Habitat Selection by Red-Breasted Sapsucker (Sphyrapicus

Home , Sapsucker

HABITAT SELECTION BY RED-BREASTED SAPSUCKER (SPHYRAPICUS

RUBER) IN SOUTHEAST ALASKA OLD-GROWTH FOREST

Marlene A. Wagner

A Thesis

Presented to

The Faculty of Humboldt State University

In Partial Fulfillment

Of the Requirements for the Degree

Master of Science

In Natural Resources: Wildlife

March, 2011

ABSTRACT

Habitat Selection by Red-breasted Sapsucker (Sphyrapicus ruber) in Southeast Alaska Old-Growth Forest

Marlene A. Wagner

Conservation of a keystone species requires knowledge of habitat use across the species’ range. The factors that influence habitat selection by Red-breasted Sapsucker

(Sphyrapicus ruber) in the temperate rainforests of southeast Alaska are poorly understood. I examined habitat selection of this keystone species during the breeding season in 2008 and 2009. I quantified the structural characteristics of sapwell trees and compared them to trees without sapwells, and I located nests to describe nest trees and compare characteristics of used and available nest trees and nest sites using model selection techniques. Sapsuckers selected trees for building sapwells that were intermediate in size, had high bark furrow depth, and had a greater incidence of conks and dwarf mistletoe. Nesting Sapsuckers did not show bias for cavity orientation and nest trees were predicted primarily by size and the presence of fungal infection at intermediate stages of decay. Nest sites contained a lower volume of trees, higher DBH, increased incidence of fungal infection, and older decay classes of coarse woody debris than available sites. These findings suggest that during the breeding season, Red- breasted Sapsuckers select habitats with attributes characteristic of the full range of old- growth forest succession, and they therefore may need substantial forest structural diversity for their feeding and nesting activities. The results from this study provide

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information that can be used to identify habitat for breeding and foraging Red-breasted

Sapsuckers. Due to their status as a keystone species, maintaining adequate breeding habitat in southeast Alaska is important not only to the local population of Red-breasted

Sapsuckers, but for other species as well.

ACKNOWLEDGEMENTS

I thank my major advisor, Dr. Matt D. Johnson, for his advice and guidance throughout this project. I thank Dr. Mark A. Colwell and Dr. T. Luke George for their comments both in the preparation of this study and in reviewing the manuscript. I extend my gratitude to those that provided field assistance and good humor in bad weather:

Jessica M. Engle, Karisa L. Garner, and E. Sam Neuwirth. Fellow graduate students

Michael A. Hardy, Joe A. LaManna, Shannon W. Murphie, and Jared T. Wolfe provided instrumental advice, support, and friendship. Dr. C. John Ralph and Dr. Carol Ralph continually offered mentorship, assistance, and encouragement. Alisa and Iris Tripp supplied accommodation and jovial perspective during both field seasons in Alaska. Dr.

Steve Herman provided me with initial inspiration into the world of ornithology and field biology, for which I will always be thankful.

Everyone at the United States Forest Service, Petersburg Ranger District, offered cheerful assistance with this research. Wildlife Biologist Chuck Parsley, Cabins Manager

Jeff W. Robinson, and Petersburg District Ranger Chris Savage were particularly helpful.

I am especially grateful to Brad L. Hunter, dedicated Wilderness Manager and bird lover, without whom this project would not have been possible.

Most importantly, I would like to express my love and thanks to my brother,

Milton A. Wagner, for his unconditional support and encouragement throughout this adventure.

TABLE OF CONTENTS

Page

ABSTRACT ...... iii

ACKNOWLEDGEMENTS ...... v

TABLE OF CONTENTS ...... vi

LIST OF TABLES ...... viii

LIST OF FIGURES ...... x

LIST OF APPENDIXES...... xi

INTRODUCTION ...... 1

METHODS ...... 5 Study Area ...... 5 Sapwell Trees ...... 8 Nest Trees ...... 10 Nest Sites ...... 12 Statistical Analysis ...... 15 Sapwell Tree Selection ...... 15 Nest Tree Selection ...... 15 Nest Site Selection ...... 16 Model Selection and Evaluation ...... 17

RESULTS ...... 19 Sapwell Trees ...... 19 Nest Trees ...... 24 Nest Sites ...... 29

TABLE OF CONTENTS (CONTINUED)

Page

DISCUSSION ...... 33 Sapwell Trees ...... 33 Nest Trees ...... 34 Nest Sites ...... 35 Management Implications ...... 36

LITERATURE CITED ...... 38

APPENDIX ...... 46

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LIST OF TABLES

Table Page

1 Average and standard error of covariates sampled at Red-breasted Sapsucker sapwell trees (n = 33) and available trees (n = 503) in Petersburg Creek-Duncan Salt Chuck Wilderness, Alaska, in 2008...... 21

2 Top five candidate models plus the null for predicting Red-breasted Sapsucker sapwell trees in Petersburg Creek-Duncan Salt Chuck Wilderness, Alaska, in 2008...... 22

3 Parameter estimates for the top three averaged models predicting Red- breasted Sapsucker sapwell trees in Petersburg Creek-Duncan Salt Chuck Wilderness, Alaska, in 2008...... 23

4 Average and standard error of Red-breasted Sapsucker nest tree (n = 31) characteristics in Petersburg Creek-Duncan Salt Chuck Wilderness, Alaska, in 2008 and 2009...... 25

5 Average and standard error of covariates sampled at Red-breasted Sapsucker nest trees (n = 31) and available trees (n = 150) in Petersburg Creek-Duncan Salt Chuck Wilderness, Alaska, in 2008 and 2009...... 26

6 Top five models plus the null for predicting Red-breasted Sapsucker nest trees in Petersburg Creek-Duncan Salt Chuck Wilderness, Alaska, in 2008 and 2009 ...... 27

