Laken Ganoe
Environmental Science: Fisheries and Wildlife Science
Dr. Carol Bocetti, Dr. W. David Walter, Dr. Craig Fox
Keywords: fisher, wildlife, mustelid, hair snare, techniques, habitat selection, pekania pennant,
wildlife biology

ACKNOWLEDGMENTS

There are many individuals with whom I would like to share my deepest gratitude for
assisting me in creating and completing this project. First of all, I would like to
acknowledge the University Honors Program for pushing my limits and offering the
opportunity to research a topic that is very important to me, as well as my thesis
committee for the time they have taken out of their busy lives to serve on my committee.
I would also like to thank the Pennsylvania Game Commission and the Pennsylvania
Department of Conservation and Natural Resources for working with me to complete
permit applications and allowing me to use their lands and equipment for this study. I
would specifically like to acknowledge the efforts of Dr. Matt Lovallo (PGC) and Dr. Jeff
Larkin (IUP) for sharing their vast knowledge of fisher in Pennsylvania, lending supplies,
and for their patience with me throughout the process. I would be remiss if I did not share
my most sincere gratitude for Dr. David Walter who has made the conscious effort to
work with a passionate young wildlife student that just really wanted to do research on
fishers even though it was not in his expertise. I am so glad that this connection we made
has grown into a research partnership and will continue to blossom as I become his
advisee in the Spring of 2018. The second to last individual I would like to acknowledge
is Dr. Carol Bocetti. Since my first days at Cal U, she has been the woman I have looked
up to most in my professional career. Without the guidance she has given me at
conferences, during class, and even in personal conversations, I would not be where I am
today. I have the utmost appreciation and respect for her and am extremely grateful that
our paths have crossed. Thank you for believing in me and pushing me to pursue my
greatest passion, I will always remember what you have done for me. Finally, I would
like to thank my parents. My mom and dad have been the greatest supporters in my life,
from my ups to my downs, and they have always been there for me. Whether they know
what I’m talking about when I get home and go off about in-depth research projects, they
still support me either way. I am very thankful to have them in my life and for their
willingness to go out into the field with me. This project would not have been the success
it was without their help. I love both of you, and I hope to make you proud.

i

TABLE OF CONTENTS
Page
List of Tables and Figures

iii

I.

Abstract

1

II.

Introduction

1

III.

a. Fisher Ecology

1

b. Pennsylvania Habitat

3

c. Fisher Status in Pennsylvania

5

d. Purpose and Objectives

7

Methods

8

a. Sampling Design

IV.

V.

8

b. Timeline

10

c. Sampling Collection and Microscopy

11

d. Sampling Design Evaluation Methods

12

e. Habitat Sampling

13

Results

15

a. Fisher Detection

15

b. Sampling Design Results

17

c. Habitat Data

18

Discussion

19

a. Suggestions for Further Research

25

Literature Cited

27

Appendix A

29

Appendix B

30

Appendix C

31

Appendix D

32

Appendix E

33

ii

LIST OF TABLES AND FIGURES
Page
Figure 1

Map of tree associations found in Pennsylvania

4

Figure 2

Map of fisher reintroduction sites

6

Figure 3

Close-up of unit B from map found in Appendix A

9

Figure 4

Photograph of site B1 hair snare set-up

10

Figure 5

Photograph of inside of hair snare from entrance

10

Figure 6

Photographs of microscopy analysis

12

Figure 7

Design of 17.8m-radius vegetation plot

14

Figure 8

Efficiency of three different snare densities based on cumulative

18

number of fisher hair samples collected at each unit.
Table 1

The number of fisher and non-fisher hair samples collected across

16

the three sampling periods of the study.
Table 2

Locations of fisher hair sample collection across sampling periods.

17

H indicates fisher hair sample collected, C indicates fisher caught
on camera
Table 3

The cumulative number of detections as trap sites are added to units

18

Table 4

Habitat characteristics for sampling locations that detected fisher

19

(either via hair sample or camera photo) compared to locations that
did not detect fisher

iii

Title: An evaluation of capture methods and habitat preference of fisher (Pekania
pennanti) in Clarion County, PA
Author: Laken Samantha Ganoe
Thesis Chair: Dr. Carol Bocetti
Thesis Committee Members: Dr. David Walter, Dr. Craig Fox, and Dr. Loring Prest

I. ABSTRACT
Fisher (Pekania pennanti) have been thriving in Pennsylvania since their reintroduction
in the late 1990’s. Efforts to mark their presence and absence across the state have been
conducted by the Wildlife Conservation Officers from the Pennsylvania Game
Commission. The purpose of this study was to determine the feasibility of using hair
snares to determine the presence of fisher and to describe the habitat characteristics of
locations where fisher presence was detected. I identified 40 fisher detections during a
single summer session from 60 hair snares and trail cameras that were sampled over three
time periods. Habitat characteristics of sampling locations that detected fishers were not
significantly different from the locations that did not detect fishers. The habitat
description of fisher locations in my study supports the wider niche description of the
species as previously described in Pennsylvania. This study demonstrates the
repeatability of hair sample collection in Clarion County which is the first criteria for
development of a remote mark-recapture method for estimating population size for this
species.
II. INTRODUCTION
FISHER ECOLOGY
The fisher (Pekania pennanti) is a member of the weasel family, Mustelidae. The
genus can be broken down into three subspecies that are distinguished by ranges within
North America: P. p. columbiana (northwestern and central areas), P. p. pacifica
(western areas), and P. p. pennanti (northcentral and northeastern areas) (Hall 1981).
Fishers are dark brown, furred, arboreal mesocarnivores with tails that encompass almost
a third of their body length. Some individuals have dark brown to almost black-tipped
tails and may also display white patches on their chest (Douglas and Strickland 1987).
They are also sexually dimorphic with males being generally larger than females,
1

weighing from 3.5 to 5.5kg and from 2.0 to 2.5kg, respectively (Powell 1993). Although
they are one of the largest members of their family, fishers have a lean body mass with
only about 2.4 to 4.6% extractable fat (Leonard 1980).
To maintain their lean body weight, the diet of a fisher consists mainly of small
rodents, but will occasionally include carrion and even small birds. Fishers also are one
of the main predators of porcupine. The fisher populations found in the eastern U.S. are
believed to have a more diverse diet than those found elsewhere (Zielinski et al. 1999).
The species is crepuscular in nature, and thus hunts during the twilight hours. Although
they are an arboreal mesocarnivore, they spend most of the time hunting on the ground.
According to a study done by Buskirk and Powell (1994), fishers tend to only spend the
minimum time necessary in open habitats when foraging. They also use a predation
approach, similar to other species in Mustelidae, that requires them to utilize temporary
refugia while stalking prey (Buskirk and Powell 1994). For reasons primarily unknown,
fishers will use tree cavities or brush piles as rest sites. There is speculation that fishers
will visit the nearest rest site post-feeding to sleep (Gilbert et al. 1997).
As with rest sites, fishers will use similar structures for denning and raising their
young. They will den in brush piles and downed logs, but prefer tree cavities for rest sites
and den sites. The study conducted by Gess et al. (2013) found that fisher in
Pennsylvania preferred structures that were cavities or broken tops of black cherry trees
(Prunus serotina). The breeding season for Pekania pennanti occurs between March and
May. Fisher will become sexually mature at about one year of age depending on
nutritional status (Wright and Coulter 1967). The average litter size is between two and
three, but can be as many as six altricial kits (Powell 1993, Powell et al. 2003). The kits

