John E. Lundquist

Approaches to predicting potential impacts of climate change on forest disease: an example with Armillaria root disease

Climate change will likely have dramatic impacts on forest health because many forest trees could become maladapted to climate. Furthermore, climate change will have additional impacts on forest health through changes in the distribution and severity of forest disease. Methods are needed to predict the influence of climate change on forest disease so that appropriate forest management practices can be implemented to minimize disease impacts. Initial approaches for predicting the future distribution of pathogens are dependent on reliable data sets that document the current, precise location of accurately identified pathogens and hosts. Precise distribution information can be used in conjunction with available climate surfaces to determine which climatic factors and interactions influence species distribution. This information can be used to develop bioclimatic models to predict the probability of suitable climate space for host and pathogen species across the landscape. A similar approach using climate surfaces under predicted future climate scenarios can be used to project suitable climate space for hosts and pathogens in the future. Currently such predictions are well developed for many forest host species, but predictive capacity is extremely limited for forest pathogens because of lacking distribution data. Continued surveys and research are needed to further refine bioclimatic models to predict influences of climate and climate change on forest disease.

Integrating concepts of landscape ecology with the molecular biology of forest pathogens

Increasingly more research has focused on characterizing diversity within forest pathogen populations using molecular markers but few studies have characterized features of the landscape that help create or maintain this diversity. Forest diseases commonly occur in patchy distributions across natural landscapes which can be reflected in the genetic composition of the fragmented pathogen populations. This metapopulation structure has seldom been examined by forest pathologists but we believe it offers a potential means to understand the genetic ecology of pathogens in natural landscapes. Molecular markers can be used to detect, identify, and measure detailed differences among subpopulations of forest pathogens. Geographical information systems, spatial analysis and modeling, digital imagery of remotely sensed images, and other tools of landscape ecology provide the means to detect and interpret patterns associated with genotypic asymmetry. Integrating the tools and concepts of molecular biology and landscape ecology by focusing on metapopulation disease phenomena offers a way of conceptually linking molecules and ecosystems.

Spatial relationship of resident and migratory birds and canopy openings in diseased ponderosa pine forests

Abstract A method is described for predicting the spatial distribution of individual birds using presence data. The approach is demonstrated using a statistical habitat association model developed for resident and migratory birds on a 12 ha plot of ponderosa pine ( Pinus ponderosa) heavily infested with southwestern ponderosa pine dwarf mistletoe ( Arceuthobium vasinatum subsp. Cryptopodum ( Englemann) Hawksworth and Weins). Bird locations and densiometer readings of canopy opening were recorded on a 5 m×5 m sampling grid. Minimum threshold theory was used to fit a logistic regression model to the presence data as a function of canopy opening. Highest occupancy of birds occurred at 61% canopy density. Higher probability of birds occurred in more dense canopy than less dense. Model validation indicated that the model adequately described the spatial distribution of the presence of individual birds with respect to canopy opening. Such a model could be used to determine stand conditions that are conducive and/or necessary for certain bird species, and to characterize and quantify the likely ecological consequences of changes to stand structure caused by diseases and other small scale disturbances.

Host-environment mismatches associated with subalpine fir decline in Colorado

Subalpine fir decline (SFD) has killed more trees in Colorado’s high elevation forests than any other insect or disease problem. The widespread nature of this disorder suggests that the cause involves climatic factors. We examined the influence of varying combinations of average annual temperature and precipitation on the incidence and distribution of SFD. Climatic transition matrices generated in this study indicate that most healthy trees are found in climatic zones with moderate to low temperatures and high precipitation; whereas, SFD occurs mostly in zones of moderate temperatures and moderate precipitation. The contrasting distributions define an environmental mismatch. Forests matched with favorable climatic conditions thrive; those that are mismatched can become vulnerable to decline disease.

Tree Diseases, Canopy Structure, and Bird Distributions in Ponderosa Pine Forests

Abstract We examined how canopy patterns at the landscape scale can influence bird community composition, abundance, or distribution. Our long-term goal is to determine how diseases and other small-scale disturbances that change canopy patterns influence bird distribution. Little is known about these relationships, partly because most measures of disturbance are based on timber production metrics. We developed a spatially dependent metric referred to as canopy closure roughness, which was significantly correlated to bird diversity on 4 ha sample plots, and used it to generate a spatial model showing the distribution of bird diversity at a resolution of 30 mover an area of 1 million acres (the entire Black Hills National Forest). Number of bird species per stand varied between 2 and 16. Number of species and bird diversity were positively related to intensity of tree cutting. Most common bird species were yellow-rumped warbler, dark-eyed junco, Townsends solitaire, black-capped chickadee and red-breasted nuthatch. The spatial model of bird diversity showed clusters of high diversity at different locations within the forest. These methods may help lead to better tools for managing the linkages between specific disturbances and bird usage and enable more effective disturbance management by offering a platform for spatial planning.

Characterizing Spatial Distributions of Insect Pests Across Alaskan Forested Landscape: A Case Study Using Aspen Leaf Miner (Phyllocnistis populiella Chambers)

Insects are ectotherms that cannot regulate their own temperature, and thus rely on and are at the disposal of the surrounding environment. In this study, long-term climatic data are used to stratify forested regions of Alaska into climatic zones based on temperature and precipitation. Temperature and precipitation are shown to be important ecological drivers in determining the distribution of aspen leaf minor (Phyllocnistis populiella Chambers) and the aspen (Populus tremuloides Michx.) host in the state of Alaska. Climatic regions based on temperatures and precipitation accounted for 83 to 97% of the variability in the probability of observing aspen and the aspen leaf minor (ALM). The frequency of observing aspen was highest throughout the central region of the state, which represents a climate with low to moderate levels of precipitation and cold to mild temperatures. The highest probability of observing aspen was in the mild-very cold region of the state. The probability of observing ALM in a given climate zone followed a pattern similar to aspen. Differences were in the colder and drier climate zones where the probability of observing ALM decreased to near zero. The derived climatic models could be used to provide a basis for the analysis of climatic impacts on the distribution of forest insects throughout the state.

Predicting the Landscape Spatial Distribution of Fuel-Generating Insects, Diseases, and Other Types of Disturbances

We developed a method of mapping fuel-generating disturbances based on spatial fuel models which were in turn developed using a combination of satellite imagery, topographic data, and field data. This is a potentially significant product for fuel management, pest management, forest planners, and others. With these maps, the spatial distribution, extent, and abundance of different fuel-generating disturbances can be estimated, and spatial prescriptions developed. The procedures are demonstrated by modeling the spatial distribution of various small-scale disturbances that cause fuels in the Black Hills National Forest, South Dakota and the Lincoln National Forest, New Mexico.