Ocean zoning within a sparing versus sharing framework

Ocean zoning within a sparing versus sharing framework The land-sparing versus land-sharing debate centers around how different intensities of habitat use can be coordinated to satisfy competing demands for biodiversity persistence and food production in agricultural landscapes. We apply the broad concepts from this debate to the sea and propose it as a framework to inform marine zoning based on three possible management strategies, establishing: no-take marine reserves, regulated fishing zones, and unregulated open-access areas. We develop a general model that maximizes standing fish biomass, given a fixed management budget while maintaining a minimum harvest level. We find that when management budgets are small, sea-sparing is the optimal management strategy because for all parameters tested, reserves are more cost-effective at increasing standing biomass than traditional fisheries management. For larger budgets, the optimal strategy switches to sea-sharing because, at a certain point, further investing to grow the no-take marine reserves reduces catch below the minimum harvest constraint. Our intention is to illustrate how general rules of thumb derived from plausible, single-purpose models can help guide marine protected area policy under our novel sparing and sharing framework. This work is the beginning of a basic theory for optimal zoning allocations and should be considered complementary to the more specific spatial planning literature for marine reserve as nations expand their marine protected area estates. . . . . . Keywords Sparing vs sharing Marine protected areas Fisheries management Marine zoning Open-access fisheries Marine policy The original version of this article was revised due to a retrospective Open Access order. Electronic supplementary material The online version of this article (https://doi.org/10.1007/s12080-017-0364-x) contains supplementary material, which is available to authorized users. * Jennifer McGowan Australian Research Council Centre of Excellence for Environmental j.mcgowan@uq.edu.au Decisions, The University of Queensland, St Lucia, QLD 4072, Australia Michael Bode Department of Biological Sciences, Macquarie University, North mbode.web@gmail.com Ryde, New South Wales 2109, Australia Centre for Biodiversity and Conservation Science, School of Matthew H. Holden Biological Sciences, The University of Queensland, St m.holden1@uq.edu.au Lucia, QLD 4072, Australia Katrina Davis Centre for Applications in Natural Resource Mathematics, School of k.davis@uq.edu.au Mathematics and Physics, The University of Queensland, St Lucia, QLD 4072, Australia Nils C. Krueck Marine Spatial Ecology Lab and Australian Research Council Centre nils.krueck@uqconnect.edu.au of Excellence for Coral Reef Studies, The University of Queensland, St Lucia, QLD 4072, Australia Maria Beger m.beger@uq.edu.au School of Environment and Life Sciences, University of Salford, Manchester, UK Katherine L. Yates Australian Institute of Marine Science, PMB 3, k.l.yates@salford.ac.uk Townsville, QLD 4810, Australia Hugh P. Possingham The Nature Conservancy, 4245 North Fairfax Drive, Suite 100, h.possingham@uq.edu.au Arlington, VA 22203-1606, USA 246 Theor Ecol (2018) 11:245–254 Introduction strategy to achieve fisheries objectives, rather than an either/or argument (Holland and Brazee 1996; Mangel 2000; White The land-sparing versus land-sharing (sparing vs sharing) de- et al. 2010). bate emerged from contrasting views about how to balance the Valid concerns remain regarding the socioeconomic im- competing demands for biodiversity persistence and food pro- pacts of marine reserves on communities and countries. duction in agricultural landscapes (Green et al. 2005; Fischer Indeed, most studies modeling the use of reserves for fisheries et al. 2014). Land sparing involves spatial consolidation and management have found that the addition of reserves will re- intensification of agricultural activities. This approach is duce yields whenever fisheries are already well managed based on the idea that concentrated agricultural activity can (Tuck and Possingham 2000; Hilborn et al. 2006), or suggest achieve equal or higher yields in a smaller land area than low reserves are an effective secondary management option in intensity usage. More land is available for biodiversity protec- cases where fisheries are heavily exploited or where effort tion thereby providing a net conservation benefit. The reductions are unlikely to succeed (Holland and Brazee counter-argument in support of sharing argues that wildlife- 1996). The establishment of marine reserves can lead to a friendly farming produces lower yields per unit area, but sup- redistribution of fishing effort within a region, potentially ne- ports biodiversity conservation by using less intensive produc- gating any net benefit of the reserve through increased fishing tion techniques across larger portions of the landscape pressure elsewhere (Agardy et al. 2011). Other studies have (Fischer et al. 2008). Studies typically investigate the sparing identified scenarios in which reserves could be essential for vs. sharing dichotomy to identify the most appropriate strate- maintaining high yields in spite of otherwise effective manage- gy for a given context, because how well species or popula- ment regulations. These include, for example, the potentially tions fare alongside increasing agricultural yields depends up- critical function of reserves as a buffer against environmental on species traits and local production methods (Balmford et al. stochasticity (Mangel 2000;West et al. 2009), and the positive 2005; Green et al. 2005; Phalan et al. 2011;Grau et al. 2013). impact of reserves on the density-dependent survival of young Although much of the debate centers around semantic issues fish (White 2009) which could increase the net productivity of (Tscharntke et al. 2012; Fischer et al. 2014), more recent em- fished populations adjacent to reserves (but see White et al. pirical research supports the discussion with quantitative data 2008; Hart and Sissenwine 2009; Russ and Alcala 2011). (Lee et al. 2014; Butsic and Kuemmerle 2015;Kremen 2015; Similar to the terrestrial debate, there is no standard solu- Law and Wilson 2015) particularly in plantation and livestock tion to protecting biodiversity and meeting human needs from production (Grau et al. 2013). the sea. Equipping decision-makers with a variety of tools to While not framed as sparing vs. sharing per se, equivalent inform policy will enable better and more flexible manage- discussions in ocean management debate the benefits of either ment strategies as to which zoning allocation should be pur- sued in a given context. Australia’s Great Barrier Reef Marine prohibiting fishing in some parts of the seascape or constraining fishing through management (White and Park, for example, represents one of the first systematically Kendall 2007;Hilborn 2016). Marine reserves that exclude designed networks of marine protected areas in the world all extractive activities are a popular tool for conserving ma- whose shared seascape consists of roughly equal proportions rine biodiversity. Efforts are underway to increase the number of marine reserves, managed fisheries and general use areas of reserves globally, particularly in developing countries (Fernandes et al. 2005). While successful in Australia where inshore fisheries experience heavy exploitation (McCook et al. 2010), encouraging other countries to adopt (White et al. 2014). In contrast, it is argued that traditional the exact same allocation would be unfounded given the di- fisheries management, such as catch and size regulations, are verse ecological, socioeconomic, and governance structures more effective mechanisms to maintain healthy fish stocks across marine jurisdictions globally. Yet, general ecological and productive fisheries (Hilborn et al. 2004). In this context, and socioeconomic principles apply everywhere, and rules quantitative investigations about sparing vs sharing in the sea of thumb based on plausible, single-purpose models can help traditionally argue whether or not marine reserves will provide guidepolicy(Starfield 1997;Gerber et al. 2003) in a time of greater fish biomass and environmental benefits than fishery rapid marine protected area expansion (Klein et al. 2015). regulations (Hastings and Botsford 1999; Hilborn et al. 2006; Here, we transfer the land sparing vs. sharing debate to the White and Kendall 2007)—a typically either/or argument. sea using three common zoning types: fully protected no-take These studies identify whether a fraction of the system in marine reserves, managed fishing zones, and unregulated and/ marine reserves—sparing—or regulation across the entire ar- or unmanaged fishing zones, hereafter called Bopen-access.^ ea—sharing—maximizes fishery yields or profits (Sanchirico We choose to characterize an allocation with only marine re- and Wilen 2001; Gerber et al. 2003; Hastings and Botsford serves and open-access areas as a Bpure^ sea sparing strategy. 2003; Sanchirico et al. 2006; White et al. 2008). We note, In the sea, we translate sharing to be any strategy that incor- however, there is a body of literature that considers and tests porates managed fishing zones, which can manifest as regu- lations on spatial or temporal effort, or gear restrictions that the utility of marine reserves as part of a mixed management Theor Ecol (2018) 11:245–254 247 minimize impact to the benthos or non-target species. We the seascape. The seascape is divided into three management characterize sharing along a continuum where some propor- zones: protected marine reserves (fraction R), managed fishing tion of the seascape is managed, but consider a Bpure^ sharing zones (fraction M), and open-access fishing zones (fraction F; strategy to be when the entire seascape is managed and no so every part of the system is in one of the zones,R+ M+F = reserves or open-access zones exist (Fig. 1). When defined 1). There is a financial cost to reserving (C ) and managing in this manner, we move beyond the sparing vs sharing di- (C ) habitat, the sum total of which must not exceed an allot- chotomy that prevails in the terrestrial debate (Kremen 2015), ted total management budget (B), R*C + M*C ≤ B.We R M to develop a framework that includes seven potential spared assume there is no management cost incurred in the open- and/or shared seascapes. We then illustrate how to access zone. Our objective is to maximize the total population operationalize the framework using a simple modeling ap- of our fishery species subject to the budget constraint and a proach whose optimally zoned seascapes secure a minimum minimum biomass yield. Our model identifies the optimum biomass yield while maximizing standing stock biomass (the proportional allocation of a seascape among the three zones. environmental benefit) for a given management budget. This To link the decisions about seascape zoning allocation to approach considers a single habitat-dependent fished species our objectives and constraints, we use a simple population whose harvest methods exert different levels of pressure on model tracking adult post-harvest biomass, A,at time t.Let the benthos. We are interested in the circumstances in which L and K, be fecundity and the total number of potential sites the optimal seascape is either a sparing strategy, defined here available for larval settlement (i.e., larval carrying capacity), when the case study area is allocated among no-take reserves respectively. Fishing mortality in the managed and open- and open-access zones, and when that changes to a sharing access zones are (1-S ) and (1-S ), respectively. We assume M F strategy, defined when the case study includes a managed habitat damage temporarily reduces the proportion of avail- fishery