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2013 SOUTHEASTERN NATURALIST 12(Monograph 5):1–36
A Database and Meta-Analysis of Ecological Responses to
Stream Flow in the South Atlantic Region
Ryan A. McManamay1,*, Donald J. Orth2, John Kauffman3, and Mary M. Davis4
Abstract - Generalized and quantitative relationships between flow and ecology are pivotal
to developing environmental flow standards based on socially acceptable ecological
conditions. Informing management at regional scales requires compiling sufficient hydrologic
and ecological sources of information, identifying information gaps, and creating a
framework for hypothesis development and testing. We compiled studies of empirical and
theoretical relationships between flow and ecology in the South Atlantic region (SAR) of
the United States to evaluate their utility for the development of environmental flow standards.
Using database searches, internet searches, and agency contacts, we gathered 186
sources of information that provided a qualitative or quantitative relationship between
flow and ecology within states encompassing the SAR. A total of 109 of the 186 sources
had sufficient information to support quantitative analyses. Ecological responses to natural
changes in flow magnitude, frequency, and duration were highly variable regardless
of the direction and magnitude of changes in flow. In contrast, the majority of ecological
responses to anthropogenic-induced flow alterations were negative. Fish abundance,
diversity, reproduction, and habitat consistently showed negative responses to anthropogenic
flow alterations, whereas other ecological categories (e.g., macroinvertebrates and
riparian vegetation) showed somewhat variable responses and even positive responses
(e.g., algal abundance). Fish and organic matter had sufficient sample sizes to stratify natural
flow-ecology relationships by specific flow categories (e.g., high flow, baseflows) or
by physiographic province (e.g., Coastal Plain, Piedmont). After stratifying relationships,
we found that significant correlations existed between changes in natural flow and fish
responses. In addition, a regression tree explained 57% of the variation in fish responses
to anthropogenic and natural changes in flow. Altogether, our results suggested that the
source of flow change and the ecological category of interest played primary roles in determining
the direction and magnitude of ecological responses. Furthermore, our results
suggest that developing broadly generalized relationships between ecology and changes
in flow at a regional scale is unlikely unless relationships are placed within meaningful
contexts, such as environmental flow components or geomorphic settings.
Understanding the role of hydrology in structuring the biota of river environments
has been a recent theme in stream ecology (Allan 1995, Gordon et al.
2004). The complexity in which moving water interacts with physical and chemical
properties of a stream provides the template for ecosystem functions (Cuffney
and Wallace 1989, Hornick et al. 1981, Newbold et al. 1982) and the habitats to
1Environmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge, TN
37831-6351. 2Department of Fish and Wildlife Conservation, Virginia Polytechnic Institute
and State University, Blacksburg, VA 24061. 3John Kauffman, LLC, PO Box 66, Free
Union, VA 22940. 4Southern Instream Flow Network, Southeastern Aquatic Resources
Partnership, Decatur, GA 30030. *Corresponding author - email@example.com.
2 Southeastern Naturalist Vol. 12, No. 5
which organisms are adapted (Bunn and Arthington 2002, Poff and Allan 1995,
Poff et al. 1997). Although the potential and realized effects of hydrological
modifications on ecological systems has been clearly communicated (Carlisle
et al. 2011, Jackson and Pringle 2010, Pringle et al. 2000), the prevailing questions
related to ecologically sustainable flows, such as “How much?” and “How
often?”, remain to be answered (Richter et al. 1997, 2003).
Because of the extent and potential impact of anthropogenic disturbances on
flowing environments, river managers require consistent guidelines to organize
water policies geared towards water consumption and streamflow regulation.
Unfortunately, the complexity of socio-economic, political, and ecological needs
typically result in overly simplistic, static-flow guidelines that do not protect
the natural flow variability of river systems (Arthington et al. 2006). Predictable
and quantitative relationships between flow and ecology are pivotal to informing
social processes (Poff et al. 2010), such as developing environmental flow
standards based on socially acceptable ecological conditions (Richter et al.
2003). For example, the Ecological Limits of Hydrologic Alteration (ELOHA)
framework, the consensus view of 19 international scientists, includes developing
empirically testable relationships between flow alteration and ecological
responses within different river types (i.e., groups of streams and rivers characterized
by similar hydrologic regimes and geomorphic characteristics) (Poff
et al. 2010). Presumably, different types of rivers may respond similarly to flow
alterations (Arthington et al. 2006).
Developing these “flow-ecology” relationships will obviously require compiling
hydrologic and ecological databases to support regional quantitative analyses.
Water policies are typically developed within state boundaries without regard to
holistic basin needs (Sherk 1991, 1994, 2000). However, from a regulatory
perspective, some state water resource programs have established some impressive
research-based environmental flow protection standards. In Massachusetts,
Armstrong et al. (2011) established quantitative relationships between fluvial fish
relative abundance and species richness in response to % alteration in August
median flows from groundwater withdrawals and % impervious cover. Michigan
established legislation requiring a model to estimate the potential impacts of water
withdrawals (Zorn et al. 2008). Using habitat suitability indices, Zorn et al.
(2008) developed a model to predict fish responses to withdrawal scenarios and
by association, summer temperatures. Results of the model were integrated into
sophisticated impact assessment software (IWR 2008).
Due to practical constraints and the desire to develop more region-specific
guidelines, there is a need to compile sources of information at small operating
scales, such as ecoregions or the US Fish and Wildlife Landscape Conservation
Cooperatives (USFWS 2012). One approach is to use publically available spatial
datasets, such as the USGS NAQWA program (USGS 2012), the EPA REMAP program
(EPA 2010), or localized agency-derived databases. However, overlapping
hydrologic and ecological spatial datasets are not available for many areas, which
may preclude robust analyses for particular basins or geopolitical boundaries
2013 R.A. McManamay, D.J. Orth, J. Kauffman, and M.M. Davis 3
(Knight et al. 2008) or may lead to coarse national analyses (Carlisle et al. 2011).
A different approach includes conducting reviews and meta-analyses of the existing
literature concerning flow-ecology relationships. Within the specific context
of ecological responses to anthropogenic flow modifications, literature compilations
to inform water policy are not unprecedented (e.g., Loyd et al. 2003, Poff and
Zimmerman 2010). Loyd et al.(2003) reviewed 70 grey and peer-reviewed studies
predominately conducted in Australia but also from the global literature and found
that 86% of the studies reported ecological changes associated with anthropogenic
flow modifications. Poff and Zimmerman (2010) conducted a global review of
165 peer-reviewed sources and found that 92% of the papers reported decreases
in ecological responses to anthropogenic-induced flow alterations. Both studies
reported a deficiency in the number of studies containing sufficient information to
conduct quantitative analyses. Furthermore, one of the central and yet disconcerting
conclusions from both studies was that “simple thresholds” (Loyd et al. 2003)
or “general, transferable quantitative relationships” (Poff and Zimmerman 2010)
could not be obtained from the existing literature. Given the limiting information at
the global or continental scale, what is more disconcerting is the potential for inadequate
information at smaller regional scales.
In response to a possible information deficit, developing generalized relationships
between flow and ecology has become a nation-wide research priority
(Poff et al. 2010). For example, the Southern Instream Flow Network (SIFN), a
program within the Southeastern Aquatic Resources Partnership (SARP), defined
a comprehensive research agenda in 2010 to improve and provide new tools for
instream flow protection and management (SIFN 2010). The research agenda
identified five prioritized scientific needs, one of which included using existing
information to develop commonalities or generalizations in ecological responses
to hydrologic alterations. From this information, hypotheses regarding ecological
responses to changes in flow can be developed, tested, and then used to support
establishing regional environmental flow standards.