7 Parameter estimates for the top model predicting Red-breasted Sapsucker nest trees in Petersburg Creek-Duncan Salt Chuck Wilderness, Alaska, in 2008 and 2009 ...... 28

8 Average and standard error of covariates sampled at Red-breasted Sapsucker nest plots (n = 31) and available plots (n = 31) in Petersburg Creek-Duncan Salt Chuck Wilderness, Alaska, in 2008 and 2009 ...... 30

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LIST OF TABLES (CONTINUED)

Table Page

9 Top five candidate models predicting Red-breasted Sapsucker nest-site selection in Petersburg Creek-Duncan Salt Chuck Wilderness, Alaska, in 2008 and 2009 ...... 31

10 Model-averaged parameter estimates for the top two ranking models predicting Red-breasted Sapsucker nest sites in Petersburg Creek-Duncan Salt Chuck Wilderness, Alaska, in 2008 and 2009 ...... 32

LIST OF FIGURES

Figure Page

1 Petersburg Creek Duncan-Salt Chuck Wilderness (in green) on Kupreanof Island in Tongass National Forest of southeast Alaska ...... 6

2 Locations of sapwell tree plots in Petersburg Creek-Duncan Salt Chuck Wilderness, Alaska, in 2008 ...... 9

3 Location of 62 paired Red-breasted Sapsucker nest sites and available sites at 3 field camps within Petersburg Creek-Duncan Salt Chuck Wilderness, Alaska, in 2008 and 2009...... 11

4 Plots were centered around nest trees (in purple) and locations measured at a random distance 50 to 100 m away at a random azimuth to compare habitat characteristics at Red-breasted Sapsucker nest sites and available sites in Petersburg Creek-Duncan Salt Chuck Wilderness, Alaska, in 2008 and 2009 ...... 14

LIST OF APPENDIXES

Appendix Page

1 Candidate model set for predicting Red-breasted Sapsucker sapwell trees in Petersburg Creek-Duncan Salt Chuck Wilderness, Alaska, in 2008 ...... 46

2 Candidate model set for predicting Red-breasted Sapsucker nest trees in Petersburg Creek-Duncan Salt Chuck Wilderness, Alaska, in 2008 and 2009...... 47

3 Candidate model set for predicting Red-breasted Sapsucker nest sites in Petersburg Creek-Duncan Salt Chuck Wilderness, Alaska, in 2008 and 2009...... 48

INTRODUCTION

Southeast Alaska holds the largest remnant of lowland temperate rainforest, encompassing one-third of total temperate old-growth rainforest left on Earth (Alaback

1991, Schoen and Dovichin 2007). However, within southeast Alaska, only two percent of the most productive old-growth stands remain (O’Clair et al. 1997). Old-growth forest stands are important to ecosystem processes because they contain more structural diversity and function than younger forests (Thomas et al. 1988). Additionally, old- growth forests provide an opportunity to examine ecological processes unfettered by anthropogenic disturbance and therefore are useful for collecting baseline data with which to compare effects of ecosystem disturbance.

Old-growth forests are threatened by a number of anthropomorphic activities, including fire suppression, habitat conversion, climate change, and introduced pathogens

(Agee 1993). However, the greatest loss of temperate old-growth rainforests is associated with the cutting of trees for forest products. Timber harvest, especially in the form of clear-cutting, reduces the abundance of legacy structures essential to the habitat needs of many species of flora and fauna. Legacy structures are old-growth trees that have withstood natural or other stand-replacing events (Franklin et al. 2002, Mazurek and

Zielinski 2004) and are vital for cavity-nesting wildlife species. Forest management plans attempting to protect biodiversity and wildlife must therefore be attentive to the needs of this specialized guild of animals.

Yellow-bellied Sapsucker (Sphyrapicus varius), Red-naped Sapucker (S. nuchalis), and Red-breasted Sapsucker (S. ruber) were originally considered the same species, “Yellow-bellied Sapsucker.” However, studies conducted after the advent of molecular techniques demonstrated that this taxonomic unit actually represents three distinct species (Walters et al. 2002). Among these closely-related species, Alaskan populations of the Red-breasted Sapsucker are the most poorly understood. Prior to

1983, the majority of research done on sapsuckers was in eastern North America or conducted on Red-naped Sapsuckers in the Rocky Mountains (Walters et al. 2002).

Few studies have focused explicitly on populations of Red-breasted Sapsuckers that inhabit the coastal region from southeast Alaska to Northern California (Suring 1985, Joy

2000). In addition, most studies involving Red-breasted Sapsuckers have been in conjunction with other cavity-nesting birds (see Mannon et al. 1980, Lundquist 1988,

Nelson 1988, Bate 1995, Mahon et al. 2008), and thus there is a paucity of information on the biology specific to Red-breasted Sapsuckers.

A Habitat Capability Model (HCP) was developed for breeding Red-breasted

Sapsuckers in southeast Alaska (Suring 1988). This HCP, however, was based on material gleaned from literature on other Sphyrapicus species as well as a study from southeast Alaska that examined standing dead trees with cavities. The density of standing dead trees with cavities was quantified by forest type, but without knowledge of what excavator species created the cavities (Hughes 1985).

Studies on southeast Alaska Red-breasted Sapsuckers (hereafter, sapsuckers) are critically needed as the species is known to play a double keystone species role within their biotic communities (Daily et al. 1993). Keystone species are organisms that have a disproportionately large effect on their ecosystems relative to their abundance (Paine

1995). First, sapsuckers drill a series of shallow holes in the outer bark of tree boles to access the phloem or xylem tissue and feed on the resultant exuding sap. They maintain sapwells throughout their foraging range, providing a plentiful food resource that affects the distribution and abundance of sympatric species (Navarro et al. 1995). Feeding at sapwells has been observed for at least 48 species of birds, 6 species of mammals, and dozens or more arthropods (Sutherland et al. 1982, Miller and Nero 1983, Foster and Tate

1996). Second, as the most common primary cavity excavators in southeast Alaska

(Suring 1988), sapsuckers provide obligatory habitat for secondary cavity nesters who are unable to create their own cavities, yet require them for one or more life history functions. For example, two obligate secondary cavity nesters, Tree Swallows

(Tachycineta bicolor) and Violet-green Swallows (Tachycineta thalassina) are dependent on sapsucker cavities, and extirpation of sapsuckers may result in local extinctions of secondary cavity nesters (Daily et al. 1993). Northern flying squirrels (Glaucomys sabrinus), a species of conservation concern and potential old-growth obligate, also use sapsucker cavities for roosting (Holloway and Malcom 2007). In southeast Alaska, 73 percent of northern flying squirrels nested in tree cavities (Bakker and Hastings 2002). In the Pacific Northwest, 25-30 % of forest vertebrates nest in cavities (Bunnel et al. 1999).

