No abstract

Climate change is altering ecological systems throughout the world. Managing these systems in a way that ignores climate change will likely fail to meet management objectives. The uncertainty in projected climate‐change impacts is one of the greatest challenges facing managers attempting to address global change. In order to select successful management strategies, managers need to understand the uncertainty inherent in projected climate impacts and how these uncertainties affect the outcomes of management activities. Perhaps the most important tool for managing ecological systems in the face of climate change is active adaptive management, in which systems are closely monitored and management strategies are altered to address expected and ongoing changes. Here, we discuss the uncertainty inherent in different types of data on potential climate impacts and explore climate projections and potential management responses at three sites in North America. The Central Valley of California, the headwaters of the Klamath River in Oregon, and the barrier islands and sounds of North Carolina each face a different set of challenges with respect to climate change. Using these three sites, we provide specific examples of how managers are already beginning to address the threat of climate change in the face of varying levels of uncertainty.

Despite a critical need to evaluate effectiveness of forest treatments in improving stand health, practitioners lack quantitative, repeatable metrics to assess tree vigor and stand health. We evaluated canopy and whole tree attributes of ponderosa pine (Pinus ponderosa Dougl. Ex Laws) related to carbon balance, water balance, and susceptibility to insects and pathogens in dry, pine-dominated forest stands during a multi-year drought, an environmental challenge to stand resilience. Metrics of trees in two unmanaged, and seven treated forested stands, in both uplands and lowlands to develop the quantitative approach. Whole tree and crown attributes including needle length and color, branchlet length and diameter, needle retention (needle ages and retention within ages), and frequency of insects, fungi, and abiotic needle damage were statistically selected to assess tree vigor. Cluster analysis of vigor attributes revealed that trees responded or persisted independently within a forest treatment; forest treatments did not necessarily yield similar tree responses within a stand. A rapid, qualitative assessment was developed to rank trees as low, average, and above-average vigor. To demonstrate an application of our approach, trees were ranked annually over six years in most stands, as well as in a stand where the prescription was adjusted due to the evaluation. The proportion of trees in the three tree vigor ranks differed, suggesting differing levels of stand health. Quantitative metrics and qualitative ranking of tree vigor could assist in selecting trees to be retained to meet specific management objectives, to evaluate treatment implementation, and to monitor post-treatment changes in stand health.

Ponderosa pine is an integral part of the forested landscape in the western US; it is the dominant tree species on landscapes that provide critical ecosystem services. Moderate drought tolerance allows it to occupy the transition zone between forests, open woodlands, and grasslands. Increases in stand density resulting from wildfire suppression, combined with lengthening, intensifying, and more frequent droughts have resulted in reduced tree vigor and stand health in dry ponderosa pine throughout its range. To address a management need for efficient landscape-level surveys of forest health, we used Random Forests to develop an object-oriented classification of individual tree crowns (ITCs) into vigor classes using existing, agency-acquired four-band aerial imagery. Classes of tree vigor were based on quantitative physiological and morphological attributes established in a previous study. We applied our model across a landscape dominated by ponderosa pine with a variety of forest treatments to assess their impacts on tree vigor and stand health. We found that stands that were both thinned and burned had the lowest proportion of low-vigor ITCs, and that stands treated before the 2014–2016 drought had lower proportions of low-vigor ITCs than stands treated more recently (2016). Upland stands had significantly higher proportions of low-vigor trees than lowland stands. Maps identifying the low-vigor ITCs would assist managers in identifying priority stands for treatment and marking trees for harvest or retention. These maps can be created using already available imagery and GIS software.

Ponderosa pine is an integral part of the forested landscape in the western US; it is the dominant tree species on landscapes that provide critical ecosystem services. Moderate drought tolerance allows it to occupy the transition zone between forests and open woodlands and grasslands. Increases in stand density resulting from wildfire suppression, combined with lengthening, intensifying and more frequent droughts have resulted in reduced tree vigor and stand health in dry ponderosa pine throughout its range. To address a management need for efficient landscape-level surveys of forest health, we used Random Forests to develop an object-oriented classification of individual tree crowns (ITCs) into vigor classes using existing, agency acquired 4-band aerial imagery. Classes of tree vigor were based on quantitative physiological and morphological attributes established in a previous study. We applied our model across a landscape dominated by ponderosa pine with a variety of forest treatments to assess their impacts on tree vigor and stand health. We found that stands that were both thinned and burned had the lowest proportion of low vigor ITCs, and that stands treated before the 2014-2016 drought had lower proportions of low vigor ITCs than stands treated more recently (2016). Upland stands had significantly higher proportions of low vigor trees than lowland stands. Maps identifying the low vigor ITCs would assist managers in identifying priority stands for treatment and marking trees for harvest or retention. These maps can be created using already available imagery and GIS software.