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The metabolic regimes of flowing waters


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The processes and biomass that characterize any ecosystem are fundamentally constrained by the total amount of energy that is either fixed within or delivered across its boundaries. Ultimately, ecosystems may be understood and classified by their rates of total and net productivity and by the seasonal patterns of photosynthesis and respiration. Such understanding is well developed for terrestrial and lentic ecosystems but our understanding of ecosystem phenology has lagged well behind for rivers. The proliferation of reliable and inexpensive sensors for monitoring dissolved oxygen and carbon dioxide is underpinning a revolution in our understanding of the ecosystem energetics of rivers. Here, we synthesize our current understanding of the drivers and constraints on river metabolism, and set out a research agenda aimed at characterizing, classifying and modeling the current and future metabolic regimes of flowing waters.
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The metabolic regimes of flowing waters
E. S. Bernhardt ,
* J. B. Heffernan ,
N. B. Grimm ,
E. H. Stanley ,
J. W. Harvey ,
M. Arroita,
A. P. Appling,
M. J. Cohen,
W. H. McDowell ,
R. O. Hall, Jr.,
J. S. Read,
B. J. Roberts,
E. G. Stets,
C. B. Yackulic
Department of Biology, Duke University, Durham, North Carolina
Nicholas School of the Environment, Duke University, Durham, North Carolina
Arizona State University, Tempe, Arizona
Center for Limnology, University of Wisconsin, Madison, Wisconsin
National Research Program, U.S. Geological Survey, Reston, Virginia
Department of Plant Biology and Ecology, University of the Basque Country, Bilbao, Spain
Department of Zoology and Physiology, University of Wyoming, Laramie, Wyoming
US Geological Survey, Office of Water Information, Tucson, Arizona
School of Forest Resources and Conservation, University of Florida, Gainesville, Florida
Department of Natural Resources and the Environment, University of New Hampshire, Durham, New Hampshire
U.S. Geological Survey, Office of Water Information, Middleton, Wisconsin
Louisiana Universities Marine Consortium, Chauvin, Louisiana
U.S. Geological Survey, National Research Program, Boulder, Colorado
U.S. Geological Survey, Southwest Biological Science Center, Flagstaff, Arizona
The processes and biomass that characterize any ecosystem are fundamentally constrained by the total
amount of energy that is either fixed within or delivered across its boundaries. Ultimately, ecosystems may
be understood and classified by their rates of total and net productivity and by the seasonal patterns of pho-
tosynthesis and respiration. Such understanding is well developed for terrestrial and lentic ecosystems but
our understanding of ecosystem phenology has lagged well behind for rivers. The proliferation of reliable
and inexpensive sensors for monitoring dissolved oxygen and carbon dioxide is underpinning a revolution
in our understanding of the ecosystem energetics of rivers. Here, we synthesize our current understanding of
the drivers and constraints on river metabolism, and set out a research agenda aimed at characterizing, classi-
fying and modeling the current and future metabolic regimes of flowing waters.
The fuel that powers almost all of Earth’s ecosystems is
created by organisms capable of the alchemy of photosyn-
thesis, in which solar energy, water, and carbon dioxide are
converted into reduced carbon compounds that are then
used to sustain life. We measure this conversion of solar
energy into organic energy as the gross primary productivity
(GPP) of ecosystems. The collective dissipation of this
organic energy through organismal metabolism (of both
autotrophs and heterotrophs) is measured as ecosystem res-
piration (ER). Together, GPP and ER are the fundamental
metabolic rates of ecosystems that constrain the energy sup-
ply and energy dissipation through food chains, and the bal-
ance of these two fluxes, measured as net ecosystem
production (NEP), determines whether carbon accumulates
or is depleted within an ecosystem. Terrestrial ecosystems
often have predictable annual cycles, with both GPP and
NEP typically peaking during warmer and wetter months of
the year. In many well-studied lakes productivity peaks
when warming temperatures, lengthening days, and high
nutrient concentrations occur in concert. The life cycles of
many consumers are likely synchronized to these seasonal
oscillations such that periods of peak energetic demand by
consumers coincide with or follow the peak productivity of
their preferred plant or prey (e.g., Lampert et al. 1986; Berger
et al. 2010). As a result, ecosystem respiration tends to
Present address: Flathead Lake Biological Station, University of Montana,
Polson, Montana
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OCEANOGRAPHY Limnol. Oceanogr. 00, 2017, 00–00
C2017 The Authors Limnology and Oceanography published by Wiley Periodicals, Inc.
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doi: 10.1002/lno.10726
covary with GPP. This phenology of the ecosystem, or its
seasonal timing of carbon, water and energy exchange (sensu
Noormets 2009) is both a cause and a consequence of the
phenology of all component organisms.
The same “cause and consequence of organism
phenology” argument cannot be made for river ecosystems
for three reasons. First, in many rivers seasonal variation in
light is uncorrelated with seasonal variation in temperature,
because of the reduction in light supply due to canopy inter-
ception, sediment loads or colored organic matter. Second,
in many rivers intense and frequent high flow events regu-
larly reduce the biomass of autotrophs (algae, mosses, and
macrophytes) through scouring or burial while stream drying
can strand and desiccate autotrophs on the channel bed.
Finally, most rivers receive energetic subsidies in the form of
detritus and dissolved organic matter from their surrounding
watersheds. These allochthonous inputs can match or exceed
in situ GPP and thus decouple the seasonal and annual pat-
terns of GPP and ER. For each of these reasons we expect a
reduced coherence between climate drivers and river ecosys-
tem productivity and respiration.
Of course, the relative importance of terrestrial shading
and terrestrial organic matter inputs varies with river size
(Vannote et al. 1980). Just as the importance of terrestrial
inputs of nutrients and organic matter to lake food webs
diminishes as the ratio of lake size to watershed size
increases (Tanentzap et al. 2017), we expect that the relative
importance of canopy shading, allochthonous inputs, and
hydrologic disturbance should decline between headwater
streams and large rivers. This gradient in river size impacts
the expected ecosystem phenology, with well-lit and less fre-
quently disturbed large rivers having regular summer pro-
ductivity peaks while shaded headwaters with frequent
flooding are likely to have productivity peaks that are mis-
matched to the terrestrial growing season (Fig. 1). These pre-
dicted longitudinal patterns can be obscured for rivers with
high sediment or colored organic matter inputs. Because the
temporal signals of GPP and ER are so diverse across streams
Fig. 1. Temporal trends in dissolved oxygen (DO shown as % of atmospheric saturation) for four contrasting U.S. rivers over a 4-yr period. High diel
variation in dissolved oxygen is a proxy for high ecosystem GPP. The top trace is from the Menominee River in northern, Wisconsin, a large river with
clear summer peaks and winter lows in stream metabolism. Dissolved oxygen traces for the more southern Five Mile Creek in Alabama and San Anoto-
nio River in Texas show little seasonality, with the smaller Creek having sustained high diel variation in DO and the more urban river having many
alternating periods of high and low diel DO variation. The bottom trace is from Fanno Creek, a heavily shaded and frequently flooded small stream in
western Oregon. Data from each of these four streams appears again (along with axes labels) in Figs. 3, 5. Here, we remove axes scores to focus on
the differences in seasonality of a common signal across streams. The scale of both axes is the same for all four series. [Color figure can be viewed at]
Bernhardt et al.Metabolic regimes
and years, and so often asynchronous with terrestrial pro-
ductivity and climate drivers, we propose that the term meta-
bolic regimes is more appropriate than phenology to describe
these patterns. Here, we define a metabolic regime as the
characteristic temporal pattern of ecosystem GPP and ER
observed for a river.
Despite the frequent mismatches in the timing of peak
energy supply, thermal optima, and disturbance river ecosys-
tems support a tremendous diversity of species (Strayer and
Dudgeon 2010) and can convert enormous quantities of
organic matter and inorganic nutrients into CO
and N
O gases (Cole et al. 2007; Mulholland et al. 2008; Bat-
tin et al. 2009; Raymond et al. 2013; Stanley et al. 2016).
The capacity of rivers to support these critical functions
depends, fundamentally, on ecosystem metabolism, defined
as “the production and destruction of organic matter, and the
associated fluxes of nutrients, through the gross photosynthetic
and respiratory activity of organisms” (Odum 1956). Although
H. T. Odum developed the general concept and made the
first measurements of whole ecosystem metabolism in a river
over 60 yr ago (New Hope Creek, North Carolina, Odum
1956), stream ecologists have made remarkably little progress
in building our empirical understanding of stream metabo-
lism (McDowell 2015).
It is perhaps not surprising, given the extremely dynamic
nature of river metabolism, that we have uncovered no uni-
versal or even regional predictors of river productivity.
Unlike terrestrial ecosystems, where rainfall and temperature
explain much of the global variation in primary production
(Whittaker 1962; Leith 1975; Field et al. 1998), or lentic eco-
systems, in which nutrient loading and organic matter are
primary drivers of productivity (Schindler 1978; Lewis et al.
2011), attempts to uncover these same patterns in streams
have proven elusive (Lamberti and Steinman 1997; Bernot
et al. 2010). Ironically, there is a rich history of conceptual
models predicting spatial patterns of metabolism in streams
and rivers beginning with the River Continuum Concept
(RCC; Fig. 2) (Vannote et al. 1980). Tests of this and other
models have been limited and often equivocal (e.g., Bott
et al. 1985; Minshall et al. 1992; McTammany et al. 2003). A
literature synthesis showed that watershed area (and thus
river size) predicted the magnitude of annual GPP in rela-
tively undisturbed watersheds, but had little predictive
power for GPP in even moderately developed watersheds, or
for ER across all rivers (Finlay 2011). Other syntheses at daily
rather than annual timescales have found even less predict-
ability in metabolic rates (Mulholland et al. 2001; Bernot
et al. 2010; Hoellein et al. 2013).