Sapsuckers also play a vital role in structural function of forests by behaving as ecological engineers. Ecological engineers directly or indirectly cause physical state changes in their habitat and in doing so create or maintain habitat (Jones et al. 1994).

Sapsuckers contribute to decay of live trees by damaging the protective bark and permitting fungal inoculations in their wells and nesting cavities. This decay has an important, if often overlooked, role in disturbance ecology of forests. In mature forests, decay results in shifting canopy gaps (Hennon 1995). Gaps occur as trees weakened by decay fall and knock down neighboring trees creating small open areas, resulting in a stochastic canopy structure and a significant increase in stand heterogeneity. Because stand heterogeneity ultimately equates to habitat heterogeneity, thereby increasing overall biodiversity (Lindenmeyer et al. 2006), it is important to better understand how sapsuckers select habitat features within the forests they inhabit (Daily et al. 1993).

Forests in Southeast Alaska contain low tree species richness, but therein exhibit complex age and tree-size structure (Deal 2007). The goal of this study was to identify structural attributes selected by Red-breasted Sapsuckers in an old-growth forested landscape in central southeast Alaska. My objectives were to (1) describe physical characteristics associated with Red-breasted Sapsucker sapwell trees and nest trees in old-growth forests; (2) identify physical and biological characteristics of Red-breasted

Sapsucker nest-sites; and (3) model habitat selection of Red-breasted Sapsucker sapwell trees, nest trees, and nest-sites.

METHODS

Study Area

Data were collected on the Petersburg Creek, Duncan Salt-Chuck Wilderness of the Petersburg Ranger District, Tongass National Forest (hereafter, The Tongass). This wilderness is comprised of 18,959 hectares ranging from sea-level to 1,090 m in elevation, is located on Kupreanof Island, and lies directly west of the nearby city,

Petersburg, Alaska, on Mitkof Island (Figure 1).

The Tongass is the largest National Forest in the United States. Located in southeast Alaska in the Alexander Archipelago, encompassing some 70,000 km2, the

Tongass contains the largest remnant of temperate rainforest in the world. Spanning 800 km long, 20% of the area of the Tongass is rock and ice, 12% is densely vegetated forest,

43% is moderately vegetated forest, and 25% is wetlands (United States Forest Service

2005). The Tongass consists of over 2,000 islands as well as a section of the mainland contiguous with the international border of British Columbia, Canada. The area is influenced by a maritime climate characterized by mild winters and cool summers with year-round precipitation around 279 cm per year (United States Forest Service 2005).

Total hectares allocated to Wilderness is 1,067,274, of which 494,191 hectares is old- growth forest (United States Forest Service 2008).

Figure 1. Petersburg Creek Duncan-Salt Chuck Wilderness (in green) on Kupreanof Island in Tongass National Forest of southeast Alaska.

Forests in the Tongass are predominately comprised of coniferous tree communities of western hemlock (Tsuga heterophylla), and Sitka spruce (Picea stichensis). Other less prevalent tree species include western red cedar (Thuja plicata),

Alaska yellow cedar (Chamaecyparis nootkaensis), coast pine (Pinus contortus), black cottonwood (Populus trichocarpa) and red alder (Alnus rubrus) (Willson and Comet

1996, Dellasala et al. 1996). Understory vegetation is primarily composed of blueberry and huckleberry (Vaccinium spp.), devil’s club (Oploplanax horridus), and salmonberry

(Rubus spectabilis). Forest communities in riparian areas, landslides and beaches contain red alder, Sitka alder (Alnus sinuata), Oregon crabapple (Malus diversifolia), red elderberry (Sambucus pubens), and salmonberry (Webster 1950). In areas with poor drainage, bogs and ponds called muskegs form, and trees are stunted or nonexistent.

Here the substrate consists of sphagnum mosses, small pools, herbs and small shrubs such as crowberry (Empetrum nigrum), bog laurel (Kalmia latifolia), and cranberry

(Vaccinium oxycoccus) (Webster 1950).

Common natural disturbance in southeast Alaskan forests is low or moderate in intensity and primarily attributed to wind throw (McClellan et al. 2000, Dellasala et al.

1996). In older forests, disease in the form of heart rot and dwarf mistletoe

(Arceuthobium spp.) have a significant impact on stand structure (McClellan et al. 2000).

Less common disturbance is caused by insects and fire.

Sapwell Trees

During the first season of this study in 2008, seven transects each consisting of 10 plots spaced 200 m apart were created and surveyed for the presence of sapwell trees.

Plots were rectangular, measuring 10 m x 20 m (0.02ha). Transects were randomly positioned on a series of polylines in a Geographical Information System (GIS). The polylines corresponded to trails, shorelines, or Wilderness Area boundaries located within

2 km of a road, to ensure accessibility. Seven random starting positions were selected along these polylines with at least 1 km separating neighboring transects. From each of these start points, a transect line was delineated at a perpendicular direction from original polylines, except where terrain prohibited (Figure 2). This sampling protocol is thus biased toward the edges of the wilderness area and accessible elevations and biased against higher, interior habitats. However, approximately 67% of the study area was potentially sampled with this protocol, and much of the unsampled area is above the timberline. Also, no transect originated at the edge of an abrupt change of habitat such as silvicultural manipulation. Moreover, accessibility constraints are unavoidable in remote

Alaskan wilderness, and this protocol achieved reasonable coverage of the study area without exorbitant expense of vehicular (e.g., helicopter) support.