2

will stay with their mother and littermates from three to five months. Once on their own,
fishers have a lifespan of about eight years in the wild (Weckworth and Wright 1968).
The historic range of this animal covered most of Canada and across the northern
United States. Due to overharvest and habitat loss, this range has been modified and
fragmented in recent years. There have been differences displayed between P. p. pennanti
and the other two subspecies when it comes to habitat preference. P. p. pennanti has been
known to be the more adaptable subspecies that is found in varying forest types. The
initial habitat suitability index for the fisher by Allen (1983) predicted individuals would
select primarily large diameter trees in stands with 50—90% conifer composition. In the
west, P. p. pacifica and P. p. columbiana display the preference described by Allen
(1983) for mixed coniferous forests with high vegetation and downed woody debris on
the forest floor (Lancaster et al., 2008). There is some controversy in the literature about
fisher habitat selection between Powell (1994b) and Weir and Harestad (1997). The
former described fishers as selecting true conifer habitats, whereas Weir and Harestad did
not find any difference in habitat preference. In a more recent article, P. p. pennanti were
found to occupy not only the traditional coniferous stands, but also fully deciduous stands
(Powell et al. 2003).
PENNSYLVANIA HABITAT
The state of Pennsylvania has five different distinct forest types across the state:
beech-maple forest, Appalachian oak forest, northern hardwood forest, hickory-oak-pine
forest, and mixed mesophytic forest (Fig. 1). The two late-succession forest types
relevant to the study area in Clarion County are northern hardwood forest and
Appalachian oak forest. The northern hardwood forest contains mostly conifers but also
3

some hardwoods, including black cherry (Prunus serotina), beech (Fagus grandifolia),
sugar maple (Acer saccharum), and birch (Betula spp.). The understory is comprised of
witch-hazel (Hamamelis spp.) and mountain holly (Ilex mucronate). Appalachian oak
forests make up most of the state and consist of oaks (Quercus spp.), red maple (Acer
rubrum), tuliptree (Liriodendron tulipifera), and hickories (Carya spp.). Black
huckleberry (Gaylussacia baccata) and mountain laurel (Kalmia latifolia) are abundant in
the understory (Rhodes and Block 2005).

Figure 1: Map of the tree association found in Pennsylvania from Trees of Pennsylvania:
a complete reference guide (Rhodes and Block 2005)
The majority of the study area was at one time impacted by the coal mining
industry. Most of the mining sites in Clarion County were surface mines. Surface mining
(also known as strip mining) is a mining practice where the entire biomass of an area is
cleared out and moved aside to allow access to the coal layers below the earth’s surface.

4

Coal mining hit a peak in Pennsylvania in the 1950’s, and it was not until 1977 when the
federal government created the Surface Mining Control and Reclamation Act (SMCRA)
[30 U.S.C. 1258] that regulations were put in place on the proper reclamation of mine
sites. The original SMCRA did not give much in the form of guidelines for the types of
vegetation that could be planted on reclamation sites, and therefore, companies planted
whatever plants would grow in the compacted soils. The neglect of environmental
consideration that occurred during replanting resulted in the spread and colonization of
many invasive and non-native species. Therefore, many of the habitats at sites in this
study reflect the consequences of land management of that era.
FISHER STATUS IN PENNSYLVANIA
The fisher was once a thriving species in the eastern United States. Due to the high
demand for their fur and drastic urbanization in the early 1900’s, overharvesting, along
with loss of habitat led to the extirpation of the fisher in Pennsylvania. In the years 1994
to 1998, a reintroduction project led by the Pennsylvania Game Commission (PGC) in
cooperation with several agencies and biologists occurred within the state to re-establish
the species (Fig. 2). During the project 190 individuals were reintroduced into six
different sites within the state on available public land, such as State Forest Land (SFL)
and State Game Lands (SGL).

5

Figure 2: Reintroduction sites in New York, Pennsylvania, and West Virginia (Lovallo, 2008)

In 2008, PGC Furbearer Biologist Matt Lovallo created a post-reintroduction
monitoring program for fisher in Pennsylvania in which he outlines the results of ongoing monitoring projects and recommends potential future management through 2017.
The fisher population has become very well established and is steadily rising each year to
a self-sustaining population. Current methods of population estimation include the
combination of four different monitoring approaches: 1) incidental fisher captures, 2)
fisher observations, 3) fisher mortality reports, and 4) harvest reports. Wildlife
Conservation Officers (WCO) are required to fill out a report at the end of each year that
includes fisher observations seen personally and that are reported by the public, reported
incidental captures, and reported harvests from trapping within their respective
management units. They are also required to report the number of fisher mortalities
6

observed and the causes of each. Most mortality is caused by vehicle collisions in the
state of Pennsylvania. In fact, in 2007, there were over 30 reported fisher mortalities that
were vehicle-caused (Lovallo, 2008). Twenty percent of all furtakers are sent a similar
annual survey that asks them to report the number of incidental captures and sightings of
fishers they have experienced over the year.
In 2007, the number of WCO’s reporting fisher within their districts, based on the
combination of approaches above, was at 75%. Pennsylvania is split into 23 different
Wildlife Management Units (WMU), and according to the same survey results, 14 of
them have reported presence of fishers. There is no doubt that the population has
expanded successfully across the landscape. This success has led to the PGC opening a
trapping season for fishers in Pennsylvania in 2010. During the 2011 trapping season
there were 138 harvest reports, and an estimated 1,632 fishers that were captured and
released throughout the year. The current harvest limit is one fisher per furtaker with
mandated permit each year (Lovallo and Hardisky, 2012). The most recent reports on
harvest and population estimates have not been released.
PURPOSE AND OBJECTIVES
With the fisher population in Pennsylvania expanding since the reintroduction of
the species in the 1990’s, it is time for additional research to develop better population
estimation methods and to understand dispersal and use of habitat by fisher. This study
was created to take a genetic mark-recapture method that has had success in the western
United States and bring it to Pennsylvania in order to examine the potential for its use on
P. p. pennanti on the east coast. The Pennsylvania Game Commission was intrigued to
see if the use of hair snares would be successful in repeatedly collecting DNA samples
7

from individual fishers and what the appropriate site design would be to insure the
greatest recapture success with the least amount of effort.
This study took place in central Clarion County, Pennsylvania between the towns
of Shippenville and Strattenville from west to east, and Clarion and Cooksburg from
south to north, encompassing an area of 80km2. In total, there were 60 snares strategically
placed across my sample grid. The objectives of the study were to 1) determine the
occurrence of fisher in central Clarion County, 2) serve as a pilot study to determine the
feasibility of the remote sampling method of hair snares to collect repeated samples of
fisher hair, 3) analyze the effort efficiency in order to determine the appropriate hair
snare density, and 4) Compare habitat characteristics at snare locations where fisher were
detected against those where they were not to improve sampling site selection for fisher
in future studies.
III.

METHODS

SAMPLING DESIGN
After researching the history and distribution of fisher in Pennsylvania, as well as
taking into account my own personal experiences out west and in Pennsylvania, I selected
Clarion County as the location of my study. I reside in this area, and there have been
sightings of fisher within the county. I began by creating a sampling grid in ArcGIS
(Appendix A). Each grid cell was 4km2 and roughly resembles the size of a female fisher
home range (Ellington 2010). I strategically placed my grid so that it included as much
possible SGL and SFL as possible while remaining continuous. Within each cell (referred
to hereafter as a “unit”), I placed the first snare site in forested habitat insuring it was at
500m from the forest edge. I also took into consideration my own ease of access when
8

selecting snare sites, but made sure no snares were placed within 100m of a heavily
travelled road. I then located an additional two snare sites at least 500m from the first,
making sure they were also at least 500m apart from each other, with the same conditions
as above. I labeled each unit A-T going from the northwest corner to the southeast
(Appendix B). Within a unit, snare sites were labeled 1-3 according to their spatial
arrangement from west to east (for example, the snare placed farthest west in unit B, is
B1) (Fig. 3).

