Managing for change: wetland transitions under sea-level rise and outcomes for threatened species

Abstract

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.

A global standard for monitoring coastal wetland vulnerability to accelerated sea-level rise

“…This highlights the need for site-specific data that accurately represent local processes to initialize, calibrate and validate site-specific wetland models, and to evaluate the outcome of different SLR scenarios 35,36 . …”

“…RSET data have also contributed to more applied research assessing the impacts of management practices on site-specific vulnerability to SLR, such as prescribed burning 49 , sedimentation from point-source coastal management interventions 50 , water diversion 51 , fence construction to enhance sediment deposition 52 and thin-layer deposition of dredged sediment 53 . Most recently, surface elevation change data collected by RSETs have been incorporated into estimates of carbon sequestration 54 , and studies have begun to incorporate RSET data with spatial data (such as LiDAR and GIS) into spatial modelling platforms 35,36,55 to evaluate specific wetland vulnerability to SLR.…”

“…These short-term measurements of process rates (for example, sediment accretion, root expansion, belowground primary production and decomposition, autocompaction and soil shrink-swell) can be used to calibrate, parameterize and validate locally relevant models 36 to make longer-term predictions of coastal wetland response to changes in the rate of SLR. Thus, although RSET data provide direct, shortterm indications of marsh resilience, modelling allows prediction at the appropriate timescales for management action 35,42,43,58 . Second, to calculate the local difference between wetland elevation change and sea-level change so that absolute site vulnerability can be compared across sites over a broad geographic area (for example, a continent), RSETs need to be levelled (referenced) into a common regional vertical datum 59 .…”

Bringing it all together: researcher dialogue to improve synthesis in regional climate adaptation in South-East Queensland, Australia

“…As sea level rises, coastal wetlands have the ability to colonise new areas on progressively higher ground (see Shoo et al 2012). To support this adaptation, however, the likely paths of advancing wetlands will need to be clear of hard (urban) infrastructure and other obstacles (Traill et al 2011). …”

Building adaptive capacity in South East Queensland, Australia

“…Traill et al 2011;Burley et al 2012;Shoo et al 2012). Of particular note is the increased vulnerability of disadvantaged groups in terms of their residential dwellings and their location.…”