Stream Nutrient Processing:
Spiraling, Removal and Lotic
Eutrophication
Ecohydrology
Fall 2013
Nutrient Cycles
• Global recycling of elemental requirements
– Major elements (C, H, N, O, P, S)
– Micro nutrients (Ca, Fe, Co, B, Mg, Mn, Cu, K, Z, Na,…)
• These planetary element cycles are:
– Exert massive control on ecological organization
– In turn are controlled in their rate, mode, timing and
location by ecological process
– Are highly coupled to the planets water cycle
– In many cases, are being dramatically altered by
human enterprise
– Ergo…ecohydrology
Global Ratios of Supply and Demand –
Aquatic Ecosystems
Inducing Eutrophication
Leibig’s Law of the Minimum
– Some element (or light or
water) limits primary
production (GPP)
– Adding that thing will
increase yields to a point;
effects saturate when
something else limits
– What limits productivity in
forests? Crops? Lakes?
Pelagic ocean?
(GPP)
Justus von Liebig
Phosphorus Cycle
• Global phosphorus cycle does not include the
atmosphere (no gaseous phase).
– Largest quantities found in mineral deposits and
marine sediments.
• Much in forms not directly available to plants.
– Slowly released in terrestrial and aquatic ecosystems
via weathering (and, not slowly, by mining).
• Numerous abiotic interactions
– Sorption, co-precipitation in many minerals (apatite),
solubility that is redox sensitive
Phosphorus Cycle
http://arnica.csustan.edu/carosella/Biol4050W03/figures/phosphorus_cycle.htm
Nitrogen Cycle
• Includes major atmospheric pool - N2.
– N fixers use atmospheric supply directly (prokaryotes).
• Energy-demanding process; reduces to N2 to
ammonia (NH3).
– Industrial N2- fixation for fertilizers exceeds biological
N fixation annually. (We do it with Haber-Bosch)
– Denitrifying bacteria release N2 in anaerobic
respiration (they “breathe” nitrate).
– Decomposer and consumers release waste N in form
of urea or ammonia.
– Ammonia is nitrified by bacteria to nitrate.
– Basically no abiotic interactions (though recent
evidence of rock sources in Rocky Mountain forests)
Global Nitrogen Enrichment
• Humans have
massively amplified
global N cycle
– Terrestrial Inputs
• 1890: ~ 150 Tg N yr-1
• 2005: ~ 290+ Tg N yr-1
– River Outputs
• 1890: ~ 30 Tg N yr-1
• 2005: ~ 60+ Tg N yr-1
• N frequently limits
terrestrial and aquatic
primary production
– Eutrophication
Gruber and Galloway 2008
Watershed N Losses
• Applied N loads >>
River Exports
– Slope = 0.25
• Losses to assimilation
(storage) and
denitrification
Boyer et al. 2006
– Variable in time and
space
– Variable with river
order and geometry
– Can be saturated
Van Breeman et al. 2002
Rivers are not chutes
(Rivers are the chutes down which slide the ruin of continents. L. Leopold)
• Internal processes dramatically attenuate load
– Assimilation to create particulate N
– Denitrification – a permanent sink
• Understanding the internal processing is
important
– Local effects of enrichment (i.e., eutrophication)
– Downstream protection (i.e., autopurification)
• Understanding nutrient processing (across
scales) is a major priority
Nutrient Cycling in Streams
• Advection it commanding organization process in
streams and rivers – FLOW MATTERS
• Nutrients in streams are subject to downstream
transport.
– Nutrient cycling does not happen in one place.
– Flow turns nutrient cycles in SPIRALS
– Spiraling Length is the length of a stream required for
a nutrient atom to complete a cycle (mineral – organic
– mineral).