zone, and potentially the addition of either or both able sites for settlement in zone type i,by D ,for i in {M, F, R}, no-take and/or open-access zones (Fig. 1). at time t. We assume the damage is more severe in the open- access zone (D <D ), and that no habitat damage occurs in M F the no-take reserves, (D = 0). Assuming fish reproduce post- harvest and contribute larva to a common pool, which are then Material and methods allocated to the three zone types proportionally based on area, we obtain the following difference equation for total post- Model description harvest population size Our model assumes we are managing a single habitat- ½ S ðÞ 1−D M þ SðÞ 1−D F þ R LA M M F F t dependent fished species that reproduces with a pelagic larval A ¼ : ð1Þ tþ1 1 þ LA =K phase leading to evenly distributed recruitment in all parts of This formula is derived by assuming that larva uniformly settle at random among a fraction of available sites, which yields a Beverton-Holt recruitment relationship of the above form (Duncan et al. 2009). The model has a stable equilibrium at A ¼ S ðÞ 1−D M þ SðÞ 1−D F þ R− K; ð2Þ M M F F and analogous equilibrium harvest ½ ðÞ 1−S ðÞ 1−D M þðÞ 1−S ðÞ 1−D F LA M M F F H ¼ : ð3Þ 1 þ LA =K For simplicity, we assume 100% adult mortality after har- vest and reproduction, but acknowledge the lifecycle for many Fig. 1 Classes of sparing and sharing seascapes derived from our three- short-lived species may not be annual. We then search through zone framework. Pure spared seascapes are those defined by no-take reserves (R) and open-access areas (F) and defined in these plots as any all financially possible zoning configurations to find the opti- point on the line between F and R (excluding apex points where the mal seascape at equilibrium. The optimal solution is the sea- zoning allocation would be 100%). Shared seascapes are defined by scape allocation that delivers the largest environmental benefit any allocation with managed fishing zones (M), with a pure shared sea- (total equilibrium post-harvest adult population size), while scape defined by apex M (100% managed). Pie charts offer illustrative examples to help interpret the zone allocation at given points on the graph meeting the minimum harvest and budget constraints. 248 Theor Ecol (2018) 11:245–254 Ignoring the catch constraint we obtain an analytic solution for survival proportion that will yield MSY in a fully managed this optimal zoning allocation, which produces a general rule seascape and S to be the survival that leads to an equilibrium of thumb which holds true for small budgets (see BResults^). of 10% of virgin biomass when the fishery is completely un- However, to account for the nonlinear catch constraint, we regulated, open access. We assume that fishers will not toler- solved for the optimal allocation using simulations conducted ate a level of catch lower than the pre-managed open access in Matlab (MathWorks, Natick Massachusetts, USA; yield therefore the catch threshold (CT) is set to the open- Appendix A). access harvest. Case study parameterization Costs For our case study, we apply our model to derive an optimum Despite being critical to decision-making about natural re- zone allocation based on the conditions of tiger prawn fisher- source management (Naidoo et al. 2006), costs associated ies (O'Neill and Turnbull 2006) using the parameters outlined with establishing and managing protected areas are often in Table 1. Damage caused by benthic fishing is difficult to poorly reported, difficult to quantify (Balmford et al. 2004; quantify and depends on the type of gear, and the frequency Ban et al. 2011), and highly contextual (Rojas-Nazar et al. and distribution of effort (Thrush et al. 1998; Collie et al. 2015). As a flexible way to integrate the amalgam of costs 2000). Impacts to coastal habitats range from diminished (e.g., stock assessments, ecological monitoring, staffing, en- structural complexity (Auster 1998), changes to community forcement, etc.) associated with the different zones (Ban et al. composition (Thrush et al. 1998), and altered ecological pro- 2011) and across regions, we parameterize the relative costs cesses (e.g., reduced primary production from macrofauna between protected and managed areas. One key factor driving depletion; enhanced nutrient cycling via suspended sediment the cost of management interventions, be they marine reserves loads (Auster and Langton 1999)). or gear restrictions, is the cost of enforcing compliance. The For the purpose of this exercise, we make several necessary costs associated with surveillance and enforcement depend on simplifying assumptions about benthic impacts from fishing both the size of the zones and the social and economic char- activities. We recognize benthic habitat condition is case-spe- acteristics of the resource users. Only a few studies have ex- cific. In cases where more detailed data exist, this information plicitly quantified these costs (Ban and Klein 2009; Davis can easily be incorporated into our modeling framework. We et al. 2015). Ban et al. (2011) compared the enforcement costs assume that previously unregulated trawling has impacted the for staffing an entirely no-take protected area versus a mixed benthic community in the open-access zone. We define impact zone seascape (protected and fished) and found that compli- as the mean mortality (20–50%) of benthic invertebrates re- ance staffing was doubled when mixed zoning occurred. ported in Collie et al. (2017) for towed benthic fishing gears. As a starting point for our case study, we assume the cost of We assume perfectly enforced restrictions in the managed enforcing fisheries management is twice that of protecting zone reduce the fishing impacts on the benthos by half so that area, C =2C but we test the sensitivity of the outcome to M R D =0.5*D (Chuenpagdee et al. 2003). We set S to be the variations in the relative costs to protect and manage when M F M Table 1 Case study parameters Parameter Description Value Source based on population conditions for Penaeus esculentus (tiger s Intrinsic survival 1 O'Neill and Turnbull 2006 prawn) KCarryingcapacityofwhole 30 O'Neill and Turnbull 2006 environment L* Fecundity of adults 5 O'Neill and Turnbull 2006 D * Habitat damage in the 0.35 Collie et al. 2017 open-access fishing zone D Habitat damage in the managed 0.175 (derived as 0.5*D ) Chuenpagdee et al. 2003 M F fishing zone S * Survivorship in fished zones 0.48 To achieve 10% virgin biomass at equilibrium. See formula in code, Appendix A S Survivorship in managed zones 0.65 To achieve MSY at equilibrium. See formula in code, Appendix A CT* Catch threshold 1.85 Open-access equilibrium C to Cost ratio between managing 2:1 Ban et al. 2011 C * and protection *Sensitivity tested (see Fig. 3 and Appendix) Theor Ecol (2018) 11:245–254 249 C =C and when the cost of enforcing reserves is double the zones. We find this departure is most sensitive to changes in R M cost of enforcing managed fishing areas C =2C .We also fecundity (L) and occurs when the reserve coverage is be- R M examine the case of additional fixed costs (e.g., costs that do tween 45 and 70% of the seascape. When fecundity is greater, not scale with area) of reserves and managed areas in the we switch to investing in management zones at lower propor- appendix (see Appendix B). Management budgets can vary tions of reserves in the seascape. enormously between regions and in time; therefore, we are Regardless of the parameter tested, we consistently observe most interested in identifying the circumstances under which the phenomenon of sea sparing when budgets are small, as the optimal management strategy shifts between sparing and well as the switch to the three-zone version of sharing as sharing as the management budget changes. We investigate budgets increase. This trend is robust to changes in the cost the optimal strategy under different budgets to variations in ratio as well as when we eliminate the influence of habitat several parameters of interest: habitat damage in the open- damage caused by fishing in each zone (D = 0 and D =0) M F access fishing zone (D ), escapement in the open-access fish- (see Appendix B–C for further sensitivity analyses). ing zone (S ), fecundity (L), and the catch threshold (CT). Sensitivity manifests in two possible ways that affect the op- timal seascape as the budget grows: (1) the point of departure from sparing to sharing and (2) the proportion allocated to Results each zone (Fig. 3). Interestingly, the proportion of area protected, R, at the point of departure from sparing to sharing Case study remains fairly constant irrespective of the cost ratio for our case study (Appendix B; about 60% of the seascape). When If there is no management budget, then fishing must occur the cost of protection is double the cost of management, under open-access conditions throughout the seascape, re- C =2C , the point of departure is substantially delayed as R M gardless of the fishery being considered, because managed the budget grows large enough to share the seascape but ulti- areas and reserves require financial investment. In our case mately follows the same investment strategy. study, we find that when management budgets are low (Fig. 2 where B ≤ 0.61), the optimal choice is to allocate the Optimal rule of thumb for small budgets entire budget to establishing no-take zones and have no man- aged areas. With the budget exhausted the rest of the seascape Our approach also allows us to derive an analytic rule of remains in open-access fishing—considered here as a sea thumb to assist decision-makers about what the optimal in- sparing strategy where the portions of the seascape not under vestment strategy may be for their given context. With no protection are intensively harvested. As the budget increases, catch constraint, the optimal zoning solution is to allocate so does the fraction of the protected seascape. During this the entire budget to marine reserves (sparing) if the benefit stage, initially, the catch increases because additional reserves of adding a reserve (relative to open-access fishing), per unit increase larvae production, which is then mostly distributed to cost, is greater than the cost-benefit of adding a managed area. unregulated zones for fishing. However, after a critical reserve Otherwise, the decision-maker should spend their entire bud- threshold, catch declines because additional reserves do not get on managed areas. This rule can be simplified mathemat- provide sufficient larval export to the open-access zones to ically as Bspend the entire budget on reserves^ if compensate the fishery for the population now excluded from harvesting. Eventually, the optimal seascape switches from 1−S ðÞ 1−D C M M M 1− > : ð4Þ sparing (reserves and open-access) to include all three 1−SðÞ 1−D C F F R zones—a version of sea sharing (Fig. 1). This occurs when further expanding the reserved area prevents the fishery from To derive this rule, let x be the amount of money satisfying the minimum harvest constraint. In this case, bio- allocated to reserves and, B – x, the amount of money mass can be increased further with the addition of managed allocated to managed areas. Then R = x/C and M =(B- zones while still meeting the catch constraint. x)/C ,and F = 1 – R-M. One can solve for the x that Figure 3 shows how the optimal zoning allocation changes maximizes A* by substituting these quantities into Eq. 2 as a function of the budget for our parameters of interest: D , which produces condition 4. S , L,and CT. Beginning with no budget, the seascape is Based on our numerical simulations, the rule of thumb held completely open-access fishing (apex F). As the budget for all tested cases until so many reserves had been purchased grows, the allocation moves along the Bsparing^ boundary, that the catch constraint would no longer be satisfied if the where the seascape consists of open-access and increasing decision maker continued adding reserves. For our baseline proportions of no-take reserves. A point of departure, or tran- parameterization, we found that reserves were favored over sition point, finally moves the allocation away from sea spar- managed areas unless the cost of reserves was nearly five ing and into a shared configuration consisting of all three times that of managed areas. Even for the combination of 250 Theor Ecol (2018) 11:245–254 Fig. 2 The optimal sparing versus sharing strategy (top) showing the fraction of the seascape allocated to each of the three zones with an increasing budget for our case study. No-take marine reserves in blue (R); open-access fishing in green (F); and managed zones in yellow (M). The white dashed line is the departure point between sparing and sharing. When there is no budget we can neither reserve nor manage. As the budget increases, first marine reserves and then managed fisheries, enter the optimal zoning allocation. Also shown are catch, biomass, and the spending regime parameters most favorable for managed areas in the sensitivity unmanaged open-access system (F = 1) likely results in over analysis, managed areas were not selected for low budgets exploitation and potential fishery collapse (Hutchings 2000); unless the cost of reserves was over three times higher than finally, while (3) a purely shared system is possible (e.g., M = the cost of managed areas. 