Identifying Coastal Forest Merlin (Falco columbarius suckleyi) Breeding Habitat Using Geographical Information Systems Christopher M. Talley Western Washington University Abstract. The Coastal Forest Merlin (Falco columbarius suckleyi) natural breeding habitat has traditionally been located in the temperate rainforests of the Pacific Northwest of the United States and Canada. The natural habitat has experienced a significant reduction in habitat quantity due to anthropogenic influence over the last 150 years. Despite the reduction in their traditional habitat the Merlin has been able adjust to changes in habitat and expand their population. During each breeding season from 1986 to 2013, nest sites and home ranges were geographically located for a population of Coastal Forest Merlin (Falco columbarius suckleyi) in an 116,660 km² study area that encompassed areas of Northwestern Washington State and Southeastern and the Central Interior of British Columbia, Canada. Geographical Information Systems (GIS) and satellite imagery were used to determine and compare the amount, distribution, and configuration of several key habitat variables within 8km circular plots centered on known nest sites and random control sites. The plot size utilized for analysis was based on the observed distribution and behavioral characteristics of Merlins within the study area Analysis demonstrated that complex habitat edge configuration, greater spatial heterogeneity, and higher amounts of habitat richness were the most significant Merlin breeding habitat variables. The results of analysis are intended for landscape scale systematic analysis of breeding habitat variables, demographic assessments, and to guide recovery and management decisions. Key Words: Coastal Forest Merlin; Falco columbarius suckleyi; Raptors; Geographical Information Systems, habitat use; landscape ecology. INTRODUCTION In 2012, the Coastal Forest Merlin was listed in Washington State as a species of concern based on the declining amounts of suitable habitat throughout their range, declining population trends, and lack of existing regulatory methods to protect the species (WDRW, 2012). Habitat characteristics such as land cover, land use, vegetative composition, and spatial configuration are key elements that influence wildlife breeding success and species evolution (Rodiek & Bolan, 1991). In order to comprehensively understand the importance of land cover characteristics on a species viability and development, it is necessary to effectively model wildlife habitat in terms of spatial and land cover characteristics (Turner & Gardner, 1991). With increased importance being placed on spatial dynamics in relation to landscape ecology and species evolution, it important to utilize modeling methods that consider variety of environmental variables to produce relevant habitat models (Tutle. Et. al, 2006). Quantifying information about habitat characteristics such density and distribution over large geographical areas by field surveys can be expensive, time consuming, and impractical. To complete this task, computer derived habitat models created using Geographical Information Systems (GIS) can be used effectively to depict the vegetative and groundcover characteristics of a large study area
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Identifying Coastal Forest Merlin (Falco columbarius suckleyi) Breeding Habitat Using
Geographical Information Systems
Christopher M. Talley Western Washington University
Information Systems, habitat use; landscape ecology.
INTRODUCTION
In 2012, the Coastal Forest Merlin was listed in Washington State as a species of
concern based on the declining amounts of suitable habitat throughout their range, declining
population trends, and lack of existing regulatory methods to protect the species (WDRW, 2012).
Habitat characteristics such as land cover, land use, vegetative composition, and spatial
configuration are key elements that influence wildlife breeding success and species evolution
(Rodiek & Bolan, 1991). In order to comprehensively understand the importance of land cover
characteristics on a species viability and development, it is necessary to effectively model
wildlife habitat in terms of spatial and land cover characteristics (Turner & Gardner, 1991). With
increased importance being placed on spatial dynamics in relation to landscape ecology and
species evolution, it important to utilize modeling methods that consider variety of
environmental variables to produce relevant habitat models (Tutle. Et. al, 2006). Quantifying
information about habitat characteristics such density and distribution over large geographical
areas by field surveys can be expensive, time consuming, and impractical. To complete this task,
computer derived habitat models created using Geographical Information Systems (GIS) can be
used effectively to depict the vegetative and groundcover characteristics of a large study area
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(Lillesand and Kiefer, 1987). Geographic Information Systems significantly increase
productivity by allowing researchers to efficiently survey and analyze many aspects of wildlife
ecology without the spatial and temporal limitations of traditional methods (Shaw & Atkinson,
1990).
