Am. Midl. Nat. 164:61–73
Assessing the Distribution of Eastern Moles (Scalopus
aquaticus) in Canada in Relation to Loam Soils and Forest Cover
LOUISE E. RITCHIE1
AND
JOSEPH J. NOCERA
Ontario Ministry of Natural Resources, Trent University, DNA Building, 2140 East Bank Drive,
Peterborough K9J 7B8
ABSTRACT.—We assessed the distribution of Eastern moles Scalopus aquaticus in relation to
loam soils under the hypothesis that the species’ Canadian distribution is limited by soil type.
We also explore the relationship between mole occurrence and the amount of forest cover at
a local (49 m) and landscape (305 m) scale. We resurveyed 46 sites dispersed across much of
the species’ Canadian range in southern Ontario. These sites initially were inspected for mole
sign (e.g., surface tunnels and earth mounds) in 1997, allowing us to compare between study
periods to assess changes in species distribution. Eastern moles were eight times more likely
to occur at sites with loam or sandy loam soils than at sites with other soil textures (e.g., coarse
sands, clays). The likelihood of mole sign no longer occurring at a site in 2008 increased in
the absence of loam or sandy loam soils. At sites with loam or sandy loam soils, including the
proportion of forest cover within the surrounding landscape increased our ability to
discriminate between sites with and without mole sign. We noted a 26% decrease in mole
occurrence across our study area since it was surveyed more than a decade ago.
INTRODUCTION
Talpid moles are relatively common in North America, yet they remain surprisingly
understudied and are among the most poorly understood North American mammalian taxa
(Hartman and Yates, 2003). The Eastern mole (Scalopus aquaticus Linnaeus, 1758) has the
largest range of all North American moles (Yates and Schmidly, 1978). It is a conservation
concern in several states (Colorado, West Virginia and Wyoming) and has a very limited
distribution within Canada (NatureServe, 2008). The Canadian race is geographically
restricted to the vicinity of Essex County and Chatham-Kent municipality in Southern Ontario
(see Waldron et al., 2000) and has the largest individuals of the species (Banfield, 1974).
Currently, there are few quantitative data describing the occurrence patterns, habitat
associations and population stability of Eastern moles. This species is the most subterranean
of North American moles (Banfield, 1974), rarely straying from underground tunnel
networks. Individuals rarely are observed directly but their tunnelling behaviour provides an
index of species occurrence and activity. Such surface indices are frequently used for broad
scale studies of species abundance and distribution (Hartman and Krenz, 1993; Rosenblatt
et al., 1999; Duhamel et al., 2000; Waldron et al., 2000; Berthier et al., 2005; Delattre et al.,
2006). Eastern moles construct two distinct types of tunnels; surface tunnels (,10 cm) that
are foraging runways and deep (10–40 cm) tunnels that are less noticeable, more
permanent structures. Deep tunnels are typically associated with earth mounds caused by
animals piling soil removed during tunnel construction. Eastern moles are intolerant of
openings in their burrow system and will persistently repair damaged tunnels (Hartman and
Yates, 2003).
Soil type, condition and moisture levels may be important limiting factors affecting mole
distribution. Individuals of the species reportedly prefer moist loams, may use sandy soils,
1
Corresponding author: e-mail: [email protected]
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but avoid clay, stony or gravely soils and arid lands (Arlton, 1936; summarized in Yates and
Schmidley, 1978; Waldron et al., 2000). However, quantitative data for these relationships
are lacking because authors fail to provide support or cite largely descriptive studies that did
not quantify the relationship (Arlton, 1936; Davis, 1942; Banfield, 1974; Yates and Schmidly,
1978; Hartman and Yates, 2003 and references therein). It has been suggested that the
distribution of Eastern moles may be affected by proximity to forest cover. Banfield (1974)
indicated that the species ‘‘prefers moist friable loams in open woodlands and pastures.’’
Waldron et al. (2000) found mole signs most frequently in forested areas, along hedgerows,
watercourses and open drains. Species are influenced in different manners by processes
operating at different scales, resulting in the emergence of scale-dependent patterns
(Wiens, 1989). The effects, if any, of wooded areas on the distribution of Eastern moles
remains relatively unexplored.
