Linking “the clouds” to endangered songbird habitat conservation and management

Getting the big picture

Light Detection and Ranging airborne remote sensing technology, widely known as “LiDAR,” is being used more frequently as data collection and computing power for processing it become more affordable. It is often used to create a very detailed model of elevation and topography that can be used in a geographic information system (GIS). A LiDAR instrument sends thousands of infrared laser light pulses toward the ground from an airplane or helicopter and then simply records the x, y and z coordinates marking the return location for each beam of light. When viewed with specialized computer software, the points resemble a cloud, known as a “point cloud” that describes the height of objects. Detailed LiDAR “Bare Earth” models of topography are commonly at a much greater spatial resolution and vertical and horizontal accuracy than those developed through traditional methods such as aerial photography, making them well suited for civil engineering, geology, and hydrology applications.

LiDAR 3D point cloud showing an open area and adjacent trees.
LiDAR 3D point cloud showing an open area and adjacent trees.
Hillshade map of LiDAR bare Earth elevation.
Hillshade map of a LiDAR bare Earth elevation.

Early on, LiDAR points returned from trees, buildings, and other objects above the ground were considered a nuisance to be removed before producing good topographic data. Nevertheless, scientists and natural resource managers quickly understood the value of LiDAR point clouds and potential to create highly detailed information about vegetation structure, habitat conditions, human infrastructure, geomorphology, and other land features that can vary substantially across large landscapes. This potential is now gaining the attention of many private, county, state, and federal entities who are finding LiDAR to be an essential tool for managing natural resources, urban growth, flood control, water management, disaster mitigation, and other purposes, naturally driving down the cost of acquiring LiDAR data.

 Gaining ground for songbird conservation

Currently, LiDAR is opening new doors for characterizing and managing wildlife habitat for the US Fish and Wildlife Service (USFWS) Southwest Region Inventory and Monitoring (I&M) Program, starting with endangered songbirds. A common theme contributing to songbird declines is loss and fragmentation of habitat caused by agricultural development and urbanization. The Golden-cheeked Warbler (Setophaga chrysoparia) and Black-capped Vireo (Vireo atricapilla) were listed by the USFWS as Endangered in 1990 and 1987, respectively. The 25,000 acre Balcones Canyonlands National Wildlife Refuge (BCNWR) was established in 1992 to protect habitat for these two species. Both birds are Neotropical migrants, spending winter months in Mexico and Central America while occupying a narrow breeding range in the southwestern USA during the spring and summer. The warbler prefers older oak (Quercus spp.) and Ashe juniper (Juniperous ashei) woodlands while the vireo prefers semi-open shrublands.

Balcones Canyonlands National Wildlife Refuge is made up of large and small parcels of land purchased from private citizens and resides within the breeding range of the Golden-cheeked Warbler and Black-capped Vireo. Breeding habitat for the vireo (not shown) extends north to Oklahoma and south to northern Mexico.
Typical habitat conditions preferred by the golden-cheeked warbler in oak-juniper woodlands.
Typical habitat conditions preferred by the black-capped vireo in semi-open shrublands.

BCNWR managers and I&M needed a way to determine where the most suitable habitat conditions exist for warblers and vireos on and off Refuge lands. Specifically, we wanted to know how future land acquisitions, habitat restoration, and protection activities can best be prioritized to make the most of resources allocated to warbler and vireo conservation.

Translating point clouds to habitat

In 2012, the first BCNWR-wide bird point count survey was conducted following a protocol developed by I&M Zone Biologist Dr. Jim Mueller. Drawing on modern sampling techniques from published studies, a total of 250 randomly selected locations were surveyed to record presence, distance, and time of detection of the Golden-cheeked Warbler and the Black-capped Vireo, and potential nest predators such as the Brown-headed Cowbird (Molothrus ater), Western Scrub-jay (Aphelocoma californica), and Blue Jay (Cyanocitta cristata), at four separate occasions during the breeding season. Detections for the Northern Bobwhite (Colinus virginianus), a species of conservation concern, were also recorded.

LiDAR and on-the-ground bird surveys are now beginning to play a role in estimating woodland conditions that are most important to the warbler and vireo, and eventually map locations across the landscape where they are likely to exist or which habitats are likely to be colonized in the future. Of considerable advantage, the state of Texas maintains substantial LiDAR data archives for many of the counties known to maintain warbler and vireo populations. In addition, the US Department of Agriculture National Agricultural Imagery Program (NAIP) acquires high-quality and high spatial-resolution color-infrared (CIR) aerial photography for the entire state of Texas every 2 to 3 years.  Each of these data sources is freely available through the Texas Natural Resource Information System (TNRIS) and important to developing relationships between songbirds and habitat characteristics such as woodland vegetation composition and structure.

Remotely sensed data must first be processed, often using sophisticated computational techniques that require fast computers to translate them into information that is useful for conservation planning and management. However, results can be astonishingly accurate and simple to interpret for making management decisions.  For the warbler, we have developed highly accurate vegetation height, density, and canopy cover data layers from LiDAR that can be mapped and quickly be related to preferred habitat conditions by songbirds.

LiDAR derived vegetation height useful for identifying older oak-juniper woodlands (darker green to blue color) important to the golden-cheeked warbler.
LiDAR derived relative vegetation density for trees between 5 and 10m tall. Height breaks can be used to determine both overstory and understory vegetation density important to songbirds.
Golden-cheeked warbler occurrence data collected in 2012 combined with LiDAR derived vegetation height indicating how late successional oak-juniper woodland structure is important habitat.
Golden-cheeked warbler occurrence data collected in 2012 combined with LiDAR derived canopy cover indicating how relatively closed canopy oak-juniper woodland structure is important habitat.

Synthesizing LiDAR outputs with data collected in the field is not only telling a story about preferred songbird habitat conditions, but also where these conditions exist over large areas. A recent study by Farrell et al. (2013) provides an excellent example of how LiDAR derived vegetation data can be used effectively to identify key habitat for the Golden-cheeked Warbler and Black-capped Vireo on the Fort Hood military installation. We are taking similar steps to develop spatial models of songbird and nest-predator occupancy that will afford important information on where to prioritize conservation and habitat restoration actions both on and off Refuge lands. LiDAR and CIR imagery are also helping to address other questions such as understanding how understory vegetation, heterogeneity in height and canopy structure, successional status, and woodland species composition are related to the presence of warblers and vireos. This information will provide keen insights into how management activities such as hazardous fuels mitigation and other woodland treatments may best enhance habitat conditions and help minimize the negative influence of songbird nest predation. These monitoring and modeling activities are aimed at achieving refuge management goals, consistent with the 2001 Comprehensive Conservation Plan (2001) and Draft Habitat Management Plan (2010).

In the future, larger-scale efforts to characterize habitat conditions throughout the range of these two species may also help to identify locations where conservation credits to private land owners can best meet endangered songbird recovery objectives. Thus, the answer to these and many other questions about wildlife habitat relationships and management might just be in the clouds.


Balcones Canyonlands National Wildlife Refuge Comprehensive Conservation Plan. 2001. U.S. Fish and Wildlife Service, Albuquerque, New Mexico.

Balcones Canyonlands National Wildlife Refuge Habitat Management Plan (Draft). 2010. U.S. Fish and Wildlife Service, Marble Falls, Texas.

Farrell, S. L., B. A. Collier, K. L. Skow, A. M. Long, A. J. Campomizzi, M. L. Morrison, K. B. Hays, and R. N. Wilkins. 2013. Using LiDAR-derived vegetation metrics for high-resolution, species distribution models for conservation planning. Ecosphere 4:1-18.

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