I surveyed each plot for compositional variables focusing on structural aspects potentially important to Sapsuckers as well as those that characterize old-growth forest attributes. Each tree in the plot was classified as used or unused as a

Figure 2. Locations of sapwell tree plots in Petersburg Creek-Duncan Salt Chuck Wilderness, Alaska, in 2008.

sapwell tree. The diameter at breast height (DBH) was measured (if > 2.5 cm), and species was recorded. To assess the furrow depth of bark, a randomly chosen furrow at the DBH line was measured to the nearest millimeter using a small flat ruler at the same location where DBH was measured (MacFarlane and Luo 2009). An ordinal measure of the stage of decay (0; live, and 1-5; dead) was determined using the USFS Forest

Inventory and Analysis Program methodology (United States Forest Service 2006).

Decadence in the form of broken tops, dead tops, bole fluting, and the presence of fungal fruiting bodies (conks) were recorded. Additionally, dwarf mistletoe was quantified using the Hawksworth Dwarf Mistletoe rating system (Hawksworth 1977). This rating system produces an ordinal categorical variable that I treated as a continuous variable for analysis.

Nest Trees

Nest searching was conducted around three remote field sites (Salt Chuck,

Petersburg Lake, and Steelhead Camp) that represent the general topographic variation below timberline within Petersburg Creek-Duncan Salt Chuck Wilderness during May and June of 2008 and 2009 (Figure 3). The Salt Chuck site consists of fairly flat forest and muskeg situated next to tidally influenced bay and riverine systems. The Petersburg

Lake site is surrounded by forested slopes of moderate elevation that rise abruptly from the lowland lacustrine environment. The Steelhead Camp site is a riparian zone

(Petersburg Creek) characterized by extensive beaver damage and upland forest in a

Figure 3. Location of 62 paired Red-breasted Sapsucker nest sites and available sites at 3 field camps within Petersburg Creek-Duncan Salt Chuck Wilderness, Alaska, in 2008 and 2009.

typical u-shaped glacial valley. From each site a base camp was established, and from the base camp randomly selected cross-country routes were walked in areas of suitable habitat.

Visual and auditory cues were used to locate active nests. Rather than survey particular forest stands, the sapsuckers led field observers to nests (McClelland and

McClelland 2000). Nests were located during the nest-building phase by following adult birds and later in the nesting cycle by honing in on begging cries of young in the nest. I found that sapsucker nestlings can be heard from at least 250 m away if conditions are ideal.

If nests were located before hatching, they were revisited to ensure they were active. Nests were assigned UTM coordinates using a handheld GPS unit and a flag was hung discretely at least 10 m away to facilitate relocation. By locating nests from adult behavior and begging nestlings, this method was biased against nests that may have failed or were abandoned early in the nesting cycle (e.g., during incubation). However, as a cavity-nester, sapsuckers suffer relatively low nest predation and have a high rate of nest success (Martin and Li 1992, Martin 1995, Fleury 2000, Walters and Miller 2001, Sperry et al. 2008, Sadoti and Vierling 2010), and thus I assume my methods provided a representative sample of sapsucker nesting locations within the study system.

Nest Sites

After fledging (late June), nests were relocated and vegetation plots were established. At each nest tree, the height of the nest cavity, height of the tree,

presence/absence of conks, percentage of bark, percentage of branches, number of additional cavities, and cavity orientation were recorded. The long axis (20 m) of the plot was oriented in the direction of the opening of the nest cavity (Figure 4). In addition to the metrics described above, canopy cover was quantified using 4 readings taken from cardinal directions with a spherical densiometer at the center of each plot. Coarse woody debris (CWD) was measured using a line intersect technique; all downed logs over 5 cm

DBH and crossing a 20 m transect through the center of the plot were counted, identified to decay class and species if possible, and the width was measured where intersecting the transect line. From the nest tree a random distance was selected (50-100 m), and random azimuth (0-359 degrees,) to locate the center of an available plot, where all measurements were repeated (Figure 4).

Figure 4. Plots were centered around nest trees (in purple) and locations measured at a random distance 50 to 100 m away at a random azimuth to compare habitat characteristics at Red-breasted Sapsucker nest sites and available sites in Petersburg Creek-Duncan Salt Chuck Wilderness, Alaska, in 2008 and 2009.

Statistical Analysis

Sapwell Tree Selection:

I used standard multiple logistic regression (Hosmer and Lemeshow 2000) to estimate a resource selection probability function (RSPF; Manly et al. 2002) for trees selected for sapwells by contrasting all used and unused trees on the sapwell plots.

Before fitting the models, I considered the relationship between tree size (DBH) and the probability of use for sapwells. Though other sapsucker species have been found to use larger trees for sapwells, I anticipated the possibility that at a certain point use would decline as a tree grows very old and production of sap dwindles. Therefore, I considered both linear and quadratic functions for the covariate DBH. I conducted preliminary univariate analyses and removed those variables that were uninformative (P ≥ 0.25,

Burnham and Anderson 2002). Six variables were included in the final model selection process and included both linear and quadratic terms for DBH, furrow depth, conks, bole flute, and dwarf mistletoe. I selected 20 a priori models for the sapwell tree selection candidate set based on literature on Red-breasted Sapsuckers and other Sphyrapicus species as well as personal observation (Appendix 1). All models were created using additive combinations of the above-mentioned 6 covariates.

