Effect of Planning for Connectivity on Linear Reserve Networks

Although the concept of connectivity is decades old, it remains poorly understood and defined, and some argue that habitat quality and area should take precedence in conservation planning instead. However, fragmented landscapes are often characterized by linear features that are inherently connected, such as streams and hedgerows. For these, both representation and connectivity targets may be met with little effect on the cost, area, or quality of the reserve network. We assessed how connectivity approaches affect planning outcomes for linear habitat networks by using the stock‐route network of Australia as a case study. With the objective of representing vegetation communities across the network at a minimal cost, we ran scenarios with a range of representation targets (10%, 30%, 50%, and 70%) and used 3 approaches to account for connectivity (boundary length modifier, Euclidean distance, and landscape‐value [LV]). We found that decisions regarding the target and connectivity approach used affected the spatial allocation of reserve systems. At targets ≥50%, networks designed with the Euclidean distance and LV approaches consisted of a greater number of small reserves. Hence, by maximizing both representation and connectivity, these networks compromised on larger contiguous areas. However, targets this high are rarely used in real‐world conservation planning. Approaches for incorporating connectivity into the planning of linear reserve networks that account for both the spatial arrangement of reserves and the characteristics of the intervening matrix highlight important sections that link the landscape and that may otherwise be overlooked. El Efecto de la Planeación para la Conectividad en Redes de Reservas Lineales     

Efficiency and Concordance of Alternative Methods for Minimizing Opportunity Costs in Conservation Planning

Abstract:  Scarce resources and competing land-use goals necessitate efficient biodiversity conservation. Combining multicriteria analysis with conservation decision-support tools improves efficiency of conservation planning by maximizing outcomes for biodiversity while minimizing opportunity costs to society. An opportunity cost is the benefit that could have been received by taking an alternative course of action (i.e., costs to society of protecting an area for biodiversity rather than developing it for some other use). Although different ways of integrating multiple opportunity costs into conservation planning have been suggested, there have been no tests as to which method is most efficient. We compared the relative efficiency of 3 such procedures ( Faith & Walker [1996] , Sarkar et al. [2004] , and a procedure of our own design) in a systematic conservation-planning framework for the Milne Bay Province of Papua New Guinea. We devised 14 opportunity costs and assigned these to 3 scenarios representing different conservation planning concerns: food security, macro-economic development, and biodiversity persistence. For each scenario, we compared the efficiency of the 3 methods in terms of amount of biodiversity protected relative to total expenditure for each opportunity cost. All 3 methods captured similar amounts of biodiversity, but differed in total cost. Our method had the least overall cost and was therefore most efficient. Nevertheless, there was a high correlation and geographical concordance among all 3 methods, indicating a high degree of spatial overlap. This suggests that choosing an appropriate approach may often depend on contextual factors related to the design of the planning question, rather than efficiency alone.     

Spatial,socio‐economic,and ecological implications of incorporating minimum size constraints in marine protected area network design

Marine protected areas (MPAs) are the cornerstone of most marine conservation strategies, but the effectiveness of each one partly depends on its size and distance to other MPAs in a network. Despite this, current recommendations on ideal MPA size and spacing vary widely, and data are lacking on how these constraints might influence the overall spatial characteristics, socio‐economic impacts, and connectivity of the resultant MPA networks. To address this problem, we tested the impact of applying different MPA size constraints in English waters. We used the Marxan spatial prioritization software to identify a network of MPAs that met conservation feature targets, whilst minimizing impacts on fisheries; modified the Marxan outputs with the MinPatch software to ensure each MPA met a minimum size; and used existing data on the dispersal distances of a range of species found in English waters to investigate the likely impacts of such spatial constraints on the region's biodiversity. Increasing MPA size had little effect on total network area or the location of priority areas, but as MPA size increased, fishing opportunity cost to stakeholders increased. In addition, as MPA size increased, the number of closely connected sets of MPAs in networks and the average distance between neighboring MPAs decreased, which consequently increased the proportion of the planning region that was isolated from all MPAs. These results suggest networks containing large MPAs would be more viable for the majority of the region's species that have small dispersal distances, but dispersal between MPA sets and spill‐over of individuals into unprotected areas would be reduced. These findings highlight the importance of testing the impact of applying different MPA size constraints because there are clear trade‐offs that result from the interaction of size, number, and distribution of MPAs in a network.     

