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RESEARCH ARTICLE
Landscape context and the biophysical
response of rivers to dam removal in the
United States
Melissa M. Foley
1¤
*, Francis J. Magilligan
2
, Christian E. Torgersen
3
, Jon J. Major
4
,
Chauncey W. Anderson
5
, Patrick J. Connolly
6
, Daniel Wieferich
7
, Patrick B. Shafroth
8
,
James E. Evans
9
, Dana Infante
10
, Laura S. Craig
11
1Pacific Coastal and Marine Science Center, United States Geological Survey, Santa Cruz, California,
United States of America, 2Department of Geography, Dartmouth College, Hanover, New Hampshire,
United States of America, 3Forest and Rangeland Ecosystem Science Center, United States Geological
Survey, Seattle, Washington, United States of America, 4Cascades Volcano Observatory, Volcano Science
Center, United States Geological Survey, Vancouver, Washington, United States of America, 5Oregon
Water Science Center, United States Geological Survey Portland, Oregon, United States of America,
6Columbia River Research Laboratory, Western Fisheries Research Center, United States Geological
Survey, Cook, Washington, United States of America, 7Denver Federal Center, United States Geological
Survey, Lakewood, Colorado United States of America, 8Fort Collins Science Center, United States
Geological Survey, Fort Collins, Colorado, United States of America, 9Department of Geology, Bowling
Green State University, Bowling Green, Ohio, United States of America, 10 Department of Fisheries and
Wildlife, Michigan State University, East Lansing, Michigan, United States of America, 11 American Rivers,
Washington, D.C., United States of America
¤Current address: Institute of Marine Sciences, University of California Santa Cruz, Santa Cruz, California,
United States of America
*mfoley@ucsc.edu
Abstract
Dams have been a fundamental part of the U.S. national agenda over the past two hundred
years. Recently, however, dam removal has emerged as a strategy for addressing aging,
obsolete infrastructure and more than 1,100 dams have been removed since the 1970s.
However, only 130 of these removals had any ecological or geomorphic assessments, and
fewer than half of those included before- and after-removal (BAR) studies. In addition, this
growing, but limited collection of dam-removal studies is limited to distinct landscape set-
tings. We conducted a meta-analysis to compare the landscape context of existing and
removed dams and assessed the biophysical responses to dam removal for 63 BAR stud-
ies. The highest concentration of removed dams was in the Northeast and Upper Midwest,
and most have been removed from 3
rd
and 4
th
order streams, in low-elevation (<500 m) and
low-slope (<5%) watersheds that have small to moderate upstream watershed areas (10–
1000 km
2
) with a low risk of habitat degradation. Many of the BAR-studied removals also
have these characteristics, suggesting that our understanding of responses to dam remov-
als is based on a limited range of landscape settings, which limits predictive capacity in
other environmental settings. Biophysical responses to dam removal varied by landscape
cluster, indicating that landscape features are likely to affect biophysical responses to dam
removal. However, biophysical data were not equally distributed across variables or clus-
ters, making it difficult to determine which landscape features have the strongest effect on
dam-removal response. To address the inconsistencies across dam-removal studies, we
PLOS ONE | https://doi.org/10.1371/journal.pone.0180107 July 10, 2017 1 / 24
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OPEN ACCESS
Citation: Foley MM, Magilligan FJ, Torgersen CE,
Major JJ, Anderson CW, Connolly PJ, et al. (2017)
Landscape context and the biophysical response of
rivers to dam removal in the United States. PLoS
ONE 12(7): e0180107. https://doi.org/10.1371/
journal.pone.0180107
Editor: Hideyuki Doi, University of Hyogo, JAPAN
Received: February 6, 2017
Accepted: June 11, 2017
Published: July 10, 2017
Copyright: This is an open access article, free of all
copyright, and may be freely reproduced,
distributed, transmitted, modified, built upon, or
otherwise used by anyone for any lawful purpose.
The work is made available under the Creative
Commons CC0 public domain dedication.
Data Availability Statement: Data are available
from: The USGS Dam Removal Information Portal
(DRIP – https://www.sciencebase.gov/drip/); The
National Assessment of Fish Habitat Condition
Database (https://www.sciencebase.gov/catalog/
item/4f4e4773e4b07f02db47e241); The National
Anthropogenic Barrier Dataset (https://www.
sciencebase.gov/catalog/item/
56a7f9dce4b0b28f1184dabd); The National Land
Cover Database (http://www.mrlc.gov/).
Funding: This work was supported by the US
Geological Survey John Wesley Powell Center for
provide suggestions for prioritizing and standardizing data collection associated with dam
removal activities.
Introduction
Dams have been a fundamental part of the U.S. national agenda and economic-development
ideology over the past two hundred years because of their essential role in flood control,
municipal water supply, power generation, and irrigation. In the past several decades, how-
ever, there has been a paradigm shift in dam and watershed management—driven by environ-
mental, economic, and engineering concerns—leading to the removal of obsolete, unsafe, and
economically non-viable dams emerging as a significant management and restoration strategy.
This new agenda has led to the removal of >1,000 dams in the past few decades [1,2], yet sci-
entific assessment of the effects of dam removal lags the rate of removal [2], a theme typical of
other river restoration efforts nationally [3–5]. Though the scientific community has been
studying various aspects of dam removal in limited capacity for the last few decades, there is
still a need to provide resource managers with basic information about the likely effects of dam
removal that could affect the cost, planning process, permit requirements, and monitoring
components of dam removal projects. Moreover, dam removal studies have not been con-
ducted across a broad enough range of landscapes to establish a predictive framework linking
the context of the dam location to anticipated outcomes affecting river hydrology, channel
morphology, sediment budgets, water quality, and ecological trajectories.
General lessons regarding river response to dam removal, however, are slowly emerging.
These lessons can help identify fundamental operative processes and biophysical responses to
dam removal and further enlighten management decisions [6–8]. Multiple factors drive the
variability in geomorphic responses to dam removal, including dam size; removal method; res-
ervoir size and shape; sediment volume, cohesiveness, and grain size; and released sediment
volume relative to background sediment flux [1,6,9,10]. Contrary to some perceptions,
Major et al. [11] and East et al. [12] found that river channels can stabilize relatively quickly
after dam removal—within months or years, not decades—approaching pre-dam emplace-
ment morphology.