N
Figure 3: Close up of Unit B from map in Appendix A. North is indicated by the arrow.
Snares were made of 60cm long, 24cm diameter black corrugated drainage pipe
with a rubber cap on one end. Three, .30-caliber gun brushes were attached with T-nuts
approximately 20cm from the open end of the tube (Fig. 5). A small patch of cloth dipped
in gusto, was placed at the capped end of the snare. Gusto is a pungent long-distance
scent lure used by many trappers and biologists to attract carnivores. Due to the limited
9

amount of available trail cameras, only 7 working cameras were placed randomly across
the sampling units at sites I predicted to have fisher. Cameras were placed approximately
20cm off the ground facing the open end of the snare. Physical placement of snares
depended on location and available cover. When downed logs or large boulders were
present, snares were wedged beside the structures. If no large objects were at the
predesignated site, then the snare was butted up against a larger tree with the capped end
against the trunk (Fig. 4). Regardless of placement, large sticks were laid across the snare
(Fig. 4) to weigh it down to ensure it would not move when an animal attempted to enter.

Figure 4: Site B1 hair snare set-up

Figure 5: Inside of snare from entrance with
display of equidistant hair snares.

TIMELINE
Installation of units began at the end of May 2017 and were checked at threeweek intervals for a total of 16 weeks. The schedule ran on a three-week rotation for
feasibility of installing and checking units with limited assistance. Units A-I (27 snares)
10

were all installed in week one, M, O, P, and R-T (18 snares) were installed in week two,
and the rest (15 snares) were installed in week three. Following installation, a series of
three sampling periods occurred in the same schedule as above (Appendix C). Hair
samples were taken to Dr. David Walter’s lab at Pennsylvania State University (PSU)
intermittently throughout the summer.
SAMPLE COLLECTION AND MICROSCOPY
Upon arrival at a snare during each sampling period, the trail camera (if present)
was checked for battery life and the SD card was removed and replaced with a cleared
SD card. If the snare had been disturbed/moved from its original location, it was noted.
Gun brushes were checked for hair samples using a flashlight and white paper. If hair
samples were present, all gun brushes were removed, placed in an envelope, and replaced
with clean gun brushes. Gusto was reapplied to the existing cloth patch, or replaced with
a new patch if absent. Prior to leaving the site, the snare was replaced and weighed down
with sticks, and the camera (if present) was turned on.
Following field collection, samples were analyzed using microscopy to determine
if it contained the target species. Hair samples were removed from the gun brushes with
caution using a fine-tipped pair of tweezers, then they were placed on an adhesive
notecard with caution to avoid contact between the adhesive and the follicle. Hair scale
casts were created from the hair samples by 1) painting a layer of clear nail polish on a
blank microscope slide, 2) gently laying the edge of a hair on top of the still wet nail
polish while being careful not to have the follicle encounter the polish, then 3) gently
removing the hair from the slide using fine-tipped tweezers. A compound light
microscope was used at 400x magnification to view the hair scale casts. Two known
11

samples were used as reference slides for comparison: one from a fisher pelt, and one
from a raccoon (Fig. 6). If the hair sample suggested fisher presence, those samples were
flagged to be sent to the lab for genetic amplification. Amplification is the process of
using the polymerase chain reaction technique (Mullis and Faloona 1987) to create many
copies of a specific section of DNA.

Figure 6: Microscopy analysis of hair samples. A) Fisher guard hair, B) Raccoon guard
hair, and C) Fisher underfur

SAMPLING DESIGN EVALUATION METHODS
Snare sites were given a numbered designation a-priori to data collection to
determine the ideal sampling site density. The cumulative number of fisher hair samples
will be used to evaluate the detection efficiency of 1, 2, or 3 snare sites per unit. For
example, the number of detections in the following three scenarios will be compared: a)
when only snare 1 was used, b) when snares 1 and 2 were used, and c) when snares 1, 2,
and 3 were used.

12

HABITAT SAMPLING
Seven different habitat variables were measured from which three
additional habitat variables were derived at each snare site to use in the analysis of ten
habitat characteristics. A 17.8m-radius plot was set-up at each snare site using the snare
as the center point (Fig. 7). Within the boundaries of the plot, every tree was recorded
with its species identification and diameter at breast height (DBH). The species
identification consisted of a four-letter code abbreviation of the scientific name (e.g.
Tsuga canadensis = tsca). Species richness was derived from tree data, and is the total
number of species that were found within the plot surrounding each site. Tree density
refers to the number of trees per hectare based on a .10-hectare plot used in this study.
Percent Appalachian Oak and percent Northern Hardwood refers to the percentage of
trees within a plot that belonged to each respective group. Appalachian Oak species
include: all oaks, tuliptree, red maple, hickories, and American Chestnut (Castanea
dentata). Northern Hardwood species include: beech, birch, hemlock (Tsuga canadensis),
sugar maple, white pine (Pinus strobilus), black cherry and witch-hazel. Some sites did
not add up to 100% when totaling the two categories due to the presence of alternate
species that were introduced (Appendices D and E).

13

Figure 7: Diagram of 17.8m plot used. Snare displayed as star, and blue dots represent
points 5 and 10m from the snare in each cardinal direction that canopy and ground cover
measurements were taken. Vertical cover measurements were taken at the 10m mark
indicated by the open circle.
At 5m and 10m from the plot center in each cardinal direction, hit-miss readings
for canopy and ground cover were taken using a densitometer (Fig. 7). At each snare site,
the average percentages for canopy and ground cover were calculated by taking the sum
of hits (indicated as a 1) and dividing by 9, which is the total number of opportunities.
The grand means for these two vegetative cover variables were then calculated across all
snare sites that were used by fisher, and across those that were not used by fisher.
At the 10m mark in each direction, a 2m x 20cm vertical cover board (with 20
painted 20cmx20xm squares) made of canvas was held to collect percent vertical cover.
A square was considered a hit if 50% or more was covered by vegetation. The sum of the
number of hits from all cardinal directions was divided by the total number of squares

14

available in all directions (160) to determine the percent vertical cover at each snare site.
Each measurement of cover type occurred during the second sampling period.
Distances from the snare to roads and streams were calculated using the “Near”
function in ArcGIS. Only high traffic areas, defined by paved roads, were considered.
The layers PA_StateRoads and PAHistoricStreams given to me by Larkin at Indiana
University of Pennsylvania were used in the calculation. Only the distance to the nearest
stream and high-traffic road were used for each site.
In the data described below, habitat that is considered “used” is any snare site
where fishers were detected via genetic analysis from hair sample, or from photos taken
by a trail camera. A site is considered “unused” if genetic analysis of samples came back
negative, and if there were no photos of fishers in the area on trail cameras. P-values were
calculated using a two-tailed t-test.
IV.