Selecting cost‐effective areas for restoration of ecosystem services

Selection of areas for restoration should be based on cost‐effectiveness analysis to attain the maximum benefit with a limited budget and overcome the traditional ad hoc allocation of funds for restoration projects. Restoration projects need to be planned on the basis of ecological knowledge and economic and social constraints. We devised a novel approach for selecting cost‐effective areas for restoration on the basis of biodiversity and potential provision of 3 ecosystem services: carbon storage, water depuration, and coastal protection. We used Marxan, a spatial prioritization tool, to balance the provision of ecosystem services against the cost of restoration. We tested this approach in a mangrove ecosystem in the Caribbean. Our approach efficiently selected restoration areas that at low cost were compatible with biodiversity targets and that maximized the provision of one or more ecosystem services. Choosing areas for restoration of mangroves on the basis carbon storage potential, largely guaranteed the restoration of biodiversity and other ecosystem services. Selección de Áreas Rentables para la Restauración de Servicios Ambientales     

Evaluating approaches for scaling-up community-based marine-protected areas into socially equitable and ecologically representative networks

Marine-protected areas (MPAs) are vital to marine conservation, but their coverage and distribution is insufficient to address declines in global biodiversity and fisheries. In response, many countries have committed through the Aichi Target 11 of the Convention on Biological Diversity to conserve 10% of the marine environment through ecologically representative and equitably managed MPAs by 2020. The rush to fulfill this commitment has raised concerns on how increasing MPA coverage will affect other elements of Target 11, including representation and equity. We examined a Philippines case study to assess and compare 3 MPA planning approaches for biodiversity representation and equitable distribution of costs to small-scale fishers. In the opportunistic approach, MPAs were identified and supported by coastal communities. The donor-assisted approach used local knowledge to select MPAs through a national-scale and donor-assisted conservation project. The systematic conservation planning approach identified MPA locations with the spatial prioritization software Marxan with Zones to achieve biodiversity objectives with minimal costs to fishers. We collected spatial data on biodiversity and fisheries features and performed a gap analysis to evaluate MPAs derived from different approaches. We assessed representation based on the proportion of biodiversity features conserved in MPAs and distribution equity by the distribution of opportunity costs (fishing areas lost in MPAs) among fisher stakeholder groups. The opportunistic approach did not ineffectively represent biodiversity and resulted in inequitable costs to fishers. The donor-assisted approach affected fishers disproportionately but provided near-optimal regional representation. Only the systematic approach achieved all representation targets with minimal and equitable costs to fishers. Our results demonstrate the utility of systematic conservation planning to address key elements of Target 11 and highlight opportunities (e.g., integration of local and scientific knowledge can address representation and equity concerns) and pitfalls (e.g., insufficient stakeholder considerations can exacerbate social inequalities) for planning MPAs in similar contexts.     

Evaluating complementary networks of restoration plantings for landscape‐scale occurrence of temporally dynamic species

Multibillion dollar investments in land restoration make it critical that conservation goals are achieved cost‐effectively. Approaches developed for systematic conservation planning offer opportunities to evaluate landscape‐scale, temporally dynamic biodiversity outcomes from restoration and improve on traditional approaches that focus on the most species‐rich plantings. We investigated whether it is possible to apply a complementarity‐based approach to evaluate the extent to which an existing network of restoration plantings meets representation targets. Using a case study of woodland birds of conservation concern in southeastern Australia, we compared complementarity‐based selections of plantings based on temporally dynamic species occurrences with selections based on static species occurrences and selections based on ranking plantings by species richness. The dynamic complementarity approach, which incorporated species occurrences over 5 years, resulted in higher species occurrences and proportion of targets met compared with the static complementarity approach, in which species occurrences were taken at a single point in time. For equivalent cost, the dynamic complementarity approach also always resulted in higher average minimum percent occurrence of species maintained through time and a higher proportion of the bird community meeting representation targets compared with the species‐richness approach. Plantings selected under the complementarity approaches represented the full range of planting attributes, whereas those selected under the species‐richness approach were larger in size. Our results suggest that future restoration policy should not attempt to achieve all conservation goals within individual plantings, but should instead capitalize on restoration opportunities as they arise to achieve collective value of multiple plantings across the landscape. Networks of restoration plantings with complementary attributes of age, size, vegetation structure, and landscape context lead to considerably better outcomes than conventional restoration objectives of site‐scale species richness and are crucial for allocating restoration investment wisely to reach desired conservation goals.     

Addressing transboundary conservation challenges through marine spatial prioritization

The Adriatic and Ionian Region is an important area for both strategic maritime development and biodiversity conservation in the European Union (EU). However, given that both EU and non‐EU countries border the sea, multiple legal and regulatory frameworks operate at different scales, which can hinder the coordinated long‐term sustainable development of the region. Transboundary marine spatial planning can help overcome these challenges by building consensus on planning objectives and making the trade‐offs between biodiversity conservation and its influence on economically important sectors more explicit. We address this challenge by developing and testing 4 spatial prioritization strategies with the decision‐support tool Marxan, which meets targets for biodiversity conservation while minimizing impacts to users. We evaluated these strategies in terms of how priority areas shift under different scales of target setting (e.g., regional vs. country level). We also examined the trade‐off between cost‐efficiency and how equally solutions represent countries and maritime industries (n = 14) operating in the region with the protection‐equality metric. We found negligible differences in where priority conservation areas were located when we set targets for biodiversity at the regional versus country scale. Conversely, the prospective impacts on industries, when considered as costs to be minimized, were highly divergent across scenarios and biased the placement of protection toward industries located in isolation or where there were few other industries. We recommend underpinning future marine spatial planning efforts in the region through identification of areas of national significance, transboundary areas requiring cooperation between countries, and areas where impacts on maritime industries require careful consideration of the trade‐off between biodiversity conservation and socioeconomic objectives.     

