Yellow-billed Cuckoo (Coccyzus americanus occidentalis) Habitat Identification using GPS and GIS Based Survey Information





Michael R. Kunzmann, Alexander Rybak, and Peter S. Bennett

Abstract: The yellow-billed cuckoo (Coccyzus americanus occidentalis), a widely distributed inhabitant of the interior Southwestern cottonwood-willow riparian forest and the mixed broadleaf riparian forest types (Brown 1982), has become increasingly scarce in the United States. Western yellow-billed cuckoos have been petitioned for possible listing under the Endangered Species Act (1973 as amended). Habitat fragmentation, degradation of riparian woodlands, and the use of pesticides are possible causes of cuckoo decline in the United States (Hughes, J.M. 1999). Unfortunately, habitat factors important to cuckoos have not been convincingly defined (Magill 1999).

Dense broadleaf gallery riparian forests with abundant shrub understory are presumed to form an ideal habitat in Arizona. Yet cuckoos are found resident in pecan orchards and other stands that appear to be less than ideal. To delineate potential yellow-billed cuckoo habitat cost effective field data collection strategies were utilized, and GIS and modeling efforts were refined to include higher resolution spatial data and a wider array of secondary database attributes required to succinctly define habitat requirements. Geolink was critical in illustrating the shape and size of yellow-billed cuckoo habitat patches (polygons) in the field. Examination of the vegetation data collected indicates that the field methodologies are sensitive enough to delineate differences in riparian vegetation communities that change as a function of the perpendicular distance from the primary stream course.

Introduction:

The Yellow-billed Cuckoo (Coccyzus americanus occidentalis), an inhabitant of the interior Southwestern cottonwood-willow riparian forest and the mixed broadleaf forest types, has become increasingly rare in Arizona because of habitat fragmentation and degradation of riparian woodlands. As a result, western yellow-billed cuckoos have been petitioned for possible listing under the Endangered Species Act. This decision has to be supported by investigation of current bird distribution, which may be accomplished by obtaining information about habitat characteristics.

The goal of this study was to detect, delimit, and define efficient field validation techniques that could be utilized for subsequent satellite image analysis of riparian vegetation structure to delineate possible habitats for the, rather secretive, Yellow-billed Cuckoo. In 1998, historical habitat and initial field survey data were digitized, attributed, and modeled for predicted habitat preference using AVHRR imageryand GIS site stratification procedures (M. R. Kunzmann, et. al. 1999).

During the summer of 1999 we investigated floristic diversity and physiognomy of cuckoo habitats in Arizona and measured important structural vegetation components and other landscape-level factors that may be useful in delineating cuckoo habitat from non-habitat. A longer-term goal is to use vegetation structural components and satellite imagery to develop predictive models of Yellow-billed Cuckoo habitat. To determine which vegetation structural elements may be the most useful factors for predicting bird habitat we decided to collect a wide range of variables that have been traditionally used and reported in the literature as beneficial by a wide range of bird experts. Unfortunately, there is not a consensus on what vegetation parameters may be the best predictive indicators of preferred habitat because of insufficient basic ecological research on Yellow-billed Cuckoo habitat, habitat utilization, site tenacity, and other important life history factors. Because of time and funding constraints, there was also a need to develop an efficient field sampling strategy that was flexible enough to obtain the required vegetation and community measurements and that would provide the necessary data for subsequent habitat and remote sensing analysis. If vegetation structure is understood sufficiently and can serve as a surrogate factor for predicting Yellow-billed Cuckoo habitat, then it may be possible to use high spatial resolution remote sensing imagery analysis techniques to monitor changes in bird habitat over time.

Preliminary examination of vegetation data collected indicates that the proposed field methodologies we used may be sensitive enough to depict differences between primary and secondary Yellow-billed Cuckoo habitat and non-habitat. In addition, the field techniques are useful to delineate the various combinations of community floristic associations and concomitant vegetation structural (synusia) changes as a function of the perpendicular distance from the primary stream course in distinctively different ways. In general, most riparian communities are not well understood (ecologically) or sufficiently mapped at the scale required (Kunzmann, M.R. et. al., 1993).
 