We attribute our limited success in uncovering patterns or
building predictive models of river ecosystem metabolism to
the challenging combination of technological constraints
and the dynamic physical environment characteristic of
many rivers. In theory, the measurement of river metabolism
is straightforward. An investigator simply measures changes
in the concentration of dissolved oxygen (DO) throughout a
diel (24-h) cycle, using increases during daylight hours and
overnight declines to calculate rates of GPP, ER, and NEP. In
Odum’s initial metabolism estimates (Odum 1956, 1957)
these changes were documented by collecting samples at 2–
4 h intervals throughout a day followed by manual analysis
of DO concentration via titration. Sampling around the
clock by this method is labor intensive, and the duration of
early studies was thus limited to a handful of days during
the year. Later efforts were enabled by instantaneous meas-
urements of DO with first generation environmental sensors.
Because these sensors were expensive and required frequent
calibration, researchers tended to deploy them for very lim-
ited periods of time. As a result, most reported rates of river
ecosystem metabolism were derived from a small number of
measurement days over a year (e.g., 2–12 d; synthesized by
Lamberti and Steinman 1997; Finlay 2011). These brief sam-
pling regimes are biased toward optimum field conditions
for sensor deployment (e.g., sunny days with low flows).
They are thus unlikely to provide accurate estimates of mean
or annual metabolic rates, and are almost certainly insuffi-
cient for capturing the impacts of hydrologic disturbance or
pulsed resource supply.
Fortunately, the proliferation of more rugged and less
expensive environmental sensors is now allowing river scien-
tists to overcome the traditional logistical challenges of mea-
suring metabolism. Looking forward, we should now be able
to address fundamental questions about how river ecosys-
tems function, such as: What controls the variation in
the magnitude and timing of productivity within and
among rivers? How are these controls changing in
response to climate or land use change? How will
resulting changes in river ecosystem productivity con-
strain their capacity to support freshwater biodiver-
sity, food production, and the maintenance of water
quality? In this paper, we hope to help shape and catalyze
this research frontier by summarizing our current under-
standing of river metabolism; proposing a series of new and
fundamental research questions; and providing a series of
examples demonstrating exciting new applications of contin-
uous metabolism datasets.
What do we know so far?
How we measure and model river metabolism
Stream ecosystem metabolism (in units of oxygen, g O
) is estimated from the daily variation in the produc-
tion and consumption of oxygen by stream organisms fol-
lowing a simple model:
dt 5GPP1ER
where dDO
dt is the change in dissolved oxygen concentration
through time, GPP is the rate of photosynthetic O
Bernhardt et al.Metabolic regimes
ER is the rate of oxygen consumption through both autotro-
phic and heterotrophic respiration and KDOsat2DO
is the net
exchange of oxygen between the water column and the overly-
ing air and is governed by a per unit time gas exchange rate K.
Mean river depth (z) converts from volumetric to areal rates. By
convention, any process that lowers DO concentration in the
water takes on a negative value so that ER is always a negative
number. Whenever autotrophs are present, GPP will increase
with light. Typically, GPP results in peak DO during the day
(Fig. 3A), except when high rates of gas exchange or flow varia-
tion obscure this pattern. Variation in the shape of this oxygen
curve reflects variation in rates of GPP, ER, and Kthus, with suf-
ficient rates of GPP, it is possible to use curve fitting routines
to estimate all three parameters from the oxygen data
(Holtgrieve et al. 2010; Hall 2016) available for each day within
a time series.
A first wave of sensor-enabled studies using this model-
ing approach clearly documented that light availability and
Fig. 2. A conceptual model depicting differences in how climate, light and hydrologic regimes vary along the river continuum and between three
terrestrial biomes. The climate diagrams across the top show average monthly precipitation in blue bars with daily air temperatures shown as blue
(minimum) and red (maximum) lines. [Color figure can be viewed at]
Bernhardt et al.Metabolic regimes
flooding are dominant and countervailing drivers of river
ecosystem productivity (Uehlinger and Naegeli 1998;
Houser et al. 2005; Roberts et al. 2007; Izagirre et al. 2008;
Beaulieu et al. 2013; Hope et al. 2014; Huryn et al. 2014;
Roley et al. 2014). In contrast to lakes there is thus far lim-
ited evidence that nutrient availability controls metabolic
rates in rivers (Hoellein et al. 2013; Solomon et al. 2013). In
contrast, variation in stream metabolic rates can affect
nutrient dynamics both within and across rivers (Hall and
Tank 2003; Roberts and Mulholland 2007; Heffernan and
Cohen 2010; Lupon et al. 2016). It thus seems likely that
widespread nutrient pollution of rivers resulting from land
use change is having less of a direct effect on river metabo-
lism than are the often-accompanying reductions in ripar-
ian canopy shading and increases in the frequency and
severity of floods or droughts. Indeed, these alterations to
river light and flow disturbance regimes are likely changing
the potential for rivers to perform the critical ecosystem ser-
vice of nutrient assimilation and retention (Fellows et al.
2006; Mulholland et al. 2008). Those alterations that reduce
annual GPP and ER or which shift the timing of peak activ-
ity away from peak nutrient loading are likely to exacerbate
nutrient pollution by reducing the potential for instream
Fig. 3. Diel and Storm Recovery Patterns in Rivers. Figures in row A are conceptual models representing the typical variation in O
(as % saturation)
at diel (A1, A2) and over storm-recovery trajectories (A3). Figures in row B show three contrasting diel curves selected from each of the four rivers
shown in Fig. 1. In row C, we show 60 d of estimated rates of gross primary productivity (in green, derived from the O
data in Fig. 1) alongside the
river hydrograph (gray shading). Each 60-d period encompasses at least one major flood. The color and date of the triangles shown at the top of pan-
els in row C correspond to the dates for the diel O
curves shown in row B. [Color figure can be viewed at]
Bernhardt et al.Metabolic regimes
The light and thermal regimes of rivers
For terrestrial ecosystems, light and thermal regimes are
controlled by latitude, topography and precipitation pat-
terns, and thus two very basic descriptors of climate, mean
annual temperature and mean annual precipitation, can
explain much of the variation in GPP across terrestrial bio-
mes (Whittaker 1962). Unfortunately, the light and thermal
regimes of streams are less easily linked to these widely avail-
able environmental data. The light that penetrates from the
atmosphere to river surfaces is strongly affected by both
channel orientation with respect to landscape features (e.g.,
canyon walls or banks) and shading by terrestrial vegetation
(Vannote et al. 1980; Hill and Dimick 2002; Julian et al.
2008). For small channels, the phenology of terrestrial vege-
tation can lead to rapid transitions in the light regime dur-
ing the leaf out and litterfall periods that are particularly
pronounced in temperate streams (Hill and Dimick 2002).
Once light reaches the river surface there is a predictable
attenuation with water depth that can be exacerbated by the
reflectivity of suspended materials and light absorption by
dissolved organic matter (Davies-Colley and Smith 2001;
Julian et al. 2008). Light attenuates exponentially with water
depth, such that benthic light availability is highest during
baseflow periods and lowest during high flows. Moreover,
light attenuation tends to increase in the downstream direc-
tion as larger rivers are deeper than their headwaters (Julian
et al. 2008). For all these reasons, light availability varies sub-
stantially among sites as well as over time, well beyond the
latitudinal variation in solar radiation that is the primary
driver of variation in light regime among terrestrial ecosys-
tems. Because of these light filtering mechanisms, periods of
high light availability may not be matched to periods of
high temperature or high incident solar radiation. Indeed,
for many small, forested streams of the temperate zone, the
highest light availability occurs in early spring before the for-
est canopy leafs out and late autumn after litterfall (Roberts
et al. 2007).
Like the light regime, the thermal regime of rivers can
deviate substantially from the temperature of the overlying
atmosphere. The temperature of a river at any given time is
determined by the cumulative fluxes of energy into and out
of the water, including groundwater, evaporation, and sun-
light (Poole and Berman 2001). In general, river tempera-
tures will fluctuate seasonally in concert with air
temperature, but the average temperature and the magnitude
of diel and seasonal swings in temperature will be consider-
ably muted in rivers relative to the overlying atmosphere.
For rivers with significant rates of water and heat exchange
with groundwater, or rivers below dams that receive most of
their flow from reservoir depths there can be little to no cor-
relation between air and water temperatures over time (Poole
and Berman 2001; Olden and Naiman 2009). The resulting
mismatches between temperature and light generate a much
more diverse combination of light and thermal regimes in
river ecosystems relative to their terrestrial or lentic counter-
parts (e.g., Huryn et al. 2014). Ecosystem respiration within
rivers appears to have stronger temperature sensitivity than
GPP, leading some to suggest that rivers are poised to
become increasingly large sources of CO
to the atmosphere
in a warming climate (Demars et al. 2011a,b).
Because terrestrial vegetation both reduces light and
enhances organic matter loading to rivers, we are unlikely to
see strong coherence between the productivity of rivers and
the productivity of their surrounding terrestrial biome.
Indeed, regions of high terrestrial primary productivity (e.g.,
tropical rain forests) are often associated with very low light
availability for small receiving streams (Mulholland et al.
2008), while low productivity terrestrial ecosystems (e.g.,
deserts, tundra) can be drained by some of the most produc-
tive streams in the world (Grimm 1987). Terrestrial vegeta-
tion exerts less influence on the light regimes of larger rivers
in which the attenuation of light by water depth and turbid-
ity become dominant constraints (Vannote et al. 1980). Sim-
ilarly, as rivers increase in size, their thermal regimes
become increasingly insensitive to the stature and status of
surrounding terrestrial vegetation. Thus, the position of any
river segment within its river network is likely to be as
important a determinant of its metabolic regime as the ter-
restrial biome which it drains. The distance along the river
continuum at which terrestrial influence wanes is likely to
vary considerably among different terrestrial biomes (Fig. 2).