1 with no reserves or unmanaged fisheries), the reality of limited management budgets and global commitments to MPAs reduce the likelihood of this option persisting through Discussion time. Mixed zoning under our framework consists of (4) a pure spared seascape with both no-take reserves and open- A sea sparing and sharing framework access zones, (5) shared seascapes with managed and open- access zones, and two zoning configurations that allow Seven seascape allocations emerge from our sea sparing and Bsparing and sharing.^ The first of these last two zoning con- figurations includes (6) no-take reserves and managed fisher- sharing framework (Fig. 1). A seascape allocated entirely to one zone is highly unlikely as (1) an entirely reserved no-take ies; and (7) no-take reserves, managed fisheries and open- access zones. With this conceptual starting point, a useful next system (R = 1) cannot meet the harvest constraint; (2) an Theor Ecol (2018) 11:245–254 251 Fig. 3 Ternary plots showing the fraction of the seascape in each of the three zones (R = no take reserves, M = managed fishing zones, F = open access) for a given budget, where R+M + F= 1. When no budget exists, B =0, the entire seascape is open access, 100% F in the bottom right corner. Colored lines show the sensitivity of the seascape allocation under several values for each parameter of interest: a habitat damage caused by fishing in the open-access fishing zone (D ), b escapement in the open- access fishing zone (S ), c fecundity of adults (L), and d the catch threshold (CT). The departure from the sparing strategy (line F–R) indicates the transition point from sparing to sharing as the budget increases step for the future would be to classify existing management are treated as objectives to be maximized or minimized, and/or plans within this framework to see what the most dominant constraints. Defining a different objective for ocean manage- strategies are in practice, and to create a typology of spared ment (e.g., maximizing larval connectivity, protecting species and shared seascapes that enable moving beyond the dichot- climate refugia (Beger et al. 2015) or building near-pristine omous view of the sparing vs sharing debate. Building on this fish biomass (McClanahan et al. 2007)), or evaluating trade- idea, our framing also exposes the need for a more refined offs for multi-objective problems would also be valid classification system, as Bsparing,^ Bsharing,^ and Bsparing approaches. and sharing^ are too vague to encompass the nuanced man- We strategically simplify many assumptions in order to agement practices governing marine systems (White et al. develop a model that can begin to inform policy (Hastings 2010;Kremen 2015). and Botsford 1999). Opportunities to add complexity into our approach include incorporating a spatially realistic model- ing environment (Polasky et al. 2008; Metcalfe et al. 2015), Only the rich can afford to share alternative assumptions of density dependence before and af- ter settlement (e.g. Ricker models), age structure, overcom- When budgets are small, sea sparing is always the optimal pensation (e.g., White and Kendall (2007)), integrating more allocation. As the budget grows, we arrive at a point where complex dispersal processes, accounting for variable distribu- increasing the amount of the reserves any further will compro- tions of fishing effort and displacement, socioeconomics mise our ability to achieve the minimum harvest constraint. If budgets increase beyond this point, the optimal strategy is to (Sanchirico and Wilen 2002; Halpern et al. 2004;Armstrong and Skonhoft 2006;Costelloand Polasky 2008), and devel- start sharing. The optimal strategy under our framework will oping multi-species models. be specific to the definition of objectives and constraints For some of these limitations, we can foresee how the (White et al. 2017). For example, we approached this problem model will respond. For example, adding age structure would by identifying a single conservation objective (maximize allow biomass to accumulate in reserves, likely achieving our standing biomass), while acknowledging two constraints: a objectives with less reserved area. In instances where over- natural resource requirement (expressed by the minimum har- compensation is justified we would expect to see higher re- vest constraint) and a fixed management budget. However, it serve coverage (White and Kendall 2007). We acknowledge is important to note there are many alternate ways to frame this that our approach also depends on some degree of overfishing problem depending on whether the above outcome variables 252 Theor Ecol (2018) 11:245–254 collaborations by ARC CoE for Environmental Decisions. J.M. is funded for this framework to apply. This assumption influences the by an Australian International Postgraduate Research Scholarship. M.B. point of departure, in that, the time at which managed areas are was funded by a Discovery Early Career Research Award to the ARC added will depend on the assumptions of overfishing. CoE for Environmental Decisions (CE110001014). However, the general trend of sparing first and moving to Open Access This article is distributed under the terms of the Creative the three-zone version of sharing is robust and highlights that Commons Attribution 4.0 International License (http:// mixed management approaches have merit where substantial creativecommons.org/licenses/by/4.0/), which permits use, duplication, management capacity exists (Hilborn 2016). adaptation, distribution and reproduction in any medium or format, as The species and associated fishery we chose to represent long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if in the model are intentionally responsive to reserves, be- changes were made. cause we believe that it is these types of species and fish- eries that drive zoning decisions for coastal management. However, our findings may also apply to systems where common pool dispersal assumptions are not met. The first References empirical measurements of larval dispersal revealed unex- pectedly high levels of self-recruitment (Jones et al. 1999; Agardy T, di Sciara GN, Christie P (2011) Mind the gap: addressing the Swearer et al. 1999) which challenged the general assump- shortcomings of marine protected areas through large scale marine tion of strong population connectivity across large sea- spatial planning. Mar Policy 35(2):226–232. https://doi.org/10. scapes. More recent studies confirm that larval settlement 1016/j.marpol.2010.10.006 close to spawning locations is indeed common, but that the Almany GR, Planes S, Thorrold SR, Berumen ML, Bode M, Saenz- AgudeloP,BoninMC, Frisch AJ,HarrisonHB, MessmerV dispersal distances of a significant proportion of other lar- (2017) Larval fish dispersal in a coral-reef seascape. Nat Ecol Evol vae can still be extensive (Green et al. 2015; Jones 2015; 1:s41559–s41017 Williamson et al. 2016;Almanyet al. 2017). In such cases, Armstrong CW, Skonhoft A (2006) Marine reserves: a bio-economic reserve size and placement can be optimized with a high model with asymmetric density dependent migration. Ecol Econ 57(3):466–476. https://doi.org/10.1016/j.ecolecon.2005.05.010 level of flexibility to provide for maximum fishery benefits Auster PJ (1998) A conceptual model of the impacts of fishing gear on the (Krueck et al. 2017a, b). integrity of fish habitats. Conserv Biol 12(6):1198–1203. https://doi. Despite our stated limitations, our model goes beyond tra- org/10.1046/j.1523-1739.1998.0120061198.x ditional management zone assessments by illustrating how Auster PJ, Langton RW (1999) The effects of fishing on fish habitat. In: fisheries management influences the optimal seascape alloca- Benaka L (ed) Fish habitat: essential fish habitat and rehabilitation. American Fisheries Society, Bethesda, p 150–187 tion. Our approach is the first attempt to underpin the sharing Balmford A, Gravestock P, Hockley N, McClean CJ, Roberts CM (2004) and sparing debate with a process model. In doing so, we The worldwide costs of marine protected areas. Proc Natl Acad Sci reveal a more nuanced and practical framework than the de- USA 101:9694–9697 bate has produced to date (Kremen 2015). Ocean management Balmford A, Green R, Scharlemann JPW (2005) Sparing land for nature: exploring the potential impact of changes in agricultural yield on the can benefit from applying this framework and devising simple area needed for crop production. Glob Chang Biol 11(10):1594– rules of thumb to guide policy options, for example, investing 1605. https://doi.org/10.1111/j.1365-2486.2005.001035.x in marine reserves when budgets are low with the addition of Ban NC, Klein CJ (2009) Spatial socioeconomic data as a cost in system- managed areas when budgets are high. Building additional atic marine conservation planning. Conserv Lett 2(5):206–215. https://doi.org/10.1111/j.1755-263X.2009.00071.x complexity into this base exploration as well as developing Ban NC, Adams V, Pressey RL, Hicks J (2011) Promise and problems for the sea sparing vs sea sharing framework will help advance estimating management costs of marine protected areas. Conserv the debate and its relevance for marine policy. This work is the Lett 4(3):241–252. https://doi.org/10.1111/j.1755-263X.2011. beginning of a basic theory for optimal allocations within 00171.x Beger M, McGowan J, Treml EA, Green AL, White AT, Wolff NH, Klein seascape zoning frameworks and should be considered com- CJ, Mumby PJ, Possingham HP (2015) Integrating regional conser- plementary to the more specific spatial planning literature for vation priorities for multiple objectives into national policy. Nat marine reserve design and implementation, which addresses Commun 6:8208. https://doi.org/10.1038/ncomms9208 the size, shape, and placement of individual MPAs within a Butsic V, Kuemmerle T (2015) Using optimization methods to align food production and biodiversity conservation beyond land sharing and seascape. land sparing. Ecol Appl 25(3):589–595. https://doi.org/10.1890/14- 1927.1 Acknowledgements We would like to thank all BDichotomies in Marine Chuenpagdee R, Morgan LE, Maxwell SM, Norse EA, Pauly D (2003) Conservation^ workshop participants for their contributions in initial dis- Shifting gears: assessing collateral impacts of fishing methods in US cussions, particularly Dr. Tessa Mazor and Dr. Sylvaine Giakoumi, and waters. Front Ecol Environ 1(10):517–524 the thoughtful contributions of Dr. Natalie Ban and our three anonymous Collie JS, Hall SJ, Kaiser MJ, Poiner IR (2000) A quantitative analysis of reviewers. fishing impacts on shelf-sea benthos. J Anim Ecol 69(5):785–798. https://doi.org/10.1046/j.1365-2656.2000.00434.x Funding information This work was conceived in a workshop funded by Collie J, Hiddink JG, Kooten T, Rijnsdorp AD, Kaiser MJ, Jennings S, H. P. P.’s ARC Laureate Fellowship with additional funding for Hilborn R (2017) Indirect effects of bottom fishing on the Theor Ecol (2018) 11:245–254 253 productivity of marine fish. Fish Fish 18(4):619–637. https://doi. Hilborn R, Micheli F, De Leo GA (2006) Integrating marine protected org/10.1111/faf.12193 areas with catch regulation. Can J Fish Aquat Sci 63(3):642–649. Costello C, Polasky S (2008) Optimal harvesting of stochastic spatial https://doi.org/10.1139/f05-243 resources. J Environ Econ Manag 56(1):1–18. https://doi.org/10. Holland DS, Brazee RJ (1996) Marine reserves for fisheries management. 