 

Site Selection:

Sites (habitat patches) visited in 1998 were surveyed, digitized, and attributed by personnel at the USGS Colorado Plateau Field Station and Arizona Game and Fish Department. The early survey data and ArcInfo coverages defined the spatial extent and the polygonal area of all sites that could be used for subsequent vegetation analysis. To select individual cuckoo sites for investigation we used a stratified random sampling plan. The goal was to choose sites with different presumed breeding activity and cuckoo status, in such a way, as they would be evenly distributed in the state, cover all predicted elevation ranges, patch sizes, and vegetation communities as indicated by the 1998 survey data (ArcInfo coverages), the Arizona GAP Program habitat map (from a predicted habitat model), and possible locations as indicated by our early AVHRR imagery analysis (M. R. Kunzmann, et. al., 1999). Because of time and budget constraints, only 20 out of the original 30 targeted sites could be visited through the state. Sites with birds were classified into two categories "primary" and "secondary" based upon presumed breeding status. Sites without birds were designated as "non-habitat". Sites ranged from 180 m to 1400 m above mean sea level. At least 16 male and 7 female cuckoos (all below 1330 m of elevation) were observed when collecting vegetation measurements. Birds were seen at various times of the day ranging from 6:00am to 6:45pm. Sites represented 15 major Arizona drainages. Vegetation surveys covered almost 16 km of transect lines with 912, 4.0 m diameter, circular plots representing an area of about 11,500 m2. Because of the nature and level of detail required, the systematic transect (sampling) design, weather, and other logistic factors (not anticipated), on average, 8 hours was required per site. Approximately 4 hours were necessary to setup and read transects but 2-4 hours was often required for travel between sites.

Global Positioning System (GPS) receivers and background maps from ungenerated ARCINFO coverages and AVHRR imagery, were used to help locate the boundaries of selected habitat polygons in the field. Geolink GIS/GPS data collection and mapping software (Baker-GeoResearch Inc., Billings, Montana), was extremely valuable in helping us find difficult survey sites on back-county roads - sites that we had never been too. In addition, Geolink was critical in delineating the shape and size of yellow-billed cuckoo habitat patches (polygons) in the field.
 
 

Physiognomic and Vegetation Measurements

Three different field techniques were used to characterize vegetation communities (associations) at each targeted site. Individual habitat patches within a site were identified using GPS coordinates or were identified by examining polygonal boundaries as represented by background coverages on the field laptop computer. Transect locations were randomly placed within 100m of Yellow-billed Cuckoo GPS coordinates provided by earlier bird census teams. Typically, the accuracy of GPS coordinates ranged from 4 meters to 100 meters depending upon the receivers used by field personnel and volunteer "birders".

The vegetation measuration techniques selected were:

    1. A modified Braun-Blanquet approach using dimensionless releve's and prominence rankings (Warren, et al. 1982, Bennett, et al. 1998). This method was applied for the whole area of 30x50 m2 transect and was used for cluster analysis.
    2. A quantitative transect sampling method using systematic circular plots to record detailed species composition, canopy-based measurements, percent cover, and other vegetation characteristics, including but not limited to, canopy cover of trees, canopy cover of shrubs, stem counts, woody basal area, species density estimates, tree and shrub heights, maximum object height, and tree diameter at "breast height" (dbh = 1.4 m).
    3. A simple method of counting all shrubs and 4.0 cm diameter-at-breast-height trees over 2.0 m in height.
From these measurements numerous variables such as species richness, maximum and mean height of trees and shrubs, canopy volumes, and the number of stems in 4 different synusia layers (0-2 m, 2-8 m, 8-30 m, >30 m) were derived. Two data sets, comprised of systematically placed transects, were establish on habitat polygons. Each data set was symmetric, aligned approximately with the primary stream channel, but separated by 50 meters and a random offset. Each data set contained four (4) 50 meter transect lines parallel to the stream channel. Each transect line was separated by 10 meters (perpendicular to the channel) and contained 6 circular plots. Consequently, transect sampling consisted of obtaining floristic and physiognomic for 48 circular plots per site representing both data sets. Circular plots were laid out on 10 meter intervals and each had an approximate 4.0 m diameter base. Circular plots became vegetation sampling cylinders (3 dimensional) when the height of tallest object within the plot was recorded. Each sampling cylinder was attributed and classified according to its distance from the primary stream channel and ranked into one of three possible landscape-level riparian community type classifications; aquatic (hydroriparian), riparian (mesoriparian), or upland (xeroriparian) (Kunzmann, M.R. et al., 1993). Yellow-billed Cuckoo sites (habitats) were categorized into three ranks by the presence (type 1 or 2) or absence (3) of cuckoos or by possible reproductive status.

Primary analysis was done for the sites, which were subdivided into three major types:

    1. Primary: sites where at least one mated pair of cuckoos was detected. (N=9)
    2. Secondary: sites where only single birds were observed. (N=5)
    3. Non-Habitat: sites without observed cuckoos. (N=6)
In addition, vegetation structure by synusia (layer) was determined by the number of plants found in four vertically stratified height levels that may be useful in subsequent remote sensing analysis and be helpful to surveyors in visually identifying potential bird habitats. A "synusia" formula was developed as an integrating variable for four vegetation structural layers: layer A (0.25m-2m), layer B (2m-8m), layer C (8m-30m), and layer D (>30m). A synusia (layer) may also be thought of as a community made up of plants that share a similar life zone, form, occupy the same habitat, that may have similar ecological requirements or constraints.
 
