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Other offshore areas, mainly along the north-western and southern boundary, also had higher selection frequencies, because of the high cost effectiveness of achieving targets in these locations. We compared the results of scenario one with scenario two that used the average values for the time periods covered by data for chlorophyll a , copepods, anchovies and sardines, there were high correlation of selection frequencies Spearman's rank correlation of 0.

The proportion of total cost based on summing the cost metric values across all planning units was also similar between the averaged data best solution For a , values for chlorophyll a were monthly, copepods yearly, anchovies yearly and sardines yearly. For b , values for chorophyll a , copepods, anchovies and sardines were averaged over the entire periods of data availability. Boundary lengths, which help to determine the compactness of the area configurations, were the same in parts a and b. For c , boundary lengths between planning units were longer offshore than inshore to produce solutions with more compactness offshore.

Comparing the best solution for these two scenarios, we found measuring the proportion protected for chlorophyll a resulted in fairly similar results between the two scenarios Fig 7a. However, for copepods, anchovies and sardines, the two approaches produced quite different results Fig 7b—d. We found that time-period targets were not achieved for 9 out of 14 periods for copepods, 7 out of 24 periods for anchovies, and 16 out of 24 periods for sardines Fig 7d. Dark gray lines show level of representation in best solutions when targets were set for chlorophyll a monthly , copepods yearly , anchovies yearly and sardines yearly.

Light gray lines show level of representation in best solutions when targets were set for values of these four features averaged over the whole periods data availability January to December for chlorophyll a, — for copepod biomass, — for anchovy biomass, — for sardine biomass. For scenario three we experimented with boundary lengths of adjacent planning units to produce solutions with mixed compactness, we were able to develop solutions with compactness higher offshore than inshore Fig 6c. The selection frequencies between this scenario and scenario one were correlated albeit less so than comparisons between other scenarios Spearman's rank correlation of 0.

When benthic biodiversity was included in the prioritization Fig 8a,b , there were more areas with higher selection frequencies, indicating less spatial flexibility in the configuration of protected areas Fig 8c. There were particularly important areas to the north west of Cape Point in a linear configuration related to a canyon. The illustrative best solution Fig 8d contains areas selected that were scattered throughout the study region. The selection frequencies between this scenario and the main scenario were correlated Spearman's rank correlation of 0. Benthic data included two biodiversity surrogates used as a proxy for benthic biodiversity a biozones based on depth classes, and b different benthic habitat classes based on geology.

Both were used as a basis for designing protected areas for benthic biodiversity. Areas were selected based on a combination of the pelagic features, biozones and benthic habitat map. There is a tendency for management agencies to manage marine resources and plan management actions for individual species, separately for inshore and offshore areas, and for benthic and not pelagic habitats [58]. In this study, we successfully included spatially and temporally variable features relevant to pelagic conservation in a decision support tool usually applied to static features to design pelagic MPAs.

Our integrated approach in this dynamic oceanographic region includes planning for multiple species and oceanographic features, both inshore and offshore areas, and considered both pelagic and benthic environments. Any protected area network design is likely to be most successful when it is the result of a participatory planning approach where key stakeholders are involved in decision-making about the location of conservation management [59].

A map such as the most frequently selected areas Fig 5c could be a good starting point for negotiation. The extent to which large oceanic processes can be adequately protected in conservation areas depends to some extent on how the implementation of protected areas will impact stakeholders. The very large protected areas required to protected highly dynamic features might not be feasible, in which case, other forms of conservation management such as gear restrictions or market-based approaches [60] might be more appropriate.

We explored spatial and temporal variability mostly using surface-measured features e. Water column processes are important drivers of productivity.

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However, the inclusion of vertical processes might be challenging for science and management if surface and seafloor measured features are not adequate surrogates for vertical processes. We estimated the spatial and temporal variations in the occurrences of top predators indirectly by using time series data on chlorophyll and primary consumers. Time-series data on a monthly time scale e. The potential advantage, however, of using data on primary consumers, despite the coarser temporal resolution, is their closer trophic relationship with top predators, although top predators also feed on mid trophic levels.

