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2007 SOUTHEASTERN NATURALIST 6(2):271–282
Castor canadensis (Beaver) Impoundment Associated with
Geomorphology of Southeastern Streams
Andrew F. Jakes1,2,3, Joel W. Snodgrass1,2,*, and Joanna Burger2
Abstract - We used a geographic information system (GIS) and logistic regression to
investigate relationships between geomorphology and Castor canadensis (North
American beaver) impoundment of lower-order, blackwater streams of a southeastern
landscape. Using GIS, we divided streams into 632 500-m reaches and measured
a set of geomorphic variables for each reach. Beavers were most likely to impound
stream reaches crossed by roads with a gradient of 0.6 to 1.2% and watershed sizes
of 2500 ha; reaches with watershed sizes < 500 ha or > 5000 ha were almost
completely avoided. Gradient and road crossings contributed little to discrimination
among impounded and unimpounded reaches, suggesting these variables had relatively
small influences on beaver impoundment when compared to stream size. Our
results indicate that GIS and geomorphic variables can be used to model the
impoundment of streams over larger areas (e.g., the proportion of third-order watersheds
impounded), but are less accurate at predicting the impoundment of individual
reaches. However, the temporal dynamics of impoundment creation and abandonment
will need to be incorporated into region-specific models before they can be
used in ecosystem integrity assessment.
Before European colonization, the Castor canadensis Kuhl (North
American beaver) population was estimated at between 60-400 million
(Naiman et al. 1986, 1988), but beavers were extirpated in many areas of
North America during the late nineteenth and early twentieth centuries
(Jenkins and Busher 1979). Today, with trapping regulations, a relative
absence of natural predators, and assistance from reintroduction programs,
beavers are once again occupying many streams and lakes in North America
and are of management concern (Larson and Gunson 1983). Beaver activities,
such as foraging and dam building, influence ecosystem structure and
function and the availability of resources in streams and adjacent terrestrial
ecosystems (Naiman et al. 1988, 1991; Smith et al. 1991), thereby defining
beavers as ecosystem engineers within lotic systems (Jones et al. 1994).
These changes lead to increased biological diversity among fishes, invertebrates,
and plants in watersheds occupied by beavers (McDowell and
Naiman 1986, Snodgrass and Meffe 1998, Wright et al. 2003). On the other
hand, beavers may damage naturally aesthetic and economically important
1Department of Biological Sciences, 8000 York Road, Towson University, Towson,
MD 21252. 2Division of Life Sciences, and Consortium for Risk Evaluation with
Stakeholder Participation, Environmental and Occupational Health Sciences Institute,
Rutgers University, Piscataway, NJ 08854. 3Current address - Montana Fish,
Wildlife, and Parks, 1420 East Sixth Avenue, Helena, MT 59620. *Corresponding
author - firstname.lastname@example.org.
272 Southeastern Naturalist Vol. 6, No. 2
sites by cutting particular species of trees (Beier and Barrett 1987), flooding
timber, and damaging human-made structures such as roads and bridges
(Arner and Dubose 1980, Bullock and Arner 1985, Hill 1982, McKinstry and
Efforts to manage beaver populations would benefit from the development
of methods and models for predicting beaver impoundment of streams
over larger spatial scales. Previous studies of habitat factors affecting beaver
impoundment of streams compared field observations and manual map measurements
among impounded and free-flowing stream reaches (Allen 1983,
Barnes and Mallik 1997, Beier and Barrett 1987, Curtis and Jensen 2004,
Howard and Larson 1985, McComb et al. 1990, Slough and Sadleir 1977,
Suzuki and McComb 1998). Additionally, some authors have suggested that
roads affect the distribution of beavers (McComb et al. 1990, Slough and
Sadleir 1977), and models have been developed to predict the occurrence of
beavers at roads based on habitat conditions at stream-road intersections and
culvert characteristics (Curtis and Jensen 2004, Jensen et al. 2001).
