House Wren use of Riparian Corridors

PROJECT JUSTIFICATION

The South Platte Wildlife Management Area (SPWMA) is a 5,908 Ha property consisting of about 40km of floodplain forest with surrounding upland prairie (Knopf 1986). Riparian forests such as that which occurs along the South Platte River have been of particular interest to researchers investigating avian use of riparian corridors during migration (Machtans et al. 1996, Skagen et al. 1998), and juvenile dispersal (Machtans et al. 1996). A riparian corridor is a strip of vegetation that connects two or more larger patches, and through which an organism will likely move over time (Fischer and Fischenich 2000). Regardless of size or degree of connectivity, many studies have shown these vegetation strips along rivers support a higher diversity and abundance of birds than adjacent upland forests or grasslands (Stauffer and Best 1980, Tockner and Ward 1999). Periodic inundation of alluvial landscapes creates a shifting mosaic of aquatic and terrestrial transition zones (Tockner and Ward 1999). This ever-changing mosaic paired with increased water quality (Fischer and Fischenich 2000) results in the increased biodiversity.

In 1980, researchers inventoried breeding bird communities at the South Platte River WMA in both riparian and upland areas and compared species densities between them (Knopf 1980). Their results indicated that the floodplain forest is valuable habitat for both resident and migratory species; while 38 species occurred along the river's edge, only 9 species were present in the adjacent upland. In addition, 30 species were observed only in the floodplain, suggesting that these birds may not have been present at SPWMA in the absence of a riparian forest. Yet another surprising finding of this study was that House Wrens made up more than 20% of the bird community within the floodplain with an estimated density of 3.3 birds/Ha.

House Wrens are secondary cavity nesters (SCN), and further studies have found that density of large trees, length of dead limbs and cavity density are the most important habitat variables for density of House Wrens at SPWMA (Sedgewick and Knopf 1990). Furthermore, cottonwoods are probably critical in creating suitable nesting habitat, and a lack of regeneration due to inundation could reduce the overall density of cavity nesters (Sedgewick and Knopf 1990). Many bird species not requiring cavities however, such as Brown Thrasher and Spotted Towhee, do not appear to be as immediately affected by flooding (Knopf and Sedgewick 1987). In 1992, researchers at SPWMA found that SCN bird density was indeed being limited by cavity availability along the river (Sedgewick and Knopf 1992).

Knopf's studies over 30 years ago continues to be relevant to this day. As modern day urban sprawl encroaches on to natural landscapes, research on areas important to wildlife remains crucial. It is our goal to continue this study by assessing House Wren use of the area, by estimating House Wren density both within the wooded area, and in the adjacent upland using point counts. Furthermore, we would like to gain insight into whether House Wrens use this riparian corridor for dispersal movements through grasslands.

OBJECTIVES

The purpose of this study is to estimate House Wren density along the South Platte River floodplain near Crook, Colorado using circular plot surveys. Specifically, our objectives are to:

1. Compare House Wren use of a riparian forest and the adjacent prairie within the SPWMA;
2. Estimate density of House Wrens within the riparian woodland and extrapolate this to other floodplain regions in the United States; and
3. Compare this density with that of previous densities estimated in 1980.

METHODS

Survey Design

Woodland vs. Upland Point Counts

Building off of Knopf's 1980 study at this location, we will conduct 60- 6 minute (Thompson and Schwalbach 1995) point counts along the riparian woodland area encompassing about 3,800 Ha, and 60 counts within the adjacent upland area of 22,560 Ha. Points in both areas were created using the create random points tool in ArcMap 10.4.1, with a 300m allowance between points (Fig. 1). Any points falling in the river were moved to another random location. These surveys will be conducted between 24 May and 27 May.

Riparian Woodland Use Point Counts

Using a similar survey design, another set of 155 surveys will be conducted within the riparian woodland only. Although the efficiency in detecting new birds decreases after 3 visits to the same point (Smith et al. 1995), surveys will be replicated 4 times between 10 May and 26 May to adhere to Knopf's study. These survey locations were placed within the riparian buffer using a 200m allowance (Gutzwiller 1991) between points. These surveys will give a more accurate depiction of House Wren use of the woodland.

Figure 1- Point count design

Point Count Protocol

Observers will use Garmin GPSMAP64 GPS units (Garmin Ltd., Schaffhausen, Switzerland) to navigate to each point. Observers will arrive at the first point of the day 30 minutes before sunrise, and wait silently for 5 minutes to allow birds to reposition themselves. Using a stopwatch, observers will recording all birds they see or hear for 6 minutes. All birds detected within 200m will be recorded (Savard and Hooper 1995, Thompson and Schwalbach 1995, Wolf et al. 1995), along with the radial distance to the bird from the point using a Nikon Aculon AL11 6x20 laser range finder (Nikon Corporation, Tokyo, Japan). Surveys will continue until 3 hours after sunrise (Lynch 1995). Additional environmental information will be recorded according to the provided survey data sheet (Appendix A).