Ecological response trajectories after dam removal are difficult to generalize because
response rates can be highly variable across taxa [13] and can be affected by past and current
conditions [14–16]. In addition, most dam removal studies are short in duration and focus on
a single response metric [2]. Despite these limitations, some patterns have emerged from the
literature: there may be a lag between geomorphic and ecological responses [17, but see 18];
aquatic species typical of flowing rivers (lotic habitats) tend to replace stillwater (lentic) com-
munities in the reservoir after dam removal [15]; and upstream fish migration that was for-
merly impeded by the dam may occur swiftly after dam removal in some cases [19–22].
Biophysical river responses to dam removal are affected by the surrounding landscape, but
these effects are poorly understood [15,23] because the literature consists mainly of specific
case studies focused on short-term responses with limited comparison across regions. Without
understanding a site’s landscape context (i.e., location within a watershed or regional and local
patterns of climate, geology, and vegetation), it is difficult to interpret the broad applicability
or local limitations of the biophysical responses to dam removal [24]. As a result, our funda-
mental understanding of long-term trajectories and broad-scale patterns of ecological, geo-
morphic, and hydrologic responses to dam removal is lacking. Furthermore, the breadth (or
lack thereof) of published studies is directly tied to the expertise of researchers in each case
Landscape context of dam removal and river response
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Analysis and Synthesis (https://powellcenter.usgs.
gov/). The funders had no role in study design,
data collection and anlysis, decision to publish, or
preparation of the manuscript.
Competing interests: The authors have declared
that no competing interests exist.
study; truly interdisciplinary studies are rarely conducted for the same dam removal [2], and
studies that integrate the trajectories of physical and biological responses are even more rare
[25, but see 26].
To assess the state of science for understanding outcomes to dam removal and to determine
the representativeness of dam removal case studies compared to the national dam population,
we conducted a meta-analysis examining the landscape context—including natural and
anthropogenic factors—of more than 50,000 existing dams and nearly 900 removed dams in
the conterminous U.S. We also reviewed 104 published studies [27] with before- and after-
removal (BAR) data from 63 dam removals to analyze the influence of landscape context in
driving the biophysical response to dam removal. Because removals have occurred in settings
where the human footprint may influence the response trajectory, we characterized landscape
context as a combination of natural (e.g., ecoregion, watershed size) and anthropogenic (e.g.,
population density, transportation infrastructure) attributes. We used this approach to assess
the landscape context of dams and removed dams; examine the biophysical response of river
systems in different landscape settings; and highlight landscape contexts where additional
research is needed. In doing so, we attempt to unpack “environmental context” into more spe-
cifically defined statistical associations but with the full knowledge that we are working with
limited and geographically biased data. Finally, propose approaches for standardizing elements
of dam-removal research that could increase our understanding of biophysical responses and
help guide watershed management and restoration efforts. This type of comprehensive review
has not been reported and our study is the first to formally examine the landscape context of
dam removals with linked geospatial data at a national scale in the U.S. We also had access to a
unique dam removal database compiled by American Rivers that allowed us to examine the
geographic context for a larger population of dam removals than has been previously publicly
available.
Methods
We compiled geographic information for 50,772 existing dams listed in the National Anthro-
pogenic Barrier Dataset (NABD) [28], a subset of dams from the 2009 National Inventory of
Dams (U.S. Army Corps of Engineers– http://nid.usace.army.mil/cm_apex/f?p=838:12,
accessed July 2010). We gathered the same information for the 874 removed dams included in
the USGS Dam Removal Information Portal (DRIP– https://www.sciencebase.gov/drip/;
accessed 1 July 2016). All existing and removed dams were linked to the National Hydrogra-
phy Dataset Plus Version 1 (NHDPlusV1), allowing us to gather additional information from
the National Fish Habitat Partnership’s (NFHP) 2015 National Assessment of Fish Habitat
Condition Database [29,30] and Anthropogenic Disturbance Database [31], as well as land-
cover data summaries from the National Land Cover Database (NLCD– http://www.mrlc.gov/).
From these sources, we identified natural and anthropogenic landscape-context factors in the
river segment for each existing and removed dam (Table 1). We also examined the distribution
of dams and dam removals in relation to Environmental Protection Agency (EPA) Level III
Ecoregions, which characterize nation-wide landscape characteristics based on geology, land-
forms, soils, vegetation, climate, land use, wildlife, and hydrology [32] (https://www.epa.gov/
eco-research/ecoregions; accessed 30 January 2017).
We generated summary statistics using these landscape characteristics for existing and
removed dams to determine how representative removals have been of the overall dam popu-
lation. We reduced the number of individual landscape factors used in our analyses because
some of the variables were used to derive a habitat condition index (HCI) [29,30], an index
based on regionally specific responses of stream fishes to anthropogenic landscape factors. We
Landscape context of dam removal and river response
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Table 1. Landscape variables.
Data obtained from the National Fish Habitat Partnership (version 2015)
Data Type Data description
*Catchment slope Mean catchment slope (degrees)
*Catchment elevation Mean catchment elevation (m)
*Groundwater index Percent groundwater contribution to stream baseflow
*Precipitation Mean annual precipitation (mm)
*Air temperature Mean annual air temperature (C
o
)
*Habitat Condition Index Index scoring the risk of habitat degradation for fish (scored as 0–5, with 0
representing very low risk of habitat degradation/very high fish habitat and 5
representing very high risk of habitat degradation/very poor fish habitat)
Population density Census 2000 average population per catchment density (average population
count/km
2
)
Road crossings Road crossing density in the catchment (#/km
2
)
Toxic Release sites Toxic Release Inventory (EPA) sites in the catchment (#/km
2
)
Superfund sites EPA Superfund National Priority in the catchment (#/km
2
)
NPDES sites National Pollutant Discharge Elimination System sites in the catchment
(#/km
2
)
Water withdrawal Total annual water withdrawal (million gallons per year–MGY)
Agriculture water
withdrawal
Annual agriculture water withdrawal (MGY)
Domestic water withdrawal Annual domestic water withdrawal (MGY)
Industrial water withdrawal Annual industrial water withdrawal (MGY)
Thermoelectric water
withdrawal
Annual thermoelectric water withdrawal (MGY)
Elevation at dam location Elevation above sea level at the base of the dam location (m)
Data obtained from the National Land Cover Database (version 2006)
Data Type Data description
Open water Percent of catchment
Perennial snow/ice Percent of catchment
Developed open space Percent of catchment
Developed low intensity Percent of catchment
Developed medium
intensity
Percent of catchment
Developed high intensity Percent of catchment
Barren land Percent of catchment
Deciduous forest Percent of catchment
Evergreen forest Percent of catchment
Mixed forest Percent of catchment
Shrub/Scrub Percent of catchment
Grassland/Herbaceous
plants
Percent of catchment
Pasture/Hay Percent of catchment
Cultivated crops Percent of catchment
Woody wetlands Percent of catchment
Emergent herbaceous
wetlands
Percent of catchment
Landscape data obtained for existing and removed dams from the National Fish Habitat Partnership (NFHP)
and the National Land Cover Database (NLCD). Landscape data were summarized within network
catchments for the stream reaches immediately above the dams.