In general, these models are of use when assessing the habitat quality of a
given reach; however, because these models rely on field and manual map
measures that are labor-intensive to gather, it remains difficult to apply them
to larger areas (such as an entire third-order watershed, but see Slough and
In this paper, we present an initial attempt to quantify and model relationships
between beaver impoundment of streams and geomorphic conditions
using a geographic information system (GIS), aerial photograph interpretation,
and logistic regression. Our goals were: 1) to determine if GIS and
measures of stream geomorphology could be used to model beaver impoundment
of streams over third-order watersheds, and 2) investigate association of
roads with beaver impoundment. We concentrate on geomorphic variables as
determinants of the distribution of beaver impoundments along streams because:
1) they can be obtained from existing data or by remote sensing over
large spatial scales, 2) they are not likely to be influenced by beaver impoundments
(at least at the spatial scale we measured them), and 3) studies of
beaver-created patch dynamics using GIS suggest watersheds have a limited
amount of stream suitable for impoundment that is largely determined by
geomorphology (Johnston and Naiman 1987, 1990a, 1990b; Remillard et al.
1987; Snodgrass 1997). Because the construction of roads often results in
floodplain and stream channel constrictions, which might facilitate dam
construction (Novak 1987), we included roads in our analysis to assess their
relationship with dam-building activity.
We investigated relationships between stream geomorphology and beaver
impoundment at the Savannah River Site on the Upper Coastal Plain of
South Carolina (hereafter referred to as “the site”). The site is an 80,000-ha
Department of Energy nuclear production facility established in the early
1950s. When the site was established, a large protected area was created
2007 A.F. Jakes, J.W. Snodgrass, and J. Burger 273
to serve as a security buffer zone in which natural systems were allowed to
recover. Human-made structures on the site make up < 10% of the total area,
consisting of a few areas of concentrated production facilities, roads connecting
these areas, and roads constructed for timber harvest.
The blackwater streams of the site are low-gradient (< 3%), sand-bottom
streams that drain primarily from the northeast portion of the site southwest
to the Savannah River. Approximately 34 km of the 325 km of stream on the
site have received thermal pollution from nuclear reactors at some time in
the last 50 years, which has altered riparian vegetation along these reaches.
These impacts are primarily confined to higher-ordered streams in the
Fourmile Branch, Pen Branch, and Steel Creek watersheds. We restricted
our analyses to streams that have not received thermal effluents, including
Upper Three Runs, Lower Three Runs, Meyers Branch, and downstream
sections of Fourmile Branch, Pen Branch, and Steel Creek.
While no estimates of beaver population size exist for the site, studies of
pond creation by beavers suggest a recovery from a few colonies in the early
1950s (when the site was established) to at least 37 colonies by 1992
(Snodgrass 1997). Management of the beaver population at the site began in
1983 and focused primarily on fatal trapping of beavers from colonies at
road and railroad structures. Although these efforts appear to alter succession
of vegetation following impoundment, they do not appear to affect the
growth rate or size of ponds associated with trapped colonies (Snodgrass
1997). Therefore, because we focus here on the probability of a reach being
impounded based on its geomorphology (not on succession of pond vegetation),
management activities probably had little effect on our results.
Development of GIS coverages
Our general approach to addressing habitat relationships of beaver disturbance
involved treating streams as one-dimensional landscape structures
(rather than two-dimensional areas) and relating the presence or absence of
beaver impoundments along individual stream reaches to geomorphic conditions.
To provide a base coverage, we extracted a line coverage of streams
for the site from 1:24,000 scale digital line graph (DLG) hydrography data
(National Cartographic Information Center, US Geological Survey 1987),
and divided streams into 500-m reaches using the ArcHatch Extension of
ArcView (Environmental Systems Research Institute, Inc., Redland, CA). In
some instances, beaver ponds were located above the terminus of headwater
streams or on terminal reaches < 500 m in length. In these cases, we
extended terminal streams, based on 3-m topographic contours (1:24,000
scale DLG; National Cartographic Information Center, US Geological Survey
1987), so that all ponds were included in a complete 500-m reach.