The objective of our study was to evaluate whether the distribution of Eastern moles
coincides with that of loam and sandy loam soils. We explored whether the presence of mole
activity was associated with remnant forest cover at two different spatial scales in a region
dominated by agriculture. We used decade old mole survey data from our study area
(collected in 1997, Waldron et al., 2000) to indicate population stability at the north-eastern
edge of the species’ range.
METHODS
We surveyed 46 sites in the eastern deciduous forest region of southern Ontario (Fig. 1;
Rowe, 1972) for fresh signs of mole activity (i.e., tunnels and earth mounds). Essex County
encompassed the large majority (41/46) of our survey sites. Essex is dominated by
agricultural lands and has ,10% forest cover (Essex Region Conservation Authority, 2002a,
b; Dobbie et al., 2007). The county has ridges of gravely and sandy soils overlaying a smooth
clay plain and limestone bedrock. These soil conditions originated from the region’s
topographical history during which glaciers moved through the region and created lakes
(Richards et al., 1949). This region has the warmest temperatures in Ontario and has
relatively little annual precipitation (,70 cm).
The survey sites were originally selected and assessed for mole sign in 1997 (Waldron et al.,
2000); our return in 2008 enabled us to assess the stability of mole sign between these two
survey periods. The surveys in 1997 occurred during the summer and fall field season, but
no exact dates are available (G. Waldron, pers. comm.). In 2008, all surveys except one were
conducted between 16 and 29 Sep. 2008; Fish Point Provincial Nature Reserve was surveyed
in mid Nov., 2008. We were denied access to resurvey two sites. Survey sites varied in size and
by type of land use (e.g., woodlots, fields, manicured lawns).
We use survey site as our sampling unit during analysis. To establish a repeatable survey
method while maintaining a similar survey effort between studies, we used the following
survey protocol: (1) where pathways or trails were available, we walked the route that would
allow us to cover the largest portion of the property; (2) if no trails were apparent, we walked
a 500 m transect through the site; (3) if the property dimensions prevented us from walking
a single 500 m transect, we walked transect segments summing to 500 m. Trails and
coordinates recorded for transect ends provide more clearly defined survey routes for future
monitoring efforts. Mole presence was recorded upon the first encounter of fresh mole sign
and a geographic position was recorded using a hand-held GPS unit. Fresh mole sign
consisted of earth mounds or surface tunnels that easily gave way when slight pressure was
applied. Suspected tunnels were confirmed by feeling for tunnel passages. The mole sign
within our study area could safely be attributed to Eastern moles because they are not
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FIG. 1.—Study sites within Essex, Middlesex (Strathroy) and Elgin (Rodney) Counties and the
Municipality of Chatham-Kent where the presence or absence of mole signs were recorded during field
surveys in 1997 and 2008
sympatric with Hairy-tailed moles (Parascalopus breweri) in Canada, and summer and fall livetrapping efforts within Essex County (.500 trap nights) resulted in the capture of only
Eastern moles. Generally mole sign is more easily and quickly detected in clearings with low
vegetation than in forested areas with uneven terrain or dense ground vegetation. However,
our survey methods reduce the effects of this possible bias; we surveyed each site until we
either encountered signs of mole activity or until the entire site had been surveyed.
Typically, this means that additional time and effort was spent at sites where mole sign might
be the most difficult to detect. The presence of suspected surface tunnels was confirmed by
inserting a finger or stick into the tunnel passage. At a smaller scale, the estimated
proportion of wooded area may be less accurate due to the relative effect of small wooded
patches unaccounted for by the initial definition used during the creation of the wooded
area data layer. No such discrepancy was obvious during field visits.
To examine mole distribution in relation to soil characteristics, we classified 19 soil types
into six broader categories based on: geological parent material, drainage and general soil
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description (Hoffman et al., 1964; Schut, 1992). The six categories (Soil Type) were: Fox
Sandy Loam (n 5 8), Harrow Loam and Sandy Loam (n 5 7), Berrien Sandy Loam or
Burford Loam (n 5 8), sands (Berrien, Eastport and Plainfield Sand, n 5 6), very fine
textured sands/sandy loams and silt loams (n 5 10, Tuscola Fine Sandy Loam subset 5 3)
and clays, marshes and wetlands (n 5 7). We also defined two broader soil groups
identifying soil types as loam/sandy loam (n 5 29, including fine sandy loam) or not (n 5
17). Several of the sites were initially classified as soil spot phases (Parkhill Loam – Red
Sand, Caistor Clay Sand, Brookston Clay Sand; Richards et al., 1949). Soil conditions within
spot phases are more variable due to the presence of scattered sandy knolls, therefore these
sites were assigned based on local soil conditions. Tuscola Fine Sandy Loam was classified as
‘Loam’. We used univariate logistic regression models to select between using a six level or
binary soil classification during subsequent analyses.