As a part of this larger coordinated effort, the South Atlantic Landscape
Conservation Cooperative desired to compile and summarize sources of information
relating altered flow to ecology within the South Atlantic Region
(SAR): Alabama, Georgia, Florida, North Carolina, South Carolina, and Virginia.
The primary purpose of this project was to compile a body of knowledge on
empirical and theoretical relationships between flow and ecology in order to aid
managers in developing environmental flow standards in the SAR. Specifically,
our goals were to 1) compile sources of information, 2) develop a database of
meta-data associated with each source, and 3) conduct a qualitative and quantitative
meta-analysis to determine any generalized relationships between flow
and ecology in the SAR. Because of the potential for limiting availability of
information at this scale, we broadened our search to not only peer-reviewed
publications within databases but also grey literature and unpublished data
through contacting representative federal and state agencies. Empirically based,
tested relationships between natural flow variation and ecological responses
4 Southeastern Naturalist Vol. 12, No. 5
obviously aid in generating hypothetical ecological response to anthropogenic
flow alterations (Arthington et al. 2006, Poff et al. 2010). Thus, we expanded
our search to include any ecological response to changes in flow, regardless of
whether the source was from natural variation or anthropogenic stressors. Here
we define natural flow variation as changes in flow attributed to natural hydrologic
processes (e.g., increases in flow magnitude due to flooding or decreases
in flow magnitude due to drought). We classify changes to the natural flow regime
attributed to some anthropogenic stressor (e.g., decreases in high-flow duration
due to urbanization, or increases in daily magnitudes due to hydroelectric
generation) as anthropogenic flow alterations.
Ecological response categories in our analysis included fish, macroinvertebrates,
algal and macrophytic vegetation, riparian vegetation, aquatic and
terrestrial wildlife, organic matter, ecosystem metabolism, and nutrients. For
fish, macroinvertebrates, and riparian vegetation, responses included changes
in abundance, growth, survival, species richness, community composition, diversity
(including biotic integrity indices and trophic diversity), reproduction,
behavior, and habitat. Although habitat is only a surrogate for ecological responses,
habitat-flow relationships have been used extensively and successfully
to aid in developing environmental flow standards (Annear et al. 2004, Tharme
2003) and they can be linked to biological changes if used appropriately (Poff
et al. 2010). Reproduction studies typically included measures of nesting success,
spawning habitat, and egg abundance. Behavior studies included fish and
macroinvertebrate drift, migration, or changes in use of different habitat types
in relation to flow. For studies involving periphyton and algae, typical responses
included abundance, community composition, or primary production. Ecosystem
responses included alterations in metabolism, such as gross primary production.
We also included studies documenting changes in organic matter, such as decomposition
rates, fine and coarse-particulate export, and nutritional quality. Nutrient
responses were included as export or concentration in relation to flow.
For relevant ecological categories, habitat responses included habitat
suitability indices (HSI), habitat area (e.g., weighted usable area—habitat
availability), or specific habitat components of a particular category (e.g., fish
migratory habitat, floodplain habitat). Flow-habitat ecology studies included
defined areas of the river channel or floodplain important to various ecological
groups, such as the aerial extent of fish nursery habitat, but also theoretical
relationships, such as those found in Instream Flow Incremental Methodology
(IFIM) studies. IFIM studies evaluate changes in habitat suitability or area in
relation to incremental changes in flow. These studies typically are conducted by
staging discharges of various magnitudes from dams or by measuring dischargehabitat
relationships at different time periods in free-flowing rivers. IFIM studies
2013 R.A. McManamay, D.J. Orth, J. Kauffman, and M.M. Davis 5
vary from simple 1-dimensional habitat relationships for individual species to
multi-dimensional habitat relationships that incorporate biogenergetic models or
ecosystem-level process (Tharme 2003). Typically, habitat area or suitability is
calculated using combinations of depth, velocity, and substrate preferences for
aquatic organisms. We excluded IFIM studies from our analysis that used predefined
habitat-suitability models (e.g., Edwards et al. 1982). We only included
IFIM or habitat-suitability studies where habitat area or HSI was empirically derived
from field assessments of habitat preferences within the location of interest.
Other habitat studies (non IFIM) were included only if they presented habitat as
a defined area of the field site in relation to flow. For example, Townsend (2001)
assessed pre- and post-dam flooding regimes in the Roanoke River at Roanoke
Rapids, NC and reported associated changes in the area of floodplain inundation
and consequently, riparian species composition.
To find peer-reviewed published literature, we conducted literature searches
using three databases (BioOne, CabDirect, and ISI Web of Science) because
they seemed the most appropriate in finding relevant flow-ecology articles and
provided the broadest scientific coverage. An exhaustive list of keywords were
developed, reviewed, and then shortened to provide the most relevant keywords
for searches. We searched the US Geological Survey database containing openfile
reports or professional papers within the SAR relating to flow-ecology
relationships. Searches were also conducted within the Southeastern Association
for Fish and Wildlife Agencies (SEAFWA) conference proceedings database
since SEAFWA has broad membership and encompasses the entire SAR.
Agency reports or unpublished data related to flow-ecology relationships were
obtained by contacting agency and university personnel or by using search engines
on the web. We compiled contact information for members of the Instream
Flow Council, Warmwater Streams Committee within the Southern Division
of the American Fisheries Society, and SIFN within the SARP program. Each
of the organizations contained members who specifically have conducted management
or research related to fluvial ecology. Individuals were contacted by
email or phone to request reports or unpublished data that specifically addressed
quantitative relationships between alterations in flow, due to natural or anthropogenic
causes, and ecological responses. Members responded to the request by
sending reports or unpublished data in electronic form. Internet searches were
conducted using “Google” as a search engine to find agency reports, theses and
dissertations, conference proceedings, and publications in open-access, narrow
readership journals. Keywords used in internet searches were commonly associated
with studies cited in other reports or publications, specific high-profile
rivers, agencies, hydroelectric project names, or specific species listed as endangered,
threatened, or species-of-concern. All reports and unpublished data were
6 Southeastern Naturalist Vol. 12, No. 5
reviewed to ensure that the sources included an association with a legitimate
management agency or university and provided a date and location of report/data.
All journal articles, conference papers, reports, and unpublished data were
reviewed to determine their relevance in terms of 1) the occurrence within a
SAR state, and 2) the ability to isolate one qualitative or quantitative relationship
between a primary flow component (magnitude, duration, frequency, timing,
rate of change; Olden and Poff 2003) and an ecological response. After isolating
references that met our criteria, we constructed a database that included
attribute information useful for stratification and a summary of each study (see
Supplemental File 1, available online at https://www.eaglehill.us/SENAonline/
suppl-files/mon5-1123-McManamay-s1, and, for BioOne subscribers, at http://
dx.doi.org/10.1656/S1123.s1). A subset of variables and their descriptions used
to stratify studies is provided in Table 1. We recorded the latitude, longitude,
province, and drainage area of each study location. If a study encompassed more
Table 1. Subset of explanatory variables used in meta-database construction. “Y” in the Tree column
indicates variables were used in the regression tree (for fi sh responses only).
State Primary state location of each study.
Time start Beginning of hydrologic period of record encompassing study.
Time end End of hydrologic period of record encompassing study.
Sites Number of sites (see methods for site designation).