For example, riparian canopy cover is typically absent from
the headwaters of desert, grassland, and alpine streams and
seasonal light regimes are considerably different for small
streams draining temperate deciduous vs. tropical or ever-
green forests despite their similar channel widths. These
interactions between geomorphology, vegetation, and chan-
nel size will drive wide variation in both the annual magni-
tude and the timing of primary production and ecosystem
Disturbance regimes in river ecosystems
Though much of what we have learned about annual pat-
terns of river metabolism has come from studies of spring
fed or regulated streams (Odum 1957; Roberts et al. 2007;
Heffernan and Cohen 2010), a minority of rivers have such
predictable flows. The potential for rivers to support high
rates of GPP is maximized in slow flowing, clear water
streams with stable flow and high light availability where
productivity can rival that of temperate forests (Odum 1957;
Heffernan and Cohen 2010; Acu~
na et al. 2011). In contrast,
rivers with frequent bed-moving events typically have signif-
icantly lower productivity, even under similarly high light
regimes (Uehlinger and Naegeli 1998; Uehlinger 2006). A
rapidly growing body of literature documents the overriding
importance of high-flow or desiccation-initiated disturbances
of benthic primary producers in structuring the magnitude
and timing of river ecosystem productivity (Acu~
na et al.
Bernhardt et al.Metabolic regimes
2004, 2005; Atkinson et al. 2008; O’Connor et al. 2012;
Beaulieu et al. 2013).
Floods can regulate spatial and temporal patterns of many
ecological processes in rivers including metabolism (Fig. 3).
The return interval for events that lead to reductions in liv-
ing biomass or organic matter stocks in rivers is much
shorter than for almost any other ecosystem type (Grimm
et al. 2003). In the most extreme cases forests may be har-
vested on decadal time scales and grasslands may burn annu-
ally, but some rivers experience dozens of biomass-reducing
disturbances per year. A large flood can have multiple effects
on primary producers and the macro- and microconsumers
that live on or within riverbed sediments. Floods that are
sufficiently powerful to mobilize bed sediments may lead to
burial, scour or export of benthic producers and organic mat-
ter (Grimm and Fisher 1989; Young and Huryn 1996; Ueh-
linger and Naegeli 1998; Biggs et al. 1999; Uehlinger 2000;
Uehlinger et al. 2002; Atkinson et al. 2008). It is literally true
that “the rolling stone gathers no moss
,” as mobile substrates
are unable to accumulate large and stable amounts of ben-
thic biomass. Even in the absence of physical disturbance of
channel sediments, the deeper and more turbid waters typi-
cal of floods decrease light availability to the channel bed
(Hall et al. 2015). Research to date in small streams suggests
that recovery times for both GPP and ER are expected to be
longer for large floods that exceed the critical threshold for
bed disturbance compared with small floods that mainly
generate turbidity events (Cronin et al. 2007; O’Connor
et al. 2012). It is likely, yet untested, that the mechanism
through which floods impact river productivity may shift in
larger rivers where a greater proportion of GPP may be per-
formed by algae within the water column (Oliver and Mer-
rick 2006). In these larger rivers, we may expect the light
attenuation caused by flood-associated pulses of suspended
sediment that raise turbidity to become the dominant distur-
bance impact rather than bed disturbance.
Low- and no-flow drought conditions are also strong con-
straints on river ecosystem productivity. The most conspicu-
ous effect is obviously the reduction of total habitat area
associated with drying (Stanley et al. 1997). Within the
shrinking wetted channel area, responses to diminishing
flow can be highly variable. In one case, progression of dry-
ing coupled with high light conditions were associated with
growth of floating algae and extremely high rates of produc-
tivity in increasingly isolated pools (Acu~
na et al. 2005).
Under such conditions, dissolved organic carbon can become
highly concentrated. As streambed sediments are desiccated,
primary production ceases in surface sediments and reestab-
lishment may require an extended period of recovery after
rewetting in some ecosystems (e.g., desert streams, Stanley
et al. 1997) or activate immediately in others (Antarctic
streams, McKnight et al. 2007). There has been limited study
to date of the ecosystem respiration rates of dry riverbeds,
but one might expect enhanced mineralization of buried
organic matter as anoxic areas of the sediments are oxygen-
ated during drydown as well as pulses of microbial activity
following rewetting of desiccated sediments (Merbt et al.
2016), analogous to the pulse of mineralization often
observed when rain falls on dry soils (Fierer and Schimel
Nutrient impacts on stream metabolic regimes
When light and disturbance are not limiting, nutrient
supply may limit the magnitude or influence the phenology
of river metabolism (Hill et al. 2009). Common anthropo-
genic impacts on rivers such as the removal of riparian vege-
tation and flow regulation should exacerbate the sensitivity
of metabolism to nutrient loading by reducing light limita-
tion and disturbance frequency as constraints on river eco-
system productivity. There are plentiful examples of nutrient
limitation within individual rivers (Grimm and Fisher 1986;
Francoeur 2001; Tank and Dodds 2003). Experiments to
measure the impact of nutrient loading on river metabolism
have also documented substantial increases in GPP for a river
in Alaska fertilized with phosphorus (Peterson et al. 1985)
and enhanced rates of ER under N 1P enrichment in heavily
shaded, low nutrient streams in North Carolina (Kominoski
et al. 2017). Outside of these experimental studies in well
protected watersheds, we have had limited success in uncov-
ering consistent relationships between nutrient supply and
algal biomass across rivers (Francoeur et al. 1999; Dodds and
Smith 2016). Since nutrient loading from farm or road run-
off and wastewaters is often coincident with changes in
organic matter and sediment loading and changes in distur-
bance regimes, it is perhaps not surprising that differences in
these ultimate constraints (light and disturbance) override
our ability to detect the additional effects of nutrient supply.
Linking river “climate” with river metabolism
Though we know that light, temperature and hydrologic
disturbance (a river’s “climate”) are primary determinants of
metabolic activity in rivers, and that nutrients may acceler-
ate the metabolic response to each of these drivers, we have
only limited information with which to predict how the dis-
tinct temporal dynamics of each driver interact to determine
river metabolic regimes. Because of extensive historic invest-
ments in flow monitoring, we have large amounts of data
available to understand fine scale variation in river flows
(Poff et al. 1997, 2006) and thermal regimes (Olden and
Naiman 2009; Maheu et al. 2016), but we have far less infor-
mation about river light regimes (Hill 1996). We lack empiri-
cal measurements of light availability to the river surface for
all but the largest rivers and a few well studied streams (Hill
and Dimick 2002; Hill et al. 2011). We have even less infor-
mation about the light regimes experienced by the primary
First recorded in 1508 by Erasmus in his collection of Latin prov-
erbs, Adagia.
Bernhardt et al.Metabolic regimes
producers attached to bed sediments or transported in river
flow, and thus we have limited empirical data and few mod-
els with which to estimate light availability to river auto-
trophs (Ochs et al. 2013). Better information on this aspect
of the “climate” of rivers is sorely needed to generate mecha-
nistic models that can predict the metabolic capacity of river
Such model development is essential if we want to better
understand how river ecosystems are being altered by three
major trajectories of change: rising global temperatures; land
use change; and flow regulation (Table 1). Climate change is
leading to rising temperatures and altered hydrographs for
rivers globally (Oki and Kanae 2006; Grimm et al. 2013).
Land use change is increasing sediment loads, nutrient
inputs and flood and drought frequency for at least some
portion of the channel network in every major river basin
(Vorosmarty and Sahagian 2000; Vorosmarty et al. 2000;
Allan 2004). The widespread construction of dams (Lehner
et al. 2011; Zarfl et al. 2014) has fundamentally altered the
flow regimes of many rivers (sensu Poff et al. 1997). The
implications for river ecosystem energetics are difficult to
predict, in part because the direct impacts of these drivers
on river metabolic rates can be antagonistic (higher
nutrients vs. higher disturbance frequency) and because
these direct impacts may be mitigated or enhanced by the
response of riparian vegetation to climate change. Periods of
high light, high nutrients, and stable flow—the “windows of
opportunity” for high metabolic rates within stream ecosys-
tems—seem likely to shift in their timing, duration and mag-
nitude because of these competing drivers of change (e.g.,
Ulseth et al. 2017).
Allochthonous carbon and river metabolism
Further complicating efforts to measure and model river
metabolism is that the energetic basis of many river food
webs is not limited to in situ productivity. Streams with
dense canopies of riparian vegetation, rivers carrying high
particulate loads, and blackwater rivers all can support
diverse and rich food webs and high rates of ecosystem respi-
ration that are dominantly or exclusively supported by car-
bon derived from upslope and upstream ecosystems (Fisher
and Likens 1973; Meyer et al. 1997; Wallace et al. 1997;
Moore et al. 2004). At the other end of the spectrum, rivers
with high water clarity and no canopy shading still receive
subsidies to the autochthonous-based food web in the form
of particulate detritus and dissolved organic matter from the
surrounding watershed. These fixed carbon subsidies are
often delivered to rivers in pulses. These may be regular and
predictable (e.g., annual litterfall or snowmelt fluxes of dis-
solved organic matter); frequent but unpredictable (e.g.,
inputs of large amounts of DOM during floods; Boyer et al.
1997; Raymond and Saiers 2010); or very infrequent cata-
strophic events (e.g., hurricanes, ice storms, fires) that may
Table 1. Changes in global temperatures and land cover will interact with widespread flow regulation to alter the light, thermal
and flow regimes that ultimately shape the metabolic regimes of rivers. Direct effects of these global trends on the drivers of metabo-
lism appear in black boxes while indirect effects appear as regular text.