The purpose of this project was to create a GIS based landscape level habitat model to
evaluate breeding habitat characteristics of the Coastal Forest Merlin in a study area which
comprises areas of Northwestern Washington State and Southwestern British Columbia. The
model building process consisted of creating a digital database by compiling and interfacing
comprehensive digital vegetation and land cover data generated from Landsat 7 ETM+
multispectral data satellite imagery, vector and raster based political and environmental data
created by various agencies, and field gathered groundcover data.
The objectives of this study were to: 1) determine the quantity and spatial distribution of
different of habitat variables, 2) evaluate the relative importance of habitat variables on Merlin
distribution and abundance, and 3) investigate species demographics and density in different
habitat types. The information generated by this project is designed to provide knowledge and
guidance to help inform scientists, policy makers, and property owners in making prudent
resource management decisions that will help retain valuable habitat for the continued
reproductive success for the Coastal Forest Merlin.
Study Area
The habitat modeling described in
this report was conducted on an 116,660
km² (11,666,048 ha) study area spread
over portions of Northwestern Washington
State and Southeastern British Columbia
Canada. The study area was bounded
approximately by the geographical
coordinates of 128º W to 120 º W
longitude, and 46º N to 55º N latitude. The
land forms consist of highly developed
floodplains and coastal lowlands, heavily
forested and rugged coastal mountainous
regions, and drier inland moderate
elevation plateaus.
Land ownership is a broad mix of
public, private, and tribal owned lands.
The study area occupies parts of 4 distinct
ecologically and geographically defined
level III ecoregions; 1) the Puget Trough-
Georgia Basin, 2) the Pacific Northwest
coast., 3) the central interior of British
Columbia, and 4) North Cascade and
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Pacific range (Nature Conservancy,2006).
The Puget Trough- Georgia
Basin ecoregion occupies a long narrow
continental glacial trough that consists
of many islands, peninsulas, and inlets.
Elevations in the area range from sea
level to 750-1000 meters in the foothills.
The area is characterized by a mild
maritime climate with mild, wet winters.
Summers are fairly warm and dry and
often overcast. Mean January
temperature is 4° C and mean July
temperature is 18° C. Precipitation,
falling primarily as rain, averages 100
cm per year. The Olympic Mountains
created rain shadow areas that include
the northeast corner of the Olympic
Peninsula, Whidbey Island, and the San
Juan Islands. The annual precipitation
tends to be lower in these areas
averaging 40 to 75 cm.. Rainfall is
higher in the foothills due to the
orographic lift created by the Cascade
Mountains and averages 150-200 cm a
year.
The natural landscape consisted of thick coniferous forests that grew on areas consisting
of glacial moraines, floodplains, and river terraces. Douglas-fir (Pseudotsuga menziesii), western
hemlock (Tsuga heterophylla), western red cedar (Thuja plicata), and grand fir (Abies grandis) are the predominate species in the upland forests, while black cottonwood (Populus
trichocarpa), red alder (Alnus rubra), and big leaf maple (Acer macrophyllum) are the common
forest elements in riparian areas.
The Pacific Northwest Coast region includes the coastal Ranges of Northwestern
Washington State and Vancouver Island. The region has landforms that consist of beaches, low
marine terraces, sand dunes, and spits in the marine areas, headlands, high marine terraces, and
low mountains in the uplands, and the lower portions of the Olympic Mountains up to around
1200m in elevation. The Coast Range’s climate is influenced by cool, moist air from the ocean.
Mean January temperature is 6° C and mean July temperature is 12° C. Precipitation falls mainly
as rain at the lower elevations and averages 150- 250 cm a year, with some areas receiving
upward of 500 cm of rain a year. The coastal lowlands and low mountains are dominated Mature
forest consist primarily of Coast Douglas Fir (Pseudotsuga menziesii var. menziesii), western red
cedar, western hemlock, and Douglas fir. Pacific silver fir (Abies amabilis) and mountain
The derived data from NOAA and ESOD was combined and processed using ESRI
ArcMap 10.2 to create a 9 group habitat class map for the study area. The designated habitat
classes used for analysis were based on field assessments of land cover characteristics and
observed Merlin behavior, then correlated with the National Land Cover Database (NLCD)
classification system. (Drummond & Stillman, 2014; NLCD, 2006) See appendix A for
comprehensive descriptions of the habitat classes. In order to increase the accuracy of the
analysis, a mask was created to eliminate areas of open water, and areas above 1500 m in
elevation, the observed upper elevation limits of Merlin activity. The accuracy of the classified
image was verified using field gathered vegetation plot data as well as field data obtained from
United States Bureau of Land Management (BLM), and the British Columbia Ministry of Forests
(BC MOF). The classified image was resampled to a 25m² cell size in an effort to simplify
analysis rather than increase the accuracy. Prior to measuring landscape patterns, the spatial
analysis filter tool of ArcMap was used to perform low option 3x3 smoothing procedure of the
raster land cover map. The purpose of this step was to reduce the significance of anomalous cells
giving the map a greater relevance to natural landscape patterns.