• Uptake (assimilation + other removal processes)
• Remineralization
Nutrient Spiraling in Streams
Nutrient Cycling vs. Spiraling
1) Cycling in
closed
systems
2) Cycling in open
ecosystems
[creates spirals]
Inorganic
forms
Advective flow
Organic
forms
Longitudinal Distance
Components of a Spiral
Distance
Time
Inorganic
forms
Organic
forms
Spiral
length (S)
=
Uptake
length
(Sw)
+
Turnover
length
(So)
Nutrient Spiraling
From : Newbold (1992)
Uptake Length
• The mean distance traveled by a nutrient
atom (mineral form) before removal
• Flux
–F=C*u*D
– F = Flux [M L-1 T -1], C = Conc. [M L-3], u = velocity
[L T-1], D = depth [L]
• Uptake rates
– Usually assumed 1st order (exponential decline)
– Constant mass loss FRACTION per unit distance
Constant Fractional Loss
• Basis for exponential decline
– dF/dx = -kL * F
– k = the longitudinal uptake rate (L-1)
• Integrating yields F at location x as a function
of uptake rate, distance (x) and initial
upstream concentration F0:
Fx  Fo e
kL x
Uptake Length (Sw)
Tracer abundance
Best-fit regression line using:
Fx = F0e-kx
where: Fx = tracer flux at distance x
F0 = tracer flux at x=0
x = distance from tracer addition
k = longitudinal loss rate (fraction m-1)
1/k1/k
=S
=wSw
Field data
Longitudinal distance
Turnover Lenth (SB)
• Distance that a nutrient atom travels in organic (biotic
form) before being remineralized to the water column
• Hard to measure directly
• Regeneration flux (M L-2 T-1] is:
– R = kB * XB where kB is regeneration rate [T-1] and XB is the
organic nutrient standing stock (M L-2]
– XB includes components in the sediments – XS which stay
put - and the water column - XB which move.
– The turnover length is the velocity of organic nutrient
transport (vB) divided by the regeneration rate.
– Transport velocity depends on the allocation to sediment
and water column pools (vB = u * XS/XB)
Spiral Length in Headwater Streams
(dominated by uptake length)
Uptake length
(Sw)
Advective flow
Time
Turnover
length (So)
Longitudinal distance
Open Controversy
• Headwater systems have short uptake lengths
– Direct (1st) contact with mineral nutrients
– Shallow depths
• Alexander et al. (2000), Peterson et al. (2001)
– Large rivers have much longer uptake lengths (therefore no
net N removal)
• Wollheim et al. (2006)
– Uptake length doesn’t measure removal, it measures spiral
length
– Uptake rates per unit area may be more informative when
the question is “where does nutrient removal occur within
river networks”
– Most of the benthic area and most of the residence time in
river networks is in LARGE rivers
Linking Uptake Length to Associated
Metrics
• Uptake velocity (vf; rate at which solutes move
towards the benthos; measure of uptake
efficiency relative to supply) [L T-1]
– vf = u * d / Sw = u * d * kL
• Uptake rate (U; measure of flux per unit area
from water column to the benthos) [M L-2 T-1]
– U = vf * C
Spiraling Metric Triad
Solute
Spiraling
Metric
Triad
U
solute
triad
vf
vf = (u * d)/SW
SW
Uptake Kinetics – Michaelis-Menton
• Uptake of nutrients (among MANY other
processes) in ecosystems is widely modeled
using saturation kinetics
– At low availability, high rates of change
– Saturation at high availability
U 
U MAX C
C  KM
M-M Kinetics for U provides
predictions for Sw and Vf profiles
Linear
Transitional
Saturated
U=
Umax C
C + Km
U
vd
Sw
Sw =
Umax
C+
vd Km
Umax
vf
vf =
Nutrient availability
Umax
C + Km
How Do We Measure Uptake Length?
• Add nutrients
– Since nutrients are spiraling (i.e., no longitudinal
change in concentration), we need to
disequilibrate the system to see the spiraling curve
• Adding nutrients changes availability
• Changes in availability affects uptake kinetics
• Ergo – adding nutrients (changing the
concentration) changes the thing we’re trying
to measure
Enrichment Affects Kinetics
Mulholland et al.
(2002)
Alternative Approach
• Add isotope tracer (15N)
– Isotope are forms of the same atom (same atomic
number) with different atomic mass (different
number of neutrons)
– Two isotopes of N, 14N (99.63%) and 15N (0.37%)
– We can change the isotope ratio (15N : 14N) a LOT
without changing the N concentration
• Trace the downstream progression of the 15N
enrichment to discern processes and rates
‰ Notation
• The “per mil” or “‰” or “δ” notation
 R smpl  R std
 ( ‰)  
R std


1000


 R smpl


 ( ‰)  
 1 1000
 R std

• R is the isotope ratio (15N:14N)
• Reference standard (Rstd) for N is the atmosphere
(by definition, 0‰)
• More 15N (i.e., heavier) is a higher δ value
Natural Abundances of Isotopes
light
-
-10
+
0
heavy
+30
Accounting for Isotope Fractionation
• Many processes select for the lighter isotope
– Fractionation (ε) measures the degree of selectivity
against the heavier isotope
– N fixation creates N that is lighter than the standard
(εFix = δN2 – δNO3 = 1 to 3‰)
– N uptake by plants is variable, but generally weak (εA =
δNO3 – δON = 1 to 3‰)
– Nitrification is strongly fractionating (εNitr = δNH4 – δNO3
= 12 to 29‰)
– Denitrification is also strongly fractionating (εDen =
δNO3 – δN2 = 5 to 40‰)
• Note that where denitrification happens, it yields nitrate
that “looks” like its from organic waste and septic tanks
So – How to Uptake Length (Addition
vs. Isotope) Compare?