1016/j.jeem.2008.03.001 Mar Resour Econ 11(3):157–171. https://doi.org/10.1086/mre.11.3. Davis K, Kragt M, Gelcich S, Schilizzi S, Pannell D (2015) Accounting 42629158 for enforcement costs in the spatial allocation of marine zones. Hutchings JA (2000) Collapse and recovery of marine fishes. Nature Conserv Biol 29(1):226–237. https://doi.org/10.1111/cobi.12358 406(6798):882–885. https://doi.org/10.1038/35022565 Duncan RP, Diez JM, Sullivan JJ, Wangen S, Miller AL (2009) Safe sites, Jones GP (2015) Mission impossible: unlocking the secrets of coral reef seed supply, and the recruitment function in plant populations. fish dispersal. In: Mora C (ed) Ecology of fishes on coral reefs, Ecology 90(8):2129–2138. https://doi.org/10.1890/08-1436.1 Cambridge University Press, Cambridge, p 16–28 Fernandes L, Day JON, Lewis A, Slegers S, Kerrigan B, Breen DAN, Jones GP, Milicich MJ, Emslie MJ, Lunow C (1999) Self-recruitment in a Cameron D, Jago B, Hall J, Lowe D, Innes J, Tanzer J, Chadwick V, coral reef fish population. Nature 402(6763):802–804. https://doi. Thompson L, Gorman K, Simmons M, Barnett B, Sampson K, org/10.1038/45538 De'Ath G, Mapstone B, Marsh H, Possingham H, Ball IAN, Ward Klein CJ, Brown CJ, Halpern BS, Segan DB, McGowan J, Beger M, T, Dobbs K, Aumend J, Slater DEB, Stapleton K (2005) Watson JEM (2015) Shortfalls in the global protected area network Establishing representative no-take areas in the great barrier reef: at representing marine biodiversity. Sci Rep 5(1):17539. https://doi. large-scale implementation of theory on marine protected areas. org/10.1038/srep17539 Conserv Biol 19(6):1733–1744. https://doi.org/10.1111/j.1523- Kremen C (2015) Reframing the land-sparing/land-sharing debate for 1739.2005.00302.x biodiversity conservation. Ann N Y Acad Sci 1355(1):52–76. Fischer J, Brosi B, Daily GC, Ehrlich PR, Goldman R, Goldstein J, https://doi.org/10.1111/nyas.12845 Lindenmayer DB, Manning AD, Mooney HA, Pejchar L (2008) Krueck NC, Ahmadia GN, Green A, Jones GP, Possingham HP, Riginos Should agricultural policies encourage land sparing or wildlife- C, Treml EA, Mumby PJ (2017a) Incorporating larval dispersal into friendly farming? Front Ecol Environ 6(7):380–385. https://doi. MPA design for both conservation and fisheries. Ecol Appl 27(3): org/10.1890/070019 925–941. https://doi.org/10.1002/eap.1495 Fischer J, Abson DJ, Butsic V, Chappell MJ, Ekroos J, Hanspach J, Krueck NC, Ahmadia GN, Possingham HP, Riginos C, Treml EA, Kuemmerle T, Smith HG, von Wehrden H (2014) Land sparing Mumby PJ (2017b) Marine reserve targets to sustain and rebuild versus land sharing: moving forward. Conserv Lett 7(3):149–157. unregulated fisheries. PLoS Biol 15(1):e2000537. https://doi.org/ https://doi.org/10.1111/conl.12084 10.1371/journal.pbio.2000537 Gerber LR, Botsford LW, Hastings A, Possingham HP, Gaines SD, Law, E. A. and K. A. Wilson (2015) Providing context for the land- Palumbi SR, Andelman S (2003) Population models for marine sharing and land-sparing debate. Conserv Lett 8(6):404–413. reserve design: a retrospective and prospective synthesis. Ecol https://doi.org/10.1111/conl.12168 Appl 13(sp1):47–64 Lee JSH, Garcia-Ulloa J, Ghazoul J, Obidzinski K, Koh LP (2014) Grau R, Kuemmerle T, Macchi L (2013) Beyond ‘land sparing versus Modelling environmental and socio-economic trade-offs associated land sharing’: environmental heterogeneity, globalization and the with land-sparing and land-sharing approaches to oil palm expan- balance between agricultural production and nature conservation. sion. J Appl Ecol 51(5):1366–1377. https://doi.org/10.1111/1365- Curr Opin Environ Sustain 5(5):477–483. https://doi.org/10.1016/ 2664.12286 j.cosust.2013.06.001 Mangel M (2000) On the fraction of habitat allocated to marine reserves. Green RE, Cornell SJ, Scharlemann JPW, Balmford A (2005) Farming Ecol Lett 3(1):15–22. https://doi.org/10.1046/j.1461-0248.2000. and the fate of wild nature. Science 307(5709):550–555. https://doi. 00104.x org/10.1126/science.1106049 McClanahan TR, Graham NAJ, Calnan JM, MacNeil MA (2007) Toward Green AL, Maypa AP, Almany GR, Rhodes KL, Weeks R, Abesamis pristine biomass: reef fish recovery in coral reef marine protected RA, Gleason MG, Mumby PJ, White AT (2015) Larval dispersal areas in Kenya. Ecol Appl 17(4):1055–1067. https://doi.org/10. and movement patterns of coral reef fishes, and implications for 1890/06-1450 marine reserve network design. Biol Rev 90(4):1215–1247. McCook LJ, Ayling T, Cappo M, Choat JH, Evans RD, De Freitas DM, https://doi.org/10.1111/brv.12155 Heupel M, Hughes TP, Jones GP, Mapstone B (2010) Adaptive Halpern BS, Gaines SD, Warner RR (2004) Confounding effects of the management of the great barrier reef: a globally significant demon- export of production and the displacement of fishing effort from stration of the benefits of networks of marine reserves. Proceedings marine reserves. Ecol Appl 14(4):1248–1256. https://doi.org/10. of the National Academy of Sciences 107:18278–18285 1890/03-5136 Metcalfe K, Vaz S, Engelhard GH, Villanueva MC, Smith RJ, Mackinson Hart DR, Sissenwine MP (2009) Marine reserve effects on fishery profits: S (2015) Evaluating conservation and fisheries management strate- a comment on White et al. (2008). Ecol Lett 12(3):E9–E11. https:// gies by linking spatial prioritization software and ecosystem and doi.org/10.1111/j.1461-0248.2008.01272.x fisheries modelling tools. J Appl Ecol 52(3):665–674. https://doi. Hastings A, Botsford LW (1999) Equivalence in yield from marine re- org/10.1111/1365-2664.12404 serves and traditional fisheries management. Science 284(5419): Naidoo R, Balmford A, Ferraro PJ, Polasky S, Ricketts TH, Rouget M 1537–1538. https://doi.org/10.1126/science.284.5419.1537 (2006) Integrating economic costs into conservation planning. Hastings A, Botsford LW (2003) Comparing designs of marine reserves Trends Ecol Evol 21(12):681–687. https://doi.org/10.1016/j.tree. for fisheries and for biodiversity. Ecol Appl 13(sp1):65–70 2006.10.003 Hilborn R (2016) Marine biodiverity needs more than protection. Nature 535(7611):224–226. https://doi.org/10.1038/535224a O'Neill MF, Turnbull C (2006) Stock assessment of the Torres Strait tiger Hilborn R, Stokes K, Maguire JJ, Smith T, Botsford LW, Mangel M, prawn fishery (Penaeus esculentus). Department of Primary Orensanz J, Parma A, Rice J, Bell J, Cochrane KL, Garcia S, Hall Industries and Fisheries, Brisbane City SJ , Kirkwood GP, Sainsbury K, Stefansson G, Walters C (2004) Phalan B, Onial M, Balmford A, Green RE (2011) Reconciling food When can marine reserves improve fisheries management? Ocean production and biodiversity conservation: land sharing and land Coast Manag 47(3-4):197–205. https://doi.org/10.1016/j. sparing compared. Science 333(6047):1289–1291. https://doi.org/ ocecoaman.2004.04.001 10.1126/science.1208742 254 Theor Ecol (2018) 11:245–254 PolaskyS,NelsonE,CammJ,CsutiB,FacklerP,LonsdorfE, Tuck GN, Possingham HP (2000) Marine protected areas for spatially structured exploited stocks. Mar Ecol Prog Ser 192:89–101. https:// Montgomery C, White D, Arthur J, Garber-Yonts B (2008) Where to put things? Spatial land management to sustain biodiversity and doi.org/10.3354/meps192089 economic returns. Biol Conserv 141(6):1505–1524. https://doi.org/ West CD, Dytham C, Righton D, Pitchford JW (2009) Preventing over- 10.1016/j.biocon.2008.03.022 exploitation of migratory fish stocks: the efficacy of marine Rojas-Nazar UA, Cullen R, Gardner JPA, Bell JJ (2015) Marine reserve protected areas in a stochastic environment. ICES J Mar Sci 66(9): establishment and on-going management costs: a case study from 1919–1930. https://doi.org/10.1093/icesjms/fsp159 New Zealand. Mar Policy 60:216–224. https://doi.org/10.1016/j. White C (2009) Density dependence and the economic efficacy of marine marpol.2015.06.029 reserves. Theor Ecol 2(3):127–138. https://doi.org/10.1007/s12080- Russ GR, Alcala AC (2011) Enhanced biodiversity beyond marine re- 009-0039-3 serve boundaries: the cup spillith over. Ecol Appl 21(1):241–250. White C, Kendall BE (2007) A reassessment of equivalence in yield from https://doi.org/10.1890/09-1197.1 marine reserves and traditional fisheries managament. Oikos Sanchirico JN, Wilen JE (2001) A bioeconomic model of marine reserve 116(12):2039–2043. https://doi.org/10.1111/j.2007.0030-1299. creation. J Environ Econ Manag 42(3):257–276. https://doi.org/10. 16167.x 1006/jeem.2000.1162 White C, Kendall BE, Gaines S, Siegel DA, Costello C (2008) Marine Sanchirico JN, Wilen JE (2002) The impacts of marine reserves on reserve effects on fishery profit. Ecol Lett 11(4):370–379. https:// limited-entry fisheries. Nat Resour Model 15:291–310 doi.org/10.1111/j.1461-0248.2007.01151.x Sanchirico JN, Malvadkar U, Hastings A, Wilen JE (2006) When are no- White JW, Botsford LW, Moffitt EA, Fischer DT (2010) Decision analy- take zones an economically optimal fishery management strategy? sis for designing marine protected areas for multiple species with Ecol Appl 16(5):1643–1659 uncertain fishery status. Ecol Appl 20(6):1523–1541. https://doi. Starfield AM (1997) A pragmatic approach to modeling for wildlife man- org/10.1890/09-0962.1 agement. J Wildl Manag 61(2):261–270. https://doi.org/10.2307/ White AT, Aliño PM, Cros A, Fatan NA, Green AL, Teoh SJ, Laroya L, 3802581 Peterson N, Tan S, Tighe S, Venegas-Li R, Walton A, Wen W (2014) Swearer SE, Caselle JE, Lea DW, Warner RR (1999) Larval retention and Marine protected areas in the coral triangle: progress, issues, and recruitment in an island population of a coral-reef fish. Nature options. Coast Manag 42(2):87–106. https://doi.org/10.1080/ 402(6763):799–802. https://doi.org/10.1038/45533 08920753.2014.878177 Thrush SF, Hewitt JE, Cummings VJ, Dayton PK, Cryer M, Turner SJ, White JW, Nickols KJ, Botsford LW (2017) Response to O'Leary et al.: Funnell GA, Budd RG, Milburn CJ, Wilkinson MR (1998) misuse of models leads to misguided conservation recommenda- Disturbance of the marine benthic habitat by commercial fishing: tions. Conserv Lett 10(2):269–270. https://doi.org/10.1111/conl. impacts at the scale of the fishery. Ecol Appl 8(3):866–879 12344 Tscharntke T, Clough Y, Wanger TC, Jackson L, Motzke I, Perfecto I, Williamson DH, Harrison HB, Almany GR, Berumen ML, Bode M, Vandermeer J, Whitbread A (2012) Global food security, biodiver- Bonin MC, Choukroun S, Doherty PJ, Frisch AJ, Saenz-Agudelo sity conservation and the future of agricultural intensification. Biol P (2016) Large-scale, multidirectional larval connectivity among Conserv 151(1):53–59. https://doi.org/10.1016/j.biocon.2012.01. coral reef fish populations in the Great Barrier Reef Marine Park. 068 MolEcol25(24):6039–6054. https://doi.org/10.1111/mec.13908 http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Theoretical Ecology Springer Journals
Free
10 pages
Loading next page...
 