RESULTS

FISHER DETECTION
In total, I collected 148 hair samples over the entire project. From these samples,
62 of them were identified as potentially belonging to fisher via microscopy. In addition
to the microscopy, the trail cameras confirmed the presence of fisher for 5 of the 62 hair
samples. All potential fisher hair samples were sent to the lab at Pennsylvania State
University for genetic analysis. Within the 62 samples sent for analysis, 38 were returned
with positive fisher identification (Table 1). The remaining hair samples that did not
return positive fisher identification were not further evaluated to determine the species
captured.

15

Table 1: The number of fisher and non-fisher hair samples collected across the three
sampling periods of the study.
Positive Fisher Hair
Samples

Non-Fisher Hair
Samples

Period 1

10

33

Period 2

19

30

Period 3

9

47

Overall

38

110

Detection is not only based on the number of hair samples, but camera photos of
fisher as well. Upon looking at the positive hair samples for fisher and correlating them
with their locations, fishers were detected at 32 sites within 18 units (Table 2). Out of the
32 sites, fisher were detected via trail cameras at four of the sites in four different units.
Two snare sites that had detected fisher at the camera during the second sampling period
did not return positive results from the genetic analysis of the associated hair samples.
These two camera sites that picked up fisher were included in the total detections for
habitat analysis since they were identifiable on camera as fisher being present at the site.
Units L and Q never detected a fisher at any snare site during any sampling period (Table
2). Other non-fisher detections from camera photos include opossum (Didelphis
virginiana), porcupine (Erethizon dorsatum), raccoon (Procyon lotor), black bear (Ursus
Americana), white-tailed deer (Odocoileus virginianus), gray fox (Urocyon
cinereoargenteus), coyote (Canis latrans), long-tailed weasel (Mustela frenata) , mice
(Muroidea), squirrels (Scuirus spp.), flying squirrel (Glaucomys volans), chipmunk
(Tamais striatus), birds and groundhog (Marmota monax).

16

Table 2: Locations of fisher detections across three sampling periods. H indicates fisher
hair sample collected, C indicates fisher was caught on camera.
Unit
A

B

C

D

E

F

G

H

I

J

Site
1
2
3
1
2
3
1
2
3
1
2
3
1
2
3
1
2
3
1
2
3
1
2
3
1
2
3
1
2
3

Period
1

Period
2

Period 3

Unit

H

K
C

L
H

M

H
H
H

H

N

H

O

H

H
H
H
H

HC
H
H
H

HC

P

H

Q

H

R
H

S
H
H

H

T

H

Site
1
2
3
1
2
3
1
2
3
1
2
3
1
2
3
1
2
3
1
2
3
1
2
3
1
2
3
1
2
3

Period
1

Period
2

H

Period 3
HC

H
H

H
H
C
H
H

H
H

H
H

H
H

SAMPLING DESIGN RESULTS
As the number of sampling sites were added to each unit, the number of fisher
hair samples increased. However, as the number of sites added increased, the rate of
increase in the number of fisher hair samples was diminishing (Table 3).

17

Table 3: The cumulative number of fisher hair samples collected across all units as snare
sites are added to units.
Period 1

Period 2

Period 3

Total

1

5

6

4

15

2

8

14

7

29

3

10

19

9

38

15

29

CUMULATIVE NUMBER OF FISHER HAIR SAMPLES

38

#sites/unit

NUMBER OF SNARES IN EACH UNIT

1

2

3

Figure 8: Efficiency of three different snare densities based on cumulative number of
fisher hair samples collected at each unit.
HABITAT DATA
For all of the habitat variables, none of the statistics were significant, and there
was no difference in the habitat variables in used and unused areas (Table 4).

18

Table 4: Habitat characteristics for sampling locations (either via hair samples or
camera photos) that detected fisher compared to location that did not detect fisher.
Unused by Fisher

Used by Fisher

Variables

mean

se

mean

se

p-value

%Canopy Cover

71.43%

0.029

73.96%

0.029

0.543

%Ground Cover

57.54%

0.045

54.17%

0.040

0.578

% Vertical Cover

55.31%

0.054

44.90%

0.043

0.131

Ave. DBH (cm)

22.67

1.476

24.50

1.389

0.373

Species Richness

5.41

0.274

5.84

0.229

0.223

Tree Density

397.14

43.23

421.25

33.27

0.653

% Appalachian Oak

41%

0.05

46%

0.05

0.471

% Northern Hardwood

49%

0.05

42%

0.05

0.317

Stream Distance (m)

176.62

32.89

231.01

29.56

0.222

Road Distance (m)

494.54

81.06

613.20

92.84

0.340

V.

DISCUSSION
Hair snares were indeed successful at collecting fisher hair. Using the camera

photos and the hair sample detections, fishers were found evenly dispersed across the
sampling sites at all but two units (L and Q). These two sites were extremely close to the
Clarion River, which is frequented by water sport enthusiasts. Although units K, J, and N
had fisher detections and were also along the Clarion River, they were located a bit
farther from high-impact areas. Unit L was located where the Clarion River begins to
back up and become Piney Lake. Therefore, there is more motor boat traffic in this area
than near the other units along the river where the depth is between 1-3 feet. Few people
travel the river between N and K since it is extremely shallow and only used for
canoeing, kayaking, fishing, and horseback riding (on designated trails). Unit Q is
19

sequestered from the river bank by a well-travelled road. This might suggest that fisher
have moved farther back into the forest in that area to avoid interactions with humans.
In the analysis of the feasibility and repeatability of remote sampling, the lab was
successful extracting DNA from the hair samples and returned positive fisher
identifications for 38 of the hair samples. The detection rate for fisher was 22% across all
60 snares for the combined sampling periods. Multiple sites returned hair samples from
more than one sampling period that were positively identified as fisher hair. The method
is very feasible to capture hair from the target species over the course of the study.
Objective 2 is met with positive enforcement from conducting this study. As a noninvasive technique that requires little man-power, the time and effort spent conducting
the field surveys were reasonable for a sample size of this magnitude, and was completed
by 1-2 individuals.
The effort efficiency is determined by snare density that results in the most hair
samples with the least effort. As expected, the number of fisher detections increased with
each additional snare within a unit. When only snare one was used, there were 15
detections over the course of the study. With both snare one and two being used, there
were 29 detections. The third scenario represents the overall detection number of 38
fisher. There seems to be a diminishing return on the probability of capture between the
use of two and three total snares. Final conclusions on the appropriate snare density
cannot be made at this time due to the fact that individual fisher identification needs to be
considered. Two units (G and K) had fisher detections at all three snares, with G2 having
a detection every sampling period. There is a high probability that many of these
detections at G were of the same individual fisher due to the proximity of the snare sites
20

within the unit. Knowing the identification of the fisher at each detection would greatly
help in the analysis of the snare density.
As mentioned above about unit Q, the habitat data suggests that fishers do try to
avoid busy roadways whenever possible. Although none of the statistics were significant,
there was a general difference between the averages for distance from the snare to a road.
In areas where fishers were detected, the average was 613.20m as compared to 494.54m
in unused areas (Table 3). There is a lot of noise in the data as can be seen by comparing
the used (48.21m – 1628.90m) and unused (58.46m – 1083.24m) area ranges for road
distance. The used area has the biggest range (1580.69m, Appendix D and E). The used
areas also encompass both extremes across all road distance data, suggesting there are
indeed multiple variables involved in fisher habitat selection, and that one factor might
not be more of an influence over another. I hypothesized that fisher would be using areas
with a high minimum distance from roads since they are characterized as extremely
elusive creatures and would want to remain in the forest interior (Allen 1983). With the
wide range in distance data, the hypothesis would need to have further sampling points to
make a conclusive judgement. One suggestion for the presence of fisher near roads is
access to easy food items, such as roadkill carrion.
Another distance variable that was considered as possible criteria for fisher
habitat selection is distance from the snare to a stream. The average distance from
snares in unused areas to a nearby stream was 176.62m, as compared to 231.01m in used
areas (Table 3). This was an interesting statistic in the analysis, because I was expecting
the distance to the nearest stream to be closer in used areas versus unused areas because a
prime resource in an animal’s territory is water. If a fisher is out hunting, I expected them
21