For example, Gremillet et al. They found that high production was a good predictor but, surprisingly, that primary consumers were not.

Dynamic Modeling for Marine Conservation (Modeling Dynamic Systems)

Further work on using appropriate surrogates in the absence of data on top-predators is needed. In the Southern Ocean, Lombard et al. There is evidence that many birds and seals forage in the vicinity of these fronts [62] , [63] because of the elevated plankton and fish biomass associated with them [64].

There is also evidence that mesoscale eddies created up current of the islands are important feeding grounds for top predators [63] , [65]. Our approach presented here could easily incorporate fronts that could be measured using readily available SST or Chlorophyll a data. Retention areas are important for fish recruitment when a species is going through passive life history stages where they cannot easily swim [20]. While these species are generally too small to be caught at this time by fisheries, the degree to which they are important feeding grounds for other species is uncertain. To capture the spatial and temporal dynamics of this region, we set conservation targets for different time periods e.

We found that, to represent spatial variability in features through time, it was more effective to explicitly target this variability than to target overall average values, particularly for sardines. There was, a very minor trade-off, with only slightly more area required to capture dynamic features separated into discrete time periods than to represent overall averaged values. We did not set separate targets for different time periods for meso-scale eddies and filaments because they were more dynamic that other features, but rather identified areas where they occur most frequently.

We demonstrated how artificially increasing the boundary lengths of offshore planning units resulted in solutions that were more spatially compact offshore than inshore. Such solutions might be desirable for a number of reasons: a species tend to be more mobile offshore [20] ; b it can be difficult to enforce small offshore protected areas [15] ; and c travelling longer distances past larger protected areas from ports might be prohibitively costly for some inshore fishers.

The effectiveness of area closures for increasing the sustainability of fishing is uncertain, particularly for offshore areas and wide-ranging pelagic species [41]. However, there is some evidence that protected areas might benefit highly mobile species [15] , [67] , [68]. These benefits can be further examined with ecosystem models to test the effects of different configurations of protected areas [2] , [69].

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A major impediment to building spatially explicit ecosystem models has been the lack of data on dispersal parameters and seasonal migration for large pelagic species, but this is rapidly changing with the increasing number of tracking studies [70]. It is recommended that economic costs and benefits of conservation actions be incorporated into decision-support tools such as Marxan see [71] for a review. Costs are typically included as static values, whereas costs in many regions will respond dynamically to conservation decisions. We used a coarse-scale surrogate for opportunity costs and preferentially located protected areas further from ports to reduce costs to fishers.

However, fishing vessels do not necessarily go to the nearest port to offload their fish, so our surrogate could be improved by including more detail on the cost-benefit relationship between the profitability of different ports and different fisheries. We recommend using more comprehensive cost data where possible. Costs of area closures based on catch and effort fisheries data, for example, could be used in further analyses.

Another improvement would be the dynamic coupling between planning software and cost models, an area of current research and development [72]. Developing pelagic protected areas is one approach to conservation management in exploited pelagic regions, and might reduce the in situ threats from fishing.

Their creation, however, is likely to impact fisheries and their management directly and indirectly and the costs and benefits of them assessed against other actions e. For example, protecting an area from fishing can lead to displaced fishing effort, which could require additional management action to realize the regional benefits of protected areas [67] , [73]. There are also indirect challenges associated with the creation of protected areas, in particular relating to the interpretation of biomass via traditional fisheries stock assessments, and stock monitoring [74].

Some have argued that the creation of fisheries closures will make fisheries management harder, because the underlying dynamics of fisher behavior and opportunities for fisheries-dependent data collection will be altered [74]. Fisheries assessment techniques that can overcome this problem will be needed [15] , because spatial management will continue to be an important tool for conservation and fisheries management.