Additionally, breaks in streams between their upstream terminus and their
confluence with other streams were connected based on the same contour
coverage. This process resulted in 632 reaches with a mean length of 500 m
(SE = 0.02), excluding shorter terminal segments.
274 Southeastern Naturalist Vol. 6, No. 2
To determine presence of beaver impoundments along each 500-m reach,
we developed a GIS coverage of beaver ponds on all streams unaffected by
site operations using infrared aerial photographs (1:15,840 scale) acquired in
January 1998. Photographs were geographically referenced using previously
developed coverages of roads, railroads, and pipelines for the site and the
Image Warp Extension of ArcView (RMS error m = 3.75 m; n = 46). Potential
beaver ponds or previously impounded reaches were located on aerial photographs
and visited during the summer of 2000 to verify beaver activity. The
presence of dams, lodges, scent mounds, and downed or standing dead trees
were considered indicators of past or present beaver activity. We considered
reaches occupied if all or a portion of the reach had been impounded during or
before 1998, with the exception of reaches at the confluence of smaller
tributaries with larger main channels. Smaller tributary reaches that had only
their downstream areas flooded as a result of impoundment on the main
channel were classified as unoccupied. Because of the recent recovery of the
beaver population at the site, it is unlikely we misclassified reaches as
unimpounded because of forest recovery following impoundment.
We measured four geomorphic variables to assess local habitat characteristics
within each 500-m reach: watershed size above each reach (i.e., stream
size), stream gradient, floodplain width, and the presence of roads. We
delineated watershed boundary above the downstream end of each 500-m
reach based on 3-m contours. We used the number of contour lines intersected
by each 500-m reach as an index of stream gradient. We recognized four
ordinal categories of stream gradient: 0 to 1 intersections (< 0.6 %);
2 intersections (> 0.6 to 1.2%); 3 intersections (> 1.2 to 1.8%); and > 3
intersections (> 1.8 %). Floodplain widths were measured at the downstream
end of each 500-m reach. A coverage of soil types for the site, sorted by
hydrologic class, was utilized to decipher floodplains adjacent to streams. For
reaches that had well defined floodplains along only a portion of their length
(i.e., flowed from upland areas on to the floodplains of higher-order streams),
floodplain width was measured at the downstream end of the upland area.
Reaches located entirely within the floodplains of higher-ordered streams
(< 1% of the reaches) were assigned an extreme value of 9999 m. The presence
or absence of road crossings was noted for each reach and coded as a dummy
variable (0 for absence and 1 for presence).
We used logistic regression following the methods outlined by Manly et al.
(1993) and Boyce and McDonald (1999) to evaluate relationships between the
probability of impoundment and geomorphic characteristics of each 500-m
reach. We used the stepwise logistic regression procedure of SAS (SAS
Institute 1989) and maximum-likelihood methods for estimating model
parameters. Independent variables considered as potential predictors of the
probability of impoundment included watershed size, floodplain width, gradient
index, and presence/absence of road crossings. Gradient index and
presence/absence of road crossing were coded as dummy variables because of
2007 A.F. Jakes, J.W. Snodgrass, and J. Burger 275
their discrete nature. We also included second-order polynomial terms for
watershed size and floodplain width in the set of potential independent variables
because we anticipated possible unimodal responses of beavers to these
habitat characteristics. For example, beavers are not likely to impound streams
with large or small watersheds because of intermittent surface water conditions
and physical constraints on the amount of discharge that can be impounded,
respectively. We set the level for entry or retention in the model at P 0.05.
Wald-tests were used to test the significance of individual variables. Because
our data represent a census (rather than a sample) of all stream reaches
unaffected by site operations, there was no need to correct the intercept term in
the final relationship for disproportional sampling efforts (Manly et al. 1993).
