Identifying Policy-relevant Indicators for Assessing Landscape Vegetation Patterns to Inform Planning and Management on Multiple-use Public Lands.

Understanding the structure and composition of landscapes can empower agencies to effectively manage public lands for multiple uses while sustaining land health. Many landscape metrics exist, but they are not often used in public land decision-making. Our objectives were to (1) develop and (2) apply a process for identifying a core set of indicators that public land managers can use to understand landscape-level resource patterns on and around public lands.

Predicted responses of arctic and alpine ecosystems to altered seasonality under climate change.

Global climate change is already having significant impacts on arctic and alpine ecosystems, and ongoing increases in temperature and altered precipitation patterns will affect the strong seasonal patterns that characterize these temperature-limited systems. The length of the potential growing season in these tundra environments is increasing due to warmer temperatures and earlier spring snow melt. Here, we compare current and projected climate and ecological data from 20 Northern Hemisphere sites to identify how seasonal changes in the physical environment due to climate change will alter the seasonality of arctic and alpine ecosystems.

Indicators of ecosystem function identify alternate states in the sagebrush steppe.

Models of ecosystem change that incorporate nonlinear dynamics and thresholds, such as state-and-transition models (STMs), are increasingly popular tools for land management decision-making. However, few models are based on systematic collection and documentation of ecological data, and of these, most rely solely on structural indicators (species composition) to identify states and transitions. As STMs are adopted as an assessment framework throughout the United States, finding effective and efficient ways to create data-driven models that integrate ecosystem function and structure is vital.