Not So Good
• Our two methods give dissimilar information
• Isotopes are impractical for large rivers
• Large rivers are important to network removal
• But…if we’re interested in the entire kinetic
curve, then this may be a GOOD thing
• Enter TASCC and N-saturation methods
What Happens to Uptake Length as we
Add Nutrients
• Sequential steady state additions (Earl et al. 2006)
Back-Extrapolating From Nutrient
Additions
• Multiple additions (Payn
et al. 2005) result in a
curve from which ambient
(background) uptake rate
can be inferred
Laborious but Fruitful
(back extrapolation to negative ambient)
Lazy People Make Science Better
• Use a single pulse co-injection to get at
multiple concentrations in one experiment
(Covino et al. 2010)
Method Outline
• Add tracers in known ratio
• Measure the change in
ratio with concentration;
the ratio at each time
yields an uptake length (Sw)
which can be indexed to
concentration
• U can be obtained from Sw
from the triad diagram
(U = u*d*C/Sw = Q*C/w*Sw)
• Fit to Michaelis-Menten
kinetics and back
extrapolate to ambient
Data
Stream Biota and Spiraling Length
• Several studies have shown that aquatic invertebrates can
significantly increase N cycling.
– Suggested rapid recycling of N by macroinvertebrates may
increase primary production.
• Excreted and recycled 15-70% of nitrogen pool as ammonia.
• Stream ecosystem organization creates short spirals for
scarce elements
– In a “pure” limitation, uptake length goes to zero and all
downstream transport occurs via organic particles
• CONCENTRATION GOES TO ZERO @ LIMITATION
– Any biota that accelerate remineralization (e.g., shorten
turnover length) amplify productivity
– Invertebrates accelerate remineralization
19_16.jpg
Invertebrates and Spiraling Length
Eutrophication
• Def: Excess C fixation
– Primary production is
stimulated. Can be a good
thing (e.g., more fish)
– Can induce changes in
dominant primary producers
(e.g., algae vs. rooted plants)
– Can alter dissolved oxygen
dynamics (nighttime lows)
• Fish and invertebrate impacts
• Changes in color, clarity, aroma
Typical Symptoms: Alleviation of
Nutrient Limitation
• Phosphorus limitation in
shallow temperate lakes
• Nitrogen limitation in
estuarine systems
(GPP)
V. Smith, L&O 2006
V. Smith, L&O 1982
Local Nitrogen Enrichment
• The Floridan Aquifer (our
primary water source) is:
– Vulnerable to nitrate
contamination
– Locally enriched as much as
30,000% over background
(~ 50-100 ppb as N)
• Springs are sentinels of
aquifer pollution
– Florida has world’s highest
density of 1st magnitude
springs (> 100 cfs)
Arthur
et al.
2006
Mission Springs
Chassowitzka (T. Frazer)
Mill Pond
Spring
Weeki Wachee
1950’s
Weeki Wachee
2001
In Lab Studies:
Nitrate Stimulates Algal Growth
Stevenson et al. 2007
In laboratory studies, nitrate increased biomass and
growth rate of the cyanobacterium Lyngbya wollei.