To evaluate mole response to local and landscape forest cover, we used logistic regression
to assess the correlation between mole occurrence and the proportion of forest cover within
an estimated mean home range size (49 m radius, 0.75 ha, ‘Local Forest’) and an estimated
dispersal distance (305 m radius, ‘Landscape Forest’). Forest cover at these two scales was
calculated using a Geographic Information System data layer adopted from the Southern
Ontario Ecological Land Classification (Lee et al., 1998). We used the center of the survey
site when determining forest cover in the surrounding area. Although male Eastern moles
typically have larger home ranges than females (1 ha and 0.3 ha respectively; Harvey, 1976),
we used a home range size averaged across both sexes for our calculations because outside
the breeding season, the observed sex ratio likely does not differ from 1:1 (0.75 ha; Harvey,
1976; Hartman, 1995a). We use a dispersal distance of 305 m to delimit a landscape extent
for forest cover. This radius was estimated from Townsend’s moles (Scapanus townsendii)
because little is known about the dispersal behaviour of Eastern moles. Giger (1965) found
that 87% of juveniles S. townsendii dispersed ,305 m from their birth nests. In a study on
Eastern mole home range size, movements and activity patterns, Harvey (1976) remarked
one mole undertook an unusually far displacement away from his nest (204 m). We do not
report on the effect of forest patch size (in hectares) because this variable had a skewed
distribution even after transformation.
We used several statistical descriptors to summarize logistic regression model performance (i.e., amount of information lost corrected for small sample size—AICc and DAICc;
Akaike, 1974; see review by Burnham and Anderson, 2002), fit (residual deviance) and
accuracy (Area Under the receiver operating characteristic Curve, AUC) and the associated
model (Mann-Whitney U P-value). AUC measures a model’s ability to discriminate between
sites with and without observed mole activity. Values $ 0.7 indicate acceptable
discrimination; whereas, those $ 0.8 indicate excellent discrimination (Hosmer and
Lemeshow, 2000). We evaluated the distribution of standardized deviance residuals in
normal Q-Q plots and use the Cook Statistic to assess whether any sites exerted a
disproportionate influence on model prediction. We retain all sites during our analyses of
the 2008 survey data, but discuss any sites identified as potential outliers.
We determined the amount of unique (or conditional) variance explained by each
variable in our global model which included Loam, Local Forest and Dispersal Forest as
predictor variables. We did this by subtracting the amount of shared (or confounded)
variance explained by each predictor variable from the amount of variance it explained in a
univariate context. A variable’s unique variance represents the additional variance it
explains after accounting for the variance explained by all other variables (Fletcher and
Hutto, 2008).
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We restricted our initial analyses to main effects, but conducted a post hoc assessment of
putative interactions for all variables, including Land Class. We used the Southern Ontario
Land Resource Information System (2000–2002 release) to classify sites into one of three
Land Class categories: Vegetated (e.g., deciduous forests, forests, hedgerows, n 5 19), Built
up/Lawns (open and/or grassy areas, n 5 20) and Wetlands (marshes, swamps and
shorelines, n 5 9). We did so to assess whether any correlation between Eastern mole
occurrence and soil condition or forest cover varies with local land cover.
We used the sites with mole sign in either 1997 or 2008 (n 5 23) to assess what site
characteristics, if any, were correlated with the change in mole sign distribution between
surveys. Sites occupied in 1997 but without mole sign in 2008 were classified as having
experienced a change in distribution. Statistical significance was assumed at P # 0.05 when
assessing statistical interactions and for change in distribution analyses. Values are reported
as Estimate(Standard Error). We conducted our statistical analyses using R v. 2.7.1 (R
Development Core Team, 2008).
RESULTS
Evidence of Eastern mole activity was detected at 37% (17/46) of survey sites in 2008
(Fig. 1), only two of these 17 sites were classified as not having loam or sandy loam
(‘‘Loam’’) soils. Among all 46 sites, 29 were classified as having Loam soils, and just over
half of those had Eastern mole activity (15/29). No new mole sign was found at sites
where none had been detected in 1997, and moles apparently were absent from six sites
where their activity previously had been detected. Only one of these sites had Loam
soils.
