Global coastal wetland change under sea-level rise and related stresses: The DIVA Wetland Change Model

The Dynamic Interactive Vulnerability Assessment Wetland Change Model (DIVA_WCM) comprises a dataset of contemporary global coastal wetland stocks (estimated at 756 × 10^3 km^2 (in 2011)), mapped to a one-dimensional global database, and a model of the macro-scale controls on wetland response to sea-level rise. Three key drivers of wetland response to sea-level rise are considered: 1) rate of sea-level rise relative to tidal range; 2) lateral accommodation space; and 3) sediment supply. The model is tuned by expert knowledge, parameterised with quantitative data where possible, and validated against mapping associated with two large-scale mangrove and saltmarsh vulnerability studies. It is applied across 12,148 coastal segments (mean length 85 km) to the year 2100. The model provides better-informed macro-scale projections of likely patterns of future coastal wetland losses across a range of sea-level rise scenarios and varying assumptions about the construction of coastal dikes to prevent sea flooding (as dikes limit lateral accommodation space and cause coastal squeeze). With 50 cm of sea-level rise by 2100, the model predicts a loss of 46–59% of global coastal wetland stocks. A global coastal wetland loss of 78% is estimated under high sea-level rise (110 cm by 2100) accompanied by maximum dike construction. The primary driver for high vulnerability of coastal wetlands to sea-level rise is coastal squeeze, a consequence of long-term coastal protection strategies. Under low sea-level rise (29 cm by 2100) losses do not exceed ca. 50% of the total stock, even for the same adverse dike construction assumptions. The model results confirm that the widespread paradigm that wetlands subject to a micro-tidal regime are likely to be more vulnerable to loss than macro-tidal environments. Countering these potential losses will require both climate mitigation (a global response) to minimise sea-level rise and maximisation of accommodation space and sediment supply (a regional response) on low-lying coasts.The authors gratefully acknowledge funding from the European Union under contract number EVK2-2000-22024. They thank all their partners in the DINAS-COAST project Dynamic and Interactive Assessment of National, Regional and Global Vulnerability of Coastal Zones to Climate Change and Sea-level rise. We are grateful to staff at UNEP-WCMC for generous access to evolving databases on global coastal wetland extent: Jon Hutton, Hannah Thomas, Jan-Willem van Bochove, Simon Blyth and Chris McOwen. Current wetland databases held at WCMC build upon the pioneering efforts of Mark Spalding and Carmen Lacambra.This is the author accepted manuscript. The final version is available from Elsevier via http://dx.doi.org/10.1016/j.gloplacha.2015.12.01

Managing future risks and building socio-ecological resilience

The Mediterranean Basin is experiencing major changes in environmental conditions, which can introduce new challenges to the resilience of its natural and human systems. This situation is combined with rapid and spatially diverse socio-economic development in the region, mainly in terms of demographic trends and settlement patterns, thus leading to higher exposure to environmental hazards. Furthermore, new risks are expected to emerge from interactions between drivers and impacts across sectors, thus increasing the vulnerability of natural systems and human populations

Systematic sensitivity analysis of the full economic impacts of sea level rise

The potential impacts of sea level rise (SLR) due to climate change have been widely studied in the literature. However, the uncertainty and robustness of these estimates has seldom been explored. Here we assess the model input uncertainty regarding the wide effects of SLR on marine navigation from a global economic perspective. We systematically assess the robustness of computable general equilibrium (CGE) estimates to model’s inputs uncertainty. Monte Carlo (MC) and Gaussian quadrature (GQ) methods are used for conducting a Systematic sensitivity analysis (SSA). This design allows to both explore the sensitivity of the CGE model and to compare the MC and GQ methods. Results show that, regardless whether triangular or piecewise linear Probability distributions are used, the welfare losses are higher in the MC SSA than in the original deterministic simulation. This indicates that the CGE economic literature has potentially underestimated the total economic effects of SLR, thus stressing the necessity of SSA when simulating the general equilibrium effects of SLR. The uncertainty decomposition shows that land losses have a smaller effect compared to capital and seaport productivity losses. Capital losses seem to affect the developed regions GDP more than the productivity losses do. Moreover, we show the uncertainty decomposition of the MC results and discuss the convergence of the MC results for a decomposed version of the CGE model. This paper aims to provide standardised guidelines for stochastic simulation in the context of CGE modelling that could be useful for researchers in similar settings

Comment on ‘The Global Impacts of Extreme Sea-Level Rise: A Comprehensive Economic Assessment’

Pycroft et al. (Environ Resour Econ 1–29, 2015) used incorrect and outdated data to study the economic impact of sea level rise. Theymisinterpret some of their input data, and fail to exploit the strengths of their computable general equilibrium model and previously developed methods to study impacts and adaptation

Future response of global coastal wetlands to sea-level rise.

