-------
Concurrent studies of Cd v< t ^ r>rn- nu using the stream
crayfish (Thorp et al. 1979), ,=>, s ^ n ,i .. »sy et ai, 1*377. A
Giesy 1978), and leaf decompo- • « [( .!„•*,t *.
STREAM MODEL
An energy and matter flow model of the artificial streams was con-
structed first as a diagram using the energy circuit language of Oduffi {1971}.
f.*>e Itiod^' * n, J < , tYc'* "Sit' "P ll ri, !' •, I , >11 1 1 ^ < ir*
alone, hi ?> r ».s , rt ^ • ,'>r . > *iv|	c •( i ,r^rtKj .it -me response
to Cd at different concentrations, further details of the model are des-
cribed in the results section of this report.
The major blomass storages arid their Cd content were monitored through-
out the 2-yr study and have been used directly to calibrate the model when
possible. However, few of the data are for average levels throughout the
i.ttcrocc^nH, i> i . r\.r ~->r >	.* <\* r.-r 1" Vs >c *whM, -«ip« ,
Thus, to calibrate the model to whole-system averages, assumptions and
extrapolations from a few measurements were made to other data.
¦VI io s"o» :K > >tes i -r ,i • i > j! b< i ,> r*sc> :w 1 riv I'm ; -nbc-*
than Cd uptake and release, systen production and respiration, and export;
and therefore, a considerable amount of parameterization was done by
simulating the model and comparing results to the actual measured storages
over time. Specific rates from the literature were used when available.
luiiwuinr Sii'.f li if*' -t'n- ci er "«a(!yt5«iq3: ciurfw? the
early stages and finished using BASIC language with an Intercolor desk top
microcomputer. Integration was by means of simple difference equations with
variable tiros steps*
ruuth .vuh v_J	at- ru i.h, i K tn>: r^rio*- cn	ie>.he.r*fis we*	. 3 be ,r n * 1 v,t * ,ih *(. j< i a or other a misms
ncccssar, to »-s zt<- the im . • u ti m, i " - ; < > • y\
ENERGY RELATIONSHIPS
la.t» La i i
In oi
storage, <
sible for
for a simj
•erg)
\
on
pr
in prn^.
n made
•, emboc
'ow or :
! "IS 0
i--, F
V>cen a>
embodied is
sy
low or
pon-
>Uuh u model
amass (\J,»
43

-------
OTHER
ENERGIES
SOLAR
ENERGY
figure v.1. Aggregated rodel of a production process Kith two
energy inputs (A and 5), gross production (C) of a
stored product (0) with feedback maintenance (0)
and maintenance energy loss from the system (E).
The embodied energies of flows C, D, and E are
equivalent and are equal to the sum of input e ^ od-
1ed energies (A + b). The embodied energy in tj is
equal to the total embodied energy input {A + 8}
multiplied by the turnover time of Q.
44