Bernhardt et al.Metabolic regimes
deliver large quantities of terrestrial organic matter to river
ecosystems (Bernhardt et al. 2003; Earl and Blinn 2003;
Dahm et al. 2015). Floods deliver, bury and remove the
organic matter stored within riverbeds. The extent to which
rivers store or transmit this supply of fixed OM downstream
will determine the degree to which ER is tied to temporal
variation in river productivity. In those river reaches where
large standing stocks of organic matter accumulate, rates of
ER may be decoupled from GPP, and the stored OM can sup-
port significant biological activity in rivers where primary
productivity is negligible (reviewed in Webster and Meyer
1997). Differences between rivers in their capacity to store
OM introduces considerable variation in the extent to which
autochthonous and allochthonous energy sources support
river food webs, as well as the coherence between seasonal
and disturbance recovery patterns of GPP and ER.
Annual patterns of river metabolism
As we amass a new understanding of the annual patterns
of metabolism in rivers, we anticipate that there are likely to
be discrete classes of river ecosystems that share a character-
istic rhythm in the foundational metabolic processes of GPP
and ER (e.g., Fig. 4). These “metabolic regimes” may be char-
acterized by differences in: mean rates and their variability
and skewness; the temporal structure of metabolism such as
the autocorrelation and periodicity of ER and GP; the dura-
tion and timing of metabolic peaks and troughs; the post-
disturbance rates of recovery; and by the variation in these
characteristics among years and decades. These patterns are
likely to be linked to the overlapping temporal patterns of
the many factors that potentially control metabolism, and
thus provide diagnostic information to determine the pri-
mary constraints on metabolism and to predict the likely
energetic consequences of climate change, land use change
or flow management for river ecosystems. Particularly for
river ecosystems that have only short periods of peak metab-
olism, small shifts in the timing or magnitude of resource
supply or of the peak flows, droughts or other events that
constrain or reset metabolic rates may have disproportion-
ately large impacts on river productivity at daily, seasonal,
and annual time scales.
A global effort to measure, model and synthesize metabo-
lism across many river ecosystems will reveal controls on the
rates, timing and sensitivity of freshwater metabolism. Dif-
ferences in metabolic regimes among rivers, and changes in
these regimes over time, are likely to have wide-ranging eco-
logical consequences. Metabolic regimes incorporate not
only the amount of energy available to fuel secondary pro-
duction, but also the temporal pattern of energy availability
that determines which consumers are phenologically best
suited to capitalize on metabolic products. Understanding
ecosystem phenology and what it reveals about coupling
between energetics and element cycling will open new
opportunities to apply our emerging understanding of meta-
bolic regimes as diagnostic tools for river management.
Three frontier opportunities suggest themselves as particu-
larly exciting avenues for progress:
FRONTIER #1 – linking metabolic regimes and
organismal phenology
Ecosystem rates of GPP and ER are maximized at times
when and places where multiple potentially limiting resour-
ces are abundant and the biomass of primary producers is at
its peak. Variation in resource supply and biomass removal
thus drive considerable temporal variation in energy produc-
tion across systems (Fig. 5). The study of the match or mis-
match between an organism’s life history and organic matter
supply has a rich history in stream ecology, where many
consumers are dependent upon relatively discrete and pre-
dictable periods of either autochthonous production (e.g.,
spring algal blooms) or allochthonous organic matter supply
(e.g., autumn litter fall). Disturbances that occur within
these short periods of peak metabolic activity may have dis-
proportionate effects on annual rates of ecosystem metabo-
lism as well as on the productivity and identity of secondary
consumers (Wootton et al. 1996; Power et al. 2008; Spon-
seller et al. 2010). In some rivers, changes in the identity of
secondary consumers associated with intermediate levels of
disturbance can lead to increased production of tertiary and
higher trophic levels even as primary and secondary con-
sumption decline (Power et al. 1996; Cross et al. 2011).
Fig. 4. A conceptual model of four possible and contrasting patterns of annual productivity that could arise for river ecosystems within the same lati-
tude and terrestrial biome. The annual pattern of solar radiation (above any vegetation) is shown in yellow while GPP is shown in green. Maximum
potential GPP is always constrained by incident light. Disturbance and the interception of light by canopy, DOC or sediment each reduce the capacity
for river autotrophs to levels of productivity well below that predicted from light availability alone. [Color figure can be viewed at wileyonlinelibrary.
Bernhardt et al.Metabolic regimes
However, more frequent disturbances have been shown and
are predicted to favor small bodied, fast growing consumers
(Gray 1981; Fisher and Gray 1983). Increased mortality and
longer recovery times of larger predatory animals are pro-
posed explanations for this trend. It is also possible, and
likely, that reductions in the total energy available to con-
sumers because of the removal of autotrophs and organic
matter are in part responsible for these negative effects on
higher trophic levels (as per predictions of the trophic pyra-
mid, Elton 1927).
We suggest that simultaneous measurement and model-
ing of river ecosystem energetics and food web properties
will be needed to predict the likely consequences of climate
and land use change (Table 1) on river biodiversity and food
web structure. Sabo et al. (2010) documented a negative rela-
tionship between flow variability (estimated from 16 to 20 yr
of continuously measured flow data) and food chain length
(FCL) for 20 U.S. rivers. In the same study, the authors con-
cluded that there was no relationship between FCL and rates
of gross primary production (Sabo et al. 2010). Since the GPP
estimates used in the Sabo et al. (2010) synthesis were
derived from only 1 to 20 d of midsummer (low flow) meas-
urements they are likely highly inaccurate estimates of
annual ecosystem productivity. As our measurements of river
metabolism grow more similar in temporal resolution and
longevity to our hydrologic records we predict we will dis-
cover strong, synergistic interactions between flow and meta-
bolic regimes in constraining biodiversity and food web
structure. There is mounting evidence that frequent high
flows significantly constrain river GPP (Uehlinger 2006;
Beaulieu et al. 2013, Fig. 3), and we suggest that the altera-
tions in animal assemblages often attributed to hydrologic
alteration or disturbance (Poff and Ward 1989; Sabo et al.
2009; Poff and Zimmerman 2010) may be due in part to the
indirect effects of these flow alterations on ecosystem metab-
olism. If more comprehensive data support this prediction, it
will only reinforce the importance of maintaining and
restoring natural flow regimes to sustain both the distur-
bance and the energetic regimes that structure river food
Widespread measurement of river ecosystem metabolism
offers a new opportunity to confront this rich conceptual
understanding with large volumes of empirical data describ-
ing the seasonal patterns of energy production and dissipa-
tion in rivers (Fig. 5). Coupling ecosystem metabolism time
series with contemporaneous measurements of benthic sec-
ondary production or food web characteristics is likely to
lead to new insights and re-examination of current assump-
tions. For example, studies of the impacts of altered flow
regimes on the species composition of insect and fish com-
munities often focus on how the life history of declining or
extirpated taxa depended on natural flow regimes (Lytle and
Poff 2004; Lytle et al. 2008). There has been far less consider-
ation of how the direct impacts of flow modification on
Fig. 5. Cumulative annual metabolism graphs for the four rivers from
Fig. 1. GPP is in green, ER is in brown. Units on the yaxis are in g O
Note that the southern river, Five Mile Creek has relatively uniform GPP
while the northern Menominee River has high accumulation only during
the summer months. The San Antonio River in Texas has alternating peri-
ods of high and very low productivity, while Fanno Creek has low GPP
year-round. Rates of ER exceed GPP annually and for most daily time steps
in all four streams. [Color figure can be viewed at]
Bernhardt et al.Metabolic regimes
higher trophic levels may be comfounded by the indirect
effects of flow on metabolism, the energetic base of these
food webs. A cursory look at newly available data from just a
few rivers in the United States (e.g., Fig. 3) demonstrates
that high flows consistently reduce the biomass and cumula-
tive GPP of river autotrophs. It is not just the “green,” or
algal supported food web that is likely to be affected. Many
river biota consume detritus delivered from the surrounding
terrestrial ecosystem, with the growth and diversity of shred-
ders and detritivores strongly tied to the standing stocks of
leaf litter in small streams (Wallace et al. 1997, 1999). In soil
and sediment food webs, heterotrophs rely on slow turnover
of massive standing stocks of organic carbon—but in streams
and rivers this “brown food web” is far more temporally
dynamic due to events that can export, bury or fragment
benthic organic matter standing stocks (Wallace et al. 1995).
Thus, shifts in the timing of OM supply (via changes in ter-
restrial phenology) and removal or burial (via changes in
storm magnitudes or timing) may have important implica-
tions for the wide variety of shredders and collectors that
rely on these allochthonous carbon sources. The lost produc-
tion that results from increasingly frequent or severe flows
will certainly outlast the impact of the physical disturbance
and, in some systems, may substantially alter the commu-
nity of secondary consumers, with additional effects at
higher trophic levels. Shifts in peak and total annual produc-
tivity resulting from global change drivers (Table 1) are likely
to have important implications for the biomass and diversity
of aquatic consumers that can be supported within a river,
while shifts in the timing of peak productivity (Table 1) may
favor new types of animals at the expense of historically
dominant taxa.
FRONTIER #2 - coupling energetics and element
In rivers, indeed in all ecosystems, cycling of nutrients
and other elements can both depend on and influence meta-
bolic patterns, and these reciprocal interactions operate over
a wide range of time scales, within days, across seasons and
through recovery from antecedent disturbances (Kirchner
et al. 2004; Appling and Heffernan 2014). There is a rich his-
tory of stream ecological research that has documented
strong links between metabolic phenology and the timing
and magnitude of nutrient retention (Meyer 1980; Mulhol-
land et al. 1985; Meyer et al. 1998; Roberts and Mulholland
2007). The emerging transition of stream metabolism studies
from daily rates to annual regimes is part of a much wider
effort to document and draw inference from hydrochemical
patterns across the full span of relevant time scales, from
days and storm events to seasons and decades (Kirchner
et al. 2004). These efforts are greatly enabled by new tech-
nologies and approaches that can measure a rapidly
expanding portfolio of constituents continuously over long
time periods (Porter et al. 2012; Pellerin et al. 2016).