Nest Tree Selection:

I used Rayleigh’s test to determine if circular uniformity was exhibited for the orientation of nest cavities. I used standard logistic regression to estimate a resource

selection function (RSF; Manly et al. 2002) by comparing sapsucker nest trees and available snags in both nest and random plots over 17 cm DBH, as this has been found to be the smallest diameter tree a sapsucker could nest in (Crocket and Haddow 1975). This was used as a metric for comparing Red-breasted Sapsucker nest trees to available trees in another study (see Joy 2000). I conducted a univariate analysis and removed variables at a cut-off of P ≥ 0.25 (Burnham and Anderson 2002). I selected 11 a priori models for the nest tree selection candidate set based on literature on Red-breasted Sapsuckers and other Sphyrapicus species as well as personal observation (Appendix 2).

Nest Site Selection:

I used 1-1 matched pairs conditional logistic regression (Hosmer and Lemeshow

2000) to estimate a resource selection function for nest-site selection (RSF; Manley et al.

2002). The logistic regression included nest-site locations and available locations; because the ratio of these two classes in the dataset was not governed by the prevalence of nest-sites on the landscape, this analysis cannot yield a true probability of selection; rather it provides a resource selection function that is proportional to a selection probability function (Johnson et al. 2006). Prior to building models for the conditional logistic regression, I tested for collinearity and removed covariates with an R > 0.7

(Burnham and Anderson 2002, Manly et al. 2002). I conducted univariate analyses and discarded variables at a more rigorous cut off P 0.1 in order to minimize the number of variables in the models to determine the most parsimonious model that still adequately explained the data (Bakker and Hastings 2002). This resulted in 7 covariates included in

the model-building: average DBH, number of stems, percentage of stems with conks, percentage of stems with broken tops, decay class, percent of dead trees and average decay class of CWD. I selected 24 a priori models for the nest-site selection candidate set. These models were also based on literature on Red-breasted Sapsuckers and other

Sphyrapicus species as well as personal observation (Appendix 3).

Model Selection and Evaluation

I used an information-theoretic technique to assess the best-fitting models for all three model-selection analyses by examining Akaike’s information criterion corrected for small sample sizes (AICc; Burnham and Anderson 2002) and AICc weights (wi). If model selection did not indicate strong support for one model (ΔAICc ≤ 2), I used a model-averaging approach to estimate parameter coefficients and unbiased standard errors. I examined model fit for the RSPF (e.g, used-unused; sapwell tree selection) by evaluating the correct classification rate (CCR), using a cut point of 0.05, and examining the area under the receiver operating characteristic (ROC) curve. For the 2 RSF analyses

(e.g., used-available; nest tree and nest-site selection), these model evaluation metrics are inappropriate because used and available are not mutually exclusive classes.

Accordingly, I used area-adjusted frequency bins (Boyce et al. 2002) to evaluate the expectation that observed number of selected probabilities within bins was positively correlated with the number expected based on RSF model-output scores. Significance of the correlation was tested with a Spearman-rank correlation test at P ≤ 0.05. Bin size was established by dividing predictions between minimum and maximum scores, merging

bins as necessary to achieve a sample size of at least 6 in each bin. Area-adjusted bins for nest-tree and nest-site selection amounted to 8 and 6 bins respectively. Because my datasets of used sample units were small, I did not partition my data into training and testing datasets. Instead, I used all the data to build the best possible models. Therefore, the model evaluation procedures yield optimistic measures of prediction success

(Fielding and Bell 1997). I conducted all analyses using program R version 2.10.0 (R

Development Core Team 2009) and add-in packages “survival” (Therneau 2009),

“design” (Harrel 2009), and “circular” (Lund and Agostinelli 2005). Results are reported as means ± 1 SE.

RESULTS

Sapwell Trees

Seventeen of 70 (24%) plots had evidence of sapsucker wells. Within these 70 plots, 32 (7%) out of 537 trees had sapwells (Table 1). Of the 32 sapwell trees, 18 were in western hemlock, 3 were in mountain hemlock, 2 were in Sitka spruce, 1 was in red alder and 9 were in trees that were unidentifiable due to decay. AICc scores and Akaike weights suggest that DBH, DBH2, and bark roughness were the most important predictors influencing selection of a tree for creating sapwells (wi = 0.45, Table 2). A second competitive model included conk as a covariate in addition to DBH, DBH2, and bark roughness (wi = 0.25, Table 2). The third ranking model was also competitive (∆AICc <

2 2, wi = 0.17, Table 2) including the covariates DBH, DBH , bark roughness, and dwarf mistletoe (Table 2). Averaged parameter coefficients in the top three models indicated that sapsuckers selected trees for sapwells that were of intermediate size, had high bark roughness, and greater incidence of conks and dwarf mistletoe than available trees (Table

3). Standard errors for covariates conk and dwarf mistletoe overlap zero, indicating weak relationships. All three models performed well at predicting Red-breasted Sapsucker sapwell trees with the correct classification rate of the top ranked model (94.5%) performing comparably with the second (94.3%) and third (94.5%) models. The area under the ROC curve (AUC = 0.70) was the same for all three models. However, because the prevalence of sapwell trees in the dataset was only 7%, the apparently high

correct classification rate may be a product of skewed prevalence, and the ROC is thus a better metric.

Table 1. Average and standard error of covariates sampled at Red-breasted Sapsucker sapwell trees (n = 33) and unused trees (n = 503) in Petersburg Creek-Duncan Salt Chuck Wilderness, Alaska, in 2008.

Sapwells No Sapwells

Covariate SE SE

DBH (cm) 34.6 4.43 14.91 0.71 Furrow Depth (mm) 11.79 1.43 5.66 0.23 Conk 0.09 0.05 0.02 0.01 Broken top 0.00 0.00 0.01 0.08 Dead top 0.03 0.17 0.01 0.11 Bole flute 0.03 0.17 0.00 0.00 Dwarf mistletoe 0.85 0.27 0.31 0.05 Decay class 0.48 0.17 0.72 0.06

Table 2. Top five candidate models plus the null for predicting Red-breasted Sapsucker sapwell trees in Petersburg Creek-Duncan Salt Chuck Wilderness, Alaska, in 2008.