-------
wj*th minfen*nre	?nd	pi^i^tGn^nc^1 {0}* Fo^
this no lei rou;d k»>,"> '.stMl j.for1 t .ior n ' lvpr trc crp^sy a.^ucs-jlc3 w> t» c,• nthsr inputs
such -: TUit' -iift? ii ri*1n t "W t ur^ r t f >7
flows rust ?!¦;'• tf "jlctsl •1 a1 r* nm<1
frwde v.tth the use uf e^irrt^ o~ Cf.un.s
kinet tr enerq% of >-nn, c, > 'l i1 ni v>il>iP;
(qua! Hy f ic'or O piiMiiHOu >w Hd >1,1 ? h (•!•-
: S.E. Ca 1.
content (fi
for enerqy
Jdum
1980)
'"h e z c . 1 cu I .it.^ Oft rc»i>
« *// of ..ft"(iiicrmst ' -If, f"31f"j
I'hAt ^ -11 , J^RCH
he
E
fo
»1 embodied energy fit
1 fl
ernt
is thin the systen tousxlary
1 energy in f Ic.r, C, 1),
r:s may be very u.ffutr
integrated inpit energy
w. Thi,r ¦
iiil ^lihmjo!, 1 he, > vot ? inalerit em
•iie'S energy "f a r-ot jc- ^ equal to 1
storage.
tr«e ,k;ual e/'trrpe; us 1 „ >» and E (C<
n ratios (TR) may be calculated from 1
input energy {fi- * Bs by the ar<-tjai fnpK.^ in <
EM/f > pre^fnt', t ht 'k tor aiv 1 j.tix'u i>Mfv
Ca I *Cci 1"^ ! t > value5 may tr>er« be  be ca«c ii Kit cd from sev-
eral different models arre coitifsrtr. 1 ho1-^ mny be <1 theoretical minimum walue
for each FR that represents the •ijjLhw1 "iTteicKy for the civen energy
transformation. Precise TR /alr.-'j of en-my fvpp- at\i flows are net yet
known, so all calculations ar: «$sunn>d to bp pre I Hi'siry.
i.>ni" ) art* iiHiflt, t»>on trans-
fm nvael b/ idi!*g the total
h rt^il Mni flow, Thus (A +
in Fig. 5.1, with units of S.E.
0 evdKate sens? other
Toxicity Effect
The ener/y ®f<"act of a unxir or control 1 er Ss tifasure'i m an amplifi-
cation (either tivc or fiLH)dttvirl „>f ,in	or stmt'je expressed
in embodied enrr'iv ants, Thii »Mp11 1 cati^1' tner control-
ler. t
1 or t'^ainple, nci'ini- th ^ a . " ini-u' 01 : «j«j 01' i ^**1"^ tr. *
steady stdtv mcroco;-ra is found to r'ecrea-,^ cim«t7 orodurtivicv relative to
a control bv lu C?'	. Fra«-	pst^nnie"? ws fir.vi th.it t' 0
"iR for primary product 11 ity is 100 \.T CjI *f\il -l- .rH thu. tht cn^rqy
etfcct or We ii\en CJ	i*. - .s.T.	, 'Ins 1 cxm,
effect may be oi v'do." bv r,nf Cd inpMt to giv-? -IC0C 3.F, "a' -uq Ca"^ as
t.lif. lU'rw.ihiix! t.fftlc+, TU'- oniA>,yv ^i + .r.t in •} rnnlro^ 1 ira; ;»bstancf« i»>iv ^ 1
function of its rorv^nt > a* urn vHi."1 efnro tnc '-onrcr.r.r^ticn iru;;t be ip'ict-
tied *or copspariscis. hi v.ith eTOodied erwyy cjlci.,1 ationb, energy effect
cj leu 1 at inns ."v ir ? pr<>l imtha1 ^	.ifsil -Htgcc^ ' .1 rwisiun, "lie ¦sranor-
tance cf th^ enf ry.v ;•? leu lotions c.adc ir tSi:5 »eport 95 m<
-------
SECTION 6
RESULTS
CADMIUM STREAKS
The Cd-stream study lasted 2 yr with five persons actively sampling
various components of the biota for toxicity effects and measurement of Cd
concentration. The final report for the project (Giesy et al, 1979) suanar-
ized the major findings but did not include a surimary model of how the over-
all system was reacting to Cd dosing. In this section we integrate the data
that are necessary to calibrate a simulation model of the streams.
Unfortunately, only a small part of the data was collected in convenient
form for a system model; therefore, it has been necessary to extrapolate from
artificial samplers to the whole stream community and to prepare new graphs
on a square-meter basis. All of the data presented hers are averaged over
the entire stream area of 56 rn% but in fact, the corrmunities observed were
quite variable depending on their location in the streams. Thus, coloniza-
tion by algae and macrophytes was most rapid at the upstream end of the chan-
nels while a few species were always most abundant at the downstream end.
Data from ail samplers showed position effects; however, a zonation model of
the channels was not attempted.
Biological Effects
The biological effects of Cd input to the artificial streams were
affected by season, successional state, and taxonomic affinity. Prior to the
addition of Cd the streams were all similar in composition of periphyton,
populations of invertebrates, and plant, growth. After Cd inputs of 5 or 10
ppb began, the streams demonstrated significant changes in response to the
low Cd levels tested.
Algal populations in the treated channels were never as high as those in
control channels (Fig. 6.1}. Significant treatment as well as seasonal
effects on algal pigment ratios were observed throughout the Cd input, and,
on a macroscopic basis, the different treatments were visibly different in
color. At least two algal species coimon in the control channels were never
found in the treated channels during Cd input while other species formed lux-
urient filamentous blooms in the Cd streams.
The nonalga.1 portion of the periphyton was considered collectively as
detritus and microbes. The biomass of this community was significantly lower
in the treated channels than in controls within 2 mo of initial Cd input, but
within 6 mo significant differences in this assemblage between treatments had
46
-------
\J Sppb
/ —-—
CONTROL
rt D »J F M. A M J J A S 0 M D lj P M A M J
1976	1977
SAMPLE DATE
figure 6.1. Live algal biomass during the ?2-m Cd-stream study.
Values are stream averages extrapolated from glass slide
and wall data for control, 5 ppb Cd, and 10 ppb Cd.
47
-------
disappeared (Fig. 6*2). At all times during the study, the detrital biomass
was about 5X as great as the algal component individually.
At the end of 1 yr of continuous Cd dosing, macrophyte populations were
greatly reduced with respect to control populations. In March 1977, average
dry matter densities were; control, 39; 5 ppb Cd, 5; and 10 ppb Cd, 6
g*m~2. Cadmium input was suspended in the spring arid by the end of
that summer the macrophyte populations had increased greatly, resulting in a
substantial change of habitat in the channels.
An Initial sensitivity of some groups such as protozoans, ostracods,
cladocerans, and copepods to Cd input was demonstrated in mfcroinvertebrate
studies. Cadmium severely reduced copepods, ostracods, and testate amoe> :
however, overall populations of microinvertebrates were increased because of
stimulation of protozoans and rotifers.
Macroinvertebrate data indicated variable population responses in the
different Cd treatments. At some sampling times, chironomid larvae were more
abundant in the Cd streams than in controls; but, during most of the study,
total macroinvertebrate biomass was reduced in the treated channels (Fi".
6.3).
Initially, 200 mosquito fish, Gambusia affinis, were released into each
channel. Recovery of dead fish indicated increased mortality in the 10 ppb
Cd treatment (55%) compared to the 5 ppb Cd treatment (23%) and controls
(21%) within 3 mo of the beginning of Cd inputs. Ho further attempt was made
to quantify the fish populations during this study.
Overall community metabolism was significantly lower in Cd-treated
streams throughout the period of Cd input, and showed quick recovery soun
after Cd input was stopped (Figs. 6.4a, b, and 6,5). The complete diurnel
oxygen change curves from the Cd streams are given in Appendix A. All
streams were autotrophic (P/R > 1), although the treated streams were less
so. Cadmium treatment also significantly lowered community export of organic
matter during this study with rapid recovery after treatments stopped (Figs.
6.4c and 6.5). Nutrient regeneration by microbial communities was signifi-
cantly reduced by Cd treatment as indicated by ".-sight loss in leaf litter
packs.
In summary, Cd input at concentrations of i and 10 ppb demonstrated
inhibitory effects In every trophic level examined, and yet was riot com-
pletely inhibitory to any biological parameter.
Bioconcentration
Cadmium uptake by the stream periphyton communities was rapid with
steady state levels reached within 50 days. Steady state levels were 3, 36,
and 58 yg Cd*g dry weight"* for control, 5, and 10 ppb Cd treatments.
When Cd inputs were turned off, peri phy ton Cd concert! rations dropped to con-
trol levels within 50 days.
Macrophyte uptake of Cd in the treated channels was much slower than for
the periphyton, with steady state concentration attained after 5 mo of con-
tinuous input. Root Cd concentrations were 3-4 X as high as leaf concentra-
tion in the two macrophytes examined. Whole plant averages were approxi-
mately 2, 75, and 150 pg Cd*g dry weight"1 for control, 5, and 10 ppb
Cd treatments.
48
-------
200
150-
C0NTR0L
5ppb
100
50-
.Cd ON
*»¦- .it*. .Jk*
1976
197?
SAMPLE DATE
Figure 6,2. DttrHai c*fi»f rcncobi a< birwar.s dining the ?2-mo
C •,~tH re-..- s 11 '<1;< . Vdu^, or\i o\t rjp^ljtcV f row i, lass
si u-ij, <*<. 11 cere les rot :ontr 0 ppu Cd»
a
-------
M
'g
3K
"8.
CD
0
05
UJ
'5
m
s
0£
w
>
Z
o
CC
o
<
2
0.0
M-
•Cd ON
M
-CONTROL
*3ppb
lOppti-
a	s__j.
J	I	I	I	I	L.
J	L-L,
N ~ | J FM A MJ JASONOIJFMAMJJ
SAMPLE DATE
Figure 6,3. Biomass of roacroinvertebrates during the Cd-stream study.
Data are extrapolated from plate samples for control, 5
ppb Cd, and 10 ppb Cd.
50
-------
9
¦CONTROC
Ci 01
X £
Oppo
1ST?
197®
SAMPLE DftTE
Figure 6.4. << «x.««y cv • y,< >.< l.w. .lata during the
ud c. L « 1 -"i > v\ - . ! 5 ppb , -
51
-------
f
6.0
V
ei
*E
5
•o
ot
s
GROSS
&
3E
pNET
EXPORT
0,0
0
5
Cd CONCENTRATION (ppb)
figure 6,5. Summary graph cif system-level t-a meters measured in
artificial streams receiving continuous Cd inputs.
Point represent 1-yr averages for two replicate
streams at each treatment.'
52
-------
Mosquito f' ih >o<; > m\ "1 v 101 rwhzJ »rlcr 6 mo of up-
take. radi«iwii C'sicpfu r. t i lun , i'i t> *• r f».,\ vo«m, r2, 24, and 40
sig Cd'§ dr vreioH fo" < Mm? u. S, vd K i>ch t d -.^Mtreits.
No Cd
or wi v Hi
water
tiors in un
ccncPhtrjt
ma»ino] s.
Pound to be associated with the
		. <_m -s' » T'orgf^rc
been due to biological uptake,
red water samples indicated an
^ 0 .i ppb i" t'u; ^ . ,(, <. t ii
«vnd	In the stream;
•il kc 1i» fes Iras tho si**ear»>
Jv;	cf Co com w.tra-
larage lowering of effective
Wd fl- ii> pph ih V>-"pb
SlKfAP HClS SIMULATIONS
General Model
An aqg? egated vdal «»f a •jtrvdiii ecosystem *,~<» .<>.	i tor experimen-
tal ton wnb Loxrn and rcnv-.'m'ot i>^n¦ rul  (where
h represents iit rogon} aew ti t» trjvi< wfti>d< i'ttvir.« - v.• i n 3 ccmpl leafed
biologtCiil system. lt=e !¦ ic k-cteal r.yste^ tc^t-x1 is	o* str^.-ms in
low-slope areas with nedprrstG to rlcv "ur- nt VL^cit ie^, F-'-im.isy producers
include rwcrophytps (i c Jted plants, djl wrr| theiav.iunft1 ed H-r t pnyt i t
algae (Q?j. In this nwdel, i omuaer "ire 'urnped into o<». unit M4). All
unassimaiatfc1 and -kw mtv»>nol is r,fIo1 thromih the dwitaKmcrobial
storage (t^)„ which ir> winy  1 rocser, r-rp] cm rhment w,thi» f lit "O.niunity is
priiirelv from microbial	!cion q5 1t 1 f'Vii,
K'.gure 6,7 is a .1 > ci . )*r »!rt.ids »1 ^he a 19<'i'i wurnty. Remain-
ing sunli-jht Jjr) i«t;crati< w [1 n * a^vr? iU) ?nd -3a1 bKrwss to contrib-
to gcocs ^«\.ttosv."!rr ^ff«Jt ¦ / ,\nk». -Sciiji; l?wl,	is also
absorbed *>011, ^f'urien t, a v\»-! 1 »u~,~ • er pi^ -r n»oc;« h	hi amass a«s the
Uniting suHstr*-tiA. tadr.ium If>:! fmn iN» al'.uia hy I°«iurati3fi and partic-
ulate los; tv eviwt, CvOSiine! 1;, (id'" tiotntus =
Citimiu.i to\Kir> ti> ui»« v	if.	us a dirtrt interac-
tive drain bv watei '"ri > f-rv^nir jt ton n? alqtu hiuRMS,, j«.r'1iqh* icts on
aloal Dii'Ra^s 1 h'Mii'ih phc^oicstjit it ,!nch mav -><;ve b?.n^ iimportant in the
shallow t'A '-irpe-ms,«
K ic;np[ • rc int**' ¦'f n^s* »>< icmtuf-i/ed hi "u;, ^ H, All flews are
analogoiit. tu *h.-	1 mhc a>?rcr	t nj. 6. 1 except r.hat. no photores-
pffaticn i"»t t,iru..m was inch, it d -n ;!t» a^oir.~;;~n patnivav.
Iigtire ti.^ ;]lustt.u f> Uif-	.-on^u.n^r «~'wii!ittit> in this model
stream ecosvst a. uinsuituM- 0,crr„^r /) ;> 1 o-«> y;, c I. "^erophytes, and
det f it'js-iru rotv1 , with semv ' 1 t (v> 'i-^tr»naJ asp^'litej and some last
di t eut i v 1.,"*	« r'>'rn 1 i „ '>0 ind ' j t t"r< m thii storage by the
same "wchaniims itou^I ,ii m nrpd.ir,»r umtij, an" 01 t :> i011/ acts directly
as a drair v»t cir>.Dianass.
53
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EXPORT
IHI ! CSV
Cd
/V
SUN