*indicates variables that were used in our analyses.
https://doi.org/10.1371/journal.pone.0180107.t001
Landscape context of dam removal and river response
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excluded the variables used to create that index—including land cover, population density,
road density, and the number of dams, mines, and point-source pollution sites—from subse-
quent analyses to avoid overrepresentation. The HCI uses a ranking of 1 through 5, with low
scores corresponding to low risk of fish-habitat degradation and high scores to high risk of
fish-habitat degradation.
We used seven variables—mean watershed slope, elevation, and area; precipitation; air tem-
perature; ground water input; and HCI—in a Principal Components Analysis (PCA) to deter-
mine which landscape variables best explained the variability in landscape context among dam
removals. Because landscape variables were measured using a variety of units, all variables
were normalized prior to analysis (for each variable, the variable mean was subtracted from
the value and then divided by the standard deviation). We also conducted a cluster analysis
(using a resemblance matrix based on Euclidean distance) to determine whether dam removals
formed significantly distinct clusters based on landscape context. We used similarity profile
analysis (SIMPROF) to assign groupings for all dam removals and a subset of dam removals
with BAR studies that had statistically different (p0.01) landscape characteristics [33].
To determine if biophysical response to dam removal varied with landscape context, we
selected a subset of dam removals from the DRIP database that had BAR data upstream of the
reservoir, within the reservoir, and/or downstream of the dam site. When we accessed the
database (November 2016), it contained information from 104 BAR studies from 63 dam
removals (S1 Table). For each study, we classified the response to dam removal categorically
for each biophysical variable as “increased,” “no change,” or “decreased.” We did not control
for time frame of response (e.g., weeks to years after dam removal) following dam removal
because the duration of studies was highly variable. For each variable (e.g., turbidity), we tallied
the number of each response type, irrespective of methodological differences. We recognize
that this way of analyzing the data resulted in a loss of resolution and somewhat limits our abil-
ity to compare across dam removals, but vagaries among studies required a level of generaliza-
tion to assemble data coherently.
Based on the clusters determined in our SIMPROF analysis, we examined biophysical
responses to dam removal within each geographic cluster having more than three dams and
qualitatively compared the responses across geographic clusters. We could not conduct robust
quantitative analyses on landscape context and biophysical responses because we were limited
by the number of removals within each cluster, as well as by the overlap of data types among
studies (S1 Table). We used PRIMER (v. 7, Primer Ltd.) and QGIS (v. 2.8.1) for all our analyses
[34,35].
Results
The densities of existing and removed dams, and studied dam removals varied greatly across
the U.S. (Fig 1) [2]. The highest concentrations of existing dams were in the Southeastern
Plains, Central Great Plains, Piedmont, and Northwestern Great Plains EPA Level III Ecore-
gions (Fig 2,S2 Table), predominantly on headwater streams (stream order = 1) that had small
upstream watershed areas (<10 km
2
) and low mean catchment slope (<5 degrees) (Fig 3A–
3C). Many were also located in areas where the HCI of the upstream catchment was very high,
indicating an anthropogenic stressor(s) causes significant fish habitat degradation in those
areas (Fig 3D). In contrast, the highest concentrations of dam removals have occurred in the
Ridge and Valley, Northern Piedmont, Northeastern Highlands, and Northeastern Coastal
Zone Ecoregions (Fig 2,S2 Table). Unlike existing dams, dam removals have occurred in a
range of stream sizes, with a nearly equal number coming out of stream orders 1–4; and in
river systems where the upstream catchment area is large, up to two orders of magnitude
Landscape context of dam removal and river response
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a.
b.
c.
Fig 1. Geography of dams. U.S. distribution of (a) existing dams listed in the National Anthropogenic Barrier
Dataset (n= 50,772); (b) removed dams from the Dam Removal Inventory Project (n= 874); (c) removed
dams with before-after studies (n = 63).
https://doi.org/10.1371/journal.pone.0180107.g001
Landscape context of dam removal and river response
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greater than that of existing dams (Fig 3B). Similar to existing dams, removed dams were
located in watersheds with a low mean catchment slope (Fig 3C). Nearly 40% of removed
dams were in watersheds with a low or very low risk of upstream habitat degradation (i.e., very
low or low HCI score), and just over 30% of existing dams that were located in areas with a
very high risk of habitat degradation (Fig 3D).
The landscape context of dam removals with BAR studies also differed in many respects
from that of existing or removed dams (Figs 2and 3). BAR studies were most numerous in the
Eastern Corn Belt Plains (Ohio), Driftless Area (southern Wisconsin), Cascades (western U.
S.), Southeastern Wisconsin Till Plains, and Piedmont Ecoregions (Fig 2,S2 Table). Except for
the studies from the Eastern Corn Belt Plains and Cascades Ecoregions, these studies repre-
sented fewer than 13% of the removals in those areas (S2 Table). Studied dam removals have
occurred predominantly on larger streams and in watersheds with low mean catchment slope
and moderate to low risk of habitat degradation (HCI >3) (Fig 3D).
We identified several notable spatial patterns in the landscape context of dam removals
with respect to their distribution throughout the U.S. (Fig 4). The clusters of removals in the
upper Midwest and upper New England generally occurred in large, low elevation, low slope
watersheds, many with degraded fish habitat (Fig 4A–4D). In contrast, removals in the western
U.S. were in high elevation, steep, small watersheds with predominantly moderate- to low-risk
of habitat degradation (Fig 4A–4D). We identified a dearth of dam removals in central and
south-central areas of the continental U.S., despite this area having one of the highest concen-
trations of existing dams (i.e., Central Great Plains).