Model K AICc ∆AICc wi DBH + DBH2 + Furrow Depth 4 199.78 0 0.45 DBH + DBH2 + Furrow Depth + Conk 5 201.01 1.23 0.25 DBH + DBH2 + Furrow Depth + DM 5 201.71 1.93 0.17 DBH + DBH2 + Furrow Depth + Conk + DM 6 202.97 3.18 0.09 DBH + DBH2 3 206.64 6.86 0.01 Null 1 249.91 50.13 0 DBH = diameter at breast height, Conk = presence of fungal fruiting body, DM = dwarf mistletoe

Table 3. Parameter estimates, standard errors, and P values for the top three averaged models for predicting Red-breasted Sapsucker sapwell trees in Petersburg Creek-Duncan Salt Chuck Wilderness, Alaska, in 2008.

Parameter Estimate SE P Intercept -4.88 0.49 < 0.01 DBH 0.07 0.02 < 0.01 DBH2 -0.0004 0.0002 0.01 Furrow Depth 0.1 0.03 < 0.01 Conk 0.21 0.23 0.1 Dwarf Mistletoe 0.01 0.02 0.15

Nest Trees

Thirty-one active red-breasted sapsucker nests were located during 2008 and

2009. Nests were located in Sitka Spruce (n = 21), Western Hemlock (n = 9), and one unidentifiable species. All nest cavities were excavated in snags, with the exception of one nest, which was located in the dead top of a live hemlock. Twenty-nine (94%) nest trees exhibited the presence of external conks including Ganoderma applanatum,

Fomitopsis pinicola, and Laetiporus sulfurous. Additional descriptive statistics are presented in Table 4.

Nest orientation did not significantly differ from a random distribution

(Rayleigh’s test; R = 0.16, P > 0.05). The 31 nest trees were compared with 150 available trees for the model selection analysis (Table 5). The model with the lowest

AICc value included the covariates DBH, conk, decay class and quadratic decay class

(wi = 0.75, Table 6). Parameter coefficients suggest that sapsuckers chose nest trees that were large, contained conks, and were at intermediate stages of decay (Table 7). The top ranking model performed well at predicting Red-breasted Sapsucker nest trees with area- adjusted frequencies demonstrating a significantly positive Spearman-rank correlation (rs

= 0.83, P = 0.01)

Table 4. Average and standard error of Red-breasted Sapsucker nest tree (n = 31) characteristics in Petersburg Creek-Duncan Salt Chuck Wilderness in 2008 and 2009.

Covariate Average SE Range DBH (cm) 86.22 6.48 31.3-162.8 Tree Height (m) 27.54 2.1 9.1-55.6 Cavity Height (m) 17.58 1.04 6.9-29.1 No. Cavities 7.16 1.13 1.0-30.0 Decay Class 2.71 0.12 1.0-4.0 % Bark 30.87 5.4 0-95 % Branches 16.87 3.73 0-85

Table 5. Average and standard error of covariates sampled at Red-breasted Sapsucker nest trees (n = 31) and available trees (n = 150) in Petersburg Creek-Duncan Salt Chuck Wilderness, Alaska, in 2008 and 2009.

Nest Trees Available Trees Covariate SE SE

DBH (cm) 86.22 6.48 46.32 3.78 Conk (%) 0.94 0.17 0.35 0.03 Broken top (%) 0.74 0.13 0.63 0.05 Decay class 2.71 0.49 3.43 0.28

Table 6. Top five models and the null for predicting Red-breasted Sapsucker nest trees in Petersburg Creek-Duncan Salt Chuck Wilderness, Alaska, in 2008 and 2009.

Model K AICc ∆ AICc wi DBH + Conk + DC + DC² 5 90.42 0.00 0.75 DBH+ Conk + BT + DC + DC² 6 92.71 2.29 0.24 DBH+ DC + DC² 4 99.7 9.28 0.01 DBH + BT + DC + DC² 4 101.07 10.65 0.00 Conk + DC + DC² 4 106.55 16.13 0.00 Null 1 167.83 77.41 0.00 BT = broken top, Conk = presence of fungal fruiting body, DBH = diameter at breast height, DC = decay class

Table 7. Parameter estimates for the top model predicting Red-breasted Sapsucker nest trees in Petersburg Creek-Duncan Salt Chuck Wilderness, Alaska, in 2008 and 2009. Parameter Estimate SE P Intercept -8.64 2.23 < 0.01 DBH (cm) 0.04 0.01 < 0.01 Conk 2.45 0.87 < 0.01 Decay Class 3.79 1.74 0.03 Decay Class2 -0.9 0.34 0.01

Nest Sites

Nest-site habitat measurements were completed at 62 pairs of used and available nest locations (Table 8). AICc weights and AICc values indicated that the top model differentiating used from available locations included number of stems, percentage of stems with conks, and average decay class of CWD (wi = 0.48; Table 9). An equally competitive model included the above mentioned variables as well as the average DBH

(wi = 0.31; Table 9). Averaged parameter coefficients indicated that sapsuckers selected nest sites with fewer stems, higher DBH, greater incidence of fungal infection (conk), and a higher decay class of coarse woody debris than locally available random sites (Table

10). Area-adjusted frequencies exhibited a significant positive Spearman-rank correlation (rs = 0.96, P < 0.001), indicating good model performance.

Table 8. Average and standard error of covariates sampled at Red-breasted Sapsucker nest plots (n = 31) and available plots (n = 31) in Petersburg Creek-Duncan Salt Chuck Wilderness, Alaska, in 2008 and 2009.