River type Categorizes rivers into free-flowing, dam-regulated, regulated by
canal or diversion, reservoir (inflow studies), or a combination .
Flow alteration Y Source of change in flow: general-natural variation, natural flooding,
natural drought, reservoir operation improvements, withdrawal,
urbanization, agriculture, or channelization.
Study scale Y Primary scale of analyses. Spatial, Temporal, or Spatio-temporal.
Latitude/longitude Latitude/Longitude of study location (see methods for multiple
USGS gage number USGS gage number for study location, if present (see methods for
Drainage area (DA) Drainage area or range in drainage area of study site (see methods
for multiple sites).
DA category Y Categories for drainage area: small (less than 12 mi2 or mesocosims),
small-med (21–150 mi2), med (203–1972 mi2), med-large
(2058–10,102 mi2), large (14,700–86,771 mi2), and indeterminant
(refers to sloughs, wetlands, or tidal influenced waterbodies
where drainage area could not be determined).
Province Y Physiographic province of study location (see methods for multiple
Quantitative Indicates if quantitative information exists for both the flow alteration
and the ecological response.
2013 R.A. McManamay, D.J. Orth, J. Kauffman, and M.M. Davis 7
than one location, we provided coordinates for the centroid of the study area associated
with the nearest USGS stream gage site, if applicable, and the average
drainage area. In each study, we recorded the primary flow components used in
each study and recorded any associated flow sub-components that would provide
additional information (e.g., annual flow, baseflows, flood, rise rate). Because
flow sub-components became complex, we created an additional variable that
lumped sub-components into composite flow categories (e.g., low flows, highflood
flows). We categorized each study by the source of change in flow, whether
due to anthropogenic sources (e.g., withdrawal, urbanization, reservoir operations)
or natural variation (e.g., flood, drought, variation). We also categorized
studies by ecological categories (e.g., fish, macroinvertebrate, riparian vegetation)
and by types of responses (e.g., abundance, growth, habitat, behavior).
In order to determine the spatial and temporal extent required to determine
flow-ecology relationships, we assessed each study’s period of record and
Table 1 continued.
Data type Indicates whether study was a peer-reviewed publication (Pr), grey
literature (Grey), or unpublished data (Up).
Hydrologic resolution Y Temporal resolution of the hydrologic data used in the analysis
(annual, monthly, daily, sub-daily).
Flow component Y Primary flow component of central importance in analysis (magnitude,
duration, frequency, timing, rate of change). From Olden
and Poff (2003).
Flow sub-component Sub-category for primary flow components. Sixteen sub-components:
baseflow, low baseflows, annual flow, monthly flow, high
flow/small flood, large flood, water level, drought-low flow,
intermittency, hydroperiod, constancy, rise rate, range, daily
Flow category Y Categorizes flow sub-component in 7 broader categories for multivariate
analyses: baseflows, low flows, flood-high, water level/
hydroperiod, constancy, rate of change, variability.
Ecological category Y Primary ecological response group of central importance in analysis
Response type Y Type of ecological response within each group (see methods).
Group Indicates whether analyses were based on individual species, genera,
families, guilds, or assemblages.
Flow-eco relationship Y Indicates whether flow-ecology relationship was direct or indirect.
Other factors complicate flow-ecology relationships. If they
were provided by authors, they were indicated (e.g., sediment,
temperature, salinity, nutrients).
Curve Indicates whether flow-ecology relationship was linear or curvelinear,
if predictable relationship was presented in study.
% flow alteration Y The percent alteration in the flow component.
% ecological response Y The percent alteration in the ecological response.
8 Southeastern Naturalist Vol. 12, No. 5
number of sites. We considered the period of record (POR) as the entire time
in years in which hydrologic records were needed to formulate ecological relationships,
not the time required to collect ecological information. In general,
the hydrologic POR directly overlapped with the time period of ecological data
collection. However, in some instances, a longer hydrologic record was used to
generate relationships in which ecological data were collected within a shorter
time span. We considered sites as areas representing independent samples (replicates)
in spatial studies or as areas used to develop independent flow-ecology
relationships. However, in the case of IFIM studies, although flow-ecology data
is collected from multiple reaches, the data is typically compiled to generate
composite flow-ecology relationships for a single river system; thus, these studies
were represented by only one site.
We also recorded whether each study provided a qualitative or quantitative
flow-ecology relationship. The direction of the change in flow and ecological
responses primarily depended on how the author(s) presented the results. For
example, authors reporting a positive correlation between fish abundance and
monthly flow resulted in both positive changes in ecological response and flow
in our dataset. Although theoretically the same relationship could be used to
generate negative changes in both flow and ecological responses, we only present
the direction presented by the authors. The directionality of some ecological
responses, such as abundance and richness, seem fairly straightforward to interpret.
However, changes in community composition, organismal behavior, and
organic matter responses are less intuitive. Generally, we interpreted alterations
in community composition as positive or negative if native, endemic, or flowspecialists
increased or decreased, respectively. Alterations in general habitat
area, availability, or suitability due to some disturbance use were considered
negative responses. We relied heavily on author interpretation to distinguish
negative and positive behavior responses. We separately reviewed the database
to ensure interpretation was as consistent as possible and to validate findings.
Increases in dispersal or migration, if indicated beneficial to populations by
authors, were considered positive. In contrast, forced movements due to disturbance
(e.g., hydroelectric peaking) were considered negative. Increases in nutrients
and organic matter export were considered positive, whereas decreases
were considered negative. Increases in organic matter decomposition rates and
increases in nutritional quality (e.g., increases in nitrogen or phosphorus content)
were considered positive. Although our qualitative analysis supported behavioral
and nutrients studies, we do not include any results from these studies
in our quantitative analyses.
Similar to Poff and Zimmerman (2010), for studies reporting quantitative
relationships, we recorded changes in flow and ecological responses as percent
changes. All flow-ecology relationships represented in each study were recorded
as long as separate flow components or separate ecological categories were
being evaluated. Studies frequently had more than one quantitative relationship.
For anthropogenic flow alterations, we presented % changes as alterations
from pre-disturbance (temporal) or reference conditions (spatial). For example,
2013 R.A. McManamay, D.J. Orth, J. Kauffman, and M.M. Davis 9
increases in flow magnitudes due to hydroelectric peaking operations were presented
as positive % changes from baseflow to peak flow magnitude, assuming
that most flows in reference streams do not exhibit daily fluctuations of this
magnitude and rate of occurrence. For changes in natural flow, we presented
% changes as natural linear relationships, changes from median conditions, or
changes from conditions prior to an acute hydrologic event. For example, if
authors presented changes in flow magnitude as a result from the occurrence
of a flood, we recorded positive % changes in flow from conditions prior to
the occurrence of the flood. As another example, losses in flow magnitude due
to droughts were recorded as negative % changes from flow magnitude during
non-drought years. In contrast to acute hydrologic events, natural flow
variation may occur along inter- and intra-annual scales, such as analysis within
the same river system, or occur across spatial scales, such as differences in
climate among basins. The majority of these studies were presented as linear
relationships between gradients of flow and ecology. Because of the complexity
of interpreting curvilinear trends, we did not include these results in the
quantitative analysis. We calculated % changes in flow and ecological variables
across the entire range of measured values and in the direction presented by the
authors. For example, Rogers et al. (2005) reported positive linear relationships
between minimum river stage and fish abundance in the Ocklawaha River, FL.