to want to remain close to a water source since prey items will go there to drink and the
fisher itself may prefer to remain close to a water source, but this did not seem to be the
case. The snare closest to water (03 at 9.76m) was actually in an unused area (Appendix
D). The farthest snare from water was 699.82m away, and it was used by fisher
(Appendix E). A possible explanation for this intriguing finding is interspecies
competition between fisher and river otter. As fisher in Pennsylvania have been shown to
have a very diverse diet (Zielinski et al. 1999) and would therefore be more likely to use
alternate food sources before risking confrontation with river otter, this avoidance could
explain the further distance of “used” fisher sites from streams. However, along the
Clarion River, I documented several latrine sites for river otter and where they were in
proximity to nearby snares. I found latrines on the bank of the river below sites N1 and
K1. Both of these sites had fisher detections, so I do not believe they are being deterred
by river otter, but this could be an interesting research topic in the future.
Three types of vegetation cover were investigated: ground, canopy, and vertical.
Once again, none of the result were significant, and the means of used and unused sites
were very similar. For instance, the average percent vertical cover was the closest to
being significant, but the means for used (55.31%) and unused (44.90%), do not display
any ecological significance (Table 3). The vertical cover estimate is very subjective and
does not really accurately represent the vertical cover presence of the sites. For instance,
a large leaf could cover half of two different squares, and instead of counting that as only
one square, the result would be both squares get counted toward the total since 50% or
more of each square was covered. In the future, I would like to change the method to
taking a photograph of the coverboard at each survey point and calculating the actual

22

cover once I returned home from the field. I believe altering this method would result in
more accurate data and potentially better results. The results for the cover variables were
not much different when taking fisher presence into consideration. I expected there to be
a preference for high canopy cover, high vertical cover (leaning logs, boulders, etc), and
medium to low ground cover (grass, ferns, etc) to fit the previous studies performed on
fisher habitat preference (Allen 1983). The lowest canopy cover (33%) was at a site
where fishers were detected. The range for used areas for ground (11-89%) and vertical
(8-100%) were extremely broad (Appendix E). These results suggest that fishers in
Clarion County are not selective when it comes to cover percentages.
The final habitat variables assessed pertain to the tree composition at each site. In
much of the literature, fishers are described as preferring mature, coniferous stands, so I
predicted the fisher would use areas that had conifers present over the fully deciduous
stands. The results indicated no preference for mature forests (trees with larger DBH), or
for the northern hardwood forest that includes the coniferous species found in
Pennsylvania. The distribution of used and unused sites was practically equal in both the
Appalachian Oak forest and the Northern Hardwood forest (Table 3). This implies that
the fishers in the area have adapted to thrive in forested stands of a variety of age and
composition. The average DBH was almost the same for areas where fishers were
detected and areas where they were not (Table 3). There are several ecological
implications of these findings. One is that fishers have become highly adaptable and are
not being partitioned to certain successional stages or types of forest stands. Since the
lure in this study creates a scenario where a fisher is going to come in contact with the
bait due to being on the prowl, it implies that fishers are using a variety of different

23

habitats when hunting. Previous studies that implied fishers prefer coniferous stands were
based on the locations of rest-sites and dens but not on the preference of hunting grounds.
This may indicate a gap in the knowledge of alternate habitat preference when hunting.
In conclusion, the fisher population found in central Clarion County is extremely
adaptable to the current environment. The fishers displayed no significant habitat
preference that would expressively aid us in improve fisher detectability in future studies.
Additional sampling seasons may be required to better answer questions surrounding the
habitat preference of fisher in Pennsylvania. There were no specific cover types, forest
age, or forest composition that was more or less likely for a fisher detection to occur.
With the majority of the land where sampling occurred being reclaimed coal mine
sites, the fishers seem to have recolonized these disturbed areas without hesitation. This
study concludes that of this hair snare design can repeatedly capture fisher non-invasively
and has the potential to be used in future years to monitor the presence and habitat use of
fisher in Clarion County or in the state of Pennsylvania.
I would suggest if this study design is to be used, that no more than three snares
be placed within a unit as the effort put into adding a snare may not reap the benefits of
more detections. This project was very feasible for one or two people to conduct over the
course of a summer season, and it was relatively inexpensive compared to other methods
of monitoring such as radio telemetry. I would highly recommend this type of genetic
presence/absence monitoring for elusive creatures such as fisher.

24

SUGGESTIONS FOR FURTHER RESEARCH
There is much yet that the scientific community needs to investigate for Pekania
pennanti. Once the lab has finished processing the hair samples fully, I intend to use the
individual identifications of fishers to evaluate the number of recaptures. From this
information, I hope to be able to estimate the population size from the probability of
detection which would be a novel method for fisher population estimation in
Pennsylvania. There is a possibility that recaptures have occurred at 10/20 units which
should roughly represent 10 different individuals. Although it is expected to be
successful, if the results do not return multiple recaptures, this would be important
information for future projects involving hair snares and may lead to alterations of the
study design.
Another suggestion is the analysis of fisher use of reclaimed mine sites, and their
hunting ground habitats. From this study, I have found that fishers have moved into
reclaimed mine sites and seem to be prospering, while other species have not moved back
into those areas. Pinpointing what the fishers use within reclaimed mine areas, may help
other reclamation sites in the future. I also believe it would be interesting to conduct a
study on the habitats where fishers hunt. In this study, I used a long-distance lure that
mimicked a prey item to bring fisher to the area. The nature of the lure may have
manipulated a fisher’s normal hunting patterns, so perhaps using a different method to
track fishers while they are hunting could give insight to a different habitat need other
than those already known for den and rest sites.
Lastly, I have been in contact with many fisher researchers who use both the longdistance lure (gusto) and a bait (chicken) when conducting studies on fisher. There is not
25

much information on the effectiveness of gusto and/or bait on detection probability. In
previous studies and personal experience, when using gusto and chicken bait there was
success in detecting fisher, but many of the sites were altered or destroyed by bear. When
conducting this study, I only used gusto and was also successful detecting fisher. The
interesting thing I found was I had a total of three occasions where bear interfered with
the hair snares, and only one of them the bear made the snare inoperable for one sampling
period. I would like to continue this study, but include sites with bait and sites without to
compare bear interference at each. This would help answer a larger question that fisher
researchers have been asking, and if bait is indeed unnecessary, could save research
projects funds that they could use elsewhere.