We assessed and ranked eight models generated from Loam, Local Forest and Dispersal
Forest (Table 1, rlocal-landscape forest 5 0.29). Fairview Cemetery, Cinnamon Fern Environmentally Significant Area (ESA) and Kurtz Farm were identified as sites that exerted a
disproportional influence on one or more models. Fairview Cemetery and Cinnamon Fern
were both located in areas with Plainfield Sand soils and were the only sites with mole sign
not classified as Loam soils. Kurtz Farm had a high proportion of forest cover within 305 m
(0.84). We observed no mole sign at this site.
Loam occurred in the top four models as ranked by AICc. These models explained the
greatest amount of variance (residual variance: 51.04–52.48) and had AUC scores ranging
from 0.63 to 0.77 (indicating reasonable discrimination ability). The models best able to
discriminate between sites with and without mole sign were those including Loam and forest
cover (Loam and Dispersal Forest: AUC 5 0.77; Loam and Local Forest: AUC 5 0.75). The
model including only the presence of loam or sandy loam soils had lower discriminatory
ability (AUC 5 0.70). Loam uniquely explained 79% of the total variance explained by the
global model, whereas Local and Landscape Forest cover accounted for 6% and 5%
respectively (Fig. 3).
Post hoc assessment of interactions indicated that the effect of landscape forest cover
depended on both the site’s land classification and the presence of Loam soils. There was a
positive correlation between the amount of landscape forest cover and the presence of mole
sign at sites in open grassy areas; we detected no relationship between sites with woody
vegetation or located within wetland areas [Built up lawn: 8.33(4.19), P 5 0.05; Fig. 2]. At
sites with Loam soils, mole sign was more likely with increasing proportions of landscape
forest cover [Loam 5 1: 4.89(2.42), P 5 0.04; Loam 5 0: 22.27(3.33), P 5 0.50]. We did not
detect any other two-way interactions (P . 0.05).
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TABLE 1.—Logistic regression models describing the distribution of Eastern moles Scalopus aquaticus
in southern Ontario based on soil type (Loam, a binary variable: 1 5 Loam, 0 5 Not Loam) and the
proportion of forest cover at a local (within home range, 49 m radius, 0.75 ha) and landscape (within
dispersal distance, 305 m, 29 ha) scale. Model reporting includes Estimate(SE), model ranking criteria
(AICc, unadjusted Mann-Whitney U P-value), measures of fit (residual deviance, Null 5 60.60) and
accuracy (area under the receiver operator curve AUC)
Model
2.08(0.84) Loam 2 2.01
2.16(0.86) Loam + 1.90(1.88) Dispersal Forest 2 2.45
2.01(0.85) Loam + 0.86(0.94) Local Forest 2 2.25
2.08(0.87) Loam + 0.65(0.98) Local Forest + 1.55(1.97)
Dispersal Forest 2 2.54
1.13(0.87) Local Forest 2 0.92
1.45(1.68) Dispersal Forest 2 0.82
1.00(0.91) Local Forest + 0.95(1.76) Dispersal Forest 2 1.06
AICc
DAICc
Variance
df
AUC
56.76
58.05
58.21
0.00
1.29
1.45
52.48
51.48
51.64
44
43
43
0.70
0.77
0.75
60.02
63.18
64.13
65.18
3.26
6.42
7.37
8.42
51.04
58.90
59.85
58.61
42
44
44
43
0.76
0.63
0.65
0.63
CHANGE IN DISTRIBUTION (1997–2008)
Approximately one quarter (6 of 23) of the sites where mole sign had been reported in
1997 no longer had mole activity. The only predictor of this change in distribution was the
presence of loam or sandy loam soils, which was inversely related to the probability of mole
sign disappearing from the site. Loam accounted for approximately 2/5 of the variance
(10.55, null variance 5 26.40, Px2 , 0.01, AUC 5 0.86, PAUC , 0.01).