To investigate overall fit of the final model, fit in relation to individual
observations, and the influence of individual observations on parameter
estimates, we followed methods presented by Hosmer and Lemeshow
(1989). The overall significance of the final relationship was tested using a
G-statistic (Sokal and Rohlf 1995). We investigated deviation of individual
observations from predicted responses and their influence on parameter
estimates using plots of changes in deviance (D), Pearson chi-squared
statistic (2), and the standardized differences in the parameter estimates
() resulting from deleting individual observations versus predicted probability
of a reach being impounded. Large values of D and 2 indicate
poorly fit observations, and large values of indicate observations with
undue influence on parameter estimates.
We assessed model performance from two respects: 1) the ability to
predict the impoundment of individual reaches (i.e., discriminatory ability);
and 2) the ability of the model to predict the percentage of small watersheds
impounded. To assess the discriminatory ability of the model, and the
contribution of individual variables to discriminatory ability, we compared
the full model to models containing only subsets of the independent variables
included in the full model. We used a one-step approximation to
estimate sensitivity (i.e., the ability of the model to correctly predict impoundment)
and specificity (i.e., the ability of the model to correctly predict
non-impoundment) for each model. We selected the cut point for classification
to maximize sensitivity and specificity simultaneously (i.e., so they
were nearly equal). We also calculated a c-statistic for each model; c ranges
from 0.5 to 1.0, where 0.5 indicates a model with discriminatory ability no
greater than random. To validate the model and assess the ability of the
model to predict the percentage of small watersheds impounded, we withheld
100 randomly selected reaches from the model building process and
compared the predicted percentage of stream impounded to the observed
percentage for this set of reaches, where the predicted percentage of stream
impounded was calculated as the mean probability of impoundment
multiplied by 100. We assessed the contribution of individual variables to
predictive power at the watershed scale in the same way we assessed contribution
to discriminatory ability.
276 Southeastern Naturalist Vol. 6, No. 2
Of the 632 reaches assessed, 501 (79.3%) showed no signs of beaver
impoundment and were classified as unoccupied, while 131 reaches (20.7%)
showed evidence of present (81%) or past (19%) impoundment and were
classified as impounded during or before 1998. Watershed size above reaches
ranged from 15 to 51,374 ha (mean = 5056 ha; SD = 11,880). Floodplain
widths for those reaches with defined floodplains ranged from 34 to 1507 m
(mean = 209 m; SD = 230), with the majority of stream reaches having
floodplain widths < 200 m (65%). Overall, stream reaches had relatively low
gradients; 28.5%, 32.2%, 19.8%, and 19.5% of the reaches had gradients
scores of 1, 2, 3, and 4, respectively. Twenty-two percent of stream reaches
were crossed with roads. In general, there was an increase in floodplain width
and a decrease in gradient from headwater stream reaches (with small watersheds)
through downstream reaches (with larger watersheds). Stream reaches
with watershed sizes > 1000 ha were all low gradient (i.e., gradient index was
1 or 2). Streams with a gradient index of 1 had wider floodplains than streams
with higher gradients. The majority of streams with gradient indices of 3 or 4
had floodplain widths of < 600 m (Fig. 1) and were restricted to headwater
streams (i.e., had watershed sizes of 500 ha or less). Roads were evenly
distributed in regards to watershed size (no roads: mean = 4981 ha, SD =
11,603; roads: mean = 5322, SD = 12,854; t-test with correction for unequal
variance: P = 0.778), floodplain widths (no roads: mean = 1146 m, SD = 2885;
roads: mean = 970 m, SD = 2663; t-test with correction for unequal variance:
P = 0.500) and gradient (chi-squared test of no relationship between road
presence/absence and gradient index: P = 0.251).
In general, beavers were more likely to impound moderate-sized (watershed
size 1000 to 5000 ha), lower-gradient streams (gradient index of 1
or 2) that were crossed by roads (Fig. 1). Stepwise logistic regression
retained watershed size, its second-order polynomial, gradient index, and
the presence or absence of road crossings in the full model (Table 1).