Diel oscillations in a wide range of solutes are common in
rivers and are linked to metabolism by both direct and indi-
rect mechanisms (Nimick et al. 2011; Hensley and Cohen
2016). By quantifying variation in diel oscillations over time,
recent empirical studies have demonstrated close coupling
between instantaneous rates of metabolism and the assimila-
tion of dissolved nutrients (e.g., Heffernan and Cohen 2010;
Rode et al. 2016). While links between metabolism and
nutrient cycling are also observed across rivers (e.g., Hall and
Tank 2003), high-frequency continuous monitoring can illu-
minate relationships between metabolic processes and
longer-term changes in material export. For example, in a
Tennessee stream, daily GPP can drive variation in both diel
3oscillations and total uptake (Roberts and Mulholland
2007) (Fig. 6); similarly, interannual variation in springtime
GPP due to storm frequency and timing accounts for much
of interannual variation in watershed nutrient export (Lutz
et al. 2012) (Fig. 6).
Joint high-frequency measurements of oxygen and other
solutes can also illuminate the cascade of interactions
between metabolism and other biogeochemical processes. In
a spring-fed Florida River, variation in metabolism drives diel
and seasonal variation in NO2
3uptake, and also directly
affects day-to-day variation in denitrification, which
accounts for the majority of riverine NO2
3removal (Hef-
fernan and Cohen 2010). In the same system, metabolism
affects diel variation in PO32
4concentrations, both directly
through assimilatory uptake and indirectly via effects of pH
on calcite saturation (de Montety et al. 2011; Cohen et al.
Riverine metabolism is obviously not the only potential
cause of fine-scale variation in river chemistry; indeed, many
such patterns reflect hydrologic and anthropogenic processes
occurring in hillslopes, riparian zones, and upstream within
river networks (Kirchner et al. 2001; Harvey 2016). For exam-
ple, daily variation in evapotranspiration rates of catchment
vegetation can drive diel variation in streamflow and thus
the relative contribution of groundwater and shallow subsur-
face flowpaths, a mechanism that can drive diel variation in
stream solute concentrations even in the absence of high
rates of instream nutrient assimilation. Assimilation and
transformation processes well upstream of a sampling loca-
tion can result in temporal variation in solute concentra-
tions which are inconsistent in their timing or magnitude
with local control by in-stream processes (Pellerin et al.
2009, 2014). Relatively few studies have attempted to disen-
tangle hydrologic and biotic drivers of diel nutrient variation
using direct measurements of both processes (but see Aubert
and Breuer 2016; Lupon et al. 2016).
Although nutrients do not appear to drive major differ-
ences in metabolism across rivers, it is likely that nutrients
do limit metabolism in rivers where nutrient supply is low,
Bernhardt et al.Metabolic regimes
light is abundant and disturbance is infrequent. It has
been suggested that continuous daily estimates of nutrient
concentrations could provide strong direct evidence for
nutrient dependence of metabolism (Hall 2016). At still
finer scales of diel variation, theoretical models predict
that the magnitude of diel variation, relative to autotro-
phic demand, may depend on whether nutrients are avail-
able in sufficient supply (Appling and Heffernan 2014).
High-resolution sensors are particularly valuable for testing
such links between organismal physiology and ecosystem
Taking full advantage of the growing capabilities of in
situ sensors will require ongoing methodological and theo-
retical advances (Pellerin et al. 2016; Rode et al. 2016).
Within rivers, the physical dynamics of transport are likely
to affect covariation of solutes in ways that may both mask
and influence biogeochemical processes. As one example,
the footprint of processes that involve dissolved gases is
likely to differ from those that lack gas phase reactants and
products (Hensley and Cohen 2016). Similar challenges may
arise in linking and disentangling processes that act at very
different rates or in opposition (e.g., nitrification vs.
Fig. 6. Data collected from Walker Branch watershed in Oak Ridge Tennessee (Roberts and Mulholland 2007; Roberts et al. 2007; Lutz et al. 2012).
Upper panels during periods of the year with high GPP, diel increases in dissolved oxygen are linked to diel declines in stream nitrate concentrations
while nitrate concentrations are constant (and elevated) during summer months when the forest canopy is closed. Middle panels: Seasonal variation
in GPP explains the low stream nitrate concentrations during spring and fall. Lower panels: Years with larger spring algal blooms (e.g., 2005) have
greater total annual instream nitrogen uptake than years in which spring storms reduce the longevity and peak productivity of spring algae (e.g.,
2006). [Color figure can be viewed at]
Bernhardt et al.Metabolic regimes
denitrification) within different habitat compartments (Hel-
ton et al. 2012; Gomez-Velez and Harvey 2014). Experimen-
tal approaches that take advantage of sensor capabilities may
help provide estimates of whole system and compartment-
specific biogeochemical processes.
One clear need is the further development of integrative,
ecosystem-level models that link metabolic, biogeochemical,
and hydrologic processes within rivers. Widely used chemi-
cal loading models (i.e., Sparrow, HYDRA) couple dynamic
hydrology with static assumptions about element processing
within rivers. At present, river science lacks the portfolio of
theoretical and modeling approaches akin to those devel-
oped by terrestrial biogeochemists and ecologists (e.g., CEN-
TURY, Biome-BGC, P-NET) that allow for dynamic, non-
equilibrium modeling of ecosystem and biogeochemical pro-
cesses. Because rivers provide opportunities to observe meta-
bolic and biogeochemical processes over comparable time
scales, novel river ecosystem models offer the potential to
develop and test more general theory of the interactions
among element cycles and energy flow in ecological systems.
Frontier #3 - river metabolism for diagnosis and
Basal metabolism constrains the “work” that ecosystems
can do and we can measure this process for an entire ecosys-
tem just as we do for an organism through monitoring its
exchange of O
or CO
with the atmosphere. Many govern-
ment agencies monitor dissolved oxygen in freshwater eco-
systems to avoid or regulate low oxygen events. At no
additional costs, these same data can be repurposed to pro-
vide real time, continuous measures of ecosystem function.
To take advantage of this new information, we need new
diagnostic tools that are easy to explain and interpret. We
propose the metabolic fingerprint as one such diagnostic
tool and framework for hypothesis testing (Fig. 7). The meta-
bolic fingerprint can be represented as the entire distribution
of daily estimates of GPP and ER that are observed for a
river, or the summary of those data into kernel density plots
that allow easy visualization of both peak and median meta-
bolic rates as well as variance in their ratio (Fig. 7). In Fig. 7,
we show an explanatory cartoon of the fingerprint graph
alongside the “fingerprints” of the four rivers presented pre-
viously in Figs. 1, 3. The highly productive Menominee River
in Wisconsin occupies a much larger volume of metabolic
space than does the very frequently flooded Fanno Creek in
Oregon. We hypothesize that higher light and nutrient sup-
plies will expand both the total area and the maximal rates
represented by a river’s fingerprint, while hydrologic distur-
bance and sediment loading will constrain the metabolic fin-
gerprint to values near the origins of both the GPP and ER
axes. We suspect that as we gain annual metabolism data
from an increasing number of rivers we will discover recog-
nizable clusters of river metabolic regimes. As we develop
our mechanistic understanding of how river metabolic
regimes are established, maintained and disrupted, we will
become better able to determine how river metabolic
regimes are being altered by pollution, flow regulation or cli-
mate change as well as how effective mitigation, restoration,
and preservation efforts are at returning rivers toward more
natural metabolic regimes.
In addition to comparing fingerprints across streams,
these same visualization tools can be used to compare across
Fig. 7. The metabolic fingerprint is a diagnostic tool for comparing annual patterns of metabolism across rivers or across years for the same river.
Panel A shows the metabolic fingerprint for 2014 GPP and ER estimates for each of the four streams shown in Fig. 1. The “fingerprint” is represented
as a kernel density plot of all daily estimates of GPP and ER rates observed within each stream. The area of a river’s fingerprint (its variation along
both the 1 : 1 line and ER axis) should be compressed by hydrologic disturbances and expanded by the supply of either solar energy of fixed carbon.
Bernhardt et al.Metabolic regimes
years or among sites within the same river to examine the
effects of infrastructure or restoration efforts, land use
change, or hydrologic extremes. For example, the metabolic
fingerprint of the Oria River in the northern Spain changed
in response to the implementation of a wastewater treatment
plant (WWTP) (Fig. 8). The Oria River drains a basin of
882 km
with 126,000 inhabitants in which industries had
previously diverted their wastewater directly to the river.
Historic water quality data collected by the monitoring sta-
tion located in the upper basin (333 km
) revealed that
untreated sewage directly coming from houses and industries
carried large amounts of both inorganic and organic pollu-
tants, elevating ammonium in the river to concentrations as
highs as 2.5 mgL
. High loads of organic matter resulted in
very high rates of stream ER that were not accompanied by
similarly high rates of GPP. Although hyperoxic conditions
(saturation 150%) were common during the day due to the
high rates of GPP, even higher ER rates derived from organic
pollution frequently resulted in hypoxia at night (satu-
ration <40%). In 2003, a WWTP was put into operation
approximately 8 km upstream from the water quality moni-
toring station, and now treats the domestic sewage of 60,000
inhabitants as well as industrial sewage. The amount of inor-
ganic and organic pollutants entering the river subsequently
declined, with average ammonium concentrations falling to
0.18 mgL
. This improvement in water quality resulted in
reduced rates of both GPP and ER, significantly changing the
distribution of metabolic rates—the “metabolic finger-
print”—of the Oria River (Fig. 8). Daily amplitudes of dis-
solved oxygen greatly decreased due to the reduced
metabolic rates with oxygen saturation now consistently
between 80% and 120%, resulting in greatly improved con-
ditions for river biota. This case study shows just one exam-
ple of how the metabolic “fingerprint” can serve as both a
sensitive detector and a clear outreach tool to describe eco-
system functional responses to intervention.