Figure 8.6, Overall system model of Cd streams. Sunlight interacts with dissolved chemi-
cals to maintain complicated biological systems and Cd cycling. Each unit has
stimulative and toxic action of Cd (see details in Figs. 6.7-6.10). Computer*
program and rate constants are listed in Tables B.5-B.7,
-------
Q2 55	(1+- ^^)-KoQ2JR-KxQ2t}4-KpQ2-KuQ2-|-4(l2Cz
C? = f the ,7
' -- "• - •*" >':J iir< P; <»^ry > ^ >' » {ls) ^	,'^t in
Computer pr'»jiyih * >< pate > u !pis are	ii ' !r>'c* a.id—B.
55
-------
h * (K9N2JRq3)(l+ ^^)-KqQ3-KyQ3Q4-L2Q3-L5Q3Ca-K£Q3
k " KlQ3(K^)™CcKYQ3QrCC{L2Q3+L5%%^%%-CcKQ%
Figura 6.8. Detail of the Cd-stream model showing interaction of
macrophytic plant community. As with the alga.-, a stimu-
, latory effect of Cd is included (Lt), r(i'nputer progr.v
r arid rate constants are listed i n Tabl - 5-B .7.
56
-------
Q# = L9Q4(KxQ2+KyQ3+L6Q5)-KsQ4-LqQ42-LpQ4CA-KpQ42
C4 s L9Q4 (KxC2+KyC3+I-6C5)+*\]Q4	"K0C4"C0 (l-|Q#2+ipQ4cft)"Co C%%)
Figure 5,3. Pn^ril of iiodol -b-wirtg the ,?tj«rcqat?d
tviiruiPt-r s >t^i J. ~	i1- la ion ip through
bcst'i surface afi?,»*pUw ;nd *ee:linn Computer pmgram
and rate constants arc "Hr-ted in Tan»f«f p.s—3.7.
5?
-------
The last section of this stream model is diagramed in Fig. '•. The
storage of detritus and associated microbes (bacteria and fungi) is indicated
as Qsj, receiving inputs from all of the biological components in th*
Cadmum is taken up and lost as in the other components, but exerts Us toxic
action as a reduction of nutrient regeneration and metabolism of the
microbes. As shown in Fig. 6.7, the storage Q5 intercepts a portion of the
incoming sunlight and therefore, reduces regaining sunlight (JR) available
for photosynthesis.
The model shown in Fig. 6.6 represents a simplification of the actual
streams and yet is a very complex nonlinear model. Since the put cose of the
model simulations was to provide approximate data for the effect:. Cd con-
centrations not actually studied in the artificial streams to be used ir
example correlations of embodied energy and toxicity effect; exact fitting of
model output to actual data was not attempted. Instead, the model was simp-
lified whenever possible, while retaining both fate and effects of the toxin.
Simulations were made using a desk-top microcomputer and BASIC computer lan-
guage because of the immediate feedback between model and modeler. Slowness
of these simulations run at small time-step intervals was a disadvantage and
limited the goodness of fit between model results and actual measured data.
A complete list of the model storages, pathways, and parameters Is given
in Tables B.6 and B.7. A copy of the BASIC computer program used for the
simulations reported in this section is given in Table 8.6.
Parameterization
Although the model illustrated in Fig. 6.6 is a simplification of the
actual stream microcosms, it contains 39 constants that had to be estimated
from data collected during the Cd study or from published reports. Many of
these constants were not known exactly and in fact many may not. have wen
constant during the 2-yr successions! period. A discussion of the imis for
the choice of the model parameters is presented below.
Units-
Flows In the model were In the following units; pure energy, Cal {kilo-
gram calories); biomass, grams of dry weight (g dw); nitrogen, mg N; and Cd,
pg Cd. Rates are all on a per square meter per day basis {!rr<-*d~4).
Solar Input-
As seen in Fig. 6.6, solar energy is one of the two primary driving for-
ces included in the stream's model. For simplicity on the microcomputer,
solar input (J0) was simulated by a sine function with maximum f„i.'.'::i'jm
values of 6000 and 2720 Cal4m"2«d~l, respectively. Actual solar
energy at the channels was taken as 70% of these maximum values from averge
cloud cover data published for Columbia, South Carolina (MOM 19/6, 1977).
In the channels, remaining solar input 
-------
Kb
EXPORT

I
L2+L5
DETRITUS
M1CRC .
% = L2%+KU,Q2,JR'fLB%2+L4Q2cA+L5%cA+LpQ4Cil|-!C5Q5 (l-LECft)-KRQ5
"f,
€g = Cc(12Q3+L5%caJ+cB ^uQ2JR+L#Q2cA)+K#5ffp§^)+cD
-------
Cal absorbed per gram of dry weight produced was calculated. Thus the con-
stants KA and KB were set equal to 143 Cal-g"1,
Mater Inflow—
Incoming water flow (JW) was constant and equal to 136,000 L*d~l.
This water contained N (Ml * 0.015 mg N't"1) and Cd (CI = variable with
0.023 yg Cd*L_1 as the background concentration).
Nitrogen Dynamics—
The total nitrogen concentration measured in the channel input water was
15.8 yg N*L"^ while the total phosphorus concentration was measured as
2.9 yg*L_1 giving a ratio by atoms of about 13:1. Since the optimal
ratio is generally considered to be 16:1, nitrogen may be slightly mors
limiting and was chosen as the nutrient to monitor in the model. ft few cal-
culations show the importance of this nutrient in the streams and conse-
quently in the model simulations. With a water input of 136,800 I'd"*
to each channel with 15,8 pg N-t"l and 56 m* surface area, we calcu-
late a nitrogen flow of 38.6 mg	Actual net productivi-
ties measured in the channels during the second year of study were about 2,5
g dwm"2>d"!. This means, if ail of the f) was taken up in biomass
during each 24-hr period, the N content on a dry weight basis could have only
been about 1.5%, which is low for algae and plants (Odum 1973). Luxury
uptake of N in the dark is known (Ketchum 1954) but algae cannot take up N
from extremely dilute water. Therefore, the constants for K uptake, K4 for
algae and K6 for rracrophytes, were assumed to be 0,5% or 5 mg N*g dvr1.
The importance of nutrient cycling in these channels for maximizing produc-
tivity is immediately obvious from the above discussion.
Recycling of N was simplified in the model by the assumption that all M
remineralization was from the detrital-microbial storage 
-------
JC - Ci-JH.	(6.5)
Cadmium uptake by the biota was modeled as a hyperbolic Michael is-
Menton function;
FH - <•"«'	(5-6'
PI = U^a!M (macrophytes)	(6.7)
Fj =	(consumers)	(6.8)
FK =	{detritus-microbes) (6.9)
llVJk " ivl IS
This uptake functir-n ha*. b-;en ob-ervfd for Cd with most biota studied
(see Section 4}. ilit- It-saturation cnt'st.^nt (KI) was set equal to 200 ug
CcH~ ¦ as u rou or ?arh of the four biological storages
was incI>jded in the not.'el ¦ • ?, Cd in	C3, Cd in macrophytes; C4, W In
consumer:,; ard C5, Cd in diaritu'-nncrotes.
Loss of Cd fr«n each of those storages wis in two forms: 1. dissolved
Cd modeled 3% 4 simple linear 4echy; and 2. particulate Cd transport to other
storages. For the	i d decay w> fV>t i: 1 in the artificial streams. For the
consumers, Cd ie<.a> kj.	* as:
fO - KO'C#	(6.12)
where a v.tlue of  • u<-.-."icrobes, Cd decay was equal to:
01 = tl-CS	(6.13}
with 11 = KL = 0,065 d"1. Cd was also remineralized In microbial
respiration:
FT - FG'CE	(6,14)
where CE was the concentration of Cd In Q5 and wa^ >xiual to C5/Q5.
Cd loss in particulate form was simply calculated as g dw*m~2-d~*
multiplied times the Cd concentration in W a3«> (ug Cd*g dvrl) ¦
51
-------
Overall Cd flow In the channel water was equal to:	•
F2 - JC + FL + FM + FO + FT + J1 - PK - FJ - FH - FI (6,15)
and Cd concentration In this stream water was calculated as:
. CA - g	. .(6.16)
A1—-
The living algal component (Q2) of the periphyton (see Fig. 6.7) was
monitored separately because of its importance in the primary energy fixation
in the channels. The modeled relationship for gross primary production was:
F8 • K8-N2-JR-Q2.	(6.17)
Algal respiration was equal to:
FD - KD-Q2MR __	{6.18}
where the JR term indicates the possibility of photoresplration in the
shallow streams. In addition the algal storage Is also drained by consumer
feeding:
by death to detritus:
arid by export:
FX * KX-Q2-Q4	(6,19)
FU = KU-Q2	(6,20)
FP = KP-Q2.	(6.21)
The effect of Cd was modeled as both stimulatory	at low concentrations:
J8 -	(6.22)
and as a toxic drain on biomass:
J4 ¦ L4-Q2-CA.	* (8,23)
The constants in the above relationships (K8, K0S KX, KU, KP» IS, LU, and
14) were all adjusted by an initial approximation and then simulation runs to
fit model output to observed alga] biomass patterns.
Microphytes—
The aquatic macrophyte population (Q3) is illustrated in Fig. 6.8. All
flows are analagous to the algal flows except that respiration;
FE » KE-Q3	. . (6.24)
62
-------
had no-sunlight component. Table 8,6 lists the details of th« •. flows,
Once again	constants governing macrort.. V	s,i»iv adjusted by
simulations to fit observed blomass changes in tSt* .v* i hm screams.
Consumers—•
Details of the urj.t • v. -orient } - the stream model are shown in
Fig, 6,9, Consumers	;
on macrophytes:
and on detritus-microbes;
FX = KX'Q2-Q4	(6.25)
FY « KY-Q3-Q4	(6,26}
J6 = L6-Q5-Q4.	(6,27)
Assimilation efficiency was assumed to be 30?
J9 - L9-(FX + FY + J6)	(6,281
where L3 = 0*3, The remainder of the ingested food was returned to the
detritus-microbes;
JK = FX + Ff + J6 - J9.	(6.29)
Losses from the consumers were respiration;
FF - KF-Q42	(6,30)
with a square term to indicate predation or crowd!	?cts; death to
detritus:
JB « LB-Q4	(6.31)
and export;
FS = KS-Q4.	(6,32)
Ccl toxicity was rac as an interactive drain:
JP « LP-Q4-CA.	(6.33)
Once again the constants listed above (KX, KY, 16, KF, LB, KS, and LP)
were approximated and then adjusted to give realistic output.
Qetrituv^M > ;K»; -
I lit* UK r«	nVw	(Q5) is must, h ,3 t" fig, 6,10. These
two fiO?'Uun: -'T str ~	s-R'-iM comprise the te * portion of the
peri.JhViO'i ' . -.."ift	|wi' ^ Hv remainder coni|K - -1 - living algae).
§3
-------
Detritus and microbes may be conveniently modeled together because of their
intimate association.
Inputs to Q5 were mentioned in the preceding paragraphs. The two major
drains on 05 are export:
PR = KR-Q5	{6.34}
and respiration;
FS = KG*Q5*(1 - LE'CA).	(6.35}
As seen in equation 6.35, Cd toxicity to the detritus-microbes 1s a nega-
tive interaction with respiration ana nutrient remineralization. This formu-
lation is consistent with actual stream data for leaf litter packs (Giesy et
al. 1979),
Parameter Approximation—
In order to approximate the unmeasured constants discussed above, a
"steady state" period of the artificial streams succession was evaluated,
figure 6,11 illustrates the four biomass storages with inputs and outputs of
dry weight for data from September 1976 when little net growth was observed.
Bicmass values, total net production and respiration, and export values were
known. Gross productivity was partitioned between the algae ami macrophytes
as shown. The partition of respiration was also based on assumptions. Total
export at this time was assumed to be twice the measured value or 3 a
dwm~'*d"l. This number divided by the total biosass of 210 g dwm"*
gives the export constants of 0.014 
-------
algae
FD»
IKD-9.6 * I#1
.EXPORT
PRODUCTIVITY --	FB • &0
(K8»
* 11 ,ii>rar>< for iVor liioKiijir.il
stor,u.icr< •'n Ct stiv,nodf 1. r\ita frnra
^ptembvr Wi wre used ta app?u:nmcit e
stead'/ strife t"1 owf -r p.i-jun^i -.flinia-
t ion,	-re m n i1w*rt'l>;
11 ovi s i sri ^	*d" *; -tnd
constar?t, in q<* -tnth^sc5. hsv? variable
units listed in Table 8,7,
65
-------
S3
* 30 *
9*
<	20-
3
<	10 -
»
fiso
=so
	j			1			
a 1 J F MA MJ J A SO N Fj
1976
FM AMJ
1977
SAMPLE DATE
Figure 6.12, Stream model simulation results for algal
and detrual-mi crobiai biornasses at con-
trol Cd concentration • of 0.023 ug Cd*L"l.
Solid lines are simulation results and
dots are measured data from Figs. 6,1 and
6.2.
66
-------
dnf no* ovt"-;ap. Im>-
"> .Vifyi'sT *	tCt"
port to the measured data. Figure 6.
microphyte and macroinvertebrate bio
ting an Increase observed for macroph;
te n1	node! was .tpptx-';-
aay	[.t-M'J .!. fn the <¦' i s^tp 11» "Hi.,-
,t r> i , ( «( >r j i-.tK >'Sf"'Ofl 1"
itplex forcing function with this same
, t i	; lil>« I <51		I
at Ion
concentv: imKj j*p!i !
i in mo:'.!orti , <• nh*¦>' i pq
* ' '	it i il'. - t >•
rates were also estimated frou
"Iciliated fran these values for
I ^ f lifea Wet c t H t
ntrol streams)
dw"-"-,
p-'^>»3nte-! * j''! 'er
}X-
a half-saturation
;' i .,-tiy i.o improve
control simulation run prefl
Cd cor
lyrik i jr
facias? tnpiit *n tH<-"	• "<$ reqi
I ate>iif fit s, " "inn > ;tn»v.r t\ * m o o4" t"
time reached 136 days (March 18, 1376),
-ifeVutiK1 v 'r-'-npnt ut ^ |.r *-.imf v»,»' ,~r,
to, lli/') 11 f -t i.'t «¦ v<< *Jit> er^r r
,.»xr rr ti »r-M
Cd streams were used to calibrate the toxic-
LP,	. The constants LS
..ict of Cd o
¦ fit rc '),r> ,'
-------
/