The response of coastal wetlands to sea-level rise during the twenty-first century remains uncertain. Global-scale projections suggest that between 20 and 90 per cent (for low and high sea-level rise scenarios, respectively) of the present-day coastal wetland area will be lost, which will in turn result in the loss of biodiversity and highly valued ecosystem services1-3. These projections do not necessarily take into account all essential geomorphological4-7 and socio-economic system feedbacks8. Here we present an integrated global modelling approach that considers both the ability of coastal wetlands to build up vertically by sediment accretion, and the accommodation space, namely, the vertical and lateral space available for fine sediments to accumulate and be colonized by wetland vegetation. We use this approach to assess global-scale changes in coastal wetland area in response to global sea-level rise and anthropogenic coastal occupation during the twenty-first century. On the basis of our simulations, we find that, globally, rather than losses, wetland gains of up to 60 per cent of the current area are possible, if more than 37 per cent (our upper estimate for current accommodation space) of coastal wetlands have sufficient accommodation space, and sediment supply remains at present levels. In contrast to previous studies1-3, we project that until 2100, the loss of global coastal wetland area will range between 0 and 30 per cent, assuming no further accommodation space in addition to current levels. Our simulations suggest that the resilience of global wetlands is primarily driven by the availability of accommodation space, which is strongly influenced by the building of anthropogenic infrastructure in the coastal zone and such infrastructure is expected to change over the twenty-first century. Rather than being an inevitable consequence of global sea-level rise, our findings indicate that large-scale loss of coastal wetlands might be avoidable, if sufficient additional accommodation space can be created through careful nature-based adaptation solutions to coastal management.Personal research fellowship of Mark Schuerch (Project Number 272052902) and by the Cambridge Coastal Research Unit (Visiting Scholar Programme). Furthermore, this work has partly been supported by the EU research project RISES-AM- (FP7-ENV-693396)

Understanding extreme sea levels for broad-scale coastal impact and adaptation analysis

One of the main consequences of mean sea level rise (SLR) on human settlements is an increase in flood risk due to an increase in the intensity and frequency of extreme sea levels (ESL). While substantial research efforts are directed towards quantifying projections and uncertainties of future global and regional SLR, corresponding uncertainties in contemporary ESL have not been assessed and projections are limited. Here we quantify, for the first time at global scale, the uncertainties in present-day ESL estimates, which have by default been ignored in broad-scale sea-level rise impact assessments to date. ESL uncertainties exceed those from global SLR projections and, assuming that we meet the Paris agreement goals, the projected SLR itself by the end of the century in many regions. Both uncertainties in SLR projections and ESL estimates need to be understood and combined to fully assess potential impacts and adaptation needs

Global-scale climate impact functions: the relationship between climate forcing and impact

Although there is a strong policy interest in the impacts of climate change corresponding to different degrees of climate change, there is so far little consistent empirical evidence of the relationship between climate forcing and impact. This is because the vast majority of impact assessments use emissions-based scenarios with associated socio-economic assumptions, and it is not feasible to infer impacts at other temperature changes by interpolation. This paper presents an assessment of the global-scale impacts of climate change in 2050 corresponding to defined increases in global mean temperature, using spatially-explicit impacts models representing impacts in the water resources, river flooding, coastal, agriculture, ecosystem and built environment sectors. Pattern-scaling is used to construct climate scenarios associated with specific changes in global mean surface temperature, and a relationship between temperature and sea level used to construct sea level rise scenarios. Climate scenarios are constructed from 21 climate models to give an indication of the uncertainty between forcing and response. The analysis shows that there is considerable uncertainty in the impacts associated with a given increase in global mean temperature, due largely to uncertainty in the projected regional change in precipitation. This has important policy implications. There is evidence for some sectors of a non-linear relationship between global mean temperature change and impact, due to the changing relative importance of temperature and precipitation change. In the socio-economic sectors considered here, the relationships are reasonably consistent between socio-economic scenarios if impacts are expressed in proportional terms, but there can be large differences in absolute terms. There are a number of caveats with the approach, including the use of pattern-scaling to construct scenarios, the use of one impacts model per sector, and the sensitivity of the shape of the relationships between forcing and response to the definition of the impact indicator

Combining qualitative and quantitative understanding for exploring cross-sectoral climate change impacts, adaptation and vulnerability in Europe

Climate change will affect all sectors of society and the environment at all scales, ranging from the continental to the national and local. Decision-makers and other interested citizens need to be able to access reliable science-based information to help them respond to the risks of climate change impacts and assess opportunities for adaptation. Participatory integrated assessment (IA) tools combine knowledge from diverse scientific disciplines, take account of the value and importance of stakeholder ‘lay insight’ and facilitate a two-way iterative process of exploration of ‘what if’s’ to enable decision-makers to test ideas and improve their understanding of the complex issues surrounding adaptation to climate change. This paper describes the conceptual design of a participatory IA tool, the CLIMSAVE IA Platform, based on a professionally facilitated stakeholder engagement process. The CLIMSAVE (climate change integrated methodology for cross-sectoral adaptation and vulnerability in Europe) Platform is a user-friendly, interactive web-based tool that allows stakeholders to assess climate change impacts and vulnerabilities for a range of sectors, including agriculture, forests, biodiversity, coasts, water resources and urban development. The linking of models for the different sectors enables stakeholders to see how their interactions could affect European landscape change. The relationship between choice, uncertainty and constraints is a key cross-cutting theme in the conduct of past participatory IA. Integrating scenario development processes with an interactive modelling platform is shown to allow the exploration of future uncertainty as a structural feature of such complex problems, encouraging stakeholders to explore adaptation choices within real-world constraints of future resource availability and environmental and institutional capacities, rather than seeking the ‘right’ answers