Concluding remarks
Syntheses of daily metabolism measurements from across
different rivers have revealed enormous variability and had
limited success in explaining this variance. We suggest that
estimating GPP and ER for one or a few days provides little
information about the energetics of most rivers where fre-
quent disturbance and highly variable light regimes lead to
high temporal variation in GPP and ER rates. By examining
the patterns of metabolism over entire years, we can observe
how the extrinsic controls of light, heat, allochthonous
inputs, and disturbance together shape metabolism, and we
can begin to understand and predict how these drivers have
changed and are likely to change because of widespread flow
regulation, climate change, land use, and eutrophication.
Land use and climate change are altering the light, ther-
mal and disturbance regimes of rivers at both local and
Fig. 8. Two photos of the Oria River and its metabolic fingerprint before (black) and after (green) the construction of a wastewater treatment plant.
Photo credits to M. Arroita and A. Elosegi. [Color figure can be viewed at]
Bernhardt et al.Metabolic regimes
global scales. Climate change has already shifted the timing,
magnitude and frequency of flooding events in rivers
throughout the world (Milly et al. 2002, 2005; Oki and
Kanae 2006). Even in the absence of directional climate
change, hydropower and water supply dams are leading to
major shifts in the hydrologic regimes of most the world’s
rivers (Poff and Zimmerman 2010; V
osmarty et al. 2010);
while the frequency and magnitude of peak flows in smaller
streams have been increased by urbanization’s spreading
influence (Paul and Meyer 2001; Walsh et al. 2005). All
forms of land use change tend to generate increased turbid-
ity events and accelerated bed and bank erosion (Leopold
et al. 1964). Approaches to manage the stressors and protect
ecosystem services of rivers are in their infancy, and we sug-
gest that effective river conservation and management
requires that we devote as much attention to the metabolic
regimes of rivers as we have already invested in understand-
ing river flow regimes.
Fortunately, we now have the technical and logistical
capacity to measure dissolved gas and solute fluxes and
model ecosystem metabolism at the same highly resolved
time steps at which streamflow has historically been mea-
sured. If we can match these technological innovations with
equally innovative theoretical breakthroughs we will enable
river ecosystem science to link energetics and element cycles
at the time scales at which: organisms assimilate elements
(seconds to hours to days); disturbance initiates succession
(weeks to months); and terrestrial and aquatic element cycles
are linked (from hours to seasons). The emergent research
will generate novel and sophisticated understanding of the
multi-scale controls of stream metabolism, facilitating the
transition from short-term, reach-scale studies toward annu-
alized, scalable models of freshwater ecosystem energetics. In
turn, these models will enable sophisticated predictions
about how river food webs, biodiversity, and nutrient proc-
essing capacity are likely to change under realistic scenarios
of climate and land use change.
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We wish to thank fellow river metabolism enthusiasts Tom Battin,
Joanna Blaszczak, Natalie Griffiths, Ashley Helton, Brian McGlynn, Eliza-
beth Sudduth, Phil Savoy, and Amber Ulseth for the many productive
conversations on these topics that have helped refine the ideas pre-
sented here. The ideas discussed here have resulted from collaborations
among the authors that have been enabled by working group funds
through the USGS Powell Center Synthesis Center and the NSF Macro-
systems Program (Grant # EF 1442439). Individual participants have
been supported by postdoctoral funding from the Basque Government
(to M. Arroita) and a Humboldt Foundation Sabbatical Fellowship (to E.
Conflict of Interest
None declared.
Submitted 18 May 2017
Revised 29 August 2017
Accepted 14 September 2017
Associate editor: Ryan Sponseller
Bernhardt et al.Metabolic regimes
... DO concentrations often plummet as respiration increases 16 . Riparian canopy shading, terrestrial organic matter inputs and hydrological disturbance (for example, droughts and floods) often exert large impacts in loworder streams; their influences often decline in large, wide and deep rivers 17,18 . Changes in the aquatic food web (for example, species invasions) could also influence DO by changing respiration via altered zooplankton and phytoplankton biomass 19 . ...
... Riverine DO concentrations are therefore commonly perceived as hinging upon thermal, light and flow regimes 13,14,17 . Their continentalscale drivers across gradients of climate, vegetation and land-use conditions however have remained poorly understood. ...
... It echoes the theory of oxygen solubility that temperature is a major driver 32 . It is, however, counter-intuitive, because riverine DO dynamics are known to be complex and depend not only on physics and chemistry, but on an array of biological activities in rivers that are regulated comparably by thermal, light and flow regimes 17 . DO solubility drops as temperature increases, whereas photosynthesis and respiration tend to rise with temperature. ...
Riverine dissolved oxygen (DO) is thought as comparably driven by light, temperature (T) + flow, although its continental-scale drivers remain elusive. Here a Long-Short Term Memory model reveals T as the predominant driver of daily DO in CONUS.
... 179 New opportunities for developing pattern detection and modeling approaches for high-frequency data sets could potentially utilize freely available software, where models are provided as services such as the Mobius model builder, 180 the Cloud Services Innovation Platform, 181 and the streamPULSE platform. 26 The Mobius model builder is a freely available tool using a modular approach which implements water quality models such as the INCA and Simply models. 182 The Cloud Services Innovation Platform is a web interface compatible with a variety of models, requiring no in-house maintenance and with adequate data security tools. ...
... The streamPULSE platform facilitates stream metabolism modeling through providing consistent approaches to sensor data collection and protocols for data quality assurance and control and stream metabolism modeling. 26 Additionally, several freely available toolboxes designed to analyze high-frequency water data have been released in the past years, including the R packages oddwater developed to detect outliers in WQ data from in situ sensors, 183 waterData which calculates and plots anomalies, ensemble hydrograph separation scripts, 175 and EndSplit for end-member splitting analysis 184 and Python packages AbspectroscoPY to analyze UV−vis sensor data 185 and pyhydroqc for automating detection and correction of anomalies in sensor data. 169 ...
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High-frequency water quality measurements in streams and rivers have expanded in scope and sophistication during the last two decades. Existing technology allows in situ automated measurements of water quality constituents, including both solutes and particulates, at unprecedented frequencies from seconds to subdaily sampling intervals. This detailed chemical information can be combined with measurements of hydrological and biogeochemical processes, bringing new insights into the sources, transport pathways, and transformation processes of solutes and particulates in complex catchments and along the aquatic continuum. Here, we summarize established and emerging high-frequency water quality technologies, outline key high-frequency hydrochemical data sets, and review scientific advances in key focus areas enabled by the rapid development of high-frequency water quality measurements in streams and rivers. Finally, we discuss future directions and challenges for using high-frequency water quality measurements to bridge scientific and management gaps by promoting a holistic understanding of freshwater systems and catchment status, health, and function.
... One of the biggest challenges faced by hydrologists and stream ecologists lies in the attempt to integrate and resolve ecosystem dynamics at the scale of entire river networks. The advent of affordable sensors has boosted the availability of reach-scale time series of GPP and ER estimated from dissolved oxygen (DO) time series (Appling et al., 2018;Beaulieu et al., 2013;Diamond et al., 2021;Hall & Beaulieu, 2013), greatly advancing our understanding of drivers of local stream metabolism (e.g., Bernhardt et al., 2018;Segatto et al., 2020;Ulseth et al., 2018). However, few studies have so far attempted to upscale GPP and ER from stream reaches to an entire river network (see Rodríguez-Castillo et al. [2019] for the spatial distribution of metabolic metrics and Segatto et al. [2021] for network-scale ecosystem regimes both in space and time). ...
... . This general pattern is in line with earlier predictions on stream ecosystem metabolism (Fisher & Likens, 1973;Hotchkiss et al., 2015;Vannote et al., 1980) and studies compiling data from a wide suite of stream ecosystems (Battin et al., 2008;Bernhardt et al., 2018;Bertuzzo et al., 2022;Diamond et al., 2021;Hoellein et al., 2013). ...
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Climate change and the predicted warmer temperatures and more extreme hydrological regimes could affect freshwater ecosystems and their energy pathways. To appreciate the complex spatial and temporal interactions of carbon cycling in flowing waters, ecosystem metabolism (gross primary production [GPP] and ecosystem respiration [ER]) must be resolved at the scale of an entire river network. Here, we propose a meta‐ecosystem framework that couples light and temperature regimes with a reach‐scale ecosystem model and integrates network structure, catchment land cover, and the hydrologic regime. The model simulates the distributed functioning of dissolved and particulate organic carbon, autotrophic biomass, and thus ecosystem metabolism, and reproduces fairly well the metabolic regimes observed in 12 reaches of the Ybbs River network, Austria. Results show that the annual network–scale metabolism was heterotrophic, yet with a clear peak of autotrophy in spring. Autochthonous energy sources contributed 43% of the total ER. We further investigated the effect of altered thermal and hydrologic regimes on metabolism and ecosystem efficiency. We predicted that an increase of 2.5°C in average stream water temperature could boost ER and GPP by 31% (24%–57%) and 28% (5%–57%), respectively. The effect of flashier hydrologic regimes is more complex and depends on autotrophic biomass density. The analysis shows the complex interactions between environmental conditions and biota in shaping stream metabolism and highlights the existing knowledge gaps for reliable predictions of the effects of climate change in these ecosystems.
... (a) A conceptual model presented inBernhardt et al., (2018) depicting how climate, light and hydrologic regimes vary along the river continuum and between three terrestrial biomes.Bernhardt et al., (2018) hypothesized that the combination of variable light and flow regimes given landscape context (such as biome and network position) would control the timing and magnitude of stream metabolism. The climate diagrams across the top show average monthly precipitation in blue bars with daily air temperatures as blue (minimum) and red (maximum) lines. ...