Overall, the model fit the data (RL
2 = 0.73, P < 0.001; Fig. 1). Inspection of
plots of versus predicted probability of impoundment indicated no
single observation had undue weight on parameter estimates (i.e., the estimates
of parameters in the model were stable). However, plots of D and
2 versus predicted probability of impoundment indicated that the model
poorly predicted seven observations. These observations were all impoundments
on small streams with high gradients (i.e., gradient indices of
3 or 4), and we interpret them as unusual, yet biologically reasonable,
outcomes since impoundments on higher-gradient streams are likely to be
more ephemeral (J.W. Snodgrass, unpubl. data). The highest probability of
impoundment ( 0.78) occurred among streams reaches crossed by roads
with gradient indices of 2 ( 0.6 to 1.2%) and watershed sizes of 2500 ha
(Fig. 1). Although reaches with gradient indices of 2 had higher probabilities
of impoundment, they were not significantly different from reaches
with gradient indices of 1. Reaches with watershed sizes < 500 ha or >
5000 ha, or with gradient indices of 3 or 4, had low probability of being
2007 A.F. Jakes, J.W. Snodgrass, and J. Burger 277
impounded. Although the model predicted higher probabilities of impoundment
for reaches with watershed sizes of 2500 ha and gradient
indices of 3 or 4, these conditions did not occur in the study area, and most
reaches (94%) with gradient indices of 3 or 4 had watershed sizes < 500 ha
and predicted probabilities of impoundment < 0.24. The observed frequency
of impoundment among all reaches with gradient indices of 3 or 4
was 0.08. Among reaches with gradient indices of 1 or 2, the presence of
one or more road crossings increased the probability of impoundment by
10% when watershed sizes were near 2500 ha (Fig. 1).
While the full model fit the data well (i.e., predicted the percentage of
streams impounded in relationship to watershed size, gradient, and road
crossings), the discriminatory ability of the model was marginal. For the full
model c = 0.84, sensitivity was 74%, specificity was 75%, and 75% of the
reaches were correctly classified at a cut point of 0.23. Among the 100
reaches withheld from the model building process, 84% were correctly
classified with 2 impounded reaches classified as unimpounded and 12
unimpounded reaches classified as impounded. The model was better at
predicting the percentage of a watershed that would be impounded (measured
as the mean probability of impoundment for all reaches in the watershed);
of the 100 reaches withheld from the model building process 18.0%
were impounded, and the model predicted 18.7% impoundment.
Figure 1. Model predictions (lines) of impoundment of streams by beavers as a
function of watershed size above stream reaches, presence or absence of roads
crossings, and gradient for relatively low-gradient streams of South Carolina.
Streams in gradient class 1 had gradients of 0 to 0.6%, and streams in gradient class
2 had gradients of > 0.6 to 1.2%.
278 Southeastern Naturalist Vol. 6, No. 2
Examination of reduced models indicated no interaction between any of
the terms included in the full model, and watershed size was the most
important variable in discriminating among impounded and free-flowing
reaches. The reduced model containing only watershed size and its polynomial
term (Table 1) correctly predicted 76% of the reaches as to beaver
impoundment; sensitivity, specificity and c for the reduced model were 0.74,
0.76, and 0.83, respectively. Addition of other terms to the reduced model
containing only watershed size did not improve the discriminatory ability of
the model. The reduced model did predict slightly higher occurrence of
impoundment at the watershed scale (19.7%) than was actually observed
(18.0%). Addition of gradient or presence/absence of road crossing resulted
in slight improvement of model prediction to 18.7% impounded.
