Jody C. Vogeler

LIDAR-DERIVED CANOPY ARCHITECTURE PREDICTS BROWN CREEPER OCCUPANCY OF TWO WESTERN CONIFEROUS FORESTS

Abstract. In western conifer-dominated forests where the abundance of old-growth stands is decreasing, species such as the Brown Creeper (Certhia americana) may be useful as indicator species for monitoring the health of old-growth systems because they are strongly associated with habitat characteristics associated with old growth and are especially sensitive to forest management. Light detection and ranging (lidar) is useful for acquiring fine-resolution, three-dimensional data on vegetation structure across broad areas. We evaluated Brown Creeper occupancy of forested landscapes by using lidar-derived canopy metrics in two coniferous forests in Idaho. Density of the upper canopy was the most important variable for predicting Brown Creeper occupancy, although mean height and height variability were also included in the top models. The upper canopy was twice as dense and the mean height was almost 50% higher at occupied than at unoccupied sites. Previous studies have found indicators of canopy density to be important factors for Brown Creeper habitat; however, this represents the first time that lidar data have been used to examine this relationship empirically through the mapping of the upper canopy density that cannot be continuously quantified by field-based methods or passive remote sensing. Our models performance was classified as “good” by multiple criteria. We were able to map probabilities of Brown Creeper occupancy in ∼50 000 ha of forest, probabilities that can be used at the local, forest-stand, and landscape scales, and illustrate the potential utility of lidar-derived data for studies of avian distributions in forested landscapes.

How much does the time lag between wildlife field-data collection and LiDAR-data acquisition matter for studies of animal distributions? A case study using bird communities

Vegetation structure quantified by light detection and ranging (LiDAR) can improve understanding of wildlife occupancy and species-richness patterns. However, there is often a time lag between the collection of LiDAR data and wildlife data. We investigated whether a time lag between the LiDAR acquisition and field-data acquisition affected mapped wildlife distributions ranging from an individual species distribution to total avian species richness in a conifer forest. We collected bird and LiDAR data in 2009 across a 20,000 ha forest in northern Idaho. Using the 2009 LiDAR data, we modelled the probability of occurrence for the brown creeper (Certhia americana). Using the same 2009 LiDAR data, we additionally modelled total avian species richness and richness of three different bird nesting guilds (ground/understory, mid/upper canopy and cavity). We mapped brown creeper occupancy probability and species richness using the 2009 models, and then compared these maps with maps based on the same models applied to a 2003-LiDAR dataset. A prior study identified areas harvested between 2003 and 2009. There was on average a 5% absolute decrease in mapped probabilities of brown creeper occurrence in non-harvest areas between 2003 and 2009. Species richness changed by less than one species in all cases within non-harvest areas between the 2003 and 2009 maps. Although these comparisons were statistically significant at the p < 0.0001 level, it is likely that the high number of map cells (~480,000) influenced this result. Similar patterns between our 2003 and 2009 maps in non-harvest areas for this suite of avian responses suggests that a 6-year difference between field-data collection and LiDAR-data collection has a minimal effect on mapped avian patterns in an undisturbed coniferous forest. However, because this is one case study in one ecosystem, additional work examining the effect of temporal lags between LiDAR and field-data collection on mapping wildlife distributions is warranted in additional ecosystems.

Evaluating carbon storage, timber harvest, and habitat possibilities for a Western Cascades (USA) forest landscape

Forest policymakers and managers have long sought ways to evaluate the capability of forest landscapes to jointly produce timber, habitat, and other ecosystem services in response to forest management. Currently, carbon is of particular interest as policies for increasing carbon storage on federal lands are being proposed. However, a challenge in joint production analysis of forest management is adequately representing ecological conditions and processes that influence joint production relationships. We used simulation models of vegetation structure, forest sector carbon, and potential wildlife habitat to characterize landscape-level joint production possibilities for carbon storage, timber harvest, and habitat for seven wildlife species across a range of forest management regimes. We sought to (1) characterize the general relationships of production possibilities for combinations of carbon storage, timber, and habitat, and (2) identify management variables that most influence joint production relationships. Our 160 000-ha study landscape featured environmental conditions typical of forests in the Western Cascade Mountains of Oregon (USA). Our results indicate that managing forests for carbon storage involves trade-offs among timber harvest and habitat for focal wildlife species, depending on the disturbance interval and utilization intensity followed. Joint production possibilities for wildlife species varied in shape, ranging from competitive to complementary to compound, reflecting niche breadth and habitat component needs of species examined. Managing Pacific Northwest forests to store forest sector carbon can be roughly complementary with habitat for Northern Spotted Owl, Olive-sided Flycatcher, and red tree vole. However, managing forests to increase carbon storage potentially can be competitive with timber production and habitat for Pacific marten, Pileated Woodpecker, and Western Bluebird, depending on the disturbance interval and harvest intensity chosen. Our analysis suggests that joint production possibilities under forest management regimes currently typical on industrial forest lands (e.g., 40- to 80-yr rotations with some tree retention for wildlife) represent but a small fraction of joint production outcomes possible in the region. Although the theoretical boundaries of the production possibilities sets we developed are probably unachievable in the current management environment, they arguably define the long-term potential of managing forests to produce multiple ecosystem services within and across multiple forest ownerships.

Mapping Suitable Lewis's Woodpecker Nesting Habitat in a Post-Fire Landscape

Abstract As remote sensing mapping products representing important habitat components increase in availability, detail, and accuracy, new opportunities arise to map predicted habitat for forest species of conservation concern. One such species is the Lewiss woodpecker which is a species of conservation interest in multiple states and throughout its range in British Columbia, Canada with habitat loss and degradation proposed as contributing factors in the species decline. The purpose of this study was to model and map Lewiss woodpecker nesting habitat using primary (directly derived) and secondary (modeled using ground calibration data) remote sensing products, as well as contribute to the knowledge of nesting ecology for the species in a source habitat type. We found promise in the utility of lidar and Landsat time series modeled snag and shrub products in conjunction with additional lidar structure and topographic metrics for predicting nesting habitat for the Lewiss woodpecker across a post-fire landscape. Our selected model had a percent correctly classified rate of 83.3% and contained additional variables (variability in canopy cover and topographic slope) to those included in the Fish and Wildlife Service habitat suitability model (HSM) for the species (canopy cover, shrub cover, and density of large snags). We were able to apply the remote sensing products to map realized habitat relationships for this species of conservation concern in an identified source habitat type, providing a potential resource for local scale conservation and management efforts and adding to the regional knowledge of habitat selection for the Lewiss woodpecker.

Incorporating Shrub and Snag Specific LiDAR Data into GAP Wildlife Models

Abstract The U.S. Geological Survey’s Gap Analysis Program (hereafter, GAP) is a nationally based program that uses land cover, vertebrate distributions, and land ownership to identify locations where gaps in conservation coverage exist, and GAP products are commonly used by government agencies, nongovernmental organizations, and private citizens. The GAP land-cover designations are based on satellite-derived data, and although these data are widely available, these data do not capture the 3-dimensional vegetation architecture that may be important in describing vertebrate distributions. To date, no studies have examined how the inclusion of snag- or shrub-specific Light Detection and Ranging (LiDAR) data might influence GAP model performance. The objectives of this paper were 1) to assess the performance of the National GAP models and Northwest GAP models with independently collected field data, and 2) to assess whether the inclusion of 3-dimensional vegetation data from LiDAR improved the performance of...