For the seven variables we analyzed for all dam removals, the cluster analysis revealed 57
unique clusters of dam removals based on their landscape characteristics (Fig 5A). Although
many of these clusters were concentrated in specific geographic regions, some removals that
Ecoregion
% of dams
Huron/Erie Lake Plains
Klamath Mountains
Coast Range
Columbia Plateau
N Rockies
Willamette Valley
AZ/NM Mountains
E Cascades Slopes & Foothills
Wasatch & Uinta Mountains
C Corn Belt Plains
SE WI Till Plains
N Central Appalachians
CA Foothills & Coastal
Cascades
C Appalachians
Middle Rockies
Acadian Hills & Plains
Atlantic Coastal Pine Barrens
Driftless Area
Erie Drift Plains
S MI/N IN Drift Plains
AK Valley
S TX Plains
E Corn Belt Plains
N Piedmont
N Central Hardwood Forests
Blue Ridge
TX Blackland Prairies
Int Plateau
High Plains
W Allegheny Plateau
S Tablelands
S Rockies
Ozark Highlands
MS Valley Loess Plains
N Lakes & Forests
S Central Plains
Flint Hills
Int River Valleys & Hills
Ridge & Valley
NW Glaciated Plains
Cross Timbers
NE Highlands
NE Coastal Zone
C Irregular Plains
W Corn Belt Plains
NW Great Plains
Piedmont
C Great Plains
SE Plains
0
15
5
10
Existing dams
Removed dams
Studied dam removals
Fig 2. Ecoregions. EPA Level III Ecoregions for existing and removed dams in the U.S., and before-after-removal studies.
https://doi.org/10.1371/journal.pone.0180107.g002
Landscape context of dam removal and river response
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had similar landscape characteristics were widely distributed across the U.S. (Fig 6A). The
PCA suggested the main factors differentiating the dam removal clusters were watershed eleva-
tion, groundwater input, and air temperature on principal component axis 1 (PC1); watershed
area, watershed slope, and precipitation on PC2; and groundwater input, watershed elevation,
and watershed slope on PC3 (Table 2); these three PCA axes explained 66% of the variation in
landscape characteristics. Studied dam removals were represented in 36 of the 57 geographic
clusters (Fig 5B); and BAR studies were conducted in 32 of the 57 geographic clusters (Fig 5C).
Although over half of the geographic clusters had at least one BAR study, clusters in the lower
right quadrant of the PCA axes had the greatest number of studies, representing large, low-
176
5
432
Stream order
% of dams
Existing dams
Removed dams
Studied dam removals
70
60
50
40
30
20
10
0
% of dams
60
50
40
30
20
10
0
<1 >10000
1000-10000
1-10 100-1000
10-100
Upstream watershed area (km
2
)
a. b.
c.
70
60
50
40
30
20
10
0
80
% of dams
<5 >2520-25
5-10 15-20
10-15
Upstream slope (degrees)
d.
30
25
20
15
10
5
0
35
Very low Unknown
Very high
Low High
Moderate
Habitat Condition Index
Fig 3. Landscape context. Comparison of (a) stream order; (b) watershed area (km
2
); (c) watershed slope (degrees); and (d) habitat condition index (risk
of degradation) for existing (n= 50,772) and removed dams (n= 874), and dam removals with before- and after-removal studies (n= 63).
https://doi.org/10.1371/journal.pone.0180107.g003
Landscape context of dam removal and river response
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elevation, and low-slope watersheds. Few BAR studies were conducted in small, high-eleva-
tion, high-slope watersheds (Fig 5C).
We conducted a separate cluster analysis based only on the landscape variables for BAR
studies. This reduced analysis revealed eight significantly distinct clusters of removals, some
b.
0-10 10-100 100-1000 1000-10000 >10000
0
100
200
300
# of dams
d.
0
100
200
300
Very low Low Moderate High Very high
Habitat Condition Index
# of dams
c.
0
100
200
300
400
500
0-5 5-10 10-15 15-20 20-25 >25
Upstream watershed slope (degrees)
# of dams
a.
<250 250-500 1000-1500 >1500
0
100
200
300
500-1000
Upstream watershed elevation (m) Upstream watershed area (km2)
# of dams
Fig 4. Spatial distribution of landscape characteristics. Spatial distribution of landscape characteristics for all removed dams: (a) upstream watershed
elevation (m), (b) upstream watershed area (km
2
), (c) upstream watershed slope (degrees), and (d) habitat condition index (risk of habitat degradation).
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with a wide geographic distribution (Fig 6B). Seven removals could not be categorized because
data were not available for all landscape variables (Table 3). We used these new clusters to look
at patterns of biophysical responses to dam removal.
Parameters reported most frequently across all BAR studies included sediment grain size,
water temperature, aquatic invertebrates, and fish (Table 4). However, not all of these parame-
ters were reported above the dam, within the reservoir, or downstream of the dam. For nearly
all of the biophysical parameters we characterized, measurements were most frequently
-10 -5 0 5
PC1
-5
0
5
10
PC2
Habitat condition
Area
Slope
Elevation
Groundwater
Temperature
Precipitation
a. All dam removals
c. Before- and after-removal studies
-10 -5 0 5
PC1
-5
0
5
10
PC2
Habitat condition
Area
Slope
Elevation
Groundwater
Temperature
Precipitation
-10 -5 0 5
PC1
-5
0
5
10
PC2
Habitat condition
Area
Slope
Elevation
Groundwater
Temperature
Precipitation
b. All studied dam removals
Fig 5. Principal Components Analysis results. Principal Components Analysis results for (a) all dam removals (57 clusters); (b) all studied dam removals
(36 clusters); and (c) before-after studied dam removals (32 clusters). The number of clusters in (a) was determined from a cluster analysis; clusters in (b)
and (c) show how many original clusters were represented in those subsets.
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Landscape context of dam removal and river response
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a.
b.
Upper Midwest Northeast
Fossil Creek
Appleton, Brewster, Embrey, Fifth Avenue, Main Street, Munroe Falls, North Avenue, South Batavia, St. John
Chiloquin, Mystic
Condit, Dinner Creek, Elwha, Hemlock, Marmot
Big Spring, Boulder Creek Lower & Upper, Dexter, Fort Covington, Hinkletown, LaValle, Nashville,
Oak, Rockdale, Sandstone, Shopiere, Stronach, Waterworks, Woolen Mills (WI)
Brownsville, Franklin Mills, Good Hope, Hellberg’s, Homestead, Manatawny, McCormick-Saeltzer,
Merrimack Village, Mill, Pawtuxet Falls, Pelham, Shearer, Simpkins, Woodside I & II, Woolen Mills (VA), Zemco
Edwards, Gold Ray, Milltown, Savage Rapids
Carbonton, Dead Lake, Lowell, Murphy Creek
Fig 6. Spatial distribution of landscape clusters. (a) Spatial distribution of clusters based on landscape
characteristics for all dam removals. Upper Midwest and Northeast sections magnified to show details. (b)
Spatial distribution of clusters based on landscape characteristics of before-after studied dam removals.