Nest Available Covariate SE SE Stems 15.93 1.49 20.26 1.97 DBH (cm) 34.45 2.45 26.97 2.47 Conk 1.9 0.25 1.29 0.21 Broken top 3.1 0.39 2.81 0.35 Dead top 0.58 0.14 0.71 0.2 Bole flute 0.61 0.16 1.1 0.33 Dwarf mistletoe (0-6) 2.29 0.52 2.97 0.57 Decay class (1-5) 1.11 0.13 0.73 0.08

Table 9. Top five candidate models predicting Red-breasted Sapsucker nest-site selection in Petersburg Creek-Duncan Salt Chuck Wilderness, Alaska, in 2008 and 2009.

Model K AICc ∆AICc wi Stems + Conk + DC CWD 3 27.71 0 0.48

Stems + DBH + Conk + DC CWD 4 28.55 0.83 0.31

Stems + DBH + Conk + DC CWD + DC 5 30.9 3.18 0.1

Conk 1 33.87 6.15 0.02

Stems + DBH + Conk + DC CWD + DC + Dead + BT 7 36.5 8.79 0.01 (Per plot): Stems = number of stems, Conk = percentage of trees with conks, DC CWD = average decay class of coarse woody debris, DC = decay class of trees, Dead = number of dead trees, BT = number of broken tops

Table 10. Model-averaged parameter estimates for the top two ranking models predicting Red-breasted Sapsucker nest sites in Petersburg Creek-Duncan Salt Chuck Wilderness, Alaska, in 2008 and 2009.

Parameter Estimate SE Stems -0.09 0.06

DBH 0.03 0.03

Conk 0.12 0.06

DC CWD 1.03 0.45

DISCUSSION

Sapwell Trees

Red-breasted Sapsuckers used trees that were intermediate in size, had high bark furrow depth, and a greater incidence of conks and dwarf mistletoe for building sapwells.

These results suggest that both structure and some level of pathogenic weakness are considerations for sapsuckers when selecting sapwell trees in the study area. The reason for a preference for intermediate-sized trees is unclear, although it likely represents a tradeoff between less suitable substrate characteristics associated with smaller trees and reduced sap yield in larger senescent trees. In old-growth longleaf pine (Pinus palustris) forests in the southeastern United States, and mixed hardwood and pine forests in

Michigan, Yellow-bellied Sapsuckers selected larger trees for creating sapwells compared to those without sapwells (Eberhardt 2000, Varner et al. 2006). The amplified bark furrow depth on sapwell trees may provide enhanced refugia for food resources consumed by foraging sapsuckers. In central Europe, a higher diversity and abundance of arthropod fauna used fissured versus smooth bark (Nicolai 1986). Quantitative analyses examining both foraging rates and stomach material have indicated that the Red- breasted Sapsucker’s diet consists of a considerable amount of animal content (e.g., not exclusively sap; Beal 1911, Foster and Tate 1966, Raphael and White 1984). If arthropod abundance is indeed greater on trees with higher bark furrow depth, then selection of these trees for sapwell production may reflect a trade-off that maximizes the cumulative benefits of the two food sources. From an energetic standpoint, having both

sap and insect food sources in the same location may be most efficient. Drilling sapwells in trees with fungal and dwarf mistletoe infection may be adventitious to sapsuckers because weakened trees exhibit more sap production than healthy trees (Kilham 1964).

Yellow-bellied sapsuckers select sapwell trees with a lower health index than random trees (Eberhardt 2000, Walters et al. 2002, Varner 2006). Dwarf mistletoe infestation is known to reduce wood quality and increase a tree’s susceptibility to pathogens

(Mathaison 1996). Further, several species of arthropods feed on mistletoe shoots, resulting in a greater abundance of insects in stands infected with mistletoe than without

(Bennets et al. 1996). Sapsuckers may cue into softened wood, facilitating sapwell construction, while taking advantage of the greater amount of invertebrate food. In

Colorado, cavity nesting birds including Red-naped Sapsuckers, were more common in stands infected with mistletoe than in uninfected stands (Bennets et al. 1996).

Nest Trees

I found no significant evidence for an orientation bias for Red-breasted Sapsucker nest cavities in southeast Alaska. This corroborates with Joy (2000), who studied Red- breasted Sapsucker in the coastal montane forests of British Columbia, Canada. In contrast, other studies on Yellow-bellied Sapsucker and Red-naped Sapsucker have shown there is an orientation bias in nest cavities (Dobkin et al. 1995, Butcher et al. 2002,

Walters et al. 2002, Losin et al. 2006). One potential explanation for the differences between taxa may be that Yellow-bellied and Red-naped Sapsuckers nest primarily in live hardwood trees. Orientation bias in these species may represent prospecting for

softer sites, as south or southeast facing trajectories tend to be warmer and may facilitate heart-rot (Losin et al. 2006). Effects of orientation on wood hardness may not be important when excavating in the deadwood the birds used in my study area, because dead trees would be expected to have more uniform decay characteristics.

Nesting sapsuckers selected large dead trees with the presence of conks at intermediate stages of decay. The average DBH in this study in trees with actively nesting birds was somewhat lower than Red-breasted Sapsucker nest trees on northern

Vancouver Island (86.2 cm versus 93.3 cm, Joy 2000). However, Red-breasted sapsuckers in both southeast Alaska and Vancouver Island preferred trees with greater

DBH than available trees. Large trees presumably offer protection from predators as well as enhanced insulation for thermoregulation. Nest trees had visible evidence of external conks in 94 % of the nests found. The Red-breasted Sapsucker is a weak cavity excavator (Walters et al. 2002), thus the presence of rot likely reduces the energetic cost required to create nest cavities. Decay in an advanced stage, however, would not maintain the structural integrity needed to protect nestlings from predation or tree fall.