Assumptions in Survey Design

In order to extrapolate the House Wren use of the surveyed area to the entire study area, we must meet two assumptions in regards to our survey design. These assumptions are critical to address before implementing the survey to ensure extrapolation is possible. First, the points must be randomly located. This states that to the best of our knowledge, the surveyed area is representative of the entire study region. In addition, we need a large sample of points (>20 points) that are evenly distributed across the study region. A sample of 60 points in each habitat meets this criteria, and an even distribution was achieved through use of a 200m allowance between points.

Analysis

Detection Function

The probability of detecting a bird, given that it is a distance r from the observer is the detection function, denoted by g(r). This value will tell us how many House Wrens we are detecting relative to the "real" number of House Wrens in a survey. This is important to know, as not every individual is usually detected. We expect to see a detection function that has a broad shoulder and then decreases as distance increases (Thomas et al 2010). This means that the observer detects birds that are nearby at a higher rate, and as the distance from observer to bird increases, detection ability falls.

Distance Sampling Assumptions

In order to obtain reliable density estimates from point counts, we must meet several critical assumptions. The first is that birds are distributed independently of the point, which we did by placing the points at random locations. Secondly, we assume that birds directly on the point are detected with certainty, or g(0)=1. Third, all objects are recorded at their original location, prior to movement in response to the observer. Since observers are not moving, and utilize a resting period before a survey begins, point counts for a House Wren seems to be advantageous over a line transect. Next, all distances recorded are assumed to be accurately measured. This assumption will be met since observers will be using a range finder. Lastly, all detections are assumed to be independent from one another. This means that the presence of one House Wren will not attract or deter another wren from being present.

Density Estimates

Density estimates will be attained using DISTANCE 7.0 (CREEM, St. Andrews, Scotland). Since we already know that density and habitat differs to some degree between the forested and upland areas, we made sure to stratify the survey area into upland and riparian. Thus, density estimates will be calculated separately for each habitat. Density in point counts are calculated using the following equation (Thomas et al. 2006):

where k is the number of points, w is the radius of each plot, and n is the number of birds detected within the plot. Once we have calculated House Wren density for both prairie and woodland habitats, we can also obtain global(overall) density for the entire area. This is done using the individual area sizes, and overall density for both habitats, in the following equation (Thomas et al. 2006):

EXPECTED RESULTS AND BENEFITS

With the South Platte River watershed encompassing such a large area, it is important to know how any land management practices would alter the bird community and secondary cavity nesters such as the House Wren. The proposed study will increase our knowledge of avian use of the woodland area surrounding the Platte River, which in turn will aid in future habitat alteration decisions.

If funding for the proposed project is given, the project would start right away. Reports of raw abundance and estimated density will be submitted annually, and a final report in the form of a thesis will be presented at project closure.

Project Deliverables will include:

• Annual Report of House Wren abundance and densities in each habitat.
• Final report by end of study discussing results and future considerations; final report will be in the form of a thesis.

ENDANGERED SPECIES CONSIDERATIONS

No special considerations need to be taken for the project in regards to endangered species, as our surveys will be non-invasive and do not require capture of animals.

NECESSITY AND ETHICAL USE OF ANIMALS

We will not be trapping or coming in contact with the study animals, however all federal and state guidelines regarding use of animals will be properly followed.

PERSONNEL

This study will require 3 avian survey technicians in order to meet the goals of the project. Two biologists already trained in identification of Colorado birds will be obtained through the Texas A&M job board. The third person involved in this project will be a master's students at Texas A&M University- Kingsville, and will act as the project leader.

• 2 field technicians to conduct point count surveys and enter data
• 1 project leader (M.S. student) to conduct surveys and coordinate survey methodology

BUDGET

Year1:$2.91 Flagging tape (Walmart), 3 at $0.97

$509.97 Laser rangefinder (Nikon Aculon AL11 6x20), 3 at $169.99

$599.97GPS unit (Garmin GPSMAP64), 3 at $199.99

$1000.00Apartment rental for one month

$1,200. 00Rental truck (AVIS)

$3200.00Technician salary, 2 at $1600.00 for one month

Total:$6512.85

Year 2:$1000.00Apartment rental for one month

$1,200. 00Rental truck (AVIS)

$3200.00Technician salary, 2 at $1600.00 for one month

Total:$5400.00

Year 3:$1000.00Apartment rental for one month

$1,200. 00Rental truck (AVIS)

$3200.00Technician salary, 2 at $1600.00 for one month

Total:$5400.00

Project Total:$17,312.85

TIME SCHEDULE

2017Activity

May 1-5Place flagging tape and distance markers at appropriate locations.

May 10-23Conduct surveys within riparian woodland

May 24-27Continue riparian woodland use surveys

Begin woodland and prairie comparison surveys

May 28Take down flagging tape and distance markers, data entry

JuneData analysis

July 312017 annual report turned in

2018Activity

May 1-5Place flagging tape and distance markers at appropriate locations.