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reported downstream of the removed dam (Fig 7). For example, approximately half of the
BAR studies reported grain size measurements downstream of the former dam, while only
33% reported measurements within reservoir reaches and 25% in upstream reaches. Biotic var-
iables were more consistently reported for all three river reaches than physical variables. Some
variables were quantified using different metrics, particularly nutrients, aquatic invertebrates,
and fish (Table 5).
We could not formally test for differences in biophysical responses to dam removal because
variables were not consistently reported across all dam removals in the eight geographic clus-
ters (Fig 8). Water quality variables, including phosphate, nitrate, water temperature, and dis-
solved oxygen, were measured in only three of eight geographic clusters. In contrast, sediment
Table 2. Principal component loadings.
PC 1 PC 2 PC 3 PC 4 PC 5
Eigenvalue 2.12 1.50 1.01 0.87 0.69
% Variation 30.3 21.4 14.4 12.5 9.9
Variables:
Area -0.55 -0.491 0.062 -0.787 -0.351
Slope -0.339 0.473 0.461 -0.335 0.103
Elevation -0.547 0.006 0.458 0.106 0.096
Groundwater -0.436 -0.084 -0.568 -0.053 0.275
Temperature 0.493 0.280 0.218 -0.002 -0.275
Precipitation 0.146 0.579 -0.343 -0.484 0.260
Habitat condition -0.358 0.340 -0.294 0.140 -0.799
Principal component loadings for the full PCA on all removed dams.
https://doi.org/10.1371/journal.pone.0180107.t002
Table 3. Landscape clusters for before and after-removal studies.
Cluster membership Dam name and location
a (Mountain West) Chiloquin, OR; Mystic, MT
b (West) Edwards, ME; Gold Ray, OR; Milltown, MT; Savage Rapids, OR
c (Pacific Northwest) Condit, WA; Dinner Creek, OR; Elwha, WA; Hemlock, WA; Marmot,
OR
d (Arizona) Fossil Creek, AZ
e (Upper Midwest) Big Spring, WI; Boulder Creek (Lower & Upper), WI; Dexter, MI; Fort
Covington, NY; Hinkletown, PA; LaValle, WI; Nashville, MI; Oak
Street, WI; Rockdale, WI; Sandstone, MN; Shopiere, WI; Stronach,
MI; Waterworks, WI; Woolen Mills, WI
f (New England) Brownsville, OR; Franklin Mills, PA; Good Hope, PA; Hellberg’s, PA;
Manatawny Creek, PA; McCormick-Saeltzer, CA; Merrimack Village,
NH; Mill, NH; Pawtuxet Falls, RI; Shearer, OR; Simkins, MD; Sodom,
OR; Woodside (I & II), SC; Woolen Mills, VA; Zemko, CT
g (Midwest) Appleton, MN; Brewster Creek, IL; Embrey, VA; Fifth Avenue, OH;
Main Street, OH; Munroe Falls, OH; North Avenue, WI; South
Batavia, IL; St. John, OH
h (Southeast) Carbonton, NC; Dead Lake, FL; Lowell, NC; Murphy Creek, CA
No cluster assigned due to missing
landscape data
Central Avenue, OH; Homestead, NH; Off Billington Street, MA;
Pelham, MA; Quaker Neck, NC; River Street, OH; Secor, OH
Significant clusters for before- and after-removal studies. Locations are indicated with abbreviations for
states in the U.S. The cluster names in parentheses denote the region where a majority of the removals in
each cluster were located.
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Table 4. Reported biophysical metrics.
Physical Water quality Biological
Dam name and
location (US state
abbreviation)
Sediment
grain size
Turbidity Suspended-
sediment
concentration
Phosphate
concentration
Nitrate
concentration
Temperature Dissolved
oxygen
Aquatic
invertebrates
Fish
single
species
Fish
community
Appleton, MN
Big Spring, WI
Boulder Creek, WI*
Brewster, IL
Brownsville, OR
Carbonton, NC
Central Avenue, OH
Chiloquin, OR
Condit, WA
Dead Lake, FL
Dexter, MI
Dinner Creek, OR
Edwards, ME
Elwha, WA
Embrey, VA
Fifth Avenue, OH
Fort Covington, NY
Fossil Creek, AZ
Franklin Mills, PA
Gold Ray, OR
Good Hope, PA
Hellberg’s, PA
Hemlock, WA
Hinkletown, PA
Homestead, NH
LaValle, WI
Lowell, NC
Main Street, OH
Manatawny, PA
Marmot, OR
McCormick-
Saeltzer, CA
Merrimack Village,
NH
Mill, ME
Milltown, MT
Munroe Falls, OH
Murphy Creek, CA
(Continued)
Landscape context of dam removal and river response
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Table 4. (Continued)
Physical Water quality Biological
Dam name and
location (US state
abbreviation)
Sediment
grain size
Turbidity Suspended-
sediment
concentration
Phosphate
concentration
Nitrate
concentration
Temperature Dissolved
oxygen
Aquatic
invertebrates
Fish
single
species
Fish
community
Mystic, MT
Nashville, MI
North Avenue, WI
Oak, WI
Off Billington Street,
MA
Pawtuxet Falls, RI
Pelham, MA
Quaker Neck, NC
River Street, OH
Rockdale, WI
Sandstone, MN
Savage Rapids, OR
Secor, OH
Shearer, OR
Shopiere, WI
Simkins, MD
Sodom, OR
South Batavia, IL
St. John, OH
Stronach, MI
Waterworks, WI
Woodside, SC*
Woolen Mills, VA
Woolen Mills, WI
Zemko, CT
Total: 34 9 14 9 8 14 14 25 28 28
Biophysical metrics that were reported before and after dam removal; blank cell = no response reported, grey cell = response reported.
*In two instances, two dam removals were reported together in the literature–Upper and Lower Boulder Creek, WI, and Woodside I and II, SC.
https://doi.org/10.1371/journal.pone.0180107.t004
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grain size and fish species data were reported in all clusters (Fig 8). Physical responses to dam
removal tended to be more consistent across geographic clusters than either water quality or
ecological parameters. Sediment grain size tended to remain mostly unchanged in upstream
reaches, coarsened in reservoir reaches, and fined downstream after dam removal; turbidity
Grain size Turbidity Suspended
sediment
Phosphorus Nitrogen Temperature Dissolved
oxygen
Benthic
invertebrates
Fish
species
Fish
assemblage
0
5
10
15
20
25
30
35
# of dam removals
Biophysical response parameters
Upstream
Reservoir
Downstream
Fig 7. Before- and after-removal biophysical study parameters. Number of dam removals with upstream, reservoir, and downstream studies that
reported the before- and after-removal responses of physical, water quality, and biological parameters.
https://doi.org/10.1371/journal.pone.0180107.g007
Table 5. Measurement metrics.