 

Preliminary Results:

A majority of assumptions about yellow-billed cuckoo habitat requirements were derived from observations made by a wide range of people ranging from highly trained ornithologist to hobbyist "bird watchers", who conducted a variety of systematic and non-systematic studies of limited duration. Most studies did not focus on vegetation structure as the primary analytical goal nor were most studies interested in characterizing the vegetation community in such a way that field information collected could be used by the remote sensing specialist to predict and detect site habitat changes. Earlier studies indicate that for the yellow-billed cuckoo the following habitat features may be significant or at least be somewhat preferred characteristics:

In addition, most studies indicate that some combination of community floristics, specific plant species, and or community age play a large role in defining habitat requirements. For example, cottonwood/willow (Populus fremontii/Salix gooddingii) communities are often thought of as primary indicators of "preferred" yellow-billed cuckoo habitat. Undoubtedly this is may be true, but upon examination of the data (and as more ecological data becomes available) one finds that yellow-billed cuckoos often have a wider ecological "niche" than originally presumed. Preliminary data in this study suggest that different floristic and synusia combinations are important. However, statistical significance of each variable is dependent upon numerous ecological factors, including but not limited to, the synusia complexity, the relative proportions and extent of the vertical vegetation structures and associated canopies, floristic composition, hydrological/ riparian moisture gradients responsible for the establishment and maintenance of hydro- and meso-riparian communities, and of course other ecological factors necessary for bird survival but not yet adequately identified. It is not possible to adequately define yellow-billed cuckoo habitat based on this study. However, that said, we present a few observations that may be of interest. Observations of specific species associated with cuckoos are mostly right in terms that they are indicate hydrological and riparian community gradients that are commonly found in cuckoo habitats. For example, Goodding willow (Salix gooddingii) and mesquite (Prosopis velutina) are representative species indicators of riparian communities adapted to different hydrological regimes.


 

Species richness, number of all plants stems, and "empty space" sampling unit statistics are also interesting factors to examine trends across Yellow-billed Cuckoo sites. Please note that the species richness and empty space are not directly correlated across all habitat types.


 

In addition to transect variables such the number of trees and shrubs, the height of trees and shrubs, stem counts, and other primary data derived directly from cylinder sampling units there are a number of derived variables that show promise. In addition, these derived variables permit better visual representation and interpretation of vegetation structural difference between sites. Two of the derived variables converted canopy volume and synusia vegetation structural coefficients may serve as an illustration of integrating variables that are somewhat predictive of yellow-billed cuckoo habitat groups stratified across site and riparian community types. A preliminary summary of variables that may be used to depict differences between primary, secondary, and non-habitats was examined.

Upon examination of all variables, floristic and structural differences could be detected between the sites with and without yellow-billed cuckoos. From a derived statistical profile (representation) of each significant variable grouping "type" sites can be illustrate by constructing a "generalized" schematic of the vegetation structural differences that are indicative of our sites and between habitats. Sites with cuckoo have larger total canopy volume, larger tree canopy volume, but smaller shrub canopy volume. Trees here are taller, but shrubs are shorter. Sites with cuckoo have smaller number of all plants, almost the same number of trees, but much fewer shrubs. So, every tree on a site with cuckoo has larger canopy, but every shrub has smaller canopy, and tree cover is bigger, but shrub cover is smaller.

Synusia structure is completely different: sites with cuckoos in layer A (0.25m -2m) have more plants (7.4 vs. 6.8); in layer B (2m-8m) - much less plants (5.5 vs. 13.4); in layers C (8-30 m) and D (higher than 30 m) significantly more trees (1.1 vs. 0.7 and 0.12 vs. 0.01 respectively). These differences are also supported by a derived synusia coefficient (1.25 vs. 0.31). However, sites with cuckoos have fewer plants higher than 2.0 m (6.7 vs. 14.1), so basal area is smaller, but the empty space between canopies is larger. Vegetation structure may be a more universal analytical tool for predicting possible bird habitats across geographically broad areas of the state because of differences found in floristic provinces within Arizona. Riparian species which may be utilized by yellow-billed cuckoos do not occur with equal frequency across the state for many reasons - some ecological and others anthropogenic. For example, occasionally, birds have been observed in orchards near historic riparian habitat that has been reduced, modified, and in some cases eliminated. Habitat structural characteristics, on a comparative basis to floristic variables based on the identification of specific species, require less training and are easier to collect reliably year round. In addition, changes in vegetation structure may also be detected by remote sensing techniques. Appropriate measurement resolution and spatial scale are critical factors that must be examined to coordinate field and remote sensing activities.
 