N 0 ' J F M \ •* l.J A SO MO'JFMAMJ J
1= '	1377
SAMPLE DATE
Figure 6.13, Stream model simulation results for gross
production, cot mity t c.*soiration, and
export at control Cd concentration of 0.023
yg UrL"1. Solid lines are simulation
results and dots are measured data from Fig.
8.4,
68
-------
(.31-
j i * r *s % t r n * i r j i * r f r ?
1976	19??
SAMPLE BATE
Figure 6,14, jtrvjun modtl si^rjl u tt.fcril,e a. i m?cr'ip(iyi > amma^^s at con-
I "(I •.iMueitf «t ion ot* 0.1)22 uj Cd L"-.
,u »i1 Mne*; sirmii (tu>K results and Jots
fj'-f menM-r:n oati trmn Tig, ..,3 and the
69
-------
-oaoM-
% m~
"S 3D -
20-
//
i. ISO
Id
US
CO
$977
1976
SAMPLE DATE •
Figure 6.15. Stream model simulation results for algal
and detrital-microbial biomasses at 5 and
10 ppb Cd input levels. Solid and dotted
lines are simulation results for 5 and 10
ppb Cd, and circles arid triangles are
measured values for 5 and 10 ppb Cd from
Fig. 6.1 and 6.2.
70
-------
151
U3
sC
m *
Ui **
ON-
a	5 «
fi-J-4==£«==
sf;

«
<
Sf°
"i
#
N D'JF M A M J J 4 5
1976	I3T7
SAMPLE DATE
fi'.J1,ire 6.16,
.. _ if" „ . „
5
71
-------
»t-
3 -
¦ca on
6
« ON-
197?
1976
SAMPLE DATE
Figure 6.1?. Stream model simulation results for gross
production,, community respiration, and
export at 5 and 10 ppb Cd input levels*
Solid and dotted lines are simulation
results for 5 and 10 ppb Cd, and circles
and triangles are measured values for 5 and
10 ppb Cd from Fig. 6,4,
72
-------
D.vnriMKi-
Th® dynnmi :s or C'i tjncrjt i i,j 'ri r*« venous i^olo^pcal storages ms
mom tire1 in the mortal «; ip«i» i a*. ¦?,•> cnr i omp,n f *-*n 1 o fbt* actual	J-.ita.
St,f«<1v 3tote >:yoLi-.iril iti'-s c* »¦< in the	>r . w<§ler concentration of 5
ppb Cc v»pte, l« *"cj•, rsctrrc.pfsvf--,, \>0 "rrrumtt ?, 33, arc! dotfi-ric~
rcops , in jus Co • ] dr!. r.>r Jn« JO p. b ,'cl	recent rxcion,
r (otic, r«J concord raTiour. '*< 1t\ au;-ic, SO, .ikk»\>. f vtv >, 'Ju, Tonsurors, 40; arid
d*?trit-is-~i cr.tf e< , !*8 n<4 fd-f, aw"1-, Th ^ row>t? fa, jr.^b' y utb U>e
VotuPi-, presented >*>.ir! ~er if .Mr; n- t > (i;s.
The stream model pr ovi !t- ; a r.rsive-m ont mean?. j? .rmmarization of the
fate of Ccf ifi th? ?qy it :e shyster « pfkiuse o>ll f1 of the metal 4»-e
accounted for. fiyye 6.JH illtr' -i,..;. (he major C-1 f'owi arri storages pre-
dicted by tne n-oaei at tin-	Cd -ow entrati o.is. at tually testoo during
rt.eddv state orwii tion: jcJ m-»r .i I -vr p^iod), All f1 ow-~ arf in
r.J-a"and storages are in pg Cu*m" , :a itode' p • •¦iieied an average
lowering or water Cd con>vi»i.rcit ior> of »1. I ppb us th^ Li pob Cd channels, cind
0.2 ppb In the 10 pph Cd chdnrels. The^e '/al.^es wrrc slightly ?i.'«l l was in »m M.icdate fori. A] i-o,
the model indicated thai n»t jre the effects of
other Cd	fand.i«?ns	^vsteir d^namn >mJ prediction of
toKin effect over t f:.ntje ol C'f iwncentnc'c^ nutsid? the ores actuaily
studied.
Toxicity cunct1o,is—
Particolsr airi	>ias direoret! toward th-v orcyrrenre ct stimulatory
effects ar 'ow Ct! con:eitr-->t'!^i-;. The	rail.il as present,?d in Fig. 6.6
Indicates 3 direct stlwtlalory {limiting faci.n) rr»le in pripary production.
A question t ~ by aiKwer^d is vd fo»- a series cf Cd cnticentrat ions '*onqin-] from
bdekgrouna fo pp<> Ui with the rtiirtul^ory c m>iarts IS and LT e^udl t>
zero. No :t '"mulacion uf oroductivity v*;.s founn. Tfiis may '.:e due to the sim-
plicity ot* mrdrfi in s of ocpn) ar ion g-oirth :h.iracto>-i sties or simply
a prediction tnat no siimultitton w»>u 1 d have b»5en observed i«i these systems.
However, for the	ccrelatson ot iifftotiied e:terov and enetq,v effect in
the ne>t -.ieit io?i, the stimnuitory cffees mj added to the iwrnt:! with LS and
LT equal Hi 0 U?5.
Cd To,—
The predicted respot^e o
concentrations is or^sei*j.d i
tions artu. ; 'y U icm< d ar^ sh
6.6-6.!'), 'He sti ivd^'! pr^
71
j «j
e>'n-levc>1 par ar M.«rs to a wide "-an ;»> of Cd
h. 19. Thw iiaca froi? the three roncentra-
r c>>nif»ason. prfrentt»d in Figs,
rnav,rrt'iin enhdnre/^ii i>f stredm metabolism
-------
DISSOLVED
m
ESS*
CO 23)
FIXED
Cd
2S4
OSSO-VED
" Cd
OUTWT
PARTICULATE
Cd
OUTPUT
DISSOLVED
Cd
INPUT
C5D}
DISSOLVED.
Ct!
INPUT
mm