In this case, % increase in river stage and % increase in fish abundance was
calculated from the minimum to maximum values presented along the regressed
line. In some cases, differences in natural flow were reported across different
periods or different locations. For example, Lorenz (1999) assessed variation
in hydroperiod magnitude and fish assemblage biomass across several sites in
Florida Everglades sloughs. Percent changes in hydroperiod magnitude (e.g.,
water depth) and fish biomass were presented as changes from values at sites
considered optimal, i.e., higher ecological values and associated hydrologic
values, to values considered the least optimal. Although these studies are expected
to present variable changes in flow and consequently, ecological responses,
they still may provide results informative to generalizing flow-ecology
relationships. Our interpretation of natural flow variation attempted to provide
comparable results to that of anthropogenic flow alterations. For example, in
the case of Lorenz (1999), we could determine whether anthropogenic reductions
in hydroperiod magnitude and associated fish responses emulate patterns
observed from natural variation.
A central task of this paper was to summarize the impacts of changes in flow
on ecology (positive or negative responses), according to different sources of
change (e.g., withdrawals, flooding). We partitioned studies by source of change
in flows and then summarized how each primary flow component was altered and
any associated ecological responses. We compared anthropogenic-induced hydrologic
disturbances to natural variation to determine if there was any evidence
of overlap in ecological responses.
10 Southeastern Naturalist Vol. 12, No. 5
Quantitative and statistical analysis
Another central purpose of this study was to provide quantitative relationships
and to determine if flow-ecology relationships were similar with regard
to similar changes in hydrology, regardless of whether the cause of change was
from anthropogenic or natural sources. We expanded all flow-ecology relationships
into separate data entries despite some being found within the same study
(as long as each data entry represented a unique flow-ecology relationship). We
tested whether % ecological responses were different among different sources
of flow change, different study scales (e.g., spatial, temporal, spatio-temporal),
and study hydrologic resolution (e.g., annual, monthly, daily, sub-daily) using
Kruskal-Wallis tests followed up by post-hoc comparisons using a Tukey’s test
(alpha = 0.05 significance level).
We created separate plots of % ecological response versus % change in flow
according to different primary flow components: magnitude, frequency, and
duration. There were insufficient data to consider timing and rate of change. Prior
to plotting results and statistical procedures, we transformed the data by taking
the log(x + 1) for the absolute value in % alterations and % responses and then
retaining the sign from the original value. However, we provide untransformed
axis values for ease of interpretation. Analyses were separated into ecological
responses to natural flow variation relative to anthropogenic flow alterations. We
further explored relationships between fish metrics and flow magnitude because
of sufficient data. For fish responses to natural changes in flow magnitude, we
separated responses by physiographic province (i.e., Blue Ridge, Coastal Plain,
Piedmont, and Ridge and Valley; Fenneman and Johnson 1946). Because of the
limited number of natural flow studies in the Blue Ridge and Ridge and Valley
provinces, we created a composite category as “Mountains”. We also stratified
fish responses to natural flow by separating plots by flow categories (i.e., baseflows,
low flows, water level, and variability). For fish responses to anthropogenic
changes in flow magnitude, we observed that fish responses segregated into only
two quadrats, leaving unclear patterns across the entire plotted space. Thus, we
separated anthropogenic flow-fish relationships by quadrat and plotted responses
according to the source of flow change. In addition to fish, organic matter had
sufficient data to evaluate responses to changes in natural flow. Reservoir operation
improvement studies were also evaluated in a separate analysis. We tested
individual relationships using Spearman’s rank correlations.
We questioned the relative importance of various factors, such as basin
size, province, flow components, or type of hydrologic alteration, in determining
percent ecological responses. We used flow categories as potential
explanatory variables rather than flow sub-components. We focused solely
on fish responses because they had a sufficient sample size for a multivariate
analysis. We imported the % responses along with the variables (see
Supplemental File 1, available online at https://www.eaglehill.us/SENAonline/
suppl-files/mon5-1123-McManamay-s1, and, for BioOne subscribers, at
http://dx.doi.org/10.1656/S1123.s1) into the program R (ISM 2011) and developed
regression trees using the rpart package (Therneau et al. 2011). The
2013 R.A. McManamay, D.J. Orth, J. Kauffman, and M.M. Davis 11
rpart package uses recursive partitioning, which involves splitting the data
on each sequential node using variables that maximize the between-groups
sum-of-squares or maximizes the reduction in the total sum-of-squares. We
used a parametric analysis-of-variance procedure since % responses were
transformed and encompassed negative and positive values greater than 1.
This procedure continues throughout subsequent nodes until the subgroups
reach a specified minimal size or no further splits can be made (Breiman et al.
1998, Therneau and Atkinson 1997). Trees could become very complex; thus,
the second step involves a pruning procedure that minimizes the cross validation
error while also minimizing the mean-square error (increasing tree size or
complexity). Subsets of the dataset are retained and used to “test” the tree to
calculate an average cross-validation error (x-val error) across all nodes. The
x-val error is then compared to the cost complexity factor (cp), a parameter
that takes into account the residuals from the sum-of-squares of the tree in
relation to tree size (number of nodes). The tree is pruned at the cp value that
minimizes the x-val error within 1 SE (Breiman et al. 1998, Therneau and Atkinson
A total of 186 sources were isolated that provided a qualitative or quantitative
relationship between flow and ecology within states encompassing
the SAR (Fig. 1). Studies had fairly broad geographic representation. Of the
sources, 128 were peer-reviewed published articles, 55 were grey literature,
and 3 were unpublished data. Fish were the predominant ecological category
of interest in most studies (125), followed by macroinvertebrates (33) and riparian
vegetation (16) (Table 2). In general, within most ecological categories,
more sources were peer-reviewed literature than grey literature. Fish were the
only ecological category with sources of unpublished data (3). The majority
of studies were conducted or were focused within the Coastal Plain Province
(114), followed by the Piedmont (41), Blue Ridge (13), and Ridge and Valley
Table 2. Number of peer-reviewed, grey-literature, and unpublished studies within different ecological
categories. Multiple ecological categories could be represented within each study.
Ecological category Total Peer-reviewed Grey Unpublished
Fish 125 78 44 3
Macroinvertebrate 33 24 9 -
Riparian 16 15 1 -
Organic 10 9 1 -
Nutrient 9 5 4 -
Algae 6 5 1 -
Ecosystem GPP 4 2 2 -
Macrophyte 4 1 3 -
Mammal 2 - 2 -
Bird 1 - 1 -
Grand total 186 128 55 3
12 Southeastern Naturalist Vol. 12, No. 5
Provinces (7). Five of the studies were mesocosm experiments. Over 50% of
studies used hydrologic information collected within 5 years or less, whereas
over 80% used hydrologic information from 20 years or less. Over 50% of
studies were conducted at only one site, and 80% of studies were collected at 5
or less sites. There was a higher number of studies that documented ecological
Figure 1. Study sites in the South Atlantic Region within different physiographic provinces
(Fenneman and Johnson 1946) and according to different types of sources. Each dot
represents each study site or the approximate centroid of multi -site analyses.
2013 R.A. McManamay, D.J. Orth, J. Kauffman, and M.M. Davis 13
responses to natural flow variation (96) compared to studies documenting ecological
responses to anthropogenic flow alterations (76) or reservoir operation
improvements (e.g., flow restoration) (12).