Cowell and Dawes 2004
• Hnull: N loading alleviated GPP limitation, algae exploded
(conventional wisdom)
• Evidence generally runs counter to this hypothesis
– Springs were light limited even at low concentrations (Odum 1957)
– Algal cover/AFDM is uncorrelated with [NO3] (Stevenson et al. 2004)
– Flowing water mesocosms show algal growth saturation at ~ 110
ppb (Albertin et al. 2007)
– Nuisance algae exists principally near the spring vents, high
nitrate persists downstream (Stevenson et al. 2004)
Field Measurements:
Nitrate vs. Algae in Springs
Fall 2002 (closed circles)
Spring 2003 (open triangles)
From Stevenson et al. 2004 Ecological condition of algae
and nutrients in Florida Springs DEP Contract #WM858
No useful correlation between
algae and nitrate concentration
Visualizing the Problem
Silver Springs (1,400 ppb N-NO3)
Alexander Springs (50 ppb N-NO3)
Synthesis of Ecosystem Productivity:
Nitrate vs. Metabolism in Springs
Data Sources:
- WSI (2010)
- WSI (2007)
- WSI (2004)
- Cohen et al. (2013)
Slight Digression - Nutrient
Contamination Broadly in Florida
Source: USEPA (http://iaspub.epa.gov/waters10/state_rept.control?p_state=FL&p_cycle=2002)
Recent Developments – Numeric
Nutrient Criteria
• Nov 14th 2010 – EPA signed into law new rules
about nutrient pollution in Florida
– Nutrients will be regulated using fixed numeric
thresholds rather than narrative criteria
– Became effective September 2013
• Result of lawsuit against EPA by Earthjustice
arguing that existing rules were under-protective
– Why?
Stressor – Response for Streams
• No association found between
indices of ecological condition and
nutrient levels
• Elected to use a reference standard
where the 90th percentile of
unimpacted streams is the criteria
Eutrophication in Flowing Waters?
• Why no clear biological effect of enrichment in lotic
systems?
– What is ecosystem N demand?
– How does this compare with supply (flux)?
– What does this say about limitation?
• Is concentration a good metric of response in lotic
systems?
– In lakes/estuaries, diffusion matters.
– In streams, advection continually resupplies nutrients.
Qualitative Insight: Comparing
Assimilatory Demand vs. Load
• Primary Production is very high
– 8-20 g O2/m2/d (ca. 1,500 g C/m2/yr)
• N demand is basically proportional
– 0.05 – 0.15 g N/m2/day
• N flux (over 5,000 m reach) is large
– Now: ca. 30 g N/m2/d (240 x Ua)
– Before: ca. 2.5 g N/m2/d (20 x Ua)
– This assumes no remineralization (!)
• In rivers, the salient measure of availability
may be flux (not concentration)
• Because of light limitation, this is best
indexed to demand
• When does flux:demand become critical?
Metrics of Nutrient Limitation
• Concentration
– Ignores the fact that flux/turbulence reduces local
depletion, and that light conditions affect demand
• Flux-to-demand (Q*C/Ua) (unitless)
– Requires arbitrary reach length to estimate demand
• Autotrophic uptake length (Sw,a) (length units)
– Consistent with nutrient spiraling theory (Newbold et al. 1982)
– Ratio of flux to width-adjusted benthic uptake
Autotrophic Uptake Length
• Mean length (downstream) a molecule of
mineral nutrient travels before a plant uses it
– Not dissimilatory use, which typically dominates
• Shorter lengths imply greater limitation
• For N: Sw,a,N
• For P: Sw,a,P
Predicting GPP Response
• Nutrient Limitation Assay (NLA)
– Relative response (RR) of N enrichment:control
– Regressed vs. Concentration and Sw,a,N
NLA Response Data from Tank and Dodds (2003); Analysis by Sean King
Estimating Ua from Diel Nitrate Variation
(Ichetucknee River, 5 km downstream of headspring)
YSI Multiprobe
Submersible UV Nitrate
Analyzer (SUNA)
Diel Method for Estimating
Autotrophic N Demand
[NO3-]
[NO3-]max
Autotrophic
Assimilation
[NO3-]min
0:00
Assumptions:
Heffernan and Cohen 2010
12:00
0:00
12:00
0:00
No autotrophic assimilation at [NO3-]max
Other processes constant (unknown)
Other N species constant (validated)
Net Primary Production (NPP) (mol C/m2/d)
Ua Estimates Yield Reasonable C:N
Stoichiometry at the Ecosystem Scale
NPP = Ua * 25.4
R2 = 0.67, p < 0.001
C:N Ratios
Vascular Plants ~ 25:1
Benthic Algae ~ 12:1
N Assimilation (Ua) (mol N/m2/d)
Inducing N Limitation in Spring Runs
[some were, many springs were not N limited at 0.05 mg/l]
Autotrophic Uptake Length Globally
Summary
• Spiraling the dominant paradigm for nutrient
dynamics in flowing water
– Stream ecological self-organization creates short
spirals for scarce elements
• Measuring spiraling (esp. in larger rivers) can
leverage new methods (diel, TASCC)
• Lotic eutrophication is different than other
aquatic ecosystems, and requires a spiraling
basis
So – Why All the Algae?
