and stocked species; it is fished primarily for harvest but is released voluntarily at low rates (Fenton et al. 1996, Beard et al. 2003, Gaeta et al. 2013). Collective action organizations in this region often invest in stocking walleye in their lakes, even though maintaining and enhancing fisheries is only one of many factors that led to the initial formation of those organizations (Gabriel and Lancaster 2004). As in northern Wisconsin, walleye and its congeners support important recreational fisheries across northern North America and Eurasia.
We solved the model numerically to find the optimal stocking rates through time that maximized the management objective under either local or centralized management, and identified the conditions that created incentives for stocking investments.
As a check on the validity and utility of our model structure, we examined whether model-predicted rates of local and centralized stocking, and model-predicted fish abundance, were similar to observed data from a set of lakes in the region for which the model was parameterized. Data on local and centralized stocking, resident and roving angler effort, and (in most cases) walleye abundance were available for 46 lakes in Vilas and Oneida Counties, northern Wisconsin. All of these lakes have public boat launches that are maintained by the state. For each of these lakes, we parameterized a version of our model that included lake-specific estimates of resident and roving angler effort, roving angler access costs and willingness to pay for harvest, and catchability. We then asked, without fitting or tuning the model, whether lake-specific model predictions of stocking rates and walleye abundance were similar to the observed data.
Local users had clear incentives to invest in the fishery despite open access (Fig. 1). The optimal equilibrium stocking rate for local managers was positive as long as resident anglers were present, and it was positively related to the contribution of resident anglers to total effort (Fig. 1A). The contributions of resident and roving anglers at equilibrium depended on initial conditions because high initial effort by one group reduced the catch benefits available to the other group (Appendix 1, Fig. A1.1). Local investments in stocking led to gains in welfare for local residents, and also for rovers (Fig. 1B, Appendix 3). The gains for residents were largest when residents comprised most of the equilibrium angling effort but were positive even when they were rare relative to rovers.
Incentives for local investments arose from the transient welfare that accrued during the transition to equilibrium (Fig. 2A). We illustrate this result with a simulation initialized at the open access, no-stocking equilibrium; this represents the least favorable conditions for the emergence of investment incentives, and the results hold for other initializations, such as a “pristine” state with low fishing effort and a fish stock near carrying capacity (Appendix 4, Fig. A4.1). Our model, like classic open access fisheries models, shows that rents are dissipated at equilibrium (Fig. 2A). Nonetheless, substantial gains in welfare occur during the transition to equilibrium as higher catch rates draw effort into the system. These welfare gains are followed by welfare losses as catch rates decline and effort begins to leave the system, but the gains outweigh the losses. Furthermore, switching at any time from the optimal stocking path to a no-stocking alternative results in sharp reductions in welfare, and so is disincentivized (Fig. 2A, dashed line). Incentives for local investments did not depend on institutional limits on open access (which were absent from our model) or on high access costs for roving anglers relative to residents (Fig. 1), and key results from our model hold if marginal costs of effort are increasing (Appendix 5).
Transient welfare also created incentives for a centralized manager to invest in the fishery (Fig. 1, Fig. 2B). The centralized manager’s definition of welfare included roving as well as resident anglers; thus, the optimal stocking rate was higher under centralized management (Fig. 1A) and the gain in welfare from stocking was larger (Fig. 1B). These increases arose partly from rovers’ high access costs and thus the high value that they placed on harvest, relative to residents (Appendix 3), but were present even when we set the value of harvest equal for rovers and residents (dashed yellow line in Fig. 1A). The centralized manager’s more inclusive definition of welfare also meant that, unlike under local management, the optimal stocking rate and the welfare gains from stocking were negatively related to the contribution of resident anglers to total equilibrium effort (Fig. 1A, 1B). When residents comprised most of the angling effort, centralized and local management led to similar stocking rates and welfare gains.