The majority of studies evaluated the effects of changes in flow magnitude,
followed by duration and frequency. Fewer studies evaluated the influence of
rate of change in flow or flow timing. Overall, we isolated 16 different flow
sub-component categories (Table 1, see also variable descriptions in Supplemental
File 1, available online at https://www.eaglehill.us/SENAonline/supplfiles/
mon5-1123-McManamay-s1, and, for BioOne subscribers, at http://dx.doi.
org/10.1656/S1123.s1). High flows, flooding, average flow conditions (monthly,
annual, baseflows), and low baseflows had the highest frequency of quantitative
flow-ecology relationships. We created 7 broader composite flow categories
(Table 1) to simplify flow sub-components and to use in multivaria te models.
Studies evaluating relationships between natural flow variation and ecology
showed a variety of responses (Fig. 2; see Supplemental File 2, available online
and, for BioOne subscribers, at http://dx.doi.org/10.1656/S1123.s2). Changes in
flow and ecological responses in drought and flood studies typically represented
changes from baseline conditions along temporal scales (e.g., drought versus
non-drought years). Because these studies represent acute changes in flow due
to some disturbance, their results tend to be more intuitive. Interpreting changes
in flow and ecological responses in response to general flow variation, however,
becomes less clear since these studies were conducted over various spatial and
Within each natural flow variation type, the number of studies reporting positive
responses was very similar to those reporting negative relationships, with
the exception of drought studies and reservoir operation improvement studies
(Fig. 2; see Supplemental File 2, available online at https://www.eaglehill.us/
SENAonline/suppl-files/mon5-1123-McManamay-s2, and, for BioOne subscribers,
at http://dx.doi.org/10.1656/S1123.s2). Studies concerning droughts
reported more negative responses, whereas reservoir improvement studies reported
more positive responses. For ease of representation, we included reservoir
improvement studies in the natural flow variation summary (Fig. 2). Fish,
macroinvertebrates, and riparian ecological categories showed variable and
non-consistent responses to changes in average, high, and low flows as well as
variability. For example, increases and decreases in the magnitude of flows led to
increases and decreases in fish abundance and riparian tree growth (see Supplemental
File 2, available online at https://www.eaglehill.us/SENAonline/supplfiles/
mon5-1123-McManamay-s2, and, for BioOne subscribers, at http://dx.doi.
org/10.1656/S1123.s2). In contrast, organic matter export and decomposition, as
well as algal and primary production responses, showed consistent responses to
hydrologic alterations. For example, decreases in magnitude consistently led to
decreases in organic matter export and increases in algal abundance/production.
14 Southeastern Naturalist Vol. 12, No. 5
For anthropogenic flow alterations, ecological responses were more consistently
negative for most categories (Fig. 3; see Supplemental File 2, available online
and, for BioOne subscribers, at http://dx.doi.org/10.1656/S1123.s2). Fish consistently
showed negative responses regardless of the type of anthropogenic flow alterations,
whereas algae tended to respond responded positively. Although macroinvertebrates
and riparian ecological categories showed variable responses, the
majority of studies reported negative responses to anthropogenic flow alterations.
Quantitative and statistical analysis
A total of 109 studies out of the 186 included quantitative flow-ecology
relationships. We expanded the entire database into individual, quantitative flowecology
relationships from each study. The resultant database totaled 213 unique
flow-ecology relationships for all ecological categories combined, 140 of which
were for fish.
Figure 2. The number of negative (black) and positive (white) ecological responses to
changes in flow within natural flow categories and reservoir operation improvement studies.
No general patterns were apparent except the predominance of negative responses
to drought. Each study could potentially report both positive and negative relationships;
thus, the sum of positive and negative relationships may be greater than the total number
of papers (see Supplemental File 2, available online at https://www.eaglehill.us/SENAonline/
suppl-files/mon5-1123-McManamay-s2, and, for BioOne subscribers, at http://
dx.doi.org/10.1656/S1123.s2 for more detailed information).
2013 R.A. McManamay, D.J. Orth, J. Kauffman, and M.M. Davis 15
In general, ecological responses to natural flow variation were highly variable
whereas ecological responses to anthropogenic flow alterations were
predominately negative, regardless of the direction of flow change and the type
of ecological response. Ecological responses were significantly different among
sources of flow change (c2 = 25.14, df = 8, P = 0.0015). Ecological responses
to floods, natural variation, and improving reservoir operations were significantly
higher than ecological responses to withdrawals and reservoir operations,
whereas they were not significant from other categories (Tukey’s test: P <0.05).
Multiple comparisons among all other sources of flow change were not significantly
different. Ecological responses were not significantly different among
different study scales (c2 = 0.603, df = 2, P = 0.7399) or among different hydrologic
resolutions (c2 = 3.036, df = 3, P = 0.3862).
When considering all ecological categories, responses to natural changes in
flow magnitude were highly variable (Fig. 4). However, once we placed fish
responses into various contexts, patterns emerged, which explained more varia-
Figure 3. The number of negative (black) and positive (white) ecological responses to
types of anthropopogenic flow alterations. Responses for most ecological categories were
predominately negative with the exception of algae. Each study could potentially report
both positive and negative relationships; thus, the sum of positive and negative relationships
may be greater than the total number of papers (see Supplemental File 2, available
online at https://www.eaglehill.us/SENAonline/suppl-files/mon5-1123-McManamay-s2,
and, for BioOne subscribers, at http://dx.doi.org/10.1656/S1123.s2 for more detailed
16 Southeastern Naturalist Vol. 12, No. 5
Figure 4. Relationships between % changes in flow magnitude and % ecological changes
for natural flow variation (top) and anthropogenic flow alterations (bottom) according to
different ecological groups. Ecological responses to natural flow variation were highly
variable; however, responses to anthropogenic flow alterations were predominately negative.
Lower-left quadrat (A) and bottom-right quadrat (B) refer to negative % ecological
responses to decreases and increases in flow magnitude, respectively and are specifically
addressed in Figure 7.
2013 R.A. McManamay, D.J. Orth, J. Kauffman, and M.M. Davis 17
tion. Fish exhibited significant positive correlations with natural flow magnitude
within the coastal plain but showed no significant pattern within the mountain
(BlueRidge, Ridge and Valley) or Piedmont provinces (Fig. 5A, B). After
Figure 5. Positive correlation between natural % changes in flow magnitudes and % fish
responses for sites occurring in the coastal plain (A). No correlation was observed for
sites occurring in the upland provinces (Mountains, i.e., Blue Ridge and Ridge and Valley
combined , and Piedmont) (B). ρ represents Spearman’s rank coefficients followed by
P-values for statistical significance.
18 Southeastern Naturalist Vol. 12, No. 5
Figure 6. Relationships between % changes in the magnitude of various flow categories
(A–D) versus % changes in fish responses according to different response types. ρ represents
Spearman’s rank coefficients followed by P values for statistical significance.
stratifying data by flow categories, fish had significant positive correlations with
natural increases in moderate flow conditions (e.g., baseflow, monthly flow) and
marginally significant positive correlations with natural increases in water levels
(gage height) (Fig. 6A, B). Conversely, fish exhibited a significant negative
correlation with increases in flow variation (e.g., range in flows, coefficient of
variation; Fig. 6D). However, fish showed non-significant responses to natural
decreases in low-flow conditions (Fig. 6C).
In contrast to natural flows, most ecological responses to anthropogenic flow
alterations were negative (Fig. 4). Fish consistently responded negatively to
anthropogenic flow alterations. However, algae and macrophytes responded positively
to decreases in flow magnitude due to anthropogenic sources. Although
responses were at times unpredictable, macroinvertebrates typically responded
negatively to anthropogenic changes in flow magnitude. Riparian vegetation
responses were more variable. After separating fish responses by quadrat in
Figure 4, we observed that fish responses showed significant decreases with decreases
in flow magnitude (Fig. 7A). However, fish responses to increases in flow
magnitude were not significant (Fig. 7B).
