In this paper, we review the need for, use of, and demands on climate modeling to support so-called 'robust' decision frameworks, in the context of improving the contribution of climate information to effective decision making. Such frameworks seek to identify policy vulnerabilities under deep uncertainty about the future and propose strategies for minimizing regret in the event of broken assumptions. We argue that currently there is a severe underutilization of climate models as tools for supporting decision making, and that this is slowing progress in developing informed adaptation and mitigation responses to climate change. This underutilization stems from two root causes, about which there is a growing body of literature: one, a widespread, but limiting, conception that the usefulness of climate models in planning begins and ends with regional-scale predictions of multidecadal climate change; two, the general failure so far to incorporate learning from the decision and social sciences into climate-related decision support in key sectors. We further argue that addressing these root causes will require expanding the conception of climate models; not simply as prediction machines within 'predict-then-act' decision frameworks, but as scenario generators, sources of insight into complex system behavior, and aids to critical thinking within robust decision frameworks. Such a shift, however, would have implications for how users perceive and use information from climate models and, ultimately, the types of information they will demand from these models-and thus for the types of simulations and numerical experiments that will have the most value for informing decision making.

Use of coastal armoring is expected to escalate in response to the combination of expanding human populations, beach erosion, and sea level rise along the coasts. To provide a conceptual framework, we developed hypotheses concerning the ecological effects of beach habitat loss associated with coastal armoring. As beaches narrow in response to armoring, dry upper intertidal zones should be lost disproportionately, reducing the habitat types available and the diversity and abundance of macroinvertebrates. Predators, such as shorebirds, could respond to a combination of (i) habitat loss; (ii) decreased accessibility at high tides; and (iii) reduced prey availability on armored beaches. To examine those predictions, zone widths and the distribution and abundance of macroinvertebrates and birds were compared on paired armored and unarmored segments of narrow bluff‐backed beaches in southern California. Our results supported the predictions and revealed some unexpected effects of armoring on birds. Dry upper beach zones were lacking and mid‐beach zones were narrower (>2 times) year‐round on armored segments compared to adjacent unarmored segments. The abundance, biomass and size of upper intertidal macroinvertebrates were also significantly lower on armored segments. Shorebirds, most of which were foraging, responded predictably with significantly lower species richness (two times) and abundance (>3 times) on armored segments. Gulls and other birds (including seabirds), which use beaches primarily for roosting, were also significantly lower in abundance (>4 times and >7 times respectively) on armored segments, an important unexpected result. Given the accelerating pressures on sandy beaches from coastal development, erosion and rising sea levels, our results indicate that further investigation of ecological responses to coastal armoring is needed for the management and conservation of these ecosystems.

Sea-level rise will increase the risks associated with coastal hazards of flooding and erosion. Along the active tectonic margin of California, the diversity in coastal morphology complicates the evaluation of future coastal hazards. In this study, we estimate future coastal hazards based on two scenarios generated from a downscaled regional global climate model. We apply new methodologies using statewide data sets to evaluate potential erosion hazards. The erosion method relates shoreline change rates to coastal geology then applies changes in total water levels in exceedance of the toe elevation to predict future erosion hazards. Results predict 214 km 2 of land eroded by 2100 under a 1.4 m sea level rise scenario. Average erosion distances range from 170 m along dune backed shorelines, to a maximum of 600 m. For cliff backed shorelines, potential erosion is projected to average 33 m, with a maximum potential erosion distance of up to 400 m. Erosion along the seacliff backed shorelines was highest in the geologic units of Cretaceous marine (K) and Franciscan complex (KJf). 100-year future flood elevations were estimated using two different methods, a base flood elevation approach extrapolated from existing FEMA flood maps, and a total water level approach based on calculations of astronomical tides and wave run-up. Comparison between the flooding methods shows an average difference of about 1.2 m with the total water level method being routinely lower with wider variability alongshore. While the level of risk (actual amount of future hazards) may vary from projected, this methodology provides coastal managers with a planning tool and actionable information to guide adaptation strategies.

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