26

LITERATURE CITED

Allen, A.W. 1983. Habitat Suitability Index (HIS) Models: Fisher. U.S. Fish and Wildlife
Service Biological Report 82, Washington, D.C., USA.
Buskirk, S.W., and R. A. Powell. 1994. Habitat ecology of fishers and American martens.
Pages 283-96 in S.W. Buskirk, A.S. Harestead, M.G. Raphael, and R. Powell,
editors. Martens, sables, and fishers: Biology and conservation. Cornell
University Press, Ithaca, New York, USA.
Douglas, C.W., and M.A. Strickland. 1987. Fisher. Pages 511-30 in M. Novak, J.A.
Baker, M.E. Obbard, and B. Malloch, editors. Wild furbearer management and
conservation in North America. Ontario Ministry of Natural Resources, Toronto,
Canada. (511-30).
Ellington, E. H. 2010. Developing habitat models to predict fisher occupancy in
Pennsylvania. Indiana University of Pennsylvania, Indiana, Pennsylvania, USA
Gilbert, J.H., J.L. Wright, D.J. Lauten, J.R. Probst. 1997. Den and rest-site characteristics
of American marten and fisher in northern Wisconsin. Pages 135-145 in Martes:
taxonomy, ecology, techniques, and management. Provincial Museum of Alberta,
Edmonton, Alberta, CAN.
Gess, S.W., E.H. Ellington, M.R. Dzialak, J.E. Duchamp, M. Lovallo, and J. L. Larkin,
2013. Rest-Site Selection by Fishers (Martest pennanti) in Eastern Deciduous
Forest. Wildlife Society Bulletin, 37(4): 805-814.
Hall, E.R. 1981. The mammals of North America. Second Edition. Volume 2. John Wiley
and Sons, New York, New York, USA.
Lancaster, P.A., J. Bowman, and B.A. Ford. 2008. Fishers, farms, and forests in eastern
North America. Environmental Management 42(1): 93-101.
Leonard, R.D. 1980. Winter activity and movements, winter diet and breeding biology of
the fisher in southeast Manitoba. Thesis, University of Manitoba, Winnipeg,
Canada.
Lovallo, M. J. 2008. Status and Management of Fisher (Martes pennanti) in Pennsylvania
2008-2017. Pennsylvania Game Commission, Harrisburg, Pennsylvania, USA.
Lovallo, M.J., and T.S. Hardisky. 2012. Pennsylvania Game Commission Bureau of
Wildlife Management Project Annual Job Report. Furbearer Population and
Harvest Monitoring. Pennsylvania, USA.
Mullis, K.B., and F.A. Faloona. 1987. Specific synthesis of DNA in vitro via a
polymerase catalyzed chain reaction. Methods in Enzymology, 155: 335-350.

27

Powell, R.A. 1993. The Fisher: life history, ecology, and behavior. Second edition.
University of Minnesota Press, Minneapolis, USA.
Powell, R.A. 1994. Effects of small scale on habitat selection and foraging behavior of
fishers in winter. Journal of Mammalogy 75: 349-56.
Powell, R.A., S.W. Buskirk, and W.J. Zielinski. 2003. Fisher and marten. Pages 635-649
in Wild mammals of North America: Biology, management and economics. G.A.
Feldhamer, B.C. Thompson, and J.A. Chapman, editors. Second edition. John
Hopkins University Press, Baltimore, Maryland, USA.
Rhodes, A.F., and T.A. Block. 2005. Trees of Pennsylvania: a complete reference guide.
The University of Pennsylvania Press, Philadelphia, PA, USA
Weckworth, R.P., and P.L. Wright. 1968. Results of transplanting fisher in Montana.
Journal of Wildlife Management 32: 977-80.
Weir, R.D., and A.S. Harestad. 1997. Landscape-level selectivity by fishers in southcentral British Columbia. Pages 252-264 in Martes: taxonomy, ecology,
techniques, and management. G. Proulx, H.N. Bryant, and P.M. Woodard, editors.
Provincial Museum of Alberta, Edmonton, Alberta, Canada.
Wright, P.L., and M.W. Coulter. 1967. Reproduction and growth in Maine fishers.
Journal of Wildlife Management 31: 70-87.
Zielinski, W.J., N.P. Duncan, E.C. Farmer, R.L. Truex, A.P. Clevenger, and R.H. Barrett.
Diet of fishers (Martes pennanti) at the southernmost extent of their range.
Journal of Mammalogy 80: 961-71.
30 USC 25: 1201-1309b.

28

APPENDIX A

29

APPENDIX B
Demonstration of labeling units A-T based on columns. North is represented by the arrow.

N

B

E

D

A

C
F

G

H

I
Q

R

S

N

O

T

J

L

P

K

M

30

APPENDIX C
Detailed view of schedule for this project broken down into phases.

Phase
Snare placement

Sampling Period 1

Sampling Period 2

Sampling Period
3/Removal of snares

Dates
MAY 29-31
JUN 5-7
JUN 12-14
JUN 19-21
JUN 26-28
JUL 3-5
JUL 10-12
JUL 17-19
JUL 24-26
JUL 31 – AUG 2
AUG 7-9
AUG 14-16

31

Units
A-I
M,O,P,R-T
J-L,N,Q
A-I
M,O,P,R-T
J-L,N,Q
A-I
M,O,P,R-T
J-L,N,Q
A-I
M-O,P,R-T
J-L,N,Q

APPENDIX D
Data from sites consider unused by fisher. Note: E3 was located on the edge of a severe
drop off where tree data could not be collected for one quadrant due to possible dangers
associated with area.
SnareID
A2
A3
B2
C1
D3
E1
E3
F1
H2
H3
I2
J3
L1
L2
L3
M1
N2
O2
O3
P1
Q1
Q2
Q3
R1
R3
S2
S3
T3
A1
B1
B3
C2
C3
D1
D2
E2
F2
F3
G1
G2
G3
H1
I1
I3
J1
J2
K1
K2
K3
M2
M3
N1
N3
O1
P2
P3
R2
S1
T1