Relationship to other studies
In the southeastern landscape that we studied, beavers tended to impound
streams with low gradients, intermediate watershed sizes, and with roads
crossing them (as opposed to reaches without road crossings). However,
stream size (as measured by watershed size) appeared to be the most important
factor in determining impoundment probability among the geomorphic
variables we considered. In general, our results are consistent with past
studies and the view of beaver habitat preference as a tradeoff between
maximizing pond size and physical constraints of impoundment of larger
discharges (Johnston and Naiman 1990b). Watershed size, or its correlates
(stream width, average annual water flux, stream depth, and cross-sectional
area), have been reported as both positively (Beier and Barrett 1987, Howard
and Larson 1985) and negatively (Barnes and Mallik 1997, Slough and
Sadleir 1977) correlated with beaver impoundment, and Suzuki and
McComb (1998) incorporated a unimodal response of beavers to stream
width in their habitat suitability model. Therefore, although beavers do not
directly use watershed size to select locations for dam construction, for
Table 1. Results of stepwise logistic regression analysis of relationships among road crossings,
stream gradient, watershed area, and the probability of beaver impoundment within 500-m stream
reaches. The full model contains all of the independent variables and the reduced model contains
only those variables contributing substantially to the discriminatory ability of the model.
Model/Parameter DF Estimate SE 2 P
Full intercept 1 -1.91600 0.3759 25.9769 < 0.001
Gradient (2 vs. 1) 1 0.22630 0.3083 0.5386 0.463
Gradient (3 vs. 1) 1 -0.72280 0.4232 2.9173 0.088
Gradient (4 vs. 1) 1 -1.72210 0.6173 7.7839 0.005
Road crossing 1 0.71550 2.89E-01 6.1211 0.013
Watershed size (ha) 1 0.00183 0.000367 24.8371 < 0.001
Watershed size (ha2) 1 -0.0000004 8.42E-08 19.2357 < 0.001
Reduced intercept 1 -2.36810 0.2059 132.2495 < 0.001
Watershed size (ha) 1 0.00255 0.000334 58.1679 < 0.001
Watershed size (ha2) 1 -0.0000005 8.21E-08 37.7888 < 0.001
2007 A.F. Jakes, J.W. Snodgrass, and J. Burger 279
modeling purposes, watershed size may act as a surrogate for more proximate
geomorphic factors directly selected by beavers.
The relationship between stream gradient and beaver impoundment in our
study may reflect a lack of water availability in small streams rather than
avoidance of relatively high gradient streams by beavers. In landscapes with
relatively large amounts of topographic relief (i.e., some streams with gradients
> 3 %), gradient may be an important factor in beaver habitat selection
(Beier and Barrett 1987, Curtis and Jensen 2004, Howard and Larson 1985,
McComb et al. 1990, Slough and Sadleir 1977, Suzuki and McComb 1998).
However, in lower gradient streams (< 1.5% gradient) of topographically flat
terrain, stream gradients vary little and are not related to beaver impoundment
(Barnes and Mallik, 1998). In our study, streams with gradients > 1.5% (i.e.,
gradient indices of 3 or 4) were restricted to extreme headwaters and included
in our analysis because they appeared on USGS hydrography data. These
relatively high gradient streams were intermittent in most cases and may not
have been impounded for lack of water.
Like stream gradient, the presence or absence of road crossings on a
reach was significantly related to the probability of impoundment. Our
results do suggest that road crossings that partially obstruct stream flow and/
or a portion of the floodplain increase beaver habitat quality within the
smaller streams preferred by beavers at the site. When culverts associated
with roads are small and reduce channel area, resulting in slower flows
upstream of the culvert, the energy required to dam the stream may be
reduced, and beavers will locate dams at culverts (Jensen et al. 2001).
Scope and limitations
Our model predicted a maximum of 80% impoundment under optimal
geomorphic conditions, resulting in the selection of a cut point of 0.23 for
classification purposes. By selecting a cut point lower than 0.50 we essentially
emphasized misclassification of unimpounded reaches as impounded;
of the 16 reaches that were misclassified among the validation data set, only
2 were incorrectly classified as unimpounded. The lack of impoundments on
reaches that were apparently suitable may have resulted from failure to
consider vegetative characteristics that may influence beaver impoundment
in our study area. Although authors have often reported geomorphic characteristics
as being most important in determining beaver dam location
(Howard and Larson 1985, McComb et al. 1990), others have found the
availability of forage and preferred dam building material to be important
factors in determining dam location (Barnes and Mallik 1997, Curtis and
Jensen 2004, Slough and Sadleir 1977). Because our study area did not
include land-use practices that resulted in complete forest clearing along
streams, a lack of woody vegetations along streams probably did not limit
beaver impoundment. However, more subtle differences in forest characteristics
such as stem size and forest composition may have influenced
impoundment probabilities in our area. These characteristics will be difficult
to incorporate into models designed to predict impoundment over larger
scales, and may limit the application of our approach.