Empirical observations showed patterns similar to those predicted by our model (Fig. 3). Stocking of walleye by local lake organizations and the centralized management agency varied widely, in both absolute and relative terms (Fig. 3A). Local lake organizations stocked at lower rates than the centralized agency (mean = 4 and 31 fish ha-1 year-1, respectively, t38 = 5.2, p < 0.001). Local stocking was positively related, and centralized stocking was negatively related, to the proportion of residents in the angler pool, and stocking rates under the two management regimes were similar in lakes where residents comprised > 80% of angling effort (Fig. 3B; compare to solid lines in Fig. 1A). Quantitatively, the model predicted local stocking rates reasonably accurately but under-predicted centralized stocking rates (Fig. 3C). Empirical observations of walleye density also agreed well with model predictions, for both local and centralized stocking (Fig. 3C); this makes sense despite the high empirical centralized stocking rates because equilibrium fish density under open access is independent of stocking rate and depends only on parameters for which we had lake-specific empirical estimates (Appendix 1, Eq. A1.8, Table A1.1).
Our results demonstrate that transient dynamics create incentives to invest in improving common pool resources, even under open access. Economists have considered transient welfare in dynamic models as an incentive to invest in exploitative capital such as fishing boats (Smith 1968, Berck and Perloff 1984, McKelvey 1985, Sanchirico and Wilen 1999, Wilen 2018), but we show it can also create incentives to invest in improving the resource and that those incentives can persist even when net benefits are driven to zero in equilibrium. Moritz et al. (2018) hypothesized that ecological dynamics such as disturbance regimes that keep a system in transition to equilibrium can prevent overuse of open access common pool resources. Our results provide a mechanistic understanding of the importance of transitional periods for unique investment incentives for open access common pool resources that can drive collective-action decisions and equilibrium outcomes.
The model predicts positive stocking rates at equilibrium (Fig. 1), even while net benefits to anglers are driven to zero (Fig. 2). Together these results imply that it is optimal to operate at a loss, paying for stocking even when anglers receive no net benefits from their harvest of stocked fish because their utility from harvest is exactly offset by their access costs. This occurs because ceasing to stock at any point would create a painful transition to a new bioeconomic equilibrium with a lower unstocked fish population. While the assumption of complete dissipation of net benefits may be strong for recreational fisheries (Horan et al. 2011), our results suggest that observing collective action investments in a common pool resource system does not necessarily mean that resource exploitation in the system is prudent or efficient.
Local stocking occurred at rates similar to our predicted optima, while stocking by the central management agency occurred at considerably higher rates (Fig. 3C). At least three mechanisms not captured by our model may contribute to high centralized stocking. First, centralized managers may consider a broader set of benefits than we included in their objective function. In particular, high fishing effort is often an important management goal in itself, despite posing challenges to fishery sustainability, because of its positive near-term economic impacts. This is commonly recognized in marine commercial fisheries (Stephenson and Lane 1995, Worm et al. 2009) but likely applies in recreational fisheries in places like our study region where fishing effort is an important contributor to regional economies (United States Census Bureau 2016). Second, the centralized management agency in our study region prioritizes stocking for population rehabilitation over stocking for recreation. Therefore, centralized mangers may value fish population conservation targets in ways that are unrelated to the benefits and costs to anglers. Stocking for rehabilitation may require the input of many fish to overcome ecological tipping points, positive feedbacks between fish stocks and fishing effort, or environmental stochasticity. Third, centralized managers may face significant political pressure to stock, even when doing so is not biologically or economically warranted. Future elaborations of our modeling approach could consider more nuanced models of centralized decision-making process and broader definitions of objective functions. For example, including the economic multiplier effects of fishing effort in objective functions could account for manager considerations of regional benefits of stocking. In addition, considering potential costs of stocking to biodiversity and ecosystem function could better align fisheries management with conservation objectives (Camp et al. 2017).