%Canopy %Ground
%Vertical Ave. DBH total species
total trees density
stream_dist road_dist %App. Oak%N. Hard
78%
56%
42%
7.11
6
76
760 339.2606264 262.6892 22.37%
68.42%
67%
44%
28%
19.87
6
33
330 269.1397605 147.532 78.79%
21.21%
78%
78%
87%
19.65
9
37
370 194.6218038 185.1367 48.65%
51.35%
100%
78%
51%
7.83
4
124
1240 147.7332878 826.7798 54.84%
41.94%
78%
67%
73%
22.75
4
40
400 98.0830167 1377.792 15.00%
35.00%
89%
89%
35%
15.04
7
59
590 166.9758526 856.1581 22.03%
71.19%
44%
78%
99%
0 51.56129663 966.638
100%
33%
30%
23.88
4
32
320 188.2283121
678.86 28.13%
68.75%
56%
33%
57%
22.62
5
31
310 750.639242 136.223
3.23%
48.39%
67%
56%
23%
22.01
3
35
350 674.8914075 90.71265 11.43%
77.14%
67%
100%
59%
26.41
5
24
240 36.45988703 398.484 75.00%
20.83%
78%
56%
57%
27.79
6
34
340 70.4242742 1555.274 32.35%
67.65%
56%
67%
63%
17.58
6
52
520 103.0939896 1036.922 53.85%
1.92%
89%
33%
93%
20.15
7
61
610 84.52418793 577.672 59.02%
9.84%
89%
22%
97%
22.00
6
42
420 135.2710455 281.0506 52.38%
9.52%
56%
11%
11%
27.12
5
52
520 42.23981173 228.4205 25.00%
75.00%
67%
56%
40%
25.15
8
43
430 26.60401364 1083.244 46.51%
44.19%
67%
44%
64%
25.27
3
30
300 155.4564886 89.77458 43.33%
56.67%
44%
11%
4%
27.06
4
39
390 9.761617942 93.11561
5.13%
94.87%
67%
44%
100%
22.30
5
21
210 52.89227269 325.7336 76.19%
23.81%
78%
78%
19%
37.27
7
20
200 157.0689379 58.46288 75.00%
25.00%
67%
89%
28%
42.73
5
19
190 213.2487244 92.55511 21.05%
78.95%
67%
56%
45%
30.59
5
27
270 207.174374 120.6944 14.81%
85.19%
67%
33%
64%
20.68
6
42
420 12.72151195 557.746 33.33%
61.90%
89%
78%
87%
12.39
6
53
530 256.8959329 537.281 18.87%
81.13%
89%
67%
47%
23.65
5
28
280 165.142703 204.4943 57.14%
39.29%
44%
89%
100%
15.58
4
26
260 80.83561245 157.506 100.00%
0.00%
67%
67%
47%
27.74
5
32
320 254.4442316 920.2599 31.25%
68.75%
78%
67%
53%
19.48
5
41
410 74.66403116 243.7134 29.27%
36.59%
89%
56%
42%
21.36
5
60
600 510.2723039 209.2785 16.67%
13.33%
44%
78%
44%
15.67
5
38
380 206.7040439 97.81455 44.74%
55.26%
78%
67%
27%
18.52
4
58
580 399.7804415 418.5731 72.41%
0.00%
67%
56%
68%
43.49
4
17
170 378.423051 74.37233 100.00%
0.00%
78%
78%
55%
22.18
7
48
480 173.4398631 1164.748 14.58%
37.50%
78%
56%
41%
8.42
7
81
810 266.3959229 1019.737 34.57%
61.73%
67%
56%
49%
11.67
4
107
1070 174.0817387 676.4571 57.94%
42.06%
78%
22%
92%
19.23
7
42
420 251.093529 541.333 69.05%
2.38%
89%
78%
80%
22.99
7
31
310 359.1200033 371.4821 48.39%
45.16%
89%
44%
88%
15.09
6
40
400 294.385468 107.2204
0.00%
77.50%
89%
44%
51%
26.77
8
36
360 15.01671149 298.6066 27.78%
72.22%
89%
11%
16%
30.94
4
34
340 170.3998661 95.95578 32.35%
67.65%
67%
67%
28%
25.10
5
41
410 577.2399607 195.4646 97.56%
2.44%
56%
89%
24%
19.10
6
49
490 298.3546061 364.283 34.69%
63.27%
100%
56%
34%
20.99
8
52
520 228.8072128 175.813 46.15%
48.08%
89%
22%
22%
21.90
7
38
380 123.6688355 1100.39 57.89%
34.21%
78%
67%
23%
25.85
7
32
320 134.0514076 1513.873 68.75%
12.50%
89%
56%
93%
29.03
5
20
200 72.59806287 1474.63 20.00%
60.00%
78%
44%
30%
30.74
7
34
340 67.57134814 1628.896 35.29%
58.82%
89%
44%
45%
30.51
6
36
360 93.02929513 1593.412 38.89%
58.33%
67%
67%
63%
37.78
5
18
180 260.6262421 585.442 38.89%
61.11%
78%
67%
34%
37.21
5
20
200 699.819246 776.2355 15.00%
70.00%
89%
67%
75%
22.15
8
50
500 13.88427504 1002.253 46.00%
20.00%
56%
89%
74%
38.36
7
15
150 32.88215057 1287.14 13.33%
80.00%
67%
11%
8%
27.66
61
610 104.0835367 99.93174 21.31%
77.05%
32 6
33%
67%
61%
19.15
6
40
400 133.1353813 101.3046 55.00%
20.00%
89%
33%
14%
20.95
6
56
560 254.6800306 203.5601 19.64%
78.57%
44%
89%
16%
23.11
5
23
230 475.6244143
80.526 95.65%
4.35%
44%
56%
18%
28.98
4
37
370 249.1195176 48.21284 75.68%
24.32%
67%
22%
36%
30.02
7
41
410 73.7706618 1037.288 43.90%
56.10%