Two types of metrics were analyzed to help define Merlin habitat: landscape composition
and landscape configuration (McGarigal & Marks, 1995). Composition refers to the abundance
of a land cover type or attribute, whereas configuration describes the spatial arrangement of
patches or features. Landscape composition characteristics of the habitat class map were
measured using the class metrics function of FRAGSTATS v4 spatial pattern analysis program
(McGarigal, Cushman, & Ene, 2012). Landscape pattern configuration variables for the study
were measured using the patch metrics function of FRAGSTATS.
Landscape scale habitat pattern characteristics were determined for areas within an 8km
radius (201.06 km²) plots centered on known nest sites. This area represents the observed extents
of Merlin's home range activity (Drummond & Stillman, 2014). 9 variables were utilized to
analyze habitat quality; 1) the total amount and percent of land cover contained in each of the 9
habitat classes, 2) patch density, a index of spatial heterogeneity; 3) the density of habitat edge
(m/ha), 4) the number of different habitat types within each 25m² cell defined habitat richness
(ha), 5) stream density (m/ha), 6) distance to riparian areas, 7) patch shape which indicates the
geometric complexity of the patch, 8) the amount of impervious surfaces, and 9) the percentage
of forest canopy cover.
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Standardized residuals of each variable were tested for normality. Independent sample t-
tests were employed to test the distribution of habitat variables between “used” habitat plots and
“random” plots. Additional analysis of nest site density and habitat associations was conducted
using Pearson correlation coefficient testing. Statistical analysis testing was conducted using
SAS 9.3 (SAS Institute, Cary NC). Due to the conservation status of the Pacific Forest Merlin, an
alpha level of <0.05 was selected for all tests of significance (WDFW, 2013).
Ground Plots
Habitat microhabitat structure and configuration play a vital role in a land bird’s selection
of breeding territory and nest site (James & Shugart, 1970; Block & Brennan, 1993). In an effort
to depict the full spectrum of vegetative and physiographic characteristics reference 238
vegetation plots were collected during field assessments. The 25 m radius (0.196 ha) vegetation
plots were delineated and surveyed near Coastal Forest Merlin nest sites during the study period.
The classes defined in the process were designed to represent the various types habitat Coastal
Forest Merlin encounter in association with different aspects of their behavior.
RESULTS
Land Cover Characteristics
Analysis of habitat landscape configuration and composition was conducted on 70
individual non overlapping 8km radius (201.06 km²) home range plots centered on known
Merlin nest sites, and 33 randomly generated (Figure 3). In the 70 used home range plots the
largest habitat classes in terms of total area were conifer forest which comprised 3108.46 km²/
58.42 %; followed by; mixed forest 486.71 km²/ 9.15 %; shrub/scrub 412.90 km² / 7.76%,
agriculture 362.43 km²/ 6.35%, and developed low intensity 337.92 km²/ 6.14 %. The rest of the
habitat classes individually made up less than 5% of the groundcover in the analyzed regions
each (Table 1). Bare land constituted 0.38% of the land cover and was eliminated from analysis.
0
500
1000
1500
2000
2500
3000
3500
4000
4500
5000
Agriculture Deciduous
Forest
Developed Open
Space
Evergreen Forest High Intensity
Developed
Low Intensity
Developed
Medium Intensity
Developed
Mixed Forest Scrub/Shrub
Habitat Class
Sq
uare
Kil
om
ete
rs
Figure 3. Abundance and distribution of habitat classes within 70 201 km² analysis plots.