Phosphate Nitrate Aquatic Invertebrates Target Fish Fish Assemblage
Total = 5 Total = 2 Abundance = 7 Abundance = 22 Abundance = 2
Dissolved = 4 Dissolved = 7 EPT abundance = 6 CPUE = 2 Biomass = 1
Particulate = 1 Particulate = 1 % EPT = 2 # of redds = 1 Composition = 7
SRP = 2 Diversity = 4 Size = 1 Diversity = 9
MRP = 1 Richness = 7 Richness = 6
HBI score = 2 IBI = 2
Multiple metrics were used to measure the same parameter in before-after dam-removal studies. For each
metric, the type of measurement reported is listed, followed by the number of dam removals using each
metric. SRP–soluble reactive phosphorus; MRP–Molybdate reactive phosphorus; EPT–Ephemeroptera,
Plecoptera, Trichoptera assemblage; HBI–Hilsenhoff biotic index; IBI–Index of biotic integrity.
https://doi.org/10.1371/journal.pone.0180107.t005
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Increased No change Decreased 5 = # of samples
No data
Grain size Turbidity SSC Phosphate Temperature DO Target FishInverts Fish CmtyNitrate
Upstream
Downstream
Reservoir
15 6
22
14
6
32
96
65
11
14
9825
2
15
22
822
18
10
25
21
7
7
184
19
20
All dam removals with before-after studies
Cluster b - West (Edwards, Gold Ray, Milltown, Savage Rapids)
Grain size Turbidity SSC Phosphate Temperature DO Target FishInverts Fish CmtyNitrate
Upstream
Downstream
Reservoir
10
0
1
0
1
01
00
0
0
000
0
0
0
01
0
0
0
20
0
00
0
0
Grain size Turbidity SSC Phosphate Temperature DO Target FishInverts Fish CmtyNitrate
Upstream
Downstream
Reservoir
32
3
3
1
7
32
12
4
3
317
0
3
7
18
7
2
10
8
1
1
8
1
9
7
Cluster e - Upper Midwest (Big Spring, Boulder Creek, Dexter, Ft Covington, Hinkletown, LaValle, Nashville, Oak St., Rockdale,
Sandstone, Shopiere, Stronach, Waterworks, Woolen Mills)
Cluster c - Pacific Northwest (Condit, Dinner Creek, Elwha, Hemlock, Marmot)
Grain size Turbidity SSC Phosphate Temperature DO Target FishInverts Fish CmtyNitrate
Upstream
Downstream
Reservoir
31
4
3
0
5
0
1
10
0
2
200
0
2
0
01
0
1
2
2
0
0
0
0
1
1
Cluster g - Midwest (Appleton, Brewster, Embrey, Fifth Ave, Main St, Munroe Falls, North Ave, South Batavia, St. John)
Grain size Turbidity SSC Phosphate Temperature DO Target FishInverts Fish CmtyNitrate
Upstream
Downstream
Reservoir
10
2
2
1
1
00
00
1
0
100
1
0
2
32
0
1
1
1
0
2
21
0
1
Grain size Turbidity SSC Phosphate Temperature DO Target FishInverts Fish CmtyNitrate
Upstream
Downstream
Reservoir
42
8
3
2
10
42
32
4
6
2412
1
6
5
46
7
4
9
64
3
52
9
6
Cluster h - Southeast (Carbonton, Dead Lake, Lowell, Murphy Creek)
Cluster f - New England (Brownsville, Franklin Mills, Good Hope, Hellbergs, Manatawny Creek, McCormick-Saeltzer,
Merrimack Village, Mill, Pawtuxet, Shearer, Simpkins, Sodom, Woodside, Woolen Mills, Zemko)
Grain size Turbidity SSC Phosphate Temperature DO Target FishInverts Fish CmtyNitrate
Upstream
Downstream
Reservoir
11
3
2
1
3
1
0
11
1
0
112
0
0
4
02
3
0
1
0
0
0
20
0
2
Fig 8. Biophysical responses to dam removal. Biophysical response for all before- and after-removal
studies (top row) and within each distinct geographic cluster.
https://doi.org/10.1371/journal.pone.0180107.g008
Landscape context of dam removal and river response
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did not change upstream or in the reservoir reach but increased downstream; and suspended-
sediment concentration increased downstream after dam removal. On the basis of limited
measurements, water quality responses varied by geographic cluster, but many locations
showed no change in water quality parameters in any of the three river reaches. In the Upper
Midwest and New England clusters, however, phosphorus concentration (inclusive of all
reported phosphate metrics listed in Table 5) increased downstream after dam removal, while
nitrate concentration increased in the reservoir reach and downstream after dam removal in
the Southeast cluster. Water temperature did not change in any river section after dam re-
moval in a majority of studies, but after three removals—including two large removals in the
Pacific Northwest—water temperature decreased downstream of the removed dams. A de-
crease in water temperature in the reservoir reach after dam removal was observed in only two
of ten studies (Fig 8), yet a decrease in water temperature in the reservoir reach is assumed to
be a typical response following dam removal [36].
Biological responses to dam removal were more variable than physical and water quality
responses, particularly downstream of the dam. Aquatic invertebrate and fish (single species or
Table 6. Anthropogenic landscape context.
Cluster (HCI
score)
Urban
(%)
Forested
(%)
Agriculture
(%)
Population
density (#/km
2
)
Road
crossings
(#/km
2
)
Water
withdrawal
(MGY)
Phosphorus
input (kg/km/yr)
Nitrogen
input (kg/km/
yr)
Sediment
input (kg/km/
yr)
a–Mountain
West
(2.9 –
moderate
risk)
0.02 72.9 1.0 34.3 0.14 30.7 9.0 39.0 2292
b–West
(2.1 –high
risk)
1.5 63.0 5.2 9.3 0.31 16.6 16.7 58.0 6814
c–Pacific
Northwest
(2.9 –
moderate
risk)
1.0 82.1 0.8 10.1 0.17 3.6 7.1 68.1 17738
d–Arizona
(3.3 –low
risk)
0.1 60.3 0 5.2 0.17 3.6 2.1 8.5 4610
e–Upper
Midwest
(3.0 –
moderate/low
risk)
3.2 30.2 48.0 15.9 0.43 13.2 77.8 723 57149
f–New
England
(2.9 –
moderate
risk)
5.1 53.8 20.5 44.7 0.57 25.9 97.2 697 85414
g–Midwest
(1.1 –high
risk)
9.7 19.6 54.1 25.1 0.49 57.6 92.9 1288 71285
h–Southeast
(3.0 –
moderate/low
risk)
2.6 30.7 20.4 77.9 0.44 108.4 49.0 321 51079
Anthropogenic landscape context for before- and after-removal studies clusters.