280 Southeastern Naturalist Vol. 6, No. 2
It is possible that beaver populations in our study area are not at carrying
capacity. If the population is still expanding and dispersal is limited
(i.e., all reaches are not readily accessable from existing colonies), some
reaches may not have been impounded because of isolation from points of
colonization (Bergerud and Miller 1977). Furthermore, access to some
reaches may be limited due to the territorial behavior of beavers. Beaver
colonies consisting of an adult male, an adult female, and several offspring
maintain one to several dams and aggressively defend reaches of streams
against dispersers (Hill 1982, Nolet and Rosell 1994). This territorial
behavior often results in separation of territories by 100 m or more of
unoccupied stream (Bergerud and Miller 1977). Johnston and Naiman
(1990a) documented an asymptote of pond area over a 46-year period in a
northern Minnesota landscape. While beaver impoundment of streams was
evident in 1978 at our study site (Snodgrass 1997), sufficient data to assess
equilibrium of beaver patch dynamics is lacking. Therefore, further model
development will require assessment of population and impoundment dynamics
over longer periods to assess the equilibrium assumptions of our
modeling approach (Manly et al. 1993).
The accuracy of the model depended on the scale of the prediction being
made; at the individual-reach scale, accuracy was relatively low (86% correctly
classified in the validation data set), but was higher at the watershed
scale (18.0% predicted and 18.7% observed in the training data set). Therefore,
use of GIS-based geomorphology models of beaver impoundment may
be most appropriate at the watershed scale. For example, models could be
used to assess the degree of ecological integrity exhibited by a watershed; if
percent impoundment of streams is similar to that predicted by models, a
watershed might be considered to have high ecological integrity from the
standpoint of beaver disturbance. However, because positive influences of
beaver impoundment on biological diversity are dependent on the temporal
dynamics of pond creation and abandonment (Snodgrass and Meffe 1998),
development of models that incorporate these dynamics will be required for
the complete incorporation of beaver disturbance into ecological assessments.
Finally, while our general approach to developing models of beaver
disturbance of streams may be exportable to other areas, the specific relationships
and parameter estimates are likely to vary greatly among regions
with different geomorphology. For example, beavers in streams of the
Coastal Range of Oregon preferred streams with gradients of 1 to 3%
(Suzuki and McComb 1998). In contrast, beavers at our study site on the
upper coastal plain of South Carolina preferred streams with gradients of
< 0.6%. Therefore, models will need to be developed individually for regions
differing in geomorphology (Barnes and Mallik 1997).
This project was funded by the Consortium for Risk Evaluation with Stakeholder
Participation (CRESP; through the Department of Energy Cooperative
Agreement, AIDE-FC01-95EW55084, DE-FG-26-00NT 40938), NIEHS Grant
2007 A.F. Jakes, J.W. Snodgrass, and J. Burger 281
ESO 5022, the Environmental and Occupational Health Sciences Institute; Financial
Assistance Award No. DE-FC09-96SR18546 from the US Department of
Energy to the University of Georgia Research Foundation; and a grant from the
Towson University Graduate Student Association. We thank Deno Karapatakis and
Helen Wiggins-Brown for assisting with GIS coverage development. Logistic support
at the Savannah River Site was provided by Larry Bryan, William Hopkins,
John Roe, and Gary Wein. We thank Don Forester, Karen Gaines, Scott Johnson,
Brenda McComb, Marty Roberge, and two anonymous reviewers for providing
helpful insights on earlier versions of the manuscript.
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