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0
500
1000
1500
2000
2500
3000
3500
4000
4500
5000
Agriculture Deciduous
Forest
Developed Open
Space
Evergreen Forest High Intensity
Developed
Low Intensity
Developed
Medium Intensity
Developed
Mixed Forest Scrub/Shrub
Habitat Class
He
cta
res
Figure 4. Mean amounts and standard deviation of habitat classes within 20106 ha (201 km²) analysis plots.
Table 1. Description of classes used to characterize the breeding habitat of Coastal Forest Merlin.
Habitat Type Code Description
Developed
High Intensity HID
Industrial, commercial, and high density residential areas with 80-100% impervious surfaces.
These are zones cleared of major vegetation and include land cover such as concrete, tarmac, or
buildings.
Developed
Medium
Intensity
URES
Medium density residential, commercial and small city parks with 50-79% impervious surfaces.
Generally consist of areas of mixed deciduous/conifer forest, as well as non-native species.
Canopies have a low average percentage of vertical cover. Many non-native species are mixed
with natives trees to make a mixed, low density forest that usually have a minimum of 30%
conifer composition. Patches of vegetation are frequent but highly fragmented. The edge
interface between patches is generally complex in shape.
Developed
Low Intensity RRES
Rural areas with varying amounts of low density residential or commercial activity with 20-49%
impervious surfaces Contains groundcover that consists of a mix of shrub, herbaceous, and
forested areas of mixed species and seral development of conifers and hardwoods. These areas
have similar characteristics as developed medium density, but generally have smaller patch size
Developed
Open Space OPEN
Developed rural and urban areas that include; agriculture, pasture, grasslands, and utility
corridors. Generally have low height vegetation, and square edge configuration
Agriculture AGRI Areas of agricultural, pasture, and human created grassy area. Vegetation ≤ 2 m
Young Forest YOUNG
Early seral stage successional forests with an open or patchy canopy structure. Trees >5m tall,
>20% cover, >75% tree species shed foliage Usually riparian or disturbed areas with Red Alder,
Black Cottonwood, Big Leaf Maple, Vine Maple, conifer saplings and various shrubs.
Mixed Forest INTER
Areas of mixed forest in mid seral development with a patchy canopy closure; Trees >5m tall, >20% cover.
Contains a variety of species consisting of Douglas Fir, Western hemlock, Western red cedar, with some
Hardwoods as well. Arboretums, larger parks, some golf courses, and wooded reserves within areas of more
intense human activity.
Conifer Forest OGM
Mid and late stage seral conifer forest with a heterogeneous spatial configuration. Trees >5m
tall, >20% cover, >75% species maintain leaves. Typical species include Douglas Fir, Western
Hemlock, Western red cedar, grand fir, and Sitka spruce. These forests show a diversity of tree
ages and species, indicating a natural succession. Saplings to snags, young trees to trees
decaying from old age are represented. Patch size and core area tends to be relatively large.
Shrub/Scrub SCRUB
Non forested areas consisting of bare ground, small shrubs, saplings, or herbaceous groundcover
Shrubs/trees <5m tall, >20% cover. These areas consist of recent clear cuts, construction sites, or
areas of disturbance.
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National Land Cover Database 2006 (NLCD200)
Coastal Forest Merlin Distribution and Density In Different Habitat Classes
The distribution and abundance of a Coastal Forest Merlin population was surveyed from
1986 to 2013. For the purposes of this project, a sample of 219 individual Coastal Forest Merlin
nest sites was used for analysis (Figure 3). Merlin nest sites were located in 4 of the 9 defined
habitat classes; conifer forest, mixed forest, developed medium intensity and developed low
intensity. The highest number of nest sites were located in the conifer forest class; 82, followed
by developed medium intensity 77, mixed forest; 37, and developed low intensity; 23.
The observed nest site densities were significantly higher in the developed medium
intensity and developed low intensity classes than Conifer and Mixed forest. Demographic
surveys revealed that the highest density of Merlin nest sites was located in the developed
medium intensity class which contained 77 of 219 nests or 35.16 % despite the class only
representing 577.08 km² or 4.10% of the available habitat in their home ranges. Similar
associations were noted in the developed low intensity class which contained 23 of 219 nest or
16.89% of 864.21km² or 6.14% of the available habitat.