DISCUSSION
Eastern moles were approximately eight times more likely to occur at sites with soils
classified as either loam or sandy loams than any other soil type. Evidence of mole activity
was no longer detected at 26% of the surveyed sites where moles had been detected a
decade prior. We returned to those survey sites with a change in mole distribution with the
lead author of the original survey work, G. Waldron, to assess if there was a noticeable
change in site conditions. Other than the addition of recreational infrastructure (e.g., stage,
maintained lawn, etc.) at one site, no obvious changes were observed. We were unable to reaccess one site due to logistical constraints. In contrast to the disappearance of moles at six
sites, mole sign was not found at any survey sites where it had not previously been recorded.
Sites with loam or sandy loam soils were more likely to retain signs of mole activity between
the 1997 and 2008 sampling periods. However, our study was not designed to determine the
mechanism(s) of this correlation.
The structure and moisture balance of loam soils may make them easier to dig through,
thus allowing a tunnelling mole to conserve energy (Arlton, 1936; Hartman and Yates, 2003).
Conversely, moles may not select loams or sandy loams per se, but rather avoid harder and drier
soils that are more difficult to tunnel through (Yates and Schmidly, 1978). Evidence of mole
activity was absent from all but two sites without Loam soils. It was also absent from
approximately half of the survey sites with Loam soils, suggesting that knowledge of a site’s soil
texture is important, but insufficient, information to predict mole occurrence.
Moles are adapted to a subterranean and energetically expensive lifestyle involving an
increased need for heat dissipation while digging extensive tunnel networks (Hartman and
Yates, 2003); Habitat selection may also relate to these challenges (e.g., selection of soils with
better oxygen availability). Alternatively, variation in prey density such as earthworms, grubs
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FIG. 2.—Interaction between A) open grassy areas/lawns and B) loam or sandy loam soils with the
amount of forest cover within the surrounding landscape (305m radius). Sample sizes are indicated
above the error bars illustrating the standard error
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FIG. 3.—The amount of unique and shared variance explained by each predictor of Eastern mole sign.
Values are reported as a percentage of the total variance explained by the global model including soil
conditions and the amount of forest cover within a 49 m (Local Forest) and 305 m radius
(Dispersal Forest)
or ants between Loam and other soil types may affect the distribution of Eastern moles by
altering food availability (Arlton, 1936; Brown, 1972; Edwards et al., 1999).
The number of sites with loam or sandy loam soil texture lacking mole sign highlights the
need to consider other factors affecting Eastern mole distribution. The relationship
between forest cover (or a latent covariate) and Eastern mole occurrence appears to vary
with scale, soil texture and possibly on the type cover at the site (e.g., vegetated, wetland or
lawns). Sites with loam or sandy loam soils were more likely to have mole sign if the
surrounding landscape had higher proportions of landscape forest cover. Moles may
abandon tunnels for a variety of reasons (e.g., soil desiccation, low food availability,
structural disturbance, to undertake natal or breeding dispersal, Arlton, 1936). It is possible
that moles are more likely to abandon surface tunnels in areas with little forest cover
(Arlton, 1936). Forested areas may serve as core areas from which surface tunnel networks
can extend. Moles are prone to deserting or deepening their tunnels during periods of
drought and high temperatures (Hisaw, 1923; Arlton, 1936). The shady conditions provided
by forests may buffer the rate of moisture and temperature change. Moles apparently can
detect and respond to prolonged cool temperatures. This is supported by the fact that moles
near wooded areas seem to moult later than those found in treeless areas (Arlton, 1936). We
hypothesize that the prolonged retention of soil moisture near wooded areas may allow
moles to maintain a larger foraging area during dry periods and to avoid the energy costs of
digging new surface tunnels or deepening old ones.
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There are several reasons why mole distribution may more closely coincide with forest
cover at a landscape scale than at a local scale. The processes for which forest cover may be
the most important could include dispersal or exploratory movements and/or seeking
mating opportunities. The most vulnerable life stage for subterranean animals is within the
first 6 mo after birth (50% mortality, Hartman, 1995b), likely in part due to increased
predator exposure during dispersal (Hartman and Yates, 2003). A subset of juvenile moles
may disperse above ground (Leftwich, 1972 in Hartman and Yates, 2003) and moles
inhabiting isolated tunnel systems may occasionally visit the surface during the breeding
season to find mates (Arlton, 1936). We hypothesize that availability of forest cover during
these dispersal movements may decrease the dispersal mortality rate and increase the
probability of successful colonization.
