A Participatory Approach for Balancing Accuracy and Complexity in Modeling Resilience and Robustness.

Robustness and resilience are widely used in the biological sciences and related disciplines to describe how systems respond to change. Robustness is the ability to tolerate change without adapting or moving to another state. Resilience refers to the ability for a system to sustain a perturbation and maintain critical functions. Robustness and resilience transcend levels of biological organization, though they do not scale directly across levels. We live in an era of novel stressors and unprecedented change, including climate change, emerging environmental contaminants, and changes to the Earth's biogeochemical and hydrological cycles. We envision a common framework for developing models to predict the robustness and resilience of biological functions associated with complex systems that can transcend disciplinary boundaries. Conceptual and quantitative models of robustness and resilience must consider cross-scale interactions of potentially infinite complexity, but it is impossible to capture everything within a single model. Here, we discuss the need to balance accuracy and complexity when designing models, data collection, and downstream analyses to study robustness and resilience. We also consider the difficulties in defining the spatiotemporal domain when studying robustness and resilience as an emergent property of a complex system. We suggest a framework for implementing transdisciplinary research on robustness and resilience of biological systems that draws on participatory stakeholder engagement methods from the fields of conservation and natural resources management. Further, we suggest that a common, simplified model development framework for describing complex biological systems will provide new, broadly relevant educational tools. Efficient interdisciplinary collaboration to accurately develop a model of robustness and resilience would enable rapid, context-specific assessment of complex biological systems with benefits for a broad range of societally relevant problems.

Forest restoration as a strategy to mitigate climate impacts on wildfire, vegetation, and water in semiarid forests.

Climate change and wildfire are interacting to drive vegetation change and potentially reduce water quantity and quality in the southwestern United States, Forest restoration is a management approach that could mitigate some of these negative outcomes. However, little information exists on how restoration combined with climate change might influence hydrology across large forest landscapes that incorporate multiple vegetation types and complex fire regimes. We combined spatially explicit vegetation and fire modeling with statistical water and sediment yield models for a large forested landscape (335,000 ha) on the Kaibab Plateau in northern Arizona, USA. Our objective was to assess the impacts of climate change and forest restoration on the future fire regime, forest vegetation, and watershed outputs. Our model results predict that the combination of climate change and high-severity fire will drive forest turnover, biomass declines, and compositional change in future forests. Restoration treatments may reduce the area burned in high-severity fires and reduce conversions from forested to non-forested conditions. Even though mid-elevation forests are the targets of restoration, the treatments are expected to delay the decline of high-elevation spruce-fir, aspen, and mixed conifer forests by reducing the occurrence of high-severity fires that may spread across ecoregions. We estimate that climate-induced vegetation changes will result in annual runoff declines of up to 10%, while restoration reduced or reversed this decline. The hydrologic model suggests that mid-elevation forests, which are the targets of restoration treatments, provide around 80% of runoff in this system and the conservation of mid- to high-elevation forests types provides the greatest benefit in terms of water conservation. We also predict that restoration treatments will conserve water quality by reducing patches of high-severity fire that are associated with high sediment yield. Restoration treatments are a management strategy that may reduce undesirable outcomes for multiple ecosystem services.

Semi-arid aquifer responses to forest restoration treatments and climate change.

The purpose of this study was to develop an interpretive groundwater-flow model to assess the impacts that planned forest restoration treatments and anticipated climate change will have on large regional, deep (>400 m), semi-arid aquifers. Simulations were conducted to examine how tree basal area reductions impact groundwater recharge from historic conditions to 2099. Novel spatial analyses were conducted to determine areas and rates of potential increases in groundwater recharge. Changes in recharge were applied to the model by identifying zones of basal area reduction from planned forest restoration treatments and applying recharge-change factors to these zones. Over a 10-year period of forest restoration treatment, a 2.8% increase in recharge to one adjacent groundwater basin (the Verde Valley sub-basin) was estimated, compared to conditions that existed from 2000 to 2005. However, this increase in recharge was assumed to quickly decline after treatment due to regrowth of vegetation and forest underbrush and their associated increased evapotranspiration. Furthermore, simulated increases in groundwater recharge were masked by decreases in water levels, stream baseflow, and groundwater storage resulting from surface water diversions and groundwater pumping. These results indicate that there is an imbalance between water supply and demand in this regional, semi-arid aquifer. Current water management practices may not be sustainable into the far future and comprehensive action should be taken to minimize this water budget imbalance.