Our finding that incentives exist for local investment in open access common pool resources adds to a growing literature that emphasizes the benefits of polycentric governance arrangements that involve institutions at multiple scales (Schoon et al. 2015). Our analysis emphasizes that permitting and even encouraging local users to invest in improving a common pool resource, rather than limiting those powers to a centralized government, can provide benefits to both local and non-local users. This could relieve pressure on the budgets of centralized managers, thereby allowing funds to be redeployed strategically. Taken together with other arguments for local management—such as policy diversification, experimentation, responsiveness, and learning (Lorenzen and Garaway 1998, Carpenter and Brock 2004, Lebel et al. 2006, Berkes 2009, Fujitani et al. 2017)—our work helps show how local management of common pool resources can be successful, even under open access. Yet our work also demonstrates clear roles for centralized governance in enhancing social welfare, despite the social and political constraints on moving away from open access in recreational fisheries. For example, we show that in lakes where roving anglers are abundant, relying strictly on local investments yields much lower welfare than can be achieved under centralized management because local managers’ investments benefit rovers only incidentally (Fig. 1B). Given real landscapes on which the abundance of local and roving resource users varies widely (e.g., Fig. 3B), intervention by a centralized manager is likely essential to optimize investments for inclusive social welfare. Similarly, centralized interventions might be necessary to counter residents’ incentives to reduce the accessibility of lakes to rovers and so capture for themselves a greater share of the benefits of the fishery and any investments in it (Fig. 1), or to achieve other societal and conservation goals (Carpenter and Brock 2004). Thus, we emphasize both the potential for greater devolution of power and the necessity of continued centralized governance in spatially complex, open access common pool resources.
We are grateful to the Wisconsin Department of Natural Resources for providing data used in this manuscript and to G.G. Sass for feedback on a draft of the manuscript. This work was supported by the U.S. National Science Foundation under grant number 1716066 and by the Natural Sciences and Engineering Research Council of Canada under grant numbers 475586-2015 and 402530-2011.
All data and code used here will be made publicly available, upon publication of the manuscript, in the Cary Institute's figshare repository (https://caryinstitute.figshare.com/). In the interim the data and code are available from the authors upon request.
Anderson, L. G. 1993. Toward a complete economic theory of the utilization and management of recreational fisheries. Journal of Environmental Economics and Management 24:272-295. https://doi.org/10.1006/jeem.1993.1018
Arlinghaus, R., J. K. Abbott, E. P. Fenichel, S. R. Carpenter, L. M. Hunt, J. Alós, T. Klefoth, S. J. Cooke, R. Hilborn, and O. P. Jensen. 2019. Opinion:Governing the recreational dimension of global fisheries. Proceedings of the National Academy of Sciences of the United States of America 116:5209-5213. https://doi.org/10.1073/pnas.1902796116
Baggio, J. A., A. J. Barnett, I. Perez-Ibarra, U. Brady, E. Ratajczyk, N. Rollins, C. Rubiños, H. C. Shin, D. J. Yu, R. Aggarwal, et al. 2016. Explaining success and failure in the commons: the configural nature of Ostrom’s institutional design principles. International Journal of the Commons 10:417-439. https://doi.org/10.18352/ijc.634
Beard, T. D., S. P Cox, and S. R. Carpenter. 2003. Impacts of daily bag limit reductions on angler effort in Wisconsin walleye lakes. North American Journal of Fisheries Management 23:1283-1293. https://doi.org/10.1577/M01-227AM
Berck, P., and J. M. Perloff. 1984. An open-access fishery with rational expectations. Econometrica 52:489-506. https://doi.org/10.2307/1911500
Berkes, F. 2009. Evolution of co-management: role of knowledge generation, bridging organizations and social learning. Journal of Environmental Management 90:1692-1702. https://doi.org/10.1016/j.jenvman.2008.12.001
Berkes, F., D. Feeny, B. J. McCay, and J. M. Acheson. 1989. The benefits of the commons. Nature 340:91-93. https://doi.org/10.1038/340091a0
Brown, G., and R. Mendelsohn. 1984. The hedonic travel cost method. Review of Economics and Statistics 66:427-433. https://doi.org/10.2307/1924998
Camp, E. V., S. L. Larkin, R. N. M. Ahrens, and K. Lorenzen. 2017. Trade-offs between socioeconomic and conservation management objectives in stock enhancement of marine recreational fisheries. Fisheries Research 186:446-459. https://doi.org/10.1016/j.fishres.2016.05.031
Carpenter, S. R., and W. A. Brock. 2004. Spatial complexity, resilience, and policy diversity: fishing on lake-rich landscapes. Ecology and Society 9(1):8. https://doi.org/10.5751/ES-00622-090108
Clawson, M. 1959. Methods of measuring the demand for and value of outdoor recreation. Resources for the Future Inc., Washington, D.C., USA.