2013 R.A. McManamay, D.J. Orth, J. Kauffman, and M.M. Davis 19
Sample sizes for ecological responses to natural and anthropogenic changes
in flow duration and flow frequency were not as large as that for flow magnitude,
which precluded statistical analyses. However, we observed the following apparent
trends in the data. Fish responded negatively to both natural and anthropogenic
Figure 7. Negative fish responses stratified by anthropogenic losses (A) and increases
(B) in flow magnitude. Graphs A and B refer to fish responses in Figure 4A and 4B. Fish
responses decreased predictably with losses in flow magnitude (A) whereas no relationship
was observed for increases in flow magnitude (B). ρ represents Spearman’s rank
coefficients followed by P values for statistical significance.
20 Southeastern Naturalist Vol. 12, No. 5
Figure 8. Ecological responses to % changes in flow duration due to natural flow variation
(top) and anthropogenic flow alterations (bottom). Fish displayed negative responses to
changes in flow duration regardless of whether the source was natural or anthropogenic
whereas responses by riparian vegetation and macroinvertebrates were variable.
2013 R.A. McManamay, D.J. Orth, J. Kauffman, and M.M. Davis 21
changes in flow duration (Fig. 8). Fish responses to changes in flow frequency
were negative for anthropogenic sources and variable to natural sources (Fig. 9).
Figure 9. Ecological responses to % changes in flow frequency due to natural flow variation
(top, fish only) and anthropogenic flow alterations (bottom). Fish responses were
variable to natural changes in flow and consistently negative to anthropogenic changes
22 Southeastern Naturalist Vol. 12, No. 5
Again, macroinvertebrates and riparian vegetation showed variable responses
to changes in flow duration or frequency, regardless of whether the source was
anthropogenic or natural (Figs. 8, 9).
Organic matter export exhibited a significant positive correlation with natural
changes in flow associated with baseflow magnitudes, flooding magnitudes, and
flooding frequency, whereas organic decomposition and nutritional content did
not show any pattern (Fig. 10). Reservoir improvement studies typically (7 of 8
responses) reported increases in flow magnitude, which generally led to positive
fish responses and inconclusive responses for macroinvertebrates; however, there
was no significant correlation for fish (Fig. 1 1).
We used regression trees to determine the relative importance of predictor
variables in determining the direction and magnitude of % ecological responses
for fish (n = 140). Cross-validation error minimized at a tree size of 5 branches.
The tree for fish explained 57% of the variation in % ecological responses
and included the source of flow change, % change in flow, flow category, and
drainage area size as predictor variables (Fig. 12). Anthropogenic flow alterations
and flooding led to negative fish responses, whereas drought, reservoir
operation improvements, and natural flow variation led to variable responses
(Fig. 12). Changes in flow less than 19.5% led to negative fish responses within
intermediate-sized river systems but more neutral fish responses in small and
large river systems. Changes in average flow conditions (baseflow, monthly
Figure 10. Positive relationship between percent changes in organic matter export, decomposition,
and nutrient composition in relation to % changes in flood-frequency (FF),
flood-duration (DF), flood magnitude (MF), and baseflow magntiude (MBFL).
2013 R.A. McManamay, D.J. Orth, J. Kauffman, and M.M. Davis 23
Figure 11. Percent ecological responses to % changes in flow magnitude due to reservoir
operation improvements. ρ represents Spearman’s rank coefficients followed by P values
for statistical significance.
Figure 12. Regression tree predicting % fish responses to natural and anthropogenicinduced
flow alterations using primary splitting variables (in box directly below each
node). Categories or values for each splitting variable are represented along branches.
Top value in each circle or box represents the average % ecological response at that specific
node or branch, respectively, whereas the bottom number represents the sample size.
24 Southeastern Naturalist Vol. 12, No. 5
flows, water levels) greater than 19.5% led to positive fish responses, whereas
19.5% or greater increases in fall rates, high flows, and ranges in flow led to
negative fish responses.
From our examination of responses to flow variation in 186 separate studies
in the SAR, we found that ecological responses to flow changes were primarily
dependent upon the source of change and the ecological category of interest.
Furthermore, over-generalized flow-ecology relationships, at least with regard to
primary flow components, were not supported unless relationships were placed in
appropriate contexts. For example, fish responses to natural changes in primary
flow components were highly variable and inconsistent; however, once responses
were stratified by flow categories and by geomorphic context, quantitative and
predictable relationships could be extracted (e.g., Figs. 5, 6). In addition, our
multivariate analysis using fish responses suggested that if sufficient meta-data
are included in database compilations, the predictive capabilities of these models
can be dramatically increased.
The evidence of common, directional (positive or negative) flow-ecology
relationships among studies in natural and anthropogenic-modified systems,
if present, would suggest that the results of flow-ecology studies can be
used interchangeably in supporting environmental flow standards, regardless
of temporal, spatial, or disturbance contexts. For example, losses in flow
magnitude, whether anthropogenic or naturally induced, led to predictable
decreases in fish metrics (abundance, diversity, and habitat) and increases
in algal abundance. However, the majority of ecological responses to natural
changes in flow were highly different than those to anthropogenic flow
alterations, despite similar directional changes in primary flow components.
Most meta-analyses in ecology, including ours, are designed to generalize
ecological responses, and thus have limitations. Determining what constitutes
a negative or positive response when considering response types or the focal
scale of the study (e.g., community, population, or individual) can be subjective
and influenced by interpretation. Although we attempted to be sensitive
to how the authors interpreted the ecological response, our results highlight
types of ecological categories that may be more prone to judgment-related uncertainty.
Generalizing studies conducted across various spatial and temporal
scales can also lead to ambiguous results. For example, the response of fish
abundance to changes in flow magnitude across sites with varying daily flow
averages may be very different compared to a single site with varying hourly
flows due to hydroelectric generation.
Natural flow variation. The majority of studies reported negative and
positive ecological responses to natural flow variation, regardless of similarities
in the direction of changes in flow. One exception was droughts,
2013 R.A. McManamay, D.J. Orth, J. Kauffman, and M.M. Davis 25
which consisted of decreased magnitudes and high-flow frequencies, and
in turn, negative ecological responses, such as decreased fish and macroinvertebrate
metrics and alterations to trophic community structure. However,
Grossman et al. (1998) and Grossman et al. (2010) reported increases in fish
abundance and diversity during drought because stream conditions in a North
Carolina mountain stream became more suitable to “drought immigrants”. In
addition, Averett et al. (2004) found that lower flows during drought conditions
increased algal abundance and habitat. In contrast to droughts, ecological
responses to flooding were less predictable. For example, a 500-yr flood event
and associated debris-flows resulted in, on average, 76% declines in Brook
Trout populations in 3 mountainous river systems in Virginia (Smith and Atkinson
1993). However, increases in the magnitude of flooding in the coastal
plain streams were associated with increased fish diversity (Strong and Nagid
2006). Floods typically have many beneficial ecological responses, such as increased
organic matter export (Atkinson et al. 2009) and increases in riparian
seed germination (Pierce and King 2007); however, the short- and long-term
ecological responses may depend on whether floods occur as habitat creation
or destruction. In rivers systems draining mountainous or piedmont provinces,
floods may be more disturbance-related, whereas in coastal plain rivers, floodplain
inundation occurs for major portions of the year and provides important
habitats and refuge for a host of fish, macroinvertebrates, plants, and wildlife
(Light et al. 1998, Pearsall et al. 2005, Rehage and Loftus 2007, Walsh et al.