Back to First Principles:
Controls on Algal Biomass
Grazers
top down effects
Flow Rates
Dissolved
Oxygen
mediating factors
Algae
Biomass
Nutrients
bottom up effects
Light
What else has changed? –
Water Chemistry.
• Despite relative constancy,
variability in springs flow and
water quality can be large and
ecologically relevant
• The changes are poorly
understood because of a)
uncertain flowpaths, and b)
uncertain residence times
• The changes are understudied
because of the plausibility of
the N loading story
Data from Scott et al. 2004
What else has
changed? Flow.
Weber and Perry 2006
• Changes in flow occur
in response to climate
drivers and human
appropriation
• Kissingen Springs
Munch et al. 2007
Field Measurements:
Algal Cover Responds to Flow
• Flow has widely
declined
– Silver Springs
– White Springs
– Kissingen Spring
• Reduced flow is
correlated with higher
algal cover (King 2012)
Gastropod Biomass (wet weight g/m2)
Flow and DO Affect Grazers
300
250
200
150
100
50
0
0
2
4
8
10
DO (mg/L)
300
Gastropod Biomass (wet weight g/m2)
6
250
200
150
100
50
0
0
0.1
0.2
Velocity (m/s)
0.3
0.4
Observational Support: Grazer Control
Algal Biomass Accrual
Algae biomass (g m-2)
A)
B)
C)
y = 2350x-1.592
R² = 0.38
p < 0.001
Gastropod biomass (g m-2)
Note: Multivariate Model of Algal Cover explained 53% of
variation, with gastropod density as a dominant predictor along
with shading and flow velocity. Nutrients were pooled (no
significant effect).
Liebowitz et al. (in review)
Evidence of Alternative States?
A)
Gastropod biomass > 20 g m-2
0.00 0.05 0.10 0.15 0.20 0.25
B)
0.10
0.15
0.20
0.25
Gastropod biomass < 20 g m-2
0.05
0.00
Proportional Frequency
• Below 20 g m-2 – always high algae
• Above 20 g m-2 - both high a low algae
• Mechanism?
-6
-4
-2
0
2
Residual algae biomass
4
6
-6
-4
-2
0
2
Residual algae biomass
4
6
Qualitative Confirmation: Gastropods
Control Algal Biomass
Quantitative Confirmation
45
HS
y = 38.13e-0.009x
R² = 0.93
GF
y = 14.95e-0.008x
R² = 0.85
y = 12.84e-0.005x
R² = 0.55
y = 2.46e-0.003x
R² = 0.64
40
Algae AFDM (g m-2)
35
MP
30
ST
25
Expon. (HS)
20
Expon. (GF)
15
Expon. (MP)
10
Expon. (ST)
5
0
0
50
100
150
200
250
Gastropod wet weight (g m-2)
300
350
Further Evidence
of Alternative
States
Experiment 1 – Low Initial Algae:
Intermediate density of snails able to
control algal accumulation.
Experiment 2 – High Initial Algae: No
density of snails capable of controlling
accumulation.
Shape of hysteresis is site dependent.
Alternative Mechanisms?
– Mullet excluded (90+% loss) from
Silver Springs with construction of
Rodman dam
– ~2 orders of magnitude increase in
snail density with distance
downstream in Ichetucknee
• Changes in flow (direct and
indirect effects)
– Significant declines regionally
(Kissingen Springs)
• Changes in human disturbance
– Recreational burden is 25,000
visitors/mo at Wekiva Springs
1972
15
10
5
0
20
Number of Springs
Declines in animal populations that
control algae [top-down effects]
Number of Springs
20
2002
15
10
5
0
0-1
1-2
2-3
3-4
4-5
5+
Dissolved Oxygen (mg/L)
Heffernan et al. (2010)
Controls on Grazers
• Dissolved oxygen is an important control
• Multivariate model explained 60% of grazer
variation with DO, pH, shading, SAV and salinity
Gastropod biomass (g m-2)
A)
B)
C)
Dissolved Oxygen (mg L-1)
DO Management Thresholds?
Experimental Manipulation of DO
Short Term DO Effects
(2-day pulses of hypoxia)
• DO dramatically
controls snail grazing
rates
Behavioral and Mortality Responses
Complex
Ecological
Controls?
Heffernan et al. (2010)
Why is Grazing SO Important in Springs
• General theory on what
controls primary
producer community
structure (Grimes 1977)
– Nutrient stress (S)
– Disturbance (R)
– Competition (C)
• In springs, nutrients are
abundant, disturbances
are absent, so competion
controls dynamics
• Grazing is a dominant
control on competition