Nest Sites

Sapsuckers selected nest sites with lower stem density, greater DBH, higher incidence of trees with conks and increased decay class of CWD. These results are supported by previous research suggesting Red-breasted Sapsuckers prefer older forests in southeast Alaska (Dellasalla et al. 1996, Cotter and Andres 2000, Andres and Stotts

2004). A lower density of trees may allow for more rapid and efficient flight between

nests and feeding locations. If sapsuckers are choosing nest sites in close proximity to foraging sites, as suggested for Red-naped Sapsuckers by Crockett and Hadow (1975), older trees with more conks may be ideal for foraging. Eberhardt (2000) however, did not find evidence that Yellow-bellied sapsuckers choose trees closer to nests. General decadence is a ubiquitous attribute of old-growth forests, and therefore the hypothesis regarding selection of sapwell trees in the vicinity of nest trees should be further explored. Downed logs are important structural components for colonies of arthropods, including log-dwelling ants (Togersen and Bull 1995), which are the preferred animal prey for Red-breasted Sapsuckers (42.5 % stomach content mass in 34 specimens; Beal

1911, Foster and Tate 1966). As ants attain high densities in southeast Alaska, and use dead wood for nesting, they likely play a central role in ecosystem processes as food sources (Francoeur 1987). Therefore, downed decaying logs may be of importance for sapsuckers as they supply significant amounts of nutrients. This resource is not limited to the ground; coarse woody debris has been positively linked to densities of arthropods on live tree boles (Horn and Hanula 2007). Surprisingly, the amount of coarse woody debris did not appear to influence nest-site selection.

Management Implications

Several studies have examined habitat selection by other members of the

Sapsucker complex, yet there is a paucity of information regarding Red-breasted

Sapsuckers. I sought to model habitat selection specific to Red-breasted Sapsuckers in a

specific region and habitat type. Results indicate that many of the habitat characteristics used by Red-breasted Sapsuckers are similar to other Sphyrapicus species, while others are not.

Analyses from this study suggest that Red-breasted Sapsuckers need large old trees for nesting and intermediate sized trees for sapwells. Maintaining a combination of old and intermediate-aged forests is likely important when managing for this species.

There is current interest in developing silvicultural systems that sustain or augment wildlife communities and processes (Deal 2007). As most systematic studies of landbirds in the Tongass have been conducted in managed forests, current knowledge of bird- habitat interactions in old-growth forests is useful to understand management impacts on avifauna (McClellan et al. 2000, Andres et al. 2004). The model results from my study may provide useful knowledge needed to update harvest techniques that support a wider range of forest resource values. Future studies should also examine sap yield and arthropod diversity across trees of different age, size, and bark classes to further elucidate the foraging patterns of this important double-keystone species in the Tongass National

Forest.

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Appendix 1. Candidate model set for predicting Red-breasted Sapsucker sapwell trees in Petersburg Creek-Duncan Salt Chuck Wilderness, Alaska, in 2008.

Model K AICc ΔAICc wi DBH + DBH2 + BM 4 199.78 0.00 0.45 DBH + DBH2 + Conk + BM 5 201.01 1.23 0.25 DBH + DBH2 + BM + DM 5 201.71 1.93 0.17 DBH + DBH2 + BM + Conk + DM 6 202.97 3.18 0.09 DBH + DBH2 3 206.64 6.86 0.01 DBH + DBH2 + Conk 4 207.65 7.87 0.01 DBH + DBH2 + DM 4 208.36 8.58 0.01 DBH + DBH2 + Conk + DM 5 209.32 9.54 0.00 BM + Conk + DM 4 225.24 25.46 0.00 BM + DM 3 225.34 25.56 0.00 Null 1 249.91 50.13 0.00

Appendix 2. Candidate model set for predicting Red-breasted Sapsucker nest trees in Petersburg Creek-Duncan Salt Chuck Wilderness, Alaska, in 2008 and 2009.

Model K AICc ΔAICc wi DBH + Conk + DC + DC2 5 90.42 0.00 0.75 DBH + Conk + BT + DC + DC2 6 92.71 2.29 0.24 DBH + DC + DC2 4 99.70 9.28 0.01 DBH + BT + DC + DC2 5 101.07 10.65 0.00 Conk + DC + DC2 4 106.55 16.13 0.00 DBH + Conk 3 111.16 20.74 0.00 Conk + BT + DC + DC2 5 123.30 32.88 0.00 Conk + BT + DC + DC2 5 123.30 32.88 0.00 DBH + BT 3 130.80 40.38 0.00 Conk + BT 3 131.66 41.24 0.00 Null 1 167.83 77.41 0.00

Appendix 3. Candidate model set for predicting Red-breasted Sapsucker nest sites in Petersburg Creek-Duncan Salt Chuck Wilderness, Alaska, in 2008 and 2009.

Model K AICc ΔAICc wi Stems + Conk + DC CWD 3 27.71 0.00 0.48 Stems + DBH + Conk + DC CWD 4 28.55 0.83 0.32 Stems + DBH + Conk + DC CWD + DC 5 30.90 3.18 0.10 Conk 1 33.87 6.15 0.02 Stems + DBH + Conk + DC CWD + DC + Dead + BT 7 36.54 8.83 0.01 Conk+ DC 2 35.25 7.54 0.01 Stems + DC CWD 2 35.28 7.57 0.01 Stems + Conk 2 35.36 7.65 0.01 DC CWD 1 35.77 8.05 0.01 Stems + DBH + Conk 3 36.33 8.62 0.01 Stems + Conk + DC 3 36.86 9.15 0.00 DBH + DC 2 37.18 9.47 0.00 DBH 1 37.15 9.43 0.00 Stems + DBH + Conk + DC 4 38.24 10.53 0.00 DC 1 37.85 10.14 0.00 DBH + BT 2 38.04 10.33 0.00 Stems + Conk + BT + DC 4 38.88 11.17 0.00 Dead 1 38.56 10.85 0.00 Stems + DC 2 38.90 11.19 0.00 Stems + DBH + DC 3 39.39 11.67 0.00 BT 1 39.25 11.54 0.00 DBH + Stems 2 39.28 11.56 0.00 Stems + DBH + Conk + BT + DC 5 40.15 12.44 0.00 Stems + BT 2 40.14 12.43 0.00 Stems 1 41.94 14.23 0.00