M1
56%
11%
11%
27.12
5
52
520 42.23981173 228.4205 25.00%
75.00%
N2
67%
56%
40%
25.15
8
43
430 26.60401364 1083.244 46.51%
44.19%
O2
67%
44%
64%
25.27
3
30
300 155.4564886 89.77458 43.33%
56.67%
O3
44%
11%
4%
27.06
4
39
390 9.761617942 93.11561
5.13%
94.87%
P1
67%
44%
100%
22.30
5
21
210 52.89227269 325.7336 76.19%
23.81%
Q1
78%
78%
19%
37.27
7
20
200 157.0689379 58.46288 75.00%
25.00%
Q2
67%
89%
28%
42.73
5
19
190 213.2487244 92.55511 21.05%
78.95%
Q3
67%
56%
45%
30.59
5
270 207.174374 120.6944 14.81%
85.19%
APPENDIX
E 27
R1
67%
33%
64%
20.68
6
42
420 12.72151195 557.746 33.33%
61.90%
R3
89% with snares
78%
87% considered
12.39
6 by fisher.
53
530 256.8959329 537.281 18.87%
81.13%
Data
associated
in areas
used
S2
89%
67%
47%
23.65
5
28
280 165.142703 204.4943 57.14%
39.29%
S3
44%
89%
100%
15.58
4
26
260 80.83561245 157.506 100.00%
0.00%
SnareID
%Canopy
Oak%N. Hard
T3
67% %Ground67% %Vertical
47% Ave. DBH
27.74 total species
5 total trees32 density 320 stream_dist
254.4442316 road_dist
920.2599 %App.
31.25%
68.75%
A2
78%
56%
42%
7.11
65
76
760
68.42%
A1
78%
67%
53%
19.48
41
410 339.2606264
74.66403116 262.6892
243.7134 22.37%
29.27%
36.59%
A3
67%
44%
28%
19.87
65
33
330
147.532 78.79%
21.21%
B1
89%
56%
42%
21.36
60
600 269.1397605
510.2723039 209.2785
16.67%
13.33%
B2
78%
78%
87%
19.65
95
37
370
51.35%
B3
44%
78%
44%
15.67
38
380 194.6218038
206.7040439 185.1367
97.81455 48.65%
44.74%
55.26%
C1
100%
78%
51%
7.83
44
124
1240
41.94%
C2
78%
67%
27%
18.52
58
580 147.7332878
399.7804415 826.7798
418.5731 54.84%
72.41%
0.00%
D3
78%
67%
73%
22.75
44
40
400
15.00%
35.00%
C3
67%
56%
68%
43.49
17
170 98.0830167
378.423051 1377.792
74.37233 100.00%
0.00%
E1
89%
89%
35%
15.04
77
59
590
71.19%
D1
78%
78%
55%
22.18
48
480 166.9758526
173.4398631 856.1581
1164.748 22.03%
14.58%
37.50%
E3
44%
78%
99%
0 51.56129663
966.638 34.57%
D2
78%
56%
41%
8.42
7
81
810
266.3959229 1019.737
61.73%
F1
100%
33%
30%
23.88
44
32
320 188.2283121
678.86 28.13%
68.75%
E2
67%
56%
49%
11.67
107
1070
174.0817387 676.4571
57.94%
42.06%
H2
56%
33%
57%
22.62
57
31
310
3.23%
48.39%
F2
78%
22%
92%
19.23
42
420 750.639242
251.093529 136.223
541.333 69.05%
2.38%
H3
67%
56%
23%
22.01
37
35
350
77.14%
F3
89%
78%
80%
22.99
31
310 674.8914075
359.1200033 90.71265
371.4821 11.43%
48.39%
45.16%
I2
67%
100%
59%
26.41
56
24
240
398.484 75.00%
20.83%
G1
89%
44%
88%
15.09
40
400 36.45988703
294.385468 107.2204
0.00%
77.50%
J3
78%
56%
57%
27.79
6
34
340
70.4242742
1555.274
32.35%
67.65%
G2
89%
44%
51%
26.77
8
36
360 15.01671149 298.6066 27.78%
72.22%
L1
56%
67%
63%
17.58
64
52
520
1.92%
G3
89%
11%
16%
30.94
34
340 103.0939896
170.3998661 1036.922
95.95578 53.85%
32.35%
67.65%
L2
89%
33%
93%
20.15
75
61
610
577.672 59.02%
9.84%
H1
67%
67%
28%
25.10
41
410 84.52418793
577.2399607 195.4646
97.56%
2.44%
L3
89%
22%
97%
22.00
6
42
420
135.2710455
281.0506
52.38%
9.52%
I1
56%
89%
24%
19.10
6
49
490 298.3546061 364.283 34.69%
63.27%
M1
56%
11%
11%
27.12
58
52
520
75.00%
I3
100%
56%
34%
20.99
52
520 42.23981173
228.8072128 228.4205
175.813 25.00%
46.15%
48.08%
N2
67%
56%
40%
25.15
87
43
430
44.19%
J1
89%
22%
22%
21.90
38
380 26.60401364
123.6688355 1083.244
1100.39 46.51%
57.89%
34.21%
O2
67%
44%
64%
25.27
37
30
300
56.67%
J2
78%
67%
23%
25.85
32
320 155.4564886
134.0514076 89.77458
1513.873 43.33%
68.75%
12.50%
O3
44%
11%
4%
27.06
45
39
390
5.13%
94.87%
K1
89%
56%
93%
29.03
20
200 9.761617942
72.59806287 93.11561
1474.63 20.00%
60.00%
P1
67%
44%
100%
22.30
57
21
210
23.81%
K2
78%
44%
30%
30.74
34
340 52.89227269
67.57134814 325.7336
1628.896 76.19%
35.29%
58.82%
Q1
78%
78%
19%
37.27
76
20
200
25.00%
K3
89%
44%
45%
30.51
36
360 157.0689379
93.02929513 58.46288
1593.412 75.00%
38.89%
58.33%
Q2
67%
89%
28%
42.73
55
19
190
78.95%
M2
67%
67%
63%
37.78
18
180 213.2487244
260.6262421 92.55511
585.442 21.05%
38.89%
61.11%
Q3
67%
56%
45%
30.59
55
27
270
85.19%
M3
78%
67%
34%
37.21
20
200 207.174374
699.819246 120.6944
776.2355 14.81%
15.00%
70.00%
R1
67%
33%
64%
20.68
68
42
420
557.746 33.33%
61.90%
N1
89%
67%
75%
22.15
50
500 12.72151195
13.88427504 1002.253
46.00%
20.00%
R3
89%
78%
87%
12.39
67
53
530
81.13%
N3
56%
89%
74%
38.36
15
150 256.8959329
32.88215057 537.281
1287.14 18.87%
13.33%
80.00%
S2
89%
67%
47%
23.65
56
28
280
165.142703 204.4943
39.29%
O1
67%
11%
8%
27.66
61
610 104.0835367
99.93174 57.14%
21.31%
77.05%
S3
44%
89%
100%
15.58
4
26
260 80.83561245 157.506 100.00%
0.00%
P2
33%
67%
61%
19.15
6
40
400 133.1353813 101.3046 55.00%
20.00%
T3
67%
67%
47%
27.74
5
32
320 254.4442316 920.2599 31.25%
68.75%
P3
89%
33%
14%
20.95
6
56
560 254.6800306 203.5601 19.64%
78.57%
A1
78%
67%
53%
19.48
5
41
410 74.66403116 243.7134 29.27%
36.59%
R2
44%
89%
16%
23.11
5
23
230 475.6244143
80.526 95.65%
4.35%
B1
89%
56%
42%
21.36
5
60
600 510.2723039 209.2785 16.67%
13.33%
S1
44%
56%
18%
28.98
4
37
370 249.1195176 48.21284 75.68%
24.32%
B3
44%
78%
44%
15.67
5
38
380 206.7040439 97.81455 44.74%
55.26%
T1
67%
22%
36%
30.02
7
41
410 73.7706618 1037.288 43.90%
56.10%
C2
78%
67%
27%
18.52
4
58
580 399.7804415 418.5731 72.41%
0.00%
T2
78%
11%
33%
19.57
4
52
520 225.4727661 1034.465 98.08%
1.92%
C3
67%
56%
68%
43.49
4
17
170 378.423051 74.37233 100.00%
0.00%
D1
78%
78%
55%
22.18
7
48
480 173.4398631 1164.748 14.58%
37.50%
D2
78%
56%
41%
8.42
7
81
810 266.3959229 1019.737 34.57%
61.73%
E2
67%
56%
49%
11.67
4
107
1070 174.0817387 676.4571 57.94%
42.06%
F2
78%
22%
92%
19.23
7
42
420 251.093529 541.333 69.05%
2.38%
F3
89%
78%
80%
22.99
7
31
310 359.1200033 371.4821 48.39%
45.16%
G1
89%
44%
88%
15.09
6
40
400 294.385468 107.2204
0.00%
77.50%
G2
89%
44%
51%
26.77
8
36
360 15.01671149 298.6066 27.78%
72.22%
G3
89%
11%
16%
30.94
4
34
340 170.3998661 95.95578 32.35%
67.65%
H1
67%
67%
28%
25.10
5
41
410 577.2399607 195.4646 97.56%
2.44%
I1
56%
89%
24%
19.10
6
49
490 298.3546061 364.283 34.69%
63.27%
I3
100%
56%
34%
20.99
8
52
520 228.8072128 175.813 46.15%
48.08%
J1
89%
22%
22%
21.90
7
38
380 123.6688355 1100.39 57.89%
34.21%
J2
78%
67%
23%
25.85
7
32
320 134.0514076 1513.873 68.75%
12.50%
K1
89%
56%
93%
29.03
5
20
200 72.59806287 1474.63 20.00%
60.00%
K2
78%
44%
30%
30.74
7
34
340 67.57134814 1628.896 35.29%
58.82%
K3
89%
44%
45%
30.51
6
36
360 93.02929513 1593.412 38.89%
58.33%
M2
67%
67%
63%
37.78
5
18
180 260.6262421 585.442 38.89%
61.11%
M3
78%
67%
34%
37.21
5
20
200 699.819246 776.2355 15.00%
70.00%
N1
89%
67%
75%
22.15
8
50
500 13.88427504 1002.253 46.00%
20.00%
N3
56%
89%
74%
38.36
7
15
150 32.88215057 1287.14 13.33%
80.00%
O1
67%
11%
8%
27.66
6
61
610 104.0835367 99.93174 21.31%
77.05%
P2
33%
67%
61%
19.15
6
40
400 133.1353813 101.3046 55.00%
20.00%
P3
89%
33%
14%
20.95
6
56
560 254.6800306 203.5601 19.64%
78.57%
33 5
R2
44%
89%
16%
23.11
23
230 475.6244143
80.526 95.65%
4.35%
S1
44%
56%
18%
28.98
4
37
370 249.1195176 48.21284 75.68%
24.32%
T1
67%
22%
36%
30.02
7
41
410 73.7706618 1037.288 43.90%
56.10%
T2
78%
11%
33%
19.57
4
52
520 225.4727661 1034.465 98.08%
1.92%