We also found some support for a positive correlation between the amount of landscape
forest cover and the presence of mole sign in open grassy areas. The surface tunnels
observed at sparsely vegetated sites (e.g., grassy or bare ground) may have been linked to
deeper tunnel networks radiating from forested areas with more stable soil conditions where
tunnels are protected from frequent mechanical disturbance. The permanent, deep tunnels
of Eastern moles may be preferentially situated under fencerows and serve as major travel
corridors (Harvey, 1976). A comparatively low rate of soil disturbance would reduce the
need for tunnel repair while protecting nest sites and possible areas of food storage (as seen
in Talpa europaea; see Gorman and Stone, 1990, p. 21) from physical disturbance. These areas
may serve as a source for dispersing individuals.
CONCLUSION
We quantitatively assessed the distribution of Eastern moles in relation to loam or sandy
loam soils and explored the interaction between Eastern moles and elements of landscape
composition. We found that (1) Eastern moles are more likely to occur at sites with loam soil
conditions, (2) the species’ continued presence at a site is more likely in the presence of loam
and sandy loam soils (3) Eastern moles were more likely to occupy sites with a greater
proportion of forest cover within 305 m, an estimated distance over which dispersing moles
may travel. Our results suggest that, in addition to being associated with loam and sandy loam
soils, moles might do best in a heterogeneous landscape, with forested areas potentially
providing long-term stability whereas open areas may provide more efficient foraging
grounds. An understanding of the factors influencing the species’ distribution will help
provide focus for future scientific research and in supporting population management efforts.
Acknowledgments.—We are grateful to Point Pelee National Park (particularly V. McKay and T. Dobbie)
and the Essex Regional Conservation Authority for logistical support. G. Waldron provided additional
details regarding the 1997 survey. We thank G. Waldron, A. Argue and H. Simpson for assistance in the
field. Funding was provided by the Ontario Ministry of Natural Resources (Wildlife Research and
Development Sections, Species at Risk Branch and Youth Programs).
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SUBMITTED 27 FEBRUARY 2009
ACCEPTED 31 SEPTEMBER 2009
Supplementary Material
TABLE S1.—Sites resurveyed for mole sign (surface tunnels and push-ups) in Sep. 2008, including
UTM coordinates (Zone 17, NAD83), soil classification, proportion of local forest cover (within an
average home-range area, 0.75ha, Local Forest) and forest cover within a dispersal distance (305m,
Landscape Forest). E.S.A 5 Environmentally Significant Area, C.A. 5 Conservation Area. A) Sites
without mole sign; B) Sites with mole sign. Permission was not granted to resurvey two sites in 2008
X
LaSalle
Kurtz Farm
West Branch of Two
Creeks
Kennedy Woods, Jack
Miner Sanctuary
East Mersea Public
School
331262
348400
378948
4678639 Berrien Sand
4654800 Bottom Land
4660556 Bottom Land
0
0
0
Vegetated
Wetlands
Built-up lawns
0.26
0.21
0.25
0.54
0.84
0.09
355529
4658472 Brookston Clay
0
Vegetated
0.59
0.13
376799
0
Built-up lawns
0.00
0.00
Oxley Poison Sumac
Swamp E.S.A.
Wilson Farm (Rd 2
West)
Point Pelee Dr.