DISSOLVED^!	24,15?
12.059 , DISSOLVED
* Cd
OUTPUT
PARTICULATE
		 Cd
OUTPUT
.DISSOLVED
at
OUTPUT
PARTICULATE
Cd
OUTPUT
Figure 6.18. Overview of Cd fate in artificial
streams from model output. Values are
averages over a 1-yr period. Storages
are in ug Cd«nT2, flows are in yg Cd-m"-
and concentrations Jn oarentheses) are
in ug Cd-L"1.
74
-------
5
4
3
ROSS PRODUCTION
2
I
0
20	»
C.".0MIUM CONCENTF-:.'TION Cppb)
Figure 6,19, Average gross productivity, respiration, and export
values during 1 yr of continuous Cd input predict®! by
stream model for Cd concentrations up to 50 ppb. mea-
sured data from Cd streams are indicated by dashed lines
for com) ison.
75
-------
at a Cd concentration of 0.5 ppb. These predicted data may now be used for -
Illustration In the calculation of energy effect of Cd in the next
section.
EMBODIED ENERGY AND CONTROL
Quality Factors
The calibrated Cd-streams model facilitates calculation of
factors for analysis of the amplifier effect by toxins on system
flow.
The entire energy Income of the Cd streams must be krio-./n In order to
calculate ratios of energy transformation (qua!ity facial s). If ws c^rmdsr
the situation in natural streams, we can appreciate the eff>:! of rnor^v con-
centration in the maintenance of a stream. Not only fs enrvyy nvoivw
directly from the sun, but energy is also concentrated from indirect vmirces
such as runoff from the watershed, which creates the stream flow ano struc-
ture, In the Cd streams this flow and structure were added to th- interring
sunlight from human energies and fossil fuel work. These additional fioigies
can only be estimated, and although errors in their calculation mv iftoct
the magnitude of the numbers reported, the qualitative results remain f,p
-------
The tot.jI energy contributor) to t?«e stress i„ the sum of trie three
factors hste-i aooyc In oqm valont one^iy quality tri* ^ ooo *s ^qurl to
32,298 5.1, Ul	r *»nf.for»tatiCJ! rot ins Have l~ ^
calculated using yearly i^-agp* from t*? stre-an mcael and the t.nal energy
Hoot gtvert rbnve^ £ conversion factor of 4 'al-o dry woiyhfJ v.as
used to convert the biomaas units to energy utiils, These values ore listed
in Table 8.1.
Energy Quality—Energy Effect Correlation
The Cd-streams model *d»> simo ate, at •-  CJ, Ywly a/eratjo0- or gross produc-
tivity, respiration, export, alia-i, maer^jihyfes, crmsiimert, and detntus-
microbes were calculated for iiMlyjis oi the effect of Ctl cn components of
varying ertergv quality, Ihe. cral;oo*.
Cadmium transfunuation ratio was ca!cui at erf for the different concentra-
tions simulated in the stream mode!, As 4 base!trie, the trarisformationTratio
of pure Cd calculated for the industrial process in Section 1 (4.6 x 10'
S.E. Cal*g Cd~*) was «i>eci. Using :he solubility of CdClg 1 n water
(1400 g CdCl2"L~ *) from Hafioons et at* (1 ^78), a water concentration
of 8,6 x IEP ppb Cd (saturate!) was as-iawl to have a trans Format! on ratio
equal to pure'Cd* The lowest concent rat, ion or Cd noma "My found in water is
approximately 0,02 ppb, and the free energy change between these^two Cd con-
centrations was calculated usiikj gqintirn 6.38 as 0.13 Cal *3 Cd"*,
Dividing this value into 4.6 x i0/ S.E. Cal *y Cd"* gives the trans-
formation ratio of pure Cd on a Cal per Ca1 basis of 3.5 x 18® S.E.
oal"Cal"1.
In order to calculate the transforation ratio of Cd at any other water
Cd concertrat:on, tne free energy change between the saturated solution and
the given concentrot ion must faf; calculated.( ror example, at 10 pnn Cd, the
free energy,Chang? is A'i =. -0,097 Cal-.j feT^. This value is multiplied
oy 3.5 < i(^ S.E. Cal -Cal"' to yivo the eharioo its transformation
ratio going frnm the saturated Cd solution to a less concentrated one. for
10 ppb Cd tnis chdnot ^qual> -3.4 x 10' i.L, Cal -g Co"*, This value
is subtracted iron 4 o , $*i< Cal •>) Ccl""1 to give the transforma-
tion ratio of Cd at 10 ppb, or
TRCd, 10 ppb = 1.2 X 10? S.E, Cal*g Cd'l.
These calculations of unbodied enoniy of Cd were combined with calcu-
lations of energy effect from data predicted o> the stream model. figure
6.20 presents the correlation diagrams for the system-level parameters and
for the biological storages, fill of the parameters except the macrophyte
storage showed firsc a positive, then a neqativt>, and finally zero correla-
tion between these two parameters. Positive correlations between Cd trans-
formation ratio and energy effect were generally found at concentrations
below 0.1 ppb Cd. Figure 6.20 also indicates that as a biological control-
77
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TABLE 6.1. tfit"RGY TRANSFORMATION RATIOS FOR MAJOR STORAGES AND HOWS IN CD-STREAMS MODEL.
EflFRGY VALUES ARE DERIVED FROM DRY WEIGHT VALUES USING 1 HE FACTOR 4 CAL = 1 G
DRV WEIGHT. TOTAL ENERGY INPUT TO STREAMS fAKEN AS 32,298 S.r. CAL'M"2'D_1
AHO GROWTH TIMES OF STORAGES TAKEN FROM MODEL SIMULATION DATA. ALL DATA USED
ARE FROM CONTROL STREAM SIMULATION (0.023 PPB CD)
Flow or Storage
Average Value
Actual Energy
Cal*nf
Energy
Transformation Ratio
S.E. Cal-Cal"1
Gross production
4,2! g d.w.*nf2*d~l
16*8
1923
Community respiration
2.51 9 d.w. •nT2'd'"1
10.0
3217
Export
1.52 g d.w.•m~2,d~1
6.1
5312
Algae ((fe)
21.4 § d.w.-m"2
2,la
15,093
Macrophytes (Q3)
8.06 g d.w.'nf2
0.161^
2.0 x 105
Consumers {Q4)
0.70 g d.w.'m"2
0.014b
2.3 x 106
Detritus-Microbes (Q5)
159.0 g d.w.'m"2
3.18b
10,157
aCharge-up time to steady state biomass was estimated as 40 days.
bCharge-up time to steady state biomass was estimated as 200 days.
-------
GROSS PRODUCTION
P
^ — 2
0
RESPIRATION
DETRITUS-MICROBES
suo
CONSUMERS
V MACROPHYTES
ty
14
rRAN'v-i;OMAT:rN R&rio
(S.E. Cai-q Of1* 10*1
Figure 6.20, Pr§J4i^:r'	betw»vn Cd formatrat 1c* *
Cci > >u>f >' ^ rect i ufio for • vbt.-vt-Vv^l -'\ . V ¦ 11, ^ are valcuM«c» > r< -« ;
oT ct 1 nu* it.krvi d 3 to From C d** b cr^dins inudp-a
79
-------
1er, Cd has little marginal effect above a transformation ratio of 16 x 10®
S.E. Cal *g Cd"l {100 ppb Cd).
The actual values of the two parameters in Fig. 6.20 show an order-of-
iragnitude comparison between energy effect and transformation ratio of a
controller like Cd, Given the assumptions upon which these calculations were
made, this result is encouraging. Notice that the storages have a much
higher energy effect than the system parameters. The significance of this
finding may be that selection is taking place for maximizing metabolism
rather than storage as discussed in Section 4,
The results presented in Fig. 6.20 are model predictions and, therefore,
only as accurate as the model is an accurate description of the real Cd
streams. A second qualifier of this simulation data (and the actual data,