... (a) A conceptual model presented inBernhardt et al., (2018) depicting how climate, light and hydrologic regimes vary along the river continuum and between three terrestrial biomes.Bernhardt et al., (2018) hypothesized that the combination of variable light and flow regimes given landscape context (such as biome and network position) would control the timing and magnitude of stream metabolism. The climate diagrams across the top show average monthly precipitation in blue bars with daily air temperatures as blue (minimum) and red (maximum) ...
... The study of biotic aspects of water resources across the terrestrialaquatic interface is one of the major thrusts in the rapidly growing field of biogeosciences (Richter et al., 2018). Considering the interplay among climate, recent volcanism, extremely rich soil carbon stores, and complex topography in páramo regions, it is important to assess how metabolic regimes and biogeochemical processes influence the system's water and nutrient cycles (Bernhardt et al., 2018). Here, we summarize the limited biogeochemical knowledge across the terrestrial-aquatic interface in páramo. ...
Interdisciplinary knowledge is necessary to achieve sustainable management of natural resources. However, research is still often developed in an exclusively disciplinary manner, hampering the capacity to holistically address environmental issues. This study focuses on páramo, a group of high-elevation ecosystems situated around ∼3000 to ∼5000 m a.s.l. in the Andes from western Venezuela and northern Colombia through Ecuador down to northern Peru, and in the highlands of Panama and Costa Rica in Central America. Páramo is a social-ecological system that has been inhabited and shaped by human activity since ∼10,000 years BP. This system is highly valued for the water-related ecosystem services provided to millions of people because it forms the headwaters of major rivers in the Andean-Amazon region, including the Amazon River. We present a multidisciplinary assessment of peer-reviewed research on the abiotic (physical and chemical), biotic (ecological and ecophysiological), and social-political aspects and elements of páramo water resources. A total of 147 publications were evaluated through a systematic literature review process. We found that thematically 58, 19, and 23 % of the analyzed studies are related to the abiotic, biotic, and social-political aspects of páramo water resources, respectively. Geographically, most publications were developed in Ecuador (71 % of the synthesized publications). From 2010 onwards, the understanding of hydrological processes including precipitation and fog dynamics, evapotranspiration, soil water transport, and runoff generation improved, particularly for the humid páramo of southern Ecuador. Investigations on the chemical quality of water generated by páramo are rare, providing little empirical support to the widespread belief that páramo environments generate water of high quality. Most ecological studies examined the coupling between páramo terrestrial and aquatic environments, but few directly assessed in-stream metabolic and nutrient cycling processes. Studies focused on the connection between ecophysiological and ecohydrological processes influencing páramo water balance are still scarce and mainly related to the dominant vegetation in the Andean páramo, i.e., tussock grass (pajonal). Social-political studies addressed water governance and the implementation and significance of water funds and payment for hydrological services. Studies directly addressing water use, access, and governance in páramo communities remain limited. Importantly, we found only a few interdisciplinary studies combining methodologies from at least two disciplines of different nature despite their value in supporting decision-making. We expect this multidisciplinary synthesis to become a milestone to foster interdisciplinary and transdisciplinary dialogue among individuals and entities involved in and committed to the sustainable management of páramo natural resources. Finally, we also highlight key frontiers in páramo water resources research, which in our view need to be addressed in the coming years/decades to achieve this goal.
... Headwater streams play a pivotal role in the biogeochemical functioning of river networks and regulate key ecosystem services associated to fluvial environments Bernhardt et al., 2018). Furthermore, mountain streams not only transport matter and chemicals from the uplands to downstream water bodies, but are also able to exchange gaseous compounds with the overlying atmosphere (Butman and Raymond, 2011;Battin et al., 2009). ...
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Headwater streams are important sources of greenhouse gases to the atmosphere. The magnitude of gas emissions originating from such streams, however, is modulated by the characteristic microtopography of the river bed, which might promote the spatial heterogeneity of turbulence and air entrainment. In particular, recent studies have revealed that step-and-pools, usually found in close sequences along mountain streams, are important hotspots of gas evasion. Yet, the mechanisms that drive gas transfer at the water-air interface in a step and pool configuration are not fully understood. Here, we numerically simulated the hydrodynamics of an artificial step-and-pool configuration to evaluate the contribution of turbulence and air entrainment to the total gas evasion induced by the falling jet. The simulation was validated using observed hydraulic features (stage, velocity) and was then utilized to determine the patterns of energy dissipation, turbulence-induced gas exchange, and bubble-mediated transport. The results show that gas evasion is led by bubble entrainment and is mostly concentrated in a small and irregular region of a few dm2 near the cascade, where the local gas transfer velocity, k, peaks at 500 md−1. The enhanced spatial heterogeneity of k in the pool does not allow one to define a priori the region of the domain where the outgassing takes place, and makes the value of the spatial mean of k inevitably scale-dependent. Accordingly, we propose that the average mass transfer velocity could not be a meaningful metric to describe the outgassing in spatially heterogeneous flow fields, such as encountered in step-and-pool rivers.
... These results are consistent with another meta study (Seybold et al., 2022) that found disproportionate nitrate exports linked to winter events, thus surges and crashes of DIN can lead to punctuated drops in C:N albeit to general increases in these ratios at the annual scale. Together, the evolving C:N ratio and shifts in the total N pool in streams will likely have implications for stream metabolism and biogeochemical reaction rates that are difficult to predict (Wymore et al., 2015;Bernhardt et al., 2018;Rodríguez-Cardona et al., 2022). ...
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The concurrent reduction in acid deposition and increase in precipitation impact stream solute dynamics in complex ways that make predictions of future water quality difficult. To understand how changes in acid deposition and precipitation have influenced dissolved organic carbon (DOC) and nitrogen (N) loading to streams, we investigated trends from 1991 to 2018 in stream concentrations (DOC, ~3,800 measurements), dissolved organic nitrogen (DON, ~1,160 measurements), and dissolved inorganic N (DIN, ~2,130 measurements) in a forested watershed in Vermont, USA. Our analysis included concentration-discharge (C-Q) relationships and Seasonal Mann-Kendall tests on long-term, flow-adjusted concentrations. To understand whether hydrologic flushing and changes in acid deposition influenced long-term patterns by liberating DOC and dissolved N from watershed soils, we measured their concentrations in the leachate of 108 topsoil cores of 5 cm diameter that we flushed with solutions simulating high and low acid deposition during four different seasons. Our results indicate that DOC and DON often co-varied in both the long-term stream dataset and the soil core experiment. Additionally, leachate from winter soil cores produced especially high concentrations of all three solutes. This seasonal signal was consistent with C-Q relation showing that organic materials (e.g., DOC and DON), which accumulate during winter, are flushed into streams during spring snowmelt. Acid deposition had opposite effects on DOC and DON compared to DIN in the soil core experiment. Low acid deposition solutions, which mimic present day precipitation, produced the highest DOC and DON leachate concentrations. Conversely, high acid deposition solutions generally produced the highest DIN leachate concentrations. These results are consistent with the increasing trend in stream DOC concentrations and generally decreasing trend in stream DIN we observed in the long-term data. These results suggest that the impact of acid deposition on the liberation of soil carbon (C) and N differed for DOC and DON vs. DIN, and these impacts were reflected in long-term stream chemistry patterns. As watersheds continue to recover from acid deposition, stream C:N ratios will likely continue to increase, with important consequences for stream metabolism and biogeochemical processes.
Streams and rivers play an important role in the global carbon cycle. The origins of CO2 in streams are often poorly constrained or neglected, which is especially true for CO2 originating from heterotrophic metabolism in streambeds. We hypothesized that sediment movement will have a direct effect on stream metabolism, and thus, the aim of this study was to quantify the effect of moving bedforms on the production of CO2 in sandy streambeds. We conducted flume experiments where we used planar optodes to measure the distributions of O2 and CO2 under various streambed celerities. We combined these measurements with an assessment of bed morphodynamics and modeling to calculate O2 consumption and CO2 production rates. Our results indicate that sediment transport can strongly influence streambed metabolism and CO2 production. We found that bedform celerity controls the shape of the hyporheic zone and exchange flux, and is directly linked to the spatial and temporal distributions of O2 and CO2. It was also found that the most pronounced change in CO2 production occurred when the bed changed from stationary conditions to a slowly moving bed. A more gradual increase in O2 consumption and CO2 production rates was observed with further increase in celerity. Our study also points out that bedform movement causes hydraulic isolation between the moving and the non‐moving fraction of the streambed that can lead to a transient storage of CO2 in deeper sediments, which may be released in bursts during bed scour.
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Whole‐stream metabolism characterizes energy and carbon transformations, thus providing an estimate of the food base and CO2 emission sources from streams and rivers. Metabolism models are generally implemented with a steady flow assumption that does not hold true for many systems with sub‐daily flow variation, such as river sections downstream of dams. The steady flow assumption has confined metabolism estimation to a limited range of river environments, thus limiting our understanding about the influence of hydrology on biological production in rivers. Therefore, we couple a flow routing model with the two‐station stream metabolism model to estimate metabolism under unsteady flow conditions in rivers. The model's applicability is further extended by including advection‐dispersion processes to facilitate metabolism estimation in transient storage zones. Metabolism is estimated using two approaches: (a) an accounting approach similar to the conventional two‐station method and (b) an inverse approach that estimates metabolism parameters using least squares minimization method. Both approaches are complementary since we use outputs of the accounting approach to constrain the inverse model parameters. The model application is demonstrated using a case study of an 11 km long stretch downstream of a hydropower plant in the River Otra in southern Norway. We present and test different formulations of the model to show that users can make an appropriate selection that best represents hydrology and solute transport mechanism in the river system of interest. The inclusion of unsteady flows and transient storage zones in the model unlocks new possibilities for studying metabolism controls in altered river ecosystems.