/lp/springer_journal/ocean-zoning-within-a-sparing-versus-sharing-framework-ICqT3F9N7B
Publisher
Springer Netherlands
Copyright
Copyright © 2018 by The Author(s)
Subject
Life Sciences; Theoretical Ecology/Statistics; Plant Sciences; Zoology
ISSN
1874-1738
eISSN
1874-1746
D.O.I.
10.1007/s12080-017-0364-x
Publisher site
See Article on Publisher Site

Abstract

The land-sparing versus land-sharing debate centers around how different intensities of habitat use can be coordinated to satisfy competing demands for biodiversity persistence and food production in agricultural landscapes. We apply the broad concepts from this debate to the sea and propose it as a framework to inform marine zoning based on three possible management strategies, establishing: no-take marine reserves, regulated fishing zones, and unregulated open-access areas. We develop a general model that maximizes standing fish biomass, given a fixed management budget while maintaining a minimum harvest level. We find that when management budgets are small, sea-sparing is the optimal management strategy because for all parameters tested, reserves are more cost-effective at increasing standing biomass than traditional fisheries management. For larger budgets, the optimal strategy switches to sea-sharing because, at a certain point, further investing to grow the no-take marine reserves reduces catch below the minimum harvest constraint. Our intention is to illustrate how general rules of thumb derived from plausible, single-purpose models can help guide marine protected area policy under our novel sparing and sharing framework. This work is the beginning of a basic theory for optimal zoning allocations and should be considered complementary to the more specific spatial planning literature for marine reserve as nations expand their marine protected area estates. . . . . . Keywords Sparing vs sharing Marine protected areas Fisheries management Marine zoning Open-access fisheries Marine policy The original version of this article was revised due to a retrospective Open Access order. Electronic supplementary material The online version of this article (https://doi.org/10.1007/s12080-017-0364-x) contains supplementary material, which is available to authorized users. * Jennifer McGowan Australian Research Council Centre of Excellence for Environmental j.mcgowan@uq.edu.au Decisions, The University of Queensland, St Lucia, QLD 4072, Australia Michael Bode Department of Biological Sciences, Macquarie University, North mbode.web@gmail.com Ryde, New South Wales 2109, Australia Centre for Biodiversity and Conservation Science, School of Matthew H. Holden Biological Sciences, The University of Queensland, St m.holden1@uq.edu.au Lucia, QLD 4072, Australia Katrina Davis Centre for Applications in Natural Resource Mathematics, School of k.davis@uq.edu.au Mathematics and Physics, The University of Queensland, St Lucia, QLD 4072, Australia Nils C. Krueck Marine Spatial Ecology Lab and Australian Research Council Centre nils.krueck@uqconnect.edu.au of Excellence for Coral Reef Studies, The University of Queensland, St Lucia, QLD 4072, Australia Maria Beger m.beger@uq.edu.au School of Environment and Life Sciences, University of Salford, Manchester, UK Katherine L. Yates Australian Institute of Marine Science, PMB 3, k.l.yates@salford.ac.uk Townsville, QLD 4810, Australia Hugh P. Possingham The Nature Conservancy, 4245 North Fairfax Drive, Suite 100, h.possingham@uq.edu.au Arlington, VA 22203-1606, USA 246 Theor Ecol (2018) 11:245–254 Introduction strategy to achieve fisheries objectives, rather than an either/or argument (Holland and Brazee 1996; Mangel 2000; White The land-sparing versus land-sharing (sparing vs sharing) de- et al. 2010). bate emerged from contrasting views about how to balance the Valid concerns remain regarding the socioeconomic im- competing demands for biodiversity persistence and food pro- pacts of marine reserves on communities and countries. duction in agricultural landscapes (Green et al. 2005; Fischer Indeed, most studies modeling the use of reserves for fisheries et al. 2014). Land sparing involves spatial consolidation and management have found that the addition of reserves will re- intensification of agricultural activities. This approach is duce yields whenever fisheries are already well managed based on the idea that concentrated agricultural activity can (Tuck and Possingham 2000; Hilborn et al. 2006), or suggest achieve equal or higher yields in a smaller land area than low reserves are an effective secondary management option in intensity usage. More land is available for biodiversity protec- cases where fisheries are heavily exploited or where effort tion thereby providing a net conservation benefit. The reductions are unlikely to succeed (Holland and Brazee counter-argument in support of sharing argues that wildlife- 1996). The establishment of marine reserves can lead to a friendly farming produces lower yields per unit area, but sup- redistribution of fishing effort within a region, potentially ne- ports biodiversity conservation by using less intensive produc- gating any net benefit of the reserve through increased fishing tion techniques across larger portions of the landscape pressure elsewhere (Agardy et al. 2011). Other studies have (Fischer et al. 2008). Studies typically investigate the sparing identified scenarios in which reserves could be essential for vs. sharing dichotomy to identify the most appropriate strate- maintaining high yields in spite of otherwise effective manage- gy for a given context, because how well species or popula- ment regulations. These include, for example, the potentially tions fare alongside increasing agricultural yields depends up- critical function of reserves as a buffer against environmental on species traits and local production methods (Balmford et al. stochasticity (Mangel 2000;West et al. 2009), and the positive 2005; Green et al. 2005; Phalan et al. 2011;Grau et al. 2013). impact of reserves on the density-dependent survival of young Although much of the debate centers around semantic issues fish (White 2009) which could increase the net productivity of (Tscharntke et al. 2012; Fischer et al. 2014), more recent em- fished populations adjacent to reserves (but see White et al. pirical research supports the discussion with quantitative data 2008; Hart and Sissenwine 2009; Russ and Alcala 2011). (Lee et al. 2014; Butsic and Kuemmerle 2015;Kremen 2015; Similar to the terrestrial debate, there is no standard solu- Law and Wilson 2015) particularly in plantation and livestock tion to protecting biodiversity and meeting human needs from production (Grau et al. 2013). the sea. Equipping decision-makers with a variety of tools to While not framed as sparing vs. sharing per se, equivalent inform policy will enable better and more flexible manage- discussions in ocean management debate the benefits of either ment strategies as to which zoning allocation should be pur- sued in a given context. Australia’s Great Barrier Reef Marine prohibiting fishing in some parts of the seascape or constraining fishing through management (White and Park, for example, represents one of the first systematically Kendall 2007;Hilborn 2016). Marine reserves that exclude designed networks of marine protected areas in the world all extractive activities are a popular tool for conserving ma- whose shared seascape consists of roughly equal proportions rine biodiversity. Efforts are underway to increase the number of marine reserves, managed fisheries and general use areas of reserves globally, particularly in developing countries (Fernandes et al. 2005). While successful in Australia where inshore fisheries experience heavy exploitation (McCook et al. 2010), encouraging other countries to adopt (White et al. 2014). In contrast, it is argued that traditional the exact same allocation would be unfounded given the di- fisheries management, such as catch and size regulations, are verse ecological, socioeconomic, and governance structures more effective mechanisms to maintain healthy fish stocks across marine jurisdictions globally. Yet, general ecological and productive fisheries (Hilborn et al. 2004). In this context, and socioeconomic principles apply everywhere, and rules quantitative investigations about sparing vs sharing in the sea of thumb based on plausible, single-purpose models can help traditionally argue whether or not marine reserves will provide guidepolicy(Starfield 1997;Gerber et al. 2003) in a time of greater fish biomass and environmental benefits than fishery rapid marine protected area expansion (Klein et al. 2015). regulations (Hastings and Botsford 1999; Hilborn et al. 2006; Here, we transfer the land sparing vs. sharing debate to the White and Kendall 2007)—a typically either/or argument. sea using three common zoning types: fully protected no-take These studies identify whether a fraction of the system in marine reserves, managed fishing zones, and unregulated and/ marine reserves—sparing—or regulation across the entire ar- or unmanaged fishing zones, hereafter called Bopen-access.^ ea—sharing—maximizes fishery yields or profits (Sanchirico We choose to characterize an allocation with only marine re- and Wilen 2001; Gerber et al. 2003; Hastings and Botsford serves and open-access areas as a Bpure^ sea sparing strategy. 2003; Sanchirico et al. 2006; White et al. 2008). We note, In the sea, we translate sharing to be any strategy that incor- however, there is a body of literature that considers and tests porates managed fishing zones, which can manifest as regu- lations on spatial or temporal effort, or gear restrictions that the utility of marine reserves as part of a mixed management Theor Ecol (2018) 11:245–254 247 minimize impact to the benthos or non-target species. We the seascape. The seascape is divided into three management characterize sharing along a continuum where some propor- zones: protected marine reserves (fraction R), managed fishing tion of the seascape is managed, but consider a Bpure^ sharing zones (fraction M), and open-access fishing zones (fraction F; strategy to be when the entire seascape is managed and no so every part of the system is in one of the zones,R+ M+F = reserves or open-access zones exist (Fig. 1). When defined 1). There is a financial cost to reserving (C ) and managing in this manner, we move beyond the sparing vs sharing di- (C ) habitat, the sum total of which must not exceed an allot- chotomy that prevails in the terrestrial debate (Kremen 2015), ted total management budget (B), R*C + M*C ≤ B.We R M to develop a framework that includes seven potential spared assume there is no management cost incurred in the open- and/or shared seascapes. We then illustrate how to access zone. Our objective is to maximize the total population operationalize the framework using a simple modeling ap- of our fishery species subject to the budget constraint and a proach whose optimally zoned seascapes secure a minimum minimum biomass yield. Our model identifies the optimum biomass yield while maximizing standing stock biomass (the proportional allocation of a seascape among the three zones. environmental benefit) for a given management budget. This To link the decisions about seascape zoning allocation to approach considers a single habitat-dependent fished species our objectives and constraints, we use a simple population whose harvest methods exert different levels of pressure on model tracking adult post-harvest biomass, A,at time t.Let the benthos. We are interested in the circumstances in which L and K, be fecundity and the total number of potential sites the optimal seascape is either a sparing strategy, defined here available for larval settlement (i.e., larval carrying capacity), when the case study area is allocated among no-take reserves respectively. Fishing mortality in the managed and open- and open-access zones, and when that changes to a sharing access zones are (1-S ) and (1-S ), respectively. We assume M F strategy, defined when the case study includes a managed habitat damage temporarily reduces the proportion of avail- fishery zone, and potentially the addition of either or both