 

Future Research Required:

The next phase of our research will be to use our twenty field sites as remote sensing "training" sites so we can examine which combinations of imagery and analysis techniques may be used predict possible habitat. Current efforts are underway to reexamine how our field-based measurements of vegetation structural, community structure, and other ecologically important habitat parameters may be integrated with a wide variety of spectral data, imagery products, an remote sensing analysis techniques. For example, Lidar, is an established remote sensing technology that is commonly used to obtain accurate, high spatial resolution, measurements of surface elevations from airborne and Space Shuttle platforms (Krabill et al 1984, Bufton et al. 1991). However, one of the more interesting applications of Lidar technology was recently published by M.A. Lefsky et. al. (1999). It was pointed out in the article that the SLICER (Scanning Lidar Imager of Canopies by Echo Recovery) could characterize multiple canopy elements (foliage and woody vegetation structures) in a 5m to 25m diameter area. This spatial scale fits well with traditional field-based measurement techniques. In addition, unlike traditional microwave and optical sensors, lidar sensors directly measure the distribution of vegetation components along a vertical axis and can be used to provide three-dimensional and volumetric characterizations of vegetation structure. If these techniques (after standardization and localized calibration) could reduce the number of ground-based measurements required per site to predict yellow-billed cuckoo habitats, then it would be possible to expedite inventory and monitoring programs necessary to predict bird distributions and develop better habitat protection plans.

However no matter how well we are able to measure site vegetation structures or catalog floristic data, the yellow-billed cuckoo will be at risk unless more long-term ecological investigation are initiated to determine specific habitat requirements. Many aspects of yellow-billed cuckoo ecology have not been adequately investigated. Long-term, multi-scale, integrated, multi-disciplinary research are needed to address basic life history questions. Time, energy, and habitat utilization studies should be a high priority for anyone interested in protecting cuckoo habitat. More research is also required on migratory routes and dispersal mechanisms which are virtually unknown. Optimistically, GIS, GPS, spatial-based analytical tools, and remote sensed imagery techniques may provide a means for ecological insight. However, without consistent long-term funding it is doubtful that significant ecological advances can be made to adequately understand why western populations of the Yellow-billed Cuckoo have been declining dramatically.
 
 

Acknowledgements:

  We would like to thank the USGS Biological Resources Division Regional Office and staff for project funding to do the field work necessary to conduct this preliminary investigation; Dr. William Halvorson, Unit Leader, USGS BRD Sonoran Desert Field Station at the University of Arizona for his dedicated support of graduate students, field assessment activities, and the necessary disk drives to store the data; Dr. Charles Van Riper, Unit Leader, USGS BRD Colorado Plateau Field Station, Flagstaff, and his staff for census work, data sharing, and digitizing efforts; Mr. Robert MaGill, Arizona Game and Fish Department for project coordination; Ms. Murrelet Halterman for her practical advice and yellow-billed cuckoo expertise; The School of Renewable Natural Resources and the following Staff members and graduate students who assisted with the project and related field work: Mr. Craig Wissler, Ms. Patty Guertin, and Mr. Volodymyr Ivakhnyk; We also thank Mr. Douglas Richardson of Baker-GeoResearch Inc. (Billings, Montana) for his support and the educational use of Geolink mapping software to train a new generation of students on GPS technologies.
 
 

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Author Information:

Michael R. Kunzmann is an Ecologist at the USGS Sonoran Desert Field Station which is located within the School of Renewable Natural Resources. The School of Renewable Natural Resources is in the College of Agriculture and is centrally located on The University of Arizona campus. Correspondence may be addressed: Michael R. Kunzmann, USGS Sonoran Desert Field Station, The University of Arizona, 125 Biological Sciences East, Tucson, Arizona, 85721. Mr. Kunzmann may also be reached by telephone at (520) 621-7282 or by email: mrsk@sherpa.srnr.arizona.edu.

Alexander R. Rybak is an Associate Researcher at the USGS SDFS, an exchange scholar at the School of Renewable Natural Resources at the University of Arizona, and a Landscape Ecologist at the Ukrainian Academy of Agrarian Sciences - National Botanical Gardens. Correspondence may be addressed: Alexander R. Rybak, C/O USGS Sonoran Desert Field Station, The University of Arizona, 125 Biological Sciences East, Tucson, Arizona, 85721. Mr. Rybak may also be reached by email: ryback@excite.com.

Peter S. Bennett is an Ecologist at the USGS SDFS which is located within the School of Renewable Natural Resources. The School of Renewable Natural Resources is in the College of Agriculture and is centrally located on The University of Arizona campus. Correspondence may be addressed: Peter S. Bennett, USGS Sonoran Desert Field Station, The University of Arizona, 125 Biological Sciences East, Tucson, Arizona, 85721. Mr. Bennett may also be reached by telephone at (520) 670-6886.