Small pelagic fishes have an important ecological role in the Benguela ecosystem [27] , [33]. We were able to use time series data on anchovies and sardines that were based on a mixture of life history stages. The fishery and ecosystem consequences of protecting only a portion of the distribution of these species are uncertain.

The anchovy fishery is a recruit fishery and operates in the inshore nursery area. It is probably most important to protect spawners to improve recruitment of both species [33]. Spawners are predominantly located on the Agulhas Bank, although their location has been dynamic over time. The Agulhas Bank is also a spawning and nursery area for numerous other species and the area of highest abundance for many endemic species of fishes e. Sparidae , several of which are in decline [33]. Consequences of protecting spawners are uncertain, however, as most eggs have a very low probability of survival arising from transportation off the shelf into unsuitable conditions or because of high predation risk [32] , [33].

Genetic studies have shown that only a few individuals that spawn contribute to reproductive success, most likely because of patchy favourable conditions during spawning [33]. The distribution and movement of different life history stages is not well understood [75]. Additionally, sardines for example, have previously shifted their spawning location and are thought to be flexible in their selection of spawning areas [33] , [76] , [77].

By using time series data on anchovies and sardines we were able to locate the most predictable occurrences over time assuming that past areas will be indicative of future areas. We identified solutions that contained a proportion of total sardine abundance for each previous year. This was to try and represent the inter-year anomalies of anchovy and sardine abundance. Given that the locations of recruits and spawners can change over time, an alternative approach to using fixed locations for protected areas could be the use of a dynamic protected area system [15].

Protected area locations could be determined based on the recruitment and spawner surveys that delineated their distribution in near-real time. For coastal seabirds, we identified areas that would protect their pelagic prey species from purse-seine fishers. We did this by using estimated foraging ranges of breeding seabirds, and variables such as chlorophyll as a proxy for primary production.

Predictably, important areas were foraging zones around islands where the majority of colonies are located [52]. Important areas were particularly concentrated around Cape Point and in the eastern part of the study area. This analysis was based on data describing their feeding distribution during the breeding season and, whilst the distribution of these birds is likely to be different outside of the breeding season, it is during breeding times that they are most vulnerable to competition for food [50].

Although we included the most recent data on the location of breeding colonies, these localities have shifted in the past [78]. For example, three new colonies of African penguins have appeared since the s [50]. If closures were to be implemented using this approach, then planners would have to decide which colonies should be included in the analysis or when to revise recommended closures as new colonies were established or old ones abandoned.

While we account for within-species differences among colonies for African penguins in their foraging distances, there are likely to be other inter-colony differences for other penguins and seabirds [50] , [79]. Ideally, further research is needed to decide on the most appropriate targets and configurations of protected areas and their likely influence on seabird populations e.

For example, the energetic needs of seabirds and relationships between foraging distances and breeding success require further investigation. More information on these issues could support more specific criteria for incorporation into the analysis. Similarly, further studies that predict likely effects of closures on fishers would help to determine what management actions are feasible to protect seabirds outside, as well as inside, protected areas [80].

Applying protected areas can result in complex, uncertain, and in some situations even negative changes in seabird populations. For example, cormorants compete with the critically endangered Leach's Storm Petrel for breeding sites in South Africa [52].

Conservation management might increase the populations of cormorants but consequently reduce the availability of breeding sites for storm petrels. There are also competing and complex interactions with fishers. One hypothesis suggests possible benefits to penguins from purse-seine fishing, which disrupts shoaling defense mechanisms thereby making them more accessible to penguins [53]. Closing foraging areas to all types of fishing could be detrimental to some species.

While many seabirds compete with fishers for prey, some have developed a reliance on fishery discards as a source of food [81]. Walmsley et al. Some bird species probably rely on these discards [50] , [79] , although the relationship is not well understood for some species [49]. It is likely, however, that protected areas could help increase the population viability of some seabirds in this study region.

By-catch from longline fisheries is of major conservation concern in the study region [54]. While many of these species, including those caught as by-catch, are highly mobile, they tend to aggregate in areas of high productivity such as eddies [25] , [83]. Eddy activity is concentrated in the southern part of the study area and along the shelf.