May 10-23Conduct surveys within riparian woodland

May 24-27Continue riparian woodland use surveys

Begin woodland and prairie comparison surveys

May 28Take down flagging tape and distance markers, data entry

JuneData analysis

July 312018 annual report turned in

2019Activity

May 1-5Place flagging tape and distance markers at appropriate locations.

May 10-23Conduct surveys within riparian woodland

May 24-27Continue riparian woodland use surveys

Begin woodland and prairie comparison surveys

May 28Take down flagging tape and distance markers, data entry

JuneData Analysis

July 312019 annual report turned in

DecemberFinal report turned in as M.S. thesis

LITERATURE CITED

Fischer, R.A., and J.C. Fischenich. 2000. Design recommendations for riparian corridors and vegetated buffer strips (No. ERDC-TN-EMRRP-SR-24). Army Engineer Waterways Experiment Station, Vicksburg, MS. Engineer Research and Development Center.

Gutzwiller, K.J. 1991. Estimating winter species richness with unlimited-distance point counts. The Auk 108(4):853-862.

Knopf, F.L. 1986. Changing landscapes and the cosmopolitism of the eastern Colorado avifauna. Wildlife Society Bulletin 14(2):132-142.

Knopf, F.L., and J.A. Sedgewick. 1987. Latent population responses of summer birds to a catastrophic, climatological event. The Condor 89: 869-873.

Lynch, J.F. 1995. Effects of point count duration, time-of-day, and aural stimuli on detectability of migratory and resident bird species in Quintana Roo, Mexico. General Technical Report. PSW-GTR-149. USDA Forest Service.

Machtans, C.S., M.A. Villard, and S.J. Hannon. 1996. Use of riparian buffer strips as movement corridors by forest birds. Conservation Biology 10(5):1366-1379.

Savard, J.L., and T.D. Hooper. 1995. Influence of survey length and radius size on grassland bird surveys by point counts at Williams Lake, British Columbia. General Technical Report. PSW-GTR-149. USDA Forest Service.

Sedgewick, J.A., and F.L. Knopf. 1992. Cavity turnover and equilibrium cavity densities in a cottonwood bottomland. The Journal of Wildlife Management 56(3):477-484.

Sedgewick, J.A., and F.L. Knopf. 1990. Habitat relationships and nest site characteristics of cavity-nesting birds in cottonwood floodplains. The Journal of Wildlife Management 54(1):112-124.

Skagen S.K., C.P. Melcher, W.H. Howe, and F.L. Knopf. 1998. Comparative use of riparian corridors and oases by migrating birds in southeast Arizona. Conservation Biology 12(4):896-909.

Smith, W.P., D.J. Twedt, R.J. Cooper, D.A. Widenfeld, P.B. Hamel, R.P. Ford. 1955. Sample size and allocation of effort in point count sampling of birds in bottomland hardwood forests. Monitoring bird populations by point counts. General Technical Report. PSW-GTR-149. Albany, CA. USDA, Forest Service, Pacific Southwest Research Station p. 7-18.

Stauffer, D.F., and L.B. Best. 1980. Habitat selection by birds of riparian communities: evaluating effects of habitat alterations. The Journal of Wildlife Management 44(1):1-15.

Thomas, L., S.T. Buckland, K.P. Burnham, D.R. Anderson, J.L. Laake, D.L. Borches, S. Strindberg. 2006. Distance sampling. Encyclopedia of Environmetrics.

Thomas, L., S.T. Buckland, E.A. Rexstad, J.L. Laake, S. Strindberg, S.L. Hedley, J.R. Bishop, T.A. Marques, and K.P. Burnham. 2010. Distance software: design and analysis of distance sampling surveys for estimating population size. Journal of Applied Ecology 47:5-14.

Thompson, F.R. and M.J. Schwalbach. 1995. Analysis of sample size, counting times, and plot size from an avian point count survey on Hoosier National Forest, Indiana. General Technical Report. PSW-GTR-149. USDA Forest Service.

Tockner, K., and J.V. Ward. 1999. Biodiversity along riparian corridors. Large Rivers 11(3):293-310.

Wolf, A.T., R.W. Howe, G.J. Davis. 1995. Detectibility of forest birds from stationary points in northern Wisconsin. General Technical Report PSW-GTR-149. USDA Forest Service, Pacific Southwest Research Station. Albany, CA.

Apendix A- data sheet for avian point counts at South Platte Wildlife Management Area

SOUTH PLATTE WILDLIFE MANAGEMENT AREA BIRD SURVEY

Site #: ________________Habitat Type: Prairie / WoodlandDate: __________________

Observer Name: __________________________Start Time: _________________________

Wind: calm light moderate strongTemperature: <40 41-50 51-60 61-70 >70

Cloud %: _________Precipitation: drizzle snow fog