too) is that the streams were still in a successional state during the period
of Cd inputs.
Actual stream systems that are capable of steady state growth popula-
tions may have much tighter correlations between the transformation ratio of
Cd (its cost to the system) and the energy effect of Cd {its ability to con-
trol the system). If these correlations are found to be consistent in other
systems and with other controllers, embodied energy of a controller may be
calculated from its effect and vice versa. Widely different studies of
toxicity effect could be compared using embodied energy values. Studies of
several seemingly unique toxins may be comparable if their embodied energy
content is known. The idea of toxin effect being a direct function of energy
cist may allow a needed synthesis of information in dealing with the modern
world's increasing toxic wastes. The recognition of the stfsnulatory role of
naturally occurring chemicals in biological systems greatly broadens our
theoretical understanding of the world's processes and allows a more finely
tuned control of our life-support systems.
80
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Kerfoot, y, 8., and S. A. Jacobs, 1976, Cadmium accrual in ccnbined waste-
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Ketchutn, 8, H. 1954, Mineral nutrition of phytop ianktcn. Ann, Review Plant
Physiology 5:55-74.
Klass, E., 0. W. Rowe, and E. J. Massaro 1974. The effect of cadmium on
population growth of the green algae Scenedesrous quadricauda, Bull.
Environ. Contain. Toxicol. 12:442-45.
Knauer, 6, A,, and J, H, Martin. 1973, Seasonal variations of cadmium,
copper, manganese, lead, and zinc in water and phytoplank ton in Monterey
Say, California. Limnol. Oceanogr. 18:597-604.
Kneip, T, J., K. Buehler, and H. L. Hirshfield. 1974. Cadmium In an aquatic
ecosystem: Distribution and effects. Interim Progess Report, N.Y.
Med. Center Inst. Environ, Med, 35 pp.
Knight, R. t. 1980. Energy basis of control in aquatic ecosystems. Ph.D.
dissertation, Unive - lorida. 138 pp.
Kumada, H., S. Kimura, M. Yokote and ¥. Matida. 1973, Acute and chronic
toxicity, uptake, and retension of cadmium in freshwater organisms.
Bull. Freshwater Fish Res. Lab, Tokyo 22;157—65.
Lamanna, C., and M. F. Mallette. 1353, Basic bacteriology. Milliams &
Wt Ikins, Co.t Baltimore.
lotfea, A. J. 1922. Contributions to the energetics of evolution. Proc.
Natl. Acad. Sci. 8:147-51.
Lucas, J. M. 1973, Cadmium. Mineral	comrodity profiles. U.S. 3ur. Mines.
13 pp.
McKellar, H. N. 1975. Met~~~ it and models of estyarine bay ecosystems
affected by a coastal	>1ant. Ph.D. dissertation, University of
Florida, Gainesvilie.	J.
National Oc ba
-------
Odum, E. P. 1973, Fundamentals of ecology, 3rd Ed, W. B. Saunders, Phila-
delphia, 574 pp.
Odum, E. P., J. T. Finn, and E. H. Franz. 1973. Perturbation theory and the
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Odum, H. T, 1956, Primary production in flowing waters- Lirrmol. Oceanogr.
1:102-16.
Odum, H. T. 1968. Work circuits and system stress. Pages 81-138 in_ Y.
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tems, University of Maine Press, Orono.
Odum, H. T. 1971. Environment, power, and society. Wiley-Interscience, Sew
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Odum, H, T. 1978. Energy analysis, ?> ergy quality, and environment. Pages
55—78 _1n_ M. W. Si Hi land (ed.), Energy analysis: A new public policy
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Odum, H. T. 1979. Energy quality control of ecosystem design. Pages 221-45
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"South Carolina Press, Columbia.
Odum, H. T., and R. F. Pigeon (eds.). 1970, A tropical rain forest. U.S.
Atomic Energy Commission* NTIS, TID-24270( 'NC-138), Springfield, Va.
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Pages 105-67 J_n Proceedings of Energy Modeling Symposium, Ministry of
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8570. 10—14 pp.
84
-------
Pickering, Q. H., ,vu! *4, K, Gast. 1""??. Acute and chronic toxiciH of cad-
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£u! .^pvan col loqinm smb.'ems c*" "1i€ cm ¦'mtrut i.tn n-f nun wn hi.-, environ-
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Rzewuska, E., and ft. Wernikowsta-Ukr 1974, Research on the ir.f"isien<"€ of
heavy metals on the develupi-,.- " o' S^xneoasiius quadricauda {Tu-"- l urc+>.
Pt, 1, Mercury. Pol, Arch. • y.1 r obici71'1:109-17^
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cadmium and zinc mixtures on flaqfish (Jordanella floridae). Trans,
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Thorp, .]. N., J, P, Giesy, ami S ft, Wineriter. 1979, Effects of chronic
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Turner, M. A, 1973, Effect of cadmium treatment on cadmium and zinc uptake
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Vlasov, K. A, 1966, Geochemistry of rare elements, Vol. 1; Cadmium. Israel
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and cine1 at*1'rig j^ents. Agron. J. 69;iS~M.
Wang, F. C., H. T. Oduni, and P. C. Kangas. 1380. Energy analysis for
environmental impact assessment. J. Mater Res. Plan, Manage, Division
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Wedepohl, K. H. 1970, Handbook of geochemistry, Vol. 2; Cadmium,
Springer-Verlag, New York.
Williams, D, R.t and J, P. 6u?sy. 1978, Relative importunes ">f food and
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Environ, ties, 16:326 j..
Woodwel1, 6, M, 1967. Radiation and the patterns of nature. Science
156:461-70.
85
-------
APPENDIX A
DIURNAL OXYGEN CURVES
86
-------
CONTROL
IOPPB
r— CONTROL
5PPB
Q 0
iOPPB
2400
0800
1800
2400
TIME
Figure A.l. Diurnal oxygen ch
1976, for six exp
ing Cd inputs.
is from June 30,
streams- receiv-
es 7
-------
CONTROL
IQ Pro
CONTROL
I0PPB
10000
tft
£
"g
o
u
B 5000-
x
o
2400
0600
1200
NOON
TIME
1800
2400
Figure A.2. Diurnal oxygen change curves from July 28,
1976, for six experimental streams receiving
Cd inputs.
88
-------
I-CONTROL
£ o
- IOPPB
o
CONTROL
5PPB
10 PI
m
m
5000
2400
0800
1200
2400
1800
NOON
TIME
Figure A.3. Diurnal oxygen change curves from September
23, 1376, for six Dxptrimental streams
receiving Cd inputs
89
-------
3
2
i
0
2
i
0
2
!
0
4
3
2
i
o
2
0
I
0
-f
CONTROL
CONTROL
IOPPB
>400
0600
I2C0
NOON
TIME
1800
2400
.,4, Diurnal oxygen chanae curves from October
20, 1976, for six experimental streams
receivinq Cd inputs.
90
-------
OJ 0
5PP8
CONTROL
5PP8
v>
V5000
o
2400 0600
1200
1800
240 0
MQOM
TIME
figure A,5. 0<". o-sl «««« change curves from
ito .'itTiter J 976, for six experimental
ing Cd inputs.
91
-------
I -
'is _
eM 0
it 1
go
s2
* 1
I '
0
1
CONTROL
- 5PPB
10PPS
- CONTROL
1 -
8
5000
X
o
~
y* » *•
. 5PP8