Habitat Associations
Coastal Forest Merlin Preference
for habitat groundcover composition and
configuration as well as other geographic
and environmental factors was evaluated
by comparing the habitat characteristics
of used home range plots with randomly
generated home range plots. Refer to
appendix B for complete habitat variable
descriptions. In terms of topographic and
hydrographic features Coastal Forest
Merlins utilized locations that were
located in areas with a closer proximity
to areas with greater stream density
(TSD, t = 6.07, df = 105, P < 0.05),
closer to riparian areas (RIPA, Z = -5.59,
df = 105, P = 0.0003), and locations that
were lower in elevation (ELEV, t = 2.15,
df = 105, P < 0.05). In terms of landscape
configuration, Merlin sites were found
more frequently than in habitat classes
with a lower level of patch density
( PD, t = 3.22, df =105 , P = < 0.05),
greater edge density ( ED, t = 9.19, df =
105, P < 0.05), and greater complexity of
patch shape ( SHAPE, t = 2.12, df =105,
P < 0.05).
9
Nest site density had a moderately negative level of correlation for the amount of
impervious surfaces near nest sites (P = 0.22, r² = 0.41, ß = -0.64). Nest sites were located in areas
ranging from 0-75 % impervious ground cover. Nest site densities were not strongly correlated
with the percent forest cover (P = 0.67, r² = 0.14, ß = 0.35). 31 nest sites were located in areas with 5-
30% forest cover while areas with area with greater than 55% forest cover had consisted of 27
nest sites. Table 2. Comparisons of landscape characteristics for Coastal Forest Merlin study plots sampled in the study area. Values are means (± SD).
J.(2011). Completion of the 2006 National Land Cover Database for the Conterminous United
States, PE&RS, Vol. 77(9):858-864.
Glenn, E.M, & Ripple, W.J. (2004). On Using Digital Maps to Assess Wildlife Habitat. Wildlife Habitat
Mapping, 32(3):852-860, pp. 852-860.
Global Raptor Information Network. (2014). Species account: Merlin Falco columbarius. Downloaded
fromhttp://www.globalraptors.org on 21 Sep. 2014
Gratto-Trevor, C.L. (1995). Use of Landsat TM Imagery in Determining Important Shorebird Habitat in
the Outer Mackenzie Delta, Northwest Territories. Artic, VOL. 49, NO. 1 (March 1996) P. 11– 22
Homer, C.G., Edeards, T.C., Ramsey, R.D., & Price, K.P. (1993) Use of Remote Sensing In Modeling
Sage Grouse Winter Habitat. The Journal of Wildlife Management, Vol. 57, No. 1 (Jan., 1993),
pp. 78-84
Iachetti, P., J. Floberg, G. Wilhere, K. Ciruna, D.Markovic, J. Lewis, M. Heiner, G. Kittel, R.
Crawford,S. Farone, S. Ford, M. Goering, D. Nicolson, S. Tyler, and P. Skidmore. (2006). North
Cascades and Pacific Ranges Ecoregional Assessment, Volume 1 - Report. Prepared by the
Nature Conservancy of Canada, The Nature Conservancy of Washington, and the Washington
Department of Fish and Wildlife with support from the British Columbia Conservation Data
Centre, Washington Department of Natural Resources Natural Heritage Program, and
NatureServe. Nature Conservancy of Canada, Victoria, BC. James, F.C. & Shugart, H.H. Jr. (1970). A quantitative method of habitat description. Audubon Field
Notes 24, 727–736.
Johnsgard, P.A. (1990). Hawks, eagles, and falcons of North America. Smithsonian Institution Press,
Washington, D.C.
Johnston, R.M., & Barson, M.M. (1993). Remote sensing of Australian wetlands: An evaluation of
Landsat TM data for inventory and classification. Australian Journal of Marine and Freshwater
Research, 44:235–252.
Kittle, G., Cadrin, C., Markovic, D., Stevens, T. (2011). Central Interior Ecoregional Assessment:
Terrestrial Representation in Regional Conservation Planning. Journal of Ecosystems and
Management, North America, 12, may. 2011. Available at:
<http://jem.forrex.org/index.php/jem/article/view/103/58>. Date accessed: 22 Sep. 2014.
Knutson, K. L., and V. L. Naef. (1997). Management recommendations for Washington’s priority
habitats: riparian. Wash. Dept. Fish and Wildlife. Olympia. 181pp.
Lillesand, T.M. & Kiefer, R.W. (2000). Remote sensing and image interpretation, 4th edn. John Wiley