2009). Thus, additional information, such as geomorphic structure of river
channels (e.g., confined versus unconfined), is essential to predicting ecological
responses to natural flow variation across broad regions (McCargo and
Anthropogenic flow alterations. In comparison to natural flows, ecological
responses to anthropogenic flow alterations were consistently negative.
Withdrawals were predominately associated with losses in flow magnitude,
and although most ecological responses were negative, there was some degree
of variability. Reservoir operations caused many more negative ecological
responses than any other source of hydrologic alteration. The ecological consequences
of dam operations are well documented within the SAR (Freeman et al.
2001, Hupp et al. 2009, Travincheck and Maceina 1994, West et al. 1988).
Fish tend to respond predictably to anthropogenic flow alterations, whereas
riparian and macroinvertebrate responses tend to be inconsistent (Poff and
Zimmerman 2010). The majority of studies that evaluated the effects of urbanization-
induced flow alterations on fish reported negative associations (Adams
et al. 2009, Helms et al. 2009a, Roy et al. 2005). In contrast, reported macroinvertebrate
responses to urbanization were, at times, positive (Helms et al.
2009b), and the algal responses were typically positive (Taulbee et al. 2009).
Interestingly, Brown et al. (2009) conducted a multi-regional study on the ecological
effects of urbanization-induced hydrologic alterations and reported that
macroinvertebrates, as opposed to fish and algae, showed the most consistent
26 Southeastern Naturalist Vol. 12, No. 5
Quantitative and statistical analysis
The advantage of quantitative analyses is that they can provide more digestible
pieces of information, stratify analyses into appropriate contexts, and finally,
organize predictions into quantitative predictions. Prior to segregating studies
into context-specific analyses, the results of our quantitative and statistical
analysis reiterated the results of the qualitative analysis: ecological responses to
natural flow variation were highly variable, whereas responses to anthropogenic
flow alterations were predominantly negative.
Natural flow variation. Once we stratified fish responses to natural flow
variation by flow category and by province, predictable patterns emerged that
provided opportunities for statistical analysis. Fish showed positive correlations
with increases in natural flow magnitudes in the coastal plain, whereas
no relationship was apparent in upland areas. Geomorphology may influence
how river communities respond to changes in flow magnitudes. For example,
simply organizing stream reaches on the basis of their ability to migrate may
increase the predictive accuracy of assessing ecological responses to flow
variation (Liermann et al. 2011, McCargo and Peterson 2010). Streams within
the Virginia piedmont commonly show parabolic relationships between Micropterus
dolomieu Lacepède (Smallmouth Bass) recruitment and spring/
summer flow magnitudes (Copeland et al. 2006, Smith et al. 2005), which
suggests low and high flows during spawning and young-of-year growth periods
in these systems may be detrimental to populations. In contrast, multiple
sources report positive linear relationships between fish abundance and flow
magnitudes in coastal environments for estuarine fish (Greenwood et al. 2008,
Peebles 2005), Morone saxatilis Walbaum (Striped Bass; James Bulak, South
Carolina Department of Natural Resources, Eastover, SC, unpubl. data), and
Micropterus salmoides Lacepède (Largemouth Bass; Bob Greenlee, Virginia
Department of Game and Inland Fisheries, Suffolk, VA, unpubl. data). Thus,
the occurrence of high flows or flooding in an unconstrained coastal plain
stream may be less of a disturbance to river communities than in a floodplainconstrained
Interestingly, fish responses were positively correlated with changes in
average flow magnitudes and water levels, but negatively correlated with
increases in flow variation. We cannot say with certainty that this is a trend
applicable to all systems and all fish species within the region. However, the
various types of responses (e.g., abundance, growth, diversity) in these analyses
were fairly diverse, which indicates our results are doubtfully influenced
by certain taxa.
Anthropogenic flow alterations. Fish had significant, negative responses
to reductions in flow magnitude as a result of withdrawals or reservoir operations.
These studies suggest that losses in fish habitat accompany losses in flow
magnitude, and the relationship can be predicted with some certainty. Given
2013 R.A. McManamay, D.J. Orth, J. Kauffman, and M.M. Davis 27
these results, we predicted fish responses would be inversely correlated to
anthropogenic increases in flow magnitude; however, no trend was observed.
Unlike decreased flows, increases in flow magnitude may not directly translate
to losses in habitat, especially due to reservoir operations. For example, increases
in magnitude may result from increased daily discharges from dams
during hydroelectric generation or flow inflation from seasonal storage. In a
nationwide assessment, Carlisle et al. (2010) found that predicting ecological
impairment or fish life-history traits from flow inflation was more difficult
compared to that of decreasing flow magnitudes.
Fish and organic matter responded consistently with alterations in some primary
flow components, regardless of the source of flow change. For example, fish
responded fairly consistently to changes in the duration of flows, whereas organic
matter responded consistently to changes in the magnitude, frequency, and duration
of flows. Increases or decreases the in the frequency, duration, or magnitude
of flows generally led to increases or decreases in organic matter export and decomposition,
respectively (Battle and Golladay 2001, Cuffney and Wallace 1989,
Wallace et al. 1995).
Reservoir improvement studies. Most responses of fish to reservoir operation
improvements were positive, whereas insufficient data existed to form
conclusions for macroinvertebrates or algal communities. Of the seven reservoir
improvement studies with quantitative information, five were associated
with increases in minimum flows. The degree of ecological benefits associated
with increased minimum flows will most likely depend on the extent of
disturbance conditions prior to restoration or the prevalence of other limiting
factors. For example, Travnicheck et al. (1995) reported a 138% increase in
fish species richness (8 to 19 species) following a 340% increase in minimum
flows below a dam. In contrast, Bednarek and Hart (2005) found that the effect
of increases in minimum flows below dams on macroinvertebrate richness,
although positive, was more effective if used in conjunction with increased
dissolved oxygen levels. We also found one study documenting the use of
pulsed releases from a hydroeletric facility to control nuisance periphyton
growth in a regulated river (Flinders and Hart 2009).
Similar to the other quantitative analyses, results of the regression tree suggested
that the source of flow change was the most important predictor of the
magnitude of fish responses. The combined results from our analyses suggest that
fish tend to respond negatively to changes in the extremities of the hydrograph.
For example, fish responded negatively to increases in flood magnitude/frequency,
high flows, fall rates, and ranges whereas responses to increases in average
conditions (baseflows, hydroperiod, monthly flows) were typically positive (e.g.,
Fig. 6 and 12). Flow categories are summaries of combinations of primary flow
components; thus, we expected that flow categories would explain more variation
in predictive models. For example, low flows suggest not only a direction
in magnitude but also duration whereas flooding suggests high magnitudes and
a frequency for particular river systems (assuming flooding is predictable). The
28 Southeastern Naturalist Vol. 12, No. 5
regression tree also suggested that the size of a particular basin may influence fish
responses, depending on the degree of flow change.