Fish Point Provincial
Nature Reserve
Marentette Beach
Two Creeks
Conservation Area
Hillman Marsh
Conservation Area
345254
0
Vegetated
0.38
0.44
0
Vegetated
0.00
0.10
371471
360932
4660443 Brookston Clay
Sand—Spot
Phase
4652590 Caistor Sand—Spot
Phase
4657016 Caistor Sand—Spot
Phase
4649953 Eastport Sand
4621218 Eastport Sand
0
0
Built-up lawns
Vegetated
0.00
0.43
0.00
0.11
376546
379300
4652601 Eastport Sand
4663500 Eroded Channel
0
0
Wetlands
Vegetated
0.00
1.00
0.01
0.14
374738
4655492 Marsh
0
Wetlands
0.00
0.00
354284
Y
Soil classification
Loam
Land class
Local Landscape
forest
forest
A) Site name
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THE AMERICAN MIDLAND NATURALIST
164(1)
TABLE S1.—Continued
A) Site name
X
Anderson Woods
359360
Wheatley Provincial
Park
Strathroy
Bayview Cemetery
Heinz Woods
Iler Cemetery
Olinda UnitarianUniversalist
Cemetery
Cedar Creek
Conservation Area
Ruthven Cemetery
Union Water Plant
Afflect Woods
Lot 10, Concession III
Anglican Cemetery
Oxley Intalian Park’
(campground)
Palen Road Woodlot
St Marks Cemetery
Rodney
Y
Soil classification
Loam
Local Landscape
forest
forest
Land class
0
Vegetated
0.02
0.24
380508
4658341 Parkhill Loam Red
Sand—Spot Phase
4660105 Tavistock
0
Vegetated
0.22
0.15
444810
368779
367855
347456
361798
4754892
4654333
4655562
4650990
4660774
0
1
1
1
1
Built-up lawns
Built-up lawns
Vegetated
Built-up lawns
Built-up lawns
0.00
0.00
0.53
0.00
0.01
0.03
0.02
0.08
0.00
0.27
348609
4654111 Fox Sandy Loam
1
Wetlands
0.00
0.58
363920
361476
342993
341470
340006
341756
4656525
4655174
4656130
4657575
4650008
4649867
Fox Sandy Loam
Fox Sandy Loam
Harrow Loam
Harrow Loam
Harrow Sandy Loam
Harrow Sandy Loam
1
1
1
1
1
1
Built-up lawns
Built-up lawns
Wetlands
Wetlands
Built-up lawns
Built-up lawns
0.00
0.00
1.00
1.00
0.00
0.47
0.17
0.13
0.31
0.17
0.00
0.10
340025
339845
434327
4651272 Harrow Sandy Loam
4652124 Harrow Sandy Loam
4713456 Wattford
1
1
1
Wetlands
Vegetated
Built-up lawns
1.00
0.44
0.00
0.31
0.03
0.01
Soil classification
Loam
Local Landscape
forest
forest
B) Site Name
X
Cinnamon Fern
E.S.A.
Fairview Cemetery
Bennie Woods
Klie’s Sugar Bush
Sweetfern Woods
E.S.A.
White Oak Woods
E.S.A.
Kopegaron Woods
C.A.
Kingsville Golf and
Curling Club
Arner Point
Conservation
Area
Evergreen Memorial
Cemetery
Holy Family Family
Retreat House
Seacliff Park
Union Ravine
Mill Creek Ravine
372700
4656500 Plainfield Sand
0
Wetlands
0.80
0.32
378956
369861
346250
372429
4660328
4654132
4653669
4662927
Plainfield Sand
Berrien Sandy Loam
Berrien Sandy Loam
Berrien Sandy Loam
0
1
1
1
Built-up lawns
Vegetated
Vegetated
Vegetated
0.00
0.60
1.00
0.31
0.09
0.17
0.33
0.17
373156
4660598 Berrien Sandy Loam
1
Vegetated
0.34
0.44
376612
1
Wetlands
1.00
0.37
1
Built-up lawns
0.36
0.35
349463
4659463 Brookston Clay
Sand—Spot Phase
4655500 Caistor Sand—Spot
Phase
4654448 Fox Sandy Loam
1
Vegetated
0.81
0.16
364903
4656206 Fox Sandy Loam
1
Built-up lawns
0.00
0.02
343546
4650408 Fox Sandy Loam
1
Built-up lawns
0.53
0.26
367148
361380
355354
4654584 Fox Sandy Loam
4655210 Fox Sandy Loam
4654801 Harrow Sandy Loam
1
1
1
Vegetated
Built-up lawns
Built-up lawns
0.00
0.66
0.21
0.00
0.13
0.30
353500
Y
Walsingham
Berrien Sandy Loam
Berrien Sandy Loam
Berrien Sandy Loam
Burford Loam
Land class
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RITCHIE & NOCERA: EASTERN MOLE DISTRIBUTION
2010
73
TABLE S1.—Continued
B) Site Name
X
Harrow Park
341301
Harrowood
Retirement
Community
New Settlement
Woods E.S.A.
340900
341346
Y
Soil classification
4654852 Tuscola Fine Sandy
Loam
4654800 Tuscola Fine Sandy
Loam
4652523 Tuscola Fine Sandy
Loam
Loam
Land class
Local Landscape
forest
forest
1
Built-up lawns
0.06
0.20
1
Built-up lawns
0.00
0.04
1
Vegetated
0.31
0.40
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