Protecting areas of most consistent eddy activity and those with most by-catch gives the highest probability of protected areas being effective for the species concerned. Because many of these species are wide ranging, their conservation will simultaneously depend on complementary management in other regions.

Grantham et al. Moveable closures could be incorporated into the approach we describe here. For longline fisheries with high bycatch, complementary and alternative types of management might be more appropriate, given the likely impact of closures to fishers. Alternative types of management include gear restrictions and other mitigation mechanisms such as excluder devices and market-based approaches such as compensatory mitigation [54] , [60].

Our intention here was to investigate an approach for identifying pelagic protected areas rather than provide a prescriptive conservation solution for the southern Benguela and Agulhas Bank ecosystems. Accordingly, our analysis was completed without stakeholder consultation that is critical for successful implementation of protected areas [84]. To credibly engage stakeholders and plan pelagic protected areas, we must fill the gaps in our knowledge of how spatial management might protect pelagic biodiversity.

For the southern Benguela and Agulhas Bank ecosystems, more research would be beneficial on how spatial protection influences pelagic breeding seabirds, fisheries catch and bycatch species.

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It would also be beneficial to better understand the dynamics of displaced fishing effort as a result of spatial management and its influence on the effectiveness of spatial conservation management. Broader challenges include accounting for benthic and pelagic coupling, resolving how climate change will alter pelagic processes, and demonstrating the likely effectiveness of spatial management given the large movements of many pelagic species [15]. Our knowledge of how to best do pelagic conservation planning is in its infancy, however, some of these lessons can only be learned through the establishment of pelagic protected areas that can be used to advance our understanding of the role they have in the future sustainable management of the ocean.

Despite uncertainty, planning should always proceed in the context of uncertainty, and that the burden of proof should not rest solely on those promoting conservation. The resolution of planning units was chosen due to match the scale of the input data. The shelf break was identified as the continental margin from maps produced by the South African Council for GeoScience Fig 2a. We assume the area of influence of these structures to be approximately 10 km each side of the shelf break and a radius of 10 km around each seamount.

We identified coastal upwelling areas using chlorophyll a concentrations measured from the SeaWiFS satellite for the period 1 January to 31 December , composited at a temporal resolution of 8 days and spatial resolution of 0. Clouds can inhibit visible radiation, leading to lower recorded chlorophyll values or missing pixels in these images.

We therefore developed monthly composite images based on the highest pixel value during a monthly period, and repeated this for each of the 72 months. Upwelling and downwelling features included offshore eddies and filaments. Upwelling features are often included in pelagic conservation planning primarily due to them being a good indicator for top predators. We also included downwelling features due to several reasons. These areas are likely to contain high biodiversity in the warmer and more stable areas outside upwelling areas [88] , they are likely to contain some unique biodiversity compared to upwelling features and surrounding areas, and many downwelling features often have a deep chlorophyll maximum layer at the base of the thermocline, below the optical depth of satellites that can have a thin layer with relatively high chlorophyll [89].

We identified these using data on sea surface height for the same time period 8 days as the analysis of the chlorophyll data.

This product provides sea level anomalies relative to a 7-year mean from through Data provided a temporal resolution of 7 days and a spatial resolution of 0. Upwelling negative anomaly and downwelling positive anomaly features were identified separately in each image [66]. For upwelling and downwelling features, strength and persistence are key determinants of increased primary productivity and thus aggregations of biota [91]. We then calculated the proportion of time a pixel had an upwelling or downwelling feature across all images. Retention areas are important for fish recruitment and production of food for many life stages [20] , [33].

We used results from a Lagrangian particle-tracking model that simulated oceanographic conditions to predict areas of retention described in [92]. The model was seeded every two weeks from to with , particles released across the south Benguela region. Retention was defined as the proportion of total particles released that remained within 50 km from where they were released 14 days previously.

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