—4—

-
- I0PPB




m
2400
0600
1200
NOON
1800
TIME
Figure A.6, Diurnal oxygen change curves from February
9, 1377, for six experimental streams
receiving Cd inputs.
92
-------
:ONTROL
:OPPS
CONTROL
5P!
IOPP1
*600
2400
0600
1200
NOON
TIME
Figure A.7. Diurnal oxygen change curves from March
16—17, 1977, fur six experimental streams
receiving Cd inputs.
93
-------
if- CONTROL
tOPPB
CONTROL
2400
0600
1200
NOON
TIME
1800
2400
Figure A.8. Diurnal oxygen change curves from April 29,
1977, for six experimental streams previously
receiving Cd inputs.
94
-------
CONTROL
i - 5rPB
1200
NOON
BOO
l.400
0600
1200
NOON
TIME
figure A.3. CHurrt*1 oxygen chame rnrves from May
1, 1977, for ' Mvrimental
•	previously >v sr, ng Cd Inputs,
95
-------
3
2
I
0
2
I
0
2
I
0
2
I
0
2
I
0
!
0
-I
- CONTROL
~ IO Pro
- CONTROL
/
2400
0600
1200
NOON
TIME
WO 2400
e A.10. Diurnal oxygen change curves from July 6,
1977, for six experimental streams previously
receiving Cd inputs.
96
-------
APPENDIX 8
COMPUTER PROGRAMS
97
-------
TABLE B.l. COMPUTER MODEL IN BASIC USED TO SIMULATE MIMMODEL
ILLUSTRATED•IN FIG. 4.14
18 PLOT 23#18
28 PLOT 12
30 J=±
40 DT=1/J
58 ND=25
60 5=10
70 Q=1000
80 TX=. 1.
98 K±=. 081
100 K2=lE-5
113 K3~, 85
200
210 1=0
220 P=K1*0*S
230 R=K2*Q*Q
240 JX»K3*Q*TX
25® Q-Q+DT+CP-R-JX)
260 IF Q<0 TM£N 0-0
270 1=1+1
280 IF I=J GOTO 300
290 GOTO 229
300 T=T+1
310 IF T«WD GOTO 858
315 GOTO 210
328 PLOT 29,18
330 PLOT 29,22
248 PLOT 2, T, Q/15, 255
258 PLOT 29,18
260 PLOT 2, T, P, 255
376 PLOT 29.. 1?
380 PLOT 2., T, JX, 255
860 GOTO 219
859	PLOT 29/18
860	PLOT 2, TX*10, Q/10, 255
864 PRINT TX, G, P, R, JX
870 TX-TX+. 5
889	IF TX>10 GOTO 999
890	GOTO 208
999	PLOT 29/18
1000	END
98
-------
TABLE 8.H. COMI\ TtR mt\ IN BASIC USED TO'SIMULATE MIMIHODEL
III 'J'ITSAI tD IN FIG. 4.15
10 PLOT 29/IB
20 PLOT 12
38 J»1
40 OT =1/J
58 »=5i
55 TX-. 1
68 J0»4000
62 JR-2000
64 M=2&m
70 Q=i000
yw -1=5.. 52E-5
100 K2=iE-5
110 K2= 011
=2
0
--0
210 1=@
212 JR=J§~JK
214 IF JR<0	1
220 P=K1*JR*	C4*TX?*Q
220 R=K2*Q*Q
240 jx=k2 f .:y t t;i > E:iP<-K4*ix:i*Q
25® Q=Q+D"r-> • c *K'•
260 IF CK0 TUFM 0-0
?-c ir i3t o j,09
312 IF SCI GOTO 218
~\5 "" 01 0
316 PRINT T, Qi P, R, JX
~rv '£> I'*-
330 PLOT 29,22
340 PLOT 2,T,9/15. 255
359 PLOT 23,18
8©8 GOTO 208
85® PLOT 29,18
3, 255 •
B64 PF'.M ' S. >*. P. .X
870 JK=TH+, 5
§80 IF TK">10 GOTO 999
890 GOTO 6®
993 PLOT 23,13
i&.'M END
99
-------
TABLE B.3. COMPUTER MODEL IN BASIC USED TO SIMULATE MINIMODEL
ILLUSTRATED IN PIS. 4.16,
10 PLOT 23>18
28 PLOT 12
25 PLOT 2, 252, 9, 0, 242, 0,131,159,131,153, 8, 0, 0, 255
30 J=t
40 DT=i/J
50 ND=50
55 TX=. 01
70 Q=50
75 N-2i
80 N0-2
85 Kl=±E-2	830 IF TX>1G GOTO
87 K2=5E-2	830 GOTO 70
89 K3=5E-6	993 PLOT 29,18
91 K4=iE~4	1060 END
93 K5«. 1
95 KG—4. 9E-S
37 K?-, 05
98 K8SK2/K1
208 T=0
208 5=0
218 1=8
220 P=K1+Q*N
222 R=K2*Q*G
224 N1"K3*G*N
226 N2=K8*«1+R>
228 N3=K5*N
230 J1=K?*Q#TX
250 GM3+DT*
252 N=N+DT*<:N0+N2-N1-N3>
260 IF CK0 THEM Q=0
262 IF MC0 THEM
278 1=1+1
288 IF 1-J GOTO 300
239 GOTO 220
208 T=T+1
310	IF T=ND GOTO 858
311	S=S+. 2
212 IF Sd GOTO 218
314	PLOT S
315	PRINT 1, Q, N> P, R
329 PLOT 29»18
328 PLOT 23, 22
248 PLOT 2, T, Q, 255
359 PLOT 29,13
S80 GOTO 288
850 PLOT 29,18
868 PLOT 2, TX+10, P*10, 255
864 PRINT TX, Q, H, P, R
878 TK=TX+, 5		 . .
100
-------
TABLE B.4. COMPUTER MODEL IN BALTIC USED TO SIMULATE MINIMODEL
ILLUSTRATED IN FIG. 4.21
18
20 BT=1/J
30 C8= 0091
41
58 ND=10
60 M-4BBB
70 JR=3000
8i
30 R=±£-4
108 RT=2*B/R
118 N=i
120 Ci=20
138 K2=t§®
140 ftSBK2*Cl
•fiy
163 IC1-3 33E-3
170 K2-S, OE-3
180 K4=3, 32E-5
ISO K5= 05
208 Kb- OK
218 K7- 005
228 KS-, 0i35
228 K9~ 03
240 07
2P0 KB=, 01
ZfM KC=. 01
270 KF=1
280 KG=J.»T<
230 KE'2/R
380 I
210 F1-K1'R-jR
1S0 F2=--K2*e+J^
21Q *+=K4*B*JR
340 fS^kb-+B
200 F6=K€+B
F£»=M:<+ri+LO
370 F7-K2*F?
380 F8=KZ*F9
33Q F < F2-F5 ) /R
400 Ffl-r'i'I w**i
410 FP=kI*K.H
420 FOK^FR
430 0 ~ F 7 - F 0 > +•¦ F 3- F C >
440 FE=KE"'h, V'f:.
450 FF=KF^r,tF6
460 FG-KG+*F6
470 vs= es
480 JR= '0-Fj.
490 D~&»XTr'.FZ-F5-F6>
600
610
500 Cl=Cl+M-t
510 ft.~B+DT-*»FC~P?~FE+Fl>
520 P^-RS+DT* 3 IF P<8 THCN M=8
5rjd !F *S<0 THEM FlS-0
¦390 IF ftKO THEN RT=9
1 = 1+1
IF I=J GOTO 630
620 GOTO 318
t.lb T=T*1
*40 IF 1 =MD GOTO 668
658 GOTO 300
r'SO PLOT 23,< IS
670 PLOT 2/CO+IOOj C/ii? 255
em PLOT £9,18
€90 PLOT 11
7t)0 PRINT CO, C
710 C0«C®+. 005
728 IF C9=l GOTO 999
730 GOTO 40
999 PLOT 29, IS
1008 EN'D
10!
-------
BLE B.5. COMPUTER MODEL IN BASIC USED TO SIMULATE CD-STREAMS.
THIS MODEL IS ILLUSTRATED IN FIGS. 6.6-6.10,
1 CLERR (580)
10 PLOT 23-18
20 PLOT 12
30	PLOT Z> 253/ 0,0.242,0,191,159,19L159,8* 8» 0,255
31	GGSUB 2609
32	PLOT 4
35 WJ
40 J=1
50 DT=¥/J
55 NT=DT
60 NO=600
78 S=S00
75	Tl=8
76	T2=8
77	T3=0
78	NZ=0
79	B2*0
80	T4~0
102 J0=3442
104 JR=3800
106 JH=2442.8fi
108	Ni=. 815
109	22s. 023
110	Cl=. 023
112 Q2=. 1
114 03=1
116 Q4=. 1
118 05= 1
128 N2=. 915
124 C2=Q2
126 C3=Q2
128 C4=Q4
130 C5=Q5
132 CR=. 823 "
134	CB=i
136 CC=1
135	CD=i
140	CE=i
141	C2=. 023
142	Fl=36. 64
144 F2=56. 2
152 F1-. 049
154 FJ». 018
156 FK» 036
158 FL- 061
168 FM=. 0826
164 F0= 4
174 FX* 9001
173 FE=, ®03
102
-------
TABLE 8,5. (CONTINUED)
176	FD». 125
177	J4=8
178	J5=i
188 JP*8
212 Ki=208
204 K2=. 136
21® K4=5
214 KS=5
216 K8®. 095
218 K3=. 0024
228 W=143
222 m=im
224 KC= 003
226 M-5
228 KEc 118
22§ KF*. §2
232	KG= 80812
234 KM»iS§
236 KI-108
238 KJ=8
240 KK=8®
242 KL= 145
244' KM=. §2
248 K0= 1055
250 KP*. 8«8
252 W
254 KR«KP
256 ICS*
2« WtSs 16
266 KX- §027
268 K¥~ 0015
272 Ll= 065
274 12= 82
27'- t 4'.* 103
288 i5» 8015
282 LS= §087
286 L8=K6
288	LS». 3
289	IP». 818
296 Lfl=. 136
291 LB=. 115
293 IE- 8i
233	15®, 825
a
302 LU=. 2
m t=8
310 1=8
320 J®=C4268+iS4i»SINCCC6. 28>/265>«KS-88» >*. 7
132 JN=N3L*JH
324 JC=C1*JW
336 F8"K8*N2*JR*Q2
228 F9«K9*N2*JR*a3
333 FD=KD*82*JR
341 FE=KE#S3
103
-------
TABLE 8.5.
{CONTINUED}
342
F4=K4*(F9-FE>

342
IF F4<0 THEM F4=0

350
F&4C6*CF8~H>>

251
IF F€<8 THEN F6=8

3SS
FB=Kft*P8

358
F8=K6#f9

360
FOKC*Q5*JR

J66
Ff=XF»t«4*Q4

m
FG«KG*05*(l-L£*Cfl>

377
IF FGFY

410
JM2*«

412
J3*CC*«4

432
JB=CD«

458
GP=F8+JS+F9+JT

4®
RT=FD+FE+FF+FG

508
Q2=Q2"H)T * < F8+JS-FO-R-FP-FU-
i)
510
03=63+0T*(F5+JT-FO-FV-J2-FE-
5)
520
64^4+OT* (J9-FS-JB-FF-JP)

530
Q5=Q5+DT*< J2+FU+JB+JK-FR-FG+
N-J5+J4-J6)
521
IF Q2<8 THEN 02=8. 01

532
IF Q3C8 THEN 03=0, 01

533
IF 94<0 THEN 04=0. @1

104
-------
TABLE B.5. {CONTINUED)
S34 IF Q5CB THE! 95*8. 81
541 flZ>KJ«flZ*0*
549 FK=K'K«*«
350 CB=C2/t2
531 FL=Kl*t2
552	CC=C2/13
553	Fmmm
554	C«4/ft4
555	fQ=K0*C4
556	CE=C5/85
55? J 1=4.1*05
558	Pi=JN#JS~f4~f€
559	F2=JC+FL+Fl+fO+F1'+Ji-FK-FI-fH-FI
562 IF Fice THEN Fl=8
566 IF F2CI TH® F2=i
570 C2=C2+NT#583 THEM 6010 61®
585	NZ-NZ*i
590 Ti«fiP+Ti
595 TSH?r+T2
600 T3=F3+T3
685 T4=Ji+T4
618 1=1+1.
628 IF I«JT GOTO 640
630 GOTO S2M
648 T»T+V
650 S=S+¥
652 IF T>138 THEM C1=ZZ
€53 IF T>5i3 THEN Cl«. 823
660 IF DM> GOTO 885
£38 PLOT 29,18
715 TG=T/5
719
PLOT
8
720
PLOT
29,18
?4i
PLOT
2, T6, 75+J0/150# 255
750
PLOT
as 122
755
PLOT
2, T(L 2*02,255
768
PLOT
23,1?
765
PLOT
2, T(L m, 255
778
PLOT
29/50
775
PLOT
2. TG. 05/2/ 255
782
PLOT
23,18