able sites for settlement in zone type i,by D ,for i in {M, F, R}, no-take and/or open-access zones (Fig. 1). at time t. We assume the damage is more severe in the open- access zone (D <D ), and that no habitat damage occurs in M F the no-take reserves, (D = 0). Assuming fish reproduce post- harvest and contribute larva to a common pool, which are then Material and methods allocated to the three zone types proportionally based on area, we obtain the following difference equation for total post- Model description harvest population size Our model assumes we are managing a single habitat- ½ S ðÞ 1−D M þ SðÞ 1−D F þ R LA M M F F t dependent fished species that reproduces with a pelagic larval A ¼ : ð1Þ tþ1 1 þ LA =K phase leading to evenly distributed recruitment in all parts of This formula is derived by assuming that larva uniformly settle at random among a fraction of available sites, which yields a Beverton-Holt recruitment relationship of the above form (Duncan et al. 2009). The model has a stable equilibrium at A ¼ S ðÞ 1−D M þ SðÞ 1−D F þ R− K; ð2Þ M M F F and analogous equilibrium harvest ½ ðÞ 1−S ðÞ 1−D M þðÞ 1−S ðÞ 1−D F LA M M F F H ¼ : ð3Þ 1 þ LA =K For simplicity, we assume 100% adult mortality after har- vest and reproduction, but acknowledge the lifecycle for many Fig. 1 Classes of sparing and sharing seascapes derived from our three- short-lived species may not be annual. We then search through zone framework. Pure spared seascapes are those defined by no-take reserves (R) and open-access areas (F) and defined in these plots as any all financially possible zoning configurations to find the opti- point on the line between F and R (excluding apex points where the mal seascape at equilibrium. The optimal solution is the sea- zoning allocation would be 100%). Shared seascapes are defined by scape allocation that delivers the largest environmental benefit any allocation with managed fishing zones (M), with a pure shared sea- (total equilibrium post-harvest adult population size), while scape defined by apex M (100% managed). Pie charts offer illustrative examples to help interpret the zone allocation at given points on the graph meeting the minimum harvest and budget constraints. 248 Theor Ecol (2018) 11:245–254 Ignoring the catch constraint we obtain an analytic solution for survival proportion that will yield MSY in a fully managed this optimal zoning allocation, which produces a general rule seascape and S to be the survival that leads to an equilibrium of thumb which holds true for small budgets (see BResults^). of 10% of virgin biomass when the fishery is completely un- However, to account for the nonlinear catch constraint, we regulated, open access. We assume that fishers will not toler- solved for the optimal allocation using simulations conducted ate a level of catch lower than the pre-managed open access in Matlab (MathWorks, Natick Massachusetts, USA; yield therefore the catch threshold (CT) is set to the open- Appendix A). access harvest. Case study parameterization Costs For our case study, we apply our model to derive an optimum Despite being critical to decision-making about natural re- zone allocation based on the conditions of tiger prawn fisher- source management (Naidoo et al. 2006), costs associated ies (O'Neill and Turnbull 2006) using the parameters outlined with establishing and managing protected areas are often in Table 1. Damage caused by benthic fishing is difficult to poorly reported, difficult to quantify (Balmford et al. 2004; quantify and depends on the type of gear, and the frequency Ban et al. 2011), and highly contextual (Rojas-Nazar et al. and distribution of effort (Thrush et al. 1998; Collie et al. 2015). As a flexible way to integrate the amalgam of costs 2000). Impacts to coastal habitats range from diminished (e.g., stock assessments, ecological monitoring, staffing, en- structural complexity (Auster 1998), changes to community forcement, etc.) associated with the different zones (Ban et al. composition (Thrush et al. 1998), and altered ecological pro- 2011) and across regions, we parameterize the relative costs cesses (e.g., reduced primary production from macrofauna between protected and managed areas. One key factor driving depletion; enhanced nutrient cycling via suspended sediment the cost of management interventions, be they marine reserves loads (Auster and Langton 1999)). or gear restrictions, is the cost of enforcing compliance. The For the purpose of this exercise, we make several necessary costs associated with surveillance and enforcement depend on simplifying assumptions about benthic impacts from fishing both the size of the zones and the social and economic char- activities. We recognize benthic habitat condition is case-spe- acteristics of the resource users. Only a few studies have ex- cific. In cases where more detailed data exist, this information plicitly quantified these costs (Ban and Klein 2009; Davis can easily be incorporated into our modeling framework. We et al. 2015). Ban et al. (2011) compared the enforcement costs assume that previously unregulated trawling has impacted the for staffing an entirely no-take protected area versus a mixed benthic community in the open-access zone. We define impact zone seascape (protected and fished) and found that compli- as the mean mortality (20–50%) of benthic invertebrates re- ance staffing was doubled when mixed zoning occurred. ported in Collie et al. (2017) for towed benthic fishing gears. As a starting point for our case study, we assume the cost of We assume perfectly enforced restrictions in the managed enforcing fisheries management is twice that of protecting zone reduce the fishing impacts on the benthos by half so that area, C =2C but we test the sensitivity of the outcome to M R D =0.5*D (Chuenpagdee et al. 2003). We set S to be the variations in the relative costs to protect and manage when M F M Table 1 Case study parameters Parameter Description Value Source based on population conditions for Penaeus esculentus (tiger s Intrinsic survival 1 O'Neill and Turnbull 2006 prawn) KCarryingcapacityofwhole 30 O'Neill and Turnbull 2006 environment L* Fecundity of adults 5 O'Neill and Turnbull 2006 D * Habitat damage in the 0.35 Collie et al. 2017 open-access fishing zone D Habitat damage in the managed 0.175 (derived as 0.5*D ) Chuenpagdee et al. 2003 M F fishing zone S * Survivorship in fished zones 0.48 To achieve 10% virgin biomass at equilibrium. See formula in code, Appendix A S Survivorship in managed zones 0.65 To achieve MSY at equilibrium. See formula in code, Appendix A CT* Catch threshold 1.85 Open-access equilibrium C to Cost ratio between managing 2:1 Ban et al. 2011 C * and protection *Sensitivity tested (see Fig. 3 and Appendix) Theor Ecol (2018) 11:245–254 249 C =C and when the cost of enforcing reserves is double the zones. We find this departure is most sensitive to changes in R M cost of enforcing managed fishing areas C =2C .We also fecundity (L) and occurs when the reserve coverage is be- R M examine the case of additional fixed costs (e.g., costs that do tween 45 and 70% of the seascape. When fecundity is greater, not scale with area) of reserves and managed areas in the we switch to investing in management zones at lower propor- appendix (see Appendix B). Management budgets can vary tions of reserves in the seascape. enormously between regions and in time; therefore, we are Regardless of the parameter tested, we consistently observe most interested in identifying the circumstances under which the phenomenon of sea sparing when budgets are small, as the optimal management strategy shifts between sparing and well as the switch to the three-zone version of sharing as sharing as the management budget changes. We investigate budgets increase. This trend is robust to changes in the cost the optimal strategy under different budgets to variations in ratio as well as when we eliminate the influence of habitat several parameters of interest: habitat damage in the open- damage caused by fishing in each zone (D = 0 and D =0) M F access fishing zone (D ), escapement in the open-access fish- (see Appendix B–C for further sensitivity analyses). ing zone (S ), fecundity (L), and the catch threshold (CT). Sensitivity manifests in two possible ways that affect the op- timal seascape as the budget grows: (1) the point of departure from sparing to sharing and (2) the proportion allocated to Results each zone (Fig. 3). Interestingly, the proportion of area protected, R, at the point of departure from sparing to sharing Case study remains fairly constant irrespective of the cost ratio for our case study (Appendix B; about 60% of the seascape). When If there is no management budget, then fishing must occur the cost of protection is double the cost of management, under open-access conditions throughout the seascape, re- C =2C , the point of departure is substantially delayed as R M gardless of the fishery being considered, because managed the budget grows large enough to share the seascape but ulti- areas and reserves require financial investment. In our case mately follows the same investment strategy. study, we find that when management budgets are low (Fig. 2 where B ≤ 0.61), the optimal choice is to allocate the Optimal rule of thumb for small budgets entire budget to establishing no-take zones and have no man- aged areas. With the budget exhausted the rest of the seascape Our approach also allows us to derive an analytic rule of remains in open-access fishing—considered here as a sea thumb to assist decision-makers about what the optimal in- sparing strategy where the portions of the seascape not under vestment strategy may be for their given context. With no protection are intensively harvested. As the budget increases, catch constraint, the optimal zoning solution is to allocate so does the fraction of the protected seascape. During this the entire budget to marine reserves (sparing) if the benefit stage, initially, the catch increases because additional reserves of adding a reserve (relative to open-access fishing), per unit increase larvae production, which is then mostly distributed to cost, is greater than the cost-benefit of adding a managed area. unregulated zones for fishing. However, after a critical reserve Otherwise, the decision-maker should spend their entire bud- threshold, catch declines because additional reserves do not get on managed areas. This rule can be simplified mathemat- provide sufficient larval export to the open-access zones to ically as Bspend the entire budget on reserves^ if compensate the fishery for the population now excluded from harvesting. Eventually, the optimal seascape switches from 1−S ðÞ 1−D C M M M 1− > : ð4Þ sparing (reserves and open-access) to include all three 1−SðÞ 1−D C F F R zones—a version of sea sharing (Fig. 1). This occurs when further expanding the reserved area prevents the fishery from To derive this rule, let x be the amount of money satisfying the minimum harvest constraint. In this case, bio- allocated to reserves and, B – x, the amount of money mass can be increased further with the addition of managed allocated to managed areas. Then R = x/C and M =(B- zones while still meeting the catch constraint. x)/C ,and F = 1 – R-M. One can solve for the x that Figure 3 shows how the optimal zoning allocation changes maximizes A* by substituting these quantities into Eq. 2 as a function of the budget for our parameters of interest: D , which produces condition 4. S , L,and CT. Beginning with no budget, the seascape is Based on our numerical simulations, the rule of thumb held completely open-access fishing (apex F). As the budget for all tested cases until so many reserves had been purchased grows, the allocation moves along the Bsparing^ boundary, that the catch constraint would no longer be satisfied if the where the seascape consists of open-access and increasing decision maker continued adding reserves. For our baseline proportions of no-take reserves. A point of departure, or tran- parameterization, we found that reserves were favored over sition point, finally moves the allocation away from sea spar- managed areas unless the cost of reserves was nearly five ing and into a shared configuration consisting of all three times that of managed areas. Even for the combination of 250 Theor Ecol (2018) 11:245–254 Fig. 2 The optimal sparing versus sharing strategy (top) showing the fraction of the seascape allocated to each of the three zones with an increasing budget for our case study. No-take marine reserves in blue (R); open-access fishing in green (F); and managed zones in yellow (M). The white dashed line is the departure point between sparing and sharing. When there is no budget we can neither reserve nor manage. As the budget increases, first marine reserves and then managed fisheries, enter the optimal zoning allocation. Also shown are catch, biomass, and the spending regime parameters most favorable for managed areas in the sensitivity unmanaged open-access system (F = 1) likely results in over analysis, managed areas were not selected for low budgets exploitation and potential fishery collapse (Hutchings 2000); unless the cost of reserves was over three times higher than finally, while (3) a purely shared system is possible (e.g., M = the cost of managed areas. 