Comparing spatial conservation prioritization methods with site- versus spatial dependency-based connectivity

Larval dispersal is an important component of marine reserve networks. Two conceptually different approaches to incorporate dispersal connectivity into spatial planning of these networks exist, and it is an open question as to when either is most appropriate. Candidate reserve sites can be selected individually based on local properties of connectivity or on a spatial dependency-based approach of selecting clusters of strongly connected habitat patches. The first acts on individual sites, whereas the second acts on linked pairs of sites. We used a combination of larval dispersal simulations representing different seascapes and case studies of biophysical larval dispersal models in the Coral Triangle region and the province of Southeast Sulawesi, Indonesia, to compare the performance of these 2 methods in the spatial planning software Marxan. We explored the reserve design performance implications of different dispersal distances and patterns based on the equilibrium settlement of larvae in protected and unprotected areas. We further assessed different assumptions about metapopulation contributions from unprotected areas, including the case of 100% depletion and more moderate scenarios. The spatial dependency method was suitable when dispersal was limited, a high proportion of the area of interest was substantially degraded, or the target amount of habitat protected was low. Conversely, when subpopulations were well connected, the 100% depletion was relaxed, or more habitat was protected, protecting individual sites with high scores in metrics of connectivity was a better strategy. Spatial dependency methods generally produced more spatially clustered solutions with more benefits inside than outside reserves compared with site-based methods. Therefore, spatial dependency methods potentially provide better results for ecological persistence objectives over enhancing fisheries objectives, and vice versa. Different spatial prioritization methods of using connectivity are appropriate for different contexts, depending on dispersal characteristics, unprotected area contributions, habitat protection targets, and specific management objectives. Comparación entre los métodos de priorización de la conservación espacial con sitio y la conectividad espacial basada en la dependencia     

Striking a Balance between Biodiversity Conservation and Socioeconomic Viability in the Design of Marine Protected Areas

Abstract: The establishment of marine protected areas is often viewed as a conflict between conservation and fishing. We considered consumptive and nonconsumptive interests of multiple stakeholders (i.e., fishers, scuba divers, conservationists, managers, scientists) in the systematic design of a network of marine protected areas along California's central coast in the context of the Marine Life Protection Act Initiative. With advice from managers, administrators, and scientists, a representative group of stakeholders defined biodiversity conservation and socioeconomic goals that accommodated social needs and conserved marine ecosystems, consistent with legal requirements. To satisfy biodiversity goals, we targeted 11 marine habitats across 5 depth zones, areas of high species diversity, and areas containing species of special status. We minimized adverse socioeconomic impacts by minimizing negative effects on fishers. We included fine‐scale fishing data from the recreational and commercial fishing sectors across 24 fisheries. Protected areas designed with consideration of commercial and recreational fisheries reduced potential impact to the fisheries approximately 21% more than protected areas designed without consideration of fishing effort and resulted in a small increase in the total area protected (approximately 3.4%). We incorporated confidential fishing data without revealing the identity of specific fisheries or individual fishing grounds. We sited a portion of the protected areas near land parks, marine laboratories, and scientific monitoring sites to address nonconsumptive socioeconomic goals. Our results show that a stakeholder‐driven design process can use systematic conservation‐planning methods to successfully produce options for network design that satisfy multiple conservation and socioeconomic objectives. Marine protected areas that incorporate multiple stakeholder interests without compromising biodiversity conservation goals are more likely to protect marine ecosystems.     

Decision-support tools for dynamic management

Spatial management is a valuable strategy to advance regional goals for nature conservation, economic development, and human health. One challenge of spatial management is navigating the prioritization of multiple features. This challenge becomes more pronounced in dynamic management scenarios, in which boundaries are flexible in space and time in response to changing biological, environmental, or socioeconomic conditions. To implement dynamic management, decision-support tools are needed to guide spatial prioritization as feature distributions shift under changing conditions. Marxan is a widely applied decision-support tool designed for static management scenarios, but its utility in dynamic management has not been evaluated. EcoCast is a new decision-support tool developed explicitly for the dynamic management of multiple features, but it lacks some of Marxan's functionality. We used a hindcast analysis to compare the capacity of these 2 tools to prioritize 4 marine species in a dynamic management scenario for fisheries sustainability. We successfully configured Marxan to operate dynamically on a daily time scale to resemble EcoCast. The relationship between EcoCast solutions and the underlying species distributions was more linear and less noisy, whereas Marxan solutions had more contrast between waters that were good and poor to fish. Neither decision-support tool clearly outperformed the other; the appropriateness of each depends on management purpose, resource-manager preference, and technological capacity of tool developers. Article impact statement: Marxan can function as a decision-support tool for dynamic management scenarios in which boundaries are flexible in space and time.