105
-------
TABLE B.5. (CONTINUED)
?m plqT 2j TOj 34*1.0,235
78b BZ=BZ+1
78? IF BZ<6 THEN GOTO 809
788 Q= : F=4 : GOSUB 5088
3068 Q*CE : F«5 ; GOSUB 5800
3870 RETURN
5089 REM PLOTTING ROUTINE FOR PRINTER
5010 0=INTCQ)
5020 IF Q<2 THEN Q=2
5030 IF 8>89 THEN Q=80
5040 ZS^niDSCFi.. F, 1)
5050 P^EFTJCRS, 8-l)+Z$+RIGHT#CP$/ 8&-Q)
5060 RETURN
106
-------
TABLE 5.6. LIST Of PARAMETERS WITH DESCRIPTIONS AND EQUATIONS FOR CD-STREAMS MODEL ILLUSTRATED
IN FIGS. 6.6-6.10
Model Parameter	Description	Equation
CI
Dissolved nitrogen in periphyton
layer
N = S+0T*CJ8-F5-F4-F6}
c
Dissolved Cd in periphyton layer
C = C+DT*(FL+FM+F0+FT+01-JZ-FK-FJ-FH-FI)
Q2
Algal biomass
02 = Q2+DT*(F8+JS-FD-FX-FP-FU-J4)
Q3
Macrophytic blomass
Q3 = Q3+DT*(F9+0T-FQ-FY-J2-FE-J5)
Q4
Consumer bionass
Q4 = Q4+0T*(09-FS-JB-f F-JP)
Q6
Oetrital-microbial blomass
Q5 = Q5+DT*(J2+FU+JB+JK-FR-F6+04+JP+J5-J6)
a
Bound Cd in algae
€2 = C2+DT*(FH-FL-FW-FV-0F)
C3
Bound Cd in macrophytes
C3 = C3+} >r *(fI-FZ-J3-FM-JG)
C4
Bound Cd in consumers
C4 » C4+0T*( FO-JQ-JI)
C5
Bound Cd in detritus-microbes
C5 = C5+0T*(J3+FV+FK-J1-JH-J7-FT+JD+JM)
N2
Dissolved nitrogen concentration
in stream
F1
JW
CA
Dibsu!v*;-ti Cd concentration in
F2
-Jw
-------
TABLE 1.6, {CONTINUED}
Model Parameter	Description
HI	Dissolved nitrogen concentration
in inflow water
CI	Dissolved Cd concentration in
inflow water
CB	Cd concentration in algae
CC	Cd concentration in macrophytes
CD	Cd concentration in consumers
CE	Cd com .'it rat ion in detritus
and microbes
J0 _	Solar energy flux
JR	Remaining solar flux (albedo)
JW	Hater input
JN	Dissolved nitrogen input
JC	Cd input
PI	Hitf 1 c„i
Equation
Constant, 15 ug H-L"1
Variable
C2
Q2
C3
w
C5
Q5
Sine function, 365 days;
maximum value s 6000 Cal*m"z*d_1
minimum value = 2720
J| = 0.7-TOTAL
JP-FA-FB-FC
Constant, 2443
Nl-JMj	,
Cl-JW
JN+J8-F4-F6
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TABLE B.6. (CONTINUED}
Model Parameter	Description
F2	Cd flow
F3	Total dry matter export
F4	Nitrogen uptake by macrophytes
FS	Kitrogeti uptake by algae
P8	Gross production by algae
F9	Gross production by macrophytes
FA	Light absorption by algae
FB	Light absorption by macrophytes
FC	light absorption by detritus and
mi crobes
FD	Algal respiration
FE	Macrophyte respiration
FF	Consumer respiration
FG	Microbial respiration
FH	Algal Cd uptake
Equation
JC+FL+FM+F0+FT+J1-FK-FJ-FH-FI
FP+FQ+FR+FS
K41 (F9-FE)
K6 *(F8-FD)
K8-N2-JR-Q2
K9-N2-JR-Q3
KA-F8
KB-F9
KC-Q5-JR
KD-Q2-JR
KE-Q3
KF*Q4'Q4
KG-Q5-(1-LE-CA)
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TABLE 8.6. {CONTINUED)
Model Parameter	Description
FI	Macrophytic Cd uptake
FJ	Consumer Cd uptake
FK	Detrltal-microblal Cd uptake
FL	Algal Cd decay
FH	Macrophytic Cd decay
FO	Consumer Cd decay
FP	Algal export
FQ	Macrophyte export
FR	Detrital-microbial export
FS	Consumer export
FT	Cd release in microbial
respiration
Fll	Algal loss to detritus
FV	Particulate Cd loss from algae
to detritus
FH	Particulate Cd loss from algae
to consumers
ki"'kI+Ea'"Q3
K0-(naS)-Q4
KK-(ja^)-Q5
KL-C2
KM-C3'
K0»C4
KP-Q2 '
KQ-Q3 '
KR-Q5 ;
KS-Q4
FG'CE !
KU-Q2
CB(FLI+J4)
Equation
CB'FX
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li;:L£ e.6. (Cr ; flNUED)
Model Parameter	Description	"	Equation
FX	Algal consumption by consumers	KX-Q2*Q4
FY	•. .crophyte consumption by
consumers	KY-Q3-Q4
FZ Particulate tv loss from micro-
phytes to consumers	CC-FY
Jl	Detrltal-microbial Cd decay	L1*C5
J2	Macrophytlc loss to detritus	L2*Q3
J3	Particulate Cd loss from macro-
phytes to detritus	CC(J2+J5)
J4	Cd toxicity to algae	L4*Q2*CA
J5	Cd toxicity to macrophytes	L5*Q3'CA
J6	Detrltal-microbial consumption
by consumers	L6*Q5-f}4
J?	Particulate Cd loss from detritus-
microbes to consumers	* CE-J8'
J8	Nitrogen remineralization from
microbial respiration	18-pG
J9	Total assimilation by consumers	L9-(FX+FY+J6)
JB	Consumer lo- - to detritus	LB-Q4
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TABLE B.6. (CONTINUED)
Model Parameter	Description
JD	Particylate Cd loss from consumers
to detritus
OF	Particulate Cd loss from algae
to export
Jfi	Particulate Cd loss from macro-
phytes to export
JH	Particulate Cd loss from detritus-
microbes to export
JI	Particulate Cd loss from consumers
to export
JJ	Total particulate Cd flow in export
JK	Loss of unassinitiated 'food by
consumers to detritus
JL	Assimilation of particulate Cd
by consumers
JH	Loss of unassimilated particulate
Cd from consumers to detritus
JP	Cd toxicity to consumers
JS	Cd stimulation of algal
production
Equation
CD(JB+JP)
FP'CB
FQ-CC
FR-CE
FS'CD
JF+JG+JH+JI
FX+FY+J6-J9
L9*(FW+FZ+J7)
FW+FZ+J7-JL
LP'Q4«CA
LS-CA-F8
LU+CA
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TABLE 6.6. (CONTINUED)
Model Parameter	Description	Equation
it * rfl«pQ
JT	Cd stimulation of microphytes	TU+CA—
GP	Total gross production	F8+F9+JS+JT
RT	Community respiration	FD+FE+FF+FG
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TABLE B.7. LIST OF INITIAL CONDITIONS AND TRANSFER COEFFICIENTS USED IN
SIMULATION OF CD-STREAMS MODEL ILLUSTRATED IN FIGS, 6,6-6.10
Initial Conditions
Q2	0.1 q-m~z	CA
Q3	1.0 r»"2	CI
Q4	0.1 Q-m-2	CB
Q5	0.1 g*m"2 „	CC
C2	0.1 ug Cd-m"2	CD
C3	1.0 ug Cd-nf2	CE
C4	0.1 Jjg Cd'nT2	J0
CS	0.1 ug Cd'm"2	JR
N2	0.015 mg N-L"1	JW
Transfer	Coefficients
K1	200 ug Cd-L"1
K4	5 mg N*g_1
K6	5 mg N*g"l
K8	0.009 L-m2;Car1*mg N"1,
K9	0.0024 L*m-*Ca]"^*mg N~*
KA	143 Cal'g"1
KB	143 Cal-g"1
KC	0.003 m^-g"1
KD	6 x 10"5 m •Cal"1
KE	0.018 d"1
KF	0.03 d"1
KG	0.00012 d"1
KH	ISO ug Cd-g-J-d"1
KI	100 ug Cd*g~i-jrl
KJ	8 ug Cd'g'-'d-1
KK	80 ug Cd*g"l"d"!
KL	0.045 d"1
KH	0.02 d"1
KO	0.0055 d"1
0.023 yg Cd-L"1
0.023-100.0 ug Cd-L"1
1.0 ug Cd*g"J
1.0 ug Cd-g~*
1.0 ug Cd* g*J
1.0 Pi Cd-g"1
3442 Calpm"^*d"|
3000 Cal•m-2-d"'
2443 L-m-Z-d"1
KP	0,008 d"1
KQ	0.008 d"1
m	0.008 d"1
KS	0.008 d"1
KU	0,06 d-1
KX	0.002? nr *d~ ;•§"*¦
KY	0.0015 m2'd"^*g"^
tl	0.065 d"1
L2	0.02 d"1 ,
14	0.003 L'd-1-vg Cd"1
L5	0.0015 L;d"l-ng Cd"1
L6	0,0007 ro2*d""^*g"^
L8	5 mg N-g"*
L9	0.3
LP	0.008 L-d"1-pg Cd'1
LB	0.015 d"1
LE	0.01 L'uQ Cd"1
LS	0.025
LT	0.025
LU	0.2 ug Cd-L"1
114
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