Dietz, T., E. Ostrom, and P. C. Stern. 2003. The struggle to govern the commons. Science 302:1907-1912. https://doi.org/10.1126/science.1091015
Feeny, D., F. Berkes, B. J. McCay, and J. M. Acheson. 1990. The tragedy of the commons: twenty-two years later. Human Ecology 18:1-19. https://doi.org/10.1007/BF00889070
Fenton, R., J. A. Mathias, and G. E. E. Moodie. 1996. Recent and future demand for walleye in North America. Fisheries 21:6-12.
Fujitani, M., A. McFall, C. Randler, and R. Arlinghaus. 2017. Participatory adaptive management leads to environmental learning outcomes extending beyond the sphere of science. Science Advances 3(6):e1602516. https://doi.org/10.1126/sciadv.1602516
Gabriel, A. O., and C. Lancaster. 2004. Management issues, characteristics and effectiveness of Lake Associations and Lake Districts in Wisconsin. Lake Reservoir Management 20:27-38. https://doi.org/10.1080/07438140409354098
Gaeta, J. W., B. Beardmore, A. W. Latzka, B. Provencher, and S. R. Carpenter. 2013. Catch-and-release rates of sport fishes in northern Wisconsin from an angler diary survey. North American Journal of Fisheries Management 33:606-614. https://doi.org/10.1080/02755947.2013.785997
Gordon, H. S. 1954. The economic theory of a common-property resource: the fishery. Pages 178-203 in Classic papers in natural resource economics. Palgrave Macmillan, London, UK. https://doi.org/10.1057/9780230523210_10
Gutiérrez, N. L., R. Hilborn, and O. Defeo. 2011. Leadership, social capital and incentives promote successful fisheries. Nature 470:386-389. https://doi.org/10.1038/nature09689
Hardin, G. 1968. The tragedy of the commons. Science 162:1243-1248. https://doi.org/10.1126/science.162.3859.1243
Horan, R. D., E. P. Fenichel, K. L. S. Drury, and D. M. Lodge. 2011. Managing ecological thresholds in coupled environmental–human systems. Proceedings of the National Academy of Sciences of the United States of America 108:7333-7338. https://doi.org/10.1073/pnas.1005431108
Johnson, B. M., R. Arlinghaus, and P. J. Martinez. 2009. Are we doing all we can to stem the tide of illegal fish stocking? Fisheries 34:389-394. https://doi.org/10.1577/1548-8446-34.8.389
Korth, R. M., and L. L. Klessig. 1990. Overcoming the tragedy of the commons: alternative lake management institutions at the community level. Lake and Reservoir Management 6:219-225. https://doi.org/10.1080/07438149009354712
Lebel, L., J. M. Anderies, B. Campbell, C. Folke, S. Hatfield-Dodds, T. P. Hughes, and J. Wilson. 2006. Governance and the capacity to manage resilience in regional social-ecological systems. Ecology and Society 11(1):19. https://doi.org/10.5751/ES-01606-110119
Liu, J., T. Dietz, S. R. Carpenter, M. Alberti, C. Folke, E. Moran, A. N. Pell, P. Deadman, T. Kratz, J. Lubchenco, et al. 2007. Complexity of coupled human and natural systems. Science 317:1513-1516. https://doi.org/10.1126/science.1144004
Lorenzen, K., and C. J. Garaway. 1998. How predictable is the outcome of stocking? Pages 133–152 in T. Petr, editor. Inland fishery enhancements. Fisheries Technical Paper 374, FAO, Rome, Italy.