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community) responses varied among geographic clusters, and were also highly variable within
a single geographic cluster (Fig 8). This variability was particularly evident at sites downstream
of the dam in the two geographic clusters with the highest number of biological BAR studies,
the Upper Midwest and New England, where there were nearly equal numbers of studies
showing an increase, decrease, or no change in aquatic invertebrate and fish responses (Fig 8).
In contrast, a majority of the BAR studies from reservoir and upstream reaches reported an
increase in aquatic invertebrates or fish. BAR studies reporting the response of fish community
composition were entirely absent from dam removals in the West and Pacific Northwest clus-
ters—the clusters containing some of the largest dam removals.
Discussion
Dam removals have occurred throughout the United States but have been concentrated in
watersheds that represent a relatively narrow range of landscape characteristics compared to
the characteristics of the existing dams throughout the U.S. Most dam removals have occurred
in low-elevation watersheds with low catchment slope and large upstream areas, and most
BAR studies were conducted in watersheds with similar characteristics. Watersheds in wet
climates (high precipitation) with steep slopes, high mean elevations, and good fish habitat
conditions (low chance of degradation) were poorly represented in BAR studies. Apparent
geographic discrepancies between existing-dam density and removed dams may be due to fac-
tors related to economics, historical context, and dam function (e.g., irrigation, flood control,
hydropower), but that information is rarely reported, and the discussion of those factors is
beyond the scope of our analyses.
Biophysical responses to dam removal varied by geographic region, and not all biophysical
variables were consistently reported after dam removals. Inconsistencies in the metrics
reported, measurement timing, and study duration made it difficult to quantitatively assess
biophysical responses in geographic regions with different landscape characteristics and pre-
dict how a system might respond to a dam removal based on its landscape context. We identi-
fied distinct differences in landscape context among existing and removed dams, and BAR
studies. Our analysis comparing existing and removed dams, however, was limited to dams
that were either 8 m tall with an 18,500-m
3
or larger impoundment or 2 m tall with an
impoundment at least 62,000 m
3
. Many removed dams did not meet those height or impound-
ment size requirements; of the 874 removed dams included in our analysis, only 165 of them
met the criteria for being listed in the NID. Some states have more comprehensive inventories
of existing dams, including small dams, but the NABD—which draws data from the NID—is
the only publicly available list of existing dams throughout the country that is spatially linked
to the NHDPlusV1.
Fish habitat condition index scores for existing dams were nearly the opposite of HCI
scores for removed dams. Very low-quality fish habitat with high risk of degradation charac-
terized many landscapes around existing dams, but dam removals have occurred in landscapes
with moderate to high quality fish habitat with moderate to low risk of degradation. Dam
removals may have been more common in areas with high quality fish habitat to enhance the
probability of a successful outcome, particularly if ecosystem restoration was a goal of the dam
removal. The HCI was calculated based on landscape characteristics of the watershed above a
dam, and is an important metric to consider when planning dam removals because habitat
quality within the watershed influences the biophysical responses to dam removal and the
potential for habitat condition improvements [37]. River ecosystems may be more likely to
recover to pre-dam conditions if dam emplacement is a main source of anthropogenic stress-
ors on the landscape, contributing to an increased risk of habitat degradation (Table 6).
Landscape context of dam removal and river response
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Watershed area, elevation, and precipitation were the dominant landscape variables sepa-
rating the geographical clusters of removed dams. Of the 57 unique clusters identified in the
cluster analysis, 43 were concentrated in the lower-right quadrant of the PC plot, representing
large-area, low-elevation, and low-precipitation watersheds (Fig 5A). This pattern held for all
studied dam removals (Fig 5B) and BAR studies (Fig 5C). This predominant clustering of
removals suggests that our frame of reference for understanding the biophysical response to
dam removal is quite limited. This was especially true for BAR studies, which rarely examined
physical and biological responses.
For the eight clusters of dam removals with BAR data, we were unable to quantitatively
compare the biophysical responses with respect to landscape context because reported vari-
ables were neither consistent nor standardized. With the exception of BAR studies in the New
England cluster, each cluster had missing data for at least one of the ten metrics examined, and
many variables were only reported in one dam removal in the cluster. For dam removals with
landscape characteristics outside the main groupings, whole classes of response variables were
missing, including water quality and fish response data (Fig 8).
A number of factors likely contributed to the variation in biophysical response among geo-
graphic clusters. Firstly, the metrics used to measure responses varied among dam removals.
For example, in the papers we reviewed, investigators used five different metrics to measure
changes in phosphorous concentration and six metrics to measure changes in aquatic inverte-
brates (Table 5). Secondly, metrics were reported over different temporal scales [2], thus
potentially obscuring differences between short-term and long-term changes after dam
removal. For instance, after the removal of the Boulder Creek dams in South Carolina, soluble
reactive phosphorus concentration increased within hours [38], but concentrations decreased
after two weeks. As a result, there was no significant long-term change in phosphate concen-
tration before and after dam removal. Similarly, dissolved phosphate concentration increased
when the Good Hope Mill Dam in Pennsylvania was breached, but it returned to pre-removal
levels within hours [39]. Aquatic invertebrate and fish responses to dam removal, particularly
downstream, were strongly dependent on study timing [40]. Studies conducted immediately
after dam removal commonly showed a decrease in invertebrate and fish metrics downstream
of a dam removal, especially if sediment grain size changed [41,42]. In contrast, studies that
were conducted after the initial pulse of sediment moved through the system following dam
removal showed either no change or a positive effect of dam removal [43,44]. Finally, the
reported biological response to dam removal can be influenced by the species monitored. For
instance, in our analysis, some aquatic invertebrate studies reported responses of species that
were present before dam removal [45,46] and others reported the responses of species that
were expected to colonize after dam removal (i.e., EPT taxa) [47–49]. In the first case, species
tended to decrease after dam removal, while in the latter case they tended to increase. Other
studies reported species diversity or richness [40,50–53], which can be difficult to interpret
without species-specific information because those metrics may not change if an equal number
of pre-removal species are replaced with post-removal species.