1 with no reserves or unmanaged fisheries), the reality of limited management budgets and global commitments to MPAs reduce the likelihood of this option persisting through Discussion time. Mixed zoning under our framework consists of (4) a pure spared seascape with both no-take reserves and open- A sea sparing and sharing framework access zones, (5) shared seascapes with managed and open- access zones, and two zoning configurations that allow Seven seascape allocations emerge from our sea sparing and Bsparing and sharing.^ The first of these last two zoning con- figurations includes (6) no-take reserves and managed fisher- sharing framework (Fig. 1). A seascape allocated entirely to one zone is highly unlikely as (1) an entirely reserved no-take ies; and (7) no-take reserves, managed fisheries and open- access zones. With this conceptual starting point, a useful next system (R = 1) cannot meet the harvest constraint; (2) an Theor Ecol (2018) 11:245–254 251 Fig. 3 Ternary plots showing the fraction of the seascape in each of the three zones (R = no take reserves, M = managed fishing zones, F = open access) for a given budget, where R+M + F= 1. When no budget exists, B =0, the entire seascape is open access, 100% F in the bottom right corner. Colored lines show the sensitivity of the seascape allocation under several values for each parameter of interest: a habitat damage caused by fishing in the open-access fishing zone (D ), b escapement in the open- access fishing zone (S ), c fecundity of adults (L), and d the catch threshold (CT). The departure from the sparing strategy (line F–R) indicates the transition point from sparing to sharing as the budget increases step for the future would be to classify existing management are treated as objectives to be maximized or minimized, and/or plans within this framework to see what the most dominant constraints. Defining a different objective for ocean manage- strategies are in practice, and to create a typology of spared ment (e.g., maximizing larval connectivity, protecting species and shared seascapes that enable moving beyond the dichot- climate refugia (Beger et al. 2015) or building near-pristine omous view of the sparing vs sharing debate. Building on this fish biomass (McClanahan et al. 2007)), or evaluating trade- idea, our framing also exposes the need for a more refined offs for multi-objective problems would also be valid classification system, as Bsparing,^ Bsharing,^ and Bsparing approaches. and sharing^ are too vague to encompass the nuanced man- We strategically simplify many assumptions in order to agement practices governing marine systems (White et al. develop a model that can begin to inform policy (Hastings 2010;Kremen 2015). and Botsford 1999). Opportunities to add complexity into our approach include incorporating a spatially realistic model- ing environment (Polasky et al. 2008; Metcalfe et al. 2015), Only the rich can afford to share alternative assumptions of density dependence before and af- ter settlement (e.g. Ricker models), age structure, overcom- When budgets are small, sea sparing is always the optimal pensation (e.g., White and Kendall (2007)), integrating more allocation. As the budget grows, we arrive at a point where complex dispersal processes, accounting for variable distribu- increasing the amount of the reserves any further will compro- tions of fishing effort and displacement, socioeconomics mise our ability to achieve the minimum harvest constraint. If budgets increase beyond this point, the optimal strategy is to (Sanchirico and Wilen 2002; Halpern et al. 2004;Armstrong and Skonhoft 2006;Costelloand Polasky 2008), and devel- start sharing. The optimal strategy under our framework will oping multi-species models. be specific to the definition of objectives and constraints For some of these limitations, we can foresee how the (White et al. 2017). For example, we approached this problem model will respond. For example, adding age structure would by identifying a single conservation objective (maximize allow biomass to accumulate in reserves, likely achieving our standing biomass), while acknowledging two constraints: a objectives with less reserved area. In instances where over- natural resource requirement (expressed by the minimum har- compensation is justified we would expect to see higher re- vest constraint) and a fixed management budget. However, it serve coverage (White and Kendall 2007). We acknowledge is important to note there are many alternate ways to frame this that our approach also depends on some degree of overfishing problem depending on whether the above outcome variables 252 Theor Ecol (2018) 11:245–254 collaborations by ARC CoE for Environmental Decisions. J.M. is funded for this framework to apply. This assumption influences the by an Australian International Postgraduate Research Scholarship. M.B. point of departure, in that, the time at which managed areas are was funded by a Discovery Early Career Research Award to the ARC added will depend on the assumptions of overfishing. CoE for Environmental Decisions (CE110001014). However, the general trend of sparing first and moving to Open Access This article is distributed under the terms of the Creative the three-zone version of sharing is robust and highlights that Commons Attribution 4.0 International License (http:// mixed management approaches have merit where substantial creativecommons.org/licenses/by/4.0/), which permits use, duplication, management capacity exists (Hilborn 2016). adaptation, distribution and reproduction in any medium or format, as The species and associated fishery we chose to represent long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if in the model are intentionally responsive to reserves, be- changes were made. cause we believe that it is these types of species and fish- eries that drive zoning decisions for coastal management. However, our findings may also apply to systems where common pool dispersal assumptions are not met. The first References empirical measurements of larval dispersal revealed unex- pectedly high levels of self-recruitment (Jones et al. 1999; Agardy T, di Sciara GN, Christie P (2011) Mind the gap: addressing the Swearer et al. 1999) which challenged the general assump- shortcomings of marine protected areas through large scale marine tion of strong population connectivity across large sea- spatial planning. Mar Policy 35(2):226–232. https://doi.org/10. scapes. More recent studies confirm that larval settlement 1016/j.marpol.2010.10.006 close to spawning locations is indeed common, but that the Almany GR, Planes S, Thorrold SR, Berumen ML, Bode M, Saenz- AgudeloP,BoninMC, Frisch AJ,HarrisonHB, MessmerV dispersal distances of a significant proportion of other lar- (2017) Larval fish dispersal in a coral-reef seascape. Nat Ecol Evol vae can still be extensive (Green et al. 2015; Jones 2015; 1:s41559–s41017 Williamson et al. 2016;Almanyet al. 2017). In such cases, Armstrong CW, Skonhoft A (2006) Marine reserves: a bio-economic reserve size and placement can be optimized with a high model with asymmetric density dependent migration. Ecol Econ 57(3):466–476. https://doi.org/10.1016/j.ecolecon.2005.05.010 level of flexibility to provide for maximum fishery benefits Auster PJ (1998) A conceptual model of the impacts of fishing gear on the (Krueck et al. 2017a, b). integrity of fish habitats. Conserv Biol 12(6):1198–1203. https://doi. Despite our stated limitations, our model goes beyond tra- org/10.1046/j.1523-1739.1998.0120061198.x ditional management zone assessments by illustrating how Auster PJ, Langton RW (1999) The effects of fishing on fish habitat. In: fisheries management influences the optimal seascape alloca- Benaka L (ed) Fish habitat: essential fish habitat and rehabilitation. American Fisheries Society, Bethesda, p 150–187 tion. Our approach is the first attempt to underpin the sharing Balmford A, Gravestock P, Hockley N, McClean CJ, Roberts CM (2004) and sparing debate with a process model. In doing so, we The worldwide costs of marine protected areas. Proc Natl Acad Sci reveal a more nuanced and practical framework than the de- USA 101:9694–9697 bate has produced to date (Kremen 2015). Ocean management Balmford A, Green R, Scharlemann JPW (2005) Sparing land for nature: exploring the potential impact of changes in agricultural yield on the can benefit from applying this framework and devising simple area needed for crop production. Glob Chang Biol 11(10):1594– rules of thumb to guide policy options, for example, investing 1605. https://doi.org/10.1111/j.1365-2486.2005.001035.x in marine reserves when budgets are low with the addition of Ban NC, Klein CJ (2009) Spatial socioeconomic data as a cost in system- managed areas when budgets are high. Building additional atic marine conservation planning. Conserv Lett 2(5):206–215. https://doi.org/10.1111/j.1755-263X.2009.00071.x complexity into this base exploration as well as developing Ban NC, Adams V, Pressey RL, Hicks J (2011) Promise and problems for the sea sparing vs sea sharing framework will help advance estimating management costs of marine protected areas. Conserv the debate and its relevance for marine policy. This work is the Lett 4(3):241–252. https://doi.org/10.1111/j.1755-263X.2011. beginning of a basic theory for optimal allocations within 00171.x Beger M, McGowan J, Treml EA, Green AL, White AT, Wolff NH, Klein seascape zoning frameworks and should be considered com- CJ, Mumby PJ, Possingham HP (2015) Integrating regional conser- plementary to the more specific spatial planning literature for vation priorities for multiple objectives into national policy. Nat marine reserve design and implementation, which addresses Commun 6:8208. https://doi.org/10.1038/ncomms9208 the size, shape, and placement of individual MPAs within a Butsic V, Kuemmerle T (2015) Using optimization methods to align food production and biodiversity conservation beyond land sharing and seascape. land sparing. Ecol Appl 25(3):589–595. https://doi.org/10.1890/14- 1927.1 Acknowledgements We would like to thank all BDichotomies in Marine Chuenpagdee R, Morgan LE, Maxwell SM, Norse EA, Pauly D (2003) Conservation^ workshop participants for their contributions in initial dis- Shifting gears: assessing collateral impacts of fishing methods in US cussions, particularly Dr. Tessa Mazor and Dr. Sylvaine Giakoumi, and waters. Front Ecol Environ 1(10):517–524 the thoughtful contributions of Dr. Natalie Ban and our three anonymous Collie JS, Hall SJ, Kaiser MJ, Poiner IR (2000) A quantitative analysis of reviewers. fishing impacts on shelf-sea benthos. J Anim Ecol 69(5):785–798. https://doi.org/10.1046/j.1365-2656.2000.00434.x Funding information This work was conceived in a workshop funded by Collie J, Hiddink JG, Kooten T, Rijnsdorp AD, Kaiser MJ, Jennings S, H. P. P.’s ARC Laureate Fellowship with additional funding for Hilborn R (2017) Indirect effects of bottom fishing on the Theor Ecol (2018) 11:245–254 253 productivity of marine fish. Fish Fish 18(4):619–637. https://doi. Hilborn R, Micheli F, De Leo GA (2006) Integrating marine protected org/10.1111/faf.12193 areas with catch regulation. Can J Fish Aquat Sci 63(3):642–649. Costello C, Polasky S (2008) Optimal harvesting of stochastic spatial https://doi.org/10.1139/f05-243 resources. J Environ Econ Manag 56(1):1–18. https://doi.org/10. Holland DS, Brazee RJ (1996) Marine reserves for fisheries management. 