Lorenzen, K., C. J. Garaway, B. Chamsingh, and T. J. Warren. 1998. Effects of access restrictions and stocking on small water body fisheries in Laos. Journal of Fish Biology 53:345-357. https://doi.org/10.1111/j.1095-8649.1998.tb01036.x
McConnell, K. E., and J. G. Sutinen. 1979. Bioeconomic models of marine recreational fishing. Journal of Environmental Economics and Management 6:127-139. https://doi.org/10.1016/0095-0696(79)90025-1
McGinnis, M. D., editor. 1999. Polycentric governance and development: readings from the workshop in political theory and policy analysis. University of Michigan Press, Ann Arbor, Michigan, USA. https://doi.org/10.3998/mpub.16052
McKelvey, R. 1985. Decentralized regulation of a common property renewable resource industry with irreversible investment. Journal of Environmental Economics and Management 12:287-307. https://doi.org/10.1016/0095-0696(85)90001-4
Moritz, M., R. Behnke, C. M. Beitl, R. B. Bird, R. M. Chiaravalloti, J. K. Clark, S. A. Crabtree, S. S. Downey, I. M. Hamilton, S. C. Phang, P. Scholte, and J. A. Wilson. 2018. Emergent sustainability in open property regimes. Proceedings of the National Academy of Sciences of the United States of America 115:12859-12867. https://doi.org/10.1073/pnas.1812028115
Ostrom, E. 1990. Governing the commons: the evolution of institutions for collective action. Cambridge University Press, Cambridge, UK.
Ostrom, E. 1998. A behavioral approach to the rational choice theory of collective action: Presidential Address, American Political Science Association, 1997. American Political Science Review 92:1-22. https://doi.org/10.2307/2585925
Post, J. R. 2013. Resilient recreational fisheries or prone to collapse? A decade of research on the science and management of recreational fisheries. Fisheries Management and Ecology 20:99-110. https://doi.org/10.1111/fme.12008
Sanchirico, J. N., and J. E. Wilen. 1999. Bioeconomics of spatial exploitation in a patchy environment. Journal of Environmental Economics and Management 37:129-150. https://doi.org/10.1006/jeem.1998.1060
Schoon, M. L., M. D. Robards, C. L. Meek, and V. Galaz. 2015. Principle 7: Promote polycentric governance systems. Pages 226-250 in R. Biggs, M. Schlüter, and M. L. Schoon, editors. Principles for building resilience: sustaining ecosystem services in social-ecological systems. Cambridge University Press, Cambridge, UK.
Scott, A. 1955. The fishery: the objectives of sole ownership. Journal of Political Economy 63:116-124. https://doi.org/10.1086/257653
Smith, M. D. and J. E. Wilen. 2003. Economic impacts of marine reserves: the importance of spatial behavior. Journal of Environmental Economics and Management 46(2):183-206. https://doi.org/10.1016/S0095-0696(03)00024-X
Smith, V. L. 1968. Economics of production from natural resources. American Economic Review 58:409-431.
Stephenson, R. L., and D. E. Lane. 1995. Fisheries management sciences: a plea for conceptual change. Canadian Journal of Fisheries and Aquatic Sciences 52:2051-2056. https://doi.org/10.1139/f95-796
United States Census Bureau. 2016. National survey of fishing, hunting, and wildlife-associated recreation.
Wilen, J. E. 2018. Common property resources and the dynamics of overexploitation: the case of the North Pacific fur seal. Marine Resource Economics 33(3). https://doi.org/10.1086/698137
Worm, B., R. Hilborn, J. K. Baum, T. A. Branch, J. S. Collie, C. Costello, M. J. Fogarty, E. A. Fulton, J. A. Hutchings, S. Jennings, O. P. Jensen, H. K. Lotze, P. M. Mace, T. R. McClanahan, C. Minto, S. R. Palumbi, A. M. Parma, D. Ricard, A. A. Rosenberg, R. Watson, and D. Zeller. 2009. Rebuilding global fisheries. Science 325:578-585. https://doi.org/10.1126/science.1173146