Some of the biophysical responses we found in the literature were unexpected. For instance,
water temperature decreased in reservoir and downstream reaches in only 10% of studies we
examined [47,54,55] and nutrients increased downstream in only 30% of studies [39,45,46,
48,56–58]. We expected these percentages to be much higher based on assumptions of bio-
physical response to dam removal [15,17,59,60]. Individual fish species and fish communities
upstream of a dam removal did not change in 40% of dam removals examined, nor did they
change in more than 25% of downstream sites examined. The scientific community needs
more data to understand ecosystem response in order to inform management decisions and
create realistic expectations for post-removal recovery.
Landscape context of dam removal and river response
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Our analysis did not consider all of the possible variables that could contribute to biophysi-
cal response to dam removal, and we recognize that landscape context does not affect all
responses. For example, at Fossil Creek Dam, Arizona, native fish density increased after flow
was restored to the downstream system, but only in stream segments where invasive species
had been removed [61].
To date, most dams have been removed for economic, safety, or liability reasons rather
than to restore ecosystem function [62]. As with many restoration efforts, removal rationales
are not always available, nor is there a singularly agreed upon reason for removing a dam.
Therefore, the objectives (or lack thereof) for removing dams may affect the types of variables
monitored before and after dam removal. However, every dam removal, no matter the ratio-
nale, is an opportunity to gain further insight into how ecosystems respond and how physical
and biological responses are connected. Recognizing the need for studies to remain focused on
their objectives, we suggest that variables sampled before and after dam removal be prioritized
and protocols developed in an attempt to coordinate and standardize the type of data that are
collected. Many studies on dam removals were not comparable because of differences in met-
rics measured, methodologies employed, and study interval, including whether or not pre-
and post-removal data were collected. Standardization of the type, frequency, and duration of
data collection can help the scientific community better understand how the responses of river
ecosystems vary as a function of landscape context. The following approaches provide exam-
ples of potential standardized procedures for evaluating biophysical responses of river systems
to dam removal:
1. Sample before and after dam removal and at temporal and spatial scales that are meaningful
for the metrics sampled and the magnitude of anticipated change.
2. Sample upstream, within the reservoir, and downstream of the proposed dam removal site.
Studies that focus solely on the downstream response to dam removal do not provide a
comprehensive view of biophysical response.
3. Sample a broad range of metrics for comparative purposes. If that is not possible, prioritize
response measurements for indicator species that have known relationships to other
variables.
4. Use technology and citizen science to expand the duration of the sampling or monitoring
program. Satellite images are becoming increasingly available (e.g., Digital Globe) and can
be used to assess landform and vegetation changes. Enlist citizen scientists to take spatially
aligned repeat photographs, measure stream temperature, or record other parameters from
fixed locations.
5. Compile, preserve and publically release data. Add data to public databases, including the
Dam Removal Information Portal (https://www.sciencebase.gov/drip/).
Conclusion
Dam removal has become an increasingly common restoration strategy, and new efforts are
underway to help prioritize removals and guide removal decision-making [63]. Management
decisions to remove dams are beginning to adopt a range of strategies, from a “hot spot”
approach [64] to more overt economic strategies for prioritizing barrier removal [65,66], to
those aimed at achieving broader ecological gains [67,68]. Our results indicate that landscape
context may inform possible biophysical responses to removal, but a broader geographic range
of removals is required. Thus, along with other management priorities, decisions about dam
Landscape context of dam removal and river response
PLOS ONE | https://doi.org/10.1371/journal.pone.0180107 July 10, 2017 20 / 24
removal might consider where the proposed removal is located and how its removal can help
advance our understanding of biophysical responses of river systems. Dam removals are large-
scale experiments that offer tremendous opportunities to understand fluvial systems and the
influence of humans on watershed processes and ecosystem dynamics. Knowledge of biophysi-
cal responses to dam removal in a regional context can be leveraged to anticipate the effects of
pending dam removals and to help coordinate management efforts to meet conservation and
restoration goals.
Supporting information
S1 Table. Before- and after-removal studies. Before-after-removal studies used in our statisti-
cal analysis; biophysical parameters measured in each study are indicated with grey shading.
(DOCX)
S2 Table. EPA Level I, II, and III Ecoregions. EPA Level I, II, and III Ecoregion classifications
(https://www.epa.gov/eco-research/ecoregions-north-america) for dams listed in the National
Anthropogenic Barrier Dataset (NABD), removed dams in the USGS Dam Removal Informa-
tion Portal (DRIP), and removed dams with before- and after-removal studies (BAR).
(DOCX)
Acknowledgments
We gratefully acknowledge funding from the U.S. Geological Survey’s John Wesley Powell
Center for Analysis and Synthesis, which supported our efforts to synthesize dam removal sci-
ence. In particular, we thank Jill Baron and Leah Colasuonno at the Powell Center for their
help and encouragement. We also thank Amy East and one anonymous reviewer for their
insightful comments. Any use of trade, product, or firm names is for descriptive purposes only
and does not imply endorsement by the U.S. Government. Data used in this synthesis are pub-
licly available and are listed in the references.
Author Contributions
Conceptualization: Melissa M. Foley, Francis J. Magilligan, Christian E. Torgersen, Jon J.
Major, Chauncey W. Anderson, Patrick J. Connolly.
Data curation: Daniel Wieferich, Dana Infante, Laura S. Craig.
Formal analysis: Melissa M. Foley, Christian E. Torgersen, Daniel Wieferich.
Methodology: Melissa M. Foley, Francis J. Magilligan, Jon J. Major, Chauncey W. Anderson,
Patrick J. Connolly, Patrick B. Shafroth, James E. Evans.
Writing – original draft: Melissa M. Foley, Francis J. Magilligan, Christian E. Torgersen, Jon
J. Major, Chauncey W. Anderson, Patrick J. Connolly, Daniel Wieferich, Patrick B. Sha-
froth, James E. Evans, Dana Infante, Laura S. Craig.
Writing – review & editing: Melissa M. Foley, Francis J. Magilligan, Christian E. Torgersen,
Jon J. Major, Chauncey W. Anderson, Patrick J. Connolly, Daniel Wieferich, Patrick B. Sha-
froth, James E. Evans, Dana Infante, Laura S. Craig.
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