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Although stream ecosystems are recognized as an important component of the global carbon cycle, the impacts of climate-induced hydrological extremes on carbon fluxes in stream networks remain unclear. Using continuous measurements of ecosystem metabolism, we report on the effects of changes in snowmelt hydrology during the anomalously warm winter 2013/2014 on gross primary production (GPP), ecosystem respiration (ER), and net ecosystem production (NEP) in an Alpine stream network. We estimated ecosystem metabolism across 12 study reaches of the 254 km² subalpine Ybbs River Network (YRN), Austria, for 18 months. During spring snowmelt, GPP peaked in 10 of our 12 study reaches, which appeared to be driven by PAR and catchment area. In contrast, the winter precipitation shift from snow to rain following the low-snow winter in 2013/2014 increased spring ER in upper elevation catchments, causing spring NEP to shift from autotrophy to heterotrophy. Our findings suggest that the YRN transitioned from a transient sink to a source of carbon dioxide (CO2) in spring as snowmelt hydrology differed following the high-snow versus low-snow winter. This shift toward increased heterotrophy during spring snowmelt following a warm winter has potential consequences for annual ecosystem metabolism, as spring GPP contributed on average 33% to annual GPP fluxes compared to spring ER, which averaged 21% of annual ER fluxes. We propose that Alpine headwaters will emit more within-stream respiratory CO2 to the atmosphere while providing less autochthonous organic energy to downstream ecosystems as the climate gets warmer.
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Widespread evidence that organic matter exported from terrestrial into aquatic ecosystems supports recipient food webs remains controversial. A pressing question is not only whether high terrestrial support is possible but also what the general conditions are under which it arises. We assemble the largest data set, to date, of the isotopic composition (δ2H, δ13C, and δ15N) of lake zooplankton and the resources at the base of their associated food webs. In total, our data set spans 559 observations across 147 lakes from the boreal to subtropics. By predicting terrestrial resource support from within-lake and catchment-level characteristics, we found that half of all consumer observations that is, the median were composed of at least 42% terrestrially derived material. In general, terrestrial support of zooplankton was greatest in lakes with large physical and hydrological connections to catchments that were rich in aboveground and belowground organic matter. However, some consumers responded less strongly to terrestrial resources where within-lake production was elevated. Our study shows that multiple mechanisms drive widespread cross-ecosystem support of aquatic consumers across Northern Hemisphere lakes and suggests that changes in terrestrial landscapes will influence ecosystem processes well beyond their boundaries.
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Water availability on the continents is important for human health, economic activity, ecosystem function and geophysical processes. Because the saturation vapour pressure of water in air is highly sensitive to temperature, perturbations in the global water cycle are expected to accompany climate warming. Regional patterns of warming-induced changes in surface hydroclimate are complex and less certain than those in temperature, however, with both regional increases and decreases expected in precipitation and runoff. Here we show that an ensemble of 12 climate models exhibits qualitative and statistically significant skill in simulating observed regional patterns of twentieth-century multidecadal changes in streamflow. These models project 10-40% increases in runoff in eastern equatorial Africa, the La Plata basin and high-latitude North America and Eurasia, and 10-30% decreases in runoff in southern Africa, southern Europe, the Middle East and mid-latitude western North America by the year 2050. Such changes in sustainable water availability would have considerable regional-scale consequences for economies as well as ecosystems.
Nitrogen (N) and phosphorus (P) enrichment reduces organic carbon (C) storage in detritus-based stream ecosystems, but the relative effects of N and P concentrations and ratios on stream metabolic rates have not previously been tested. We tracked changes in whole-stream ecosystem respiration (ER) and gross primary productivity (GPP), particulate organic matter (POM) standing stocks, fungal biomass, and POM-specific respiration rates before and during 2 yr of experimental N and P enrichment in five forest streams. Nutrient additions (∼ 96 μg N L−1 to ∼ 472 μg N L−1 and ∼ 10 μg P L−1 to ∼ 85 μg P L−1) targeted dissolved N : P molar ratios of 2, 8, 16, 32, and 128. Whole-stream ER was positively related to standing stock of wood, a seasonably stable POM compartment that varied by up to 2× among streams. Nutrient enrichment generally increased ER but had no effect on low-level GPP. Prior to nutrient enrichment, ER was higher at lower N : P, but during enrichment ER increased with increasing N : P. Respiration rates on leaf litter and wood increased with enrichment but decreased with increasing P, and the quantity of leaf litter generally declined with increasing N. Respiration rates on fine benthic organic matter (FBOM) were higher with increasing N : P, and FBOM standing stocks decreased with increasing N. Fungal biomass did not change with nutrient enrichment. Compared to pre-enrichment conditions, nutrients increased seasonal variation in leaf litter standing stocks and whole-stream respiration rates. Our results demonstrate how nutrient-stimulated loss of C from detritus-based ecosystems occurs through the maintenance of enhanced respiration rates on detrital resources that are particularly sensitive to N inputs.
Stream Ecosystems in a Changing Environment synthesizes the current understanding of stream ecosystem ecology, emphasizing nutrient cycling and carbon dynamics, and providing a forward-looking perspective regarding the response of stream ecosystems to environmental change. Each chapter includes a section focusing on anticipated and ongoing dynamics in stream ecosystems in a changing environment, along with hypotheses regarding controls on stream ecosystem functioning. The book, with its innovative sections, provides a bridge between papers published in peer-reviewed scientific journals and the findings of researchers in new areas of study. Presents a forward-looking perspective regarding the response of stream ecosystems to environmental change Provides a synthesis of the latest findings on stream ecosystems ecology in one concise volume Includes thought exercises and discussion activities throughout, providing valuable tools for learning Offers conceptual models and hypotheses to stimulate conversation and advance research.
The actively flowing waters of streams and rivers remain in close contact with surrounding off-channel and subsurface environments. These hydrologic linkages between relatively fast flowing channel waters, with more slowly flowing waters off-channel and in the subsurface, are collectively referred to as hydrologic exchange flows (HEFs). HEFs include surface exchange with a channel’s marginal areas and subsurface flow through the streambed (hyporheic flow), as well as storm-driven bank storage and overbank flows onto floodplains. HEFs are important, not only for storing water and attenuating flood peaks, but also for their role in influencing water conservation, water quality improvement, and related outcomes for ecological values and services of aquatic ecosystems. Biogeochemical opportunities for chemical transformations are increased by HEFs as a result of the prolonged contact between flowing waters and geochemically and microbially active surfaces of sediments and vegetation. Chemical processing is intensified and water quality is often improved by removal of excess nutrients, metals, and organic contaminants from flowing waters. HEFs also are important regulators of organic matter decomposition, nutrient recycling, and stream metabolism that helps establish a balanced and resilient aquatic food web. The shallow and protected storage zones associated with HEFs support nursery and feeding areas for aquatic organisms that sustain aquatic biological diversity. Understanding of these varied roles for HEFs has been driven by the related disciplines of stream ecology, fluvial geomorphology, surface-water hydraulics, and groundwater hydrology. A current research emphasis is on the role that HEFs play in altered flow regimes, including restoration to achieve diverse goals, such as expanding aquatic habitats and managing dissolved and suspended river loads to reduce over-fertilization of coastal waters and offset wetland loss. New integrative concepts and models are emerging (eg, hydrologic connectivity) that emphasize HEF functions in river corridors over a wide range of spatial and temporal scales.
Ecosystem metabolism is a fundamental property of streams and rivers that comprises carbon fixation as gross primary production (GPP) and mineralization as respiration by all organisms in the ecosystem (ER). Ecologists estimate GPP and ER at a stream reach scale by measuring dissolved oxygen throughout a day and converting these data to metabolism given an estimate of the air-water gas exchange flux. Use of this method has increased greatly in the past decade due to ease of data collection and statistical modeling methods, in particular estimates of the difficult to measure gas exchange. Here, I review recent improvements in methods to estimate GPP and ER, examine physical and biotic controls on rates, and address future applications of this technique. Nearly, all streams are heterotrophic (i.e., GPP < ER). Light availability is the dominant control on GPP, observed in both spatial surveys and time series analyses. When GPP is high and variable, it strongly controls rates of ER due to autotrophic respiration by the algae. Streams respond variably to hydrologic disturbance depending on the size of the flood and the substrate. Temperature and nutrients are secondary controls on GPP and ER relative to light and hydrologic disturbance. Despite a weak relationship of nutrients controlling rates of GPP and ER, metabolism can strongly increase rates of nutrient demand in rivers. Stream metabolism responds to human alteration of streams and rivers and holds promise as a metric to quantify human impacts. In particular, time series of daily metabolism may be quite sensitive to human impacts to streams and rivers, although this topic is only beginning to be explored.
Stream microbial communities and associated processes are influenced by environmental fluctuations that may ultimately dictate nutrient export. Discharge fluctuations caused by intermittent stream flow are increasing worldwide in response to global change. We examined the impact of flow cessation and drying on in-stream nitrogen cycling. We determined archaeal (AOA) and bacterial ammonia oxidizer (AOB) abundance and ammonia oxidation activity in surface and deep sediments from different sites along the Fuirosos stream (Spain) subjected to contrasting hydrological conditions (i.e., running water, isolated pools, and dry streambeds). AOA were more abundant than AOB, with no major changes across hydrological conditions or sediment layers. However, ammonia oxidation activity and sediment nitrate content increased with the degree of stream drying, especially in surface sediments. Upscaling of our results shows that ammonia oxidation in dry streambeds can contribute considerably 50%) to the high nitrate export typically observed in intermittent streams during first-flush events following flow reconnection. Our study illustrates how the dry channels of intermittent streams can be potential hotspots of ammonia oxidation. Consequently, shifts in the duration, spatial extent and severity of intermittent flow can play a decisive role in shaping nitrogen cycling and export along fluvial networks in response to global change.