1016/j.jeem.2008.03.001 Mar Resour Econ 11(3):157–171. https://doi.org/10.1086/mre.11.3. Davis K, Kragt M, Gelcich S, Schilizzi S, Pannell D (2015) Accounting 42629158 for enforcement costs in the spatial allocation of marine zones. Hutchings JA (2000) Collapse and recovery of marine fishes. Nature Conserv Biol 29(1):226–237. https://doi.org/10.1111/cobi.12358 406(6798):882–885. https://doi.org/10.1038/35022565 Duncan RP, Diez JM, Sullivan JJ, Wangen S, Miller AL (2009) Safe sites, Jones GP (2015) Mission impossible: unlocking the secrets of coral reef seed supply, and the recruitment function in plant populations. fish dispersal. In: Mora C (ed) Ecology of fishes on coral reefs, Ecology 90(8):2129–2138. https://doi.org/10.1890/08-1436.1 Cambridge University Press, Cambridge, p 16–28 Fernandes L, Day JON, Lewis A, Slegers S, Kerrigan B, Breen DAN, Jones GP, Milicich MJ, Emslie MJ, Lunow C (1999) Self-recruitment in a Cameron D, Jago B, Hall J, Lowe D, Innes J, Tanzer J, Chadwick V, coral reef fish population. Nature 402(6763):802–804. https://doi. Thompson L, Gorman K, Simmons M, Barnett B, Sampson K, org/10.1038/45538 De'Ath G, Mapstone B, Marsh H, Possingham H, Ball IAN, Ward Klein CJ, Brown CJ, Halpern BS, Segan DB, McGowan J, Beger M, T, Dobbs K, Aumend J, Slater DEB, Stapleton K (2005) Watson JEM (2015) Shortfalls in the global protected area network Establishing representative no-take areas in the great barrier reef: at representing marine biodiversity. Sci Rep 5(1):17539. https://doi. large-scale implementation of theory on marine protected areas. org/10.1038/srep17539 Conserv Biol 19(6):1733–1744. https://doi.org/10.1111/j.1523- Kremen C (2015) Reframing the land-sparing/land-sharing debate for 1739.2005.00302.x biodiversity conservation. Ann N Y Acad Sci 1355(1):52–76. Fischer J, Brosi B, Daily GC, Ehrlich PR, Goldman R, Goldstein J, https://doi.org/10.1111/nyas.12845 Lindenmayer DB, Manning AD, Mooney HA, Pejchar L (2008) Krueck NC, Ahmadia GN, Green A, Jones GP, Possingham HP, Riginos Should agricultural policies encourage land sparing or wildlife- C, Treml EA, Mumby PJ (2017a) Incorporating larval dispersal into friendly farming? Front Ecol Environ 6(7):380–385. https://doi. MPA design for both conservation and fisheries. Ecol Appl 27(3): org/10.1890/070019 925–941. https://doi.org/10.1002/eap.1495 Fischer J, Abson DJ, Butsic V, Chappell MJ, Ekroos J, Hanspach J, Krueck NC, Ahmadia GN, Possingham HP, Riginos C, Treml EA, Kuemmerle T, Smith HG, von Wehrden H (2014) Land sparing Mumby PJ (2017b) Marine reserve targets to sustain and rebuild versus land sharing: moving forward. Conserv Lett 7(3):149–157. unregulated fisheries. PLoS Biol 15(1):e2000537. https://doi.org/ https://doi.org/10.1111/conl.12084 10.1371/journal.pbio.2000537 Gerber LR, Botsford LW, Hastings A, Possingham HP, Gaines SD, Law, E. A. and K. A. Wilson (2015) Providing context for the land- Palumbi SR, Andelman S (2003) Population models for marine sharing and land-sparing debate. Conserv Lett 8(6):404–413. reserve design: a retrospective and prospective synthesis. Ecol https://doi.org/10.1111/conl.12168 Appl 13(sp1):47–64 Lee JSH, Garcia-Ulloa J, Ghazoul J, Obidzinski K, Koh LP (2014) Grau R, Kuemmerle T, Macchi L (2013) Beyond ‘land sparing versus Modelling environmental and socio-economic trade-offs associated land sharing’: environmental heterogeneity, globalization and the with land-sparing and land-sharing approaches to oil palm expan- balance between agricultural production and nature conservation. sion. J Appl Ecol 51(5):1366–1377. https://doi.org/10.1111/1365- Curr Opin Environ Sustain 5(5):477–483. https://doi.org/10.1016/ 2664.12286 j.cosust.2013.06.001 Mangel M (2000) On the fraction of habitat allocated to marine reserves. Green RE, Cornell SJ, Scharlemann JPW, Balmford A (2005) Farming Ecol Lett 3(1):15–22. https://doi.org/10.1046/j.1461-0248.2000. and the fate of wild nature. Science 307(5709):550–555. https://doi. 00104.x org/10.1126/science.1106049 McClanahan TR, Graham NAJ, Calnan JM, MacNeil MA (2007) Toward Green AL, Maypa AP, Almany GR, Rhodes KL, Weeks R, Abesamis pristine biomass: reef fish recovery in coral reef marine protected RA, Gleason MG, Mumby PJ, White AT (2015) Larval dispersal areas in Kenya. Ecol Appl 17(4):1055–1067. https://doi.org/10. and movement patterns of coral reef fishes, and implications for 1890/06-1450 marine reserve network design. Biol Rev 90(4):1215–1247. McCook LJ, Ayling T, Cappo M, Choat JH, Evans RD, De Freitas DM, https://doi.org/10.1111/brv.12155 Heupel M, Hughes TP, Jones GP, Mapstone B (2010) Adaptive Halpern BS, Gaines SD, Warner RR (2004) Confounding effects of the management of the great barrier reef: a globally significant demon- export of production and the displacement of fishing effort from stration of the benefits of networks of marine reserves. Proceedings marine reserves. Ecol Appl 14(4):1248–1256. https://doi.org/10. of the National Academy of Sciences 107:18278–18285 1890/03-5136 Metcalfe K, Vaz S, Engelhard GH, Villanueva MC, Smith RJ, Mackinson Hart DR, Sissenwine MP (2009) Marine reserve effects on fishery profits: S (2015) Evaluating conservation and fisheries management strate- a comment on White et al. (2008). Ecol Lett 12(3):E9–E11. https:// gies by linking spatial prioritization software and ecosystem and doi.org/10.1111/j.1461-0248.2008.01272.x fisheries modelling tools. J Appl Ecol 52(3):665–674. https://doi. Hastings A, Botsford LW (1999) Equivalence in yield from marine re- org/10.1111/1365-2664.12404 serves and traditional fisheries management. Science 284(5419): Naidoo R, Balmford A, Ferraro PJ, Polasky S, Ricketts TH, Rouget M 1537–1538. https://doi.org/10.1126/science.284.5419.1537 (2006) Integrating economic costs into conservation planning. Hastings A, Botsford LW (2003) Comparing designs of marine reserves Trends Ecol Evol 21(12):681–687. https://doi.org/10.1016/j.tree. for fisheries and for biodiversity. Ecol Appl 13(sp1):65–70 2006.10.003 Hilborn R (2016) Marine biodiverity needs more than protection. Nature 535(7611):224–226. https://doi.org/10.1038/535224a O'Neill MF, Turnbull C (2006) Stock assessment of the Torres Strait tiger Hilborn R, Stokes K, Maguire JJ, Smith T, Botsford LW, Mangel M, prawn fishery (Penaeus esculentus). Department of Primary Orensanz J, Parma A, Rice J, Bell J, Cochrane KL, Garcia S, Hall Industries and Fisheries, Brisbane City SJ , Kirkwood GP, Sainsbury K, Stefansson G, Walters C (2004) Phalan B, Onial M, Balmford A, Green RE (2011) Reconciling food When can marine reserves improve fisheries management? Ocean production and biodiversity conservation: land sharing and land Coast Manag 47(3-4):197–205. https://doi.org/10.1016/j. sparing compared. Science 333(6047):1289–1291. https://doi.org/ ocecoaman.2004.04.001 10.1126/science.1208742 254 Theor Ecol (2018) 11:245–254 PolaskyS,NelsonE,CammJ,CsutiB,FacklerP,LonsdorfE, Tuck GN, Possingham HP (2000) Marine protected areas for spatially structured exploited stocks. Mar Ecol Prog Ser 192:89–101. https:// Montgomery C, White D, Arthur J, Garber-Yonts B (2008) Where to put things? Spatial land management to sustain biodiversity and doi.org/10.3354/meps192089 economic returns. Biol Conserv 141(6):1505–1524. https://doi.org/ West CD, Dytham C, Righton D, Pitchford JW (2009) Preventing over- 10.1016/j.biocon.2008.03.022 exploitation of migratory fish stocks: the efficacy of marine Rojas-Nazar UA, Cullen R, Gardner JPA, Bell JJ (2015) Marine reserve protected areas in a stochastic environment. ICES J Mar Sci 66(9): establishment and on-going management costs: a case study from 1919–1930. https://doi.org/10.1093/icesjms/fsp159 New Zealand. Mar Policy 60:216–224. https://doi.org/10.1016/j. White C (2009) Density dependence and the economic efficacy of marine marpol.2015.06.029 reserves. Theor Ecol 2(3):127–138. https://doi.org/10.1007/s12080- Russ GR, Alcala AC (2011) Enhanced biodiversity beyond marine re- 009-0039-3 serve boundaries: the cup spillith over. Ecol Appl 21(1):241–250. White C, Kendall BE (2007) A reassessment of equivalence in yield from https://doi.org/10.1890/09-1197.1 marine reserves and traditional fisheries managament. Oikos Sanchirico JN, Wilen JE (2001) A bioeconomic model of marine reserve 116(12):2039–2043. https://doi.org/10.1111/j.2007.0030-1299. creation. J Environ Econ Manag 42(3):257–276. https://doi.org/10. 16167.x 1006/jeem.2000.1162 White C, Kendall BE, Gaines S, Siegel DA, Costello C (2008) Marine Sanchirico JN, Wilen JE (2002) The impacts of marine reserves on reserve effects on fishery profit. Ecol Lett 11(4):370–379. https:// limited-entry fisheries. Nat Resour Model 15:291–310 doi.org/10.1111/j.1461-0248.2007.01151.x Sanchirico JN, Malvadkar U, Hastings A, Wilen JE (2006) When are no- White JW, Botsford LW, Moffitt EA, Fischer DT (2010) Decision analy- take zones an economically optimal fishery management strategy? sis for designing marine protected areas for multiple species with Ecol Appl 16(5):1643–1659 uncertain fishery status. Ecol Appl 20(6):1523–1541. https://doi. Starfield AM (1997) A pragmatic approach to modeling for wildlife man- org/10.1890/09-0962.1 agement. J Wildl Manag 61(2):261–270. https://doi.org/10.2307/ White AT, Aliño PM, Cros A, Fatan NA, Green AL, Teoh SJ, Laroya L, 3802581 Peterson N, Tan S, Tighe S, Venegas-Li R, Walton A, Wen W (2014) Swearer SE, Caselle JE, Lea DW, Warner RR (1999) Larval retention and Marine protected areas in the coral triangle: progress, issues, and recruitment in an island population of a coral-reef fish. Nature options. Coast Manag 42(2):87–106. https://doi.org/10.1080/ 402(6763):799–802. https://doi.org/10.1038/45533 08920753.2014.878177 Thrush SF, Hewitt JE, Cummings VJ, Dayton PK, Cryer M, Turner SJ, White JW, Nickols KJ, Botsford LW (2017) Response to O'Leary et al.: Funnell GA, Budd RG, Milburn CJ, Wilkinson MR (1998) misuse of models leads to misguided conservation recommenda- Disturbance of the marine benthic habitat by commercial fishing: tions. Conserv Lett 10(2):269–270. https://doi.org/10.1111/conl. impacts at the scale of the fishery. Ecol Appl 8(3):866–879 12344 Tscharntke T, Clough Y, Wanger TC, Jackson L, Motzke I, Perfecto I, Williamson DH, Harrison HB, Almany GR, Berumen ML, Bode M, Vandermeer J, Whitbread A (2012) Global food security, biodiver- Bonin MC, Choukroun S, Doherty PJ, Frisch AJ, Saenz-Agudelo sity conservation and the future of agricultural intensification. Biol P (2016) Large-scale, multidirectional larval connectivity among Conserv 151(1):53–59. https://doi.org/10.1016/j.biocon.2012.01. coral reef fish populations in the Great Barrier Reef Marine Park. 068 MolEcol25(24):6039–6054. https://doi.org/10.1111/mec.13908

Journal

Theoretical EcologySpringer Journals

Published: Jan 12, 2018

References

You’re reading a free preview. Subscribe to read the entire article.


DeepDyve is your
personal research library

It’s your single place to instantly
discover and read the research
that matters to you.

Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.

All for just $49/month

Explore the DeepDyve Library

Search

Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly

Organize

Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.

Access

Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.

Your journals are on DeepDyve

Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.

All the latest content is available, no embargo periods.

See the journals in your area

DeepDyve

Freelancer

DeepDyve

Pro

Price

FREE

$49/month
$360/year

Save searches from
Google Scholar,
PubMed

Create lists to
organize your research

Export lists, citations

Read DeepDyve articles

Abstract access only

Unlimited access to over
18 million full-text articles

Print

20 pages / month

PDF Discount

20% off