In a rapidly changing climate, conservation practitioners could better use geodiversity in a broad range of conservation decisions. We explored selected avenues through which this integration might improve decision making and organized them within the adaptive management cycle of assessment, planning, implementation, and monitoring. Geodiversity is seldom referenced in predominant environmental law and policy. With most natural resource agencies mandated to conserve certain categories of species, agency personnel are challenged to find ways to practically implement new directives aimed at coping with climate change while retaining their species-centered mandate. Ecoregions and ecological classifications provide clear mechanisms to consider geodiversity in plans or decisions, the inclusion of which will help foster the resilience of conservation to climate change. Methods for biodiversity assessment, such as gap analysis, climate change vulnerability analysis, and ecological process modeling, can readily accommodate inclusion of a geophysical component. We adapted others' approaches for characterizing landscapes along a continuum of climate change vulnerability for the biota they support from resistant, to resilient, to susceptible, and to sensitive and then summarized options for integrating geodiversity into planning in each landscape type. In landscapes that are relatively resistant to climate change, options exist to fully represent geodiversity while ensuring that dynamic ecological processes can change over time. In more susceptible landscapes, strategies aiming to maintain or restore ecosystem resilience and connectivity are paramount. Implementing actions on the ground requires understanding of geophysical constraints on species and an increasingly nimble approach to establishing management and restoration goals. Because decisions that are implemented today will be revisited and amended into the future, increasingly sophisticated forms of monitoring and adaptation will be required to ensure that conservation efforts fully consider the value of geodiversity for supporting biodiversity in the face of a changing climate.

The resilience of socio-ecological systems to sea level rise, storms and flooding can be enhanced when coastal habitats are used as natural infrastructure. Grey infrastructure has long been used for coastal flood protection but can lead to unintended negative impacts. Natural infrastructure often provides similar services as well as added benefits that support short-and long-term biological, cultural, social, and economic goals. While natural infrastructure is becoming more widespread in practice, it often represents a relatively small fraction within portfolios of coastal risk-reducing strategies compared to more traditional grey infrastructure. This study provides a comprehensive review of how natural infrastructure is being used along the United States Atlantic, Gulf of Mexico, and Caribbean coasts related to four habitatstidal marshes, beaches and barrier islands, mangroves, and biogenic reefs. We compare information on the benefits, opportunities and challenges of implementing natural, grey and hybrid infrastructure in the coastal zone. In addition, we present a suite of actions to increase information and reduce uncertainty so that coastal mangers and planners are aware of the full suite of options for restoration, conservation and planning that maximize ecosystem services over short-and long-term planning horizons.

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Selection of a modeling approach is an important step in the conservation planning process, but little guidance is available. We compared two statistical and three theoretical habitat modeling approaches representing those currently being used for avian conservation planning at landscape and regional scales: hierarchical spatial count (HSC), classification and regression tree (CRT), habitat suitability index (HSI), forest structure database (FS), and habitat association database (HA). We focused our comparison on models for five priority forest-breeding species in the Central Hardwoods Bird Conservation Region: Acadian Flycatcher, Cerulean Warbler, Prairie Warbler, Red-headed Woodpecker, and Worm-eating Warbler. Lacking complete knowledge on the distribution and abundance of each species with which we could illuminate differences between approaches and provide strong grounds for recommending one approach over another, we used two approaches to compare models: rank correlations among model outputs and comparison of spatial correspondence. In general, rank correlations were significantly positive among models for each species, indicating general agreement among the models. Worm-eating Warblers had the highest pairwise correlations, all of which were significant (P < 0.05). Red-headed Woodpeckers had the lowest agreement among models, suggesting greater uncertainty in the relative conservation value of areas within the region. We assessed model uncertainty by mapping the spatial congruence in priorities (i.e., top ranks) resulting from each model for each species and calculating the coefficient of variation across model ranks for each location. This allowed identification of areas more likely to be good targets of conservation effort for a species, those areas that were least likely, and those in between where uncertainty is higher and thus conservation action incorporates more risk. Based on our results, models developed independently for the same purpose (conservation planning for a particular species in a particular geography) yield different answers and thus different conservation strategies. We assert that using only one habitat model (even if validated) as the foundation of a conservation plan is risky. Using multiple models (i.e., ensemble prediction) can reduce uncertainty and increase efficacy of conservation action when models corroborate one another and increase understanding of the system when they do not.

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