It is important to note that the regression tree only explained 57% of the
overall variation in fish responses. Obviously , many factors, such as sediment
and temperature, may play a role in influencing the nature of ecological responses
and may confound the effects of flow or interact with flow to influence
ecology. A total of 22% of the studies in our analysis mentioned other variables
that may interact with flow to influence ecological responses. For example,
losses in flow magnitude in coastal rivers were many times associated with encroachment
of salt wedges or the alteration of salinity levels in estuaries, both
of which affected fish populations (Bachman and Rand 2008, Greenwood et
al. 2008, Van Den Avyle and Maynard 1994). We also found evidence that relationships
between flow and fish were complicated by flow interactions with
sediment (Roy et al. 2005, Smith and Atkinson 1999) and temperature (Baker
and Jennings 2005, Krause et al. 2005). Although we included the nature of
flow-ecology relationships (direct or indirect) as a variable in our analyses, it
was excluded as an important predictor.
Implications for future studies and environmental flow standards
Documenting the mechanisms responsible for structuring ecological patterns
in relation to hydrologic variability has become increasingly important to developing
water policy standards at regional scales (Poff et al. 2010). Unfortunately,
analyses at smaller regional scales may be constrained due to insufficient overlapping
hydrologic and ecological data (Knight et al. 2008). Because sufficient
quantitative evidence may be unavailable, or only available for individual ecological
categories, developing mechanisms to efficiently use the best available
information may be required to support decision making (Sullivan et al. 2006).
Of the 186 sources within our study, approximately 30% were gathered from
grey literature. We find this extremely important since the grey literature might
be often overlooked as a legitimate source of data. Adopting environmental flow
standards are typically executed through regional or statewide agencies and
water-supply planning offices, who are informed through agency and consultant
reports, i.e., grey literature. As one of many examples, Florida statewide law
and water policy, as documented in the Florida Statutes (Chapter 373.042), requires
that regional water-supply planning offices develop minimum flow levels
(MFLs) for specified water bodies (TFS 2011). Personnel in the regional office
or outside agencies are then contracted to conduct technical field analyses, suggest
sufficient MFL levels, and produce technical reports, which are rigorously
peer-reviewed by a local water supply district panel for legitimacy as acceptable
research. In essence, grey literature can be a valuable resource that may inform
water policy at regional scales.
Analytical approaches may fail to maximize information resources at regional
levels because of strict search criteria (e.g., only sources with quantitative information
available). For example, previous studies have suggested there is insufficient
quantitative information to document generalized relationships between
2013 R.A. McManamay, D.J. Orth, J. Kauffman, and M.M. Davis 29
altered flow and ecology at continental (Loyd et al. 2003) and global scales (Poff
et al. 2010). In addition, analytical approaches may underrepresent complex ecological
dynamics by measuring ecological responses as negative/positive changes
or as percent changes. For example, a loss in river flows may lead to an increase
in riparian coverage through encroachment, i.e., positive response (Brandt et
al. 2000); however, alterations in riparian taxa abundance from changes in flow
are also likely to alter community structure, i.e., negative response (Burke et al.
2003). In response to the limiting and potentially confusing information, one
approach could be to organize responses as supportive or harmful to ecological
goods and services (Daily et al. 1997). An alternative approach is the “eco evidence”
method, which uses weighted evidence from literature to support a series
of a priori hypotheses about a cause-effect relationship (Norris et al. 2012). Because
cause-effect relationships may be limited within the ecological literature,
eco evidence approaches are convenient in that they provide strength of evidence
without diminishing the complexity of underlying ecological rel ationships.
We suggest that in order for flow-ecology relationships to become relevant
to management and reliable in creating environmental flow standards, analyses
should either be stratified into appropriate contexts or include other associated
predictors in multivariate models. Armstrong et al. (2011) increased the accuracy
of models predicting fish responses to flow alteration by adding % impervious
surfaces as a secondary variable. Despite great variation in the direction and
magnitude of changes in flow, anthropogenic flow alterations within our analysis
led to ecological losses. Ecological relationships with natural flow variation
were highly variable; however, the inclusion of additional explanatory variables
increased model predictive capacity.
We found that as little as a 10% change in flow can result in very large ecological
responses. We observed common directional responses to changes in flow by
particular ecological groups, regardless of the type of response or whether the
source was natural or anthropogenic. Fish, algae, and organic matter responses
to changes in flow were consistent and thus, may be good candidates for future
meta-analyses. For example, losses in flow magnitude, anthropogenic or naturally
induced, led to predictable decreases in fish metrics and increases in algal
abundance. Similarly, relationships between organic matter decomposition and
flow magnitude/freqency were predictable. Our results also suggest that acute
extremities in natural hydrographs, such as droughts and flooding, show the most
altered and predictable ecological responses; thus, anthropogenic alterations that
mimic these types of flow changes, such as withdrawals and reservoir operations,
may induce the most extensive and predictable ecological impacts. We recommend
that great care should be taken in interpreting ecological responses, such
as abundance measures and community composition, since these factors may be
highly influenced by subjectivity.
Primary flow components (e.g., magnitude, frequency) were relatively unimportant
in predicting most ecological responses in our analyses. Intuitively,
these results may not come as a surprise; however, primary flow components
30 Southeastern Naturalist Vol. 12, No. 5
have proved to be an efficient organizational template of hydrologic indices and
ecological responses (Bunn and Arthington 2002, Olden and Poff 2003, Poff et al.
1997). More descriptive hydrologic units, such as flow categories, may provide
more relevance in forming predictive flow-ecology relationships. For example,
environmental flow components (EFCs) provide an additional level of detail
(low, high, variability) to hydrologic metrics, which has increased their utility in
environmental flow settings and determining the extent of hydrologic alteration
(Mathews and Richter 2007).
Although we attempt to provide an overview of results associated with our
meta-analysis, we view the database compilation as an ongoing iterative process
where hypotheses are updated as new data is acquired. More research is needed
to isolate quantitative relationships, refine existing hypotheses, and generate
new hypotheses through future literature searches, meta-analyses, regional and
basin-specific studies, as well as mesocosm studies. Approximately one half of
our studies in our database were conducted at only one site. In addition, approximately
one half were conducted in five years or less. Thus, we conclude that there
is a considerable need for short-term studies conducted at small spatial scales,
i.e., case studies, to provide important information relevant to developing environmental
This project was funded by the South Atlantic Landscape Conservation Cooperative
and was managed by the Southeastern Aquatic Resources Partnership (SARP) and the
Southern Instream Flow Network, a program within SARP. We thank Scott Robinson
for providing technical support through SARP and Marilyn O’Leary for producing email
and internet notices for data requests. We thank the following individuals for contributing
data, publications, or references to incorporate in the literature review: Brian Alford,
James Bulak, Chuck Cichra, Jason Dockendorf, Todd Ewing, Mary Freeman, Bob Greenlee,
Chris Goodreau, Gary Grossman, Paul Johnson, Paul Leonard, Graham Lewis, Scott
Longing, Eric Nagid, Jeff Powell, Jeff Quinn, Bobby Reed, Roger Rulifson, Scott Smith,
Christopher Taylor, Theresa Thom, Jack Webster, and Jerry Ziewitz.
Adams, A.J., R.K. Wolfe, and C.A. Layman. 2009. Preliminary examination of how
human-driven freshwater flow alteration affects trophic ecology of juvenile Snook
(Centropomus undecimalis) in estuarine creeks. Estuaries and Coasts 32:819–828.
Allan, J.D. 1995. Stream Ecology: Structure and Function of Running Waters. Kluwer
Academic Publishers, Boston, MA.
Annear, T., I. Chisholm, H. Beecher, A. Locke, P. Aarrestad, C. Coomer, C. Estes, J.
Hunt, R. Jacobson, G. Jobsis, J. Kauffman, J. Marshall, K. Mayes, G. Smith, R. Wentworth,
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