Aim Global sea-level rise (SLR) could be as much as 1.8 metres by 2100, which will impact coastal wetland communities and threatened species. We evaluated the likely outcomes of SLR for wetland communities using a process-based simulation model and coupled this with a metapopulation model for a threatened native rodent (Xeromys myoides). Furthermore, we tested the amplified impacts of SLR, urban growth and introduced predators on X. myoides persistence.Location South-east Queensland, Australia.Methods We adapted the Sea Level Affects Marshes Model to subtropical Australia. We used LiDAR elevation data, field data to parameterize surface accretion and shallow subsidence, and local knowledge to configure wetland transitions. SLR was simulated based on the IPCC B1 and A1FI scenarios, as well as the maximal limit of 1.8 m by 2100. Further, we coupled our demographic model to projected shifts in wetland habitat, and estimates of future wetland loss to urban expansion and feral cat (Felis catus) predation.Results Our models project a general decline in wetland communities under SLR, with a noted exception of mangroves. Under the A1FI scenario, SLR allows mangroves to migrate inland, with urban development acting as an obstruction in some areas. Mangrove expansion provides an unexpected benefit for dependent X. myoides populations, although the inclusion of predation and habitat loss due to urban development still suggests extirpation in c. 50 years.Main conclusions Through this case study, we illustrate the usefulness of process-based SLR models in understanding outcomes for wetland communities and dependent species. Our models will underscore decision-making in a dynamic system, with global applications for urban planning, conservation prioritization and wildlife management.

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.

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A multi-scaled model for biodiversity conservation in forests was introduced in Sweden 30 years ago, which makes it a pioneer example of an integrated ecosystem approach. Trees are set aside for biodiversity purposes at multiple scale levels varying from individual trees to areas of thousands of hectares, with landowner responsibility at the lowest level and with increasing state involvement at higher levels. Ecological theory supports the multi-scaled approach, and retention efforts at every harvest occasion stimulate landowners' interest in conservation. We argue that the model has large advantages but that in a future with intensified forestry and global warming, development based on more progressive thinking is necessary to maintain and increase biodiversity. Suggestions for the future include joint planning for several forest owners, consideration of cost-effectiveness, accepting opportunistic work models, adjusting retention levels to stand and landscape composition, introduction of temporary reserves, creation of ''receiver habitats'' for species escaping climate change, and protection of young forests.

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Including both economic costs and biological benefits of sites in systematic reserve selection greatly increases cost-efficiency. Nevertheless, limited funding generally forces conservation planners to choose which data to focus the most resources on; therefore, the relative importance of different types of data must be carefully assessed. We investigated the relative importance of including information about costs and benefits for 3 different commonly used conservation goals: 2 in which biological benefits were measured per site (species number and conservation value scores) and 1 in which benefits were measured on the basis of site complementarity (total species number in the reserve network). For each goal, we used site-selection models with data on benefits only, costs only, and benefits and costs together, and we compared the efficiency of each model. Costs were more important to include than benefits for the goals in which benefits were measured per site. By contrast, for the complementarity-based goal, benefits were more important to include. To understand this pattern, we compared the variability in benefits and in costs for each goal. By comparing the best and the worst possible selection of sites with regard to costs alone and benefits alone for each conservation goal, we introduced a simple and consistent variability measure that is applicable to all kinds of reserve-selection situations. In our study, benefit variability depended strongly on how the conservation goal was formulated and was largest for the complementarity-based conservation goal. We argue that from a cost-efficiency point of view, most resources should be spent on collecting the most variable type of data for the conservation goal at hand.

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